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A Search for Novel Biomarkers Predicting Toxicity and Response to Thiopurine Treatment in Patients with Inflammatory Bowel Disease

Blaker, Paul Andrew

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Download date: 29. Sep. 2021 PhD Thesis Thiopurines in IBD Paul Andrew Blaker

A Search for Novel Biomarkers Predicting Toxicity and Response to Thiopurine Treatment in Patients with Inflammatory Bowel Disease

Dr Paul A. Blaker BSc MBBS MRCP

A thesis submitted for the degree of Doctor of Philosophy.

Date of submission – April 2014

Supervisors – Dr Jeremy D. Sanderson1 and Dr Anthony M. Marinaki2

Department of Gastroenterology1 and the Purine Research Laboratory2, Guy’s and St Thomas’ NHS Foundation Trust, Westminster Bridge Road, London, SE1 7EH.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Table of Contents Acknowledgements ...... 8 Communications arising from this research ...... 9 Original research papers and review articles...... 9 Oral presentations ...... 9 Poster presentations ...... 9 Book chapters ...... 10 Abstract ...... 11 List of abbreviations ...... 12 Chapter One: Literature review ...... 16 1.1 Definition, epidemiology and pathogenesis of inflammatory bowel disease ...... 16 1.2 Natural history of inflammatory bowel disease ...... 18 1.3 Treatment strategies and goals of therapy ...... 18 1.4 Thiopurines in inflammatory bowel disease; history, efficacy and toxicity ...... 21 1.5 Thiopurine metabolism ...... 23 1.6 Mechanisms of thiopurine action ...... 28 1.7 Thiopurine metabolite monitoring ...... 30 1.8 Thiopurine hypermethylation and the use of low dose thiopurines with allopurinol ...... 33 1.9 Pharmacogenomics ...... 35 1.10 Non-genetic factors influencing thiopurine metabolism ...... 35 1.10.1 Drugs influencing TPMT activity...... 35 1.10.2 Drugs influencing other enzymes in the thiopurine pathway ...... 38 1.11.1 Genetic factors influencing thiopurine metabolism ...... 39 1.11.1 Glutathione-S-transferases ...... 39 1.11.2 Thiopurine-S-methyltransferase ...... 40 1.11.3 S-adenosylmethionine ...... 43 1.11.4 Xanthine oxidase / dehydrogenase...... 45 1.11.5 Hypoxanthine-guanine phosphoribosyltransferase ...... 47 1.11.6 Inosine monophosphate dehydrogenase ...... 48 1.11.7 Inosine triphosphate pyrophosphohydrolase ...... 48 1.11.8 Guanosine monophosphate synthase and guanosine monophosphate reductase ..... 50 1.11.9 Purine nucleoside phosphorylase and cytoplasmic 5’nucleotidase ...... 51 1.11.10 Thiopurine importer pumps ...... 51 1.11.11 Thiopurine exporter pumps ...... 52

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.12 Aims of the thesis ...... 54 Chapter Two: Materials and methods ...... 55 2.1 Patient recruitment ...... 55 2.1.1 Thiopurine hypermethylation clinical studies (Chapters 3 and 4) ...... 55 2.1.2 Real-time PCR genotyping (Chapter 5) ...... 55 2.1.3 Exome microarray genotyping studies (Chapters 6 and 7) ...... 56 2.1.4 Biochemical mechanism of allopurinol induced TPMT inhibition (Chapter 8) ...... 57 2.2 Determination of clinical response ...... 58 2.2.1 Thiopurine hypermethylation and exome microarray studies (Chapters 3, 4, 6, 7) ..... 58 2.2.2 Statistical analysis of clinical data ...... 59 2.3 Genotyping studies: laboratory methods ...... 60 2.3.1 SNP selection for real-time PCR (Chapter 5) ...... 60 2.3.2 DNA extraction and normalisation of DNA concentrations (Chapters 5, 6 and 7) ...... 60 2.3.3 Real-time PCR genotyping ...... 62 2.3.4 Statistical analysis for real-time PCR genotyping (Chapter 5) ...... 65 2.3.5 Illumina human exome beadchip (Chapters 6 and 7) ...... 65 2.4 Exome chip analysis - algorithm development and validation ...... 67 2.4.1 Genotype / phenotype analysis using PLINK ...... 67 2.4.2 Adjusting data for rare variant calling and population structure using ‘zCall’ and principal components analysis ...... 74 2.4.3 Summary of exome chip analysis algorithm ...... 86 2.5 Power calculations ...... 86 2.6 Biochemical mechanism of allopurinol induced TPMT inhibition ...... 88 2.6.1 Materials ...... 88 2.6.2 Metabolism of MP, TX and oxypurinol in intact red blood cells ...... 88 2.6.3 Reverse-phase high-performance liquid chromatography conditions ...... 89 2.6.4 Calculating the concentration of MeMP ...... 89 2.6.5 Measurement of TPMT kinetic and inhibition constants in red cell lysates using tandem mass spectroscopy ...... 90 2.6.6 Measurement of urinary TX and oxypurinol levels in controls versus IBD patients receiving AZA alone or in combination with allopurinol ...... 91 2.6 7 Power calculation for in-vivo study ...... 92 Chapter Three: An examination of factors associated with thiopurine hypermethylation in patients with inflammatory bowel disease ...... 93 3.1 Introduction ...... 93

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

3.2 Methods ...... 94 3.2.1 Statistical analysis ...... 94 3.3 Results ...... 96 3.3.1 Distribution of thiopurine metabolite profiles in patients with IBD ...... 96 3.3.2 Relationship between RBC TPMT enzyme activity and thiopurine hypermethylation . 98 3.3.4 Relationship between the normalised thiopurine dose and thiopurine metabolites 101 3.3.5 Relationship between a change in the normalised thiopurine dose and thiopurine metabolite profiles in patients with thiopurine hypermethylation ...... 104 3.3.6 The influence of gender on thiopurine metabolite profiles ...... 107 3.3.7 Thiopurine hypermethylation and the development of hepatotoxicity ...... 108 3.3.8 Logistic regression model to predict thiopurine hypermethylation from demographic, haematological and biochemical data ...... 109 3.4 Discussion ...... 112 Chapter Four: The influence of thiopurine hypermethylation on clinical outcomes in patients with inflammatory bowel disease ...... 117 4.1 Introduction ...... 117 4.2 Methods ...... 118 4.2.1 Patients ...... 118 4.2.2 Determination of clinical response ...... 118 4.2.3 Statistics ...... 118 4.3 Results ...... 119 4.3.1 Demographic comparison of IBD patients with and without thiopurine hypermethylation ...... 119 4.3.2 Average time to reach thiopurine hypermethylation ...... 121 4.3.3 Utility of thiopurine metabolite measurements at week 4 to predict steady-state metabolite profiles between weeks 12 – 52 ...... 122 4.3.4 Influence of concomitant 5-ASA therapy on MeMP levels in patients with and without thiopurine hypermethylation...... 123 4.3.5 Comparison of drug toxicity between patients with or without thiopurine hypermethylation ...... 125 4.3.6 The impact of thiopurine hypermethylation on intervention free survival during the first 12 months of AZA/MP treatment ...... 125 4.4 Discussion ...... 130 Chapter Five: A search for novel biomarkers predicting thiopurine hypermethylation using a candidate gene approach...... 134 5.1 Introduction ...... 134

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

5.2 Methods ...... 136 5.2.1 Patients ...... 136 5.2.2 Laboratory methods ...... 136 5.2.3 Statistical analysis ...... 136 5.3 Results ...... 137 5.4 Discussion ...... 141 Chapter Six: A search for novel biomarkers predicting thiopurine hypermethylation and treatment response using an exome-wide approach...... 144 6.1 Introduction ...... 144 6.2 Methods ...... 145 6.2.1 Patients ...... 145 6.2.2 Illumina human exome beadchip ...... 146 6.2.3 Statistical analysis ...... 146 6.3 Results ...... 147 6.3.1 Cohort of adult patients with IBD receiving AZA/MP ...... 147 6.3.2 Case-control analysis of genetic variants associated with thiopurine hypermethylation...... 149 6.3.3 Case-control analyses of genetic variants associated with high MeMP levels and low TGN levels...... 156 6.3.4 Case-control analysis of genetic variants associated with 12 month intervention free survival in patients with IBD prescribed AZA/MP ...... 167 6.4 Discussion ...... 174 6.4.1 A model predicting thiopurine hypermethylation ...... 174 6.4.2 Models predicting high MeMP concentrations and low TGN levels ...... 177 6.4.3 A model predicting clinical response to thiopurines ...... 178 6.4.4 Critical evaluation of methodology ...... 180 6.4.5 Conclusion ...... 181 Chapter Seven: A search for novel variants predicting adverse drug reactions in patients with IBD prescribed thiopurines...... 183 7.1 Introduction ...... 183 7.2 Methods ...... 186 7.2.1 Patients ...... 186 7.2.2 Illumina human exome beadchip and statistical analysis ...... 186 7.3 Results ...... 187

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

7.3.1 Cohort of adult patients with IBD receiving AZA/MP with outcome data describing thiopurine toxicity or tolerance ...... 187 7.3.2 Case-control study investigating for genetic variants associated with overall toxicity to AZA/MP therapy in patients with IBD ...... 189 7.3.3 Case-control study investigating AZA/MP induced nausea ...... 193 7.3.4 Case-control study investigating AZA/MP induced flu-like symptoms ...... 196 7.3.4 Case-control study investigating AZA/MP induced pancreatitis...... 201 7.3.5 Case-control study of AZA/MP-induced hepatotoxicity ...... 204 7.4 Discussion ...... 208 7.4.1 A model of overall thiopurine-induced toxicity ...... 209 7.4.2 A model of thiopurine-induced nausea ...... 210 7.4.3 A model of thiopurine-induced flu-like symptoms ...... 211 7.4.4 A model of thiopurine-induced pancreatitis ...... 212 7.4.5 A model of thiopurine-induced hepatotoxicity ...... 213 7.4.6 Conclusion ...... 214 Chapter Eight: The mechanism of allopurinol induced thiopurine-S-methyltransferase inhibition. . 215 8.1 Introduction ...... 215 8.2 Methods ...... 217 8.2.1 Metabolism of MP, TX and oxypurinol in intact red blood cells (RBCs) ...... 217 8.2.2 Measurement of TPMT kinetic and inhibition constants in red cell lysates using tandem mass spectroscopy...... 217 8.2.3 Measurement of urinary TX and oxypurinol levels in controls versus IBD patients receiving AZA alone or in combination with allopurinol...... 217 8.2.4 Statistics ...... 218 8.3 Results ...... 219 8.3.1 The effect of TX and oxypurinol on the production of MeMP in intact RBCs exposed to MP. 219 8.3.2 Apparent Km of TPMT and Ki for TX and oxypurinol...... 222 8.3.3 Urinary TX and oxypurinol levels in IBD patients receiving thiopurine therapy...... 224 8.4 Discussion ...... 227 Chapter Nine: Conclusions and future work ...... 232 9.1 Optimising thiopurine therapy in patients with IBD ...... 233 9.2 Moving from a candidate gene approach to a genome wide approach to identify novel opportunities to optimise thiopurine therapy in IBD ...... 234 9.3 Exploring thiopurine treatment response using novel whole-pathway analysis ...... 236

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

9.4 How could the genetic markers identified in this thesis be translated into clinical practice? ...... 238 9.5 Resolving the interaction between thiopurines and allopurinol ...... 238 9.6 Concluding remarks ...... 238 References ...... 240 Appendix 1 ...... 271 List of genes included in the thiopurine pathway...... 271 List of genes included in the methylation pathway ...... 274 Appendix 2 ...... 275 Demethylation of methylmercaptopurine by human liver microsomes; a role for CYP1A2 and CYP2C9 ...... 275

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Acknowledgements I would like to acknowledge and thank my supervisors, Dr Jeremy D. Sanderson and Dr Anthony M. Marinaki, for their support, reassurance and mentorship throughout this research. Without their guidance, expertise and invaluable input, this work could not have been completed.

I am indebted to the Guy’s and St Thomas’ Charitable Trust, the forCrohn’s Charity and the Crohn’s and Colitis UK Charity (CCUK) for financing this research.

I have relied on assistance from all colleagues in the Purine Research Laboratory (PRL) and the Department of Gastroenterology at Guy’s and St Thomas’ Hospital (GSTT). In particular, I would like to thank, Dr Monica Arenas-Hernandez, Ms Adele Corrigan, Dr Lynette Fairbanks, Mr El-Monsor Shobowale-Bakre, Dr Peter M. Irving, Dr Viraj Kariyawasam, Dr Melissa Smith, Dr Kirstin Taylor, Ms Julie Duncan and Mrs Anna Stanton for their advice and assistance with methodology, analysis, paper preparation and data collection. I additionally acknowledge and thank Prof Cathryn Lewis, Prof Christopher Mathew, Dr Jemma Walker and Ms Muddassar Mirza, in the Division of Genetics and Molecular Medicine at King’s College London, for providing statistical support, advice on data interpretation and assistance in the preparation and interrogation of the exome microarray chips.

I acknowledge the previous work by Dr Melissa Smith, which provided the platform for the current research.

I thank my parents Joe and Juliet Blaker for providing me with the greatest gift they could – an excellent education and thirst for knowledge.

Finally, I would like to acknowledge my wife, Laura Blaker, for her unending support throughout the years I have been involved with this project and our sons Joseph and Charles for providing the perspective needed to keep me sane whilst writing it up!

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Communications arising from this research

Original research papers and review articles Blaker PA, Arenas-Hernandez M, Marinaki AM, Sanderson JD. The pharmacogenetic basis of individual variation in thiopurine metabolism. Personalised Medicine, September 2012; 9: 707-725.

Hullah EA, Blaker PA, Marinaki AM, Escudier MP, Sanderson JD. A practical guide to the use of thiopurines in oral medicine. Submitted to the Journal of Oral Medicine and Oral Pathology, November 2013; awaiting peer review of revisions. Drs Hullah and Blaker are joint first authors.

Blaker PA, Arenas-Hernandez M, Smith MA, Shobowale-Bakre EA, Fairbanks L, Irving PM, Sanderson JD, Marinaki AM. Mechanism of allopurinol induced TPMT inhibition. Biochem Pharmacol. 2013 Aug 15; 86(4): 539-47.

Oral presentations Blaker PA, Peters van Ton AM, Arenas-Hernandez M, Smith MA, Smith CH, Irving PM, Marinaki AM, Sanderson JD. Optimising the response to thiopurine therapy: A search for novel explanations for thiopurine hypermethylation. Personalised Medicine Conference at the Sanger Institute, Sept 2011, Cambridge; DDW 2012, San Diego (abstract of distinction).

Blaker PA, Kariyawasam V, Patel KV, Goel RM, Ward M, Irving PM,Marinaki AM, Sanderson JD. The influence of gender and haemoglobin on TPMT activity. BSG 2013, Glasgow (abstract of distinction).

Blaker PA, Smith M, Arenas-Hernandez M, Fairbanks L, Irving PM, Sanderson JD, Marinaki A. Demethylation of methylmercaptopurine by human liver microsomes; a role for CYP1A2 and CYP2C9. Purine and Pyrimidine Conference, June 2013, Madrid.

Blaker PA, Arenas-Hernandez M, Shobowale-Bakre EA, Fairbanks LD, Irving PM, Sanderson JD, Marinaki AM. The mechanism of allopurinol induced TPMT inhibition. Purine and Pyrimidines Conference, June 2013, Madrid.

Poster presentations Blaker PA, Arenas M, Fairbanks L, Irving P, Marinaki AM, Sanderson J. A biochemical mechanism for the role of allopurinol in TPMT inhibition. DDW 2011, Chicago (abstract of distinction).

Smith MA, Blaker PA, Marinaki AM, Anderson SH, Irving PM, Sanderson JD. Calculating the “missed opportunity” of thiopurine monotherapy with thiopurine and allopurinol combination therapy. DDW 2012 San Diego.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Book chapters Blaker PA and Irving PM. Colonic Crohns Disease. In: Inflammatory Bowel Disease: An Evidence- Based Practical Guide. Eds Hart AL and Ng SC. TFM Publishing Ltd.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Abstract

The thiopurines, mercaptopurine (MP) and its pro-drug azathioprine (AZA), are the first line immunomodulators used in the management of inflammatory bowel disease (IBD). Unfortunately, 30 - 40% of patients are unable to derive benefit from these medicines as a result of drug toxicity or treatment non-response. The main active metabolites of these drugs are the phosphorylated thioguanine nucleotides (TGNs) and methylated derivatives of mercaptopurine (MeMP). Recent experience suggests that measurement of these metabolites can be used to explain inter-individual variation in response to treatment and identify opportunities to optimize therapy. In particular, some patients with IBD display sub-optimal TGN levels and unexpectedly high MeMP concentrations, a phenotype which is known as thiopurine hypermethylation. Importantly this skewed drug metabolism can be circumvented using a low dose of AZA/MP in combination with allopurinol.

This thesis provides an original contribution to knowledge by firstly exploring and characterizing thiopurine hypermethylation in patients with IBD to determine its impact on clinical response. Secondly, it investigates the mechanism of thiopurine hypermethylation and other thiopurine- induced drug toxicities using both candidate gene and genome-wide approaches, with the goal of identifying biomarkers that can be used to predict outcomes prior to the start of treatment. Finally, it resolves the biochemical interaction between thiopurines and allopurinol, which has remained unexplained for over half a century.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

List of abbreviations

5,10-MTHF 5, 10-methylenetetrahydrofolate 5-ASA 5-Aminosalicylates 8-OH-MP 8-hydroxy-mercaptopurine ABC Adenosine triphosphate-binding cassette transporter family ADA Adenosine deaminase (gene ADA) ADK Adenosine kinase (gene ADK) ADR Adverse drug reaction ALL Acute lymphoblastic leukaemia ALT Alanine transaminase ALP Alkaline phosphatase ANOVA Analysis of variance AOX Aldehyde oxidase (gene AOX1) APRT Adenine-phosphoribosyltransferase (gene APRT) ATP Adenosine triphosphate AZA Azathioprine bp Base pair CD Crohn’s disease CI Confidence interval DMSO Dimethyl sulphoxide DNA Deoxyribonucleic acid DNPS De Novo purine synthesis dNTP Deoxynucleotide triphosphate DPK Diphosphate kinase EBBS Earle’s balanced salt solution EDTA Ethylenediamine tetra-acetic acid F Response factor GDA Guanine deaminase (gene GDA) GKT Guy’s, King’s and St Thomas’ (patient identification number) GMPS Guanine monophosphate synthase (gene GMPS) GMPR Guanine monophosphate reductase (gene GMPR) GSH Glutathione GST Glutathione-S-transferase GSTT Guy’s and St Thomas’ NHS Foundation Trust

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

GTP Guanine triphosphate GWAS Genome-wide association study h Hour Hb Haemoglobin HPLC High performance liquid chromatography HPRT Hypoxanthine guanine phosphoribosyltransferase (gene HPRT1) HWE Hardy-Weinberg Equilibrium IBD Inflammatory bowel disease IMPDH Inosine monophosphate dehydrogenase IPTA Inosine triphosphate pyrophosphohydrolase (gene ITPA) IU International units of enzyme activity kg Kilogram KLF Krupple-like factor L Litre LD Linkage disequilibirium MAF Minor allele frequency MCV Mean corpuscular volume MCH Mean corpuscular haemoglobin MeMP Methylmercaptopurine MeMP-rib Methylmercaptopurine riboside MeTIMP Methylthioinosine monophosphate mg Milligram min Minute MMR Mismatch repair MOCOS Molybdenum co-factor sulfurase (gene MOCOS) MP Mercaptopurine (formerly known as 6-mercaptopurine or 6-MP) MP-rib Mercaptopurine riboside MPA Mycophenolic acid MPK Monophosphate kinase MTHFR Methylenetetrahydrofolate reductase (gene MTHFR) MTX Methotrexate NAD+ Oxydised nictotinamide adenine dinucleotide NICE National Institute of Clinical Excellence nm Nanometre

PhD Thesis Thiopurines in IBD Paul Andrew Blaker nmol Nanomole NNH Number needed to harm nsSNP Non-synonomous single nucleotide polymorphism P Probability PCR Polymerase chain reaction pmol picomole PRL Purine Research Laboratory PRPP 5-phosphoribosyl-1-pyrophosphate Rac1 Rhodamine GTPase protein 1 RBC Red blood cell RNA Ribonucleic acid RNR Ribonucleotide reductase (gene RRM) ROS Reactive oxygen species SAH S-adenosylhomocysteine SAM S-adenosylmethionine SD Standard deviation SEM Standard error of the mean SNP Single nucleotide polymorphism Th Type 1 helper T-cell TG Thioguanine TG-rib Thioguanine riboside TGN Thiogunaine nucleotide TGMP Thioguanosine monophosphate TGDP Thioguanosine diphosphate TGTP Thioguanosine triphosphate TIMP Thioinosine monophosphate TIDP Thioinosine diphosphate TITP Thioinosine triphosphate TNF-α Tumour necrosis factor alpha TPMT Thiopurine-S-methyltransferase (gene TPMT) Tris Tris(hydroxymethyl)methylamine TUA Thiouric acid TX Thioxanthine (2-hydroxy-mercaptopurine) TYMS Thymidylate synthetase (gene TYMS)

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

UPLC Ultra-high performance liquid chromatography UC Ulcerative colitis µmol Micromole UV Ultra violet light VNTR Variable number tandem repeats WBC White blood cells XDH Xanthine dehydrogenase (gene XDH) Y Years

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Chapter One: Literature review

1.1 Definition, epidemiology and pathogenesis of inflammatory bowel disease

The inflammatory bowel diseases (IBD), which comprise ulcerative colitis (UC), Crohn’s disease (CD) and microscopic colitis, are characterised by chronic inflammation of the gastrointestinal tract. Whilst the pathogenesis remains incompletely understood, it is generally accepted that clinical disease occurs in genetically susceptible individuals following exposure to environmental risk factors, causing dysregulation of the adaptive and innate immune responses with subsequent chronic gut inflammation (1-3). Characteristic symptoms include diarrhoea, abdominal pain, weight loss, fever, malaise and anorexia, although myriad extra-intestinal manifestations are recognised (4). The majority of affected individuals experience a relapsing-remitting course, with periods of active disease brought into remission of varying length by medical or surgical interventions. In approximately 6% of cases it is not possible to define an exact diagnosis, in which case the term ‘IBD unclassified’ (IBD-U) is applied (5-7).

The peak incidence of IBD is in young adult life (UC, 15-30 years; CD, 20 – 30 years), although a second smaller peak in later life (50 – 70 years) is observed in UC (8). The highest prevalence rates for both UC and CD are found in northern Europe (UC, 505 per 100,000 population; CD, 322 per 100,000 population) and North America (UC, 249 per 100,000 population; CD, 319 per 100,000 population) (3, 9). Worldwide, north-south, east-west and urban-rural gradients for incidence rates (new cases per 100,000 person-years) and prevalence of IBD have been described, although geographical boundaries appear to be diminishing (10). In northern Europe the incidence rate ranges between 1.5 – 20.3 cases per 100,000 for UC and from 0.7 – 9.8 cases per 100,000 for CD, equating to approximately 2.2 million affected individuals (8). In addition to being associated with significant morbidity and reduced quality of life, IBD also has major economic consequences, with estimated costs of £720 million per annum in the United Kingdom (11).

In general UC is diagnosed 5 – 10 years later in life than CD and has a slight male preponderance, whereas the opposite has been reported in CD (12). Men are often diagnosed at a later age than women (8). Despite initial reports of IBD being associated with higher socioeconomic status, this has since been disproven (13). The most significant environmental risk factors are smoking, appendicectomy and a Western lifestyle. Early tobacco use significantly increases the risk of developing CD and is associated with a more severe disease course and post-operative recurrence, whereas it appears to reduce the risk of UC (14). Appendicectomy at a young age is generally

PhD Thesis Thiopurines in IBD Paul Andrew Blaker reported to provide protection against UC, whereas it increases the risk of CD (8, 15, 16). Consumption of a Western diet, containing excessive amounts of sugar and polyunsaturated fats, is hypothesized to explain the increase in incidence rates in previously less affected ethnic groups such as Asians and Hispanics and in immigrants moving from regions of low incidence to areas of traditionally high incidence (17, 18).

The rise in the incidence of IBD in both the developed and developing world over the course of the 20th century is further hypothesized to relate to decreased microbial exposure in childhood. This is the basis of the “hygiene hypothesis”, which proposes that a child could be overprotected from exposure to common infectious agents as a result of improved hygiene (19). Such exposure is believed to be necessary in programming the immune response of the gut, establishing an immunological balance between pro-inflammatory Th1 and tolerance-inducing regulatory T-cells in early childhood (20). In the absence of this, contact with a pathogenic infectious agent later in life, could trigger an inappropriate immunological response characterized by the development of an abnormal or ineffective inflammatory process and potentially IBD.

UC and CD are complex genetic disorders. Familial aggregation has been recognised for over 70 years. In this regard, 5.5% – 15.7% of patients with UC have a first degree relative with the same disease, whereas in CD, studies of twins suggest concordance rates in monozygotic and dizygotic pairs of 35% and 3% respectively (21-23). At a population level, a genetic basis for IBD is evidenced by the disease prevalence in Ashkenazi Jews, which is higher than in any other ethnic group. Genome- wide association studies (GWAS) have thus far identified 163 susceptibility loci, of which 110 are associated with both diseases, 23 are UC specific, and 30 are CD specific (24-26). However, the number of loci identified to date expounds approximately 20% of the heritability of IBD. The missing links are likely to be explained by genetic epistasis, gene-gene interactions and the presence of environmental antigens, including the intestinal microbiota.

The identification of susceptibility loci has enhanced the current understanding of disease pathogenesis by providing signals from the dysregulated immune pathways. UC appears to involve an exaggerated T-cell (modified atypical Th2) response, causing mucosal hyper-responsiveness to commensal bacteria (27). Whereas in CD, alterations in genes associated with intestinal barrier function (MUC1, MUC19 and PTGER4) and bacteria-immune interactions (NOD2, ATG16L1, IGRM), suggest a weakened inflammatory cytokine response and impaired autophagy of invasive gut microbes (28).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.2 Natural history of inflammatory bowel disease

In UC inflammation is generally confined to the mucosal surface and spreads in a continuous manner from the rectum through the entire colon. At diagnosis, the inflammation is restricted to the rectum or sigmoid colon (distal colitis) in 30-50%, 20-30% have left-sided disease (up to the splenic flexure), and approximately 20% have extensive disease (pan-colitis) (29). Anatomic extension can occur with time and is anticipated in 25-50% with distal colitis (30). The extent of mucosal inflammation is an important prognostic factor; patients with more severe disease tend to have more extensive inflammation than those with less severe disease. Disease extent is also a predictor of both colectomy (3 – 4 fold higher risk than with proctitis) and colorectal cancer (31, 32). The life-time risk of colectomy is 20-30%, increasing to 40% in patients with extensive and long-standing disease (30). In addition, a period of less than 2 years from diagnosis to the first flare, the presence of fever or weight loss at onset, and active disease in the preceding 12 months predicts a more severe disease phenotype and risk of subsequent relapse (30).

In CD the inflammation is typically trans-mural and discontinuous in nature, affecting any point of the gastrointestinal tract from the mouth to the anus. The most common sites involved are the terminal ileum (45%), colon (32%) and ileo-colon (19%). At diagnosis the majority of patients have non-stricturing, non-penetrating disease; however, up to 20% of patients demonstrate a more aggressive phenotype by as early as 90 days, which progresses to 51% at 20 years, particularly in those with ileal involvement or perianal disease (33). Indeed, 50% of patients require surgery within 10 years of diagnosis, with a risk of post-operative recurrence of 44-55% in the subsequent decade (34). In contrast to UC, life expectancy is slightly reduced in CD. A younger age at diagnosis, perianal disease, a need for corticosteroids at presentation, colonic resection, repeated small bowel resection, a stricturing phenotype and substantial weight loss predict a more severe disease course (35).

1.3 Treatment strategies and goals of therapy

Since there is no cure for IBD, the goals of therapy are focused on eliminating symptoms (induction of remission), preventing disease flares (maintenance of remission) and restoring quality of life. In UC, first line treatments comprise topical and oral 5-aminosalicylates (5-ASAs), with corticosteroid treatment reserved for acute flares uncontrolled by high-dose 5-ASA therapy alone. It is widely accepted that exposure to corticosteroids should be limited, given their lack of efficacy for maintenance of remission and high side effect profile. Therefore in patients requiring frequent corticosteroid therapy (more than 2 courses in a 12 month period), or in those with steroid

PhD Thesis Thiopurines in IBD Paul Andrew Blaker dependent disease, escalation to a thiopurine is advocated. Whilst evidence supports the use of anti-tumour necrosis factor alpha (anti-TNF-α) antibody therapy in UC, the National Institute of Clinical Excellence (NICE) has not yet approved their use beyond acute severe UC (36). Furthermore, evidence for the use of alternative immunomodulators such as methotrexate (MTX), calcineurin inhibitors and mycophenolic acid (MPA) is currently lacking. Therefore where a thiopurine is prescribed for the management of UC, there is a need to optimise therapy, since failure to achieve disease remission may indicate the need for a colectomy, with the potential for major physical and psychological consequences.

In CD, current treatment algorithms based on the use of 5-ASAs, antibiotics, nutritional therapy, corticosteroids, immunomodulators and anti-TNF-α therapy, traditionally advocate a step-wise escalation of treatment through these drug classes (37). However, early intervention with more potent compounds, using “top-down” or “rapid step-up” regimens, with early and aggressive use of immunosuppressive antimetabolites and anti-TNF-α therapy, may be appropriate in some patients - particularly those with predictors of a more severe disease phenotype. Co-prescription of thiopurines with anti-TNF-α agents appears to provide additional benefit for both disease remission and maintenance, further extending rather than reducing the indications for thiopurine use in IBD (38). Such strategies are additionally supported by recent data showing that mucosal healing may alter the natural history of CD and to a lesser extent UC, with sustained clinical remission and improved rates of resection-free survival (39, 40).

Shifting treatment paradigms towards goals of mucosal healing with the earlier use of immunomodulators and anti-TNF-α therapy is therefore attractive; however, there are a number of reasons why these treatment options are not suitable for all patients early in the disease course. Apart from cost, which is of particular relevance to the availability of drugs on the NHS, issues related to safety, including adverse reactions and treatment complications, remains a concern. As discussed in the following section, adverse events are commonly observed during treatment with azathioprine (AZA), including leukopaenia, thrombocytopaenia, pancreatitis and impaired liver function, which fortunately improve upon drug withdrawal. However, irreversible effects including the development of veno-occlusive disease and the devastating complication of lymphoma are also reported (41). Overall, the risk of lymphoma appears to be doubled in patients treated with AZA in comparison with that of the general population (42). The risk of lymphoma is also higher in patients receiving infliximab compared to patients receiving standard therapy (43). Opportunistic infections during conventional use of antimetabolites are also often encountered, and more so when given in combination with corticosteroids or anti-TNF-α therapy (44, 45). Viral infections, including

PhD Thesis Thiopurines in IBD Paul Andrew Blaker cytomegalovirus are the most common type of opportunistic infections observed on conventional immunomodulators, and whilst causing considerable morbidity are rarely fatal. In contrast, anti- TNF-α therapy is more frequently associated with bacterial and fungal infections, such as mycobacterial infections, listeriosis and invasive aspergillosis, which carry a higher risk of mortality (46). In addition to infections, anti-TNF-α therapy is associated with the development of irreversible demyelination, exacerbations of heart failure and myriad skin manifestations including eczema and psoriasis. Given the potential of multiple complications and the risk of causing serious harm, immunomodulatory agents must therefore only be used in patients where the benefits heavily outweigh the risks and when toxicity can be limited as far as practicable. Careful selection of patients, particularly where combinations of immunosuppression are to be used, is thus of paramount importance. In this regard, the identification and use of biomarkers that predict toxicity and treatment response prior to the start of therapy would be useful in rationalising the treatment regimen selected for an individual patient.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.4 Thiopurines in inflammatory bowel disease; history, efficacy and toxicity

In the 1940s George Hitchins and Gertrude Elion theorized that, since all cells require nucleic acids, it might be possible to stop the growth of rapidly dividing cells, such as tumours or bacteria, with antimetabolites of nucleic acid bases (47). It was subsequently observed that substitution of oxygen by sulfur at the 6-position of guanine and hypoxanthine produced inhibition of purine utilization, cell-cycle arrest and apoptosis; leading to the discovery of the pro-drugs thioguanine (TG, 2,6- diaminopurine) and mercaptopurine (MP). AZA, a 1-methyl-4-nitro-5-imidazolyl derivative of MP, was developed later in an attempt to improve the bioavailability of MP (figure 1.1).

Figure 1.1 Chemical structure of the canonical nucleobases hypoxanthine and guanine in comparison with AZA, MP and TG.

The thiopurine drugs are thiol-containing analogues of the endogenous purine bases hypoxanthine (AZA and MP) and guanine (TG). AZA contains an additional imidazole ring which improves drug solubility and stability. The molecular weight of MP is 55% that of AZA, therefore a scale factor of 2.08 is needed to convert MP to an equivalent dose of AZA, assuming 100% bioavailability.

In 1953 MP was introduced for the management of acute leukaemias with the finding that it could induce complete remission, although many patients relapsed after a median of 12 months (48). MP was subsequently shown to improve the survival of canine kidney homographs, although in this regard AZA was more effective (49, 50). Following the first successful transplant of human kidneys to

PhD Thesis Thiopurines in IBD Paul Andrew Blaker unrelated recipients in 1962, AZA became a mainstay of organ transplant immunosuppression and has only been superseded by more efficacious therapies within the last two decades. MP is still used in combination with methotrexate to induce and maintain remission in some acute lymphoblastic leukaemias and both AZA and MP are recommended as first line steroid-sparing immunomodulators in a number of chronic inflammatory conditions, including; rheumatoid arthritis, systemic lupus erythematosus, pemphigus vulgaris, dermatomyositis, eczema, Bechet’s disease and IBD (51-54).

AZA and MP were first used in the management of IBD in 1968 and have since demonstrated efficacy in both the induction and maintenance of remission in steroid-dependent and chronic relapsing disease (55-57). In UC, data from meta-analysis demonstrates that induction of clinical remission is achieved in 60% – 78.6% of patients treated with AZA/MP, whilst maintenance of clinical remission is observed in 41.7% – 82.4% of initial responders (58). Similarly in CD, induction of remission is obtained in over half of patients, whilst maintenance of remission is reported in approximately three-quarters of initial responders (59). Furthermore, AZA has been shown to promote fistula healing in CD and early post-operative use reduces the risk of clinical and endoscopic disease relapse (60-62). However, the use of thiopurines in IBD is limited by the occurrence of serious adverse drug reactions (ADR), which leads to the cessation of therapy in 9-25% of patients, whereas an additional 9-15% fail to derive any therapeutic benefit (59, 63, 64).

Adverse reactions related to thiopurine therapy can be classified as either dose-independent (idiosyncratic) or dose-dependent. Idiosyncratic reactions typically occur within the first 2 - 4 weeks of therapy. These reactions are thought to be immune-mediated and include gastrointestinal complaints (1.3% - 6%), rash (< 1%), pancreatitis (3%), fever, arthralgia and flu-like symptoms (3.9%) (54). Dose-dependent reactions may occur at any time during therapy and include myelotoxicity (1.4% – 5%) and hepatotoxicity (4.2%). TG has been proposed as an alternative to AZA/MP following the occurrence of pancreatitis, whereas myelotoxicity and hepatotoxicity may respond to dose reduction (65). Potential mechanisms of thiopurine toxicity are further explored in Chapter 7 of this thesis.

According to the recent guidelines of the British Society of Gastroenterology and the American College of Gastroenterology, the regular assessment of full blood counts (FBC) is important to prevent or allow timely recognition of adverse events and evaluate clinical response in patients prescribed thiopurines; however routine testing of transaminases and serum amylase is not recommended (37, 66). At GSTT it is standard practice to monitor the FBC and liver function tests (LFTs) on a 2 weekly basis for the first 8 weeks of treatment and 3 monthly thereafter.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Since the immunosuppressive effects of thiopurines are delayed by approximately 12-17 weeks, a physician will usually need to support an acutely unwell patient for at least 3 months, with corticosteroids, calcineurin inhibitors or TNF-α inhibitors before a response can be determined (59). This emphasises the need to individualize therapy using markers that predict clinical response or ADRs prior to the start of treatment. Identification of these markers requires a detailed knowledge of thiopurine metabolism.

1.5 Thiopurine metabolism

The metabolism of thiopurines is complex (figure 1.2). AZA and MP have no intrinsic activity and need to undergo extensive metabolic transformation via enzymes of the purine salvage pathway to exert their clinical effect. Following absorption, peak plasma concentrations are reached by 1-2 hours and then rapidly decline with half-lives of less than 1 hour (67). The bioavailability of orally administered AZA (27-83%) and MP (5-37%) is highly divergent and may explain some of the inter- individual variation in response (68, 69). Indeed only one third of patients achieve plasma concentrations of MP above the minimal in-vitro cytotoxic concentration of 100 µmol/ L (70). This mainly arises due to extensive and variable first pass metabolism of MP to 8-hydroxy-MP or 2- hydroxy-MP (thioxanthine; TX) and then to thiouric acid (2,8-dihydroxy-mercaptopurine; TUA), reactions catalyzed by aldehyde oxidase (AOX) and xanthine oxidase/dehydrogenase (XDH) (71, 72). XDH is highly expressed in the intestine and liver but is absent from circulating blood cells and bone marrow, indicating differences in metabolism between these cellular compartments (73). Whilst AZA is not a substrate for XDH it can undergo hydroxylation by AOX to form TUA (74). Following a single dose of AZA, TUA is completely cleared from the urine within 24 hours (75). The other major urinary metabolites are methyl-8-hydroxy-MP and sulfate, the latter arising via desulfuration of methyl- mercaptopurines (76).

Approximately 12% of AZA is eliminated unmetabolized by the intestine (77). Of the absorbed AZA, 88% is converted to MP and methyl-4-nitro-5-imidazole, most likely by glutathione-S-transferases (78, 79). Non-enzymatic cleavage of the nitro-imidazole group has also been described (78, 80) The remaining 12% of thiolysis occurs on the opposite side of the sulfur moiety and generates hypoxanthine and methyl-4-5-thioimadazole, the latter of which has been implicated in the development of hypersensitivity reactions (81).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Figure 1.2 Summary of thiopurine metabolism

Metabolites - AZA, azathioprine; MP, mercaptopurine; 8-OH-MP, 8-hydroxy-mercaptopurine; TX, thioxanthine (2-hydroxy-mercaptopurine); TUA, thiouric acid (2,8-dihydroxy-mercaptopurine); TG, thioguanine; 8-OH-TG, 8-hydroxy-thioguanine; MeMP, methylmercaptopurine nucleobase; MeTIMP, methylthioinosine monophosphate; TIMP, thioinosine monophosphate; TIDP, thioinosine diphosphate; TITP, thioinosine triphosphate; TXMP, thioxanthosine monophosphate; TGMP, thioguanine monophosphate; TGDP, thioguanine diphosphate; TGTP thioguanine triphosphate; dTGDP, deoxythioguanine diphosphate; dTGTP, deoxythioguanine triphosphate; TG-rib, thioguanine riboside; MeTG, methylthioguanine; MeTGMP methylthioguanine monophosphate.

Enzymes – GST, glutathione-S-transferase; XDH, xanthine dehydrogenase; AOX, aldehyde oxidase; GDA, guanine deaminase; TPMT, thiopurine-S-methyltransferase; HPRT, hypoxanthine-guanine phosphoribosyltransferase, ITPase, inosine triphosphate pyrophosphatase; IMPDH, inosine monophosphate dehydrogenase; GMPS, guanosine monophosphate synthetase; NT5E, ectoplasmic 5’-nucleotidase; ADK, adenosine kinase; RNR, ribonucleotide reductase.

DNPS, de-novo purine synthesis. Adapted from Fotoohi et al, Biochem Pharmacol 2010; 79: 1211 (82).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Following intracellular uptake by nucleoside transporters (SLC28 and SLC29) MP is metabolized by 3 competing pathways (83-86). Degradation is mediated by conversion to TUA or via thiopurine-S- methyltransferase (TPMT) to form the methylmercaptopurine nucleobase (MeMP). The methyl donor for this reaction is S-adenosylmethionine (SAM). S-adenosylhomocysteine (SAH), a potent inhibitor of methyltransferase activity, is generated as a reaction product. MeMP is an inactive metabolite and is not a substrate for hypoxanthine-guanine phosphoribosyltransferase (HPRT), however it may undergo oxidation by XDH to form 8-hydroxy-methylmercaptopurine and 2,8- hydroxy-methylmercaptopurine (87, 88). Alternatively, MP can be converted to a nucleotide; thioinosine monophosphate (TIMP). This is catalyzed by HPRT, which requires 1- pyrophosphoribosyl-ribose-5’-phosphate (PRPP) as the phosphoribosyl donor. TIMP can be further transformed by inosine monophosphate dehydrogenase (IMPDH) into thioxanthosine monophosphate (TXMP), which is subsequently converted via guanosine monophosphate synthase (GMPS) to form thioguanine monophosphate (TGMP). Monophosphate and diphosphate kinases metabolize TGMP into thioguanine diphosphate (TGDP) and thioguanine triphosphate (TGTP) respectively. The metabolites TGMP, TGDP , TGTP and their deoxyribose equivalents generated by ribonucleotide reductase (RNR), form the pool of thioguanine nucleotides (TGN), which represent the active thiopurine metabolites (89). The half-life of TGNs in nucleated cells is approximately 5 days, although the range is wide (3-13 days) (90).

In the majority of the current literature the conversion of MP to MeMP is purported to be an irreversible reaction. However, in 1960 Sarcione and Stutzman reported that MeMP could also undergo demethylation, with the observation that MP is a urinary metabolite in rats given MeMP (91) . Elion et al later confirmed this finding in man, reporting the presence of TUA in urine from patients receiving MeMP (92). Further, in 1964 Mazel et al demonstrated that the liver microsome fraction is likely to be responsible for the demethylation of S-methyl compounds (93). Recently, demethylation of MeMP by cytochromes 1A2 and 2C9 has been confirmed in vitro, using human recombinant cytochrome P450 enzyme preparations; however demethylation of MeMP appears to be a relatively minor pathway (Appendix 2) (94). Nonetheless these are important findings since they suggest flux between TPMT and demethylating enzymes that may partly explain variation in thiopurine metabolite profiles and some drug interactions.

Similar to MP, TIMP can also be methylated by TPMT to form methyl-thioinosine monophosphate (MeTIMP), which is not a substrate for IMPDH. Alternatively, phosphate kinases may form thioinosine diphosphate (TIDP) and thioinosine triphosphate (TITP), both of which are substrates for TPMT forming methyl-TIDP (MeTIDP) and methyl-TITP (MeTITP) respectively (95). The methylated

PhD Thesis Thiopurines in IBD Paul Andrew Blaker derivatives of TIMP are known as the methylmercaptopurine ribonucleotides, which are the major methylated metabolites of AZA/MP metabolism (figure 1.3). Inosine triphosphate pyrophosphatase (ITPase), catalyzes the conversion of TITP back to TIMP. In comparison with TITP, MeTITP is a poor substrate for ITPase (96).

Figure 1.3 The formation of methylmercaptopurine ribonucleotides

MP and each of the thioinosine nucleotides may undergo methylation by TPMT. Methylation of these intermediates impairs the synthesis of thioguanine nucleotides (TGNs), thereby reducing the effective thiopurine dose. SAM, S-adenosylmethionine; SAH, S-adenosylhomocysteine.

It is under-appreciated that TIMP may also be hydrolyzed by cytoplasmic 5’-nucleotidase (NT5C) to form mercaptopurine riboside (MP-rib), which in turn is a substrate for purine nucleoside phosphorylase (PNP), generating the MP nucleobase (97, 98). Similarly MeTIMP can be catabolized to methyl-methylmercaptopurine riboside (MeMP-rib) by NT5C. MeMP-rib is then phosphorylated by adenosine kinase (ADK) to form MeTIMP (99) (Figure 1.4). Variation in the inter-conversion between TIMP, MP-rib, MP nucleobase and their respective methylated equivalents, may explain some of the differences in thiopurine metabolism between individuals and warrants further investigation in-vivo.

Weigel et al additionally asserted that MeMP could be converted to MeTIMP by adenine- phosphoribosyltransferase (APRT) (100). However, this miss-interprets the earlier work by Gibboney et al, who reported that ethylmercapotopurine and not methylmercaptopurine is metabolized by

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

APRT (101). Furthermore, Elion demonstrated that methylmercaptopurine is not a substrate for APRT (102).

Figure 1.4 The interconversion between mercaptopurine nucleobases and ribonucleotides

Abbreviations: AZA, azathioprine; GSH, glutathione; MP, mercaptopurine; TPMT, thiopurine-S- methyltransferase; SAM, S-adenosylmethionine; MeMP, methylmercaptopurine; HPRT hypoxanthine- guanine phosphoribosyltransferase; PRPP 1-pyrophosphoribosyl-ribose-5’-phosphate; TIMP, thioinosine monophosphate; NT5C, cytoplasmic 5’nucleotidase; MP-rib, mercaptopurine-riboside; PNP, purine nucleoside phosphorylase; MeMP-rib, methylmercaptopurine riboside; ADK, adenosine kinase; MeTIMP, methylthioinosine monophosphate; DNPS, de-novo purine synthesis; TGMP, thioguanine monophosphate; IMPDH, inosine monophosphate dehydrogenase; GMPS, guanosine monophosphate synthestase; GMPR, guanosine monophosphate reductase.

In contrast to AZA and MP, the metabolism of TG is less complex. The bioavailability of TG is estimated to be 14-46% with plasma concentrations ranging up to 30-fold (103). Due to rapid intracellular transport, the drug is undetectable in plasma after 6 hours (104). HPRT converts TG directly into TGMP, which omits many of the rate limiting steps, such as IMPDH, in the purine salvage pathway. In-vitro TG is also a substrate for TPMT and has similar enzyme kinetics to MP (105). Degradation of TG to TUA occurs via two routes. TG may be deaminated by guanine deaminase

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

(GDA) to form TX, which is metabolized to TUA by XDH (106). Alternatively, TG may be hydroxylated by AOX and then deaminated by GDA, generating 8-hydroxy-TG as an intermediate (107).

Transporters such as the ATP-binding cassette sub-family C members 4 and 5 (ABCC4, ABCC5; formerly MRP-4 and MRP-5) have been implicated in the cellular efflux of thiopurine nucleotides (108). In-vitro, ABCC4 has been shown to transport TGMP across the cell membrane, where it is dephosphorylated by ectoplasmic 5’-nucleotidase (NT5E) to form a TG-riboside (TG-rib). The extracellular circulation is completed by transfer of TG-rib back into the cell via the nucleoside transporters SLC28/29 (109). Identification of other cellular efflux pumps may further explain individual variation in thiopurine metabolism. This concept is further explored in Chapters 5, 6 and 7.

1.6 Mechanisms of thiopurine action

The immunomodulatory action of thiopurines has traditionally been ascribed to the substitution of “rogue” thiopurine nucleotides into DNA, truncating the affected replicating strands with subsequent apoptosis. On the contrary, dTGTP is a good substrate for replicative DNA polymerases and DNA can continue to replicate beyond an incorporated TGN (110). Indeed, in intact cells, a low level of DNA substitution by dTGTP is neither toxic nor particularly mutagenic (111). However, the presence of the relatively large sulfur atom in thioguanine subtly alters the structure of DNA and reduces the stability of base-pair formation. Moreover, thioguanine codes ambiguously with both cytosine and thymidine bases with approximately equal facility, creating the potential for mutations (112).

DNA incorporated TGNs are also vulnerable to attack by reactive oxygen species and, following oxidation, are incapable of forming base pairs with either cytosine or thymidine, destabilising the double helix more effectively than even a purine:purine or pyrimidine:pyrimidine pair (111, 113). Similarly, TGNs are two orders of magnitude more susceptible to SAM-mediated chemical methylation than canonical nucleotides (111, 114). They also have a lower affinity for methylguanine methyltransferase (MGMT), which is involved in the demethylation and restoration of DNA (115). Methylation has several consequences including; further distortion of DNA structure, promotion of point mutations, increased mis-pairing with thymidine and silencing of gene expression (115-117). In respect of the latter it has recently been suggested that TG may mediate immunosuppression by acting as a hypomethylating agent, through modulation of DNA methyltransferases (118). This is believed to be an epigenetic phenomenon, due to reduced expression of histone lysine-specific demethylase-1, which subsequently triggers degradation of DNA methylase-1 (119).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

The formation of methylated dTGTP:thymidine or cytosine base pairs resembles replication errors, which provoke post-replicative processing by the DNA mismatch repair (MMR) system. In this regard, the aberrant base-pairs are recognised and engaged by the MutSα (a dimer of MSH2 and MSH6) mismatch binding complex, which recruits a second dedicated MMR factor, MutLα (a dimer of MLH1 and PMS2). This triggers mismatch correction attempts that remain incomplete since it is not possible to incorporate a perfectly paired base opposite the DNA lesion. The anomalous DNA structures generated by failed repair attempts are observed as DNA strand interruptions (120). During the S phase of the subsequent cell cycle, these are interpreted as lethal aberrant DNA structures, triggering G2 cell-cycle arrest and apoptosis (111, 117). The selective killing of dividing cells likely explains the predilection of thiopurines for cells with a rapid turnover such as T and B lymphocytes (121, 122).

Cells with defective MMR systems, for example those with mutations in MutSα or MutLα appear relatively resistant to thiopurines, despite high levels of TGNs, since they are unable to initiate lethal processing (123). This has been confirmed in mice where MSH2 deficiency was shown to attenuate, although not abolish, thiopurine haemopoietic toxicity (124). Since the cytotoxic effects of thiopurines are not completely circumvented by aberrations in the MMR system, additional mechanisms are implicated. In this regard, detection of fraudulent base pairs by glyceraldehyde 3-phosphate dehydrogenase is proposed to contribute to cell death (125). Furthermore, incorporation of dTGTP into the 3’ region of chromosomes, is hypothesized to prevent binding of telomerase, an essential component of cell division (126). Of interest, reduced telomerase activity has been reported in peripheral blood lymphocytes from patients with Crohn’s disease receiving AZA (127).

Other than incorporation into DNA and RNA, TGNs additionally compete with endogenous nucleotides e.g. guanosine triphosphate (GTP), which are vital for intracellular signalling and energy carrying processes (128). In particular, TGTP may bind the small GTPase Rac1, which inhibits the activity of the guanosine exchange factor VAV1 (129, 130). This leads to reduced expression of Rac1 target genes, such as NF-kB, STAT3, Bcl-xL and mitogen-activated protein kinases, mediating a mitochrondrial pathway of apoptosis in activated T-lymphocytes (129, 130).

Recent evidence has also shown that thiopurines reduce the expression of TNF-α related apoptosis- inducing ligand, TNF-α receptor superfamily member 7 and α4-integrin (131). In addition TGN levels inversely correlate with interferon-γ levels, and natural killer cell activity is attenuated in patients with CD following treatment with MP (131, 132). MP also alters in-vitro activation of dendritic cells, denoted by attenuated IL-23 production, reduced CCR7 expression and increased IL-10 synthesis, thereby leading to a more tolerogenic phenotype (133).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Several lines of evidence suggest that thiopurines can also alter the function of macrophages. In- vitro, AZA is associated with altered recruitment, gene expression, enzyme activity and nitric oxide production in stimulated macrophages (134-138). Whereas in-vivo, treatment with AZA is noted to reduce numbers of both peripheral blood monocytes and macrophages (139).

Methylated thiopurine ribonucleotides also have biological activity (140, 141). Proliferating lymphocytes are dependent on de novo purine synthesis (DNPS) for the production of purine nucleotides and therefore DNA synthesis. MeTIMP is a strong inhibitor of glutamine-5- phosphoribosylpyrophosphate amidotransferase, the rate limiting enzyme of DNPS, which is anticipated to have several effects (142). Firstly, the concentration of PRPP increases, promoting salvage of thiopurine precursors via HPRT and enhancing the formation of TGNs. Secondly, inhibition of DNPS may facilitate incorporation of dTGTP into DNA, meaning that lower concentrations of TGNs have a greater cytotoxic effect (143). Finally, perturbation of DNPS leads to an imbalance between purine and pyrimidine nucleotides leading to cell death (144).

The extent to which MeTIMP contributes to immunosuppression in IBD has been questioned on the basis of studies that found no correlation between MeMP metabolite concentrations and disease remission (145). However, a biological effect is likely since patients with complete TPMT deficiency (who do not form MeTIMP) appear to tolerate higher concentrations of TGNs than patients with normal TPMT activity (146).

1.7 Thiopurine metabolite monitoring

Therapeutic monitoring of thiopurine therapy was initially restricted to measurement of plasma MP and urinary excretion of TUA (147). Whilst useful for monitoring adherence, neither measure correlates with clinical response. Therefore an assay to monitor TGN and MeMP levels in red blood cells (RBCs) was developed (148). Unlike the metabolite TIMP, the concentrations of TGN and MeMP in RBCs are not influenced by plasma levels of MP. Rather they represent the accumulation of these metabolites over time, reaching steady-state levels within 4 weeks of starting therapy (149-151). In particular, several studies have reported a lack of correlation between the dose/kg (normalised dose) of thiopurine and TGN levels (152-154). However, further studies to assess the relationship between the normalised thiopurine dose and end metabolite concentrations, adjusting for TPMT activity, are warranted.

In patients with leukaemia and those with IBD, research supports the use of metabolite monitoring to guide thiopurine dose adjustments (155-157). Whether or not this is a useful strategy is still being

PhD Thesis Thiopurines in IBD Paul Andrew Blaker determined, since others have reported a low specificity of TGNs in predicting clinical response (158). However, there is still a strong argument for the use of metabolite monitoring to identify poor adherence, thiopurine refractory disease (active disease despite high TGN levels) and to explain some adverse reactions (159, 160).

In patients with IBD a significant negative correlation between erythrocyte TGN levels and disease activity has been observed (161). In this regard, TGN levels are considered therapeutic above 235-260 pmol/ 8x108 RBC, whereas levels greater than 450 pmol/8x108 RBC have been associated with myelotoxicity (64, 157, 162). With regard to MeMP, levels above 5,700 pmol/ 8x108 RBC have been associated with a 3-fold increased risk of hepatotoxicity and levels greater than 11,450 pmol/8x108 RBC have been correlated with myelotoxicity (162, 163). By contrast, in a prospective study no correlation between methylated metabolites and hepatotoxicity was found, necessitating further investigation to confirm these associations (164). Most studies have reported an inverse relationship between TPMT activity and the concentration of TGN and a positive correlation with MeMP levels (161, 165, 166). The relationship between the normalised dose of thiopurine, TPMT activity, thiopurine metabolites and markers of haemopoietic and biochemical toxicity is further explored in Chapter 3.

High-performance liquid chromatography (HPLC) is commonly used to measure the concentrations of TGN and MeMP (167). The acid hydrolysis step incumbent of this assay leads to the degradation of the various thiopurine ribonucleotides and ribosides to the corresponding nucleobases. Therefore the active metabolite TGTP is not measured directly and is reported as the hydrolysed base, which can be produced from several metabolites. Using ion-pair HPLC with fluorescent detection or liquid- chromatography-tandem mass spectrometry, it is possible to measure each of the thioguanine nucleotides and MeTIMP derivatives separately. Consequently it was shown that TGTP represents 80% of the TGN pool, whereas TGDP accounts for 16% and only trace amounts of TGMP are observed (89). In patients with IBD, levels of TGDP greater than 15% of the total TGN pool have been correlated with a lack of response to AZA (89). Therefore, when TGN concentrations are reported using the acid-hydrolysis HPLC method, this may partly explain a lack of treatment efficacy in some patients who appear to have TGNs within the therapeutic range.

Assays quantifying the mono-, di- and triphosphates of thiopurines and their methylated derivatives are therefore attractive; however, they are limited by the poor stability of phosphorylated thiopurine metabolites, which are influenced by storage temperature and processing conditions of blood samples. A prospective study designed to assess the stability of thiopurine metabolites over a week when stored at different temperatures, demonstrated that median TGN concentrations at day 7 decreased significantly to 53% following storage at 22°C and to 90% at 4°C. Similarly, concerning

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

MeMP, median concentrations at day 7 decreased significantly to 55% at ambient temperature and to 86% under refrigeration (168). Therefore instability of thiopurine metabolites proffers a further explanation for the contradictory results of studies correlating metabolite levels with treatment efficacy/toxicity. From a practical point of view, if a significant delay between patient sampling and analysis is anticipated, for example where a blood test is taken on a Friday afternoon, samples should be frozen after measurement of the RBC count. In the Purine Research Laboratory (PRL) it is standard practice to store such samples at -20°C.

Another potential limitation of the standard TGN and MeMP (HPLC) assay is that it reports the concentration of these metabolites in RBCs, which are not the target cells of therapy. Furthermore, since mature erythrocytes lack IMPDH activity they are incapable of forming TGNs, and as such any TGNs present are likely to have been generated in other cells such as myeloid precursors and leucocytes and taken up into RBC’s (147). Comparison of AZA metabolites between neutrophils, lymphocytes and erythrocytes in renal transplant patients, has shown that TGN concentrations are up to 31 times higher in neutrophils as compared to RBCs (169). Interestingly, it was also observed that methylated metabolites were not present in neutrophils. This contradicts previous findings in leukaemic cell lines incubated with MP, which reported that high concentrations of MeMP are produced in leucocytes (170). The reason for these divergent results may reflect differences between in-vitro and in-vivo assays, the concentration of MP at a cellular level and differences in the expression of thiopurine metabolising enzymes between cell types. Future studies should therefore focus on the assessment of thiopurine metabolism in leucocytes derived from patients on established therapy.

Metabolite monitoring for TG therapy has not been investigated as extensively as AZA/MP therapy. Several studies have reported that RBC TGN levels are much higher following treatment with TG as compared to AZA or MP(65, 171). In a study of children with ALL prescribed either MP or TG as maintenance chemotherapy, RBC TGN levels were significantly higher in those receiving TG (172). However, when TGNs were measured in leucocytes from the same patients there were no statistical differences between MP and TG therapy. These opposing observations are likely to reflect differences in the metabolic fate of MP and TG between erythrocytes and the putative target cells, lymphocytes. For example, erythrocytes have an abundant capacity to salvage TG via HPRT to form TGMP (and hence TGTP), however they are unable to form TGMP from MP.

In addition to differences between cellular compartments, there are large variations in TGN levels between individuals, which are not explained by the normalized dose of TG, suggesting the influence of other genetic and non-genetic factors, such as absorption capacity (173). It has been shown that

PhD Thesis Thiopurines in IBD Paul Andrew Blaker the total TGN concentration correlates with the TGTP concentration, the main active metabolite of TG, and to a lesser extent with TGDP levels (174). Further work is therefore required to establish what proportion of RBC TGN content is derived during bone marrow maturation in comparison with the proportion of TGN taken up in the circulation. An understanding of these contributions is needed to derive a therapeutic range for RBC TGNs following treatment with TG. Alternatively, direct measurement of leucocyte TGNs and correlation with clinical response should be considered.

1.8 Thiopurine hypermethylation and the use of low dose thiopurines with allopurinol

Thiopurine metabolite monitoring has revealed that approximately 15-20% of patients preferentially produce methylated metabolites instead of TGNs (175). This is termed thiopurine hypermethylation (or thiopurine shunting) and is an important cause of treatment resistance, hepatotoxicity and other ADRs (154, 162). In this regard, a ratio of MeMP:TGN ≥ 11:1 has been found to correlate with a lack of efficacy in patients with IBD (64, 151, 154). However, other authors have found that a lack of clinical response is only associated with much higher ratios (>20:1 or >30:1), suggesting that this group of patients is poorly defined and that larger studies are needed (176, 177). This is further explored in Chapter 4 of this thesis.

The cause of thiopurine hypermethylation remains incompletely understood. It does not appear to be explained by the dose of the parent drug and indeed dose escalation is observed to lead to a disproportionate rise in the methylated metabolites, often with a paradoxical decrease in the TGN level (64, 178). Thus, the inability to preferentially produce TGN upon dose escalation provides one explanation for AZA/MP resistance in patients with IBD.

Hypermethylation is not usually seen in patients with low or intermediate TPMT activity, hence the traditional view is that it is associated with ultra-high TPMT activity (179, 180). However, recent evidence has shown that there is a poor correlation between TPMT activity and the MeMP:TGN ratio (177, 181). Indeed, only 3% of patients showing preferential methylation have high TPMT activity (≥40 pmol/ h/ mgHb) with the majority demonstrating normal activity. Therefore it is likely that one or more additional mechanisms are responsible for preferential MeMP production. Furthermore, the effect of the normalized dose of thiopurine on this skewed drug metabolism is yet to be explored.

Anecdotal evidence shows that thiopurine hypermethylation can be circumvented by splitting the daily dose of AZA/MP, which is observed to reduce MeMP production whilst maintaining TGN levels. In a retrospective review of 20 patients with IBD and baseline MeMP levels greater than 7000 pmol/ 8x108 RBC, dose-splitting led to a significant decrease in MeMP levels (11,879 vs 5955 pmol/ 8x108

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

RBC; p = < 0.0001), without adversely affecting disease activity or TGN levels (250 vs 227 pmol/ 8x108; p = > 0.05) (182). This finding suggests that changing the concentration of AZA/MP absorbed at any one time influences the thiopurine metabolite ratio. In support of this concept, in-vitro studies have shown that the metabolite profile is dependent on the thiopurine dose (98). In liver cytosol preparations exposed to low dose MP (10 µM), the only metabolite detected was TIMP, whereas at high dose MP (500 µM) a much wider range of metabolites was observed, including; TUA, TX, thioxanthine nucleotide, 8-hydroxy-MP, MeMP, TIMP and TGN. Of interest MeMP was only quantifiable above 50 µM of MP, whereas the formation of TGN appeared less dependent on the substrate concentration. Since metabolic flux through activation and methylation pathways is

1 influenced by the Km of the enzymes involved for their substrates, one explanation for the effect of dose-splitting might be that the absorbed concentration of AZA/MP is substantially below the optimum substrate affinity for TPMT, meaning that activation pathways which have higher enzyme affinities (or a lower Km) may be favoured over methylation.

An alternative strategy for management of thiopurine hypermethylation is combination treatment with allopurinol (100mg once daily), and a reduced dose of AZA/MP (25-33% of the standard daily dose). This is observed to cause a significant reduction in methylated metabolites and an improvement in TGN levels (181). Experience of this strategy was recently reported in 110 patients with IBD, demonstrating that treatment response could be recaptured and hepatotoxicity and other side effects circumvented (181).

1 Km is an inverse measure of the substrates affinity for an enzyme, i.e. a low Km denotes a high substrate affinity.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.9 Pharmacogenomics

Plasma concentrations of drugs can vary more than 600 fold between individuals (183). Gender, age, concomitant therapy, disease severity, hepatic and renal function are well known factors affecting drug metabolism. However it is increasingly recognized that genetic variations in drug metabolizing enzymes, receptors and transport proteins as well as disease susceptibility genes may also contribute and explain up to 40% of inter-individual variation in treatment outcomes (184).

A genetic polymorphism is defined as the existence of two or more allele or sequence variants occurring in a given population. A single nucleotide polymorphism (SNP) describes an exchange, insertion or deletion at a particular locus in the DNA sequence. Coding region SNPs (within an exon) of the DNA sequence are common and occur at a frequency of approximately 1 every 1250 nucleotide bases (185). SNPs that alter an amino acid sequence of a protein (non-synonymous polymorphisms) or the function of regulatory motifs in DNA are anticipated to have the greatest impact on drug metabolism and response (186). The study of DNA sequence variations and their influence on drug response is known as ‘Pharmacogenetics’. With advances in technology which facilitate simultaneous sequencing of multiple genes, rather than one at a time (candidate gene approach), the term ‘Pharmacogenomics’ is more often applied. Pharmacogenomic profiling of patients with IBD receiving thiopurine therapy is anticipated to identify novel markers that predict drug toxicity and response. Ultimately it is hoped that this will allow individualization of treatment, both in regard of dose and the choice of agent.

The following sections review the evidence for non-genetic and genetic influences on thiopurine metabolism, which direct the analyses presented in Chapters 5, 6 and 7.

1.10 Non-genetic factors influencing thiopurine metabolism

With respect to non-genetic influences, several drugs have been noted to interact with thiopurines and these can be divided into those that affect TPMT activity or those that affect other enzymes in the purine salvage pathway.

1.10.1 Drugs influencing TPMT activity

Allopurinol

Elion designed allopurinol as a means of enhancing thiopurine response by inhibiting the XDH mediated subtraction of MP from the TGN bioactivation pathway (187). However, the original studies of combination treatment with allopurinol and MP in childhood leukaemia failed to demonstrate

PhD Thesis Thiopurines in IBD Paul Andrew Blaker additional benefit and rather showed an increase in toxicity (47). This strategy was therefore abandoned and instead allopurinol found its niche in the treatment of gout (47). In 1993 it was reported that co-prescription of AZA with allopurinol improved renal graft survival and optimized thiopurine metabolite profiles (188, 189). More recently interest in combination treatment using low dose AZA/MP and allopurinol in IBD has focused on bypassing thiopurine hypermethylation. However, it has also been used to circumvent other side effects unrelated to this metabolic phenotype (181).

The biochemical mechanism underlying the reduction in MeMP levels following combination treatment with allopurinol is not immediately obvious. Indeed blocking the degradation of MP via the TUA pathway would logically predict a higher substrate concentration available for methylation by TPMT, leading to higher MeMP levels. Since a paradoxical decrease in MeMP is observed the conclusion must be that allopurinol inhibits TPMT activity (147). However, initial in-vitro studies using allopurinol and purified kidney TPMT failed to show evidence of TPMT inhibition (190). The likely biochemical mechanism is discussed in Chapter 8 of this thesis.

5-Aminosalicylates (5-ASAs)

Several studies indicate that 5-ASAs may influence the metabolism of thiopurines (191-193). This is important since as many as 71% of patients with IBD established on thiopurines are co-prescribed 5- ASAs (194). A recent retrospective analysis of 139 patients has shown that administration of concomitant 5-ASA (mesalazine 3 g/ day; n = 45) leads to significantly higher TGN levels in comparison with patients prescribed AZA/MP alone, and is a risk factor for myelotoxicity (odds ratio = 3.45; 95% CI = 1.31-9.04, p = 0.01) (195). Since 5-ASAs have additionally been shown to decrease the production of MeMP and do not appear to influence the phosphorylation of TGDP to TGTP, the interaction with thiopurines is best explained by TPMT inhibition (196). Additional studies are therefore indicated, in particular to determine if 5-ASAs, like allopurinol, may circumvent thiopurine hypermethylation. This is discussed in Chapter 4 of this thesis.

In-vitro, mesalazine, sulphasalazine and olsalazine have all been shown to inhibit TPMT (191). Furthermore, concurrent 5-ASA therapy with AZA significantly increases TUA excretion, consistent with an inhibitory effect on TPMT (197). However, a prospective in-vivo study failed to show that TPMT activity was significantly affected by mesalazine monotherapy during 12 months of treatment (198). One possible explanation for these incongruous results is that the washing steps involved in the ex-vivo erythrocyte TPMT assay removes any TPMT inhibitor present. Alternatively, 5-ASAs may

PhD Thesis Thiopurines in IBD Paul Andrew Blaker have an effect on other enzymes in the thiopurine pathway including efflux transporters, which is an area for future research.

Methotrexate

The synergistic action of MTX in combination with MP has been exploited for the management of acute leukaemias for several decades (70, 199, 200). In this regard low dose MTX with MP or high dose MTX with MP produces greater anti-leukaemic effects (as assessed by decreased circulating leucocyte counts), compared with MP alone (201). Congruent with this, average TGN concentrations are higher in patients receiving combination treatment and correlate with higher MTX- polyglutamate levels (202). This was initially thought to occur as a result of MTX mediated inhibition of XDH. Alternatively, MTX polyglutamates are known to compete with AZA and MP for AOX, forming 7-hydroxy intermediates (203). However, recent in-vitro and in-vivo studies have confirmed that MTX can also bind to TPMT, severely inhibiting enzyme function (204). Therefore reduced degradation of MP may partly explain the observed improvement in treatment efficacy with combination treatment.

Other medications influencing TPMT activity

Administration of diuretics has also been proposed to influence thiopurine metabolism. In-vitro, frusemide, bendroflumethiazide and trichloromethiazide inhibit recombinant human TPMT in both a

(205) mixed and non-competitive manner, with IC50 values of 170 µM, 360 µM and 1 mM respectively . For frusemide at least, the inhibition constants are within the therapeutic range and therefore physiologically relevant. However the significance of this finding in the clinical setting remains to be determined.

Non-steroidal anti-inflammatory drugs (NSAIDs) exhibit pharmacological properties similar to those of 5-ASAs. In-vitro, naproxen, tolfenamic acid and mefenamic acid were found to inhibit TPMT, in a non-competitive manner, at concentrations lower than or comparable to serum concentrations reported in patients receiving such therapies, suggesting a physiologically relevant effect of NSAIDs on thiopurine metabolism (206). Furthermore, infliximab has been shown to transiently increase the concentration of TGN in patients with CD receiving AZA, however the mechanism is unknown (207).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.10.2 Drugs influencing other enzymes in the thiopurine pathway

Mycophenolic acid

Mycophenolic acid (MPA) is a specific inhibitor of IMPDH. In leukaemic cell lines, MeTIMP production, inhibition of DNPS and subsequent cytotoxicity is increased following co-incubation with MP and MPA, as compared to MP alone (208). However, this drug combination has not been extensively trialed in-vivo.

Ribavirin

Ribavirin is also an inhibitor of IMPDH. Severe bone marrow suppression has been reported in patients co-prescribed AZA despite normal TPMT activity (209). Myelotoxicity was associated with elevated MeMP levels with a concomitant decrease in the TGN concentration. This mimics the metabolic phenotype of thiopurine hypermethylation and suggests variation in IMPDH as a candidate to explain this phenomenon. Indeed, a positive correlation between IMPDH activity in leucocytes and MeMP levels in erythrocytes has been reported (210). However, there was a lack of correlation with erythrocyte TGN concentrations, suggesting that the metabolism involved is complex.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.11.1 Genetic factors influencing thiopurine metabolism

Figure 1.5 Thiopurine pathway showing factors influencing production of end-metaboiltes

Italics, enzymes and transporters predicted to influence thiopurine metabolism.

1.11.1 Glutathione-S-transferases

The cytosolic glutathione-S-transferases (GST), GST-M1, P1 and T1, which are abundant in the liver and intestine, are responsible for over 90% of the conversion of AZA to MP by neutrophilic substitution involving glutathione (GSH) (211). Several of these GSTs demonstrate polymorphic variation and may explain some of the inter-individual variation in thiopurine metabolism. Three different polymorphisms have been described at the GST-M1 locus (chromosome 1p13.3), the most important of which is associated with a partial deletion resulting in complete absence of enzyme activity (212). Of interest, the GST-M1 null genotype, which is found in approximately 50% of Caucasians, appears protective against AZA-induced lymphopaenia and adverse events (213). This is likely to be due to reduced bioconversion of AZA to MP, and consequently to the cytotoxic nucleotide derivatives. Alternatively, decreased thiolysis of AZA to MP will attenuate cellular GSH

PhD Thesis Thiopurines in IBD Paul Andrew Blaker depletion and thereby oxidative stress and mitochondrial injury. This may be of relevance in IBD, since intestinal GSH synthesis is noted to be impaired, particularly at sites of active inflammation (214) A role for GST-M1 as a regulator of MAP kinase pathways, which are involved in cellular survival and death signals has also been described (215). Therefore, in patients with wildtype GST-M1 genotypes, predicted to be at higher risk of AZA induced adverse events, there may be an argument for using MP instead of AZA. This may also explain the tolerance to MP in up to 60% of IBD patients intolerant of AZA (216, 217).

1.11.2 Thiopurine-S-methyltransferase

TPMT is a cytoplasmic enzyme that preferentially catalyzes the S-methylation of aromatic and heterocyclic sulfhydryl compounds. However, the endogenous function of human TPMT, which is ubiquitously expressed and conserved among species from bacteria to mammals is unknown. The bacterial homologues convert selenium- and tellurium-containing compounds to less toxic methylated derivatives using SAM (218). It is speculated that the human enzyme might also detoxify these metabolically important, but potentially poisonous metals (219).

In 1980, inherited variation in TPMT activity was presented as a factor to explain individual differences in thiopurine drug response (220). Large population studies have since shown that TPMT has a trimodal distribution of activity, with 89-94% of individuals having high activity, 6-11% an intermediate activity and 0.3% low or undetectable activity (221) (figure 1.6). In a study of 106 patients prescribed AZA for IBD, 50% with intermediate TPMT activity were intolerant of AZA, compared to only 16% with normal activity, resulting in a significant association between AZA toxicity and intermediate enzyme activity (179). This was confirmed in a prospective evaluation of 207 patients which reported that the presence of a heterozygous genotype is strongly predictive of adverse events (79% heterozygous vs. 35% wild-type TPMT) (150). Pre-treatment TPMT phenotyping is therefore recommended to rationalize the starting dose of AZA/MP. Patients with intermediate activity should be prescribed 50% of the standard daily dose and those with homozygous activity should avoid thiopurines, although on occasion very low doses (around 5% of the standard dose) may be tolerated (table 1.1).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Figure 1.6 Trimodal distribution of RBC TPMT activity in the general population

Diagram modified from Sanderson et al. Ann Clin Biochem, 2004; 41: 294 – 302 (222).

Table 1.1 Dosing strategy for AZA/MP according to RBC TPMT activity status

RBC TPMT activity Pre-treatment RBC TPMT Recommended initial dose status (pmol/ h/ mgHb)

Avoid or if using AZA consider Zero 0.1 – 0.2 mg/ kg < 10 Homozygous TPMT deficiency Titrate dose according to TGN at 4 weeks

AZA dose at 1 – 1.5 mg/ kg Intermediate MP dose at 0.5 – 0.75 mg/ kg 11 – 25 Heterozygous TPMT deficiency Titrate dose according to TGN at 4 weeks

AZA dose at 2 – 2.5 mg/ kg Normal MP dose at 1 – 1.5 mg/ kg >26 TPMT wildtype Titrate dose according to TGN at 4 weeks

RBC TPMT activity ranges based on recommendations from the Purine Research Laboratory.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

The TPMT gene, which is located on chromosome 6p22.3 is approximately 34Kb in length with 9 exons, and encodes a protein of 245 amino acids (223). Exon 2 is not uniformly represented in mRNA, indicating that the gene is subject to alternative splicing (224, 225). A processed pseudo-gene, with 96% sequence homology to TPMT cDNA, has been cloned and mapped to chromosome 18q21.1 (226).

Thirty-one sequence variations in the coding and splice site regions of the TPMT gene which alter enzyme activity have been described (227, 228). However, 80-95% of all cases of null TPMT activity are related to just three variants (TPMT*2, TPMT*3A, TPMT*3C). TPMT*2 is a non-synonymous single nucleotide polymorphism (nsSNP) in exon 5 (G238C, Ala80Pro) (229). TPMT*3C (A719G, Tyr240Cys) is located in exon 9. On this genetic background, a second mutation TPMT*3B (G460A, Ala154Thr) has occurred giving rise to the variant allele TPMT*3A. In Caucasians the allele frequencies of TPMT*2, *3A and *3C are 0.17%, 4.5% and 0.4% respectively (230, 231). The proteins encoded by these genetic variants are unstable and rapidly degraded, leading to reduced enzyme activity.

TPMT activity is usually reported in RBCs, since this correlates with the enzyme activity in other cellular compartments including the liver, kidneys and lymphocytes (232-234). However, little work has been completed to determine the correlation between RBC and intestinal TPMT activity. This is important since the expression of TPMT may differ between compartments. Furthermore, it is increasingly recognised that the intestine has the ability to metabolise drugs involving both phase 1 and phase 2 reactions (235). It is therefore of interest that a master trans-regulator of TPMT activity, Krupple-like factor-14 (KLF-14), is expressed in the intestine but is not found in the human adult liver or in lymphoblasts (236, 237). Balance studies to assess the proportion of thiopurine methylation that occurs in the intestine, liver, circulation and bone marrow are therefore indicated.

The overall intra-individual variation in erythrocyte TPMT activity is approximately 7% (238). In childhood leukaemias it has been reported that RBC TPMT activity increases (by a median of 34%) following treatment with MP and decreases again following cessation of therapy (239). However, induction of TPMT activity has not been confirmed in IBD patients (240). Therefore the rise in TPMT levels in patients with leukaemia may be an epiphenomenon due to a decrease in RBC age. This is consistent with previous observations that TPMT activity is higher in patients with a young RBC population (241, 242).

Besides genetic variants in coding and splice site regions, polymorphisms that influence transcription and mRNA stability may affect TPMT gene expression. The promoter region of the TPMT gene contains a variable number of tandem repeats (VNTRs), which include GC-rich blocks that act as putative binding sites for a number of transcription factors including Sp1, Sp3, KLF-1 and KLF-14 (243,

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

244). The VNTR region architecture is defined by three types of repeat (A, B and C) that differ in length and nucleotide sequence. Repeats are consistently arranged in the same order: A is followed by B and then by C, with no intervening sequences. The number of A and B repeats varies, whereas only 1 copy of the C repeat is present (245). The most frequent VNTR alleles in Caucasians are VNTR*4a (A2BC), VNTR*5a (A2B2C) and VNTR*6a (A2B3C), which account for greater than 90% of the variation (246).

The number and intrinsic nucleotide pattern of the VNTRs has been inversely correlated with TPMT activity, although this finding is not supported by more recent studies (247, 248). Furthermore, the A repeat is reported to have a negative effect on TPMT gene transcription, whereas a positive regulatory element immediately upstream of the VNTR region appears indispensable for transcription (246). Interestingly, a recent study has shown that following treatment with MP, binding of newly recruited protein complexes to the TPMT promoter affects gene transcription, suggesting that MP may influence TPMT expression (245). The VNTR region of the TPMT promoter may therefore prove a useful pharmacogenetic marker to individualize thiopurine treatment.

1.11.3 S-adenosylmethionine

In Caucasians, the concordance between TPMT genotype and phenotype in the wild-type and homozygous ranges is high (93-100%). However, it is considerably lower in heterozygotes (53- 100%), suggesting that factors other than TPMT genotype may affect enzyme activity (249). One such factor is SAM, which stabilizes the conformational structure of TPMT by binding into its active site, protecting it from ubiquitylation and degradation (250). Therefore the intracellular bioavailability of SAM may modulate in-vivo TPMT activity and thereby influence the formation of thiopurine metabolites. Extrapolating this hypothesis, endogenous metabolites (e.g. folates, methionine, homocystine, ATP etc.) and enzymes participating in the biosynthesis of SAM may also indirectly influence TPMT activity (figure 1.7).

The relevance of SAM in thiopurine metabolism has been confirmed by several in-vitro studies. Firstly, in a human malignant cell line, SAM recycling via the methionine cycle was attenuated following the addition of MP or MeMP-rib (251, 252). It was proposed that this results from inhibition of DNPS through the action of MeTIMP, which depletes endogenous adenine nucleotide pools, thereby limiting the ATP-dependent synthesis of SAM from methionine (252, 253). Secondly, MP mediated SAM depletion is observed to cause DNA hypomethylation (144). Finally, exogenous SAM can prevent MP-induced programmed cell death via a reduction in intracellular TGN and MeTIMP levels (251).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Figure 1.7 S-adenosylmethionine metabolism and methylation of mercaptopurine via TPMT

SAM is consumed by TPMT which transfers a methyl group to MP. The metabolism of SAM is closely related to homocysteine (HCY), remethylation and methionine (Met) cycles, the folate pathway, transsulfuration and polyamine synthesis. Abbreviations; 5,10-Me-THF, 5,10- methylenetetrahydrofolate; 5-Me-THF, 5-methyltetrahydrofolate; THF, tetrahydrofolate; MS, methionine synthase; MTHFR, 5,10-methylenetetrahydrofolate reductase; CBS, cystathionine-β- synthase; GSH, glutathione; SAHH, S-adenosylhomocysteine hydrolase; MAT, methionine adenosyltransferase; MTA, 5’-methylthioadenosine; MTAP, 5’methylthioadenosine phosphorylase; SAM decarboxy, SAM decarboxylase; dUMP,deoxyuridine monophosphate; dTMP, deoxyuridine triphosphate; TYMS, thymidylate synthetase. Dotted red line - theoretical inhibition of TPMT by SAH.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

The most compelling evidence of SAM metabolism on TPMT stabilization is provided by two in-vivo studies investigating the effect of MTHFR polymorphisms on TPMT activity (254, 255). MTHFR, is the rate determining enzyme of the folate cycle, with decreased activity predicting lower serum folate levels, reduced SAM and increased SAH levels (256). The MTHFR gene is polymorphic and two common variants (677C>T and 1298A>C) are associated with reduced enzyme activity (257). Arenas et al, investigated the correlation between MTHFR genotypes and TPMT activity in healthy individuals, demonstrating that the MTHFR 677TT genotype is associated with an intermediate level of TPMT activity, in individuals with a wildtype TPMT genotype (254). In a later study on treatment with MP for ALL, 82% of patients carrying mutations in both TPMT and MTHFR experienced haemotoxicity, whereas haematotoxic events were significantly less frequent (4%) in patients with wildtype TPMT and MTHFR genotypes (255).

1.11.4 Xanthine oxidase / dehydrogenase

Xanthine oxidoreductase is a homodimer of approximately 300kD, which contains a molybdenum co- factor (Mo-co) and exists in two inter-convertible forms designated xanthine dehydrogenase (XDH) and xanthine oxidase (XO), dependent on the redox state of the enzyme. Its endogenous function is to catalyse the terminal two reactions of purine degradation; oxidation of hypoxanthine to xanthine and the subsequent oxidation of xanthine to uric acid. Purine oxidation occurs at the Mo-co site,

+ whereas nicotinamide adenine dinucleotide (NAD ) and oxygen (O2) reduction occur at a separate flavin adenine dinucleotide (FAD) site. Two iron-sulfur clusters provide the conduit for electron transfer between the two centres (258). The dehydrogenase form (XDH) is believed to be the predominant form in-vivo, where substrate-derived electrons reduce NAD+ to NADH. However, during inflammatory conditions, oxidation of cysteine residues and limited proteolysis converts XDH to XO (259). In this state enzyme affinity for oxygen is significantly increased, resulting in the transfer

• (260) of electrons from O2 generating both superoxide (O2 ⁻) and hydrogen peroxide (H2O2) . Uncontrolled increases in the steady-state concentrations of these oxidants leads to free radical- mediated chain reactions, which indiscriminately target DNA, proteins, lipids and polysaccharides (261)

Supposition that the production of reactive oxygen species (ROS) by XO is relevant to the development of thiopurine induced toxicity is supported by in-vitro studies (262). Rat hepatocytes cultured with therapeutic concentrations of AZA or MP demonstrated reduced viability in comparison with control media. This effect was blocked by the addition of allopurinol, implicating a role for XO, and also with Trolox, a strong anti-oxidant, suggesting the attenuation of ROS. The authors hypothesized that high XO activity and subsequent production of ROS may be responsible

PhD Thesis Thiopurines in IBD Paul Andrew Blaker for thiopurine-induced liver injury. An alternative mechanism was postulated by a study on human hepatocytes and hepatoma cell lines, which demonstrated that cellular damage occurs as a result of ATP depletion and mitochondrial injury (263). In this regard allopurinol may protect against hepatocyte damage through preservation of ATP pools, as a result of increases in hypoxanthine levels and promotion of the purine salvage pathway (264). Equally, allopurinol may preserve ATP pools through indirect inhibition of MeTIMP formation, which would otherwise inhibit DNPS, and hence it supports the production of SAM and GSH, both of which are important anti-oxidants. However, the situation is complex and in other models of liver injury allopurinol has been shown to attenuate the production of transforming growth factor-beta, NF-kB, TNF-α, interleukine-1β and interleukine-6 and increase interleukine-10 levels (265).

XDH competes with TPMT for the degradation of MP. Consequently, low XDH activity would be predicted to cause high TGN levels with dose-dependent toxicity and vice-versa. In this regard complete XDH deficiency (classic xanthinuria type 1) has been shown to cause severe toxicity with full dose AZA (266). Meanwhile, high XDH activity has been proposed as a cause of treatment non- response in a patient with autoimmune pancreatitis, with undetectable levels of TGN and MeMP that were reversed upon treatment with allopurinol (267). However, the influence of XDH activity in the normal range on the bioavailability and clinical efficacy of thiopurines remains largely unknown. Measurements of functional XDH activity, using in-vivo caffeine-based assays, have shown that there is little inter-individual or inter-ethnic variation of enzyme activity in the normal population (268). However, such assays may be biased by the fact that caffeine can undergo hydroxylation by enzymes other than XDH. Therefore the effect of variation in XDH activity on thiopurine metabolism may be underestimated.

Direct measurement of XDH activity in fresh human liver autopsy samples, demonstrates a four-fold inter-individual variation, with 20% of men and 27% of women having low enzyme activity (269). Since thiopurine hypermethylation occurs with a similar frequency to low XDH activity, this may be relevant to the mechanism involved, with reduced degradation of MP predicting higher concentrations of substrate for methylation via TPMT. Therefore the effect of polymorphic variation in XDH on AZA/MP metabolism, particularly with respect to thiopurine hypermethylation, requires further investigation. This is explored in Chapter 5 of this thesis.

A study on the in-vitro activity of XDH using TX as a substrate, has shown that 8 SNPs are associated with attenuated enzyme activity (p.Arg149Cys, p.Arg607Gln, p.Thr623Ile, p.Ile703Val, p.Asn909Lys, p.Thr910Lys, p.Pro1150Arg, p.Cys1318Tyr) (270). Furthermore, in human hepatoma cell lines, polymorphic variation in the XDH promoter (-1756 C > T) has been linked with reduced

PhD Thesis Thiopurines in IBD Paul Andrew Blaker transcriptional activity (271). By inference, these polymorphisms may also be important in the response to thiopurines, although in-vivo studies are currently lacking.

Recently, a prospective study by Smith et al reported that polymorphic variation in XDH, molybdenum co-factor sulfurase (MOCOS, an enzyme that sulfurates the molybdenum co-factor of XDH and AOX1), and AOX1, may influence AZA treatment outcomes in patients with IBD (n = 192). In this regard, XDH c.837C >T (p.Val279Val) and MOCOS c.2107A > C (p.Asn703His), demonstrated a weak protective effect against ADRs, which was stronger where these SNPs coincided (272). Whereas AOX1 c.3404A > G (p.Asn1135Ser) predicted a lack of response to AZA. Importantly, when this information was combined with TPMT activity, it allowed stratification of a patient’s chance of responding to AZA, ranging from 86% in patients where both markers were favourable to 33% where they were unfavourable.

Since replication is very important in reaching consensus in genetic studies, Kurzawski et al using a retrospective cohort of kidney transplant patients treated with AZA (n = 156) attempted to confirm the earlier findings of Smith et al (273). It was shown that carriers of the AOX1 c.3404A > G mutation required significantly higher doses of AZA, in comparison with wildtype homozygote patients. Accepting the differences in study design, since the dose of AZA was modified based upon treatment efficacy, this observation is in keeping with the non-responder status reported by Smith et al. Unfortunately, different definitions of ADRs were used between the studies and therefore it was not possible to confirm the associations with the polymorphisms in XDH and MOCOS. However, it was reported that MOCOS c.2107A > C heterozygote and homozygote recessive patients required significantly lower doses of AZA in the course of treatment in comparison with wildtype homozygotes, consistent with reduced degradation of MP to TUA.

1.11.5 Hypoxanthine-guanine phosphoribosyltransferase

HPRT catalyzes the first step in the conversion of both MP and TG to TGN and is a key enzyme in the purine salvage pathway. The structural gene for HPRT1 is on the X-chromosome, and mutations at this locus are, therefore, only fully expressed in males. Patients with Lesch-Nyhan syndrome, who lack HPRT activity, are resistant to AZA presumably due to a lack of TGN production (274). In blast cells from children with ALL, 10 fold differences in HPRT activity have been observed, with a poorer prognosis seen in patients with HPRT activity below the median range (275). In IBD patients prescribed AZA/MP, high HPRT activity was associated with an increased risk of leucopenia, which correlated with elevated TGN levels (276). Furthermore in cultured mammalian cells, deletion and point mutations in HPRT1 have been shown to confer resistance to both MP and TG (277).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

In other studies, thiopurine therapy has been shown to increase the mutation frequency in HPRT1 and hence it may modulate enzyme activity (278). Furthermore, in rat small intestine, administration of MP has been shown to decrease HPRT1 mRNA levels, suggesting transcriptional regulation of TIMP production; however these findings have yet to be replicated in humans (279).

1.11.6 Inosine monophosphate dehydrogenase

IMPDH has the lowest enzyme activity in the purine salvage pathway and is located at the branch point between adenine and guanine synthesis. As such it is proposed as the rate limiting step in AZA/MP drug metabolism (280). Accordingly, IMPDH activity would be expected to correlate directly with TGN (positive correlation) and MeTIMP levels (negative correlation). Hence IMPDH activity may be of significance in the development of thiopurine hypermethylation.

IMPDH is present in two isoforms encoded by two different genes. IMPDH1 is located on chromosome 7 (7q31.3) and IMPDH2 is on chromosome 3 (3q21.2). Both genes contain 14 highly conserved exons and encode proteins containing 514 amino acids that share 84% sequence homology, with similar substrate affinities and catalytic activities (281). Unlike TPMT, IMPDH activity is normally distributed and is similar in both sexes with an intra-individual variability of < 25% (282). In general IMPDH1 mRNA and protein expression is lower than IMPDH2 expression, except in peripheral blood mononuclear cells (283).

IMPDH1 activity is regulated in a tissue specific manner by 3 different promoters (P1, P2 and P3), of which the highest enzyme activity is associated with the P3 promoter. In comparison, IMPDH2 is controlled by a single promoter that responds more specifically to growth stimuli (284). An insertion in the P3 promoter of IMPDH1 has previously been reported in a patient on AZA demonstrating thiopurine hypermethylation (285). However, such mutations are rare and therefore unlikely to explain much of the variability in thiopurine metabolism.

A negative correlation between IMPDH activity in leucocytes and dose normalized MeMP levels in erythrocytes has been reported (210). However, there was a lack of correlation with erythrocyte TGN concentrations. Further studies are therefore indicated to test the association between IMPDH activity and thiopurine metabolites in the target cells of therapy.

1.11.7 Inosine triphosphate pyrophosphohydrolase

ITPase appears to have a putative role in preventing the accumulation of potentially harmful rogue nucleotides, such as inosine triphosphate (ITP) or deoxy-ITP, which would otherwise be incorporated into RNA and DNA or affect cell signalling (286). Indeed, knock-out of the inosine triphosphatase gene

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

(ITPA) in mice, leads to an accumulation of ITP in the nucleotide pool, which is associated with foetal death in-utero (>50%) and multiple birth defects (287).

In humans, red cell ITPase exhibits polymorphic activity that is genetically determined. Low enzyme activity is associated with the accumulation of ITP in RBCs, which is clinically benign (288). In Caucasian populations, two allelic variants in the ITPA gene (c.94C > A and g.IVS2+21A > C) have been associated with decreased enzyme activity (286). ITPase activity is abolished in patients homozygous for the c.94C > A transversion, whereas it is reduced to 22.5% in heterozygotes. The effect of the ITPA IVS2 +21A > C mutation is less severe, with heterozygotes exhibiting ITPase activity 60% of expected (286). The reason for the reduction in enzyme activity was previously unclear, however recent work completed in the PRL has shown that the c.94 C > A and g.IVS2+21 A > C sequence variants contribute to missplicing of the ITPA gene (289-291).

In the context of thiopurine metabolism, ITPase deficiency is anticipated to have two effects. Firstly, it predicts reduced degradation of TITP back to TIMP, which as a substrate for IMPDH, would limit the formation of TGNs. Secondly, trapping of TIDP and TITP would provide a greater substrate concentration for methylation via TPMT; hence ITPase deficiency may have relevance to the occurrence of thiopurine hypermethylation. ITPase is therefore a good candidate to further explain individual variation in thiopurine metabolism and the development of toxicity.

The original examination of polymorphic variation in ITPA on the incidence of thiopurine induced ADRs by Marinaki et al, suggested an association between ITPA c.94C > A and rash, pancreatitis and flu-like symptoms (292, 293). Subsequently, in a prospective cohort of 71 patients with CD prescribed AZA, ITPA c.94C > A was associated with early treatment failures due to an increase in ADRs (294). In a larger cohort, Ansari et al confirmed the correlation between ITPA c.94C > A and flu-like symptoms, although the association with treatment withdrawals and other ADRs was not replicated (150).

The association between ITPA c.94C > A and ADRs, however, is not universally reported. In a retrospective analysis comparing treatment response at 6 months, which included 73 cases of withdrawal from AZA due to ADRs and 74 cases of AZA tolerance as controls, no associations were seen between ITPA c.94C > A and the development of ADRs, including rash, pancreatitis and flu-like symptoms (295). Similarly, in a prospective cohort of 60 patients with IBD treated with standard doses of AZA or MP, there was no association observed between the ITPA c.94A > C polymorphism and overall ADRs (164).

Studies investigating a link between ITPA c.94A > C variant alleles and myelotoxicity have also provided conflicting results (296-300). In the largest of these studies, Palmieri et al using a multi-centre

PhD Thesis Thiopurines in IBD Paul Andrew Blaker retrospective cohort of 422 patients with IBD treated with AZA or MP, failed to show a significant relationship between the presence of ITPA c.94A > C and low white cell counts (300). Conversely, a significant association was found in a retrospective study from the Netherlands of 262 patients with IBD treated with AZA, which reported an odds ratio of 3.5 for the development of leucopaenia (296).

If ITPase deficiency is associated with thiopurine induced myelotoxicity, the mechanism may occur independently of TGNs. In a study investigating the effect of ITPA polymorphisms on MP metabolites and treatment outcomes in ALL, there were no differences in TGN levels between patients with and without non-functional ITPA alleles, despite a significantly higher probability of severe febrile neutropaenia in patients with variant ITPA alleles (301). Meanwhile, MeMP nucleotide levels were significantly higher in those with the ITPA c.94A > C polymorphism and wildtype TPMT genotype. Therefore the excess of myelotoxicity observed in some studies may relate to inhibition of DNPS by MeMPRs. Alternatively, in-vitro studies suggest that accumulation of TITP may inhibit the activity of RNA polymerases, and mediate cytotoxicity by acting as a competitive inhibitor of these enzymes at the guanosine nucleotide binding sites (302).

The only meta-analysis of polymorphic variations in ITPA in thiopurine treated patients, failed to find an association between all ADRs, myelotoxicity, hepatotoxicity or pancreatitis (303). However, this was published in 2007 and more recent data is now available. Moreover, many of the negative studies that were included in this analysis were from small retrospective cohorts, with inherent recruitment bias. Therefore, further large prospective studies are needed to define the role of variation in ITPase activity on thiopurine metabolism.

1.11.8 Guanosine monophosphate synthase and guanosine monophosphate reductase

GMPS (GMPS chromosome 3q24) catalyzes the amination (addition of an amine group) of TXMP to form TGMP in the presence of glutamine and ATP, and is expressed in bone marrow, leucocytes, RBCs and hepatocytes. In-vitro MP appears to influence the activity of GMPS. Incubation of WEHI- 3b cells with increasing doses of MP is accompanied by a rise in the concentration of TIMP and TXMP, but surprisingly, a reduction in the concentrations of TGMP, TGDP and TGTP (170). The mechanism remains unclear but may be due to decreased synthesis of ATP, which will reduce GMPS activity. Furthermore, cells exhibiting reduced expression of GMPS appear resistant to MP (304). These data support a role for genetic variation in GMPS to explain treatment non-response to AZA/MP, however in-vivo studies are currently lacking.

Guanine monophosphate reductase (GMPR) catalyzes the nicotinamide adenine dinucleotide phosphate (NADPH) dependent deamination of guanine monophosphate to form inosine

PhD Thesis Thiopurines in IBD Paul Andrew Blaker monophosphate. GMPR is present in both RBCs and mononuclear cells and opposes the action of IMPDH and GMPS. Theoretically, reduced GMPR activity predicts higher concentrations of TGMP; however, studies on the role of GMPR on thiopurine metabolism are lacking. In Leishmania donovani, allopurinol has a weak inhibitory effect on GMPR, which may provide a further explanation for the observed increase in TGN concentrations following concomitant treatment with AZA/MP (305).

1.11.9 Purine nucleoside phosphorylase and cytoplasmic 5’nucleotidase

PNP deficiency blocks the breakdown of purine nucleosides and very low enzyme levels are characterized by neuropathology and T-cell immunodeficiency. Hypothetically reduced PNP activity predicts higher concentrations of both MP riboside and TG riboside, their methylated derivatives, and the corresponding thiopurine nucleotides. However, the effect of reduced PNP activity on thiopurine metabolism remains undetermined.

5’nucleotidase, which is present in various forms in the cytoplasm (CNI, CNIA, CNIII, dNTI), mitochondria (dCNII) and cell membrane (NT5E or CD73+), is involved in the dephosphorylation of thiopurine nucleotides. In patients with low NT5C activity, treatment with AZA/MP results in the accumulation of thio-nucleotides and methyl-thio-nucleotides (97). This may represent one explanation for AZA/MP induced myelotoxicity in patients with normal TPMT activity (306). Conversely, in patients with acute lymphoblastic leukaemia (ALL), high 5’nucleotidase activity has been associated with resistance to thiopurines (307).

1.11.10 Thiopurine importer pumps

Cellular influx and efflux of thiopurine metabolites is mediated by a number of different transporters. Variation in the expression and activity of these proteins is therefore predicted to influence intracellular metabolite concentrations. Indeed resistance to nucleoside analogues as a result of defective nucleoside transporter-mediated uptake is already well described (308-310). These transporters are divided into two main classes, equilibrative and concentrative, based on their mechanism of action (311). The human equilibrative family (SLC29; genes SLC29A1-4) of proteins contains four members, which mediate the net flux of nucleoside molecules across the plasma membrane and down a concentration gradient. Of these, ENT1 and ENT2 have been most extensively studied and are shown to have a broad range of substrate specificities for purine and pyrimidine nucleosides, whereas ENT2 (and to a lesser extent ENT1) can also transport nucleobases (312, 313). The concentrative nucleoside transporter family (SLC28; genes SLC28A1-3) describes three subtypes of Na+-dependent transporters; CNT1 predominantly transports pyrimidine nucleosides,

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

CNT2 has a preference for purine nucleosides, and CNT3 is capable of transporting both pyrimidine and purine nucleosides across plasma membranes (314).

A role for ENT2 and CNT3 in the transport of thiopurines is evidenced by in-vitro studies. In a human T-lymphoblastic cell line (MOLT-4), cells resistant to both MP and TG, exhibited a marked reduction in cellular uptake of MP (70% and 80% respectively) (84). Furthermore, the addition of small interfering RNAs designed to silence the expression of ENT2 and CNT3, was accompanied by reduced transport of MP, as well as its cytocidal effect independent of HPRT, TPMT and IMPDH enzyme activity. This has been confirmed in another study where resistance to MP was mediated by down- regulation of ENT1, CNT2 and CNT3 (85).

The SLC28A1-3 and SLC29A1-4 genes show infrequent genetic variation in comparison with many other transporter gene families (315, 316). To date no studies have assessed the relevance of these polymorphisms in the context of thiopurine metabolism. However, a variant in SLC28A1, p.V189I has shown reduced affinity for the anticancer nucleoside gemcitabine, whereas the SLC28A2 variants p.F355S and p.E385K have shown altered nucleoside drug selectively and decreased overall transporter activity respectively (317, 318).

1.11.11 Thiopurine exporter pumps

The ATP-binding cassette transporters (ABC transporters) are transmembrane proteins involved in the energy-dependent import and export of a wide variety of substrates, including nucleotides and xenobiotics, across different cellular membranes. Work in the 1970’s and 1980’s revealed that overexpression of ABC exporters is associated with a multi-drug resistance phenotype in tumours (319-321). Of these the best characterised is ABCB1 (otherwise known as multi-drug resistance protein- 1, MDR-1), which is highly expressed at the apical surface of epithelial cells (colon, small intestine, pancreatic ductules, bile ductules, kidney proximal tubules and the adrenal gland) and can interact with hundreds of generally nonpolar, weakly amphipathic compounds, including chemotherapeutic agents and steroids. There is now strong evidence linking ABCB1 expression with poor response to chemotherapy in acute myeloid leukaemia (AML) and to corticosteroid resistance in UC (322-324). More recently, polymorphic variation in ABCB1 (p.Ala893Ser) has been linked with a lack of response to AZA in CD and a poorer prognosis in ALL (325, 326). It was suggested that ABCB1 p.Ala893Ser variants may exhibit enhanced activity, attenuating treatment efficacy by increasing the cellular efflux of AZA metabolites. However, other studies conclude that thiopurines are poor substrates for ABCB1 and therefore additional mechanisms may be involved (327, 328).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Additional pumps known to be involved in the efflux of thiopurine metabolites include ABCC4 and ABCC5, which are capable of carrying cyclic nucleotides. There is also emerging evidence to support roles for ABCB5 and ABCG2 (329, 330). With respect to ABCC4, up-regulation of ABCC4 was proposed as a cause of resistance to MP in an ALL cell line (85). This was confirmed in HEK293 cells where high levels of ABCC4 and ABCC5 expression were associated with attenuation of MP-induced cytotoxicity (331). In cells transfected with ABCC5, this was shown to be mediated by efflux of TIMP; however, this only occurred at high intracellular TIMP concentrations, questioning the relevance of this finding in- vivo (108). It was also demonstrated that MeTIMP was a substrate for both ABCC4 and ABCC5, a factor that may be integral to the mechanism of thiopurine hypermethylation (108).

Further evidence for the involvement of ABCC4 in thiopurine metabolism is provided by a murine ABCC4 knock-out (KO) model (332). In ABCC4 KO mice exposed to MP or MeMP-rib, bone marrow toxicity (and accumulation of TGNs) was significantly greater in comparison with wildtype mice, which were otherwise phenotypically identical (333). Moreover, treatment of wildtype mice with the ABBC4 inhibitor MK571 abolished this difference.

Since both ABCC4 and ABCC5 are subject to genetic polymorphism, several groups have investigated the effect of functional variants on response to thiopurines. In a cohort of 235 Japanese patients with IBD, the ABCC4 p.E857K variant was associated with higher TGN concentrations and lower white blood cell (WBC) counts (334). Ansari et al also demonstrated that tagging SNPs T-1393C and A934C in ABCC4 were associated with treatment outcomes and toxicity in children with ALL, although this was not replicated in a cohort of adults with ALL (335, 336). Further work to determine the effect of polymorphic variation in ABCC4 and ABCC5 on thiopurine metabolism and treatment outcomes is therefore indicated.

A recent abstract presented by Smith et al, implicates a role for ABCB5 (or MDR-5), in mediating clinical response to thiopurines in IBD (329). ABCB5 is a p-glycoprotein, which shares sequence homology with ABCB1 and has been linked with resistance to doxorubicin in melanoma cell lines (337). It was shown that the ABCB5 c.343A > G variant was associated with a lack of clinical response to thiopurine treatment and with lower TGN levels. However the effect of this polymorphism on MeMP levels and its relevance to thiopurine hypermethylation was not explored. This is examined in Chapter 5 of this thesis.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

1.12 Aims of the thesis

The overall aim of this thesis is to identify novel strategies and biomarkers that can be used to personalise thiopurine therapy in patients with IBD. In particular, it focuses on thiopurine hypermethylation, which is likely to represent our greatest opportunity to optimise treatment. In Chapters 3 and 4, work characterising the influence of thiopurine hypermethylation on treatment outcomes is presented. Chapter 5 explores the potential mechanism of thiopurine hypermethylation by seeking associations with frequently occurring SNPs in key genes involved in thiopurine metabolism. Chapters 6 and 7 expand upon this using an exome microarray, to allow the identification of novel markers and whole pathway analyses to explain thiopurine hypermethylation and other adverse events associated with thiopurine therapy. Chapter 8 presents the biochemical mechanism explaining the interaction between thiopurines and allopurinol, which is exploited to circumvent thiopurine hypermethylation.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Chapter Two: Materials and methods

2.1 Patient recruitment

2.1.1 Thiopurine hypermethylation clinical studies (Chapters 3 and 4)

Patients who had RBC thiopurine metabolites measured to monitor AZA or MP treatment were identified from the electronic patient records system at Guy’s and St Thomas’ Hospitals (GSTT) and from databases maintained by the Purine Research Laboratory (PRL). Only patients attending the dedicated IBD clinics at GSTT with a confirmed diagnosis of IBD were eligible for inclusion. In the majority of patients data on sequential thiopurine metabolite levels were available. Patients receiving thioguanine or low dose AZA/MP with allopurinol co-treatment were excluded. In each case, clinical records and results were reviewed retrospectively to record data on demographics, type of IBD, pre-treatment RBC TPMT activity, thiopurine type and weight-normalised dose, haematological (haemoglobin (Hb), mean cell volume (MCV), mean corpuscular haemoglobin (MCH), platelet count, white blood cell count, neutrophil count, lymphocyte count) and biochemical (creatinine, alanine transaminase (ALT), alkaline phosphatase (ALP)) parameters taken at the same time as the thiopurine metabolite measurements as part of standard treatment monitoring.

From the same databases, a second cohort of patients with IBD receiving treatment with AZA/MP, who were naïve to anti-TNF-α antibody therapy, were identified and used in a case-control analysis to further determine the effect of thiopurine hypermethylation on clinical outcomes. Thiopurine hypermethylation was defined as an average MeMP : TGN ratio of > 11:1, based on at least 2 metabolite profiles taken after 12 weeks of therapy. In addition to the above information, case- notes were examined to determine treatment response and the development of ADRs during the first 12 months of therapy.

2.1.2 Real-time PCR genotyping (Chapter 5)

Patients recruited to the IBD Pharmacogenetics (Research and Ethics Committee reference, 12/YH/0172; research and development reference, RJ112/N179) and the Pharmacogenetics of AZA studies (MREC, 00/1/33 and LREC, 06/Q0707/84) at GSTT were selected and separated into two groups according to the presence or absence of thiopurine hypermethylation. Inclusion criteria were as follows; i) Caucasian adult patients with a confirmed diagnosis of IBD, ii) receiving AZA/MP therapy for at least 12 weeks, iii) thiopurine metabolite profiles demonstrating adherence to therapy, and iv) RBC TPMT activity consistent with wildtype activity (≥ 26 pmol MeMP/ h/ mgHb. Exclusion criteria were as follows; i) concomitant treatment with allopurinol, and ii) non-Caucasian

PhD Thesis Thiopurines in IBD Paul Andrew Blaker ethnicity. For each individual, clinical records and laboratory results were reviewed retrospectively to record data on demographics, type of IBD, RBC TPMT enzyme activity and thiopurine metabolite profiles.

2.1.3 Exome microarray genotyping studies (Chapters 6 and 7)

Patients prescribed thiopurines for the management of IBD were selected from the IBD Pharmacogenetics study. Patients were all adults, gave written informed consent, had IBD diagnosed by standard criteria and disease managed according to national guidelines (37). Both Caucasian and non-Caucasian individuals were included, with ethnic variation in genotypes accounted for using principal components analysis (PCA). For each individual, electronic patient records, case-notes and laboratory results were reviewed retrospectively to record data on demographics, type/extent of IBD, indication for treatment, thiopurine weight-normalised dose, average thiopurine metabolite profiles, treatment outcomes during the first 12 months of therapy and ADRs (see definitions below).

As of August 2012, 763 patients had been recruited to the IBD Pharmacogenetics study. Dr Melissa Smith, Dr Kirstin Taylor, Mrs Anna Stanton and I directly recruited patients for this study from the specialist IBD clinics at GSTT. Pertaining to the current study, all data collection regarding disease phenotype, treatment outcomes and analysis was completed solely by myself. Of the 763 patients, 472 had received treatment with AZA/MP. Within this cohort 5 nested case-control studies were completed. The first separated patients according to the presence or absence or thiopurine hypermethylation, defined as an average MeMP : TGN concentration ratio of ≥ 11 : 1, based on at least 2 measurements taken after 12 weeks of therapy (n = 305, Chapter 6). The second separated patients according to average MeMP concentrations above or below 5000 pmol/8x108 RBC (n = 356, Chapter 6). The third separated patients according to average TGN concentrations >240 pmol/ 8x108 RBC and this was compared to a group with average TGNs between 100-239 pmol/ 8x108 RBC (n = 348, Chapter 6). The fourth separated patients according to the success or failure of intervention free survival during the first 12 months of thiopurine therapy of therapy (n = 329, Chapter 6). The fifth separated patients according to the absence or development of thiopurine-induced ADRs (n = 412, Chapter 7). Within this final group, sub-analyses were completed to investigate the ADRs separately, including nausea, flu-like symptoms, pancreatitis and hepatotoxicity.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.1.4 Biochemical mechanism of allopurinol induced TPMT inhibition (Chapter 8)

Samples for in-vitro assays were derived from ethylenediaminetetraacetic acid (EDTA) whole blood specimens taken from a healthy individual with wildtype TPMT activity (38 pmol MeMP/ h/ mgHb). For in-vivo studies, 21 patients with IBD receiving either AZA monotherapy (group 1, 10 patients) or low dose AZA (25-33% full dose) in combination with allopurinol (group 2, 11 patients) were prospectively identified from the specialised IBD clinics at GSTT. A further 9 thiopurine-naïve individuals without IBD provided control data. Patients with IBD were included if they demonstrated wildtype TPMT activity, they had received a steady state dose of AZA for more than 12 weeks, the thiopurine metabolite profile confirmed adherence to therapy (TGN > 240 pmol/ 8x108 RBC) and they were not receiving 5-ASA or anti-TNF-α antibody therapy that could have affected the thiopurine metabolite profiles. All participants provided written and informed consent (MREC, 00/1/33 and LREC, 06/Q0707/84).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.2 Determination of clinical response

2.2.1 Thiopurine hypermethylation and exome microarray studies (Chapters 3, 4, 6, 7)

In studies comparing thiopurine metabolite profiles against haematological and biochemical parameters, the common toxicity criteria (CTC) were used as a reference standard to define ADRs; these are shown in table 2.1 (338).

Table 2.1 Definitions of drug toxicity

Adverse event Grade 1 toxicity Grade 2 toxicity Grade 3 toxicity Grade 4 toxicity

Haemoglobin Life threatening 12.0 – 10.0g/dL < 10.0 – 8.0 g/dL < 8.0 g/Dl count decreased consequences

Platelet count < 120 – 75.0x109/ < 75.0x109/ L – < 50.0x109/ L – < 25.0x109/ L decrease L 50.0x109/ L 25.0x109/ L

WBC count < 3.0x109/ L – < 2.0x109/ L – < 4.5 – 3.0x109/ L < 1.0x109/ L decreased 2.0x109/ L 1.0x109/ L

Neutrophil count < 1.5x109/ L – < 1.0x109/ L – < 2.0 – 1.5x109/ L < 0.5x109/ L decrease 1.0x109/ L 0.5x109/ L

Lymphocyte < 0.8x109/ L – < 0.5x109/ L – < 1.5 – 0.8x109/ L < 0.2x109/ L count decrease 0.5x109/ L 0.2x109/ L

Alanine > ULN – 3.0 x ULN > 3.0 – 5.0 x ULN > 5.0 – 20 x ULN > 20 x ULN aminotransferase

Alkaline > ULN – 2.5 x ULN > 2.5 – 5.0 x ULN > 5.0 – 20 x ULN > 20 x ULN phosphatase

ULN, upper limit of the normal laboratory range. For alanine transaminase the upper limit for a female was considered as 19 IU/ L and for a male as 30 IU/ L. For alkaline phosphatase the upper limit of normal was 147 IU/ L.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

The primary end-point of studies investigating clinical response to thiopurines was defined as the success or failure of AZA/MP therapy in achieving intervention free survival during the first 12 months of treatment. Each patient was discussed in the Virtual Biologics and Immunosuppression Clinic (VBIC) by 3 investigators (Dr Paul Blaker, Dr Peter Irving and Dr Jeremy Sanderson) to determine this outcome. A failure of treatment was considered as any one of the following; i) admission to hospital for management of active disease despite maintenance therapy with AZA/MP, ii) unexpected surgery for a complication of IBD, iii) switch to a second-line immunomodulator because of failure of AZA/MP to maintain remission or the development of thiopurine-induced ADRs, iv) escalation to anti-TNF-α antibody therapy, v) failure to withdraw steroids for active disease or a new course of steroids, vi) patient choice, vii) switch to low-dose AZA/MP with allopurinol to circumvent treatment non-response or ADRs. In those patients with continuing active disease, standard assessment included measurement of serum C-reactive protein, faecal calprotectin and where indicated, endoscopy with biopsy and / or intra-abdominal imaging with contrast enhanced CT or MRI.

2.2.2 Statistical analysis of clinical data

Statistical analyses were completed using GraphPad Prism version 5.04 for Windows (GraphPad Software Inc., San Diego, USA), IBM SPSS Statistics version 21 for Windows (IBM, Portsmouth, UK) and MedCalc version 12.7.8 for Windows (MedCalc Software, Ostend, Belgium). Description of variables was in median and interquartile range (IQR), or mean and 95% confidence interval (CI). Fisher’s exact tests were performed to compare proportions of phenotype and were reported with odds ratio (OR) and 95% CI. A 3 by 2 Chi square test was used to compare proportions of phenotypes between 3 groups. One-way analysis of variance (ANOVA) was used to compare distributions between 3 groups. D’Agostino and Pearson normality tests were used to determine whether data were normally or non-normally distributed. Subsequently, independent samples Student’s t-tests or Mann-Whitney U tests were used to evaluate differences between groups. Correlations were assessed using Pearson’s (parametric) or Spearman rank (non-parametric) tests respectively. Receiver operator characteristic (ROC) curve analyses and calculation of Youden indices were used to determine the optimum cut-points for TGN and MeMP concentrations and the MeMP : TGN ratio in predicting related factors. Logistic regression modelling was completed in IBM SPSS. All tests were performed two-sided and P-values < 0.05 considered statistically significant. Power calculations are discussed in section 2.5.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.3 Genotyping studies: laboratory methods

2.3.1 SNP selection for real-time PCR (Chapter 5)

Based on the previous studies by Smith et al, known coding region SNPs in XDH, MOCOS, AOX1, MTHFR, IPTA and ABCB5, with a Caucasian minor allele frequency (MAF) of at least 0.02 were selected for genotyping as shown in table 2.2 (272, 329). SNPs that encoded a non-conservative change in amino-acid (non-synonomous single nucleotide polymorphism, nsSNP) were preferred.

Table 2.2 SNPs selected for analysis in XDH, MOCOS, AOX1, MTHFR, ITPA and ABCB5 including the predicted MAF in Caucasian populations

cDNA base Amino-acid Allele rs number Gene Exon change substitution Frequency rs4407290 XDH 10 837 C > T Val279Val 0.02 rs17323225 XDH 18 1936 A > G Ile646Val 0.05 rs17011368 XDH 20 2107 A > G Ile703Val 0.05 rs2295475 XDH 21 2211 C > T Ile737Ile 0.31 rs1884725 XDH 27 3030 C > T Phe1010Phe 0.23 rs207440 XDH 34 3717 G > A Glu1239Glu 0.06 rs3744900 MOCOS 4 359 G > A Ser120Asn 0.03 rs623053 MOCOS 4 509 T > C Ile170Thr 0.03 rs678560 MOCOS 6 1072 A > C Met358Val 0.03 rs59445 MOCOS 11 2107 A > C Asn703His 0.34 rs1057251 MOCOS 15 2600 T > G Val867Ala 0.10 rs55754655 AOX1 30 3404 A > G Asn1135Ser 0.16 rs1801133 MTHFR 7 677 C > T Ala222Val 0.33 rs1801131 MTHFR 7 1298 A > C Glu429Ala 0.23 rs1127354 ITPA 2 94 C > A Pro32Thr 0.08 124+21 A> Splice rs7270101 ITPA Intron 2 0.07 C altering rs2301641 ABCB5 5 343 A > G Lys115Glu 0.34

2.3.2 DNA extraction and normalisation of DNA concentrations (Chapters 5, 6 and 7)

Genomic DNA was extracted from EDTA whole blood samples using the QIAmp DNA Mini Kit (Qiagen Ltd. Crawley, UK). All necessary buffers were supplied with the kit. Briefly, 20 µL of protease enzyme and 200 µL of lysis (AL) buffer were added to 200 µL of EDTA whole blood in 1.5 mL Eppendorf tubes. This mixture was vortexed until the samples turned reddish-brown in colour, prior to incubation in a water bath at 56˚C for 10 minutes to digest and denature proteins. 200 µL of ethanol 100% was added, the mixture was vortexed again and transferred to a spin column (in a 2 mL collection tube). The sample was centrifuged at 8000 rpm for 1 minute. In this step the DNA is

PhD Thesis Thiopurines in IBD Paul Andrew Blaker absorbed onto the silica-gel QIAamp membrane. The spin-column was removed, 500 µL of buffer AW1 was added and the sample centrifuged at 8000 rpm for 1 minute in a new 2 mL collection tube. This step was repeated with 500 µL of buffer AW2 and samples centrifuged at 12,000 rpm for 3 minutes. 100 µL of elution buffer was added to the spin-column and the solution incubated at 56˚C for 1 minute. The extracted DNA was mixed with 50 µL of tris-EDTA (TE buffer) to inhibit DNAases and stored in a freezer at -20˚C in sealed 96 well plates.

Fluorometric quantitation of DNA was completed using a Qubit 2.0 Fluorometer (Life Technologies Ltd. Paisley, UK). Firstly, a working solution containing dye was prepared by adding 200 µL of Qubit buffer to 1 µL of dye for each DNA sample to be assayed, with the solution mixed by vortexing. For example for 10 DNA samples and 2 fluorometric standards, the working solution would contain 2400 µL of buffer and 12 µL of dye. Standards were prepared by adding either 10 µL of Qubit Standard 1 or 2 to 190 µL of working solution in thin-walled PCR tubes and vortexed. In PCR tubes prepared for DNA quantitation, 2 µL of DNA was added to 198 µL of working solution and vortexed. Hence the total volume in each tube was 200 µL. The tubes were then incubated for 2 minutes at room temperature. On the home screen of the Qubit 2.0 Fluorometer, the DNA and then the dsDNA options were selected, prior to calibration of the machine using standards 1 and 2. The DNA concentration in ng/ µL was measured against a standard curve and recorded for each DNA sample.

For DNA samples used in the exome microarray analysis, a DNA concentration of 50 ng/ µL ± 10% was required. DNA samples with concentrations greater than this were diluted using TE buffer pH 8.0 (Sigma) and made up to a volume of 10 µL. DNA samples with concentrations less than this were concentrated using a DNA precipitation technique. Briefly, 10 µL of 3 mM sodium acetate at pH 5 was added to 100 µL of each DNA sample and vortexed. 220 µL of ethanol 100% was added to each sample and the mixture vortexed again. Tubes were then left in the freezer at -20˚C for 30 minutes. The tubes were removed and the mixture agitated by turning the tubes up and down approximately 8 – 10 times, prior to centrifuging at 12,000 rpm for 12 minutes. Ethanol was then removed using a pipette and the clear DNA pellet left at the bottom of the tube. A further 500 µL of ethanol 70% was added to each tube and the mixture centrifuged at 12,000 rpm for 2 minutes. After removal of the visible ethanol using a pipette, residual ethanol was allowed to evaporate over 15 minutes under a fume hood, prior to the addition of 16 µL of TE buffer. The DNA concentration was then re-checked on the Qubit Fluorometer as descried above. Samples with a DNA concentration less than 50 ng/µL after concentrating were discarded and fresh EDTA whole blood specimens sought for re-extraction of DNA.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.3.3 Real-time PCR genotyping

Sequence variant analysis in candidate genes was performed by Allele Discrimination Real Time PCR Analysis using TaqMan SNP Genotyping Assays (Life Technologies Ltd. Paisley, UK). This assay is based on the measurement of amplified PCR products by fluorescent detection using fluorescent reporter molecules (figure 2.1). Each Taqman probe is specific to a particular allelic sequence.

Figure 2.1 Principles of the TaqMan probe assay

A). Double stranded DNA is denatured at high temperature. At lower temperature, forward and reverse primers and a sequence specific probe bind to the complementary DNA sequences. The probe differs from the primers in that it is not extended by Taq polymerase, since it lacks a free hydroxyl group and it contains two covalently bound molecules. At the 5’ end a fluorescent molecule known as a reporter is attached, whereas at the 3’ end there is a molecule known as a quencher. The reporter corresponds to the allele present at a given locus. Vic is usually assigned to the wildtype allele and Fam to the variant allele for off the shelf Taqman probes. The quencher molelcule, absorbs light energy from the reporter, provided that the molecules are less than 100Å apart. B). Taq polymerase locates the primers and creates a complementary strand of DNA (extension phase). C). At the probe site, Taq polymerase exhibits exonuclease activity and removes the reporter dye from the probe if bound to the corresponding allele, whilst making a new amplicon. Light striking the free reporter molecule leads to an increase in fluorescence. D). The increase in fluorescence accords with the quantity of DNA product. In the geometric phase of amplification there is a doubling of product for each PCR cycle.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

The Taqman assays contain 18 µM of each primer and 4 µM of the probe in a 20x mix. Taqman assays supplied as a 40x min, required dilution (1+1) to a final concentration of 20x with clean 1x TE buffer. Since the probes are light sensitive they were protected from light and stored at -20˚C.

The PCR reaction requires a buffer, all four dNTPs (dATP, dCTP, dGTP, dTTP), MgCl2 and Taq polymerase. The PCR ready-mix used was PerfectCTaqPCR SuperMix, Low ROX (Quanta Biosciences, Lutterworth, UK). This is a 2x reaction mix containing ROX reference dye (for 580 – 585 nm excitation) and stabilizers, all in optimised concentrations.

Prior to use the SuperMix (x2) reaction buffer, appropriate Taqman probe and DNA samples were defrosted, vortexed and briefly spun down on a centrifuge. A master-mix containing 5.0 µL of SuperMix (x2), 3.5 µL of DNA free water and 0.5 µL of Taqman probe for each DNA sample was prepared. Using a single-channel repetitive positive displacement pipette, 9 µL of the master mix was transferred to each well of an optically clear 96 well plate. Then using an eight channel pipette, 1 µL of DNA was added to each well. A reagent blank was included with each assay to control for contamination. The wells were closed using optically clear transparent lids, ensuring that no fingerprints were left on the lids that could affect the assay. Plates were then spun at 1500 rpm for 2 minutes to ensure that no bubbles were left at the bottom of the wells and that the contents were well mixed. Plates were then loaded onto a Stratagene Mx3005P RT-PCR instrument (Agilent Technologies UK Ltd. Winnersh, UK) for interrogation. Using the “Allele discrimination/ SNP’s Real- Time” programme and a two-step PCR programme with denaturing at 95˚C and annealing/extension at 60˚C. Fluorescence in each well was measured after extension for each cycle and the amplification plots subsequently interpreted to determine the genotype at a given locus (figure 2.2).

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Figure 2.2 Interpretation of Taqman probe amplification plots

Figure 2.2a. In this plot there is an increase in the signal for Vic (red-line) only, corresponding to the presence of the wildtype allele and a homozygous wildtype genotype.

Figure 2.2b. In this plot there is an increase in the signal for both Vic (wildtype allele) and for Fam (variant allele) indicating the presence of a heterozygous genotype.

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Figure 2.2c. In this plot there is an increase in the signal for Fam (variant allele) only, indicating the presence of a homozygous genotype for the variant allele.

2.3.4 Statistical analysis for real-time PCR genotyping (Chapter 5)

Genotypes for each SNP were tested for departure from Hardy-Weinberg equilibrium (see Section 2.4) and the frequency in the study population compared to those published for Caucasian individuals in the dbSNP database (http://www.ncbi.nlm.nih.gov/projects/SNP/). Dominant and recessive models were applied to test the association between the SNP minor allele and the presence of thiopurine hypermethylation (MeMP : TGN ≥ 11 : 1). Fisher’s exact tests were used to test differences between groups in 2 x 2 contingency tables using GraphPad Prism version 5.04

2.3.5 Illumina human exome beadchip (Chapters 6 and 7)

The Infinium HumanExome 250K Beadchip microarray (v1.1, Illumina United Kingdom, Little Chesterford, UK) was used to identify novel and functionally relevant genotypes associated with thiopurine hypermethylation, thiopurine response and the development of ADRs. The putative functional exonic variants contained on this array were selected from over 12,000 individual exome and whole-genome sequences by a panel of leading geneticists. The content consists of > 250,000 exonic variants present in diverse populations including; European, African, Chinese, and Hispanic individuals, and in addition, included patients investigated for a range of common diseases, such as cancer, type 2 diabetes, metabolic, and psychiatric disorders. However, the microarray does not provide coverage outside of coding regions. This technology was selected in preference to exome

PhD Thesis Thiopurines in IBD Paul Andrew Blaker sequencing or whole-genome sequencing, given the much lower cost, high sample throughput and fast processing time.

The Infinium Human Exome Beadchip genotyping was performed by the Biomedical Research Centre at Guy’s Campus, King’s College London. Chips were prepared and scanned by Ms Muddassar Mirza. All subsequent data input and downstream analysis in GenomeStudio (Illumina) was completed by the author. The steps involved in plate preparation and scanning are briefly outlined below.

Firstly, stock DNA at a concentration of 50 ng/µL is amplified using an iso-terminal whole genome amplification technique. This increases the yield of DNA by approximately 1000-fold and is superior to PCR as it reduces GC content bias (for review see Benjamini and Speed, 2012 (339)). Secondly, enzymatic cleavage is used to generate DNA fragments of between 300 – 600 bp in length. This provides optimum conditions for the hybridization of oligonucleotide probes. Thirdly, DNA is purified using isopropanol, resulting in the formation of a cleaned DNA pellet. The pellet is then re- suspended in a buffer solution. Fourthly, the DNA suspension is applied to the beadchip to facilitate hybridization of oligonucleotide probes contained on thousands of beads embedded on the surface of the chip. Each bead represents a single SNP and is coated with thousands of copies of the relevant oligonuelcotide probe. Probes are complementary to the sequence juxtaposed to the SNP of interest; however they do not span it. Next, single base extension of each probe is completed using chain-terminating dideoxynucleotides (ddNTPs). In this regard, adenosine and thymidine are tagged with biotin, whereas guanosine and cytosine are tagged with dinitrophenyl. Following extension the DNA fragments are washed off, leaving only labelled probes. Finally, chips are stained with the sequential application of green fluorescent streptavidin, which binds to ddATP and ddTTP, and red fluorescent anti-dinitrophenyl, which binds to ddGTP and ddCTP. The stained chips are read on an Illumina iScan microarray scanner. This uses lasers to excite the fluorophores, generating fluorescent signals that are used to create intensity plots for each SNP. The intensity plots correspond to genotypes at a given locus, with heterozygotes generating a yellow signal due to equal emission of both green and red fluorescence (figure 2.3).

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Figure 2.3 Example of an Infinium HumanExome Beadchip intensity data map. Image generated from the two colour iScan genotyping microarray scanner. Each dot is a bead specific for a SNP. A red bead represents a homozygous genotype of AA, a green bead represents homozygous BB, and a yellow bead is a heterozygote. (Image taken from http://www.ycga.yale.edu/index.aspx, date accessed 16th January 2014).

2.4 Exome chip analysis - algorithm development and validation

2.4.1 Genotype / phenotype analysis using PLINK

Analysis of the very large data set generated by the exome microarray would not be computationally efficient using standard data interpretation programs such as Excel or GraphPad. Therefore analysis of genotype/phenotype data was completed using PLINK (v1.07) (340). This is a free, open- source whole genome association analysis toolset, specifically designed to perform a range of basic, large-scale genetic analyses (http://pngu.mgh.harvard.edu/~purcell/plink/). The following sections describe the development and validation of the approach used to interpret the exome microarray data used in this thesis (Chapters 6 and 7).

Prior to interrogating the genotype data using PLINK, the raw data needed to be extracted from the Illumina GenomeStudio Data Analysis Software by creating a custom report for PLINK. This generated two files known as ‘MAP’ and ‘PED’ files that can be read by the PLINK programme. The MAP file contains a description of the genetic markers and the PED file contains a list of the sample identifiers with corresponding genotype data for each marker.

Since several different studies were run on the Infinium Beadchips simultaneously and data entered into GenomeStudio as a single project, the first step in the analysis pathway was to separate the

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IBD patients from the rest of the dataset. This was achieved in PLINK using the following command line, where ‘ibdpatients.txt’ is a text file that contains a list of the IBD patient identifiers, which in this case are unique ‘GKT numbers’ (Guy’s, King’s and St Thomas’):

“plink --file allpatients --keep ibdpatients.txt --make-bed --out ibdpatients”

The above command line generated a custom MAP and PED file containing all of the IBD patients that was used in the subsequent analyses. Within the same command line the addition of “--make- bed” converted the MAP and PED files into binary files (‘ibdpatients.bed’, ‘ibdpatients.fam.’ and ‘ibdpatients.bim’), which reduced the size of the files and therefore the time taken to complete the downstream analyses. The binary PED file included data for 768 patients, of whom 382 were males and 372 were females. Fourteen sex-mismatched patients were identified and excluded from further analyses. Prior to quality control a total of 242,901 genetic markers were available for analysis. Three pairs of duplicate samples were also included and acted as an internal control to determine genotype concordance.

The second step in the analysis pathway was to apply thresholds for the genotype calling success rate, minor allele frequency (MAF) and Hardy-Weinberg equilibrium (HWE).

In total 99.5% of individuals were successfully genotyped, which is comparable to the individual call rate (>98%) reported by Huyghe et al (341) and considered acceptable according to the WTCCC criteria (342). A genotyping success rate of > 97% was chosen as the marker-level of quality control to exclude technical failures. This was achieved using the command line “--geno 0.03” and led to the loss of 9508 SNPs (3.9%). The average successful genotyping call rate was 99.95%. The genotype concordance among the 3 duplicate sample pairs was 99%. Only 1 sample from each of these pairs was included in the subsequent trait-SNP association analyses.

An evaluation of the genotyping quality of the Infinium HumanExome Beadchip (v1.1) is beyond the scope of this thesis. However, in a study of 9,660 individuals by Huyghe et al (341), which used the same microarray, genotyping quality was compared to sequencing by Complete Genomics (http://www.completegenomics.com/public-data/69-Genomes, n=17), the 1000 Genomes Project (www.1000genomes.org, n=49) and the Illumina HumanOmni2.5 Beadchip by the 1000 Genomes Project (n=86). Overall concordance rates were 99.93%, 99.97% and 99.96% respectively, which provides confidence in the genotype calling for the current study.

To reduce the impact of monomorphic and very low frequency SNPs on the threshold for statistical significance, SNPs with a MAF < 0.05% were excluded. Exclusion of SNPs with a MAF of 0.05% (< 1 in

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10,000) is consistent with the analysis previously reported by Huyghe et al (341). Application of a MAF cut-off of 0.05% using the command “--maf 0.00005” resulted in the loss of 90,509 makers (37%). The significant loss of markers at this stage occurs since the overwhelming majority of variation assayed on the Infinium HumanExome Beadchip microarray has a MAF of < 1%.

HWE states that in any given population the allele and genotype frequencies should remain relatively constant from generation to generation, in the absence of additional evolutionary forces. Such influences include non-random mating, mutation selection, genetic/allelic drift, gene flow (transfer of alleles from one population to another due to immigration of individuals) and meiotic drive (343). Since one or more of these influences are likely to occur within a real population, HWE describes an ideal condition against which these influences can be examined. In control subjects failure to adjust for deviations from HWE may bias the estimates of genetic effects in association analyses (344). Therefore consistent with the previous studies by Huyghe et al. (341, 345) and Khrunin et al. (346), who investigated patterns of genetic variation within and among human populations, a HWE cut-off of P = < 1x10-6 was chosen. The HWE cut-off of P = < 1x10-6 was applied using the command “--hwe 0.000001” and resulted in the loss of a further 2077 SNPs (0.9%).

The thresholds for genotype success call rate, MAF and HWE were applied in the same command line, where ‘b’ denotes the use of a binary file:

“plink --bfile ibdpatients --geno 0.1 --maf 0.0005 --hwe 0.000001 --make-bed --out ibdpatientsgmh”

An example of a PLINK log for the above command line is shown in figure 2.4. After frequency and genotype pruning, 149,606 markers (61.2%) were available for the initial trait-SNP association analyses.

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Figure 2.4 Example of a ‘PLINK’ log for genotype success call rate, MAF and HWE adjustments

To validate genotype calling in the IBD dataset and importantly to confirm that the correct genotype data matched with the individual phenotype data, a trait-SNP association analysis was completed using a nested cohort of IBD patients separated into cases and controls according to their TPMT methylator status. This is a useful quality control since TPMT activity demonstrates a tri-modal distribution secondary to genetic polymorphism and further the majority of low activity phenotypes can be explained by a limited number of variants in the TPMT gene (TPMT*3A, TPMT*3C and TPMT*2). Therefore, if the genotype calling is accurate and the genetic and phenotype data match, the SNPs with the highest levels of statistical significance in a triat-SNP association analysis for patients with low or intermediate TPMT activity should be within the TPMT gene.

Of the 751 IBD patients passing the initial quality controls, TPMT activity had been measured in the PRL for 482 of these individuals (64%) as described in table 2.3.

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Table 2.3: Cohort of patients included in the TPMT genotyping quality control.

Cases - TPMT activity Controls - TPMT activity Variable Significance level <25 pmol/ h/ mg Hb >26 pmol/ h/ mg Hb Number of patients 49 433 P = < 0.001 TPMT mean 20.1 ± 0.44 36.2 ± 0.31 (95% CI = 14.918- (SEM, range) (15 - 25) (26 - 62) 17.17.047)

To complete a trait-SNP association analysis a phenotype file containing a list of individual GKT numbers and their associated TPMT activities coded as ‘0’ for missing data, ‘1’ for controls and ‘2’ for cases was created in Excel and converted to a ‘.txt’ file (‘tpmtqc.txt’). The first column of this file contained a list of the GKT number family identifiers (FID) and the second column contained a list of the GKT number individual identifiers (IID), which in this case were identical. The third column contained the TPMT phenotype codes. The association analysis was then completed using the following command line:

“plink --bfile ibdpatientsgmh --pheno tpmtqc.txt --assoc --fisher --adjust --out ibdpatients_tpmt_qc ”.

The command lines “--pheno”, “--assoc” and “--fisher”, firstly read the phenotype file, which in this case contained the categorical data on TPMT activity and secondly it completes chi-squared and then Fisher’s exact tests to determine trait-SNP associations for each of the markers included in the analysis. The outcome of this analysis was read in Excel and is shown in table 2.4.

The addition of the “--adjust” function corrected the reported P-values for the effect of multiple testing. PLINK reports several different methods to correct for multiple testing, including; Bonferroni single-step adjusted P-values, Holm (1979) step-down adjusted P-values, Sidak single- step adjusted P-values, Sidak step-down adjusted P-values, Benjamini and Hochberg (1995) step-up FDR control and Benjamini and Yekutieli (2001) step-up FDR control. Alternatively, a crude level of statistical correction can be calculated by dividing a standard α-level of 0.05 by the number of tests completed. For example if 100 tests were completed, a nominal level of statistical significance may be regarded as (0.05/100 = 0.0005) P = < 1x10-4. Failure to include a correction for multiple testing may lead to the reporting of a false association in a trait-SNP association analysis (type I error). Equally, the use of such corrections may result in too few truly significant results being reported; that is, failure to declare a result statistically significant when in fact it is (type 2 error) (347, 348). Therefore the optimum method to correct for the problem of multiplicity remains controversial and the need to apply it likely depends on the type of analysis being conducted. For example in

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

determining novel genetic markers in a trait-SNP association analysis from a large number of genetic variants (unsupervised testing), correction for multiple testing is applicable. However, in hypotheses driven trait-SNP association analyses containing small numbers of markers, for example genetic variants restricted to the thiopurine pathway, then such corrections are probably not required (349).

Table 2.4: Genetic markers associated with intermediate TPMT activity from unsupervised testing using Fisher’s exact tests on 149,606 markers in 482 individuals.

Unadjusted Bonferroni MAF MAF Chr SNP ID OR Gene Location Mutation P-value Correction Cases controls 6 exm518956 2.35E-59 2.46E-54 0.3469 0.005774 91.48 TPMT (*3C) Exon Y240C 6 exm518970 6.74E-45 7.06E-40 0.2551 0.003464 98.52 TPMT (*3B) Exon A154T Intergenic PICALM 11 exm2259893 7.92E-08 0.006796 0.0612 0.001155 56.41 Intergenic Unknown & EED Intergenic 9 exm2266922 5.55E-07 0.04763 0.6735 0.4074 3 Intergenic Unknown UNQ6494 & SYK 9 exm762395 6.16E-07 0.05284 0.22459 0.4838 0.3 WNK2 Exon V828M Intergenic 12 exm2271853 1.99E-06 0.1708 0.1122 0.01276 12.38 Intergenic Unknown NAV3 & SYT1

Chr, chromosome; SNP ID, exome chip SNP identifier; MAF, minor allele frequency; OR, odds ratio.

As expected from the analysis of patients with intermediate TPMT activity (no patients with completely deficient or low TPMT activity were included), the highest P-values returned were for TPMT*3C and TPMT*3B. This provides confidence that the genotype calling is reliable and secondly that the correct genotype data has been matched with the correct phenotype data. In this dataset 2 other SNPs (exm2259893 and exm2266922) in chromosomes 11 and 9 respectively were also noted to pass Bonferroni correction. However, before such markers can be considered as truly associated with intermediate TPMT activity phenotypes, further quality control of the dataset is required. Firstly this is to adjust for miss-calling of heterozygote states of rare variants using the ‘zCall’ algorithm. Secondly, there is a need to account for confounding variation within the cohort using principal components analysis (PCA). Both of these quality controls are described after the following section on pathway analysis.

An alternative to trait-SNP association analyses using unsupervised testing is to assess for associations within genes relevant to the phenotype of interest (supervised testing), which in this instance means restricting the analyses to the thiopurine pathway. A list of genes influencing thiopurine metabolism was established using data from published literature and the thiopurine pathway using the PharmaGKB (http://www.pharmgkb.org/pathway/PA2040), Kyoto Encyclopaedia of Genes and Genomes (KEGG, http://www.genome.jp/kegg-bin/show_pathway?map00983) and

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Reactome (http://www.reactome.org/entitylevelview/PathwayBrowser.html#DB=gk_current&FOCUS_SPECIES _ID=48887&FOCUS_PATHWAY_ID=156580&ID=156581) websites as reference sources (Appendix 1). A list of genes influencing methylation capacity was also created. The lists of genes included in the thiopurine and methylation pathway analyses were independently validated by Dr Tony Marinaki.

A further option for supervised testing is to create a list of genetic variants within a single gene. An example of this is shown below for the TPMT gene, using the same cohort of individuals separated by TPMT activity as described previously (Table 2.5). In this case the command line “--extract tpmtsnps.txt”, instructs PLINK to only test those markers contained within a defined list, which in this example includes the 9 variants in the TPMT gene included on the microarray. The command line for this restricted analysis was as follows:

“--plink --bfile ibdpatientsgmh --extract tpmtsnps.txt --pheno tpmtqc.txt --assoc --fisher --adjust -- out ibdpatientsgmh_tpmtgene_qc”

Table 2.5: TPMT variants associated with intermediate TPMT activity using Fisher’s extact tests on 9 variants within the TPMT gene in 482 individuals.

TPMT Mutant MAF Ref Chr SNP MAF controls P-value OR Variant Allele Cases allele 6 exm518956 TPMT*3C G 0.3469 0.005774 A 1.90E-31 91.48 6 exm518960 TPMT*8 A 0.0102 0 G 0.1017 NA 6 exm518964 TPMT*24 A 0 0.001157 C 1 0 6 exm518966 TPMT*16 A 0 0.001155 G 1 0 6 exm518967 TPMT*22 A 0 0 G 1 NA 6 exm518970 TPMT*3B A 0.2551 0.003464 G 1.87E-23 98.52 6 exm518975 TPMT*12 A 0 0 G 1 NA 6 exm518984 TPMT*2 C 0 0.001157 G 1 0 6 exm518987 TPMT*21 C 0 0 G 1 NA

Examining the association between TPMT variant alleles and intermediate TPMT activity, the concordance between the presence of a TPMT variant allele and intermediate TPMT activity was 71% (table 2.6).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Table 2.6: Concordance between TPMT variant alleles and intermediate TPMT activity in 482 patients

Heterozygote TPMT Wildtype TPMT

activity (n=49) activity (n=433) TPMT variant allele 35 6 PPV = 85% seen No TPMT variant allele 14 428 NPV = 97% seen Sensitivity = 71% Specificity = 98.6%

The discordance between the absence of a TPMT variant allele and the presence of intermediate TPMT activity (29%) is similar in magnitude to the studies previously reported by Ford et al (350, 351) and Larussa et al. (352) but is greater than that reported by Schaeffeler et al. (11%) (353). However, this may be explained by differences in the TPMT assays, population structure and genotyping techniques used between studies. For example, in the study by Schaeffler et al, TPMT activity was measured in peripheral lymphocytes using TG as a substrate as opposed to MP in RBCs, the cohort was restricted to German-Caucasians and where intermediate TPMT activity was not explained by the common TPMT variants (TPMT*3 and TPMT*2) direct sequencing was undertaken to examine the sequence of the entire TPMT open reading frame.

Overall the above results provide confidence that the genotype calling from the Infinium HumanExome Beadchip is accurate and secondly that the correct phenotype data is associated with the correct genotype data. However, further quality controls to adjust for calling of rare variants and population stratification are required before results of trait-SNP association analyses can be considered real.

2.4.2 Adjusting data for rare variant calling and population structure using ‘zCall’ and principal components analysis

Dr Jemma Walker, under the supervision of Professor Cathryn Lewis, in the Statistical Genetics Unit at King’s College London, completed further quality control of the dataset using the ‘zCall’ algorithm and PCA, the principles of which are herein described. All downstream association analyses including logistic regression using PCA, genotype modelling, pathway and gene analyses were completed by myself with advice from Professor Cathryn Lewis.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.4.2.1 ‘zCall’ rare variant calling algorithm

Microarray-based genotyping uses two measures of intensity to separate data-points derived from the chip into clusters that relate to a given genotype. An example of this is shown in figure 2.5, which shows a hypothetical cluster plot for a bi-allelic locus separated into three clusters labelled as ‘AA’, ‘AB’ and ‘BB’, where ‘AA’ and ‘BB’ represent homozygote clusters and ‘AB’ denotes

(354) heterozygotes . The three clusters are separated by vertical (tx) and horizontal (ty) lines that are calculated from the mean of the variance in homozygote cluster intensities and scaled according to a z-score threshold (z). The z-score threshold can be manually varied to achieve the optimum genotype concordance. Subsequently, genotypes are assigned to points based on their position relative to tx and ty, with points in quadrant I classified as homozygotes (BB), points in quadrant II as heterozygotes (AB), points in quadrant IV as homozygotes (AA), and points in quadrant III are classified as ‘No Calls’ (figure 2.5).

Figure 2.5 Example of a genotype intensity plot. Goldstein et al. Bioinformatics 2012; 28: 2543- 2545. Reproduced with kind permission from the Oxford University Press (licence number 3202540851484, 5/08/2013).

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Existing algorithms (e.g. Illumina GenCall Data Analysis Software used by GenomeStudio) that cluster data-point intensities to assign genotype calls work well for common variants (MAF > 5%) (355, 356). However, they are less well adapted to clustering rare variants in which only the common allele homozygote cluster is well populated and heterozygotes may be misclassified as a ‘no call’ (354, 357). Since the majority of variants assayed on the Infinium HumanExome microarray have a MAF < 1%, alternative algorithms to cluster rare variants are required. The ‘zCall’ algorithm was developed for this specific purpose and in comparison with default genotype callers such as GenCall, reduces the number of ‘no calls’ for rare variants.

As described by Goldstein et al the ‘zCall’ algorithm is implemented as follows. Firstly, data-point intensities are read by a default genotype caller (e.g. ‘GenCall’) to obtain genotype calls for all variants. Secondly, linear regression is used to determine the relationship between the means and standard deviations of the X and Y intensities for common variants. Thirdly, an optimum value of z is resolved for the same common variants. Finally, for rare variants where there is an excess of missing genotypes the variant is ‘recalled’ using z and the linear regression to calculate tx and ty, which allows the genotypes to be re-clustered. The use of the ‘zCall’ algorithm has been found to improve the SNP-wise concordance of singletons by approximately 7% as compared to Illumina’s default genotype caller (354). Therefore calling rare genotypes with the ‘zCall’ algorithm should be considered the gold standard.

2.4.2.2 Principal components analysis

Population stratification, which describes allele frequency differences between cases and controls that occur because of systematic ancestry differences, has been shown to cause spurious results in disease association studies (358-362). Principal components analysis (PCA) is a method can that be applied to genetic data to infer worldwide axes of human genetic variation from the allele frequencies of various populations, which thereby allows the detection of such variance and correction for population stratification (363, 364). PCA is mathematically defined and acts to transform a set of observations into co-ordinates that can help visualise the internal structure of the dataset (dimensionality) by inferring continuous axes of genetic variation. Plotting co-ordinates on such axes reduces the size of the data to a smaller number of dimensions, thereby facilitating characterisation of as much of the variability as possible. For example in the IBD cohort, since it was not restricted to the collection of samples from Caucasians alone, it is likely that differences in ancestry exist between samples and in this case the first axes of variation have a geographic interpretation. This is shown in figure 2.6, which depicts how, using the first 2 principal components (PCs), individuals within the cohort may be stratified into genotypically related ethnic groups. This also allows for sub-analyses

PhD Thesis Thiopurines in IBD Paul Andrew Blaker of the trait-SNP associations on an accurately defined set of Caucasian individuals. In this regard, 647 of the 763 individuals (85%) recruited to the IBD study classified themselves as Caucasian in origin. However, PCA suggested that in fact only 450 of the 763 individuals (58.9%) were truly of Caucasian ancestry.

A more detailed discussion regarding the theory, calculation and application of PCA is beyond the scope of this thesis and the reader is referred to Jackson et al. (2003) (365) and Price et al. (2006) (362).

Figure 2.6 PCA analysis of 1766 individuals showing geographic segregation according to genotype. Graphic representation of continuous axes for the first 2 principal components, showing geographical segregation of individuals according to genotype. Black circles represent Caucasians and red circles represent non-Caucasians. Image courtesy of Dr Jemma Walker.

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To adjust for PCA in a trait-SNP association analysis, a logistic regression using the first 4 PCs was completed in PLINK using the command line “--logistic --covar pca.txt --covar-number 1-4”, where ‘pca.txt’ is a text file containing the first 10 principal components that describes confounding variation within the dataset. Adding the command lines “--hide-covar” and “--ci 0.95”, returns the summative effect of these covariates on an additive allelic model in a case-control analysis and provides the 95% confidence intervals for the calculated P-values. An example of the full command line is shown below:

“plink --bfile ibdpatientsgmh --pheno tpmtqc.txt --logistic --covar pca.txt --covar-number 1-4 --adjust --ci 0.95 --hide-covar --out ibdpatientsgmh_pc”

A trait-SNP association analysis may be restricted to individuals of Caucasian origin alone, by replacing ‘pca.txt’ with a text file that includes information on the Caucasian individuals only (‘pca_cauc.txt’) and the analysis repeated using the first 2 PCs.

An example of how ‘zCall’ and PCA can change the reported genetic associations for a particular phenotype is shown in table 2.7, using the same cohort of IBD patients separated according to TPMT methylator status.

Table 2.7: Genetic markers associated with intermediate TPMT activity from unsupervised testing in 461 individuals adjusted for principal components analysis.

Unadjusted Bonferroni 95% CI Chr SNP ID OR Gene Location Mutation P-value correction L U 6 exm518956 9.38E-19 9.99E-14 468.1 119.8 1829 TPMT Exon TPMT*3C 6 exm518970 4.44E-14 4.73E-09 408.8 85.7 1949 TPMT Exon TPMT*3B 16 exm1226533 9.51E-05 1 7.6 2.7 21.1 PALB2 Exon G998E Within 9 exm2259059 0.000105 1 2.6 1.6 4.2 PTPRD Silent gene

Using the datasets re-called with ‘zCall’ and adjusted for PCA, the two most common low TPMT activity variants remain strongly associated with intermediate TPMT activity. However, the two additional SNPs (exm2259893 and exm2266922) in chromosomes 11 and 9 that were previously shown to have significance in the association analysis without these quality controls, no longer appear to have statistical significance. Therefore the use of ‘zCall’ and PCA appears to reduce the

PhD Thesis Thiopurines in IBD Paul Andrew Blaker false association rate when interpreting the microarray data and therefore both methods should be included in the analysis algorithm.

The ‘zCall’ correction and PCA calculations were completed using a combined dataset of 1766 individuals from several different studies, of which 763 (43%) were from the IBD cohort. In addition to this the dataset was re-checked for gender mis-matches using PLINK, which highlighted ‘problem arguments’ in 69 patients (3.8%). The effect of this on the IBD cohort meant that it was reduced to a total of 737 individuals (loss of 3.4%). Secondly, a MAF of < 0.05% and missingness thresholds of >97% for individuals and > 99% for SNP call rates were applied, prior to exclusion of variants out of HWE at a cut-off of P = < 1x10-6. Following these quality controls 106,467 SNPs remained available for analysis.

2.4.2.3 Genotype modelling

The outcome for the analyses described thus far report differences in allele frequencies between cases and controls (allelic models). However, for a particular variant it is usual to determine if its effect is expressed in a dominant (Aa) or recessive (aa) manner, as shown here for the TPMT variant analysis (Table 2.8). To model for dominant or recessive traits the command lines “--dominant” or “- -recessive” were added to the logistic regression using PCA as follows:

“plink --bfile ibdpatientsgmh --pheno tpmt.txt --logistic --dominant --covar pca.txt --covar-number 1- 4 --adjust --ci 0.95 --out ibdpatientsgmh_pca_dominant”

“plink --bfile ibdpatientsgmh --pheno tpmt.txt --logistic --recessive --covar pca.txt --covar-number 1- 4 --adjust --ci 0.95 --out ibdpatientsgmh_pca_recessive”

Table 2.8: Modelling the effect of genotypes associated with intermediate TPMT activity for dominant and recessive effects

Bonferroni 95% CI Chr SNP ID Model OR Gene Location Mutation correction L U 6 exm518956 DOM 9.38E-19 468.1 119.8 1829 TPMT EXON TPMT*3C 6 exm518970 DOM 4.44E-14 408.8 85.8 1949 TPMT EXON TPMT*3B 9 exm762395 DOM 1.61E-05 0.2285 0.1 0.4 WNK2 EXON V828M 1 exm142869 REC 9.38E-19 5.902 2.5 4.0 PM20D1 EXON R153W 19 exm-rs7507442 REC 4.44E-14 4.096 2.0 4.0 ZNF600 Within gene Silent 20 exm1520916 REC 1.61E-05 8.959 3.1 4.0 GNRH2 EXON A16V

DOM and REC denote dominant and recessive models respectively.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Modelling the unsupervised association analysis for individuals with intermediate as compared to normal TPMT activity shows that TPMT*3C and TPMT*3B have a dominant effect, i.e. the effect will be expressed in both heterozygote and homozygote variant individuals.

2.4.2.4 Adjusting data for linkage disequilibrium

Throughout the human genome, a correlation structure exists between genetic variants at different loci. This means that knowing the genotype at one locus may provide information about a genotype at another locus (366). These relationships arise when alleles at two loci are not inherited independently, due to non-random association, causing a deviation from their expected population frequencies. The correlation between alleles at two or more loci is termed linkage disequilibrium (LD). This is usually measured as either ‘D’ or ‘r2’ (r2 preferred) that represent the magnitude of the deviation from the expectation that there is no association between alleles along the genome. For example an r2 value of ‘0’ means that there is no correlation between alleles at two different loci, whereas an r2 of ‘1’ means that there is a perfect correlation. This is an important consideration in association studies (367), since a variant that is statistically significant for a given trait may not actually be the causative SNP but rather it may be tagging the true SNP through LD. Furthermore, LD needs to be considered when correcting for multiple testing. In this case, variants that are in perfect LD with one another will over-inflate the calculated level of statistical correction, which may then be too conservative. Rather one should only need to correct for a single SNP that is tagging (in LD with) a set of other variants, instead of correcting for each of these variants independently.

Identification and then removal (pruning) of SNPs that are in LD was achieved using the command line “--indep-pairwise 50 5 0.99”. This instructs PLINK to look at 50 SNPs at a time and shift the window by 5 SNPs at each step, removing variants above a specified r2 value, which in this example is an r2 > 0.99. This generates two text files called ‘plink.prune.in’ and ‘plink.prune.out’, which report SNPs that are not in LD with each other at an r2 < 0.99 and vice-versa respectively. These files may then be used to remove SNPs in LD using the following command line:

“plink --bfile ibdpatientsgmh --extract plink.prune.in --make-bed --out ld_prune_ibdpatientsgmh”

The binary files pruned for LD were then used as the base-files for the PCA adjustments and association analyses.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.4.2.5 Gene-based association tests

In a standard case-control study using high-throughput genomic data such as that derived from a microarray, the most convenient analysis approach is to test the association between a trait and every SNP. The disadvantage of this approach, as previously discussed, is that it requires a stringent threshold to declare genome wide significance to control the false discovery rate (368). Moreover, due to locus heterogeneity, a phenotype may occur because of allelic variants at different loci in different populations, making it difficult to replicate results based on a single SNP (369, 370). An alternative and potentially more powerful approach is to study the combined effect of variants at multiple loci within genes or between genes. Such gene-centric analyses are desirable for several reasons. Firstly, in comparison with SNP-based approaches they deflate the number of tests by more than 10-fold, which reduces the problem of multiplicity. Secondly, unlike the heterogeneity of a single locus, the functions of a gene are highly conserved across populations (370), improving the likelihood of replication. Finally, genes represent functional units and therefore gene-centric analyses may perform better in revealing functional mechanisms underlying a complex trait (371). This is particularly relevant to the study of thiopurine metabolites, which represent the end-products of flux through several different enzyme systems.

Numerous different gene-based association methods have been developed (340, 348, 371-374). PLINK currently provides for gene-based analysis using the ‘set-test’ function, where a set represents the SNPs contained within a single gene (or entire pathway; pathway-centric analysis). In the first step of this analysis, a single trait-SNP analysis for all SNPs within a defined set is performed. Secondly, using the single SNP statistics, a mean SNP test statistic is calculated for each SNP set using the maximum amount (“--set-max”) of independent SNPs below a certain P-value threshold (“--set-p”). Thirdly, for SNPs that are not independent i.e., in LD above a specified r2 threshold (“--set-r2”), in this case < 0.5, the SNP with the lowest P-value from the single SNP analysis within a set is selected. The analysis is then repeated for a defined number of simulated SNP sets (--mperm), in this case 10,000, in which the phenotype status of the individuals is permuted (375). An empirical P-value for the SNP set is computed by calculating the number of times the test statistic of the simulated SNP sets exceeds that of the original SNP test statistic.

The values for the LD-based set tests for “--set-r2”, “--p-value” and “--set-max” can be varied, which will naturally change the outcome of the highest empirical P-value. There are no specific rules to define these values, except to say that changing the parameters many times and then choosing the most significant will provide a biased result. Two extremes are to determine the best single SNP per set using “--set-max 1” and “--set-p 1”, or to include all SNPs in a set using “--set-max 99999”, “--set-

PhD Thesis Thiopurines in IBD Paul Andrew Blaker p 1”, “--set-r2 1”. Using the –set-test command alone applies the default values; “--set-r2” = 0.5, “-- set-p” = 0.05 and “--set-max” = 5.

To study the combined effect of all SNPs in the thiopurine pathway for a given trait, the thiopurine SNPs identifiers were recorded in a list and saved to a text file as follows (‘thiopurine.set’):

THIOPURINE_SET exm518956 exm518970 … END

The thiopurine set file was then used in the following command line, where ‘mypheno.txt’ is a file that codes GKT numbers according to the phenotype of interest (‘0’ for missing, ‘1’ for cases and ‘2’ for controls):

“plink --bfile ibdpatientsgmh --pheno mypheno.txt --set-test --set thiopurine.set--set r2 0.5 --set-p 0.05 --set-max 50 --mperm 10000 --assoc --out pheno_thiopurine_set”

Here, “--assoc” can be replaced with “--logistic --covar pca.txt --covar-number 1-4 --adjust --out pheno_thiopurine_set_pca”, to use PCA analysis to adjust for population stratification. However, given the number of permutations (n = 10,000), this significantly increases the analysis time.

An example of the how the thiopurine and methylation pathway gene lists were used in both pathway-centric and gene-centric analyses is shown for the cohort of IBD patients separated by TPMT methylator status (Tables 2.9 and 2.10). A control pathway of SNPs involved in insulin- signalling was also included.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Table 2.9: Pathway-centric analysis of intermediate TPMT (n = 47) vs normal TPMT (n = 414) activity in patients with IBD

Total number Number Total number Empirical P- Pathway of SNPs passing Top SNP genes SNPs value constraints Exm518956 Thiopurine 100 639 13 0.0004 (TPMT*3C) Exm518956 Methylation 39 181 3 < 0.0001 (TPMT*3C) Insulin 8 24 0 0.9173 NA signalling

The nominal P-value threshold is 0.017 (3 pathways tested 0.05/3). Parameters of set-test = r2 0.5, P- value = 0.001, set-max # = 99999 (include all SNPs). As expected the insulin signalling pathway shows no association with intermediate TPMT activity.

Table 2.10: Thiopurine pathway gene-centric analysis of intermediate TPMT (n = 47) vs normal TPMT (n = 414) activity in patients with IBD

Gene SNPs Sig.SNPs P(gene) Top SNP MAF OR P(SNP) TPMT 3 3 <1X10-4 exm518956 0.35 148.8 5.1e-61 SLC28A2 11 1 0.0003 exm1158800 0.06 14.05 1.66e-7 rs4636294 MTAP 4 3 0.0005 0.28 0.36 1.09e-5

ADA 4 1 0.0011 exm1543499 0.03 NA 2.62e-7

SNPs, total number of SNPs per gene; Sig.SNPs indicate the number of SNPs that passed the test constraints (r2 = < 0.9, P = < 0.01, set-max # = 10) and were thus jointly analysed in 10,000 permutations; MAF, minor allele frequency; OR, odds ratio; P, p-value. Since 100 genes in total were analysed, the threshold for statistical significance is 0.0005; e = to the power of 10.

The pathway-centric method shows that both the thiopurine and methylation pathway sets are significantly associated with the phenotype of interest, in this case low TPMT activity. As anticipated the top SNP from these analyses was for TPMT*3C. SNPs in TPMT were also the most significantly associated with low TPMT activity in the gene-centric analysis. This provides validation for the application of these methods to study other phenotypes related to thiopurine metabolism / methylation capacity.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.4.2.6 Epistasis

Genome-wide studies have provided some valuable insights into the genetic basis of complex traits, including drug metabolism; however, at present they only explain a small fraction of the heritability, with variants identified through such studies tending to have small effect sizes. A good example of this is human height, a complex trait with an estimated heritability of 80% in which over 40 loci have been implicated. Yet these loci only explain around 5% of the variation in height, despite studies of tens of thousands of individuals (376). The gap between estimated heritability and the variance currently explained by genome-wide studies is termed ‘missing heritability’. There are several explanations for this apparent ‘black-hole’, which include (i) a large proportion of variants, each with a small effect, remain to be discovered (ii) structural variants are poorly captured by existing microarrays and (iii) gene-environment and gene-gene interactions are not well accounted for (377). With regard to the latter, the interaction between genes, otherwise known as epistasis, has long been recognised to be of fundamental importance in understanding both the structure and function of genetic pathways (378, 379). This is highlighted when considering that the effect of a disease associated variant allele at one locus may be blocked by an allele at a different locus, meaning that the phenotype related to the first locus will not be observed. This would not usually be accounted for in a simple trait-SNP association analysis.

Examination of epistasis between SNP pairs is completed in PLINK using the “--epistasis” function. It is possible to run this analysis on all SNP pair combinations on the microarray, however this is computationally intensive and would generate over 10 billion results ((106,467x106,467) – 106,467)! Interpretation of such results from a relatively small case-control study would also prove problematic. A more logical and less data intensive approach is to define sets of SNPs upon which to test pairwise interactions. An example of this is shown in table 2.11 for the SNPs in the thiopurine pathway tested against SNPs in the methylation pathway, using the same cohort of IBD patients separated by intermediate and normal TPMT activities. This was completed using the following command line, where ‘epi.txt’ is a text file that contains the thiopurine (set 1) and methylation (set 2) SNPs to be tested against each other. The use of “--epi1 0.01” instructs that only results significant below a P-value of 0.01 in set 1 are investigated. A P-value cut-off of 0.2 was used to ensure that all variants with a minor effect in the methylation SNP pathway would be included in the analysis:

“plink --bfile ibdpatientsgmh --pheno tpmtqc.txt --epistasis --set-test --set epi.txt --epi1 0.01 –epi2 0.2 --out ibdpatients_tpmt_epistasis”.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

At present it is not possible to adjust for covariates, including PCA, using this analysis.

Table 2.11: Epistatic interactions between SNPs in the TPMT gene (TPMT*3C, *3B, 2) and methylation pathway in a cohort of IBD patients with intermediate (n = 47) vs normal (n = 414) TPMT activity

Proportion # Sig # Valid Best χ 2 Best Chr SNP ID Sig of valid Best Chr Best SNP Epi tests test gene tests 6 TPMT*3C 7 72 0.097 3.20 14 MTHFD1 K134R 6 TPMT*3B 4 67 0.059 3.82 11 APIP rs1998603 6 TPMT 2 0 0 NA 0 1 SRM E261K Chr, chromosome; SNP ID, SNP identifier; #Sig Epi, significant number of epistatic tests (--epi2 0.2); #Valid tests (i.e. non-zero allele counts); Best χ2, best chi-squared statistic for this test; Best Chr, chromosome of best SNP; Best SNP, SNP identifier.

The outcome of the epistasis tests do not confirm a true interaction between a pair of SNPs but rather give an indication that there may be an interaction. The finding that TPMT*3C and TPMT*3B may be associated with SNPs in methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) and methylthioribulose-1-phosphate dehydratase (APIP) is interesting, since both of these genes are involved in the formation of SAM, the essential co-factor of TPMT (380, 381).

A more ideal approach to investigating for epistatic interactions would be to complete the tests on a gene-based level, as opposed to a SNP-based one. At the time of writing this thesis, PLINK did not accommodate gene-based tests of epistasis; however several platforms including ‘SKAT’ and ‘SKAT- O’ are in development for such analyses and in the future these may provide further depth and clarity to the results presented here (348).

To complete the analysis the best candidate SNPs from the above analyses were chosen and added to a logistic regression model to determine what proportion of the variance of each phenotype could be explained by the model. IBM SPSS Statistics version 21 (IBM, Portsmouth, UK) was used for the logistic regression modelling.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.4.3 Summary of exome chip analysis algorithm

Apply: Extract custom MAP Run 'zCall' algorithm and re-cluster rare Genotype call >97% and PED files from  variants. Calculate PCA MAF >0.05% GenomeStudio covariates HWE <0.000001

Dominant and Fisher's Exact tests: recessive Adjust for PCA, multiplicity 1. Reductionist and LD modelling of Unsupervised and pathway approach significant results analyses

2. Systems Whole pathway SNP-pairwise epistasis analysis using thiopurine and based approach Gene-based analysis methylation pathways

Logistic regression modelling Selection of best % phenotypic variance candidates explained?

2.5 Power calculations

Prof Cathryn Lewis provided advice on the sample sizes needed to provide adequate statistical power for the results presented in Chapters 3 – 8.

The power of a statistical test describes the level of probability with which a study will be successful in detecting a true effect. It is dependent on a number of factors, including the magnitude of the effect of the variable being studied, the sample size and study design, and the specified false- positive rate. Historically, for many small-scale studies, investigators have adopted values such as α

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

= 0.05 (to denote the threshold at which to call a result significant) and β = 0.20 (where β describes the probability of committing a type II error). Use of these values provides a power of 80%, which is considered an adequate trade-off between the sensitivity and specificity of the test (382). The power of a statistical test can be increased by increasing the size of the study sample, and by increasing the effect size by reducing the measurement error using more accurate phenotyping.

To test for differences between the means of variables (e.g. normalised thiopurine dose) in patients with and without thiopurine hypermethylation, 80% power to detect an effect of Cohen’s d = 0.5 (standardised difference between the means of the two groups) at an alpha level of 0.05, could be achieved by recruiting 50 patients to each group in a case-control study design. Similarly, 50 patients in each group was calculated to have 80% power to detect substantial differences in the rates of ADRs (e.g. 10% vs 35%) between the 2 groups, assuming an alpha level of 0.05. These calculations were completed using an on-line power calculation tool (http://www.dssresearch.com/toolkit/sscalc/size_a2.asp, accessed 17th August 2011).

For association analyses additional factors that affect statistical power have to be considered. These include the size of a genetic effect, the mode of inheritance, the disease or trait prevalence, the ratio of case to control individuals, allelic frequencies, and the extent of linkage disequilibrium between marker and trait loci (382). With respect to disease or trait prevalence, as it increases the power to detect association using a case/control design also increases, since there will be greater divergence in the frequency of causative alleles between case and control groups. The power of a case/control association analysis also changes as a function of the relative proportions of affected and unaffected individuals in the study population. The most ideal situation is to recruit an equal number of cases and control individuals. However, this is not always possible, particularly when recruiting patients with relatively rare ADRs such as pancreatitis from a single centre, as in this study. In this situation, recruiting more control individuals can still increase power. As described by McGinnis et al, recruiting three to five times the number of control individuals as compared to cases may be adequate (383).

In the current study, 80% power to detect association for a SNP allele with a frequency of 0.3, which confers a modest (1.7-fold) increased risk of thiopurine hypermethylation, could be achieved by recruiting 100 patients to each group in a case-control study, assuming an additive genetic model and an alpha level of 0.05. This power calculation was completed using the genetic power calculator in PLINK (http://pngu.mgh.harvard.edu/~purcell/gpc/cc2.html, accessed 17th August 2011).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2.6 Biochemical mechanism of allopurinol induced TPMT inhibition

2.6.1 Materials

All reagents and chemicals were of analytical grade and were supplied by Sigma-Aldrich Ltd. (Gillingham, UK) or Merck Chemicals Ltd. (Nottingham, UK).

2.6.2 Metabolism of MP, TX and oxypurinol in intact red blood cells

1.5 mL of aliquots of EDTA whole blood were placed in 1.5 mL microcentrifuge tubes and centrifuged at 12,000 rpm for 30 seconds. The plasma and top fifth containing the buffy coat, platelets and reticulocytes was removed and the RBCs washed twice with a sodium chloride 0.9% solution. 100 µL aliquots of packed RBCs were transferred using a positive displacement pipette to microcentrifuge tubes containing 150 µL of Earle’s balanced salt solution (EBBS, 18 mM phosphate (Pi) and 1 mg/mL glucose) and 50 µL of S-adenosylmethionine (SAM, 1 mg/mL, Sigma-Aldrich) at pH 7.4. 7.5 µL of 10 mM MP (final concentration 250 µM, Sigma-Aldrich) or 7.5 µL of 10 mM TX (final concentration 250 µM, Sigma-Aldrich) was added, before the samples were vortexed briefly and incubated in a water- bath at 37°C as described by Simmonds et al (384). Samples were incubated in triplicates for 0 h (controls), 2 h, 4 h or 6 h. At the end of the incubation period the samples were centrifuged for 30 seconds at 12000 rpm and the cell-free supernatant medium transferred to clean microcentrifuge tubes. The RBCs were then washed with EBBS prior to the addition of 25 µL of dithiothreitol (DTT, 10 mM, Sigma-Aldrich) followed by 65 µL of perchloric acid 15% (Sigma-Aldrich) and vortexed for 10 seconds. The samples were then centrifuged at 12,000 rpm for 2 minutes and the protein free supernatant transferred to clean microcentrifuge tubes. Both the protein free RBC supernatant and supernatant media, which was also treated with dithiothreitol and perchloric acid 15%, were then boiled at 100°C for 1 h. 75 µL of each was injected onto a reverse-phase (RP) high-performance liquid chromatography (HPLC) system and the concentration of MeMP measured (pmol/ L).

To determine if TX inhibited TPMT and thereby the formation of MeMP in RBCs incubated with MP,

100 µL of packed RBCs were suspended in 150 µL EBBS with 50 µL SAM (1 mg/mL in 0.01 N H2SO4, Sigma-Aldrich) and pre-incubated with 250 µM MP for 2 h. TX (250 µM, final concentration) or an equal volume of EBBS (controls) was then added and the incubation continued for up to 6 h. In the reciprocal experiment, RBCs were pre-incubated with 250 µM TX or an equal volume of EBSS, prior to the addition of 250 µM MP and the incubation continued for up to 6 h. The supernatant media and protein free RBC extracts were injected onto the HPLC system and the concentration of MeMP (pmol/ L) measured at 0 h (controls), 2 h, 4 h and 6 h.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

To determine if the active metabolite of allopurinol, oxypurinol, affected the formation of MeMP in RBCs incubated with MP, 100 µL aliquots of packed RBCs were incubated for 2 h at 37°C in 150 µL EBSS with 50 µL SAM, with either 250 µM MP alone or 250 µM MP with 250 µM oxypurinol (Sigma- Aldrich). 75 µL of the RBC extracts were prepared, injected onto the HPLC system and the concentration of MeMP measured (pmol/ L).

2.6.3 Reverse-phase high-performance liquid chromatography conditions

Protein free RBC and supernatant extracts were injected onto a 5 µm ODS-1 Hypersil column (250 x 3.2 mm) protected by an Uptight 2 µm “in-line” filter (Hichrom Ltd. Berkshire, UK) and a Spherisorb 10 µm ODS guard column (50 x 3.2 mm i.d.; Jones Chromatography Ltd. Mid Glamorgan, UK).

A Waters 996 Photodiode Array Detector attached to a Waters Alliance 2690 HPLC Separations Module (Waters Ltd. Hertfordshire, UK) was set to scan from a wavelength of 230 nm to 380 nm, with a reporting wavelength of 303 nm. Extracts were separated at room temperature at a flow rate of 0.5 mL/ min by a linear gradient elution running from 100% Buffer A (40 mM ammonium acetate adjusted to pH 5.0 with glacial acetic acid, Merck Chemicals Ltd.) to 20% Buffer B (80% methanol, 10% acetonitrile and 10% tetrahydrofuran, Merck Chemicals Ltd.) over 25 min, returning to 100% A for a further 6 min equilibration delay period prior to injection of the next sample.

2.6.4 Calculating the concentration of MeMP

A MeMP standard was made up to a concentration of 1 mM with double distilled water. The maximum UV absorbance was recorded on a PerkinElmer Lambda35 UV spectrometer (PerkinElmer Ltd. Seer Green, UK), after scanning between 230 nm and 310 nm. The concentration of the standard was confirmed by measuring the maximum absorbance of a 1/31 dilution of the 1 mM standard at pH 2. The exact concentration was calculated according to the Beer-Lambert Law (A = ɛʅc), using the extinction coefficient (ɛ) of MeMP at pH 2 (18.9 L mol-1 cm-1).

The standard response factor for MeMP (F) was calculated from the area given by the MeMP standard for an injection volume of 5 µL and the exact concentration calculated using the following formula:

1 푠푡푎푛푑푎푟푑 푐표푛푐푒푛푡푟푎푡푖표푛 × 푑푖푙푢푡푖표푛 × 5 µ푙 푖푛푗푒푐푡푖표푛 퐹 = 31 퐴푟푒푎 (× 106)

MeMP concentrations for a 75 µL injection were calculated from the peak area, multiplied by the standard response factor, using the following formula, which takes into account the packed cell

PhD Thesis Thiopurines in IBD Paul Andrew Blaker volume (PCV), the dilution (100 µL RBC +15 µL DTT + 65 µL perchloric acid 15%) and the fact that approximately 1/3 of the RBC is protein:

190 µ푙 푑푖푙푢푡푖표푛 − 0.33 × 푃퐶푉 1 [푀푒푀푃] = 푀푒푀푃 푎푟푒푎 × 퐹 × × 푃퐶푉 75 µ푙 푖푛푗푒푐푡푖표푛

The peak for MeMP was identified by retention time (3.6 minutes) and maximal absorbance (λmax 290).

2.6.5 Measurement of TPMT kinetic and inhibition constants in red cell lysates using tandem mass spectroscopy

200 µL aliquots of EDTA blood, from a healthy volunteer with wildtype TPMT activity, were placed in

96 deep well plates and lysed by the addition of 400 µL of 3 mM KH2PO4 (Merck Chemicals Ltd). Plates were vortexed on a multi-vortexer for 3 x 1 minute at medium speed. The plates were then spun at 3,600 rpm for 10 minutes at room temperature. 100 µL of the red cell lysates were then transferred to clean 96 deep well plates. 50 µL of a master mix containing 25 µL 150 mM KH2PO4 buffer pH 7.0, 5 µL SAM (1 mg/mL), 15 µL DTT (10 mM), 5 µL MP (118 mM) and either TX or oxypurinol in DMSO (Sigma-Aldrich) at final concentrations of 0 µM (controls), 10 µM, 100 µM, 200 µM, 500 µM, 1 mM, 2 mM, or 5 mM was added. Each concentration point was assayed in triplicate. The plates were vortexed and then incubated in a shaking incubator at 37°C for 4 h. After 4 h incubation, 40 µL of 100 mM zinc sulphate (Merck Chemicals Ltd.) and 500 µL of acetonitrile containing deuterated MeMP (1600 pmol/ 500 µL, Merck Chemicals Ltd.) was added to each well, as previously described by Breen (385). The plates were then spun down for 10 minutes at 3,600 rpm. 10 µL of the individual well contents was injected at a flow-rate of 0.175 mL/min onto a tandem quadrupole detector (Waters Ltd., TQD) mass spectrometry system controlled by MassLynx software (Waters Ltd.), with acquisition in the Multiple Reaction Monitoring (MRM) mode. The chosen mobile phase was 50% acetonitrile in deionized water. TPMT activity was expressed as pmol MeMP/ h/ mgHb.

The assay was replicated varying the concentration of MP (0 µM, 10 µM, 100 µM, 200 µM, 500µM, 1mM, 2mM, 5mM) for each concentration point of TX and oxypurinol.

Hb was measured by spectrophotometry using Drabkins reagent (Sigma-Aldrich). Briefly, 100 µL of

RBC lysate was added to 300 µL KH2PO4, creating a 1 in 4 dilution. 900 µL of deionised water was added to the mixture and the solution vortexed for 10 seconds. 200 µL of the solution was added to 2 mls of Drabkins reagent (1/11 dilution) and vortexed for a further 10 seconds. The mixture was

PhD Thesis Thiopurines in IBD Paul Andrew Blaker then left to rest for 15 minutes. The maximum absorbance of Hb was then measured at λmax 542 nm using a PerkinElmer Lamba35 UV/spectrometer. The average of three readings was taken and the concentration of Hb calculated using the equation:

Concentration Hb (mg Hb/ 100 µL) = Maximum absorbance x 1.613

(Where 1.613 is the factor calculated for a 1cm light path, and the 1 in 11 dilution. For reference see page 1132, chapter 23, of Clinical Chemistry, Principles and Technics, Bioscience Laboratories, 1974 (386)).

2.6.6 Measurement of urinary TX and oxypurinol levels in controls versus IBD patients receiving AZA alone or in combination with allopurinol

Twenty millilitres of urine was collected from each study participant (in groups 1 and 2 and from the 9 thiopurine naïve patients). In patients receiving AZA therapy, urine was collected 4 h after oral dosing. In 1 further patient receiving low dose AZA and allopurinol, urine was collected sequentially at 30 minutes, 1 h, 4 h, 6 h, 8 h, 10 h, 12 h and 20 h post oral dosing. 50 µL of urine from each subject was added to clean microcentrifuge tubes containing 450 µL of deionized water and vortexed for 10 seconds. 2 µL of diluted urine was then injected onto a Waters UPLC system (Waters Ltd., Acuity UPLC) at room temperature and separated at a flow rate of 0.2 mL/ min with 100% Buffer A (40mM ammonium acetate adjusted to pH 5.0 with glacial acetic acid, Merck Chemicals Ltd.) for 3.5 min prior to a linear gradient elution to 20% Buffer B (100% methanol, Merck Chemicals Ltd.) over 8.5 min, returning to 100% A for a further 3 min equilibration delay period prior to injection of the next sample. The PDA was set up to scan from a wavelength of 230 nm to 400 nm, with a reporting wavelength of 340 nm. The observed concentration of both urinary TX and oxypurinol was expressed as µmol / mmol creatinine. Levels of urinary TX and oxypurinol were compared between both groups 1 and 2, and with the 9 healthy control subjects.

For IBD patients receiving thiopurine therapy, TGN and MeMP measurements were taken at the same time as the urine collection and measured as the hydrolysed base in 0.5 mL EDTA whole blood according to the perchloric acid hydrolysis method modified from Dervieux and Boulieu (387). In this regard, 100 µL of DTT (100 mg/ mL) was added to the blood samples followed by 250 µL of perchloric acid 15%. The deproteinised samples were then centrifuged at 12000rpm for 2 minutes. Hydrolysis of the thiopurine nucleotides was subsequently achieved by boiling the supernatants at 100˚C in screw cap microfuge tubes. After cooling, each sample was spun down on a centrifuge and 2 µL of the mixture injected onto the Waters UPLC reverse phase system. TGNs and MeMP were measured simultaneously, and detected at 341 nm and 304 nm respectively by retention time and

PhD Thesis Thiopurines in IBD Paul Andrew Blaker maximal absorbance. For clinical purposes the PRL uses the therapeutic range 240 – 450 pmol/8x108 RBC for TGNs. In addition to thiopurine metabolies, TPMT activity was measured using the method previously described by Breen (385).

2.6 7 Power calculation for in-vivo study

For the in-vivo study, the a-priori power calculation was based on the data previously presented by Keuzenkamp-Jansen et al. (71). In this study TX was not detected in plasma from patients receiving intravenous MP alone. However, they did find an average of 2 µM TX in plasma 24 h after an infusion of MP given in combination with allopurinol. This gives an approximate Cohen’s d level of 2, meaning that 96% power could be achieved with a total sample size of 16 patients with a minimum of 8 in each group. We assumed a more conservative anticipated effect size (‘d’) of 1.5, meaning that to achieve 92% power we would need to recruit 11 patients in each group, with a total sample size of 22 patients.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Chapter Three: An examination of factors associated with thiopurine hypermethylation in patients with inflammatory bowel disease

3.1 Introduction

AZA and MP are the first line immunomodulators used in the management of IBD. However, approximately 45 – 50% of patients are unable to derive benefit from these therapies. This is partly due to the occurrence of ADRs, which lead to the cessation of therapy in up to 28% of patients (63). A further 20% of patients fail to achieve an adequate clinical response (388, 389).

To monitor patients during AZA/MP treatment, concentrations of the thiopurine metabolites, TGN and MeMP are measured. TGN concentrations > 235 pmol/ 8x108 RBC have been associated with improved treatment outcomes in IBD, whereas concentrations of MeMP > 5700 pmol/ 8x108 RBC have been associated with an increased risk of hepatotoxicity (157, 162, 178). Many AZA/MP nonresponders have an unfavourably high MeMP : TGN ratio, in which preferential production of MeMP appears to shunt metabolism away from the formation of TGNs (64, 154). This is known as thiopurine hypermethylation and was originally defined as a ratio of MeMP : TGN of ≥ 11 : 1 (64). These patients often have low concentrations of TGN and fail to achieve therapeutic concentrations despite dose escalation (64, 178). Rather, dose escalation is observed to lead to a disproportionate rise in the concentration of MeMP and thereby increase the risk of hepatotoxicity (64). Importantly, once identified this skewed drug metabolism can be circumvented and treatment response recaptured with the use of low dose AZA/MP (25 - 33% of a standard dose) in combination with allopurinol (typically 100 mg daily).

Since TPMT is responsible for the formation of MeMP, the traditional view is that ultra-high TPMT enzyme activity is responsible for elevated MeMP : TGN ratios and thiopurine non-response (176, 179, 180). This is refuted by the results of a recent national database study from New Zealand, which demonstrated that ultra-high TPMT activity is not the major reason for preferential MeMP production in most patients with a high metabolite ratio (177). However, this study was not restricted to patients with IBD and it did not account for the concomitant use of allopurinol. Moreover the influence of additional variables such as gender, age and the normalised dose of AZA/MP, on thiopurine hypermethylation was not explored.

The hypothesis of this study is that thiopurine hypermethylation is a common problem encountered in patients with IBD receiving AZA/MP therapy, which cannot be explained by RBC TPMT activity alone. Rather it results from a combination of additional influences including gender, age and the weight-normalised dose of thiopurine. Using a large well-characterised group of IBD patients

PhD Thesis Thiopurines in IBD Paul Andrew Blaker treated with AZA/MP at a single centre, the aim of this study was to determine the number of patients demonstrating thiopurine hypermethylation and to investigate for covariates associated with this phenotype.

3.2 Methods

Patients who had RBC thiopurine metabolites measured to monitor AZA or MP treatment were identified from the electronic patient records system at GSTT and from databases maintained by the PRL. Only patients attending the dedicated IBD clinics at GSTT with a confirmed diagnosis of IBD were eligible for inclusion. In the majority of patients data on sequential thiopurine metabolite levels were available. Patients receiving thioguanine or low dose AZA/MP with allopurinol co- treatment were excluded. In each case, clinical records and results were reviewed retrospectively to record data on demographics, type of IBD, pre-treatment RBC TPMT activity, thiopurine type and weight-normalised dose, haematological (haemoglobin (Hb), mean cell volume (MCV), mean corpuscular haemoglobin (MCH), platelet count, white blood cell count, neutrophil count, lymphocyte count) and biochemical (creatinine, alanine transaminase (ALT), alkaline phosphatase (ALP)) parameters taken at the same time as the thiopurine metabolite measurements.

3.2.1 Statistical analysis

Analyses were performed to determine the distributions of thiopurine metabolite profiles in patients with IBD. The relationship between patient groups with MeMP : TGN ratios < 11 and ≥ 11 and subgroups of ≥ 11 – 20, ≥ 20 – 40 and ≥ 40 with RBC TPMT activity and the normalised thiopurine dose was examined. Statistical analyses were conducted using GraphPad Prism version 5.04. Description of variables was in median and interquartile range (IQR), or mean and 95% confidence interval (CI). Fisher’s exact tests were performed to compare proportions of phenotype and were reported with OR and 95% CI. One way ANOVA was used to compare distributions between 3 groups. D’Agostino and Pearson normality tests were used to test whether data were normally or non-normally distributed. Subsequently, independent samples Student’s t-tests or Mann-Whitney U tests were used to evaluate differences between groups. Spearman rank correlations were used to examine the relationship between changes in the normalised thiopurine dose and thiopurine metabolite profiles. Spearman rank correlation was also used to test the association between thiopurine hypermethylation and the development of hepatotoxicity. Subsequently, receiver operator characteristic (ROC) curve analysis was used to determine the optimum cut-off points for TGN and MeMP concentrations and the MeMP : TGN ratio in predicting the development of hepatotoxicity (see methods section 2.2.1). Youden indices were calcaulted in MedCalc. Univariate

PhD Thesis Thiopurines in IBD Paul Andrew Blaker logistic regression was used to identify factors associated with thiopurine hypermethylation, with significant associations used in a forwards multivariate logistic regression model to determine the proportion of thiopurine hypermethylation that could be predicted. All tests were performed two- sided and P-values < 0.05 considered statistically significant.

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

3.3 Results

3.3.1 Distribution of thiopurine metabolite profiles in patients with IBD

583 patients (n = 289 males and n = 294 females) with IBD had a total of 2197 thiopurine metabolite measurements in the PRL over a 70 month period (2103 days, between 05/06/2007 and 08/04/2013). Of these 429 (73.6%) patients had a diagnosis of CD, 136 (23.3%) had UC and 18 (3.1%) had IBD-U. The mean age of patients receiving AZA/MP was 38.5 years (range 18 – 75). Of the 2197 metabolite measurements, 1799 (81.9%) were taken from patients receiving AZA, whereas 398 episodes related to treatment with MP (18.1%). The distribution of TGN concentrations, MeMP levels and MeMP : TGN ratios are shown in figure 3.1 (a-c). Less than half (41.1%) of thiopurine metabolite profiles demonstrated a TGN level within the therapeutic range (240 - 450 pmol/8x108 RBC), whilst 21.5% were above the therapeutic range and 37.4% were below it. 138 (6.3%) of MeMP concentrations were ≥ 5000 pmol/ 8x108 RBC. Prior to separation of patients according to their RBC TPMT enzyme activity, 12.2% (67 of 583 patients) of metabolite profiles were consistent with thiopurine hypermethylation (MeMP : TGN ≥ 11).

Therapeutic range 600

400 Mean = 331.9 Median = 286 Range = 0 - 2407

200

Number thiopurine Number metabolite episodes metabolite

0 0 500 1000 1500 2000 2500 TGN pmol/8x108 RBC

Figure 3.1 (a) Distribution of TGN concentrations in patients with IBD receiving AZA/MP (n = 2197).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

2000

1600

1200 Mean = 1286 Median = 453 Range = 0 - 39222 400

Number thiopurine Number 200 metabolite episodes metabolite

0 0 4000 8000 1200016000200002400028000320003600040000 MeMP pmol/ 8x108 RBC

Figure 3.1 (b) Distribution of MeMP concentrations in patients with IBD receiving AZA/MP (n = 2197).

1600

1400 Mean = 5.1 Median = 1.7 1200 Range = 0 - 169.5

1000 500 Thiopurine hypermethylation (12.2%) 400 300

Number thiopurine Number 200 metabolite episodes metabolite 100 0 0 20 40 60 80 100 120 140 160 MeMP : TGN ratio

Figure 3.1 (c) Distribution of MeMP : TGN ratios in patients with IBD receiving AZA/MP (n = 2197).

The median (IQR) concentrations of TGNs for metabolite profiles with (n = 269) and without thiopurine hypermethylation (n = 1928) were 220.0 pmol/ 8x108 RBC (162.0 – 300.5) and 298.0 pmol/ 8x108 RBC (200.0 – 440.0) respectively (P = <0.0001, Mann-Whitney U test). Whereas the median (IQR) MeMP concentrations were 4878.0 pmol/ 8x108 RBC (2984.0 – 7071.0) and 364.0 pmol/ 8x108 RBC (112.0 – 844.5) respectively (P = <0.0001, Mann-Whitney U test). The median (IQR)

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

MeMP : TGN ratio in the group with a ratio ≥ 11 was 19.28 (14.37 – 169.5) as compared to 1.29 (0.301 – 3.414) for the cohort with a ratio < 11 (P = <0.0001, Mann-Whitney U test).

3.3.2 Relationship between RBC TPMT enzyme activity and thiopurine hypermethylation

A total of 574 patients (98.5% of total cohort) with thiopurine metabolite profiles also had RBC TPMT enzyme activity measured in the PRL prior to the start of AZA/MP treatment. Low, intermediate and high (normal) RBC TPMT activity was observed in 0.2%, 13.7% and 86.1% of patients respectively (figure 3.2). 87 patients demonstrated ultra-high TPMT activity (> 40 pmol MeMP/ h/ mgHb). The median (IQR) RBC TPMT activity of patients with thiopurine hypermethylation (n = 67; 34.0 pmol MeMP/ h/ mgHb (29.0 – 38.0)) was not statistically different from the TPMT activity of patients without thiopurine hypermethylation (n = 507; 34.0 pmol MeMP/ h/ mgHb (32.0 – 37.0); P = 0.165, Mann-Whitney U test; figures 3.3 a-b). 4 of 67 patients (6%) with hypermethylation demonstrated TPMT activity within the intermediate range (11 – 25 pmol MeMP/ h/ mgHb).

LM IM HM

100

20 Number of patients of Number

0 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 TPMT (pmol MeMP/ h/ mgHb)

Figure 3.2 Distribution of RBC TPMT enzyme activity in 574 patients with IBD treated with AZA/MP. LM, low methylator (TPMT 0 – 10 pmol MeMP/ h/ mgHb); IM, intermediate methylator (TPMT 11 – 25 pmol MeMP/ h/ mgHb); HM, high methylator (TPMT ≥ 26 pmol MeMP/ h/ mgHb).

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

Hypermethylation

Normal Methylation

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 TPMT (pmol MeMP/ h/ mgHb)

Figure 3.3 (a) Comparison of RBC TPMT enzyme activity in IBD patients with (n = 67) and without thiopurine hypermethylation (n = 507). Whisker box-plots (minimum to maximum). Dotted red line denotes cut-point between intermediate and high TPMT activity.

thiopurinehypermethylation 80 Normal methylation 20 Hypermethylation Numberof patients 60 15

40 10

20 5

Number of patients of Number methylation normal

0 0 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32 34 36 38 40 42 44 46 48 50 52 54 56 58 60 62 64 66 TPMT (pmol MeMP/ h/ mgHb)

Figure 3.3 (b) Distribution of RBC TPMT enzyme activity in patients with (n = 67) and without (n = 507) thiopurine hypermethylation. Dotted red line denotes cut-point between intermediate and high TPMT activity.

Examination of all 2197 thiopurine metabolite profiles showed that there was a very weak negative and borderline significant correlation between RBC TPMT enzyme activity and the TGN concentration (spearman r = -0.080; 95% CI, -0.162 – 0.004; P = 0.055). Whereas there were weak and highly significant positive correlations between TPMT activity and the MeMP concentration (spearman r = 0.188; 95% CI, 0.106 – 0.267; P = < 0.0001) and the MeMP : TGN ratio (spearman r =

PhD Thesis Thiopurines in IBD Paul Andrew Blaker

0.203; 95% CI, 0.120 – 0.282; P = <0.0001). However, no such relationships existed when the 269 metabolite profiles with a MeMP : TGN ≥ 11 were tested in isolation.

There was no significant difference in the proportion of patients with ultra-high TPMT activity (> 40 pmol MeMP/ h/ mgHb) between those with or without hypermethylation (OR, 1.038; 95% CI, 0.526 – 2.048; for patients with a ratio ≥ 11; P = 0.914, 2-tailed Fisher’s exact test; figure 3.4).

100 18 21

80 IM HM UM 60 67 73

Proportion of patients (%) patients Proportion of 20

15 0 6 <11 11 MeMP : TGN ratio

Figure 3.4 Comparison of TPMT activity categories for patients with (n=67) and without thiopurine hypermethylation (n = 507).

To determine if those with a very high MeMP : TGN ratio were more likely to have high TPMT activity, patients with a MeMP : TGN ratio ≥ 11, were divided into three groups; MeMP : TGN ≥ 11 – 20 (n = 39), > 20-40 (n = 23) and > 40 (n = 5). The mean RBC TPMT enzyme activities for each group were 35.6 (95% CI, 33.6 - 37.6), 34.5 (95% CI, 31.5 - 37.5) and 34.4 (95% CI, 32.3 - 36.5) respectively, with no significant difference between groups (P = 0.705, One-way ANOVA; figure 3.5).

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P = 0.705 60

20 TPMT pmol/h/mg Hb TPMTpmol/h/mg

10 11-20 >20-40 >40 MeMP : TGN ratio

Figure 3.5 Scatterplot of RBC TPMT enzyme activities in patients with thiopurine hypermethylation separated into three MeMP : TGN ratio ranges. Red-lines denote mean RBC TPMT activity with error bars.

3.3.4 Relationship between the normalised thiopurine dose and thiopurine metabolites

Data on the normalised thiopurine dose (mg/ kg/ day) were available for 2117 (96.5%) of the 2197 thiopurine metabolite measurements. There was no correlation between the normalised dose and TGN concentrations (spearman r = -0.08; CI 95%, -0.076 – 0.011; P = 0.134; figure 3.6). However, there were moderate positive correlations between the normalised dose and MeMP concentrations (Spearman r = 0.379; 95% CI, 0.341 – 0.416; P = <0.0001) and the MeMP : TGN ratio (spearman r = 0.362; 95% CI, 0.323 – 0.400; P = <0.0001). To reduce confounding caused by pre-treatment dose adjustment for RBC TPMT enzyme activity, correlations were recalculated for each TPMT enzyme activity phenotype. The mean (95% CI) normalised thiopurine dose for patients with low (n = 4), intermediate (n = 328) and normal RBC TPMT activities (n = 1785) were 0.056 (range 0.056 – 0.056) mg/ kg/ day, 1.127 (range 1.075 – 1.179) mg/ kg/ day and 1.871 (range 1.846 – 1.896) mg/ kg/ day respectively. Splitting patients according to their TPMT methylator status did not improve the correlations between TGN concentrations, MeMP levels or the MeMP : TGN ratio (table 3.1).

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Table 3.1: Correlation between the normalised thiopurine dose (mg/ kg/ day) and TGN concentrations, MeMP levels and the MeMP : TGN ratio separated by TPMT methylator status

Intermediate TPMT Variant correlated High TPMT activity All TPMT activity activity with normalised thiopurine dose (n = 1975) (n = 2117) (n = 332)

TGN concentration No correlation No correlation No correlation

MeMP concentration r = 0.279, p = < 0.0001 r = 0.266, p = < 0.0001 r = 0.379, p = <0.0001

MeMP : TGN ratio r = 0.251, p = < 0.001 r = 0.242, p = <0.0001 r = 0.362, p = <0.0001

Intermediate TPMT activity (11-25 pmol MeMP/ h/ mg Hb); High (normal) TPMT activity (≥26 pmol MeMP/ h/ mg Hb).

2000

1500

RBC 8

1000 r = -0.08

500 TGN pmol 8x10 TGNpmol

0 0 1 2 3 4 5 Normalised thiopurine dose (mg/ kg/ day)

Figure 3.6 Correlation between the normalised thiopurine dose (mg/ kg/ day) and TGN concentrations (n=2117)

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To control for bias resulting from pre-treatment AZA/MP-dose adjustment, 1975 thiopurine metabolite profiles from patients with high (normal) TPMT activity were selected. Of the 1975 profiles, 251 (12.7%) demonstrated a MeMP : TGN ratio ≥ 11, consistent with thiopurine hypermethylation. The mean normalised dose of thiopurine was higher in patients with thiopurine hypermethylation (2.11 mg/ kg/ day) in comparison with patients exhibiting normal methylation profiles (1.83 mg/ kg/ day; mean difference 0.28 mg/ kg/ day; p = <0.0001, independent samples Student’s t-test). However, there was no difference in the mean normalised dose above a MeMP : TGN ratio ≥ 11, when MeMP : TGN ratios were categorised into MeMP : TGN ≥ 11 – 20 (n = 134), > 20 – 40 (n = 86) and > 40 (n = 31) (figure 3.7).

P = 0.122

P = 0.556

P = <0.0001 5

2 (mg/ (mg/ kg/ day) 1

Normalised thiopurine dose thiopurine Normalised 0 < 11  11-20 > 20-40 > 40 n = 1724 n = 134 n = 86 n = 31

MeMP : TGN ratio

Figure 3.7 Relationship between normalised dose of AZA/MP and thiopurine hypermethylation. Whisker box plots (minimum to maximum). Data controlled for pre-treatment RBC TPMT activity dose rationalisation.

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3.3.5 Relationship between a change in the normalised thiopurine dose and thiopurine metabolite profiles in patients with thiopurine hypermethylation

Of the 583 patients prescribed AZA/MP, dose changes were made in 159 (27%) patients. In these 159 patients it was possible to study the effect of a change in the normalised dose on TGN and MeMP concentrations and the MeMP : TGN ratio. Prior to adjustment for RBC TPMT enzyme activity, there were moderate-strong positive correlations between a change in the normalised thiopurine dose and both a change in TGN concentrations (r = 0.649, P = <0.0001, 95% CI 0.545 – 0.733, Spearman rank, figure 3.8 a) and MeMP concentrations (r = 0.576, P = <0.0001, 95% CI 0.458 – 0.674, Spearman rank, figure 3.8 b), and a moderate positive correlation with a change in the MeMP : TGN ratio (r = 0.360, P = <0.0001, 95% CI 0.212 – 0.492, Spearman rank, figure 3.8 c). Restricting the analysis to patients with high (normal) RBC TPMT activity (n = 113) improved the correlation between a change in the normalised dose and TGN concentrations (r = 0.660, P = <0.0001, 95% CI 0.537 – 0.755, Spearman rank, figure 3.8 d) and reduced the correlation with a change in MeMP concentrations (r = 0.518, P = <0.0001, 95% CI 0.364 – 0.645, Spearman rank, figure 3.8 e) and the MeMP : TGN ratio (r = 0.227, P = 0.0173, 95% CI 0.0354 – 0.402, Spearman rank, figure 3.8 f).

20 of the 159 patients demonstrated average metabolite profiles consistent with thiopurine hypermethylation. In this group there was a reduced positive correlation between a change in the normalised dose and a change in TGN concentrations (r = 0.492, P = 0.028, 95% CI 0.049 – 0.773, Spearman rank, figure 3.9 a) and improved (strong) correlations with a change in MeMP concentrations (r = 0.827, P = <0.0001, 95% CI 0.598 – 0.931, Spearman rank, figure 3.9 b) and the MeMP : TGN ratio (r = 0.753, P = <0.0001, 95% CI 0.455 – 0.900, Spearman rank, figure 3.9 c). There was no significant difference in the average change in normalised dose between patients with normal methylation profiles (0.72 mg/ kg/ day ± 0.04 SEM) and those with hypermethylation (0.916 mg/ kg/ day ± 0.14 SEM; P = 0.393, independent samples Student’s t-test). The median change in TGN levels was 105.5 pmol/ 8x108 RBC (IQR 40.32 – 249.8) for patients with normal methylation profiles in comparison with 86.5 pmol/8 x108 RBC (IQR 37.6 – 212.5) for patients with thiopurine hypermethylation, which was not statistically different (P = 0.662, Mann-Whitney U test). However, the median change in MeMP levels between groups was very significantly different (225.3 pmol/ 8X108 RBC, IQR -14.6 – 845.0, versus 5070.0 pmol/ 8x108 RBC; IQR 2245.0 – 6186.0, P = < 0.0001, Mann-Whitney U test), demonstrating a disproportionate rise in MeMP levels in patients with thiopurine hypermethylation following dose escalation (figure 3.10).

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3.8 a 3.8 d

1000 r = 0.649 500 r = 0.660

RBC

RBC 8 8 500 0

-500

TGN pmol/8x10 TGN

  -1000 -1000 -2 -1 0 1 2 3 -2 -1 0 1 2 3  normalised dose (mg/ kg/ day)  normalised dose (mg/ kg/ day)

3.8 b 3.8 e

10000 r = 0.576 4000 r = 0.518 RBC

RBC 2000

5000 8 8

0 0

-5000 -2000

-10000 -4000

MeMP pmol/8x10 MeMP

MeMP pmol/8x10 MeMP   -15000 -6000 -2 -1 0 1 2 3 -2 -1 0 1 2 3  normalised dose (mg/ kg/ day)  normalised dose (mg/ kg/ day)

3.8 c 3.8 f

100 r = 0.360 10 r = 0.227

50 0

0 -10

MeMP : TGN Ratio : TGN MeMP

  -50 -20 -2 -1 0 1 2 3 -2 -1 0 1 2 3  normalised dose (mg/ kg/ day)  normalised dose (mg/ kg/ day)

Figure 3.8 (a-c) Correlations between change in the normalised thiopurine dose and change in TGN levels (a), MeMP levels (b) and the MeMP : TGN ratio (c), all patients included. Figure 3.8 (d-f) Correlations between change in the normalised thiopurine dose and change in TGN levels (d), MeMP levels (d) and the MeMP : TGN ratio (f), restricted to patients with wildtype TPMT activity.

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3.9 a 3.9 b 600 r = 0.492 10000 r = 0.827

400

RBC RBC

8 5000 8 200 0

0 -5000

-200 -10000

TGN pmol/8x10 TGN

MeMP pmol/8x10 MeMP  -400  -15000 -2 -1 0 1 2 3 -2 -1 0 1 2 3  normalised dose (mg/ kg/ day)  normalised dose (mg/ kg/ day)

3.9 c 100 r = 0.753

MeMP : TGN Ratio : TGN MeMP  -50 -2 -1 0 1 2 3  normalised dose (mg/ kg/ day)

Figure 3.9 Correlations between change in the normalised thiopurine dose and TGN levels (a), MeMP levels (b) and the MeMP : TGN ratio (c), restricted to patients with thiopurine hypermethylation (n = 20).

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500 8000

MeMPpmol/ 8x10

400

RBC 6000 8 300 4000 200

8 2000 RBC

100 TGN pmol/ 8x10 TGN pmol/ 0 0 TGN TGN (TH) MeMP MeMP (TH) TGN TGN (TH) MeMP MeMP (TH)

Before dose increment After dose increment

Figure 3.10 The effect of dose change on TGN and MeMP concentrations in patients with (n = 20) and without (n = 113) thiopurine hypermethylation

3.3.6 The influence of gender on thiopurine metabolite profiles

The total cohort of 583 patients with IBD included 289 males and 294 females. After exclusion of patients without pre-treatment TPMT activity measurement, there were 286 males and 288 females. The median TPMT activity was significantly higher in males (34.5 pmol MeMP/ h/ mgHb, IQR 30.0 – 39.0) as compared to females (33.0 pmol MeMP/ h/ mgHb, IQR 28.0 – 36.8; P = 0.0022, Mann- Whitney U-test). In females the cumulative frequency curve of TPMT activity is shifted to the left in comparison with males suggesting that the range of TPMT activity is lower in females than males (figure 3.11). Paradoxically, median TGN concentrations were statistically higher in males (n = 1070, 291.0 pmol/ 8x108 RBC, IQR 196.0 – 437.3) as compared to females (n = 1123, 281.0 pmol/ 8x108 RBC, IQR 185.0 – 408.0, P = 0.049, Mann-Whitney U test), whereas median MeMP concentrations were very significantly higher in females (507.0 pmol/ 8x108 RBC, IQR 153.0 – 1626.0) as compared to males (408.0 pmol/8x108 RBC, IQR 128.0 – 1049.0; P = <0.0001, Mann-Whitney U test). Furthermore, of the 269 metabolite profiles consistent with hypermethylation, 169 were in female patients as compared to 100 from male patients, suggesting that hypermethylation is more common in females (P = <0.0001; OR 1.715, 95% CI 1.318 – 2.231, 2-tailed Fisher’s exact test). The higher MeMP levels and more common incidence of thiopurine hypermethylation in females was not explained by a higher average normalised dose of AZA/MP, since in this cohort the normalised dose was statistically higher in males (average normalised dose in males, 1.80 mg/ kg/ day versus 1.72 mg/ kg/ day in females; P = 0.0004,independent samples Student’s t-test). Furthermore, there was no difference in the mean normalised dose between males (2.11 mg/ kg/ day) and females (2.09 mg/

107

PhD Thesis Thiopurines in IBD Paul Andrew Blaker kg/ day) when the cohort was restricted to patients with thiopurine hypermethylation alone (P = 0.399, t-test).

400

300 Female Male 200

100 Number of patients of Number

0 0 20 40 60 80 TPMT (pmol MeMP/ h/ mgHb)

Figure 3.11 Cumulative frequency histograms of RBC TPMT enzyme activity in male (n = 286) as compared to female (n = 288) patients with IBD.

3.3.7 Thiopurine hypermethylation and the development of hepatotoxicity

To test the relationship between thiopurine metabolites concentrations and the development of hepatotoxicity, all 2197 thiopurine metabolite profiles were correlated with ALP (n = 2115) and ALT (n = 2115) levels. The ALP level showed a very weak negative correlation with the MeMP concentration (r = -0.112, P = < 0.0001, Spearman Rank correlation), however there was no correlation with TGN concentrations (r = 0.001, P = 0.961). ALT levels also showed a very weak negative correlation with TGN concentrations (r = -0.074, P = 0.001) but were positively correlated with MeMP concentrations (r = 0.079, P = <0.0001).

Further examination of ALT levels confirmed that hepatotoxicity as defined by an ALT level ≥ 3 times the upper limit of normal (CTC grade 2 toxicity; male > 90 IU/ L, female > 57 IU/ L), was observed in 47 (2.2%) cases, where there was no other cause for hepatotoxicity identified. The MeMP concentration was a significant predictor for the development of hepatotoxicity (AUC = 0.739; 95% CI = 0.669 – 0.809; p = < 0.0001), however the Youden index suggested that the optimum cut-off was a MeMP concentration >536 pmol/ 8x108 RBC, which provided a positive predictive value (PPV) of 3.3% and a negative predictive value (NPV) of 99.5% (figure 3.12 a).

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MeMP levels > 5700 pmol/ 8x108 RBC have previously been associated with AZA/MP mediated hepatotoxicity (162). In this cohort, of the 113 levels where MeMP concentrations were > 5700 pmol/ 8x108 RBC, 13 episodes were also associated with hepatotoxicity, suggesting a prevalence of hepatotoxicity where MeMP is > 5700 pmol/ 8x108 RBC of 11.5%. ROC analysis suggested that a MeMP > 5700 pmol/ 8x108 RBC predicted hepatotoxicity with a PPV and NPV of 8.3% and 98.7% respectively. Fisher’s exact test revealed that the odds ratio for hepatotoxicity when MeMP >5700 pmol/ 8x108 RBC was 8.20 (95% CI 3.939 – 17.070; P = <0.0001).

There was a weak positive correlation between the MeMP : TGN ratio and the presence of hepatotoxicity (r = 0.108, P = <0.0001, spearman rank). A MeMP : TGN >9.85 demonstrated a trend towards predicting hepatotoxicity (AUC = 0.654; 95% CI 0.564 – 0.744; p = 0.00072), with a sensitivity of 37.0%, specificity of 86.6%, PPV of 5.9% and a NPV of 98.4% (figure 3.12 b).

3.12a MeMP predicting ALT > 3x ULN 3.12b MeMP : TGN ratio predicting ALT > 3x ULN 100 100

80 80

60 60 AUC = 0.7390 AUC = 0.6541 40 p = <0.0001 40 p = 0.0007 Cut-off = > 536 Cut-off = >9.85

20 Sens = 83.8 20 Sens = 37.0% Sensitivity -% 100 Sensitivity Sensitivity -% 100 Sensitivity Spec = 54.8 Spec = 86.6% 0 0 0 20 40 60 80 100 0 20 40 60 80 100 100% - Specificity% 100% - Specificity%

Figure 3.12 (a-b) Receiver operator curve analysis of MeMP concentrations and the MeMP : TGN ratio in predicting hepatotoxicity.

3.3.8 Logistic regression model to predict thiopurine hypermethylation from demographic, haematological and biochemical data

Univariate logistic regression was performed to assess the impact of a number of factors on the likelihood that patients would demonstrate thiopurine hypermethylation, using data from the cohort of 2197 (n = 269 MeMP : TGN ≥ 11 : 1) thiopurine metabolite measurements in 583 patients with IBD. The regression was conducted on 14 independent variables to determine factors that should be used in a full logistic regression model, including; gender, age, normalised dose of thiopurine, RBC TPMT activity, Hb concentration, MCV, MCH, platelet count, WBC count, neutrophil count, lymphocyte count, creatinine, ALP and ALT levels (table 3.2).

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Table 3.2: Univariate logistic regression of factors associated with thiopurine hypermethylation.

95% CI Exp(B) Variable B S.E. Wald Df Sig Exp(B) Lower Upper

Gender -0.617 0.202 9.277 1 0.002 0.540 0.363 0.803

Age 0.19 0.006 12.043 1 0.001 1.019 1.008 1.030

Normalised 0.011 0.008 1.976 1 0.160 1.011 0.996 1.026 dose

TPMT 0.050 0.010 26.223 1 0.001 1.051 1.031 1.071 activity

Hb -0.077 0.251 0.094 1 0.759 0.926 0.566 1.514

MCV 0.002 0.001 3.323 1 0.072 1.002 1.000 1.003

MCH 0.128 0.064 4.016 1 0.045 1.136 1.003 1.287

Platelets 0.126 0.044 8.350 1 0.004 1.135 1.041 1.236

WBC -0.362 0.113 10.241 1 0.001 0.696 0.558 0.869

Neutrophil 0.058 0.259 0.051 1 0.822 1.060 0.638 1.763

Lymphocyte 0.343 0.304 1.273 1 0.259 1.410 0.776 2.560

Creatinine -0.020 0.007 8.198 1 0.004 0.980 0.967 0.994

ALP -0.011 0.003 13.167 1 0.001 0.989 0.983 0.995

ALT 0.022 0.004 27.671 1 0.001 1.022 1.014 1.030

Constant -5.247 1.420 13.665 1 0.001 0.005

B, estimated logit coefficient; S.E. standard error of the coefficient; Wald, Wald statistic ([B/S.E.]2); Sig, significance level of the coefficient; Exp(B), odds ratio of the individual coefficient.

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Of the variables included in univariate logistic regression, 10 demonstrated a P-value lower than 0.1 and therefore only these parameters were used in a multivariate logistic regression model (table 3.3). A test of the full model against a constant only model was statistically significant, indicating that the predictors as a set reliably distinguished between patients with normal methylation profiles and those with thiopurine hypermethylation (χ2 = 130.42, P = < 0.0001 with degrees of freedom (df) = 10). Overall the model explained between 6.4% (Cox and Snell R square) and 12.0% (Nagelkerke R square) of the variance in thiopurine hypermethylation. The sensitivity of the model was very poor at 2.0% with a specificity of 99.7%. The PPV and NPV of the model were 45.4% and 87.6% respectively.

Table 3.3: Multivariate logistic regression model of factors associated with thiopurine hypermethylation.

Exp(B) 95% CI Exp(B) Variable B S.E. Wald Df Sig Lower Upper

Gender 0.601 0.195 9.465 1 0.002 1.823 1.244 2.674

Age 0.21 0.005 14.752 1 0.001 1.021 1.010 1.032

TPMT 0.50 0.010 27.110 1 0.001 1.051 1.032 1.072 activity

MCV 0.001 0.001 2.168 1 0.141 1.001 1.000 1.003

MCH 0.143 0.062 5.334 1 0.021 1.154 1.022 1.303

Platelets 0.127 0.043 8.695 1 0.003 1.136 1.044 1.236

WBC -0.369 0.111 10.951 1 0.001 0.691 0.556 0.860

Creatinine -0.022 0.007 10.437 1 0.001 0.978 0.965 0.991

ALP -0.012 0.003 14.420 1 0.001 0.988 0.983 0.994

ALT 0.023 0.004 31.530 1 0.001 1.023 1.015 1.032

Constant -6.146 1.540 15.918 1 0.001 0.002

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3.4 Discussion

The results of this study demonstrate that thiopurine hypermethylation occurs in approximately 12% of patients with IBD treated with AZA/MP. This is 2% - 7% lower than previously reported by two large population studies investigating the incidence of skewed thiopurine metabolism (175, 177). However, these studies used a higher MeMP : TGN ratio to define hypermethylation (≥ 20), included patients receiving thiopurines for several different indications and did not exclude those receiving combination treatment with allopurinol. Furthermore, a prevalence of 12% is consistent with the previous findings of Smith et al in a smaller cohort of patients with IBD (390). The lower MeMP : TGN ratio used in the present study is based on observations that a ratio of ≥ 11 : 1 is associated with an increase in thiopurine resistance and drug toxicity (64, 154, 181, 390). Further validation for the use of this ratio is presented in Chapter 4.

The therapeutic range for TGN concentrations was defined as 240 - 450 pmol/ 8x108 RBC. The upper limit of the range is consistent with that used in other trials, although it lacks an evidence base and further studies correlating levels > 450 pmol/ 8x108 RBC with toxicity are required (391). The lower limit is derived from the recent literature, however previous work completed in the PRL suggests that there is no significant difference in remission rates between those with TGNs between 200 and 250 pmol/ 8x108 RBC and those between 350 and 400 pmol/ 8x108 RBC indicating that further prospective studies are needed to better define the therapeutic range (151, 152, 162, 178, 390, 392). Nonetheless, using the range 240 – 450 pmol/ 8x108 RBC, only 41.1% of TGNs were within the therapeutic range, whereas 37.4% were sub-therapeutic. The latter is likely due to either poor adherence to therapy and/or under-dosing. Such patients are at risk of non-response to thiopurines and may therefore benefit from patient education and dose escalation. Of concern is that 21.5% of patients demonstrated TGN levels above the therapeutic range, which has been associated with an increased risk of myelotoxicity (64, 157, 162).

The current work supports the earlier findings of van Egmond et al showing that a high MeMP : TGN ratio is not primarily due to high TPMT enzyme activity (177). The previous study demonstrated that the distribution of TPMT activity among patients with a high ratio (≥ 20) was similar to the distribution in patients with a normal ratio, however it was reported that the mean TPMT activity was significantly higher in the former group. Since TPMT enzyme activity is not normally distributed, it would be more appropriate to report differences in the median TPMT activity. The current study shows that there is no statistically significant difference in median TPMT activities between patients with or without thiopurine hypermethylation.

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It was previously suggested that high TPMT activity (≥ 35) is associated with a reduced response to treatment, presumably as a result of elimination of TGN precursors from the thiopurine activation pathway by methylation (150). However, the current study casts doubt on this by demonstrating that there is no difference in the proportion of patients with ultra-high TPMT activity (≥ 40) and MeMP : TGN ratios ≥ 11 versus < 11. Furthermore, subgroup analysis of MeMP : TGN ratios in patients with hypermethylation, showed that there was no difference in TPMT activity between groups. The lack of relationship between TPMT activity and metabolite profiles > 11 : 1 suggests that factors other than RBC TPMT enzyme activity may influence the development of thiopurine hypermethylation. A high MeMP : TGN ratio was observed in 6 patients despite intermediate TPMT activity. Such patients would not be expected to form high concentrations of MeMP, which may suggest intracellular trapping of methylated metabolites in RBCs as a potential mechanism for hypermethylation. More likely, these patients may have a wildtype TPMT genotype but apparent intermediate enzyme activity due to the effect of low MTHFR variants as previously described (254). However, in the study by van Egmond, 3 patients with low TPMT activity variants (*1/*3 or *1/*2) also demonstrated a MeMP : TGN ≥ 20.

This work investigated the influence of the normalised thiopurine dose on the occurrence of thiopurine hypermethylation. Consistent with the previous findings of Hindorf et al there was no correlation between the thiopurine dose and TGN concentrations, however there was a positive correlation with MeMP concentrations (393). In comparison with the Hindorf et al study, the correlation between the dose of thiopurine and MeMP concentrations was lower; however, this is likely to reflect the use of the use of the weight-normalised dose and adjustment for TPMT activity in the current study, which is likely to be more accurate.

The data reveal the novel finding that the normalised dose of AZA/MP is higher in patients with thiopurine hypermethylation as compared to those with normal methylation profiles. This is of interest since it suggests that if the dose of thiopurine is increased in patients with normal methylation profiles, a proportion of these may then reveal drug metabolism consistent with hypermethylation, although this was not specifically examined. However, in subgroup analysis the normalised dose of thiopurine did not explain variation in the MeMP : TGN in patients already demonstrating hypermethylation, suggesting the involvement of additional factors.

A disproportionate rise in MeMP concentrations upon dose escalation has been reported as a feature of thiopurine hypermethylation (394). However, this is based on the findings from a small sub- analysis of thiopurine-resistant patients with IBD (n = 7 of 51) demonstrating a preferential rise in MeMP concentrations and paradoxical reduction in TGNs following dose escalation (64). Using a

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker larger number of patients, the findings presented here add to this by showing that the correlation between a change in the normalised dose and changes in MeMP concentrations and the MeMP : TGN ratio are stronger for patients with thiopurine hypermethylation, as compared to those with normal methylation profiles. Furthermore, whilst the correlation between a change in the normalised dose and TGN concentration is reduced in patients with thiopurine hypermethylation, the average TGN concentration did not decrease from baseline, as previously reported (64).

Thiopurine hypermethylation appears to occur with greater frequency in female patients despite lower median TPMT activities and normalised doses of thiopurine in comparison with male patients. Furthermore, median TGN concentrations were generally lower in female patients. The earlier findings of Hindorf et al. confirm a gender difference in thiopurine metabolites, although in this study both TGN and MeMP concentrations were higher in females (393). The divergent results with respect to TGN concentrations may be due to the use of the weight-normalised dose in the current study. The reason for the gender difference remains unclear, however it has been noted that hepatic XDH activity is 21% higher in males as compared to females, which may indicate greater subtraction of MP from the pool available for methylation in males (269). Alternatively, differential expression of the enzymes involved in folate metabolism and consequently the production of the TPMT co-factor SAM, may play a role. This is suggested in a recent study showing that low MTHFR variants have opposing effects on TPMT activity in males and females (395). Furthermore, several consensus sites for steroid hormone receptors, including progesterone, oestrogen and androgen binding sites, have been reported in the betaine-homocysteine pathway, which is an alternative pathway involved in methionine and therefore SAM recycling (396).

The current study is underpowered to demonstrate a difference in RBC TPMT activity been males and females. Based upon previous work by Schaeffeler et al, which demonstrated 7% higher TPMT activity in males as compared to females in a cohort of 1222 healthy adults, an estimated cohort of 1500 patients is required to show a difference in median TPMT activities with 95% power at an α- level of 0.05 (Cohen’s d = 0.186). However, in a recent study of 6,496 patients the cumulative frequency distribution of RBC TPMT activity was shown to be lower in females than males, which provides support for the data presented here (397).

High levels of methylated metabolites have been associated with the development of hepatotoxicity, however this not a universal finding. In the original study by Dubinsky et al levels of MeMP > 5,700 pmol/ 8x108 RBC were reported to confer a 3-fold increased risk for the development of hepatotoxicity in children with IBD, and this was later confirmed in adults (64, 162). Furthermore, Shaye et al found that MeMP concentrations > 5,300 pmol/ 8x108 RBC were associated with a 5-fold

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker increased risk of hepatotoxicity, escalating to a 9-fold elevated risk with levels > 9,800 pmol/ 8x108 RBC (398). However, Gupta et al in a paediatric IBD population treated with AZA/MP did not find elevated MeMP concentrations in 60% of patients with hepatotoxicity, and 90% with high MeMP levels did not demonstrate hepatotoxicity (399).

In the current study, there was a significant correlation between MeMP concentrations and ALT levels. However, the optimum cut-point for predicting hepatotoxicity was 536 pmol/ 8x108 RBC, which is not clinically useful given that the median concentration in the whole cohort was 453 pmol/ 8x108 RBC. Furthermore, the sensitivity of MeMP levels > 5,700 pmol/ 8x108 RBC in predicting thiopurine-induced liver injury appears to be poor. Only 13 of the 47 cases of hepatotoxicity were associated with a MeMP level > 5,700 pmol/ 8 x108 RBC, which confers a sensitivity of 27.7%. The specificity of the test was 95.2%, with a PPV for drug-induced toxicity of 8.3% at this cut-off. Furthermore, in 88.5% of cases where MeMP levels were > 5,700 pmol/ 8x108 RBC no evidence of hepatotoxicity was observed. Using a MeMP : TGN ratio > 9.85 the sensitivity for predicting CTC grade 2 hepatotoxicity was marginally improved (37.0%), although the PPV was reduced (5.9%). These data suggest that hepatotoxicity is associated with higher MeMP levels; however this does not explain all cases of thiopurine-induced hepatotoxicity. Furthermore, the majority of patients with high MeMP concentrations do not develop liver injury. However, the current study may underestimate the true risk of hepatotoxicity associated with high MeMP levels, since there may be a lag between the occurrence of high MeMP concentrations and the development of drug-induced liver injury.

Univariate analysis suggested the involvement of 10 factors which may influence the development of thiopurine hypermethylation. These included gender, age, TPMT activity, MCV, MCH, platelet count, white blood cell count, creatinine, ALP and ALT. This is consistent with the findings of Waljee et al who demonstrated that thiopurine shunting could be predicted by a random forest algorithm using standard laboratory values and patient age (AUC of 0.797; 95% CI, 0.743 – 0.850) (400). However, in the current study, combining the factors associated with hypermethylation identified by univariate analysis into a logistic regression model, only explained 6.4 – 12% of the occurrence of hypermethylation. This suggests that additional factors are involved in the development of thiopurine hypermethylation. These are likely to be of genetic origin and are further explored in Chapters 5 and 6.

There are some limitations to the current work. Firstly, the majority of the analysis relied on all available metabolite ratios, instead of using the highest calculated ratio for each patient. The latter may be preferable as the highest ratio is more likely to reflect the completion of dose escalation, and

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker therefore the most relevant for classification. Secondly, patients not responding to treatment are more likely to be sampled for thiopurine metabolites. Since thiopurine hypermethylation has been associated with a lack of treatment response, the reported 12% prevalence of thiopurine hypermethylation may be an over-representation. Thirdly, there was no account for the use of 5- ASA drugs in the study group, which are suggested to influence thiopurine metabolite profiles (196). However, data presented in Chapter 4 suggests that there is no significant effect of 5-ASAs on TGN or MeMP concentrations.

In summary, thiopurine hypermethylation is a common problem encountered during AZA/MP therapy in patients with IBD. This skewed drug metabolism cannot be predicted by the absolute TPMT activity or the normalised thiopurine dose alone. The phenotype is characterised by a preferential rise in MeMP levels upon dose escalation and is associated with an increased risk of hepatotoxicity, although it is not the sole cause of thiopurine-induced liver injury. Genetic factors are implicated to underlie the majority of the variation in thiopurine hypermethylation.

Summary of main findings:

 Thiopurine hypermethylation is observed in approximately 12% of patients with IBD prescribed AZA/MP.  RBC TPMT activity alone does not explain thiopurine hypermethylation.  Thiopurine hypermethylation is more common in females vs. males.  The weight-normalised dose of thiopurine is higher in patients with thiopurine hypermethylation as compared to those with normal methylation profiles.  A disproportionate rise in MeMP levels is observed upon dose escalation in patients with hypermethylation.  MeMP levels >5,700 pmol/ 8x108 RBC are associated with an 8-fold increased risk of hepatotoxicity; however the positive predictive valve of this cut-off is poor (8.3%).

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Chapter Four: The influence of thiopurine hypermethylation on clinical outcomes in patients with inflammatory bowel disease

4.1 Introduction

Meta-analysis suggests that TGN levels < 230 - 260 pmol/ 8x108 RBC are associated with decreased rates of clinical response in patients with IBD (157). Furthermore, MeMP levels > 5,700 pmol/ 8x108 RBC have been associated with an increased risk of AZA/MP mediated toxicity (64, 162). Hence a MeMP : TGN ratio > 20 (5,700 / 260) has been proposed as the optimum cut-off to define thiopurine hypermethylation (177, 401, 402). However, there is little data to validate this assumption. Indeed, small studies assessing clinical response support a lower MeMP : TGN ratio of ≥ 11 : 1 to identify thiopurine hypermethylation (64, 181). Therefore larger studies are indicated to confirm this.

Response to thiopurines may be delayed for as long as 12 – 17 weeks after the start of treatment, despite thiopurine metabolites reaching steady-state levels within 4 weeks (149-151). This suggests that a metabolite profile at week 4 of treatment may be useful in predicting clinical outcomes after 12 weeks of therapy. This strategy is recommended in a recent retrospective analysis on the use of TGN monitoring to optimise thiopurine therapy in patients with IBD (390). However, the time taken to develop thiopurine hypermethylation and the value of a metabolite profile at 4 weeks in predicting this is yet to be explored. Early detection of thiopurine hypermethylation would be useful, since it would facilitate prompt introduction of low dose AZA/MP with allopurinol and circumvent months of futile and potentially harmful therapy.

In-vitro studies indicate the 5-ASAs may inhibit TPMT enzyme activity and therefore when used in combination with AZA/MP, these would be predicted to influence thiopurine metabolite profiles (191). This may explain the findings of de Graaf and colleagues who reported that MeMP levels and the MeMP : TGN ratio decrease following the addition of 5-ASA therapy (196). If confirmed, concomitant therapy with 5-ASAs may prove useful in the management of patients with thiopurine hypermethylation. Indeed such a combination may be preferable to co-prescription with allopurinol, given the rare but potentially life threatening complication of toxic epidermal necrolysis associated with this strategy (403).

The aims of this study were to firstly determine if a thiopurine metabolite profile at 4 weeks predicts thiopurine hypermethylation after 12 weeks of therapy. Secondly, to investigate the effect of concomitant 5-ASA therapy in patients with and without hypermethylation and finally to determine

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker if a MeMP : TGN ratio of > 11 : 1 is associated with lower rates of intervention free survival during the first 12 months of AZA/MP therapy.

4.2 Methods

4.2.1 Patients

Patients recruited to the IBD Pharmacogenetics study (REC, 12/YH/0172; R&D, RJ112/N179) and the Pharmacogenetics of AZA studies (MREC, 00/1/33 and LREC, 06/Q0707/84), who had RBC thiopurine metabolites measured to monitor AZA or MP treatment, were identified from the electronic patient records system at GSTT and from databases maintained by the PRL. Only patients attending the dedicated IBD clinics at GSTT with a confirmed diagnosis of IBD and naïve to treatment with anti- TNF-α antibody therapy were eligible for inclusion. Data on sequential thiopurine metabolite levels were available in the majority of patients. Patients receiving thioguanine or low dose AZA/MP with allopurinol co-treatment were excluded. In each case, clinical records and results were reviewed retrospectively to record data on demographics, sub-type of IBD, disease duration, previous surgery, normalised dose of thiopurine, average thiopurine metabolite profiles after 12 weeks of therapy and where available for comparison, profiles at 4 weeks, haematological and biological parameters and clinical outcomes during the first 12 months of therapy.

Patients were matched for RBC TPMT activity and separated into two groups according to whether the average of at least 2 thiopurine metabolite profiles between weeks 12 – 52 of therapy was ≥ 11 : 1 (thiopurine hypermethylation) or < 11 : 1 (normal thiopurine methylation). Groups were then compared using a case-control study design.

4.2.2 Determination of clinical response

Development of drug toxicity was defined using the common toxicity criteria (section 2.2.1). Success or failure to achieve intervention free survival during the first 12 months of therapy was assessed by 3 investigators (PB, PI, JDS) following discussion in the VBIC (section 2.2.1).

4.2.3 Statistics

The same statistical methods applied to the analyses in Chapter 3 (and described in section 2.2.2) were used in the current study. In addition, Kaplan-Meier survival analysis and Gehan-Breslow- Wilcoxon tests were used to demonstrate differences in clinical outcomes during the first 12 months of treatment. Differences in outcomes were investigated for patients with and without thiopurine hypermethylation and for patients with average TGN levels above or below a cut-off of 240 pmol/ 8x108 RBC.

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4.3 Results

4.3.1 Demographic comparison of IBD patients with and without thiopurine hypermethylation

A cohort of 273 patients with IBD was identified from the records of the PRL and the IBD clinics at GSTT. Of these, 181 patients (66.3%) demonstrated average MeMP : TGN ratios < 11 : 1 and were used as a control group that was compared to 92 patients (33.7%) with average MeMP : TGN ratios ≥ 11 : 1 (table 4.1).

Table 4.1: Demographic comparison between IBD patients with or without thiopurine hypermethylation.

n = 92 n = 181 patients patients with Level of Odds Ratio Parameter with Av MeMP : Av MeMP : TGN significance 95% CI TGN < 11 ≥ 11 1.54, Male : Female (n) 88 : 93 35 : 57 P = 0.097 * 95% CI = 0.923-2.572

Mean age at start of treatment 35.2 ± 0.95 38.3 ± 1.39 P = 0.0650 † 95% CI = -6.338 -0.179 (years) % Caucasian 1.433, (according to 75.7 (n = 137) 68.5 (n = 63) P = 0.203 * 95% CI = 0.822 – 2.499 electronic records) CD : UC : IBD-U 126 : 45 : 10 63 : 26 : 3 P = 0.625 ¥ Thiopurine type 1.446, 158 : 23 76 : 16 P = 0.296 * AZA : MP 95% CI = 0.722 - 2.896 Thiopurine dose mg/ 1.91 ± 0.03 2.09 ± 0.04 kg/ day. Mean ± P = 0.0011 95% CI = -0.296 - -0.076 SEM (range) (0.58 – 3.75) (0.96 – 2.96) Pre-treatment RBC

TPMT activity 35.5 ± 0.48 36.2 ± 0.71 P = 0.672 + mean ± SEM

median (IQR) 35 (32 – 38) 35 (32 – 40) % patients (n) 1.457, receiving 36.5 (66) 28.3 (26) P = 0.223 * 95% CI = 0.844 –2.514 concomitant 5-ASA

5-ASA (mg/ kg/ day) 49.57 ± 3.19 45.31 ± 3.77 P = 0.450 † 95% CI = -6.901 – 15.42 mean ± SEM

Pre-treatment Hb (g/ dL) 12.7 ± 0.14 12.7 ± 0.21 P = 0.825 † 95% CI = -0.533 – 0.427 mean ± SEM Pre-treatment MCV (fL) 87.2 ± 0.76 88.4 ± 1.09 P = 0.359 † 95% CI = -3.834 – 1.386 mean ± SEM Pre-treatment MCH (pg/ cell) 29.2 ± 0.30 29.5 ± 0.44 P = 0.549 † 95% CI = -1.368 – 0.726 Mean ± SEM

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n = 92 n = 181 patients patients with Level of Odds Ratio Parameter with Av MeMP : Av MeMP : TGN significance 95% CI TGN < 11 ≥ 11 Pre-treatment Platelets (x103 mm3) 342 ± 11.1 333 ± 16.2 P = 0.652 † 95% CI = -29.13 – 46.58 mean ± SEM Pre-treatment WBC (x109 cell/ L) 8.32 ± 0.30 8.21 ± 0.36 P = 0.829 † 95% CI = -0.870 – 1.086 mean ± SEM Pre-treatment neutro(x109 cell/ L) 6.1 ± 0.28 5.6 ± 0.33 P = 0.389 † 95% CI = -0.504 – 1.300 Mean ±SEM Pre-treatment lymph (x109 cell/ L) 1.4 ± 0.05 1.8 ± 0.10 P = 0.0007 † 95% CI = -0.552 - -0.152) mean ±SEM Pre-treatment eGFR 99.5 ± 2.22 100.7 ± 2.74 P = 0.734 † 95% CI = -8.483 to 5.974 mean ± SEM Pre-treatment creatinine (µmol/ L) 70.8 ± 1.39 68.2 ± 1.60 P = 0.240 † 95% CI = -1.770 – 7.118 mean ± SEM Pre-treatment ALP (iu/ L) 79.4 ± 2.88 73.2 ± 2.48 P = 0.165 † 95% CI = -2.528 – 14.96 mean ± SEM Pre-treatment ALT (iu/ L) 25.9 ± 4.46 25.1 ± 2.94 P = 0.906 † 95% CI = -12.40 – 13.98 mean ± SEM Pre-treatment CRP (mg/ L) 22.3 ± 3.56 11.2 ± 2.79 P = 0.0430 † 95% CI = 0.420 – 21.64 mean ± SEM 349.5 ± 12.4 264.8 ± 14.8 cAv TGN

mean ± SEM P = <0.0001 + 330.0 (247.3 – 227.6 (181.4 – median (IQR) 412.5) 331.8) 728.9 ± 51.1 5901 ± 439.2 cAv MeMP

mean ±SEM P = <0.0001 + 554.0 (279.0 – 5163 (2668 – median (IQR) 921.6) 7373) 21.0 ± 28.1 cAv MeMP : TGN 2.52 ± 3.03

mean ±SEM P = <0.0001 + 20.0 (11.9 – median (IQR) 1.62 (0.8 – 3.2) 32.3) RR 1.299, 95% CI = 1.026-1.645 % patients (n) with OR 1.820, 12 month 95% CI = 1.094 – 3.027 63.5 (115) 48.9 (45) P = 0.0269 * intervention free Sensitivity = 0.719 survival on AZA/MP Specificity = 0.416 PPV = 0.635 NPV = 0.511

*Two-sided Fisher’s exact test; † independent samples Student’s t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi-squared test; Av, average; 5-ASA, 5-amino salicylate; Hb, haemoglobin; MCV, mean corpuscular volume; MCH, mean corpuscular haemoglobin; WBC, white blood cell count; neutro, neutrophil

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker count; lymph, lymphocyte count; eGFR, estimated glomerular filtration rate; ALP, alkaline phosphatase; ALT, alanine transaminase; CRP, C-reactive protein; cAv, concentration average; RR, relative risk; PPV, positive predictive value; NPV, negative predictive value.

There was a 10 fold difference in the MeMP : TGN ratio between groups, providing confidence in the separation for further analysis (table 4.1). The normalised dose of AZA/MP was higher in patients with thiopurine hypermethylation (mean difference = 0.18 mg/ kg/ day, P = 0.0011; 95% CI = -0.296 - -0.076) and there was no difference in median RBC TPMT activity between groups. Furthermore, there was no difference in the number of patients receiving, or normalised dose of, concomitant 5- ASA therapy between groups (P = 0.450; 95% CI = -6.901 – 15.42). Interestingly, the pre-treatment lymphocyte count was higher in patients with thiopurine hypermethylation (mean difference = 0.4 x109 cells/ L, P = 0.0007; 95% CI = -0.552 - -0.152). As expected, a lower proportion of patients with thiopurine hypermethylation failed to achieve intervention free survival during the first 12 months of AZA/MP therapy in comparison with the control group (P = 0.0269; RR = 1.299; 95% CI = 1.026- 1.645).

4.3.2 Average time to reach thiopurine hypermethylation

In patients with thiopurine hypermethylation (n = 92) the median time to reach a metabolite ratio of MeMP : TGN of ≥ 11 was 12 weeks (figure 4.1). The majority of patients (83.7%) demonstrated thiopurine hypermethylation by week 12, confirming the utility of a thiopurine metabolite profile at 3 months of treatment. 15 patients (16.3%) patients demonstrated thiopurine hypermethylation after 12 weeks of treatment. In these 15 patients, the median time to reach thiopurine hypermethylation was 24 weeks.

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100

11  60

40 Median time to reach

hypermethylation % with patients

MeMP : TGN MeMP 20

0 0 20 40 60 Weeks

Figure 4.1 Percentage of patients with thiopurine hypermethylation (n = 92) reaching a MeMP : TGN ≥ 11 over time (weeks). Red bars denote mean with SEM.

4.3.3 Utility of thiopurine metabolite measurements at week 4 to predict steady-state metabolite profiles between weeks 12 – 52

Of the 273 patients, 139 (50.9%) were identified as having a thiopurine metabolite profile measured at 4 weeks of therapy in addition to at least 2 profiles between weeks 12 - 52, which allowed calculation of the average steady-state TGN and MeMP concentrations and MeMP : TGN ratio. Including all 139 metabolite measurements at week 4, there was a weak correlation between the TGN level at week 4 and the steady-state TGN level after week 12 (r = 0.211; 95% CI 0.0411 – 0.369; P = 0.0127, Spearman rank). Moderate correlations were observed between both the MeMP level (r = 0.369; 95% CI 0.212 – 0.509; P = <0.0001, Spearman rank) and the MeMP : TGN ratio (r = 0.450; 95% CI 0.301 – 0.577; P = <0.0001, Spearman rank) at week 4 and the steady-state MeMP level and MeMP : TGN ratio after week 12 (figure 4.2 a-c).

Of the 139 patients with thiopurine metabolite profiles at week 4, 53 (38.1%) patients demonstrated thiopurine hypermethylation after week 12 of treatment. There was a very significant difference in the MeMP : TGN ratios at week 4 between the group that showed thiopurine hypermethylation after week 12 in comparison with the 86 patients with normal methylation profiles after week 12 (14.01 vs. 3.06; P = < 0.0001, Mann-Whitney U-test). ROC analysis demonstrated that a MeMP : TGN ratio at 4 weeks of > 6.17 (AUC = 0.839; 95% CI = 0.762 – 0.917; P = <0.0001) could predict hypermethylation between weeks 12 – 52 of AZA/MP therapy (figure 4.2 d), with a sensitivity of

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75.4% (95% CI = 61.72% - 86.24%) and a specificity of 88.4% (95% CI = 79.65% - 94.28%). The likelihood ratio, PPV and NPV were 6.49 (95% CI = 3.6 – 11.9), 47.7% and 96.3% respectively.

a. Week 4 TGN vs. steady-state TGN b. Week 4 MeMP vs. steady-state MeMP

1500 20000

RBC

8 RBC 8 15000 1000

10000

500 12 - 52 weeks - 52 12 12 - weeks 12 52 5000

cAv TGN pmol/ 8x10 pmol/ TGN cAv 0 0 cAv MeMP pmol/ 8x10 pmol/ MeMP cAv 0 500 1000 1500 0 5000 10000 15000 20000 8 TGN pmol/ 8x10 RBC at 4 weeks MeMP pmol/ 8x108 RBC at 4 weeks

c. Week 4 MeMP : TGN vs. steady-state d. Week 4 MeMP : TGN predicting MeMP : TGN hypermethylation 80 100

80 60 60 40 40 AUC = 0.839 p = < 0.0001 Cut-off = > 6.17 12 -weeks 12 52 20

20 Sens = 75.4 Sensitivity - 100 % - 100 Sensitivity

Av MeMP : ratio TGN MeMP Av Spec = 88.4 0 0 0 20 40 60 80 0 20 40 60 80 100 MeMP : TGN ratio at 4 weeks 100% - Specificity%

Figure 4.2 Correlation between thiopurine metabolite profiles at week 4 as compared to steady- state profiles after week 12. a-c, red line denotes linear regression; grey dotted line, 95% CI of linear regression; d, ROC analysis.

4.3.4 Influence of concomitant 5-ASA therapy on MeMP levels in patients with and without thiopurine hypermethylation

The influence of concomitant 5-ASA therapy on thiopurine metabolite profiles was examined separately in the two groups of patients with and without thiopurine hypermethylation. Of the 181 patients with normal steady-state thiopurine methylation profiles, 66 (36.5%) patients were also receiving concomitant 5-ASA therapy. Of the 92 patients with thiopurine hypermethylation, 26 (28.3%) patients were co-prescribed 5-ASAs. There were no observable differences in TGN or MeMP

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker concentrations or the MeMP : TGN ratios in either group as a result of 5-ASA therapy (table 4.2 and 4.3).

Table 4.2: The effect of concomitant 5-ASA therapy in patients with normal steady-state thiopurine methylation profiles (n = 181).

n = 115, n = 66, Parameter Significance no 5-ASA + 5-ASA Normalised thiopurine dose 1.89 ± 0.04 1.93 ± 0.05 P = 0.396 † mg/ kg/ day mean ± SEM 5-ASA dose mg/ kg/ day 49.57 ± 3.19 mean ± SEM MeMP 691.4 ± 54.81 794.4 ± 102.8 mean ± SEM 568.0 (291.5 – 504.4 (222.0 – P = 0.764 + median (IQR) 896.0) 993.0) TGN 340.5 ± 14.1 365.1 ± 23.4 mean ± SEM 325.0 (245.0 – 343.9 (255.7 – P = 0.514 + median (IQR) 407.0) 435.3) MeMP:TGN ratio 2.3 ± 0.19 2.9 ± 0.62 P = 0.793 + mean ± SEM 1.7 (0.84 – 3.14) 1.5 (0.74 – 3.21) median (IQR)

† Independent samples Student’s t-test; +Mann-Whitney U test.

Table 4.3: The effect of concomitant 5-ASA therapy in patients with thiopurine hypermethylation (n = 92).

n = 66, n = 26, Parameter Significance no 5-ASA + 5-ASA Normalised thiopurine dose 2.12 ± 0.05 1.99 ± 0.09 P = 0.201 † mg/ kg/ day mean ± SEM 5-ASA dose mg/ kg/ day 45.31 ± 3.77 mean ± SEM MeMP 6369 ± 567.6 4689 ± 508.6 mean ± SEM 5869 (2904 – 4509 (2525 – P = 0.161 + median (IQR) 9266) 5874) TGN 280 ± 17.8 224 ± 25.2 mean ± SEM 270 (177.5 – 217 (182.5 – P = 0.113 + median (IQR) 338.8) 266.1) MeMP : TGN ratio 24.4 ± 2.1 24.9 ± 3.4 mean ± SEM 19.87 (11.57 – 20.01 (12.50 – P = 0.809 + median (IQR) 32.86) 32.19)

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4.3.5 Comparison of drug toxicity between patients with or without thiopurine hypermethylation

Adverse events related to AZA/MP therapy were recorded in 42 (15.4%) of the 273 patients. The most common side effects in this cohort were gastrointestinal intolerance (19/ 273; 7.0%) and hepatotoxicity (14/ 273; 5.1%). Myelotoxicity (WBC < 2.0 X109/ L, CTC grade 3 toxicity) was seen in 6 (2.2%) patients, joint pain in 2 and pancreatitis (amylase > 240 U/ L with typical symptoms) was reported in 1 (0.3%) in association with thiopurine hypermethylation. Hepatotoxicity was significantly more common in patients with thiopurine hypermethylation (OR 8.058; 95% CI 2.188 – 29.67; P = 0.0006). Consistent with the data presented in Chapter 3, only 12% of patients with thiopurine hypermethylation developed hepatotoxicity (table 3.5).

Table 4.4: Comparison of adverse events related to AZA/MP therapy in patients with or without thiopurine hypermethylation.

n = 181 normal n = 92 thiopurine OR Parameter thiopurine Significance hypermethylation (95% CI) methylation Gastrointestinal 0.686 14 5 P = 0.617 * intolerance (0.24 – 1.97) 8.058 Hepatotoxicity 3 11 P = 0.0006 * (2.188 – 29.67) 0.387 Myelotoxicity 5 1 P = 0.667 * (0.04 – 3.36) Joint pain 0 2 Pancreatitis 0 1

* 2-sided Fisher’s exact test.

4.3.6 The impact of thiopurine hypermethylation on intervention free survival during the first 12 months of AZA/MP treatment

Of the 273 patients treated with AZA/MP, 113 (41.4%) failed to reach the primary end-point of intervention free survival at 12 months from the start of therapy. This included 66/181 (36.4%) patients with normal thiopurine methylation profiles and 47/92 (51.1%) patients with thiopurine hypermethylation (table 4.5). In comparison with males, a greater proportion of females failed to reach the primary end-point (n = 113, 64% females versus 36% males). There was also a trend towards younger age and a shorter duration of disease being associated with a higher risk of treatment intervention at 12 months, which was also more commonly observed in patients with CD. Both MeMP levels and MeMP : TGN ratios were higher in patients failing to continue with AZA/MP

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker as monotherapy immunosuppression at 12 months. Of interest there was no difference in the TGN concentrations or median TPMT activity between the two groups. ROC analysis suggested an optimum MeMP : TGN ratio cut-off point for predicting failure to reach the primary end-point at 12 months of >2.26 (AUC = 0.577; 95% CI 0.507 – 0.647; P = 0.033; figure 4.3). However, this is not clinically useful, since the sensitivity at this level is only 65% (specificity 47.5%) with a PPV of 23.7%. At a MeMP : TGN ratio of ≥ 11 : 1, the sensitivity, specificity, PPV and NPV were 32.2%, 77.8%, 26.0% and 81.9% respectively.

Table 4.5: Comparison between patients demonstrating success or failure of intervention free survival during the first 12 months of AZA/MP therapy.

n = 160 AZA/MP n = 113 AZA/MP OR Parameter Sig responders failures (95% CI) 1.967 Male : Female 83 : 77 40 : 73 P = 0.0094 * (1.199 – 3.227) Age years 40.5 ± 1.05 37.6 ± 1.19 P = 0.0690 † (-0.211 – 6.063) mean ± SEM CD : UC : IBD-U 102 : 52 : 6 87 : 19 : 7 P = 0.0124 ¥ Median duration of 8 (4.0 – 15.7) 5 (3.0 – 10.0) P = 0.0030 + disease years (IQR) 1.170 Previous surgery 47 (29.4%) 37 (32.7%) P = 0.595 * (0.696 – 1.335) RBC TPMT activity 35 (32.0 – 38.8) 35 (32 – 38.8) P = 0.712 + median (IQR) Normalised dose thiopurine (mg/ kg/ 1.99 ± 0.03 1.92 ± 0.04 P = 0.178 † (-0.034 – 0.185) day) mean ± SEM cAv TGN pmol/ 327.4 ± 12.2 313.5 ± 23.8 8x108 RBC mean ± P = 0.409 + SEM 301.5 (226.8 – 300.4 (189.0 – 392.8) Median (IQR) 371.9) cAv MeMP pmol/ 2084 ± 242.9 2821 ± 360.7 8x108 RBC mean ± P = 0.055 + SEM 767.8 (337.7 – 1087 (465.5 – 4258) Median (IQR) 2652) Av MeMP : TGN 7.6 ± 0.85 12.5 ± 1.8 ratio mean ± SEM P = 0.033 + Median (IQR) 2.72 (1.10 – 8.75) 3.96 (1.42 – 15.33) Normal 1.820 methylation : 115 : 45 66 : 47 P = 0.027 * (1.094 – 3.027) Hypermethylation

*Two-sided Fisher’s exact test; † independent samples Student’s t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi-squared test

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Av MeMP : TGN predicting AZA/MP failure at 12 months 100

60 AUC = 0.577 40 p = 0.033 Cut-off = >2.21 20 Sens = 47.5 Sensitivity -% 100 Sensitivity Spec = 65.1 0 0 20 40 60 80 100 100% - Specificity%

Figure 4.3 ROC analysis showing the value of the average MeMP : TGN ratio in predicting failure of intervention free survival during the first 12 months of AZA/MP therapy (n = 113).

The majority of patients failed to reach the primary end-point due to escalation of treatment to anti- TNF-α antibody therapy (53/ 113; 46.9%). Twenty-seven (23.9%) patients were switched to a low dose thiopurine with concomitant allopurinol (figure 4.4).

Hospitalisation

Unexpected surgery

Switch to another immunomodulator Escalation to anti-TNF- alpha therapy Steroid maintenance

Patient choice

LDT/allopurinol

Figure 4.4 Interventions in patients with IBD failing AZA/MP therapy between weeks 12 – 52 of therapy (n = 113). LDT, low dose thiopurine.

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Clinician defined thiopurine treatment non-response was responsible for the majority of failures (83/ 113; 73.4%; figure 4.5). This corresponds with the number of patients escalating to anti-TNF-α antibody therapy.

GI toxicity

Pancreatitis

Clinician defined treatment non-response Hepatotoxicity

Myelotoxicity

Joint pain

Figure 4.5 Cause of AZA/MP treatment failures between weeks 12 – 52 of AZA/MP treatment.

Patients demonstrating thiopurine hypermethylation were more likely to fail AZA/MP monotherapy as first line immunosuppression during the first 12 months of therapy, in comparison with patients with normal methylation profiles (figure 4.6; P = 0.0088, Gehan-Breslow-Wilcoxon test). The difference in the number of treatment failures at 12 months was 15.7%.

P = 0.0088 100

40 free survival free Normal methylation (n = 181) 20 Hypermethylation (n = 92)

0 % with intervention patients 0 100 200 300 Days to treatment failure

Figure 4.6 Kaplan Meier comparison of intervention free survival during the first 12 months of AZA/MP therapy between patients with or without thiopurine hypermethylation.

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Since there was no difference in average TGN concentrations between patients with intervention free survival as compared to those requiring intervention, treatment failures were compared using a TGN cut-off of 240 pmol/ 8x108 RBC, which is recommended as the lower limit of the therapeutic range by the PRL. Kaplan-Meier analysis showed that patients with an average TGN levels < 240 pmol/ 8x108 RBC were more likely to fail AZA/MP monotherapy by 12 months in comparison with those where average TGN concentrations were ≥ 240 pmol/ 8x108 RBC (P = 0.0454; hazard ratio = 1.561; 95% CI 1.035 – 2.355; Gehan-Breslow-Wilcoxon test). The difference between groups in the number of patients failing to remain on AZA/MP monotherapy as first line immunosuppression at 12 months was 12.8% (figure 4.7).

P = 0.0454 100

40 TGN  240 pmol/ 8x108 RBC (n = 181)

free survival free 8 20 TGN < 240 pmol/ 8x10 RBC (n = 87)

0 % intervention with patients 0 100 200 300 Days to treatment failure

Figure 4.7 Kaplan Meier comparison of intervention free survival during the first 12 months of AZA/MP therapy between patients with average TGN levels above or below the lower limit of therapeutic range.

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4.4 Discussion

The results of this study suggest that thiopurine hypermethylation confers an increased risk of AZA/MP treatment failure during the first year of treatment. This supports the earlier findings of Dubinsky et al in a smaller number of patients with IBD (n = 51), which suggested skewed drug metabolism provides an explanation for resistance to MP (64). The data also validate the use of a MeMP : TGN ratio of ≥ 11 : 1 to define thiopurine hypermethylation, by showing this ratio is associated with 15.7% more treatment failures over 12 months and a 3.6-fold increased risk of hepatotoxicity.

Confirming the results presented in Chapter 3, the normalised dose of thiopurine was higher in patients with thiopurine hypermethylation. This is consistent with the observation that dose escalation in this group leads to preferential production of MeMP and therefore a rise in the MeMP : TGN ratio (64). Whilst not reaching statistical significance, female gender (P = 0.097) and older age (P = 0.065) also showed a trend towards an association with thiopurine hypermethylation. Hindorf and colleagues previously demonstrated that both TGN and MeMP concentrations were higher in children in comparison with adults prescribed thiopurines, indicating that the reverse relationship with respect to age might have been expected; however the influence of age on the MeMP : TGN ratio has not been specifically explored until now.

A higher pre-treatment lymphocyte count in patients with thiopurine hypermethylation is a novel finding. This may suggest that hypermethylation is associated with a higher rate of lymphocyte turnover. In this regard, negligible levels of MeMP ribonucleotides were reported in CD4+ lymphocytes sampled from kidney transplant patients receiving AZA (169). Whereas, high levels of MeMP ribonucleotides were observed in leucocytes derived from children with ALL, a condition in which high lymphocyte turnover would be anticipated (172). Direct measurement of thiopurine metabolite profiles in lymphocytes from patients with thiopurine hypermethylation as compared to normal methylation profiles would clarify this further.

The current work suggests that concomitant therapy with 5-ASAs does not influence thiopurine metabolite profiles. This is contrary to the findings of Lowry et al, who demonstrated that 4 weeks of combination AZA and mesalamine treatment resulted in a 25 – 30% rise in TGN levels from baseline in comparison with patients receiving AZA monotherapy, supporting the later findings of de Graaf et al (196, 404). However, whilst both of these studies were prospective, they were relatively small (n = 31 and n = 22, respectively), the analyses were restricted to 4 weeks and neither examined the weight-normalised dose of 5-ASA. Therefore the results presented here may be considered a

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker more accurate reflection of the effect of 5-ASAs on average thiopurine metabolite profiles. Furthermore, they are consistent with the observations from a large prospective study (n = 183), which failed to show an effect of 5-ASA therapy on MeMP and TGN concentrations. Therefore these data do not support a role for co-prescription of 5-ASAs as a strategy to circumvent thiopurine hypermethylation.

It has been proposed that measurement of thiopurine metabolite profiles at 4 weeks of treatment would allow optimisation of dosing before clinical response can be assessed at 3 – 4 months (390). The results presented here add to this by showing positive correlations between metabolite profiles at 4 weeks and profiles after 12 – 52 weeks. Moreover, a MeMP : TGN ratio of > 6.17 at week 4 accurately predicted the occurrence of thiopurine hypermethylation between weeks 12 – 52 (AUC = 0.839; 95% CI = 0.762 – 0.917). The sensitivity (75.4%) and specificity (88.4%) of this cut-off for predicting hypermethylation were relatively good, meaning that this ratio may be useful in clinical practice to identify patients that could benefit from early introduction of combination treatment with allopurinol. However, this does not appear to capture all patients with hypermethylation, given the delayed presentation (up to 52 weeks) in some individuals.

The incidence of ADRs reported in the current study (15.4%) is consistent with the recent literature (59). However, the true incidence of ADRs during the first 12 months of AZA/MP therapy is likely to be underestimated in this cohort, since patients developing toxicity before measurement of thiopurine metabolites were not captured. The 3.6-fold increased risk of hepatotoxicity in patients with hypermethylation is slightly higher than the risk reported by Dubinsky et al (3-fold increase) (162). This difference is likely to have arisen since the present work correlated hepatotoxicity with metabolite ratios ≥ 11 : 1, as opposed to MeMP levels > 5,700 pmol/ 8x108 RBC. Nonetheless, thiopurine hypermethylation does appear to provide an explanation for the occurrence of dose- dependent hepatotoxicity. The mechanism of MeMP mediated hepatotoxicity remains unclear, however, it may relate to perturbation of ATP pools with consequent oxidative stress, following inhibition of DNPS by MeTIMP (251). This may also explain why thiopurine induced hepatotoxicity improves upon combination treatment with allopurinol, which is associated with a dramatic reduction in MeMP concentrations.

In the original study by Dubinsky and colleagues, levels of MeMP were higher and TGNs lower in 37 patients with IBD failing to respond to AZA/MP, in comparison with 14 patients demonstrating an adequate clinical response (64). The current work expands upon this and demonstrates that an average MeMP : TGN ratio ≥ 11 :1 is associated with an increased risk of treatment failure during the first 12 months of therapy (51.1% vs 41.4%). Subsequently, the data estimate that treatment

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker response can be recaptured in an additional 15.7% of patients, by using combination treatment with allopurinol to circumvent skewed drug metabolism. Furthermore, the success of AZA/MP in maintaining a 12 month intervention free response rate of approximately 2/3 (58.6%) in patients with normal methylation profiles is consistent with the previous literature (58, 59). This provides some validity for the definitions of treatment failure used in this analysis (Section 2.2.1). However, additional prospective studies exploring differences in response in patients with thiopurine hypermethylation, using end-points such as trimesters of remission or mucosal healing, are warranted.

The lower limit of the therapeutic range used in this study is based upon experience in the PRL and meta-analysis (157). However, additional data are required, since the use of thiopurine metabolite monitoring to aid decisions regarding dose escalation has not been universally accepted (158). The current work supports the use of TGN monitoring with the finding that average TGN levels < 240 pmol/ 8x108 RBC are associated with a significantly decreased change of intervention free survival during the first 12 months of AZA/MP therapy. In addition the data suggest that an additional 12.8% of patients would continue to benefit from AZA/MP monotherapy if the average TGN levels were increased to ≥ 240 pmol/ 8x108 RBC. This is consistent with the findings of a small prospective study including 22 patients with treatment refractory CD, which reported that remission was achieved in 18 patients when TGN concentrations were increased above 250 pmol/ 8x108 RBC (178).

Retrospective collection of clinical outcome data in this cohort introduces the possibility of a bias in the interpretation of the results. However, whilst data was collected retrospectively, the success or failure of intervention free survival during the first 12 months of therapy was prospectively recorded in the medical notes, with each case discussed between 3 gastroenterologists in the VBIC as part of treatment monitoring and standard care. Furthermore, 12 month intervention free is recognised as a robust clinical end-point, which has been used in several recent studies focusing on IBD and is considered a harder end-point than other outcome measures such as physician global rating (405, 406).

In summary, thiopurine hypermethylation as defined by an average MeMP : TGN ratio of ≥ 11 : 1 is associated with decreased rates of intervention free survival during the first 12 months of therapy. Hypermethylation is also associated with an increased risk of hepatotoxicity and is unlikely to be circumvented following co-prescription with 5-ASAs. A metabolite ratio of > 6.17 at week 4 of treatment may be useful in identifying patients likely to develop thiopurine hypermethylation after week 12 of therapy. This ratio may therefore allow early intervention with low dose AZA/MP and allopurinol. Nonetheless, a marker of hypermethylation that can be used prior to the start of treatment would be preferable. This is further explored in Chapters 5 and 6.

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Summary of main findings:

 Thiopurine hypermethylation can be defined as a MeMP : TGN ≥ 11 : 1.  A ratio of MeMP : TGN ≥ 11 : 1 is associated with 15.7% more treatment failures during the first 12 months of AZA/MP therapy.  A MeMP : TGN ratio > 6.17 at week 4 of treatment is useful in predicting patients demonstrating thiopurine hypermethylation after week 12 of therapy. This may prove useful in the early identification of patients likely to benefit from combination treatment with allopurinol.  Concomitant 5-ASA therapy does not appear useful in circumventing skewed metabolite profiles.

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Chapter Five: A search for novel biomarkers predicting thiopurine hypermethylation using a candidate gene approach.

5.1 Introduction

Thiopurine hypermethylation is a major cause of toxicity and treatment non-response in patients with IBD prescribed AZA/MP. This skewed drug metabolism, which is characterised by a MeMP : TGN ratio of ≥ 11 : 1, cannot be explained by RBC TPMT activity or the dose of thiopurine alone, suggesting the involvement of other factors within the thiopurine pathway (Figure 5.1).

Figure 5.1 Summary of thiopurine metabolism. Abbreviations: AZA, azathioprine; MP, mercaptopurine; TUA, thiouric acid; MeMP, methylmercaptopurine; 8-OH-MeMP, 8-hydroxy- methylmercaptopurine; SAM, S-adenosylmethionine; SAH, S-adenosylhomocystine; TIMP, thioinosine monophosphate; MeTIMP, methylthioinosine monophosphate; TIDP, thioinosine diphosphate; TITP, thioinosine triphosphate; MeTIDP, methylthioinosine diphosphate; MeTITP, methylthioinosine triphosphate; TXMP, thioxanthosine monophosphate; TGMP, thioguanine monophosphate; TGDP, thioguanine diphosphate; TGTP, thioguanine triphosphate; GST, glutathione synthetase; TPMT, thiopurine-S-methyltransferase; MTHFR, methylene tetrahydrofolate reductase; XDH, xanthine dehydrogenase; AOX, aldehyde oxidase; HPRT hypoxanthine-guanine phosphoribosyltransferase; ITPase, inosine triphosphate pyrophosphatase; IMPDH, inosine monophosphate dehydrogenase; GMPS, guanine monophosphate synthetase; ABC, ATP binding cassette.

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Theoretically, reduced degradation of MP to TUA via the activity of XDH and AOX predicts a higher substrate concentration of MP available for methylation by TPMT, and thereby increased concentrations of MeMP. Furthermore, reduced XDH activity will attenuate the formation of 8- hydroxy methylmercaptopurine, leading to a rise in MeMP. Hence polymorphic variation in XDH and AOX which affects enzyme activity, or in MOCOS, which produces the essential molybdenum co- factor for these enzymes, is hypothesized to contribute to thiopurine hypermethylation. Alternatively, reduced MTHFR activity, which plays an important role in the production SAM, the methyl donor for TPMT mediated reactions, is hypothesized to protect against thiopurine hypermethylation. In this regard, the concentration of SAM was found to be proportional to the activity of MTHFR in lymphocytes sampled from healthy individuals (407). Meanwhile, reduced activity of ITPase may lead to trapping of the ribonucleotide intermediates TIDP and TITP, both of which are substrates for TPMT, forming an excess of methylmercaptopurine ribonucleotides and subtracting from the pool of TIMP available for the formation of TGNs. Therefore, it is hypothesized that low activity ITPA variants can also explain hypermethylation. Finally, ABC transporters are known to mediate efflux of methylated thiopurine metabolites, therefore attenuated transporter activity is hypothesized to cause cellular trapping of these compounds (108). MeTIMP has been shown to reduce ATP production and since GMPS is an ATP dependent enzyme, high levels of MeTIMP may diminish GMPS activity and thereby the formation of TGNs (251).

The aim of this study was to investigate for associations between polymorphic variations in key enzymes of the thiopurine pathway (other than TPMT) and thiopurine hypermethylation, in patients with IBD prescribed AZA/MP. To achieve this I completed a hypothesis driven candidate gene analysis using real-time PCR to investigate for associations between specific variants in XDH, MOCOS, AOX1, MTHFR, ITPA and ABCB5 with the presence or absence of thiopurine hypermethylation. This contrasts with the use of the exome microarray technology used in Chapters 6 and 7, which allows the simultaneous analysis of thousands of genetic variants within and outside of the known thiopurine and methylation pathways, in addition to facilitating novel whole pathway analyses.

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5.2 Methods

5.2.1 Patients

Samples originated from the IBD Pharmacogenetics (Research and Ethics Committee reference, 12/YH/0172; research and development reference, RJ112/N179) and the prospective pharmacogenetics of azathioprine studies (MREC, 00/1/33 and LREC, 06/Q0707/84). Patients were all Caucasian adults, gave written and informed consent and had IBD diagnosed by standard criteria. Individuals were selected and separated into two groups according to the presence or absence of thiopurine hypermethylation (MeMP : TGN ≥ 11). Inclusion criteria were as follows; i) receiving AZA/MP therapy for at least 12 weeks, ii) thiopurine metabolite profiles demonstrating adherence to therapy, and iii) RBC TPMT activity consistent with wildtype activity (≥ 26 pmol MeMP/ h/ mgHb. Exclusion criteria were as follows; i) concomitant treatment with allopurinol, and ii) non-Caucasian ethnicity. For each individual, clinical records and laboratory results were reviewed retrospectively to record data on demographics, type of IBD, RBC TPMT enzyme activity, prescribed dose of thiopurine and metabolite profiles.

5.2.2 Laboratory methods

Known coding region SNPs in XDH, MOCOS, AOX1, MTHFR, ITPA and ABCB5 with a Caucasian minor allele frequency of at least 0.02 were selected for genotyping. SNPs that encoded a non- synonymous change in amino-acid were preferred. For details of the SNPs selected see section 2.3.1 (table 2.2). Patients were genotyped using Taqman realtime PCR probes on a Stratagene Mx3005P RT-PCR instrument (Agilent Technologies UK Ltd. Winnersh, UK). For details of the PCR protocol see section 2.3.3.

5.2.3 Statistical analysis

Genotypes for each SNP were tested for departure from HWE and the frequency in the study population compared to those published for Caucasian individuals in the dbSNP database (http://www.ncbi.nlm.gov/projects/SNP/). Dominant and recessive models were used to test for association between the SNP minor allele and thiopurine hypermethylation. Fisher’s exact tests were used to test for differences between groups in a 2x2 contingency table using GraphPad Prism version 5.04 for Windows (GraphPad Software, San Diego, USA). Independent samples Student’s t- tests or Mann-Whitney U tests were used to determine group differences in means or medians dependent on whether data were normally distributed according to D’Agostino and Pearson normality tests. Since this was a hypothesis driven candidate gene analysis, associations with α- levels < 0.05 were considered statistically significant. However, it is accepted that is higher than the

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5.3 Results

168 patients were included in the analysis. The mean age was 42 years, (range 18 – 84) and 84 (50%) were female. 89 patients had CD (53%), 76 patients had UC (45%) and 3 patients had IBD unclassified (2%). 92 patients exhibited thiopurine methylation profiles with average MeMP : TGN levels < 11 : 1 and were used as a control group, which was compared to 76 patients with average MeMP : TGN levels ≥ 11 : 1 (table 5.1). The median RBC TPMT activity was lower in controls as compared to patients with hypermethylation, although the difference was only 1 pmol MeMP/ h/ mgHb (P = 0.049). Patients were matched for the prescribed dose of thiopurine. The median MeMP : TGN ratio in patients with hypermethylation was 10-fold higher than the control cohort suggesting an adequate separation for further analysis.

SNP genotyping was successful in greater than 99% of cases. All genotypes were in HWE and the allele frequencies measured in the study cohort were similar to those reported in the dbSNP database (table 5.2).

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Table 5.1: Demographic comparison of patients with and without thiopurine hypermethylation in the candidate gene analysis.

n = 92 patients with n = 76 patients with Significance Variable MeMP : TGN < 11 : 1 MeMP : TGN ≥ 11 : 1 Gender, female (%) 42 (45%) 42 (55%) P = 0.276 * Age, mean years 39.2 ± 15.3 45.1 ± 16.9 P = 0.019 † (range) (18 – 84) (18 – 84) TPMT activity pmol 34 ± 5.93 37 ± 7.69 MeMP/ h/ mgHb, (26 – 53) (26 – 73) P = 0.049 + mean ± SEM (range) Median 34 35 Thiopurine dose (mg/ 125 (37.5 – 300) 135 (25 – 300) P = 0.098 † day) mean (range) cAv TGN 323 259 pmol/ 8x108 RBC (69 – 1314) (0 – 621) P = 0.030 + mean (range) median 282.5 145.6 cAv MeMP 574 5812 pmol/ 8x108 RBC (0 – 3544) (558 – 20031) P = < 0.0001 + mean (range) median 466.9 5172.6 MeMP : TGN ratio 1.9 25.6 mean (range) (0 – 4.2) (11.1 – 153.8) P = < 0.0001 +

median 1.94 19.54

† Independent samples Student’s t-test; * Fisher’s exact test; + Mann-Whitney U-test.

Table 5.2: Allele frequencies in the study cohort compared to reported frequencies in dbSNP.

cDNA base Frequency in Frequency in study Gene change dbSNP database cohort XDH 837 C > T 0.02 0.05 XDH 1936 A > G 0.05 0.03 XDH 2107 A > G 0.05 0.04 XDH 2211 C > T 0.31 0.29 XDH 3030 C > T 0.23 0.22 XDH 3717 G > A 0.06 0.06 MOCOS 359 G > A 0.03 0.04 MOCOS 509 T > C 0.03 0.04 MOCOS 1072 A > C 0.03 0.05 MOCOS 2107 A > C 0.34 0.29 MOCOS 2600 T > G 0.10 0.10 AOX1 3404 A > G 0.16 0.14 MTHFR 677 C > T 0.33 0.33 MTHFR 1298 A > C 0.23 0.26 ITPA 94 C > A 0.08 0.10 ITPA 124+21 A > C 0.07 0.11 ABCB5 343 A > G 0.34 0.34

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Using dominant models of interaction there were no associations between any of the SNPs tested and thiopurine hypermethylation. However using a recessive model, a weak but significant association between the ABCB5 c.343G variant and the presence of thiopurine hypermethylation was observed (P = 0.048, OR 2.96, 95% CI = 1.067 – 8.206). To explore this further the entire cohort was separated according to the absolute MeMP level using a cut-off of 5000 pmol/ 8x108 RBC. In this regard, levels of MeMP < 5000 pmol/ 8x108 RBC were observed in 129 patients and levels ≥ 5000 were seen in 35 patients. There was a strong association between the ABCB5 c.343G variant in the homozygous recessive state and levels of MeMP ≥ 5000 (P = 0.0065; OR 4.119, 95% CI 1.522 – 11.147). Overall, the ABCB5 c.343G appeared to explain 26% of cases where MeMP levels were ≥ 5000 pmol/ 8x108 RBC.

In a dominant model of interaction, separating patients according to MeMP concentrations above or below 5000 pmol/ 8x108 RBC additionally suggested a weak effect of the MOCOS 2600 T > C variant in protecting against high MeMP levels (P = 0.027, OR 0.209, 95% CI = 0.047 – 0.924).

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Table 5.3 The association between each SNP and thiopurine hypermethylation.

Normal Hypermethylation methylation Gene SNP with SNP Significance OR (95% CI) with SNP (n = 76) (n = 92) 1.069 (0.379 XDH 837 C > T 83/9 69/7 1 – 3.018) 2.318 (0.593 XDH 1936 A > G 84/8 73/3 0.348 – 9.061) 2.639 (0.689 XDH 2107 A > G 83/9 73/3 0.228 – 10.117) 1.408 (0.765 XDH 2211 C > T 43/49 42/34 0.283 – 2.591) 0.812 (0.593 XDH 3030 C > T 59/33 45/31 0.527 – 9.061) 1.622 (0.613 XDH 3717 G > A 79/13 69/7 0.351 – 4.300) 0.688 (0.221 MOCOS 359 G > A 86/6 69/7 0.571 – 2.141) 0.7 (0.242- MOCOS 509 T > C 85/7 68/8 0.591 2.027) 0.810 (0.289 MOCOS 1072 A > C 84/8 68/8 0.794 – 2.270) 1.171 (0.637 MOCOS 2107 A > C 46/46 41/35 0.644 – 2.153) 2.074 (0.914 MOCOS 2600 T > G 70/22 66/10 0.113 – 4.708) 1.182 (0.593 AOX1 3404 A > G 66/26 57/19 0.727 – 2.355) 0.802 (0.435 MTHFR 677 C > T 45/47 33/43 0.535 – 1.476) 0.736 (0.400 MTHFR 1298 A > C 53/39 38/38 0.353 – 8.939) 1.369 (0.627 ITPA 94 C > A 77/15 60/16 0.434 – 2.990) 0.928 (0.427 ITPA 124+21 A > C 74/18 62/14 1.00 – 2.017) 0.946 (0.512 40/52 32/44 0.877 – 1.747) ABCB5 343 A > G 2.96 (1.067 86/6 63/13 0.048 – 8.206)

Statistics shown for the dominant models, except for ABCB5 rs2301641 where the recessive model is also shown in red.

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5.4 Discussion

This work demonstrated that there was an association between the polymorphism ABCB5 343 A > G and thiopurine hypermethylation. The association was strengthened when patients with MeMP levels above or below 5000 pmol/ 8x108 RBC were compared, suggesting that this variant may impair cellular efflux of methylated thiopurine metabolites. In contrast, the MOCOS 2600 T > C variant was weakly associated with protection from high MeMP levels, implicating a role for the TUA degradation pathway in this phenotype.

In a prospective cohort of 192 patients with IBD, Smith et al previously reported that the ABCB5 343 A > G polymorphism was associated with lower TGN concentrations and a lack of response to AZA therapy (329). This is consistent with the current work, since median TGN levels were significantly lower in the group with thiopurine hypermethylation. However, the previous study did not assess MeMP levels or the MeMP : TGN ratio and therefore the association between ABCB5 343 A > G and these parameters is a novel finding. Furthermore, as established in Chapter 4, thiopurine hypermethylation is associated with lower rates of intervention free survival, which could partly explain the association between this variant and treatment resistance.

The role of the ABC transporters in drug-resistance is increasingly acknowledged (408). However, the general mechanism for the transport of substrates by ABC transporters has not been fully elucidated. Structural and biochemical data support a model in which substrates bind to the transmembrane binding domain leading to conformational changes in the nucleotide binding domain, encouraging the binding of ATP molecules. Subsequently, this alters the conformational structure of the transmembrane binding domain, which forms a chamber with an opening at the opposite end of the protein and reduces the transporters affinity for the substrate, which is then released (409). Therefore polymorphisms which affect the conformational structure of either the transmembrane binding domain or the nucleotide binding domain of ABCB5 are predicted to affect transporter function. In this regard, ABCB5 343 A > G codes a change from a positively charged amino acid to a negatively charged amino acid within the cytoplasmic loop of the nucleotide binding domain. In silico analysis suggests that this is functionally relevant, since it is predicted to be deleterious to protein signalling and therefore transporter function (410).

There are no functional studies confirming that ABCB5 acts as a thiopurine transporter. However, overexpression of the ABCB5 gene in haematopoietic cells has been observed in patients with drug- resistant ALL, which supports a probable role (411). Moreover, ABCB5 has a wide range of substrates, including anthracyclines and camptothecins, and it is also expressed in hepatic cells, a major site of

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The finding that MOCOS 2600 T > C is weakly associated with protection from high MeMP levels should be interpreted with caution given the borderline significance of this result. Furthermore, Smith et al. did not show any association between SNPs in XDH, AOX1 or MOCOS and changes in thiopurine metabolite profiles (272). However, another SNP in MOCOS (2107 A > C, which is not in LD with 2600 T > C) was associated with a reduced occurrence of side effects during thiopurine therapy. Since high concentrations of MeMP are shown to confer an increased risk of thiopurine toxicity (Chapters 3 and 4), the findings of the current study may therefore be of relevance. In this regard, one would expect MOCOS 2600 T > C to increase degradation of MP or MeMP to TUA or 8-methyl MP respectively, although to date this variant has not been functionally characterised.

Polymorphic variation in XDH did not appear to explain thiopurine hypermethylation. This is of interest since inter-individual non-pathogenic variation in XDH activity has been described in phenotyping studies, with approximately 20% of Caucasians displaying reduced activity (269). In cell lines XDH rs17011368 (Ile703Val) confers a 30% reduction of Vmax, however the in-vivo effect of this and other polymorphisms in the XDH gene on thiopurine metabolism has not been fully evaluated (270). Furthermore, variation in XDH activity due to polymorphic variation in the gene promoter region has not been accounted for in the present work. Direct correlation between thiopurine metabolite levels and XDH activity would therefore be ideal. However, since XDH is highly expressed only in the gut and liver, obtaining adequate samples for correlation with sequential metabolite profiles may prove problematic.

The lack of association between AOX1 3404 A > G and an effect on thiopurine metabolite profiles is consistent with the previous work by Smith et al. (272). It was proposed that inter-individual variability in TGN measurements may have accounted for the finding that AOX1 3404 A > G predicted non-response to AZA therapy despite no difference in TGN levels between treatment groups. However, the current results suggest that the risk of treatment non-response conferred by AOX1 3404 A > G may occur independently of an influence on MeMP and TGN levels.

The current work refutes the hypothesis that ITPase deficiency contributes to the metabolite profile by increasing the concentration of methylated metabolites (MeTIDP and MeTITP). This contradicts the results from a study of 244 children with ALL, which reported that the ITPA 94 C > A genotype was associated with increased blood levels of MeMP but not TGNs (301, 414). The divergent results may be accounted for by differences in the haematopoietic cell populations between patients with

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IBD and ALL, however further studies to assess the effect of polymorphisms in ITPA on thiopurine metabolite profiles are warranted.

Functionally relevant polymorphisms in the MTHFR gene did not explain thiopurine hypermethylation. However, whilst activity of MTHFR has been shown to influence SAM levels, it is not the only factor affecting its bioavailability (407). Indeed, dietary folate intake and polymorphic variation in other SAM-dependent methyltransferases, are additionally hypothesized to influence concentrations of SAM and thereby the methylation capacity of TPMT (249). The effect of polymorphic variation in other genes related to methylation capacity on thiopurine metabolite profiles is further explored in Chapter 6.

At the present time the findings in this study must be interpreted with caution, due to the borderline significance of the results, and confirmation should be sought in independent cohorts. In addition, the strongest association, which was shown between ABCB5 343 A > G and MeMP levels greater than 5000 pmol/8x108 RBC, only explained 13% of the apparent heritability. This suggests that thiopurine hypermethylation may be a complex trait, which occurs as a result of metabolic flux due to polymorphic variation in the activity of several different enzymes in the thiopurine and methylation pathways acting in concert. A novel way to examine this further is whole pathway analysis using an exome-wide approach, which is described in Chapter 6.

Summary of key findings:

 Recessive inheritance of the ABCB5 343 A > G polymorphism is associated with the development of thiopurine hypermethylation and high MeMP concentrations.  The strong association between ABCB5 343 A > G and MeMP levels > 5000 pmol/ 8x108 RBC suggests that ABCB5 may act as a transporter of methylated thiopurine metabolites.  Polymorphic variation in XDH, AOX1, MTHFR and ITPA does not appear to explain thiopurine hypermethylation.  Polymorphic variation in MOCOS (2600 T > C) is weakly associated with protection from high MeMP concentrations.  Additional genetic variants are implicated in the aetiology of thiopurine hypermethylation.

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Chapter Six: A search for novel biomarkers predicting thiopurine hypermethylation and treatment response using an exome-wide approach.

6.1 Introduction

A cut-off of >230 – 260 pmol TGN/ 8x108 RBC has been proposed as the lower limit for clinical efficacy in the management of IBD (157). In contrast, high concentrations of the other major thiopurine metabolite, MeMP, have associated with the development of both hepatotoxicity and myelotoxicity (162, 164). Consequently, a high MeMP : TGN concentration ratio indicates an increased risk of AZA/MP treatment failure and ADRs (64, 415, 416). This is anticipated to occur in approximately 12% of patients with IBD prescribed AZA/MP (Chapter 3). Importantly, once identified, this skewed drug metabolism can be resolved by using low dose AZA/MP in conjunction with allopurinol. Therefore it is anticipated that markers predicting this phenotype prior to the start of treatment would be useful in clinical practice.

The mechanism underlying preferential thiopurine methylation remains unknown. Paradoxically, it does not appear to relate to high TPMT activity, as was originally hypothesized (64, 150) Analysis of polymorphic variation in candidate genes implicates a role for the ABCB5 transporter; however this only explains a small proportion of the heritability (Chapter 5) (417). Meanwhile other groups have proposed that reduced IMPDH activity could restrict the formation of TGNs and explain a high MeMP : TGN ratio (210). However, whilst IMPDH activity is inversely correlated with the concentration of MeTIMP, it is not associated with a change in TGN concentrations, suggesting that the situation is more complex (418). In this regard, inter-individual variation in thiopurine metabolite profiles, and thereby clinical response, is likely to arise from differences in metabolic flux through several different enzymes within the thiopurine pathway or via external pathways which influence it.

The hypothesis of this study was that variants other than ABCB5 c.343 A > G within and external to the thiopurine and methylation pathways would provide additional explanations for thiopurine hypermethylation and treatment response in patients with IBD. Furthermore, novel whole pathway modelling was predicted to explain a greater proportion of the heritability than single genetic polymorphisms alone. The aim of the study was therefore to explore the genetic basis of thiopurine hypermethylation and treatment response. Using an exome microarray, which focuses on functionally relevant coding region polymorphisms, we performed a genetic analysis on blood samples from thiopurine experienced patients with IBD and related the findings to metabolite concentrations and treatment outcomes during the first 12 months of therapy.

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6.2 Methods

6.2.1 Patients

Patients were recruited from the IBD Pharmacogenetics Study at GSTT (Research and Ethics Committee reference, 12/YH/0172; Research and Development reference, RJ112/N179). All patients were adults and provided written and informed consent. Of the 763 patients with IBD diagnosed by standard criteria, 472 had received treatment with AZA/MP. In each case, clinical records and results were reviewed retrospectively to record data on demographics, type of IBD, pre-treatment RBC TPMT activity, thiopurine type, weight-normalised dose, treatment outcomes and haematological and biochemical parameters taken at the same time as thiopurine metabolite measurements as part of standard treatment monitoring. 305 of the 472 patients demonstrated treatment adherence and had data on average thiopurine metabolite concentration ratios. Using a case-control design this group was split according to the presence or absence of an average metabolite profile, derived from at least 2 measurements taken after 12 weeks of therapy, consistent with thiopurine hypermethylation (MeMP : TGN ≥ 11 : 1).

Investigating for genetic variants associated with thiopurine hypermethylation by defining cases and controls based on their metabolite concentration ratio, may be an over-simplification of the metabolism involved. Indeed, the balance of MeMP is likely to be formed by entero-hepatic metabolism, whereas TGNs are thought to be preferentially formed in the bone marrow (98, 169, 419). Therefore it follows that the formation of MeMP and TGN may be influenced by different genetic mechanisms in the two compartments. To investigate for such effects, two further groups of patients were identified from the IBD Pharmacogenetics cohort. The first of these was separated into cases and controls using a cut-off of average MeMP levels ≥ 5000 pmol/8x108 RBC to define a case and < 5000 pmol/8x108 RBC to define a control (n = 356 of 472). The second of these was separated into cases and controls using a cut-off of average TGN levels < 240 pmol/8x108 RBC to define a case and ≥ 240 pmol/8x108 RBC to define a control (n = 348 of 472). In this second cohort, patients with an average TGN level < 100 pmol/8x108 were excluded to reduce miscalling of individuals due to poor treatment adherence. Both cohorts were matched for median TPMT activity.

329 of the 472 patients had full data describing AZA/MP treatment response during the first 12 months of therapy and were discussed by three investigators (PB, PI and JDS) in the VBIC as part of standard treatment monitoring. This group was separated according to the success or failure to achieve 12 month intervention free survival, as described in Section 2.2.1.

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6.2.2 Illumina human exome beadchip

Genomic DNA was extracted from EDTA blood samples taken from each patient and normalised to a concentration of 50 ng/ µL, as described in Section 2.3.2. 10 µL of each individual sample was stored in a separate well on 96 well plates and stored at -20˚C until use. Subsequently, DNA samples were prepared and applied to Infinium Human Exome 250K Beadchips (Illumina) by the BRC, Guy’s Campus, King’s College London, as described in Section 2.3.5. The chips were scanned using an Illumina iScan microarray scanner and data entered into Genome Studio (Illumina), prior to genetic analysis using PLINK (340).

6.2.3 Statistical analysis

Description of variables was in median and interquartile range (IQR), or mean and 95% confidence interval (CI). Independent samples Student’s t-tests or Mann-Whitney U tests were used to determine group differences in means or medians dependent on whether data were normally distributed according to D’Agostino and Pearson normality tests. Fisher’s exact tests were performed to compare proportions of phenotype and were reported with odds ratio (OR) and 95% CI. 3 by 2 Chi square tests were used to compare proportions of phenotypes between 3 groups.

The algorithm used to interrogate the genetic data is described in Section 2.4 (summarised in Section 2.4.3). In summary, the raw data from Genome Studio was re-clustered using the ‘zCall’ algorithm and PCAs calculated to allow for population stratification. Thresholds for genotype call rate of > 97%, MAF of > 0.05% and HWE of P = < 1x10-6 were applied to the cleaned dataset prior to analysis using PLINK. Each phenotype was subsequently treated to an unsupervised trait-SNP association analysis, with modelling to account for dominant and recessive effects following adjustment for PCAs. The analysis was then restricted to the thiopurine and methylation pathways to allow whole pathway analysis, gene-based analysis and SNP-pairwise epistasis. An additional pathway containing polymorphisms relevant to insulin signalling was used as a control. Following these analyses, the best candidate SNPs were combined in a forwards logistic regression model to determine the variance that could be explained for each phenotype tested using the case-control design.

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6.3 Results

6.3.1 Cohort of adult patients with IBD receiving AZA/MP

Of the 763 adult patients with IBD, 472 (61.9%) were prescribed thiopurines (table 6.1). The majority receiving AZA/MP had a diagnosis of CD (330/472). TPMT levels were measured in 76.3% of patients prior to the start of AZA/MP therapy. The proportion of patients with normal or intermediate TPMT activity in this cohort was representative of the general population. The average normalised dose of AZA/MP was lower than the recommended dose in patients with wild-type TPMT activity (2 – 2.5 mg/ kg) and it was at the lower end of the recommended range in those with intermediate TPMT activity (1 – 1.5 mg/ kg). Despite the lower normalised dose of AZA/MP in patients with intermediate TPMT activity, median TGNs were higher in this group as compared to those with wildtype TPMT activity (320 pmol/8x108 RBC vs 295 pmol/8x108, P = 0.029, Mann- Whitney U-test). Predictably, average MeMP levels were highest in patients with wildtype TPMT activity. 79 of the 374 (21.1%) patients with data available on average thiopurine metabolite levels demonstrated median MeMP : TGN concentration ratios ≥ 11 : 1, consistent with thiopurine hypermethylation (figure 6.1). Failure to achieve intervention free survival during the first 12 months of AZA/MP therapy was observed in 141 (29.8%) of patients.

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Table 6.1: Demographics of adult patients with IBD prescribed AZA/MP

Variable Result Total number of patients prescribed AZA/MP 472/763 (61.9%) Prescribed AZA, n (%) 398 (84.3%) Prescribed MP, n (%) 74 (15.7%) Males, n (%) 237 (50.2%) Female, n (%) 235 (49.8%) Age (y) at study inclusion, mean ± SEM (range) 39.5 ± 0.61 (18-85) Crohns, n (%) 330, (69.9%) UC, n (%) 119, (25.2%) IBD-U, n (%) 23, (4.9%) Smoking data missing, n (%) 38 (8.0%) Non-smoker, n (%) 216 (45.8%) Ex-smoker, n (%) 161 (34.1%) Current smoker, n (%) 57 (12.1%) TPMT (pmol MeMP/ h/ mgHb) activity recorded, n (%); median (IQR) 360 (76.3%); 35 (30 – 39) TPMT wildtype, n (%); median (IQR) 319/360 (88.6%); 36 (32 - 40) TPMT heterozygote, n (%); median (IQR) 41/360 (11.4%); 20 (18 – 23) TPMT homozygote, n (%); median (IQR) 0 (0%), NA Weight-normalised dose of thiopurine (mg/ kg/ day), mean ± SEM: 1.95 ± 0.17 In TPMT wildtypes (n = 319) 1.83 ± 0.03 In TPMT heterozygotes (n = 41) 1.11 ± 0.07 Thiopurine metabolite monitoring, n (%) 374/472, (79.2%)

Av TGN (pmol/8x108 RBC) TPMT wildtypes, median (IQR) 295.0 (199.0 – 371.5) Av MeMP (pmol/8x108 RBC) TPMT wildtypes, median (IQR) 688.5 (243.8 – 2206) Av MeMP : TGN ratio, median (IQR) 2.62 (0.77 – 7.96)

Av TGN TPMT heterozygotes, median (IQR) 320.0 (243.3 – 502.0) Av MeMP TPMT heterozygotes, median (IQR) 97.8 (49.8 – 245.5) Av MeMP : TGN ratio, median (IQR) 0.29 (0.11 – 0.80) Failure of intervention free survival at 12 months, n (%) 141/472 (29.8%)

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300

200

100

20 15 10 Number of patients of Number 5 0 0 20 40 60 80 100 120 140 160 180 200 220 MeMP : TGN Ratio

Figure 6.1 Frequency histogram of MeMP : TGN concentration ratios in 374/472 patients prescribed AZA/MP in the IBD cohort.

6.3.2 Case-control analysis of genetic variants associated with thiopurine hypermethylation.

374 of the 472 patients prescribed AZA/MP had data on average thiopurine metabolite levels. Of these 226 were identified as having wildtype TPMT activity and a normal thiopurine metabolite profile, with median MeMP : TGN ratios < 11 : 1. This group was used as a control cohort for comparison to the 79 patients demonstrating thiopurine hypermethylation (table 6.2). Older age and a higher weight-normalised dose of AZA/MP were associated with hypermethylation; however, no gender influence was observed. Consistent with the previous findings, RBC TPMT activity within the wildtype range did not appear to explain thiopurine hypermethylation. There were very significant differences in the median TGN and MeMP concentrations and the MeMP : TGN concentration ratios between groups, suggesting that there was adequate separation for further analysis.

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Table 6.2: Demographic comparison between patients with normal thiopurine methylation profiles vs. cases of thiopurine hypermethylation.

Normal thiopurine Thiopurine Significance Variable methylation hypermethylation P-value, OR Controls Cases (95% CI) Number of patients 226 79 Male, n (%) 118 35 P = 0.241, OR = Female, n (%) 108 44 0.728 (0.435-1.129)* Age at study inclusion, P = 0.005 37.8 ± 0.83 (18-76) 42.5 ± 1.52 (19-79) mean ±SEM (range) (-8.011--1.444)† Prescribed AZA, n (%) 187 (82.7%) 65 (82.3%) P = 1.00, OR = 1.033 Prescribed MP, n (%) 39 (17.3%) 14 (17.7%) (0.527-2.024)* CD, n (%) 164 (72.6%) 51 (64.6%) UC, n (%) 52 (23.0%) 23 (29.1%) P = 0.396¥ IBD-U, n (%) 10 (4.4%) 5 (6.3%) Smoking data missing, n (%) 10 (4.4%) 22 (27.8%) Non-smoker n (%) 114 (50.4%) 25 (31.6%) P = 0.451¥ Ex-smoker n (%) 73 (32.3%) 24 (30.4%) Current-smoker n (%) 29 (12.9%) 8 (10.2%) TPMT activity pmol 35 35 MeMP/mg Hb/h, median P = 0.483+ (26 - 60) (26 - 51) (range) Normalised dose of P = 0.0004†, (-0.362 thiopurine (mg/ kg/ day) 1.92 ± 0.03 2.13 ± 0.05 - -0.107) mean ± SEM Av TGN pmol/8x108 RBC 325 (221.2 – 398.4) 218 (159.0 – 303.7) P = < 0.0001+ Av MeMP pmol/8x108 RBC 439 (254.0 – 832.0) 5765 (3628 – 8044) P = < 0.0001+ Av MeMP : TGN ratio 1.60 (0.79 – 2.78) 23.08 (15.85 – 43.90) P = < 0.0001+ * Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi- squared test.

6.3.2.1 Unsupervised case-control analysis of thiopurine hypermethylation

Following adjustment for LD (r2 = 0.99) and exclusion of SNPs with a MAF < 0.05%, 24,327 of 106,467 SNPs (22.8%) were included in an initial trait-SNP association analysis. Fisher’s exact tests demonstrated that no single variant passed Bonferroni correction, with the lowest P-value reported for rs892666 upstream of the gene encoding human-leucocyte antigen class A (HLA-A, P = 1.05x10-5). After adjustment for the first 4 PCAs, HLA-A rs892666 remained the most significant SNP (P = 2.66x10-5) but it did not pass Bonferroni correction (P = 0.55). After restricting the analysis to Caucasian individuals only, adjusted for the first 2 PCAs (controls, n = 146; cases, n = 41), the significance of HLA-A rs892666 was further reduced (P = 0.00242), suggesting confounding of the original P-value by ethnic variation. Overall the data suggest that no single polymorphism included in this analysis explains thiopurine hypermethylation (figure 6.2).

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Figure 6.2 Manhattan plot showing –log P-values for association with thiopurine hypermethylation in autosomal chromosomes. Dotted line denotes calculated threshold for genome-wide significance, P = 2x10-6 (0.05 / 24,237).

6.3.2.2 Supervised case-control analysis of thiopurine hypermethylation restricted to the thiopurine and methylation pathways

In a thiopurine pathway analysis (described in methods section 2.4.1, with details of candidate genes given in appendix 1), 6 variants demonstrated a P-value < 0.05. Of these the strongest effects were seen in the GDA, MGMT and the N-acetyltransferase 2 (NAT2) genes (table 6.3). ABCC4 rs9524891 demonstrated a trend towards a significant association (P = 0.055). After adjustment for the first 4 principle components the strength of the associations for NAT2 rs1799930 (P = 0.014), NT5E rs2229524 (P = 0.015), alkylation repair homolog 1 (ALKBH1) rs6494 (P = 0.017), MGMT rs12917 (P = 0.019) and ABCC4 rs9524891 (P = 0.046) were improved and for SLC29A3 rs2252996 (P = 0.057) it was reduced. After restricting the analysis to Caucasian ethnicity, the significance of ABCC4 rs9524891 (P = 0.0037), ALKBH1 rs6494 (P = 0.0062) and NT5E rs2229524 (P = 0.019) was further improved. The analysis of Caucasians alone also confirmed significant associations with MGMT rs12917 (P = 0.023) and rs7093850 downstream of MGMT (P = 0.024). Furthermore, 2 SNPs in MTAP rs7023954 (P = 0.028) and rs7023329 (P = 0.037) additionally showed association with hypermethylation. Significant polymorphisms were further assessed using dominant and recessive models restricted to Caucasian ethnicity (Table 6.4). Of the most significant variants, ABCC4 rs9524891 and NT5E rs2229524 were associated with hypermethylation and were best explained by

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Table 6.3: Case-control analysis of thiopurine hypermethylation restricted to the thiopurine pathway.

95% CI MAF MAF Chr SNP ID P (SNP) Bonf OR Gene Controls Cases 30Kb 9 rs11143230 0.02199 1 1.608 1.084 2.385 0.275 0.378 downstream GDA 10 rs12917 0.0227 1 1.882 1.129 3.136 0.110 0.189 MGMT 8 rs1799930 0.02341 1 0.600 0.391 0.922 0.340 0.237 NAT2 14 rs6494 0.03065 1 0.560 0.331 0.945 0.218 0.135 ALKBH1 10 rs2252996 0.0495 1 0.489 0.242 0.986 0.129 0.068 SLC29A3 6 rs2229524 0.04987 1 2.071 1.044 4.108 0.052 0.101 NT5E 13 rs9524891 0.05489 1 1.457 1.001 2.12 0.4202 0.514 ABCC4 Upstream 5 rs1394650 0.05598 1 0.688 0.470 1.008 0.477 0.385 MTRR 2 rs2287622 0.06545 1 1.440 0.991 2.105 0.390 0.480 ABCB11 Upstream 6 rs2394180 0.07873 1 1.574 0.955 2.593 0.129 0.189 HLA-G

Table 6.4: Dominant and recessive models of variants associated with thiopurine hypermethylation restricted to Caucasians alone.

95% CI Best Chr SNP ID P (SNP) Bonf OR Gene fit L U model 13 rs9524891 0.001643 0.2892 4.650 1.786 12.1 ABCC4 DOM 14 rs6494 0.007699 1 0.311 0.132 0.734 ALKBH1 DOM 6 rs2229524 0.01875 1 3.059 1.204 7.769 NT5E DOM 10 rs12917 0.02453 1 13.65 1.399 133.3 MGMT REC Downstream 9 rs7032296 0.02557 1 0.407 0.184 0.896 DOM SLC28A3 12 rs11045689 0.02627 1 2.446 1.111 5.383 SLCO1B7 DOM 16 rs35605 0.03931 1 2.179 1.039 4.568 ABCC1 DOM 2 rs2287622 0.03964 1 2.328 1.041 5.205 ABCB11 DOM 9 rs7023329 0.04433 1 2.86 1.027 7.964 MTAP DOM Downstream 10 rs7093850 0.05165 1 0.488 0.237 1.005 DOM MGMT DOM, dominant; REC, recessive.

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Following restriction of the analysis to variants in the methylation pathway, only ALKBH1 rs6494 showed statistical significance for protection from hypermethyation in a dominant model (P = 0.006, OR 0.315, 95% CI (0.137-0.721).

Pathway-centric analyses of thiopurine hypermethylation were completed using all of the SNPs in the thiopurine and methylation pathways (table 6.5). The insulin pathway set was used as a control. When examined as a single set, polymorphisms in the thiopurine pathway showed a trend towards an association with thiopurine hypermethylation; however this did not reach statistical significance. Restricting the analysis to Caucasians alone marginally improved the strength of the association (P = 0.09). Further, there was no apparent association between thiopurine hypermethylation and variants in the methylation pathway or (as expected) the insulin signalling pathway.

Table 6.5: Pathway-centric analyses of thiopurine hypermethylation using the thiopurine, methylation and insulin signalling pathways.

Total number Number Total number of SNPs Empirical Pathway Top SNP genes SNPs passing P-value constraints rs1394650 Thiopurine 100 639 6 0.118 Upstream MTRR rs148414435 Methylation 39 181 27 1 MTRR Insulin 8 24 7 1 rs41265094 signalling IRS1

Constraints of analysis; r2 = 1, P = < 0.2, max # SNPs per set = 999. A P-value of < 0.2 was chosen to include all possible significant variants and is consistent with the analysis reported by Verschuren et al. (420). Threshold for statistical significance, P = < 0.017 (0.05/3).

In the gene-centric analysis, the genes most significantly associated with thiopurine hypermethylation were SLC29A4, PACSIN1, and ALKBH1 (table 6.6). A trend towards an association was also observed for GDA, SLC28A2 and ABCC4. However, none of these genes passed the threshold for statistical correction (P < 0.0005). Restricting the analysis to Caucasian ethnicity improved the association for ABCC4 (P = 0.045), reduced the significance of the SLC29A4 (P = 0.034) and removed the signal for PACSIN1 (P = 0.848). Furthermore, a borderline association was shown for MTAP (P = 0.05).

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Table 6.6: Gene-centric analysis of thiopurine hypermethylation using genes related to the thiopurine pathway.

MAF Gene SNPs Sig.SNPs P(gene) Top SNP OR P (SNP) Cases SLC29A4 1 1 0.0172 rs144364439 0.02 11.81 0.0054 PACSIN1 4 1 0.0376 rs149949488 0.01 NA 0.0162 ALKBH1 4 1 0.0397 rs6494 0.13 0.56 0.0284 GDA 5 1 0.0679 rs11143230 0.38 1.61 0.0178 SLC28A2 11 1 0.1459 rs17222057 0.03 5.89 0.0214 rs11568658 0.06 2.69 0.0287 ABCC4 20 2 0.1529 rs9524891 0.51 1.46 0.0490

SNPs, total number of SNPs per gene; Sig.SNPs indicate the number of SNPs that passed the test constraints (r2 <0.8, P < 0.05, set-max # = 50) and were thus jointly analysed in 10,000 permutations; P, P-value. Since 100 genes in total were analysed, the threshold for statistical significance was P < 0.0005.

Testing for epistasis between polymorphisms in the thiopurine pathway suggested interactions between ABCC4 rs1926657 and ABCC4 rs9524891 (χ2 = 7.663), ALKBH1 rs6494 and 5’nucleotidase cytosolic II (NT5C2) rs10883841 (χ2 = 7.663), SLC28A1 rs2290272 and SLC29A3 rs2277257 (χ2 = 8.350) and SLC29A3 rs2487068 and ATP-binding cassette sub-family C member 1 (ABCC1) rs35605 (χ2 = 7.299).

Based on the SNP and gene-set analyses, candidate SNPs in ABCC4 (rs9524891); ALKBH1 (rs6494); MGMT (rs12917); NT5E (rs2229524) and GDA (rs11143230) were selected and combined in a forwards logistic regression model to determine the percentage of thiopurine hypermethylation that could be explained by these variants. The model also included the normalised dose of thiopurine (mg/kg/day) and age as covariates. Pearson’s correlations confirmed the association for the selected polymorphisms, age and the normalised dose of AZA/MP with the presence of thiopurine hypermethylation (table 6.7).

When the covariates were combined in a model, a test of the full model against a constant only model was statistically significant, indicating that the predictors as a set reliably distinguished between patients with normal thiopurine methylation profiles and those with thiopurine hypermethylation (χ2 = 55.83, P < 0.001, with df = 7). As a whole the model explained between 17.7% (Cox and Snell R Square) and 26% (Nagelkerke R square) of the variance in thiopurine hypermethylation status, and correctly classified 77% of the patients. The sensitivity of the model

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Table 6.7: Pearson’s correlations between polymorphisms in ABCC4, ALKBH1, MGMT, NT5E, GDA, age, normalised dose of AZA/MP and thiopurine hypermethylation.

MGMT ABCC4 ALKBH1 GDA NT5E Normalised Age rs12917 rs9524891 rs6494 rs11143230 rs2229524 dose REC DOM DOM DOM DOM Pearson’s 0.189 0.174 0.192 0.124 -0.129 0.165 0.138 Correlation Sig. 0.001 0.003 0.001 0.036 0.029 0.005 0.022 (2-tailed) REC, recessive; DOM, dominant.

Table 6.8: Variables included in a multivariate logistic regression model to predict thiopurine hypermethylation.

Exp(B) 95% CI Exp(B) Variable B S.E. Wald Df Sig Lower Upper Age 0.46 0.12 14.519 1 0.001 1.047 1.022 1.072 Normalised dose 1.023 0.345 8.815 1 0.003 2.782 1.416 5.467 AZA/MP MGMT rs12917 3.224 1.183 7.422 1 0.006 25.130 2.471 255.574 Recessive ABCC4 rs9524891 0.756 0.361 4.374 1 0.036 2.129 1.049 4.324 Dominant ALKBH1 rs6494 -0.999 0.342 8.516 1 0.004 0.368 0.188 0.720 Dominant GDA rs11143230 0.970 0.314 9.539 1 0.002 2.637 1.425 4.879 Dominant NT5E rs2229524 0.781 0.411 3.609 1 0.057 2.183 0.976 4.885 Dominant Constant -5.913 1.032 32.843 1 0.000 0.003

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6.3.3 Case-control analyses of genetic variants associated with high MeMP levels and low TGN levels.

The mean age of patients with MeMP levels ≥ 5000 pmol/ 8X108 RBC (n = 45) was significantly higher than in patients with average MeMP levels < 5000 pmol/ 8x108 RBC (n = 311, P = 0.0034), consistent with the earlier observations for individuals demonstrating thiopurine hypermethylation. A higher proportion of patients with IBD-U were seen in the high MeMP group and there was a significant difference in the weight-normalised dose of AZA/MP. There was also a trend towards a higher median RBC TPMT activity in the high MeMP cohort, however this did not reach statistical significance (P = 0.081). TGN levels were lower in the group with high MeMP suggesting increased shunting of MP and its ribonucleotides towards the corresponding methylated derivatives. The difference in average MeMP levels between the groups was greater than 10-fold, confirming adequate separation for further analysis (table 6.9).

The group of patients with median TGN concentrations ≥ 240 pmol/8x108 RBC (n = 230), were adequately matched for dose and RBC TPMT activity with the group where TGN concentrations were between 100-239 pmol/8x108 RBC (n = 118). Indeed, the average normalised dose of AZA/MP was slightly higher (difference between means 0.13 mg/kg/day, P = 0.011) in the cohort of patients with lower TGNs. The difference in median TGN levels between the groups was 2-fold, confirming an adequate separation for further analysis. Whilst MeMP levels were statistically higher in the low TGN group, the difference was marginal (P = 0.041) and excluding patients to match median MeMP concentrations would have led to a loss of statistical power (table 6.10).

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Table 6.9: Comparison of patients demonstrating average MeMP < 5000 pmol/8x108 RBC vs patients with average MeMP ≥ 5000 pmol/8x108 RBC.

Average MeMP Average MeMP levels Significance levels ≥ 5000 Variable < 5000 pmol/8x108 P-value, OR pmol/8x108 RBC, RBC, Controls (95% CI) Cases Number 311 45 Male, n (%) P = 0.425*, 155 (49.8%) 19 (42.2%) Female, n (%) OR = 1.36 156 (50.2%) 26 (57.8%) (0.723-2.558) Age at study inclusion, 38.6 ± 0.74 44.7 ± 2.01 P = 0.0034† mean ± SEM Prescribed AZA, n (%) 261 (84.0%) 38 (84.4%) P = 1*, OR = 0.96 Prescribed MP, n (%) 50 (16.0%) 7 (15.6%) (0.406-2.275) CD, n (%) 224 (72.0%) 26 (57.8%) UC, n (%) 73 (23.5%) 11 (24.4%) P = 0.0021¥ IBD-U, n (%) 14 (4.5%) 8 (17.8%) Smoking data missing, n (%) 15 (4.8%) 19 (42.2%) Non-smoker 154 (49.5%) 13 (28.9%) P = 0.568¥ Ex-smoker 106 (34.1%) 8 (17.8%) Current-smoker 36 (11.6%) 5 (11.1%) TPMT activity pmol MeMP/ 35 35 P = 0.081+ h/ mgHb, median (range) (15-60) (30-51) Normalised dose of thiopurine (mg/ kg/ day) 1.83 ± 0.03 2.05 ± 0.08 P = 0.002† mean ± SEM Av TGN pmol/8x108 RBC 306 (206.8 – 384.4) 251 (178.7 – 340.5) P = 0.015+ Av MeMP pmol/8x108 RBC 489 (144.0 – 1316) 7920 (6446 - 11854) P = <0.0001+

* Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi- squared test.

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Table 6.10: Comparison of patients demonstrating average TGNs ≥ 240 pmol/8x108 RBC vs patients with average TGNs between 100 - 239 pmol/8x108 RBC.

Average TGNs ≥ 240 Average TGNs 100- Significance Variable pmol/ 8x108 RBC, 239 pmol/ 8x108 P-value, OR Controls RBC, Cases (95% CI) Number 230 118 Male, n (%) 124 (54.0%) 67 (56.8%) P = 0.650*, OR = Female, n (%) 106 (46.0%) 51 (43.2%) 0.891 (0.569-1.393) Age at study inclusion, 38.9 ± 0.84 38.8 ± 1.23 P = 0.941† mean ± SEM P = 0.645*, OR = Prescribed AZA, n (%) 192 (83.5%) 101 (85.6%) 0.850 (0.457 – Prescribed MP, n (%) 38 (16.5%) 17 (14.4%) 1.582) CD, n (%) 160 (69.6%) 87 (73.7%) UC, n (%) 60 (26.1%) 26 (22.0%) P = 0.700¥ IBD-U, n (%) 10 (4.3%) 5 (4.3% Smoking data missing, n (%) 14 (6.1%) 19 (16.1%) Non-smoker 114 (49.6%) 52 (44.1%) P = 0.812¥ Ex-smoker 73 (31.7%) 36 (30.5%) Current-smoker 29 (12.6%) 11 (9.3%) TPMT activity pmol MeMP/ 34.5 34.0 P = 0.844+ h/ mgHb, median (range) (26-54) (26-54) Normalised dose of thiopurine (mg/ kg/ day) 1.83 ± 0.04 1.96 ± 0.05 P = 0.011† mean ± SEM Av TGN pmol/8x108 RBC 356 (304.2 – 435.9) 186 (157.5 – 217.0) P = <0.0001+ Av MeMP pmol/8x108 RBC 683 (243.9 – 1918) 843 (222.8 – 3152) P = 0.041+

* Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi- squared test

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6.3.3.1 Unsupervised case-control analysis of patients with high MeMP levels and low TGN levels.

The initial unsupervised trait-SNP association analyses for both the high MeMP and low TGN level case-control studies included 24,327 markers. No single polymorphism appeared to explain high MeMP levels ≥ 5000 pmol/8x108 RBC (figure 6.3). Three of the variants within the 10 most significant results were in a single gene, Pericentrin (PCNT, rs34500739, rs61735814, rs743346). However, measurement of r2 showed that these variants were in high LD with each other (r2 = 0.91, 0.91 and 0.93 respectively), suggesting that these SNPs do not represent independent mutations within the PCNT gene. The second most significant variant, uridine 5’-diphospho- glucuronosyltransferase 2 family polypeptide A2 (UGT2A2) rs4148301 (P = 8.89x10-5), whilst not passing correction for multiple testing may be of relevance and is discussed later. Restricting the analysis to Caucasians alone reduced the association between UGT2A2 rs4148301 (P = 0.00134) and high MeMP levels; however there were only 18 cases (vs 200 controls) in this analysis and therefore it is likely to be underpowered.

In an unsupervised analysis, no single variant appeared to explain low TGN levels (figure 6.4). Restricting the analysis to Caucasian individuals alone also failed to reveal a SNP with genome-wide significance.

Figure 6.3 Manhattan plot showing –log P-values for association with MeMP levels ≥ 5000 pmol/ 8x108 RBC in autosomal chromosomes. Dotted line, threshold for genome-wide significance, p=2x10-6.

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Figure 6.4 Manhattan plot showing –log P-values for association with low TGN levels (100-239 pmol/ 8x108 vs. TGNs ≥ 240 pmol/ 8x108) in autosomal chromosomes. Dotted line, threshold for genome-wide significance, p=<2x10-6.

6.3.3.2 Supervised case-control analyses of high MeMP levels and low TGN levels, restricted to the thiopurine and methylation pathways

The most significant associations for high MeMP levels in both the thiopurine and methylation pathways were demonstrated for rs972283 and rs4731702 (tables 6.11). Both SNPs are ≈ 14Kb upstream of KLF-14. There was strong LD between these variants (r2 = 0.91), which showed protection from high MeMP levels. Both polymorphisms remained significant after restricting to Caucasian ethnicity (P = 0.003 and P = 0.0033 respectively) and best fit a dominant model of interaction. One-way analysis of variance confirmed protection from high MeMP levels and showed that homozygous recessive individuals tended to have the lowest MeMP levels (P = 0.031, Barlett’s test for equal variances, P = < 0.0001. KLF-14 rs972283 MAF, A = 0.337. Figure 6.5). The next most significant SNP in the thiopurine pathway analysis was ABCC4 rs9524891, a candidate also observed in the thiopurine hypermethylation analysis, providing consistency that this variant is associated with high MeMP levels.

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Table 6.11: Variants associated with high MeMP levels (≥ 5000 pmol/ 8x108 RBC) in the thiopurine and methylation pathways.

95% CI MAF MAF Pathway Chr SNP ID P(SNP) Bonf OR L U Controls Cases Gene THIO 0.113 Upstream 7 rs972283 0.00064 0.408 0.242 0.687 0.458 0.256 METH 0.035 KLF-14 THIO 0.347 Upstream 7 rs4731702 0.00197 0.435 0.260 0.727 0.458 0.268 METH 0.107 KLF-14 THIO 13 rs9524891 0.0140 1 1.814 1.137 2.893 0.425 0.573 ABCC4 THIO 1 Upstream 5 rs2924461 0.0274 1.681 1.054 2.681 0.444 0.5732 METH 1 MTRR THIO 11 rs1695 0.0464 1 0.563 0.331 0.957 0.364 0.244 GSTP1

THIO, thiopurine pathway; METH, methylation pathway.

P = 0.031

30000

20000 RBC 8 10000

1000 800 600 400

MeMP pmol/ 8x10 pmol/ MeMP 200 0 AA AG GG KLF-14 rs972283 Genotype; A = minor allele

Figure 6.5 Comparison of average MeMP concentrations for genotypes at rs972283 ≈ 14Kb upstream of KLF-14.

The most significant SNP in the thiopurine pathway associated with low TGN levels was NT5E rs2229524, which remained significant after restricting to Caucasian ethnicity and was best explained by a dominant model (table 6.12). Genotype modelling suggested additional associations between low TGN levels and polymorphisms in 5’nucleotidase cytosolic IA (NT5C1A), catechol-O- methyltransferase (COMT), ABCB5, methylenetetrahydrofolate dehydrogenase (MTFHD1) and methionine synthase reductase (MTRR) (table 6.13) and led to the loss of the signals from AOX1 rs11684227 and SLC28A1 rs2242046. APAF1-interacting protein (APIP) rs1977420 and rs2956114

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were in high LD (r2 = 0.93), protected against low TGN levels and demonstrated a recessive interaction.

Table 6.12: Variants associated with low TGN levels in the thiopurine and methylation pathways.

95% CI MAF MAF Pathway Chr SNP ID P (SNP) Bonf OR L U Controls Cases Gene THIO 6 rs2229524 0.000798 0.140 2.236 1.224 4.086 0.051 0.107 NT5E Upstream THIO 2 rs11684227 0.0246 1 0.697 0.502 0.976 0.482 0.393 AOX1 THIO 15 rs2242046 0.03141 1 1.473 1.064 2.039 0.396 0.4911 SLC28A1 METH 11 rs1977420 0.01766 0.953 0.638 0.455 0.896 0.423 0.321 APIP METH 11 rs2956114 0.01846 0.997 0.645 0.459 0.905 0.424 0.321 APIP

THIO, thiopurine pathway; METH, methylation pathway

Table 6.13: Dominant and recessive models of variants associated with low TGN levels in the thiopurine and methylation pathways, restricted to Caucasian ethnicity.

95% CI Best Pathway Chr SNP ID P (SNP) Bonf OR Gene fit L U model THIO 6 rs2229524 0.0086 1 3.066 1.33 7.070 NT5E DOM THIO 1 rs873917 0.0112 1 2.903 1.274 6.618 NT5C1A REC THIO 22 rs4680 0.0114 1 0.432 0.225 0.828 COMT DOM THIO 7 rs2301641 0.0231 1 2.603 1.110 6.106 ABCB5 REC THIO 14 rs2236225 0.0243 1 2.302 1.112 4.754 MTHFD1 REC THIO 5 rs10380 0.0279 1 0.431 0.204 0.913 MTRR DOM METH 11 rs1977420 0.0499 1 0.327 0.108 0.999 APIP REC METH 11 rs2956114 0.0499 1 0.327 0.108 0.999 APIP REC

THIO, thiopurine pathway; METH, methylation pathway; DOM, dominant; REC, recessive.

Pathway-centric analyses investigating associations with both high MeMP levels (≥ 5000 pmol/8x108 RBC) and low TGN levels (100-239 pmol/8x108 RBC) were completed using the thiopurine and methylation pathways. The insulin pathway was used as a control (tables 6.14 and 6.15). When examined as a set, only the thiopurine pathway was associated with high MeMP levels (P = 0.0301), however this did not pass correction for multiplicity. The most significant reported SNP in both the thiopurine and methylation pathways was rs972283 upstream of KLF-14. Application of the pathway analyses to investigating low TGN levels demonstrated that both the thiopurine and methylation pathways were significantly associated with low TGN levels, with TPMT*3C reported as the top SNP.

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Table 6.14: Pathway-centric analyses of high MeMP levels (≥ 5000 pmol/ 8x108 RBC) using the thiopurine, methylation and insulin-signalling pathways.

Total number Number Total number of SNPs Empirical Pathway Top SNP genes SNPs passing P-value constraints rs972283 Thiopurine 100 639 26 0.0301 Upstream KLF-14 rs972283 Methylation 39 181 14 1 Upstream KLF-14 Insulin 24 3 3 1 rs10846018 signalling SLC2A14

Constraints of analysis; r2 = 1, P = < 0.05, max # SNPs per set = 999. Threshold for statistical significance, P < 0.0167 (0.05/3).

Table 6.15: Pathway-centric analyses of low TGN levels (100-239 pmol/8x108 RBC) using the thiopurine, methylation and insulin-signalling pathways.

Total number Number Total number of SNPs Empirical Pathway Top SNP genes SNPs passing P-value constraints rs1142345 Thiopurine 100 639 7 0.0121 TPMT*3C rs1142345 Methylation 39 181 2 0.0014 TPMT*3C Insulin rs11066301 24 1 1 0.236 signalling PTPN11

Constraints of analysis; r2 = 1, P = < 0.05, max # SNPs per set = 999. Threshold for statistical significance, P < 0.0125 (0.0167/3).

In gene-set analyses, the KLF-14 gene was most strongly associated with protection from high MeMP (table 6.16) levels in both the thiopurine and methylation pathways (P = 0.00056). The ABCC4 gene was also shown to influence high MeMP levels and this relationship was strengthened when the analysis was restricted to Caucasian ethnicity (P = 0.00429). However, the same restriction led to the loss of significance for the SLC28A2 gene.

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Gene-set analysis demonstrated that the TPMT gene was associated with protection from low TGN levels, with the highest association reported for TPMT*3C (table 6.17). This was surprising since the cohort had been adjusted for RBC TPMT activity and only included patients with wildtype TPMT activity (≥ 26 pmol MeMP/ h/ mgHb). However, 2 patients within the control cohort were found to exhibit heterozygosity for TPMT*3C despite apparently normal RBC TPMT activity. Higher TGNs would therefore be expected in this group due to reduced degradation of MP via the methylation pathway. Associations were also suggested between SLC28A1 and low TGN levels and AOX1 and protection from low TGN levels; however, both signals were lost after restriction to Caucasian ethnicity.

Table 6.16: Gene-centric analyses for high MeMP levels (≥ 5000 pmol/8x108 RBC) using genes related to the thiopurine and methylation pathways.

MAF Pathway Gene SNPs Sig.SNPs P(gene) Top SNP OR P(SNP) Cases THIO KLF-14 3 2 0.0058 rs972283 0.256 0.408 0.00056 METH THIO SLC28A2 11 1 0.0351 rs17222057 0.0370 8.073 0.0045 THIO ABCC4 20 1 0.1310 rs9524891 0.5730 1.181 0.0116

Table 6.17: Gene-centric analyses for low TGN levels (100-239 pmol/8x108 RBC) using genes related to the thiopurine, methylation and TGN pathways.

MAF Pathway Gene SNPs Sig.SNPs P(gene) Top SNP OR P(SNP) Cases THIO TPMT 2 2 0.0014 rs1142345 0 NA 0.00107 THIO SLC28A1 13 1 0.0234 rs2242046 0.491 1.473 0.0194 THIO AOX1 10 1 0.0599 rs11684227 0.393 0.697 0.0310

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Testing for epistasis between polymorphisms in the methylation pathway to explain high MeMP levels suggested interactions between KLF-14 rs972283 / rs473170 and SLC29A3 rs780668 (χ2 = 6.883 and 8.909 respectively). SLC29A3 rs780668 was also shown to interact with MGMT rs12917 (χ2 = 6.701), SLC28A2 rs376335466 (χ2 = 6.978) and GSTA2 rs2180314 (χ2 = 8.899). In addition interaction was suggested between ABCB5 rs34603556 and MGMT rs2308321 (χ2 = 6.519).

Testing for epistasis between polymorphisms in the thiopurine pathway to explain low TGN levels suggested interactions between NT5E rs2229523 and ABCC4 rs1926657 (χ2 = 8.267), KLF-14 rs972283 / rs473170 and ABCC4 rs9524891 (χ2 = 12.09 and 12.79 respectively) and ABCB5 rs34603556 and KLF-14 rs473170 (χ2 = 10.73).

Based on the trait-SNP, gene-set and epistasis analyses, candidate SNPs upstream of KLF-14 (rs972283 and rs473170) and polymorphisms in ABCC4 (rs9524891), SLC28A2 (rs376335466) and ABCB5 (rs34603556) were selected and combined in a forwards logistic regression model to determine the percentage of high MeMP levels that could be explained by these variants. The model also included RBC TPMT activity, the weight-normalised dose of thiopurine (mg/ kg/ day) and age as covariates. A second model to explain low TGN levels included SNPs in NT5E (rs2229523) and ABCC4 (rs1926657 and rs9524891).

Pearson’s correlations confirmed the association between the selected polymorphisms, age and the normalised dose of AZA/MP with high MeMP levels (table 6.18).

Table 6.18: Pearson’s correlations between polymorphisms in KLF-14, ABCC4, SLC28A2, ABCB5, age, normalised dose of AZA/MP, TPMT activity and high MeMP levels (≥ 5000 pmol/8x108 RBC).

Normalised KLF14 KLF14 ABCC4 SLC28A2 ABCB5 TPMT Age dose rs972283 rs473170 rs9524891 rs376335466 rs34603556 activity AZA/MP DOM DOM DOM DOM REC Pearson’s 0.144 0.194 0.139 -0.141 -0.162 0.132 0.098 0.127 Correlation Sig. 0.022 0.001 0.011 0.100 0.003 0.015 0.072 0.020 (2-tailed) DOM, dominant; REC, recessive

When the covariates were combined, a test of the full model against a constant-only model was statistically significant, indicating that the predictors as a set reliably distinguished between patients with high MeMP levels (≥ 5000 pmol/ 8x108RBC) and those with lower MeMP levels (χ2 = 33.42, df = 8, P = < 0.001). As a whole, the model explained between 12.3% (Cox and Snell R Square) and 24.2% (Nagelkerke R square) of the variance in the development of high MeMP levels, and correctly

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Univariate analysis suggested that low TGN levels were poorly correlated with TPMT activity (r = - 0.22, P = 0.686) and ABCC4 rs1926657 (r = -0.33, P =0.556 in a dominant model). These variants were therefore excluded from the model. When the remaining covariates were combined (table 6.19), a test of the full model against a constant-only model was statistically significant, indicating that the predictors as a set reliably distinguished between patients with low TGN levels (100-239 pmol/ 8x108RBC) and those with higher TGNs (χ2 = 29.896, df = 6, P = < 0.001). As a whole the model explained between 8.7% (Cox and Snell R Square) and 12.0% (Nagelkerke R square) of the variance in TGN levels, and correctly classified 66.2% of the patients in the model. The sensitivity of the model when entered as a set was 23.1%; however the specificity was high at 90.0%. The PPV and NPV of the low TGN model were 56.3% and 67.9% respectively. As shown, the strongest predictor of low TGN levels was the normalised dose of AZA/MP (OR 2.099; 95% CI 1.307 – 3.372). This is paradoxical to the expected observation and is likely to have occurred due to attempts at dose escalation in the patients with low TGNs. Removing the normalised dose from the model, decreased the variance it explained (7.4%, Nagelkerke R squared) and reduced the goodness of fit (Hosmer and Lemeshow test, P =0.069). Of interest the significance for the ABCC4 rs9524891 polymorphism (P = 0.319) was improved when it coincided with the NT5E rs2229523 variant (combined P-value = 0.023), suggesting a possible interaction between these two variants.

Table 6.19: Variants included in a multivariate logistic regression model to predict low TGN levels.

Exp(B) 95% CI Exp(B) Variable B S.E. Wald Df Sig Lower Upper Gender 0.402 0.246 2.665 1 0.103 1.495 0.923 2.423 Age 0.15 0.10 2.425 1 0.119 1.015 0.996 1.034 Normalised dose 0.742 0.242 9.399 1 0.002 2.099 1.307 3.372 AZA/MP ABCC4 0.269 0.269 0.994 1 0.319 1.308 0.771 2.219 rs9524891 NT5E 0.895 0.348 6.617 1 0.10 2.447 1.237 4.839 rs2229524

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6.3.4 Case-control analysis of genetic variants associated with 12 month intervention free survival in patients with IBD prescribed AZA/MP

From the cohort of 472 patients treated with AZA/MP, 141 (29.9%) demonstrated a failure to reach the primary end-point of intervention free survival during the first 12 months of therapy. This group was compared to a control cohort of 188 patients, matched for the weight-normalised dose of AZA/MP and TGN levels, demonstrating successful therapy (table 6.20). The average age of patients was lower in the group with failure of intervention free survival at 12 months of therapy (mean difference 5.3 years, P = 0.0002). Furthermore, there was a higher proportion of patients with CD in this cohort, indicating the need for further analyses matched for the subtype of IBD. There was no difference in smoking behaviour between groups and they were matched for median RBC TPMT activity, the weight-normalised dose of AZA/MP and average concentrations of TGN and MeMP and the MeMP : TGN concentration ratio. Furthermore, there was no difference in average WBC or neutrophil counts between groups. However, the average lymphocyte count (mean difference 0.13 x109/L, P = 0.014), haemoglobin concentration (mean difference 5 g/ L, P = 0.012) and MCV (mean difference 2.8 fL, P = 0.0036) were lower in the cases showing failure of response. The platelet count was also higher in this group (mean difference 27.8 x109/L, p=0.014).

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Table 6.20: Comparison of patients demonstrating success or failure of intervention free survival during the first 12 months of AZA/MP treatment.

Success of AZA/MP Failure of AZA/MP Significance Variable at 12 months of at 12 months of P-value, OR therapy therapy (95% CI) Number 188 141 P = 0.579*, OR = Male, n (%) 90 (47.9%) 72 (51.1%) 0.880, (0.569 – Female, n (%) 98 (52.1%) 69 (48.9%) 1.363) Age (y) at study inclusion, P = 0.0002† 40.9 ± 0.97 (18-79) 35.6 ± 0.97 (17-75) mean ± SEM (range) (2.535 – 8.018) P = 0.065*, OR = Prescribed AZA, n (%) 162 (86.2%) 126 (89.4%) 0.534 (0.281 – Prescribed MP, n (%) 26 (13.8%) 15 (10.6%) 1.022) CD, n (%) 110 (58.5%) 114 (80.9%) UC, n (%) 71 (37.8%) 23 (16.3%) P = < 0.0001¥ IBD-U, n (%) 7 (3.7%) 4 (2.8%) Smoking data missing, n (%) 10 (5.3%) 10 (7.1%) Non-smoker 84 (44.7%) 67 (47.5%) P = 0.688¥ Ex-smoker 70 (37.2%) 50 (35.5%) Current-smoker 24 (12.8%) 14 (9.9%) TPMT activity pmol MeMP/ h/ 35 (16-58) 35 (17-54) P = 0.581+ mgHb, median (range) Normalised dose of thiopurine 1.85 ± 0.04 1.75 ± 0.05 P = 0.294+ (mg/ kg/ day) mean ± SEM

Av TGN pmol/8x108 RBC 293 (206.0 – 365.0) 305 (204.6 – 390.7) P = 0.636+ Av MeMP pmol/8x108 RBC 679 (191.7 – 2314) 711.6 (226.0 – 2188) P = 0.985+ Av MeMP:TGN ratio 2.34 (0.74 – 6.92) 2.25 (0.74 – 8.46) P = 0.973+

Av WBC (x109/L) 6.3 ± 0.1 5.8 ± 0.2 P = 0.843+ Av Neutrophil count (x109/L) 4.5 ± 0.2 4.5 ± 0.2 P = 0.794+ Av Lymphocyte count (x109/L) 1.27 ± 0.04 1.14 ± 0.04 P = 0.014+ Av Platelet count (x109/L) 271.2 ± 6.1 299 ± 9.2 P = 0.014+ Av Haemoglobin (g/L) 130.8 ± 1.0 125.8 ± 2.0 P = 0.012+ Av MCV (fL) 93.0 ± 0.8 90.2 ± 0.2 P = 0.0036+ Av MCV/WBC ratio 15.85 ± 0.36 15.95 ± 0.59 P = 0.708+

*Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi- squared test; Av, average.

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The main reason for failure to achieve intervention free survival at 12 months of therapy was escalation to anti-TNF-α treatment (figure 6.6)

Hospitalisation

Unexpected surgery

Switch to alternative immunomodulator Escalation to anti-TNF-α therapy Steroid maintenance

Low dose thiopurine / allopurinol

Figure 6.6. Aetiology of failure to achieve intervention free survival during the first 12 months of AZA/MP therapy (n = 141).

6.3.4.1 Unsupervised case-control analysis of patients with IBD failing to achieve intervention free survival during the first 12 months of AZA/MP therapy

The initial unsupervised analysis included 24,327 SNPs, adjusted for the first 4 PCAs. No single variant demonstrated genome-wide significance (figure 6.7). However, the most significant association was in the gene encoding the ribonucleotide reductase M2 subunit (RRM2, rs1130609; P = 3.80x10-5, OR = 0.461, 95% CI = 0.319 – 0.666), a candidate gene in the thiopurine pathway and, whilst not passing correction for multiple testing in an unsupervised analysis, this is likely to be of relevance.

RRM2 rs1130609 remained significant after restriction to both Caucasian ethnicity (108 controls vs. 92 cases, P = 0.0012) and Caucasian patients with CD alone (68 controls vs. 77 cases, P = 0.0014). This variant appeared to protect against a lack of clinical response and was best explained by a dominant model of interaction. Two polymorphisms in the lipoprotein A (LPA) gene (rs1084651 and rs1652507) that were in high LD (r2=0.85) were also reported in the top 10 SNPs (P = 0.000259, OR = 0.388, 95% CI = 0.234 – 0.645; P = 0.000376, OR = 0.398, 95% CI = 0.240 – 0.662, respectively). There is no known association between LPA and thiopurine response; however, LPA has been linked with

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IBD pathogenesis and therefore the associations suggested here may relate to differences in disease phenotype (421, 422). Indeed, restricting the analysis to CD reduced the association with LPA (P = 0.0017).

Figure 6.7 Manhattan plot showing –log P-values for association with clinical response to AZA/MP during the first 12 months of therapy in autosomal chromosomes. Dotted line, threshold for genome-wide significance, P = < 2x10-6.

6.3.4.2 Supervised case-control analyses of the success or failure to achieve 12 month intervention free survival restricted to the thiopurine and methylation pathways

Constraining the analyses to variants in the thiopurine and methylation pathways demonstrated additional polymorphisms influencing clinical response to AZA/MP (table 6.21). After restriction to Caucasian ethnicity the significance levels of ABCC4 rs4148546 and GSTA3 rs557135 were improved (P = 0.0072 and P = 0.0022 respectively), the association with APIP rs12793173 and ABCA1 rs2777804 remained unchanged; however the signal from MTRR rs1532268 was lost. Dominant models of interaction best explained the associations with RRM rs1130609, ABCA1 rs2777804 / rs2230808, ABCC4 rs4148546 and APIP rs12793173, whereas GSTP1 rs1695 and GSTA3 rs557135 fit recessive models.

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Table 6.21: Variants associated with 12 month intervention free survival in the thiopurine and methylation pathways.

95% CI MAF MAF Pathway Chr SNP ID P(SNP) Bonf OR L U Controls Cases Gene THIO 2 rs1130609 3.80x10-5 0.0067 0.461 0.319 0.666 0.385 0.230 RRM2 METH 11 rs12793173 0.010 0.593 0.600 0.407 0.886 0.306 0.190 APIP THIO 9 rs2777804 0.015 1 1.550 1.089 2.204 0.169 0.093 ABCA1 THIO 11 rs1695 0.020 1 0.657 0.461 0.936 0.374 0.281 GSTP1 THIO 13 rs4148546 0.023 1 0.681 0.489 0.948 0.540 0.456 ABCC4 THIO 9 rs2230808 0.025 1 1.558 1.057 2.296 0.359 0.259 ABCA1 METH 5 rs1532268 0.035 1 0.688 0.486 0.974 0.411 0.325 MTRR THIO 6 rs557135 0.036 1 0.687 0.484 0.975 0.408 0.325 GSTA3 THIO, thiopurine pathway; METH, methylation pathway.

Pathway-centric analyses demonstrated that success or failure of 12 month intervention free survival was better explained by variants in the thiopurine as opposed to the methylation pathway; however neither passed the threshold for statistical significance (P = < 0.0167) suggesting the involvement of additional factors (table 6.22). Gene-centric analyses of the thiopurine and methylation pathways confirmed RRM2 as the most highly associated gene influencing thiopurine response. The adenosylhomocystine-like 2 (AHCYL2), GSTA3 and phosphoribosyl pyrophosphate synthetase subunit III (PRPS3) genes also appeared to protect against non-response to AZA/MP, however the association with these genes was lost following restriction to Caucasian ethnicity. Restriction of the gene-centric analyses to CD alone, confirmed the association with RRM2 (P = 0.0041) and suggested an additional association with GSTP1 (P = 0.011, top SNP rs1695).

Table 6.22: Pathway-centric analyses of 12 month intervention free survival using the thiopurine and methylation pathways.

Total number Number Total number of SNPs Empirical Pathway Top SNP genes SNPs passing P-value constraints RRM2 Thiopurine 100 639 56 0.030 rs1130609 MTR Methylation 39 181 19 1 rs113042166 Insulin SHC1 24 4 4 0.234 signalling rs8191979

Constraints of analysis; r2 = 1, P = < 0.20, max # SNPs per set = 999. Threshold for statistical significance, P = < 0.0167 (0.05/3).

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Testing for epistasis between variants in the thiopurine pathway suggested interactions between RRM2 rs1130609 and rs11143230 30Kb downstream of GDA (χ2 = 13.56), ABCA1 rs4149268 and ABCB1 rs2032582 (χ2 =11.5), ABCB1 rs2032582 and SLC28A1 rs2242046 (χ2 = 10.06), ABCA1 rs1883025 and NT5C2 rs10883841 (χ2=9.79), ABCC4 rs4148546 and ABCC5 rs7636910 (χ2 = 9.96) and ABCC4 rs4148546 and AOX1 rs55754655 (χ2 = 9.96).

Based on the trait-SNP, pathway, gene-set and epistasis analyses, polymorphisms in RRM2 (rs1130609), GDA (rs11143230), ABCA1 (rs2777804 and rs2230808), ABCB1 (rs2032582), GSTA3 (rs557135), SLC28A1 (rs2242046), GSTP1 (rs1695), ABBC4 (rs4148546) and ABCC5 (rs7636910) were selected and combined in a logistic regression model to determine the percentage of 12 month intervention free survival that could be explained. Covariates included gender, age, RBC TPMT activity, IBD subtype (CD or not CD), the weight-normalised dose of AZA/MP, average TGN levels, average MeMP levels, average MeMP : TGN concentration ratios and smoking status.

Univariate analysis of the above genetic variants and covariates demonstrated significant associations between 12 month intervention free survival and RRM2 rs1130609, age, CD and the normalised dose of AZA/MP. Subsequent forwards logistic regression demonstrated that non- response to AZA/MP was best explained by a model including; RRM2 rs1130609, ABCA1 rs2230808, ABCB1 rs2032582, GSTP1 rs1695, ABCC5 rs7636910, age, presence of CD, TPMT activity, the weight- normalised dose of AZA/MP and the MeMP : TGN concentration ratio (table 6.23).

When these covariates were combined, a test of the full model against a constant-only model reliably predicted whether patients would reach 12 month intervention free survival (χ2 = 58.53, df 10, P = < 0.0001). Entered as a set the model explained between 25.4% (Cox & Snell R square) and 34.3% (Nagelkerke R square) of the variance in response to AZA/MP. The Hosmer and Lemeshow Test confirmed that the model demonstrated a good fit (χ2 = 3.008, df 8, P = 0.934). The sensitivity of the model was 67.5% and the specificity 80.8%, correctly predicting response at 12 months in 75.5% of patients within this model. The PPV and NPV were 70.1% and 78.0% respectively. Within the model, RRM2 rs1130609 (OR 0.354, 95% CI 0.181-0.691) and a higher normalised dose of AZA/MP were strongly associated with protection from non-response (OR 0.310, 95% CI 0.154 – 0.624). Whereas, the presence of CD (OR 5.007, 95% CI 2.179 – 11.507) and the ABCA1 rs2230808 polymorphism (OR 2.585, 95% CI 1.286 – 5.193) were most strongly associated with non-response. Furthermore, there was a borderline association for higher TPMT activity and a higher MeMP : TGN ratio and failure to achieve 12 month intervention free survival.

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Table 6.23: Variables included in a multiple logistic regression model to predict 12 month intervention free survival.

Exp(B) 95% CI Exp(B) Variable B S.E. Wald Df Sig Lower Upper Age -0.37 0.15 6.161 1 0.13 0.964 0.937 0.992 Presence of 1.611 0.425 14.396 1 <0.0001 5.007 2.179 11.507 CD RBC TPMT 0.66 0.24 7.965 1 0.005 1.069 1.020 1.119 activity Normalised dose of -1.170 0.357 10.779 1 0.001 0.310 0.154 0.624 AZA/MP MeMP:TGN 0.26 0.13 4.264 1 0.039 1.027 1.001 1.052 ratio RRM2 -1.040 0.342 9.258 1 0.002 0.354 0.181 0.691 rs1130609 ABCA1 0.950 0.356 7.116 1 0.008 2.585 1.286 5.193 rs2230808 ABCB1 -0.774 0.366 4.488 1 0.034 0.461 0.225 0.944 rs2032582 GSTP1 -0.565 0.343 2.712 1 0.100 0.569 0.290 1.113 rs1695 ABCC5 -0.721 0.353 4.160 1 0.041 0.486 0.243 0.972 rs7636910

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6.4 Discussion

The results of this study provide novel insights into the mechanisms underlying both thiopurine hypermethylation and clinical response to AZA/MP in patients with IBD. No single polymorphism accounted for either event, however, modelling of genetic variants within the thiopurine and methylation pathways, in combination with relevant covariates, appears to explain at least some of the heritability. In this regard, thiopurine hypermethylation was best explained by a model which includes polymorphic variation in a nucleotide transporter (ABCC4 rs9524891) and enzymes with demethylating (ALKBH1 rs6494 and MGMT rs12917), dephosphorylating (NT5E rs2229524) and deaminating activities (GDA rs11143230). Meanwhile, intervention free survival during the first 12 months of AZA/MP therapy was best explained by a model which included polymorphic variation in a subunit of ribonucleotide reductase (RMM2 rs1130609), efflux transporters (ABCA1 rs2230808; ABCB1 rs2032582; ABCC5 rs7636910) and a glutathione-S-transferase (GSTP1 rs1695).

The study included data on a large number of patients with IBD treated with AZA/MP at a single centre. In comparison with the reported incidences of UC (156-291/100,000) and CD (8- 214/100,000) from epidemiological studies, CD appeared overrepresented in this cohort (3, 9). However, this is illustrative of the population of patients with IBD attending secondary care. The number of patients with thiopurine hypermethylation was also higher (21.1% vs 12.2%) than expected in comparison with the data presented in Chapter 3. However, this may have arisen since patients with thiopurine hypermethylation were actively sought for the current study. The number of patients failing to achieve intervention free survival during the first 12 months of therapy is consistent with the data presented in Chapter 4 and comparable to the published literature (58, 59). The data also confirmed the association of thiopurine hypermethylation with a higher weight- normalised dose of thiopurine and older age, as suggested by the logistic regression analysis presented in chapter 3 (section 3.3.8); however an influence of gender was not observed.

6.4.1 A model predicting thiopurine hypermethylation

This study represents the first attempt to investigate thiopurine hypermethylation and also clinical response to AZA/MP therapy using an exome-wide approach. Using whole genome expression analysis in blood samples from a small cohort of thiopurine treated patients with IBD (n = 21), Haglund et al identified 14 genes apparently associated with thiopurine metabolite concentrations and the MeMP/TGN ratio, including; hydrogen voltage-gated channel 1 (HVCN1), TOX high mobility group box family member 4 (TOX4), small ArfGAP2 stromal membrane-associated GTPase-activating protein 2 (SMAP2), differentially expressed in FDCP 8 homolog (DEF8), phospholipase C, beta 2

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(PLCB2), ubiquitin-conjugating enzyme E2A (UBE2A), family with sequence similarity 156 member A (FAM156A), Cd1d molecule (CD1D), tumour suppressor candidate 2 (TUSC2), guanine nucleotide binding protein (G protein) beta polypeptide 4 (GNB4), custom probe mitogen activated protein kinase kinase kinase 1 (MAP3K1), fatty acyl CoA reductase 1 (FAR1), leucine aminopeptidase (LAP3) and cathepsin S (CTSS) (402). However, no genes with known associations with the metabolic pathways of thiopurine drugs or purine metabolism were identified. In an expanded cohort of 54 patients with IBD (n = 19/54 with hypermethylation), additional associations were reported for genes related to thiopurine metabolism, including; IMPHD2, microsomal glutathione S-transferase 2 (MGST2), nucleoside diphosphate kinase 6 (NME6), NT5E and TPMT (402). The current data also support associations between thiopurine metabolite profiles and both NT5E and TPMT, although no other signals were found for any of the other genes reported by Haglund et al. This may be because of differences in the platforms used to identify candidate genes, in addition to the small cohort size in the previous study, which would have increased the false discovery rate. In a larger study published in abstract form by Karsan et al., which included 258 subjects investigated using an ImmunoChip platform consisting of 120,652 SNPs, additional genes were proposed to influence thiopurine hypermethylation, including; PR domain zinc finger protein 1 (PRDM1), proteasome assembly chaperone 1 (PSMG1), cullin-2 (CUL2), G-protein coupled receptor 65 (GPR65), transmembrane protein 135 (TMEM135), ubiquitin-conjugating enzyme E2E 3 (UBE2E3), fatty acid binding protein 6 (FABP6), solute-like carrier 14 member 2 (SLC14A2) and golgi/endoplasmic reticulum recycling molecule (423). However, this study did not correct for multiplicity and none of the reported genes are known to be associated with thiopurine or purine metabolism. Indeed, 5 of these genes (PRDM1, PSMG1, CUL2, GPR65 and TMEM135) are thought to be associated with susceptibility to IBD (24, 25). Overall the combined data support a hypothesis that thiopurine hypermethylation is a complex trait occurring as a consequence of interactions between several different genes.

A model including SNPs in ABCC4 (rs9524891), ALKBH1 (rs6494), MGMT (rs12917), NT5E (rs2229524), GDA (rs11143230), the weight-normalised dose of thiopurine and age, explained approximately 1 in 4 cases of hypermethylation. Within this model the strongest predictor of hypermethylation was the presence of the MGMT rs12917 (Phe/Phe) haplotype. A role for MGMT in the pathogenesis of thiopurine hypermethylation is plausible since this enzyme is involved in the demethylation of O6-methylguanine, and it is also known to demethylate methylthioguanine, albeit with significantly slower enzyme kinetics (115, 424). Furthermore, high MGMT activity has been associated with resistance to thioguanine in melanoma cell lines (425). In healthy individuals the

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MGMT rs12917 (Phe/Phe) haplotype is also associated with the formation bulky DNA adducts, suggesting that it is functionally relevant (426).

Analogous to MGMT, the AlkB homologue family, of which there are nine members in the human genome, provides a further example of direct repair of methylated bases in nucleic acids (427, 428). All nine known human AlkB-homologues are expressed, however biochemical activities have hitherto only been identified for ALKBH1, 2 and 3 (429, 430). In particular, ALKBH1 has a wide range of substrates and is capable of demethylating 1-methylguanine, which is structurally similar to methylthioguanine. However, to date, there are no studies examining the influence of ALKBH1 activity on thiopurine metabolism and furthermore, the relevance of the rs6494 (Met/Leu) variant on protein expression / activity remains undetermined. The association between this polymorphism and protection from hypermethylation suggests that it may increase the activity of ALKBH1, however this requires confirmation.

NT5E is involved in the hydrolysis of extracellular thiopurine nucleotide monophosphates. In lymphoblastoid cell lines exposed to TG, expression of NT5E is positively correlated with intracellular TGN levels (109). Hence reduced expression of NT5E could explain the lower TGN levels observed in thiopurine hypermethylation. In this regard, Li et al demonstrated that the NT5E rs2229524 variant predicts reduced expression of NT5E, which would be consistent with this hypothesis and explain the association reported here (109). In the same study an additional SNP in the 5’-flanking region, rs9450278, appeared to have an even stronger effect on NT5E expression, however this variant was not present on the exome microarray. Examination of this variant using a Taqman probe and real- time PCR applied to the current cohort is therefore indicated.

The finding that GDA rs11143230 is associated with thiopurine hypermethylation is of interest. This SNP is approximately 30Kb downstream of the GDA gene. In a cohort of 706 adult patients this polymorphism was shown to predict an increased risk of depression and suicidal ideation, suggesting that it is functionally relevant. However, studies investigating the influence of variation in GDA activity on thiopurine metabolism are lacking. Theoretically, since GDA is involved in the conversion of TG to TX, reduced GDA activity would predict lower levels of TX, a potent inhibitor of TPMT activity (Chapter 8); hence diminished restriction of TPMT activity in nucleated cells may explain the association with hypermethylation. The effect of GDA inhibitors on the metabolism of AZA/MP in nucleated cells should now be studied to explore this concept further.

The finding that a variant in the ABCC4 gene is associated with hypermethylation is consistent with the observation that ABCC4 acts as a transporter of MeTIMP (108). ABCC4 rs9524891 (C > T) codes a

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‘silent’ mutation in intron 1. Whilst described as ‘silent’ such SNPs may be of biological relevance since they can affect protein function by altering conformational structure or interfere with microRNA binding (431). In this regard, the ‘is-rSNP’ algorithm (432) (using the TRANScription FACtor database (433)) reported that the binding affinity of two transcription factors, peroxisome proliferator activated receptor α: retinoid x receptor α complex (PRPP α:RXR α) and peroxisome proliferator- activated receptor (PRPP), implicated in the regulation of ABCC4, may be impaired by the presence of the minor allele at rs9524891 (434). The effect of this variant on ABCC4 expression and transporter activity should now be investigated in cell models and the association with hypermethylation validated in independent cohorts.

6.4.2 Models predicting high MeMP concentrations and low TGN levels

Examining for variants associated with high MeMP levels or low TGN levels separately, identified additional associations relevant to thiopurine hypermethylation. In an unsupervised analysis an association between UGT2A2 rs4148301 and high MeMP levels was observed. Whilst not passing correction for multiple testing this result may be of relevance, since 8-oxo-MeMP, an intermediate in the degradation of MeMP, is known to form a glucuronide conjugate, which increases its water solubility to facilitate excretion (435, 436). However, the specific uridine 5’-disphosphate- glucuronosyltransferase (UGT) responsible for this reaction remains unknown. UGT2A2 is a potential candidate since it is expressed in the human intestine and it has been implicated in the glucuronidation of a wide range of xenobiotics (437, 438). Furthermore, the SIFT algorithm predicts that the UGT2A2 rs4148301 (p.R308G) polymorphism is deleterious to protein function (439). This variant should therefore be validated in independent cohorts and the effect of UGT2A2 inhibitors on the intracellular concentrations of MeMP intermediates should be assessed.

The finding that two variants ≈ 14Kb upstream of KLF-14, rs972283 and rs4731702, are associated with protection from high MeMP concentrations, is consistent with work demonstrating that KLF-14 acts as a master trans-regulator of TPMT expression. In adipose tissue from a cohort of 856 Caucasian female individuals, the KLF-14 rs4731702 variant was associated with reduced expression of TPMT (237). Attenuated expression of TPMT would directly explain the lower MeMP seen in the group demonstrating heterozygosity and homozygosity for the minor alleles at rs972283 and rs4731702. Yet the work presented here, in addition to the data presented in Chapters 3 and 4; shows that variation in RBC TPMT activity does not explain high MeMP levels. This paradox may be explained by a lack of KLF-14 expression in the adult liver and bone marrow, in comparison with high levels of expression in the intestine and skeletal muscle, suggesting differential expression of TPMT

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In Chapter 5 I demonstrated a significant, albeit weak association between homozygosity for the minor allele at ABCB5 rs2301641 (c.343 A > G) and thiopurine hypermethylation. This relationship was strengthened when patients with MeMP levels above or below 5000 pmol/8x108 RBC were compared. These findings were not replicated by the current study, which found that this variant was actually associated with low TGN levels. The reason for the divergent results may relate to the lack of PCA in the previous study, which is required to account for population stratification within the dataset. Furthermore, in the previous study, this variant explained approximately 13% of the cases where MeMP levels were > 5000 pmol/8x108 RBC, suggesting that the majority of cases are explained by other genetic factors, which have been explored in the current work. Nonetheless, the finding that ABCB5 rs2301641 is associated with differences in thiopurine metabolite profiles in both studies is consistent with the hypothesis that this transporter is involved in thiopurine metabolism. Further work should involve expression of this transporter in cell models to establish its role in influencing thiopurine metabolite profiles.

The finding that TGN levels were significantly lower when polymorphisms in ABCC4 and NT5E (rs9524891 and rs2229523 respectively) coincided, is consistent with the model of extracellular thiopurine metabolism proposed by Li et al, in which TGMP is transported out of the cell by ABCC4, prior to hydrolysis via NT5E with subsequent uptake of TG-riboside into cells via SLC28/29 (109). This result also provides a good example of genetic epistasis, which is likely to explain much of the heritability of individual variation in thiopurine metabolism.

Overall, separate modelling of variants associated with high MeMP levels or low TGN levels did not explain as much of the apparent heritability, in comparison with the model of MeMP : TGN concentration ratios. Therefore, future studies investigating variants associated with hypermethylation should focus on using the metabolite ratio to define cases and controls.

6.4.3 A model predicting clinical response to thiopurines

In this large cohort of patients for which clinical response data was available, a model including SNPs in RRM2 (rs1130609), ABCA1 (rs2230808), ABCB1 (rs2032582), GSTP1 (rs1695), ABCC5 (rs7636910), age, the presence of CD, RBC TPMT enzyme activity, the weight-normalised dose of AZA/MP and the MeMP : TGN concentration ratio, explained approximately 1 in 3 cases of failure to achieve intervention free survival during the first 12 months of AZA/MP therapy. Within this model RRM2 rs1130609 and a higher weight-normalised dose of AZA/MP were most strongly associated with

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The RRM2 gene encodes a small subunit of RNR, which is the key enzyme involved in the biosynthesis of deoxynucleotides and hence dTGTP. Since reduction in the levels of ribonucleotides is a rate-limiting step in DNA synthesis, reduced activity of RNR may predict attenuated dTGTP levels and therefore clinical response to thiopurines. RRM2 rs1130609 codes an amino acid change (S59A) in exon 1 of the gene. In 89 patients with AML, the minor allele of the RRM2 SNP rs1130609 was associated with greater sensitivity to cytarabine in diagnostic leukaemic blasts (lower IC50) and, accordingly, higher rates of both event free and overall survival (440). This is consistent with the higher rate of intervention free survival observed in the current study. It is possible that the RRM2 rs1130609 variant can directly influence cellular dTGTP and TGTP levels to explain this effect. Alternatively, altered RNR levels / activity may influence clinical response by interfering with its biological role in DNA synthesis, repair and cell growth.

In a study of 266 patients with IBD treated with AZA/MP at a single centre, response to treatment was associated with female gender, a shorter disease duration, higher MCV and Hb levels and lower CRP concentrations (441). However, the subtype of IBD, weight-normalised dose of AZA/MP, smoking behaviour and age did not appear to influence response. In the current study, higher MCV and haemoglobin levels were also associated with successful therapy. However, the small differences in MCV and Hb observed between responders and non-responders are unlikely to helpful in personalising treatment strategies at an individual patient level.

The association between ABCA1 rs2230808 and failure of AZA/MP treatment response is difficult to interpret and may be indirect. ABCA1 mediates the efflux of excessive intracellular cholesterol and phospholipids from the cellular membrane, and whilst it has a wide range of substrates, it is not known to transport thiopurine metabolites (442). Earlier observations have shown that the accumulation of various lipids, including cholesterol, oxysterols and fatty acids in cells like mast foam cells, can induce an inflammatory response and up-regulate ABCA1 gene expression (443, 444). Consequently, over-expression of ABCA1 observed during active UC is hypothesized to assist cells in reducing the load of harmful oxidized lipids and circumvent cell death (444). Thus attenuated lipid transport due to polymorphic variation in ABCA1 may predict higher levels of cellular inflammation. In this regard the ABCA1 rs2230808 (R1587K) has been associated with higher concentrations of triglycerides, total cholesterol and low density lipoprotein cholesterol (445). Therefore, the ABCA1 rs2230808 variant may represent a risk factor for cellular inflammation and therefore a more severe

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In the current study variants in ABCB1 (rs2032582), GSTP1 (rs1695) and ABCC5 (rs7636910) were associated with improved rates of intervention free survival during the first 12 months of AZA/MP therapy. This contradicts earlier findings in paediatric ALL that the presence of ABCB1 T/T at the 2677 (rs2032582) position is associated with lower rates of event free survival (446). However, this may have occurred as a result of lower systemic dexamethasone exposure due to higher ABCB1 expression on the apical villi of enterocytes, causing enhanced extrusion of drugs into the intestinal lumen, as opposed to a direct effect on thiopurine metabolites (447). Therefore the effect of polymorphisms on ABCB1 activity may be dependent on the substrates as well as the tissues studied. Meanwhile, the presence of GSTP1 G/G at the 313 (rs1695) position has been associated with significant reductions in central nervous system relapses in patients with ALL and a lower risk of chemoresistance amongst doxorubicin treated patients with breast cancer, which is consistent with a protective effect on clinical response as reported here (448, 449). The influence of the ABCC5 rs7636910 variant on clinical outcomes has not previously been investigated and requires validation in independent cohorts.

6.4.4 Critical evaluation of methodology

The Illumina HumanExome Beadchip used in the current study includes markers focused on protein- altering variants derived from > 12,000 exome and genome sequences representing multiple complex traits and ethnicities. However, given the content of the exome array, the study is limited in its ability to detect very rare variants or to investigate the effects of polymorphisms in promoter sequences, insertion-deletion (indels) mutations and copy number variations. The latter is thought to account for up to 12% of human genomic DNA and may be responsible for a substantial proportion of human phenotypic variability. For example copy number variation in the ABCC4 gene, which leads to high ABCC4 expression, has recently been shown to be an independent poor prognostic risk factor for oesophageal squamous cell carcinoma (450). Whole genome sequencing would therefore be a more ideal method to investigate additional genetic aberrations associated with thiopurine hypermethylation and treatment response. Furthermore, the analysis presented here would be strengthened with the use of gene-based testing that encompasses burden tests accounting for situations in which protective, deleterious, and null variants are present within the same gene, and in which a large number of variants are causal and associated in the same direction (348).

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The present study defined a failure of intervention free survival during the first 12 months of AZA treatment as either i) hospitalisation for management of active disease, ii) unexpected surgery, iii) switch to an alternative immunomodulator because of poor treatment efficacy, iv) escalation to anti- TNF-α therapy, v) steroid maintenance or a new steroid course vi) switch to low dose AZA/MP with allopurinol. Whilst considered harder end-points than the treating physician’s global assessment, use of clinical disease activity scores (HBI, SCAI etc), and measurement of trimesters of remission or evidence of mucosal healing may have provided more robust data. Nonetheless, one year intervention free survival is a fairly strict endpoint for use in this type of retrospective study.

6.4.5 Conclusion

In summary, the current study supports the use of whole pathway analysis using SNPs in genes related to the thiopurine and methylation pathways as a novel means to conduct large-scale candidate gene association studies. As shown here this has provided new insights into the mechanisms of thiopurine hypermethylation and clinical response to thiopurines. Both appear to be complex traits due to the interplay between SNPs in several different genes, in addition to SNP- environment interactions. Failure to account for such interactions, likely explains the divergent results of smaller candidate gene studies, which confuse much of the current literature investigating individual variation in thiopurine response. Future studies, ideally using whole genome sequencing, should focus on replicating the markers discovered in these inception cohorts, with the goal of creating a panel of biomarkers that predict thiopurine hypermethylation and clinical response. At present, a metabolite ratio 4 weeks after the start of treatment remains the best tool to determine patients at risk of thiopurine hypermethylation that may benefit from combination treatment with allopurinol.

Summary of key findings:

 A model including polymorphic variation in ABCC4, ALKBH1, MGMT, NT5E, GDA, the weight normalised dose of thiopurine and age, explains approximately 25% of the heritability of thiopurine hypermethylation.  Polymorphic variation upstream of KLF-14, a master trans-regulator of TPMT expression, is associated with protection from high MeMP concentrations.  TGN levels are significantly lower in patients where polymorphic variation in ABCC4 and NT5E coincide, consistent with an influence on the cellular export of thiopurine nucleotides and their extracellular degradation to nucleosides.

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 Polymorphic variation in RRM2, which codes a small subunit of ribonucleotide reductase, protects against failure of 12 month intervention free survival.  A model including polymorphic variation in RRM2, ABCA1, ABCB1, GSTP1, ABCC5, age, the presence of CD, RBC TPMT activity, the weight-normalised dose of thiopurine and the MeMP : TGN concentration ratio, explains approximately 1 in 3 cases of failure to achieve 12 month intervention free survival.

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Chapter Seven: A search for novel variants predicting adverse drug reactions in patients with IBD prescribed thiopurines.

7.1 Introduction

Despite good clinical efficacy, thiopurines demonstrate wide inter-individual variability in terms of treatment outcomes. Indeed 15 – 28% of patients develop ADRs, which can be classified into two categories according to thiopurine metabolism (179, 293, 451). Firstly, there is dose independent toxicity, which includes flu-like symptoms, rash, acute pancreatitis and some cases of hepatotoxicity. These ADRs usually occur within the first few weeks of therapy. Secondly, there is dose dependent toxicity, which relates to intracellular concentrations of active metabolites and includes bone marrow suppression and hepatotoxicity. These ADRs may appear months or even years after the initiation of therapy.

Gastrointestinal intolerance, characterised by abdominal pain, nausea and vomiting, and a flu-like illness (myalgia, headache, and diarrhoea) are the most common adverse events reported on thiopurine therapy. These symptoms are observed in 10 – 20% of patients during weeks 2 – 3 of therapy and rapidly resolve upon drug withdrawal (83, 452). A prospective study showed that gastrointestinal intolerance is more frequent in patients carrying a heterogeneous genotype for TPMT as compared to those with wildtype TPMT (150). However, this is not a universal finding and is refuted by a large retrospective analysis (163). Meanwhile, polymorphic variation in protein kinase C and casein kinase substrate in neurons 2 (PACSIN2) has recently been associated with the development of severe gastrointestinal toxicity in patients with ALL, although this finding is yet to be confirmed in IBD (453). Overall, gastrointestinal intolerance leads to discontinuation of treatment in less than 10% of patients; however it is likely to contribute to poor adherence in a much larger number of cases (163).

Myelosuppression, typically represented by mild leucopaenia (WBC: 2.0 – 4.5 x 109/ L) and neutropaenia (neutrophil count < 1.5 x109/ L), is the next most common side effect of thiopurines, reported in 2 – 10.5% of patients receiving conventional drug doses (169, 454, 455). It can occur abruptly at any point during treatment, although it is usually evident within the first few months, beginning as early as 2 weeks after the introduction of thiopurines (454). Data from meta-analysis suggest a myelotoxicity incidence rate of 3% per patient per year, and 0.9% for severe myelotoxicity, defined as a neutrophil count < 1 x109/ L (CTC grade 3-4 toxicity). The presence of myelosuppression is strongly linked to low RBC TPMT activity and high TGN levels (165, 456). Accordingly, pre-treatment screening for TPMT deficiency is recommended to facilitate dose-adjustment (37). However, this

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Thiopurine-induced pancreatitis, characterised by the development of epigastric pain, nausea, vomiting and elevation of the serum amylase levels, often occurs in conjunction with flu-like symptoms, rash, arthralgia and fever, as part of an allergic-type reaction. It is observed in 1.4 – 3.3% of patients by a median of 23 days after the introduction of AZA/MP and usually resolves within a mean of 3 days following drug withdrawal (83). The mechanism appears independent of MeMP and TGN levels and is thought to be immune mediated (83, 459). The ITPase 94 C > A missense mutation has been proposed as a marker of pancreatitis and flu-like symptoms (150, 293). On the other hand several other studies and one meta-analysis did not report any significant association, suggesting the involvement of additional factors (295, 299, 303).

Thiopurine-induced liver injuries can be divided into three syndromes: hypersensitivity reactions, dose dependent hepatitis and nodular regenerative hyperplasia, i.e. endothelial injury with raised portal pressures resulting in veno-occlusive disease (460). A recent systematic review, including 3485 patients with IBD, suggests an overall hepatotoxicity prevalence of 3.4%, with a yearly incidence rate of 1.4% (461). This is consistent with the results of a long-term follow-up study of 3931 patients with IBD, which reported a prevalence of 4% (462). Hepatotoxicity, manifested by a rise in transaminases usually develops during the induction phase of therapy, after a median of 1.5 – 3 months (163, 463, 464). The mechanism of thiopurine-induced liver injury remains unclear, but a proportion of cases, as confirmed in this thesis (Chapters 3 and 4), appear to be related to the presence of high MeMP concentrations (64, 161, 162, 465).

Importantly, where toxicity to thiopurines is encountered, several strategies can be attempted to prevent treatment failure. For example, gastrointestinal intolerance may be reduced with a short period of treatment cessation followed by reintroduction at a lower dosage or by-passed with a switch from AZA to MP (466, 467). Prescription of low dose AZA/MP with allopurinol has also been used in patients developing gastrointestinal intolerance, an approach which is also successful in circumventing thiopurine-induced hepatotoxicity (181). Meanwhile, for patients exhibiting immune- allergic reactions on AZA/MP such as pancreatitis, treatment with TG has been proposed (468). Therefore biomarkers predicting ADRs prior to the start of treatment would allow the early

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The hypothesis of this study was that variants within and external to the thiopurine and methylation pathways would provide additional explanations for thiopurine-induced ADRs. The aim of this study was therefore to identify novel markers that predict the development of thiopurine induced ADRs including; nausea, flu-like symptoms, pancreatitis and hepatotoxicity. Using an exome microarray, which focuses on functionally relevant coding region variants, we performed a genetic analysis on blood samples from a large cohort of patients with IBD prescribed thiopurines and related the findings to treatment outcomes.

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7.2 Methods

7.2.1 Patients

Patients were recruited from the IBD Pharmacogenetics Study at GSTT (Research and Ethics Committee Reference, 12/YH/0172; Research and Development reference, RJ112/N179). All patients were adults and provided written and informed consent. Of the 763 patients with IBD, 472 had received treatment with AZA/MP. In each case, clinical records and results were reviewed retrospectively to record data on demographics, type of IBD, pre-treatment RBC TPMT activity, thiopurine type, weight-normalised dose, treatment outcomes and haematological and biochemical parameters taken as part of standard immunosuppression monitoring. 412 of the 472 patients had adequate data describing treatment outcomes with respect to drug tolerance or the development of thiopurine-induced ADRs. Patients receiving low dose AZA/MP with allopurinol were excluded. Subsequently, 154 patients developing at least 1 ADR, defined using the CTC criteria described in section 2.2.1, were compared to 258 patients demonstrating tolerance to AZA/MP using a case- control design. Sub-analyses investigating for specific genetic variants associated with nausea, flu- like symptoms, pancreatitis and hepatotoxicity (ALT ≥ 2.5 x upper limit of the normal range), were completed using the same cohort. Pancreatitis was defined as the development of epigastric pain, nausea and vomiting, in conjunction with a serum amylase ≥ 240 units/ L and radiographic evidence of pancreatitis. This is consistent with the definition of thiopurine-induced pancreatitis used by the UK IBD Genetics Consortium “PRED4” Study (http://www.ibdresearch.co.uk/pred4/).

7.2.2 Illumina human exome beadchip and statistical analysis

Preparation of genomic DNA samples and analysis using the Ilumina Infinium Human Exome 250K Beadchip is described in Sections 2.3.2, 2.3.5 and 6.2.2. Statistical analysis was identical to the description provided in Section 6.2.3, based on the algorithm developed and validated in Section 2.4.3.

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7.3 Results

7.3.1 Cohort of adult patients with IBD receiving AZA/MP with outcome data describing thiopurine toxicity or tolerance

Of the 472 patients prescribed AZA/MP, data on treatment related toxicity was available for 412 patients (87.3%). Of these 412 individuals, 154 (37.4%) reported the development of at least 1 ADR related to treatment (table 7.1). The majority of these were either transient or circumvented with a change in the thiopurine treatment regimen (i.e., dose reduction, switch from AZA to MP, or a switch to low dose AZA/MP with allopurinol); however in 59 patients AZA/MP therapy had to be withdrawn (38.3% of patients with toxicity and (59/412) 14.3% overall). After exclusion of patients with missing data for any of the categories of toxicity investigated (nausea, flu-like symptoms, pancreatitis, hepatotoxicity, myelotoxicity and rash), 258 (62.6%) patients were shown to tolerate AZA/MP without the development of side effects.

In total 202 adverse events were recorded in 154 patients prescribed AZA/MP monotherapy. Nausea was the most common side effect occurring in 20.1% of patients (figure 7.1). The finding that 31.8% of individuals reported more than one adverse reaction, may suggest that the causative genetic variants are common to more than one type of toxicity. For example, 21/83 (25.3%) patients with nausea also reported concomitant flu-like symptoms.

Table 7.1: Adverse drug reactions related to AZA/MP therapy in patients with IBD

Number patients (with full data available) confirming 258/412 (62.6%) tolerance to AZA/MP, n (%) Number of patients with missing data 60/472 (12.7%) Number of patients intolerant of AZA/MP, n (%): 154/412 (37.4%) Patients reporting more than 1 toxicity 49/154 (31.8%) Therapy withdrawn due to toxicity 59/154 (38.3%) Episodes of adverse events, n (%): 202 in 412 patients

Nausea 83/412 (20.1%) Flu-like symptoms 40/412 (9.7%) Pancreatitis 17/412 (4.1%) Hepatotoxicity 34/412 (8.3%) Myelotoxicity 19/412 (4.6%) Rash 9/412 (2.2%)

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No toxicity Nausea Flu-like symptoms Pancreatitis Hepatotoxicity Myelotoxicity Rash

Figure 7.1 Incidence of adverse reactions related to AZA/MP therapy in 412 patients with IBD. Total number of adverse events n = 202, nausea n = 83 (20.1%), flu-like symptoms n = 40 (9.7%), pancreatitis n = 17 (4.1%), hepatotoxicity n = 34 (8.3%), myelotoxicity n = 4.6%, rash n = 9 (2.2%).

When all patients with toxicity were combined as a set and compared to patients without toxicity, there was a trend towards older age being associated with an increased risk of ADRs (P = 0.073, table 7.2). More patients with toxicity were receiving MP (P = < 0.0001); however, this is likely to represent attempts to circumvent ADRs by switching from AZA to MP, since AZA is usually prescribed as the first line agent. The weight-normalised dose was higher in patients tolerating AZA/MP (mean difference = 0.15 mg/ kg/ day) in comparison with those who developed ADRs. This is consistent with difficulties in escalating the dose of AZA/MP in the latter group due to dose-dependent toxicity.

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Table 7.2 Demographic comparison of patients with and without adverse drug reactions related to AZA/MP therapy.

Patients without Patients with Significance Variable toxicity related to toxicity related to P value, OR AZA/MP AZA/MP (95% CI) Number of patients with IBD, n (%) 258/412 (62.6%) 154/412 (37.4%) P = 0.416* Males, n (%) 134 (51.9%) 73 (47.4%) OR 1.199 Female, n (%) 124 (48.1%) 81 (52.6%) (0.804 – 1.788) Age (y) at study inclusion, mean ± SEM 38.3 ± 0.834 40.78 ± 1.083 P = 0.073† (range) (18 - 79) (21 - 85) (-5.143 – 0.228) P = < 0.0001* Prescribed AZA, n (%) 247 (95.7%) 111 (72.1%) OR 8.69 Prescribed MP, n (%) 11 (4.3%) 43 (27.9%) (4.323-17.50) Crohns, n (%) 180 (69.8%) 110 (71.4%) UC, n (%) 67 (26.0%) 36 (23.4%) P = 0.787¥ IBD-U, n (%) 11 (4.2%) 8 (5.2%) Smoking data missing, n (%) 20 (7.9%) 12 (7.8%) Non-smoker, n (%) 118 (45.7%) 73 (47.4%) P = 0.920¥ Ex-smoker, n (%) 87 (33.7%) 49 (31.8%) Current smoker, n (%) 33 (12.8%) 20 (13.0%) TPMT (pmol/ h/ mgHb) activity, n (%) 181/258 (70.2) 139/154 (90.3%) Median TPMT activity 34.0 34.0 P = 0.888

TPMT heterozygote activity, n (%) 24/181 (13.3%) 14/139 (10.1%) Normalised dose of thiopurine (mg/ kg/ P = 0.003† 1.89 ± 0.32 1.74 ± 0.46 day), mean ± SEM: (0.530 - 0.266) Thiopurine metabolite monitoring, n (%) 235/258 (91.1%) 99/154 (64.3%)

Av TGN (pmol/ 8x108 RBC) median (IQR) 303 (211 – 370) 300 (191 – 420) P = 0.852+ Av MeMP (pmol/ 8x108 RBC) 839 (308 – 2340) 489 (125 – 2532) P = 0.087+ Av MeMP : TGN ratio 2.76 (1.11 – 7.85) 2.17 (0.43 – 8.67) P = 0.162+

*Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; + Mann-Whiney U-test; ¥ 3 by 2 Chi- squared test.

7.3.2 Case-control study investigating for genetic variants associated with overall toxicity to AZA/MP therapy in patients with IBD

All 154 patients reporting adverse reactions to AZA/MP were compared to the 258 patients without evidence of toxicity. After excluding patients with missing genotype data, the cohort included 389 patients (145 cases vs. 244 controls), representing a loss of 5.6% of individuals. Following adjustment for MAF (>0.05%), genotype call success rate (>97%) and variants in complete LD (r2>0.99), 24,327 SNPs were included in an initial trait-SNP association study and data adjusted for the first 4 PCs (table 7.3).

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Table 7.3: Unsupervised trait-SNP association study of variants associated with toxicity to AZA/MP in patients with IBD

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR L U Control Cases Gene Upstream 6 rs847005 0.000137 1 1.847 1.347 2.532 0.289 0.414 SCML4 11 rs2234409 0.000187 1 1.811 1.326 2.472 0.367 0.503 UBE2L6 11 rs12223229 0.000272 1 1.779 1.305 2.426 0.365 0.500 SMTNL1 Upstream 12 rs2579028 0.000365 1 0.565 0.413 0.7735 0.506 0.372 IPO8 4 rs3816873 0.00044 1 0.531 0.383 0.763 0.336 0.214 MTTP Downstream 5 rs11959209 0.000471 1 0.541 0.176 0.383 0.332 0.203 MARCH11 3 rs6767666 0.000516 1 0.574 0.419 0.785 0.494 0.372 IGSF11 2 rs13428812 0.000578 1 1.751 1.273 2.409 0.309 0.431 DNMT3A 21 rs2824790 0.000662 1 0.527 0.187 0.762 0.307 0.203 TMPRSS15 10 rs946185 0.000694 1 1.714 1.255 2.34 0.344 0.462 ADK

Chr, chromosome; SNP ID, rs-number identifier; P(SNP), P-value of SNP; Bonf, bonferroni corrected P- value; OR, odds-ratio; 95% CI, lower and upper 95% confidence intervals; MAF, minor allele frequency.

No single variant in the unsupervised analysis demonstrated genome wide significance after correction for multiple testing. However three of the genes with variants in the top ten associations, Ubiquitin-Conjugating Enzyme E2L 6 (UBE2L6), transmembrane protease serine 15 (TMPRSS15) and ADK may be of relevance and are discussed later. Restriction of the analysis to Caucasian individuals alone (controls, n = 155 vs. cases, n = 98), reduced the significance level of both ADK rs946185 (P = 0.0091) and TMPRSS15 (P = 0.0035), and improved the association with UBE2L6 rs2234409 (P = 8.74x10-5), however no single variant passed the threshold for genome wide significance in an allelic model. Genotype modelling demonstrated that UBE2L6 rs2234409 was best explained by a recessive interaction, whereas ADK rs946185 and TMPRSS15 best fit dominant models (P = 0.0082 and P = 0.0120, respectively).

A supervised analysis confined to Caucasian individuals and polymorphisms within the thiopurine pathway, adjusted for the first 2 PCs, confirmed the association with ADK rs946185 and suggested additional variants influencing toxicity (table 7.4). Of these, two polymorphisms in ABCB5 (rs2301641 and rs1858948) were in moderately high LD (r2 = 0.78). Genotype modelling reported that dominant interactions best explained the associations with ADK rs946185 (P = 0.0082), ABCB5

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Table 7.4: Case-control analysis of AZA/MP mediated toxicity restricted to the thiopurine pathway

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR Controls Cases Gene 10 rs946185 0.0078 1 1.675 1.146 2.450 0.344 0.462 ADK 15 rs2242046 0.0168 1 1.600 1.088 2.353 0.414 0.476 SLC28A1 7 rs2301641 0.0170 1 0.608 0.404 0.915 0.338 0.279 ABCB5 5 rs3733890 0.023 1 1.586 1.067 2.357 0.258 0.321 BHMT 13 rs4148549 0.027 1 0.652 0.446 0.953 0.451 0.396 ABCC4 7 rs1858948 0.028 1 0.624 0.410 0.950 0.369 0.410 ABCB5 9 rs4149268 0.033 1 1.487 1.032 2.143 0.381 0.400 ABCA1 2 rs55754655 0.038 1 0.549 0.311 0.968 0.164 0.103 AOX1 P(SNP) reported for allelic models.

Pathway-centric analysis of all the SNPs in the thiopurine pathway, in comparison with the insulin pathway that was used as a control (P = 0.908), suggested that the thiopurine pathway was significantly associated with the development of adverse reactions to AZA/MP therapy (P = 0.032, top reported SNP NT5E rs1321744). Gene-centric analysis suggested that toxicity was most highly associated with the ADK (top SNP rs946185, P = 0.0024), AOX1 (top SNP rs55754655, P = 0.041) and GSTA5 (top SNP rs2397118, P = 0.048) genes.

Testing for epistasis between polymorphisms in the thiopurine pathway suggested interactions between ABCC4 (rs2274407) and AOX1 (rs55754655) (χ2 = 10.14), SLC28A1 (rs2290272) and NT5E (rs2229524) (χ2 = 7.64) and ADK 2271415 and NT5E rs1321744 (χ2 = 7.38).

Based on the results of the trait-SNP association studies, pathway centric and gene-centric analyses, polymorphisms in ADK (rs946185), SLC28A1 (rs2242046), ABCB5 (rs2301641), ABCC4 (rs4148549), AOX1 (rs55754655) and NT5E (rs1321744 and rs2229524), were combined in a logistic regression genotype specific model to determine the percentage variance of AZA/MP toxicity that could be explained. Gender and age but not the weight-normalised thiopurine dose was included as covariates. When combined, a test of the full model against a constant-only model was statistically significant, indicating that, as a set, the predictors reliably distinguished patients with AZA/MP induced toxicity (χ2 = 33.85, df = 1, P = <0.0001). As a whole the model explained between 12.6% (Cox and Snell R Squared) and 17.1% (Nagelkerke R squared) of the toxicity observed, and correctly

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Table 7.5: Variables included in a multiple logistic regression model to predict AZA/MP mediated toxicity.

95% CI Exp(B) Variable B S.E. Wald Df Sig Exp(B) Lower Upper Gender 0.181 0.291 0.387 1 0.534 1.199 0.677 2.121 Age 0.019 0.010 3.141 1 0.076 1.019 0.998 1.040 ADK rs946185 0.926 0.309 8.959 1 0.003 2.525 1.377 4.630 Dominant SLC28A1 rs2242046 0.702 0.329 4.562 1 0.033 2.018 1.060 3.844 Dominant ABCB5 rs2301641 -0.615 0.574 1.148 1 0.284 0.540 0.175 1.665 Recessive ABCB5 rs1858948 0.528 0.353 2.234 1 0.135 1.695 0.849 3.386 Dominant ABCC4 rs4148549 0.060 1.309 0.002 1 0.963 1.062 0.82 13.807 Dominant AOX1 rs55754655 -0.776 1.302 0.355 1 0.551 0.460 0.036 5.906 Dominant NT5E rs2229524 -0.503 0.298 2.853 1 0.091 0.605 0.337 1.084 Dominant NT5E rs1321744 -0.383 0.296 1.674 1 0.196 0.682 0.382 1.218 Dominant

Since investigation for variants associated with AZA/MP toxicity, combining all categories of toxicity together, did not provide a complete explanation for adverse reactions, separate sub-analyses were completed for nausea, flu-like symptoms, pancreatitis and hepatotoxicity. The cohort of patients with myelotoxicity and rash were considered too small for meaningful analysis.

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7.3.3 Case-control study investigating AZA/MP induced nausea

Nausea and vomiting was reported in 83 of the 412 patients prescribed AZA/MP. It was not possible to circumvent nausea, using dose splitting, dose reduction or a switch from AZA to MP in 29 patients and these individuals withdrew from further thiopurine therapy (34.9% of those with nausea and 7% overall). Examination of the demographic data for AZA/MP induced nausea, demonstrated that MP was more commonly prescribed in patients with nausea (table 7.6). Furthermore, MeMP levels were lower in patients with nausea (difference between medians = 441 pmol MeMP/ 8x108 RBC, P = 0.006). This may have occurred because of the lower weight-normalised dose of thiopurine in this group; however it may also suggest increased shunting to additional unmeasured thiopurine metabolites.

Table 7.6: Demographic comparison of IBD patients with and without AZA/MP induced nausea.

Patients without Patients with Significance Variable AZA/MP induced AZA/MP induced P value, OR nausea nausea (95% CI) Number of patients with IBD, n (%) 258/412 (62.6%) 83/412 (20.1%) P = 0.107*, Males, n (%) 134 (51.9%) 34 (40.9%) OR 1.557 Female, n (%) 124 (48.1%) 49 (59.1%) (0.943 – 2.571) P = 0.078†, Age (y) at study inclusion, mean ± SEM 38.3 ± 0.834 41.3 ± 1.52 (-6.355 – (range) (17-79) (22-85) 0.324) P = < 0.0001*, Prescribed AZA, n (%) 247 (95.7%) 34 (40.9%) OR 32.36 Prescribed MP, n (%) 11 (4.3%) 49 (59.1%) (15.35 – 68.23) CD, n (%) 180 (69.8%) 63 (75.9%) UC, n (%) 67 (26.0%) 16 (19.3%) P = 0.465¥ IBD-U, n (%) 11 (4.2%) 4 (4.8%) Smoking data missing, n (%) 20 (7.9%) 8 (9.6%) Non-smoker, n (%) 118 (45.7%) 34 (41.0%) P = 0.794¥ Ex-smoker, n (%) 87 (33.7%) 29 (34.8%) Current smoker, n (%) 33 (12.8%) 12 (14.6%) TPMT (pmol/ h/ mgHb) activity, n (%) 181/258 (70.2%) 78/83 (94.0%) Median TPMT activity 34 35 P = 0.696‡

TPMT heterozygote activity, n (%) 24/181 (13.3%) 8/78 (10.3%) Normalised dose of thiopurine (mg/ kg/ 1.89 ± 0.03 1.69 ± 0.06 P = 0.0044+ day), mean ± SEM: Thiopurine metabolite monitoring, n (%) 235/258 (91.1%) 54/83 (65%)

Av TGN (pmol/ 8x108 RBC) median (IQR) 314 (211 – 356) 324 (208 – 397) P = 0.708+ Av MeMP (pmol/ 8x108 RBC) 832 (288 – 2314) 391 (83 – 1043) P = 0.0062+ Av MeMP : TGN ratio 2.66 (0.93 – 8.33) 1.54 (0.28 – 4.68) P = 0.015+ *Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; ‡Independent samples median test; +Mann-Whiney U-test; ¥ 3 by 2 Chi-squared test.

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Following exclusion of patients with missing genotype data, the cohort included 325 individuals (81 cases vs. 244 controls), representing a loss of 4.7% of patients. In the initial unsupervised trait-SNP association analysis, which included 24,327 SNPs, no single polymorphism demonstrated genome- wide significance (table 7.7). However, two of the variants, in the microsomal triglyceride transfer protein (MTTP) and pleckstrin homology domain containing family G member 2 (PLEKHG2) genes may be of interest and are discussed later. Dominant models of interaction improved the strength of the associations with MTTP rs3816873 and PLEKHG2 rs73033371, however neither passed correction for multiplicity. Constraining the analysis to Caucasian individuals alone (cases, n=61 vs. controls, n=155) did not reveal another variant with genome-wide significance and therefore the analysis was repeated following restriction to the thiopurine pathway.

Table 7.7: Unsupervised analysis of variants associated with nausea in patients with IBD prescribed AZA/MP.

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR L U Control Cases Gene 4 rs3816873 0.000135 1 0.400 0.251 0.641 0.336 0.173 MTTP 6 rs4712056 0.000156 1 2.116 1.435 3.12 0.316 0.482 MLIP 2 rs2945572 0.000169 1 2.136 1.438 3.172 0.430 0.593 LRP1B 16 rs6564838 0.000221 1 2.353 1.494 3.706 0.148 0.265 PKD1L2 10 rs2474570 0.000235 1 1.993 1.38 2.877 0.434 0.605 ZNF37A 19 rs73033371 0.000241 1 3.384 1.765 6.488 0.041 0.136 PLEKHG2 10 rs7088318 0.000248 1 0.469 0.314 0.704 0.432 0.259 PIP4K2A 16 rs11646512 0.000264 1 2.031 1.388 2.973 0.430 0.599 FTO 3 rs2366659 0.000352 1 0.506 0.349 0.736 0.502 0.352 FGF12 Downstream 5 rs11959209 0.000373 1 0.436 0.277 0.689 0.332 0.173 FBLX7 P(SNP) reported for allelic models.

Following adjustment for the first 2 PCs, restriction of the analysis to the thiopurine pathway demonstrated that 4 variants in the ABCB5 gene were associated with protection from nausea. These variants were in moderate LD (r2 = 0.33 – 0.78), suggesting partial independence of the mutations. The ABCC4 rs4148546 mutation also showed protection from nausea. A confounding variable of this result is the higher MeMP levels seen in the patients without nausea, since both ABCC4 rs4148546 and ABCB5 rs2301641 were previously shown to influence thiopurine metabolite profiles (Chapters 5 and 6). SLC28A1 rs2242046 and GDA rs11143230 were also associated with the development of nausea (table 7.8).

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Table 7.8: trait-SNP analysis of variants associated with nausea in patients with IBD prescribed AZA/MP restricted to the thiopurine pathway.

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR Controls Cases Gene 7 rs1858948 0.0027 0.483 0.440 0.258 0.753 0.363 0.216 ABCB5 7 rs2301641 0.0029 0.523 0.459 0.275 0.767 0.341 0.20 ABCB5 9 rs11143230 0.0083 1 1.808 1.165 2.805 0.295 0.417 GDA 0.490 0.288 0.835 0.183 0.305 Downstream 7 rs10950821 0.0087 1 ABCB5 7 rs34603556 0.0095 1 0.447 0.243 0.821 0.133 0.243 ABCB5 13 rs4148546 0.039 1 0.625 0.399 0.976 0.526 0.408 ABCC4 15 rs2242046 0.041 1 1.603 1.02 2.519 0.508 0.416 SLC28A1 14 rs7972 0.045 1 1.907 1.015 3.586 0.078 0.15 GSTZ1 P(SNP) reported for allelic models.

Genotype modelling of polymorphisms in the thiopurine pathway suggested that the 4 variants in ABCB5 best fit a dominant model of interaction and strengthened the association with ABCB5 rs1858948 (P = 0.0066). GDA rs11143230 (P = 0.015) and SLC28A1 rs2242046 (P = 0.056) were best explained by dominant models, whereas ABCC4 rs4148546 best fit a recessive model (P = 0.035) consistent with the previous thiopurine metabolite profile analyses.

In a pathway-centric analysis including all of the polymorphisms in the thiopurine pathway, the pathway as a set was not associated with AZA/MP induced nausea (empirical P-value = 1, top SNP MTHFD-1 rs2295639), suggesting the involvement of additional pathways or polymorphisms within the thiopurine pathway not included on the exome chip. In gene-centric analysis, only GDA was shown to be associated with nausea (P = 0.0185, top SNP rs1143230), whereas ADK (P = 0.089) and ABCC4 (P = 0.084) showed a trend towards an association. There was no association with the ABCB5 gene when all the polymorphisms (35 SNPs) in the gene were examined as a set.

Based on the results of the trait-SNP association, pathway-centric and gene-centric analyses, polymorphsisms in ABCB5 (rs1858948, rs2301641, rs10950821, rs34603556), GDA (rs11143230), ABCC4 (rs4148546) and SLC28A1 (rs2242046) were combined in a logistic regression model to determine the variance in nausea that could be explained by these variants. Age, the weight- normalised dose of thiopurine and average MeMP levels were included as covariates. Multivariate analysis using forwards logistic regression suggested that only ABCB5 rs2301641, ABCB5 rs34603556, ABCC4 rs41485461, SLC28A1 rs2242046, age and MeMP levels demonstrated independent influences on the development of nausea. Combining these variants in a model reliably separated

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Table 7.9: Variables included in a multiple logistic regression model to predict AZA/MP associated nausea

95% CI Exp(B) Variable B S.E. Wald Df Sig Exp(B) Lower Upper Age 0.029 0.012 5.380 1 0.020 1.029 1.004 1.055 Average 0.000 0.000 3.890 1 0.049 1.000 1.000 1.000 MeMP level ABCB5 rs2301641 -1.001 0.336 8.871 1 0.003 0.368 0.190 0.710 DOM ABCB5 rs34603556 -0.964 0.469 4.224 1 0.040 0.381 0.152 0.956 DOM ABCC4 rs4148546 0.636 0.339 3.515 1 0.061 0.381 0.152 0.956 REC SLC28A1 rs2242046 0.662 0.395 2.816 1 0.093 1.940 0.895 4.205 DOM DOM, dominant; REC, recessive

7.3.4 Case-control study investigating AZA/MP induced flu-like symptoms

Flu-like symptoms, typically characterised by a variable combination of myalgia, chills, pyrexia, diaphoresis, fatigue and headache, were reported in 40 of the 412 patients prescribed AZA/MP. The average time to the reporting of symptoms was 4.5 weeks (range 3 days to 16 weeks). Of the 40 cases, flu-like symptoms were circumvented in 25/40 (62.5%). This was achieved in 9/25 (36%) by a switch from AZA to MP and in 16/25 (64%) by changing to a low dose thiopurine with allopurinol. In 15 patients symptoms recurred on MP or combination treatment, leading to the withdrawal of therapy in these individuals.

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More patients with flu-like symptoms were prescribed MP than AZA (table 7.10). This likely reflects prior intolerance to AZA. However, historical data on previous exposure to AZA/MP therapy was not captured. The lower average weight-normalised thiopurine dose in patients with flu-like symptoms is consistent with difficulties with dose escalation in this group. There were no statistically significant differences in median TPMT activity or average thiopurine metabolite profiles between cohorts.

Table 7.10: Demographics of patients with AZA/MP induced flu-like symptoms in comparison with thiopurine tolerant patients.

Patients without Patients with flu- Significance Variable AZA/MP induced like symptoms on P value, OR flu-like symptoms AZA/MP (95% CI) Number of patients with IBD, n (%) 258/412 (62.6%) 40/412 (9.7%) P = 0.497* Males, n (%) 134 (51.9%) 18 (45%) OR 1.321 Female, n (%) 124 (48.1%) 22 (55%) (0.676 – 2.578) Age (y) at study inclusion, mean ± SEM 38.3 ± 0.834 39.9 ± 2.20 P = 0.471† (range) (17-79) (22-72) P = < 0.001* Prescribed AZA, n (%) 247 (95.7%) 27 (67.5%) OR 10.81 Prescribed MP, n (%) 11 (4.3%) 13 (32.5%) (4.413 – 26.49) CD, n (%) 180 (69.8%) 31 (77.5%) UC, n (%) 67 (26.0%) 8 (20.0%) P = 0.592¥ IBD-U, n (%) 11 (4.2%) 1 (2.5%) Smoking data missing, n (%) 20 (7.9%) 4 (10.0%) Non-smoker, n (%) 118 (45.7%) 17 (42.5%) P = 0.960¥ Ex-smoker, n (%) 87 (33.7%) 14 (35.0%) Current smoker, n (%) 33 (12.8%) 5 (12.5%) TPMT (pmol/ h/ mgHb) activity, n (%) 181/258 (70.2%) 38/40 (95%) Median TPMT activity 34 36.5 P = 0.152‡

TPMT heterozygote activity, n (%) 24/181 (13.3%) 3/38 (7.9%) Normalised dose of thiopurine (mg/ kg/ 1.89 ± 0.03 1.67 ± 0.09 P = 0.016+ day), mean ± SEM: Thiopurine metabolite monitoring, n (%) 235/258 (91.1%) 23/40 (57.5%)

Av TGN (pmol/ 8x108 RBC) median (IQR) 274 (178 – 364) 145.2 (0 – 402) P = 0.328+ Av MeMP (pmol/ 8x108 RBC) 738 (256 – 2390) 489 (53 – 1712) P = 0.136+ Av MeMP : TGN ratio 2.58 (0.80 – 8.29) 1.27 (0.08 – 3.74) P = 0.066+

*Two-sided Fisher’s exact test; †Two-tailed unpaired t-test; ‡Independent samples median test; +Mann-Whiney U-test; ¥ 3 by 2 Chi-squared test.

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In an unsupervised analysis, restricted to Caucasian individuals and adjusted for the first 2 PCs, multiple SNPs in the HLA region of chromosome 6 were associated with flu-like symptoms; however no single variant showed genome-wide significance in an allelic model (table 7.11 and figure 7.2). The polymorphisms upstream of HLA-B were in LD with each other. MHC Class 1 polypeptide- related sequence A (MICA) rs2844523 was in highest LD with rs2853969 downstream of HLA-B (r2 = 0.90). MICA rs2844523 was also in LD with MHC Class I Polypeptide-related Sequence B (MICB) rs2844496 (r2 = 0.27). Further examination of the LD between the top 10 highest associated polymorphisms, suggested that the most common SNPs tagged by these variants were HLA-B rs2844523 (HLA-B*44:03) and HLA-B rs2844586 (HLA-B*13:01 and HLA-B*52:01).

Table 7.11: Variants associated with AZA/MP-induced flu-like symptoms in an unsupervised analysis of 24,327 SNPs restricted to Caucasian individuals.

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR L U Control Cases Gene Upstream 6 rs2844586 6.91x10-6 0.168 10.440 3.76 29.01 0.088 0.231 HLA-B 6 rs2255221 6.99x10-6 0.170 8.181 3.271 20.46 0.090 0.231 HCP5 Upstream 6 rs1264691 7.85x10-6 0.191 9.26 3.489 24.58 0.070 0.231 HLA-L Upstream 6 rs2523741 7.85x10-6 0.191 9.26 3.489 24.58 0.071 0.205 HLA-L Upstream 6 rs2647087 9.60x10-6 0.2335 5.253 2.52 10.95 0.293 0.487 HLA-DQ2 Downstream 6 rs2596574 3.54x10-5 0.860 7.313 2.849 18.78 0.072 0.180 HLA-B MICA 6 rs2844523 3.54x10-5 0.860 7.313 2.849 18.78 0.076 0.192 (near HLA-B) Downstream 6 rs2853969 4.30x10-5 1 7.537 2.863 19.84 0.072 0.167 HLA-B Upstream 6 rs2844496 5.46x10-6 1 5.173 2.328 11.49 0.098 0.218 MICB Upstream 6 rs4947248 5.69x10-5 1 3.87 2.002 7.479 0.270 0.500 HLA-B P(SNP) reported for allelic models

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Figure 7.2 Manhattan plot showing –log P-values of variants associated with AZA/MP-induced flu- like symptoms in autosomal chromosomes. SNPs in HLA-B region highlighted. Dotted line denotes calculated threshold for genome-wide significance P = 2 x10-6

Genotype modelling suggested that the variants in HLA-B, HLA Complex P5 (HCP5) and MICA were best explained by dominant models of interaction. Whilst none of the variants in these genes reached genome-wide significance in a genotype model, there was a strong trend towards an association. Therefore these variants were combined in a logistic regression model to determine the percentage of AZA/MP-associated flu-like symptoms that could be explained by these variants.

Univariate logistic regression suggested that the minor alleles at rs2844586 upstream of HLA-B and MICB rs2844496 provided the best explanation for the occurrence of flu-like symptoms. Combining these variants together in a model, reliably distinguished between patients with and without AZA/MP-induced flu-like symptoms in comparison with a constant-only model (χ2 = 31.26, df = 2, P = < 0.0001). Overall the model explained between 15.9% (Cox and Snell R squared) and 27.9% (Nagelkerke R squared) of the cases of flu-like symptoms and in this cohort correctly predicted 85.1% of patients. The sensitivity of the model was 37% and the specificity 93.5%. The PPV and NPV were 50% and 89.4%. The strongest influence for the development of flu-like symptoms was MICB rs2844496 with an OR of 6.89 (95% CI 2.674 – 17.732, table 7.12).

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Table 7.12: Mulitivariate logistic regression modelling of variants from an unsupervised analysis associated with the development of AZA/MP-induced flu-like symptoms.

95% CI Exp(B) Variable B S.E. Wald Df Sig Exp(B) Lower Upper HLA-B 1.587 0.515 9.488 1 0.002 4.889 1.781 13.421 rs2844586 MICB 1.929 0.483 15.984 1 <0.0001 6.886 2.674 17.732 rs2844496

The analysis was repeated following restriction to the thiopurine pathway. Following adjustment for the first 4 PCs, flu-like symptoms were associated with ABCC4 rs4148549 (P = 0.0075), ADK rs946185 (P = 0.036) and GSTZ1 rs7975 (p=0.046). Confining the analysis to Caucasians only, reduced the association with ADK rs946185 (p=0.055) and improved the significance of GSTZ1 rs7975 (p=0.015). All of these variants were best explained by a dominant mode of interaction. Adding these polymorphisms into the previous logistic regression model, suggested that only ADK rs946185 might have an additional influence. The addition of this variant when combined in a model with HLA-B rs2844586 and MICB rs2844496, improved the variance in flu-like symptoms that could be explained (19.2%, Cox and Snell R squared; 33.8, Naglekerke R squared). In this model ADK rs946185 protected against flu-like symptoms (P = 0.007, OR 0.255, 95% CI 0.093 – 0.693).

Examination of the thiopurine pathway, combining all the polymorphisms as a set, suggested that variants in this pathway alone did not explain the development of flu-like symptoms (empirical P- value = 1). This is consistent with the observation that polymorphisms in the HLA-B region may play a role. Furthermore, no single gene in a gene-centric analysis of the thiopurine pathway appeared to explain flu-like symptoms. The top reported gene in this analysis was ADK with an empirical P-value of 0.111.

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7.3.4 Case-control study investigating AZA/MP induced pancreatitis

The development of pancreatitis was reported in 17 of the 412 patients with IBD prescribed AZA/MP. The average time to the development of pancreatitis was 22 days from the start of treatment (range 14 – 28 days) and the median rise in amylase was 742 pmol/ L (IQR, 241 – 3894 pmol/ L). Given the short interval between the start of treatment and the development of symptoms, data on TGNs and MeMP were not available for these patients. Three of the patients with pancreatitis were treated with MP and the rest were prescribed AZA. The average normalised thiopurine dose was 1.72 mg/ kg/ day. Data on TPMT activity was available for 11/17 patients (65%), in whom the mean and median TPMT activities were 29.09 (range 19 – 37) and 28 pmol MeMP/mg Hb/h respectively. In comparison with the cohort of 258 patients without evidence of toxicity related to AZA/MP, the median TPMT activity was significantly lower in the group with pancreatitis (P = 0.037, Mann-Whitney U-test following D’Agostino & Pearson omnibus normality test). Two of the patients with pancreatitis (11.7%) described concomitant flu-like symptoms.

In an unsupervised analysis of the 17 patients with pancreatitis in comparison with the 258 patients demonstrating tolerance to AZA/MP, which included 24,327 polymorphic variants, adjusted for the first 4 PCs, no single genetic variant demonstrated genome-wide significance (table 7.13, figure 7.3). However, several variants in the top ten associations may be of interest. Firstly, polymorphisms in two similar micro RNAs (MIR548N and MIR548F1), which are coded on different chromosomes (1 & 2) were observed. Secondly, the association between HLA-DRB1 rs17885382 and AZA/MP-induced pancreatitis may also be of relevance.

Genotype modelling suggested that MIR548N rs61999302, MIR548F1 rs3753565 and HLA-DRB1 rs17885382 were best explained by dominant models of interaction. Given the biological plausibility that variants in MIR548N/F1 and HLA-DRB1 may be involved in the development of thiopurine induced pancreatitis, these polymorphisms were combined in a logistic regression model to determine the variance in the development of pancreatitis that could be explained. In this model the OR was improved when MIR548N and MIR548F were combined, whereas HLA-DRB-1 appeared to have an independent effect (table 7.14). As a whole, this model explained between 9% (Cox and Snell R squared) and 29% (Naglekerke R squared) of the cases of pancreatitis, suggesting the involvement of additional polymorphisms.

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Table 7.13: Top ten variants from an unsupervised analysis of variants associated with AZA/MP- induced pancreatitis.

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR L U Control Cases Gene 2 rs61999302 7.26X10-6 0.906 17.99 4.556 71.04 0.058 0.269 MIR548N 6 rs204894 5.24x10-6 1 15.41 4.095 58.01 0.054 0.308 ATF6B Upstream 1 rs10911902 0.000139 1 7.042 2.58 19.22 0.163 0.500 MIR548F1 1 rs3753565 0.000164 1 5.919 2.348 14.92 0.140 0.462 MIR548F1 2 rs2302620 0.000225 1 10.03 2.947 34.15 0.111 0.346 IL1RL2 6 rs1269854 0.000315 1 11.02 2.987 40.67 0.051 0.231 TNXB 3 rs62620047 0.000321 1 5.561 2.184 14.16 0.121 0.385 PTPRG 11 rs3829241 0.000331 1 6.77 2.383 19.23 0.331 0.692 TPCN2 6 rs17885382 0.000352 1 6.44 2.319 17.89 0.121 0.385 HLA-DRB1 6 rs6899309 0.000476 1 9.631 2.703 34.31 0.066 0.231 HLA-DMA P(SNP) reported for allelic models

Figure 7.3 Manhattan plot showing –log P-values of variants associated with AZA/MP-induced pancreatitis in autosomal chromosomes. Dotted line, threshold for genome-wide significance, p = 2x10-6

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Table 7.14: Variants associated with the development of AZA/MP-induced pancreatitis included in a logistic regression model.

95% CI Exp(B) Variable B S.E. Wald Df Sig Exp(B) Lower Upper MIR548N rs61999302 + MIR548F1 2.309 0.692 11.125 1 0.001 10.065 2.591 39.093 rs3753565 DOM HLA-DRB-1 rs17885382 1.974 0.645 9.375 1 0.002 7.203 2.035 25.492 DOM DOM, dominant model

Restriction of the analysis to variants in the thiopurine pathway, suggested additional variants associated with thiopurine-induced pancreatitis. Following adjustment for the first 4 principle components, MGMT r12917 (p=0.0034, OR 6.48, 95% CI 1.853 – 22.67) and NT5E r2229524 (0.0081, OR 6.3, 95% CI 1.612 – 24.63) were associated with the development of pancreatitis. The addition of these variants into the previous logistic regression model improved the variance in pancreatitis that was explained (between 14%, Cox and Snell R square to 42.4%, Naglekerke R square). Both variants appeared to have an independent effect. The previous analyses suggested that both MGMT and NT5E may modulate thiopurine metabolite profiles, hence intracellular concentrations of both methylated metabolites and thioguanine nucleotides could play a role in the development of pancreatitis. Unfortunately, none of the patients who developed pancreatitis had metabolite levels measured at the time of diagnosis and therefore it was not possible to assess this further.

Variants in genes previously associated with the development of autoimmune pancreatitis (SPINK1, PRSS1, CFTR and CTRC) did not demonstrate an association with the development of thiopurine- induced pancreatitis.

The thiopurine pathway, when examined in a pathway-centric analysis was associated with AZA/MP- induced pancreatitis. The empirical P-value for the pathway was 0.0139 and the top reported SNP following permutation was NT5C3 rs144452782. This is a rare missense polymorphism (p.K75Q) in the coding region of NT5C3 with a MAF of 0.003. However, gene-centric analysis did not reveal a single gene demonstrating an overall association with AZA/MP-mediated pancreatitis at an α-level < 0.05. In the gene-centric analysis, NT5C3 was reported as the highest associated gene (P = 0.0501).

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7.3.5 Case-control study of AZA/MP-induced hepatotoxicity

Abnormal liver function tests related to AZA/MP therapy were reported in 34 of 412 (8.3%) patients with IBD. Of these 34 cases, 15 (44%) were associated with thiopurine hypermethylation. The average time to the development of hepatotoxicity was 13.5 weeks (range 2 – 52). The majority of the patients (32/34) demonstrated a transaminitis with an average ALT level of 162.5 U/ L (range 56 – 341), whereas 2 patients demonstrated cholestasis with an average ALP level of 208.5 U/ L (156 and 261 U/ L respectively). In 23 patients, hepatotoxicity was successfully circumvented by switching to low dose AZA/MP with allopurinol. Two patients were unable to tolerate combination treatment and the remaining 9 patients were switched to alternative therapy with either anti-TNF-α treatment (n = 5), methotrexate (n = 2) or offered surgical intervention (n = 2).

Hepatotoxicity appeared more likely to occur at an older age (n = 292, Pearson correlation = 0.13, P = 0.026). There were more patients prescribed MP in the hepatotoxic cohort, however this is likely to represent previous intolerance to AZA in this group. Indeed, of the 34 patients with hepatotoxicity, 12 also described nausea and 3 reported flu-like symptoms. This suggests possible common variants mediating thiopurine induced ADRs. As expected, average MeMP levels were higher in patients who developed hepatotoxicity (P = 0.018).

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Table 7.15: Demographic comparison of patients with and without thiopurine-induced hepatotoxicity.

Patients without Patients with Significance Variable AZA/MP induced hepatotoxicity P value, OR hepatotoxicity AZA/MP (95% CI) Number of patients with IBD, n (%) 258/412 (62.6%) 34/412 (8.3%) P = 0.148* Males, n (%) 134 (51.9%) 13 (38.2%) Female, n (%) 124 (48.1%) 21 (61.8%) OR 1.746 (0.838 – 3.636) Age (y) at study inclusion, mean ± SEM 38.3 ± 0.834 43.8 ± 2.396 P = 0.0093† (range) (17-79) (26-85) P = 0.0004* Prescribed AZA, n (%) 247 (95.7%) 26 (76.5%) OR 6.909 Prescribed MP, n (%) 11 (4.3%) 8 (23.5%) (2.550 – 18.72) CD, n (%) 180 (69.8%) 21 (61.8%) UC, n (%) 67 (26.0%) 11 (32.3%) P = 0.633¥ IBD-U, n (%) 11 (4.2%) 2 (5.9%) Smoking data missing, n (%) 20 (7.9%) 5 (14.7%) Non-smoker, n (%) 118 (45.7%) 19 (55.9%) P = 0.244¥ Ex-smoker, n (%) 87 (33.7%) 8 (23.5%) Current smoker, n (%) 33 (12.8%) 2 (5.9%) TPMT (pmol/ h/ mgHg) activity, n (%) 181/258 (70.2%) 28/34 (82.4%) Median TPMT activity 34 34 P = 0.433‡

TPMT heterozygote activity, n (%) 24/181 (13.3%) 0/34 (0%) Normalised dose of thiopurine (mg/ kg/ 1.89 ± 0.03 1.97 ± 0.09 P = 0.750+ day), mean ± SEM: Thiopurine metabolite monitoring, n (%) 235/258 (91.1%) 29/34 (85.3%)

Av TGN (pmol/8x108 RBC) median (IQR) 274 (178 – 364) 237 (137 – 374) P = 0.438+ Av MeMP (pmol/8x108 RBC) 737 (255 – 2390) 4100 (28 – 7687) P = 0.0180+ Av MeMP : TGN ratio 2.57 (0.80 – 8.29) 11.27 (0.09 – 35.17) P = 0.0150+ *Two-sided Fisher’s exact test; † Two-tailed unpaired t-test; ‡Independent samples median test; +Mann-Whiney U-test; ¥ 3 by 2 Chi-squared test.

In an unsupervised analysis restricted to Caucasian individuals and adjusted for the first 2 PCs, no single polymorphism demonstrated genome-wide significance (table 7.16). However, one of the synonymous variants in the top ten associations for the development of hepatotoxicity, Interleukin 15 (IL15) rs10519613 may be of potential importance. This variant was not in LD with the two polymorphisms reported in the centromere protein E (CENPE) gene. However, it was in moderate LD with multiple other SNPs in IL15 gene, of which the highest LD was reported for rs17007695 (r2 = 0.45). Both IL15 rs10519613 and rs17007695 were best explained by a dominant mode of interaction (P = 0.00031 and P = 0.0019 respectively).

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Table 7.16: Unsupervised analysis of variants associated with AZA/MP-induced hepatotoxicity in Caucasian individuals adjusted for the first 2 principal components.

95% CI MAF MAF Chr SNP ID P(SNP) Bonf OR L U Control Cases Gene 4 rs2243682 7.48x10-5 0.96 8.715 2.985 25.44 0.123 0.438 CENPE 4 rs2615542 7.48x10-5 0.96 8.715 2.985 25.44 0.123 0.438 CENPE 4 rs10519613 9.27x10-5 1 8.769 2.952 26.05 0.075 0.344 IL15 19 rs4801798 0.0001459 1 8.602 2.833 26.12 0.062 0.281 LOC100507003 8 rs9656982 0.0003382 1 12.6 3.153 50.39 0.026 0.156 SLC7A13 17 rs144568697 0.0005648 1 12.33 2.956 51.4 0.026 0.156 TRIM16 7 rs4580937 0.0008119 1 6.976 2.238 21.75 0.052 0.25 MICALL2 7 rs61287564 0.0008119 1 6.976 2.238 21.75 0.052 0.25 MICALL2 1 rs34868416 0.0008442 1 4.827 1.915 12.16 0.091 0.313 FCRLB 5 rs4895362 0.0009730 1 8.145 2.342 28.33 0.039 0.186 DMXL1 P(SNP) reported for allelic models

The MAF of rs10519613 and rs17007695 in Caucasian populations is approximately 15%. This is similar in magnitude to the number of patients with thiopurine hypermethylation demonstrating hepatotoxicity. To test the hypothesis that these variants may explain the development of hepatotoxicity in patients with thiopurine hypermethylation, these SNPs were sub-analysed in a cohort of 64 patients with hypermethylation without hepatotoxicity as compared to 15 patients with hypermethylation and hepatotoxicity. Both IL-15 rs10519613 (P = 0.005, OR 26.93, 95% CI 2.701 – 268.6) and rs17007695 (P = 0.0071, OR 31.95, 95% CI 2.568 – 397.6) were associated with the development of hepatotoxicity in patients with thiopurine hypermethylation.

Restricting the analysis to polymorphisms in the thiopurine pathway suggested additional variants associated with the development of hepatotoxicity. In this regard MTHFR rs17367504 and MTHFR rs17375901 were associated with hepatotoxicity (P = 0.00346, OR 2.477, 95% CI 1.349 – 4.549, and P = 0.0383, OR 2.547, 95% CI 1.052 – 6.17, respectively). These associations were strengthened following restriction to Caucasian ethnicity (MTHFR rs17367504, P = 0.00238; rs17375901, P = 0.00571). Hepatotoxicity was also associated with ADK rs946185 (P = 0.0307, OR 1.842, 95% CI 1.059 – 3.205), whereas protection from hepatotoxicity was suggested by the presence of AOX1 rs55754655 (P = 0.0381, OR 0.312, 95% CI 0.104 – 0.938). The polymorphisms in MTHFR, ADK and AOX1 were best explained by dominant models of interaction.

In a pathway centric analysis, the variants in the thiopurine pathway did not provide a complete explanation for the development of hepatotoxicity (empirical P-value = 1). In a gene-centric analysis,

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MTHFR was reported as the gene most highly associated with hepatotoxicity in the thiopurine pathway (empirical P-value = 0.0051, top SNP MTHFR rs17367504), whereas ADK and AOX-1 showed a trend towards an association (P = 0.0685 and P = 0.0892 respectively).

The variants in IL-15, MTHFR, ADK and AOX1 were combined in a logistic regression model, assuming dominant interactions, to determine the variance in hepatotoxicity induced by AZA/MP that could be explained. Age was added as a covariate to this model. Univariate analysis using Pearson’s correlation confirmed the previous associations with hepatotoxicity (table 7.17). The significance level for MTHFR rs17375901 was improved where this SNP coincided with MTHFR rs17367504 (P- value for interaction P = 0.007). Therefore in the model, the effect of MTHFR rs17375901 and MTHFR rs17367504 were combined. When entered as a block the model reliably distinguished between patients with and without hepatotoxicity in comparison with a constant only model (χ2 = 27.87, df = 5, p = < 0.0001). Overall these variants explained between 9.6% (Cox & Snell R squared) and 18.8% (Nagelkerke R squared) of the observed hepatotoxicity. In this model the most significant variants associated with hepatotoxicity were the variants in MTHFR (P = 0.007, OR 3.95, 95% CI 1.459 – 10.688; table 7.18).

Table 7.17: Univariate analysis of variables influencing AZA/MP-induced hepatotoxicity.

MTHFR MTHFR AOX1 IL-15 ADK Age rs17375901 rs17367504 rs55754655 rs10519613 rs946185 Rho 0.139 0.152 0.168 -0.124 0.177 0.135 P-value 0.021 0.012 0.005 0.039 0.003 0.021

Table 7.18: Variants associated with AZA/MP-induced hepatotoxicity in a logistic regression model.

95% CI Exp(B) Variable B S.E. Wald Df Sig Exp(B) Lower Upper Age 0.024 0.014 2.960 1 0.085 1.024 0.997 1.052 MTHFR rs17367504 + 1.374 0.508 7.313 1 0.007 3.950 1.459 10.688 MTHFR 17375901 AOX1 -1.230 0.579 4.517 1 0.034 0.292 0.094 0.909 rs55754655 IL15 1.257 0.481 6.838 1 0.009 3.515 1.370 9.017 rs10519613 ADK rs946185 0.960 0.442 4.725 1 0.030 2.612 1.099 6.207

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7.4 Discussion

The current study provides novel insights into the mechanisms responsible for the development of thiopurine-induced ADRs in patients with IBD. No single polymorphism appeared to account for the development of all drug toxicity, however modelling of genetic variants within the thiopurine pathway, in combination with relevant covariates, appears to explain some of the heritability. In this regard, the development of overall toxicity to AZA/MP was best explained by a model including polymorphic variation in ADK (rs946185) which mediates conversion between methylated thiopurine nucleosides and methylated nucleotides (figure 1.2), a nucleoside transporter (SLC28A1 rs2242046), nucleotide transporters (ABCB5 rs2301641 and ABCC4 rs4148549) and enzymes with oxidizing (AOX1 rs55754655) and dephosphorylating activities (NT5E rs1321744 and rs2229524). Sub-analyses suggested additional variants associated with specific toxicities, which are discussed below.

The study included a large number of patients with IBD treated with AZA/MP at a single centre. The development of at least one ADR was reported in just over 1/3 of patients, which led to treatment withdrawal in 1 in 7 patients. This is comparable to the rates of ADRs and consequent treatment cessation reported in the published literature (83, 451). Consistent with the reports by Chouchana et al and Bar et al, gastrointestinal toxicity was the most common ADR encountered on AZA/MP therapy. This could not be circumvented by dose-splitting, dose-reduction or following a switch from AZA to MP in 1/3 of patients (83, 452). It was previously suggested that nausea, vomiting and flu-like illness are associated with the methylnitroimidazole moiety of AZA, hence switching to MP can be successful in up to 77% of AZA intolerant patients (217, 467). The current data confirm that this strategy is not successful in all cases, suggesting involvement of additional mechanisms. However, this may account for the trend towards ADRs with older age, since levels of glutathione, which aids the non- enzymatic cleavage of the methylnitroimidazole ring of AZA to yield MP, decrease with advancing age (469).

Of interest, there was no difference in median RBC TPMT activities between patients developing toxicity as compared to those that demonstrated thiopurine tolerance. Based upon the data presented by Ansari et al in a smaller cohort of patients with IBD (n = 106), one would have expected to observe a higher rate of ADRs in patients with intermediate TPMT activity (179). The lack of correlation between ADRs and TPMT activity in the current study most likely relates to pre- treatment measurement of RBC TPMT activity and subsequent dose rationalisation, although this was not specifically investigated. However, this would be consistent with the findings of Domenech et al who reported that ADRs may be circumvented with thiopurine dose reduction (466).

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7.4.1 A model of overall thiopurine-induced toxicity

Whilst no single variant explained overall toxicity in this cohort, several genes with polymorphisms in the top ten associations are of potential interest. Firstly, UBE2L6, which plays an important role in the cellular degradation of abnormal or short-lived proteins. Although UBE2L6 has not previously been linked to thiopurine metabolism, TPMT is known to undergo ubiquitin mediated proteasome degradation, yet the specific ubiquitin responsible for this has not been identified. Furthermore, 2 other ubiquitins within the same family, UBE2A and UBE2E3, were previously associated with thiopurine hypermethylation (402, 423). Secondly, transmembrane protease serine 15 (TMPRSS15/ PRSS7), which encodes an enzyme responsible for activating pancreatic proteolytic enzymes, interacts with the serine peptidase inhibitor, kazal type 1 (SPINK1), which has been implicated in the development of idiopathic pancreatitis (470). Meanwhile, autoimmune pancreatitis has been linked to mutations in other members of the transmembrane protease family, namely PRSS1 (471). However, in the sub-analysis of patients with thiopurine-induced pancreatitis specific investigation for these genes did not reveal an obvious association with the development of pancreatitis; although the sub- analysis was likely to be underpowered and therefore further study in larger independent cohorts is warranted. Finally, ADK rs946185 was shown to be associated with an increased risk of toxicity. ADK is a candidate gene in the thiopurine pathway, given its involvement in the inter-conversion of MeMP riboside to MeTIMP (472). Modulation of ADK activity may therefore affect MeTIMP levels, which will directly influence inhibition of DNPS and thereby adenine and guanine nucleotide pools, leading to cellular stress (99, 473). ADK is also likely to be responsible for the conversion of TG riboside back to TGMP prior to conversion into TGTP.

ADK rs946185 codes an intronic synonymous polymorphism, which tags 19 other polymorphisms in the ADK gene with an r2 > 0.25 (data deposited by Dr Panos Deloukas, Wellcome Trust Sanger Institute and published on-line from the British 1958 Birth Cohort DNA Collection, 27/07/2007) (474). Furthermore, in-silico regulatory SNP detection using the ‘is-rSNP’ algorithm (and the TRANScription FACtor database) reported that this variant may affect the binding of several transcription factors, of which the most significant interaction was reported for the homeobox protein Nkx3.1 (adjusted P- value = 0.000532) (432). These data suggest that the ADK rs945185 polymorphism may be functionally relevant or it may be tagging additional SNPs that are. In-vitro examination of the effect of this polymorphism on ADK activity with respect to its endogenous substrate, adenosine, would clarify this further. In addition, comparison of thiopurine metabolite profiles using mass spectroscopy as described by Hoffman et al, studying patients with and without this SNP, would be of interest to determine its influence on thiopurine riboside and nucleotide concentrations (475).

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A model including SNPs in ADK (rs945185), SLC28A1 (rs2242046), ABCB5 (rs2301641), ABCC4 rs4148549), AOX1 (rs55754655) and NT5E (rs1321744 and rs2229524), with gender and age as covariates, explained approximately 1 in 7 cases of toxicity. Within this model the strongest predictor of ADRs was the presence of the minor allele at ADK rs945185. There was also an association with the minor allele at SLC28A1 rs2242046 and the strength of this association was improved where it coincided with ADK rs945185. SLC28A1 rs2242046 codes an amino acid change from aspartate to asparagine at codon 521 and in-vitro, this change is associated with increased uptake of a pyrimidine nucleoside, thymidine into cells (314). Furthermore, this variant is associated with increased haematological toxicity in patients with non-small cell lung cancer treated with gemcitabine (476). Whilst SLC28A1 shows a predilection for pyrimidine nucleosides, studies in lymphocyte cell lines suggest that it is also likely to transport nucleosides of MP (477). Therefore, enhanced uptake of MP nucleosides and subsequent phosphorylation by ADK may increase the intracellular concentrations of MeTIMP and TGMP to explain some cases of toxicity. Similarly, SNPs in ABCB5, ABCC4 and NT5E, which were shown to influence thiopurine metabolite profiles in Chapters 5 and 6, may mediate toxicity through modulation of intracellular thiopurine nucleoside and nucleotide concentrations. This now requires confirmation in cell models.

The association between AOX1 rs55754655 and protection from ADRs is consistent with the observations of Smith et al and subsequently Kurzawski et al, who demonstrated that patients heterozygous for this mutation were more resistant to AZA and required higher drug doses (272, 273). This likely occurs because of enhanced degradation of AZA, MP and TG towards TUA (see figure 1.2 for reference).

7.4.2 A model of thiopurine-induced nausea

Whilst unsupervised testing failed to identify a single variant passing Bonferroni correction that explained the development of nausea, two genes with variants in the top ten associations may be of relevance. Firstly, MTTP (rs3816873), the protein product of which plays a central role in lipoprotein assembly. MTTP is highly expressed in the adult liver and intestines, which are major sites of thiopurine metabolism. In humans deficiency of this protein is associated with gastrointestinal disturbances such as diarrhoea, nausea, vomiting, heartburn and abdominal pain (478, 479). Heterozygosity for the minor allele at rs3816873 has been associated with an increased risk of developing non-alcoholic fatty liver disease, suggesting that this variant is functionally relevant (480). In addition the MAF for this missense mutation, which codes a change in amino acid at codon 128, is 0.22 and therefore of similar magnitude to the number of patients experiencing gastrointestinal intolerance on AZA/MP. However, confirmation of this association is required in larger studies.

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Secondly, PLEKHG2 (rs73033371) may be of relevance, since this codes a Rho family-specific guanine-nucleotide exchange factor for RAC1, one of the key mediators of thiopurine induced immunosuppression(130, 481). Therefore polymorphic variation in this gene may indirectly regulate cellular apoptosis, and thereby thiopurine mediated toxicity. This requires further study in cell models of thiopurine metabolism and killing.

In thiopurine pathway analysis, SLC28A1 rs2242046 and GDA rs11143230 were also associated with the development of nausea. As described above SLC28A1 rs2242046 may enhance the cellular uptake of thiopurine nucleosides. Meanwhile GDA rs11143230 is understood to be a functionally relevant polymorphism with respect GDA activity; however the direction in which this variant affects enzyme activity is yet to be characterised (482). If this down-regulates GDA activity, nausea may partly relate to enhanced thiopurine cellular uptake and subsequent trapping of intermediates due to reduced degradation by GDA.

7.4.3 A model of thiopurine-induced flu-like symptoms

The current work provides novel insights into the development of flu-like symptoms on AZA/MP therapy. Such symptoms are similar to an allergic-type reaction suggesting the involvement of genes relevant to the immune system. In this regard, multiple SNPs in the HLA region of chromosome 6 were associated with flu-like symptoms, although no single variant passed correction for multiplicity. The highest association was shown for HLA-B rs2844586, which tags two additional SNPs rs2844573 and rs2253908 that in combination code the HLA allele HLA-B*13:01. This variant has previously been associated with the development of both dapsone and trichloroethylene-induced hypersensitivity reactions (483, 484). Previous work by de Bakker et al has shown that the HLA-B*13:01 allele is additionally associated with HLA-B*52:01 and HLA-C*16:01 alleles (485). It is probable that the rs2844586 SNP denotes the presence of the HLA-A*02:01-B*52:01-C*16:01-DRB1*13:01- DQB1*06:03 haplotype, which is present in 4-9% of Caucasians and therefore consistent with the frequency of flu-like symptoms reported here. The presence of this HLA haplotype leads to a change in amino acid residues (I94I95R97) that alters the motif of a key peptide binding groove (structural pocket F) (483). Of interest this amino acid sequence is also common to HLA-B*58:01 and HLA- B*15:02, which have been associated with hypersensitivity reactions to allopurinol and carbamazepine respectively (486, 487). This suggests that there may be a common molecular basis for the development of hypersensitivity reactions related to these HLA alleles.

Polymorphic variation in MICA (rs2844523) may also be relevant to the development of thiopurine induced hypersensitivity reactions. MICA produces a protein product expressed on the cell surface,

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Taken together, the current data suggest that HLA-B alleles, either alone or together with other genetic polymorphisms in the HLA region, might play a pivotal role in determining individual susceptibility to hypersensitivity reactions to AZA/MP, characterised by the development of flu-like symptoms. Therefore, the mechanism of HLA-B involved in thiopurine-induced hypersensitivity requires further investigation along these lines.

7.4.4 A model of thiopurine-induced pancreatitis

With respect to the development of pancreatitis, in an unsupervised analysis, polymorphisms in two similar micro RNAs (MIR548N and MIR548F1), which are coded for on different chromosomes (1 & 2 respectively) were observed in the top ten associations. Micro RNA’s are small non-coding RNA molecules that modulate transcriptional and post-transcriptional regulation of gene expression through a number of different mechanisms (492, 493). Recent work by Martinez et al. has suggested that MIR548F1 may be involved in the regulation of several human genes including; aldehyde oxidase 1 family member A2 (ALDH1A2), cathepsin S (CTSS), glutathione reductase (GSR), interferon regulatory factor 4 (IRF4), krupple-like factor 4 (KLF-4), Ral guanine nucleotide dissociation stimulator-like 1 (RGL1) and thioredoxin reductase 1 (TXNRD1) (494). Of these CTSS is of particular importance since it regulates trypsinogen activation within acinar cells, a key initial step in the development of pancreatitis (495). Therefore it follows that impaired regulation of CTSS via MIR548F1 may increase the risk of pancreatitis.

The finding of a possible association between HLA-DRB-1 rs17885382 and AZA/MP-induced pancreatitis may also be of relevance. Indeed, previous work by Dubois et al. has suggested that thiopurine-induced pancreatitis is related to variants in the HLA region and in particular the HLA- DQA-2 gene (496). HLA-DRB-1 rs17885382 was in LD (r2 > 0.25) with 11 other SNPs in the HLA-region, including variants downstream of HLA-DQA-2 (rs2647087, r2 = 0.33). Therefore it is possible that

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HLA-DRB-1 is tagging causative variants in the HLA region through LD. Fine mapping of this region to look for variants associated with AZA/MP-induced pancreatitis is therefore warranted.

A thiopurine pathway analysis suggested that a variant in NT5C3 (rs144452782) was also associated with pancreatitis. However, this is a rare polymorphism (MAF 0.003) and given the relatively low number of patients with pancreatitis included in the analysis, this result needs to be interpreted with caution. Finally, there was no association between pancreatitis and variants in the ITPA gene, consistent with the findings from meta-analysis (303).

7.4.5 A model of thiopurine-induced hepatotoxicity

The majority of thiopurine induced hepatotoxicity in the current study was characterised by the presence of transaminitis, indicative of hepatocyte injury. The observation that this was more likely to occur at an older age may relate to the reduction in glutathionine levels with advancing age, which can promote oxidative stress. Consistent with the data presented in chapters 3 and 4, MeMP levels were higher in patients with hepatotoxicity. However, to date it remains unclear as to why the majority of patients with high MeMP concentrations do not develop drug-induced liver injury. This suggests the involvement of a secondary mechanism. In this regard the finding that IL15 rs10519613 was within the top ten associations with hepatotoxicity may be of interest. Indeed, IL15 rs10519613 and a second SNP rs17007695, which was in LD with this variant, have previously been associated with the development of adult ALL and treatment response in childhood ALL (497, 498). Moreover, deficiency of IL15 has been shown to enhance the susceptibility to acetaminophen- induced liver injury through increased production of pro-inflammatory cytokines and chemokines (499). On sub-analysis, the presence of IL15 rs10519613 and rs17007695 polymorphisms was shown to separate patients with high MeMP concentrations who developed hepatotoxicity from those in whom the liver function tests remained within the normal range. Variation in the activity of IL15 may therefore provide the secondary mechanism. Furthermore, the MAF of these variants in Caucasian populations is approximately 20% and therefore similar in magnitude to the number of patients with high MeMP concentrations that develop hepatotoxicity.

Thiopurine pathway analysis suggested additional variants associated with the development of hepatotoxicity. In this regard MTHFR rs17367504 and rs17375901, both of which are intronic SNPs, were associated with the development of hepatotoxicity. In a large genome wide association study, MTHFR rs17367504 was associated with blood pressure control and was found to be in LD (r2 = 0.36) with MTHFR A1298C and C677T, both which are known to affect enzyme function and have a secondary influence on TPMT activity through modulation of SAM levels (255, 500, 501). ADK rs946185

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A limitation of the sub-analyses investigating variants associated with flu-like symptoms, pancreatitis and hepatotoxicity is the small number of affected individuals. This will have increased the false discovery rate, indicating the need for additional studies.

7.4.6 Conclusion

In summary, the development of thiopurine induced ADRs appears to be a complex trait, involving polymorphic variation within genes of the thiopurine pathway in addition to genes in external pathways. The novel associations reported here now require confirmation in larger cohorts. Furthermore, where genetic associations are confirmed, the molecular consequences of these variants on thiopurine metabolism, and therein the development of toxicity, should be characterised in-vitro.

Summary of key findings:

 Polymorphic variation in ADK, an enzyme which is involved in the conversion of thiopurine ribosides to nucleotides, predicts overall thiopurine-induced toxicity.  A model including polymorphic variation in ADK, SLC28A1, ABCB5, ABCC4, AOX1, NT5E, gender and age, explained 1 in 7 cases of thiopurine-induced toxicity.  HLA-B*1301 is implicated in the aetiology of thiopurine-induced flu-like symptoms, consistent with the theory that these symptoms are due to an allergic drug reaction.  The presence of the minor allele at IL15 rs10519613 appears to provide an explanation as to why only a subset of patients with high MeMP concentrations appear to develop hepatotoxicity.

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Chapter Eight: The mechanism of allopurinol induced thiopurine-S- methyltransferase inhibition.

8.1 Introduction

AZA and MP are pro-drugs with a complex metabolism. After ingestion, AZA is broken down following conjugation with glutathione to yield MP. MP is a synthetic analogue of the purine base hypoxanthine, which is converted in nucleated cells via enzymes of the purine salvage pathway to form TGNs. These end-metabolites are believed to mediate the main therapeutic effects of thiopurines, and at high concentrations (>450 pmol/ 8x108RBCs) have been associated with myelotoxicity (89).

MP may also undergo oxidation by XDH and AOX via the intermediates 8-OH-MP and TX (2-hydroxy- mercaptopurine) to form TUA. Alternatively, MP can be deactivated by TPMT to produce MeMP. TPMT is additionally responsible for the S-methylation of thioinosine nucleotides including the monophosphate nucleotide TIMP, forming MeTIMP, which is a potent inhibitor of DNPS (140, 141). TPMT activity demonstrates a tri-modal distribution according to genetic polymorphism and is inversely correlated with TGN concentrations and thereby the risk of myelotoxicity.

Metabolite monitoring of patients with IBD established on thiopurine therapy provides a rational basis for dose adjustment in order to maximize clinical response, limit toxicity and prevent treatment failure. In this regard TGN concentrations > 235-260 pmol/ 8x108RBCs have been associated with disease remission, whereas MeMP levels > 5300-5700 pmol/ 8x108RBCs have been correlated with hepatotoxicity, which is typically characterized by a transaminitis (64, 157, 398). As confirmed in Chapter 3, approximately 15% of patients with IBD demonstrate a skewed drug metabolism, preferentially metabolizing MP to MeMP at the expense of TGNs, a situation referred to as thiopurine hypermethylation. This phenotype is associated with non-response to treatment, hepatotoxicity and other side effects (154, 162, 181). Importantly, thiopurine hypermethylation is not predicted by high TPMT activity, suggesting an influence of other factors in the thiopurine and methylation pathways.

Allopurinol, an inhibitor of XDH, was originally designed by Gertrude Elion for use alongside MP to potentiate its therapeutic index in patients with leukaemia (502). Whilst the original studies of combination therapy in humans demonstrated an increase in anti-tumour activity, it was associated with a proportionate rise in toxicity (47). This strategy was therefore abandoned and allopurinol monotherapy subsequently found its niche in the management of gout and tumour lysis syndrome. Interest in co-prescription was renewed in the 1990’s with the discovery that low dose AZA and

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In patients with IBD, combination treatment with low dose AZA/MP (25-33% standard dose) and allopurinol provides an opportunity to circumvent thiopurine hypermethylation and thereby reduce hepatotoxicity and recapture treatment response (181, 190, 415). It has additionally been used to ameliorate other ADRs unrelated to preferential methylation (181, 504).

The mechanism by which allopurinol leads to a reduction in methylated thiopurine metabolites remains unclear. Inhibition of TPMT by allopurinol would explain these results; however both in- vitro and in-vivo studies have shown a lack of inhibition of erythrocyte and human liver cytosolic TPMT activity following the addition of both allopurinol and its active metabolite, oxypurinol (alloxanthine) (415). Therefore the aim of this study was to resolve the biochemical mechanism underlying the interaction between allopurinol and AZA/MP.

A previous study in patients with non-Hodgkin’s lymphoma demonstrated a rise in plasma TX levels and a reduction in RBC MeTIMP following treatment with intravenous MP and allopurinol (71). We therefore hypothesized that the thiopurine intermediate TX acts as a direct TPMT inhibitor, and secondly that levels of TX will be elevated in IBD patients receiving combination therapy with oral low dose AZA and allopurinol.

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8.2 Methods

The methods presented here are described in brief and refer to Section 2.6 of this thesis.

8.2.1 Metabolism of MP, TX and oxypurinol in intact red blood cells (RBCs)

EDTA whole blood was obtained from healthy thiopurine-naïve individuals demonstrating wild-type TPMT activity. 100 µL aliquots of packed RBCs were suspended in EBBS with SAM (1mg/ ml) and pre-incubated with 250 µM MP at 37°C. After 2 h, 250 µM TX or an equal volume of EBBS was added and the incubation continued for up to 6 h. In the reciprocal experiment, packed RBCs were pre- incubated with 250 µM TX or an equal volume of EBSS for 2 h, prior to the addition of 250 µM MP and the incubation continued for up to 6 h. The concentration of MeMP (pmol/ L) was measured at 0 h, 2 h, 4 h and 6 h by HPLC.

To determine if oxypurinol influenced the formation of MeMP in RBCs incubated with MP, 100µl aliquots of packed RBCs were incubated for 2 h at 37°C in 150 µL EBSS with 50 µL SAM (1mg/ ml), with either 250 µM MP alone or 250 µM MP with 250 µM oxypurinol, and the concentration of MeMP (pmol/ L) measured by HPLC.

8.2.2 Measurement of TPMT kinetic and inhibition constants in red cell lysates using tandem mass spectroscopy.

The direct effect of TX and oxypurinol on TPMT activity was determined by varying the concentration of TX or oxypurinol (0 µM, 0.01 µM, 0.02 µM, 0.05 µM, 1 µM, 2 µM, 5 µM) added to a standard red cell lysate assay used to measure TPMT activity by tandem mass spectroscopy.

8.2.3 Measurement of urinary TX and oxypurinol levels in controls versus IBD patients receiving AZA alone or in combination with allopurinol.

To determine if TX and oxypurinol levels were elevated in patients with IBD receiving low dose AZA/MP with allopurinol (n = 11) in comparison with those receiving AZA/MP monotherapy (n = 10), 20 mls of urine were collected from each subject 4 h after oral dosing. The concentration of both TX and oxypurinol was measured by UPLC and expressed in µmol / mmol creatinine. A group of 9 healthy thiopurine-naïve volunteers provided control urine samples. All participants were adults and provided written informed consent (MREC, 00/1/33 and LREC, 06/Q0707/84).

Patients with IBD were included if they demonstrated wildtype TPMT activity, they had received a steady state dose of AZA for greater than 3 months, the TGN profile confirmed adherence to therapy (TGN > 240 pmol/ 8x108 RBC) and they were not receiving 5-ASA preparations or anti-TNF-α antibody therapy that could have affected the thiopurine metabolite profile.

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In 1 further patient receiving low dose AZA and allopurinol, urine was collected sequentially at 30 min, 1 h, 4 h, 6 h, 8 h, 10 h, 12 h and 20 h post oral dosing.

For IBD patients receiving thiopurine therapy, TGN and MeMP measurements were taken at the same time as the urine collection and measured as the hydrolysed base in 0.5 mL whole blood using the PCA hydrolysis method. RBC TPMT activity was also measured using mass spectrometry.

8.2.4 Statistics

For each data set, normality was assessed using a D’Agostino & Pearson omnibus normality test. Accordingly, t-tests were used to compare the concentration of MeMP in protein free RBC extracts (Graph Pad Prism, 5.0). Mann-Whitney U-tests were used to compare RBC TPMT activity and MeMP levels in patients receiving monotherapy with AZA or combination treatment with AZA and allopurinol, whereas t-tests were used to compare TGN levels. Similarly, Mann-Whitney U-tests were used to compare differences in urinary TX and oxypurinol levels between patients and a Spearman rank correlation was used to determine the relationship between TX and oxypurinol levels.

For the in-vivo study, the a-priori power calculation was based on the data previously presented by Keuzenkamp-Jansen et al. (71). Assuming an anticipated effect size (‘d’) of 1.5, recruitment of 11 patients to each group was calculated to achieve a power of 92%.

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8.3 Results

8.3.1 The effect of TX and oxypurinol on the production of MeMP in intact RBCs exposed to MP.

For intact RBCs incubated with 250 µM MP, the concentration of MeMP in both the protein free red cell extract and cell free supernatant media increased with time (figure 8.1). The concentration of MeMP in the cell free supernatant media was approximately 5-fold lower than that of the protein free red cell extracts. In comparison, MeMP was not detected in either the protein free red cell extract or cell free supernatant media following incubation with 250 µM TX.

Intact RBCs pre-incubated with 250 µM MP for 2 h prior to the addition of 250 µM TX or an equivalent volume of EBBS, showed a significant reduction in the concentration of MeMP detected at 4 h and 6 h in cells exposed to TX (4 h, 1.68 (±0.11SEM) pmol/ L vs 2.81 (±0.19SEM) pmol/ L, P = 0.0078 (t-test); 6 h, 2.00 (±0.05 SEM) pmol/L vs 4.61 (±0.25 SEM), P = 0.0005 (t-test)) (figure 8.2). In the reciprocal experiment in which RBCs were pre-incubated with TX or an equivalent volume of EBBS for 2 h prior to the addition of 250 µM MP, there was a similar significant reduction in the concentration of MeMP detected at 4 h (0.28 (±0.03 SEM) vs 1.50 (±0.11 SEM), P = 0.0004 (t-test) and 6 h (0.33 (±0.02SEM) vs 2.81 (±0.19SEM), P = 0.0002 (t-test)) (figure 8.3).

Co-incubation of RBCs with MP 250 µM and oxypurinol 250µM also led to a lower but still significant reduction in the concentration of MeMP observed after 2 h, as compared to incubations with MP 250 µM alone (1.64 pmol/ L (±0.12 SEM) vs 1.00 pmol/ L (±0.07 SEM), P = 0.003 (t-test) (figure 8.4).

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Figure 8.1 Concentration of MeMP (pmol/ L) in protein free RBC extracts and cell free supernatant media following incubation with 250 µM MP. In 100 µL of intact RBCs incubated 250 µM MP, the concentration of MeMP in both the protein free RBC extract and cell free supernatant media increased with time. The concentration of MeMP detected in the cell free supernatant media was five-fold lower than the protein free RBC extract. Error bars denote SEM.

MP 250 M + TX 250 M at 2 h MP 250 M + EBBS at 2 h 6

* **

2 MeMP pmol/L MeMP

0 2 4 6 hours

Figure 8.2 Concentration of MeMP (pmol/L) in RBCs incubated with 250 µM MP with the addition of 250 µM thioxanthine or EBSS at 2 h. 100 µL of intact RBCs were incubated with 250 µM MP for 2 h prior to the addition of either 250 µM TX or an equivalent volume of EBBS (controls). There was no significant difference in the concentration of MeMP after 2 h incubation with 250 µM MP alone (p=0.84). In comparison with controls the mean concentration of MeMP was significantly lower at 4 h (*P = 0.0078) and 6 h (**P = 0.0005) in RBCs exposed to 250 µM TX after 2 h incubation with 250µM MP. Error bars denote SEM.

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TX 250 M + MP 250 M at 2 h 4 EBBS + MP 250 M at 2 h

MeMP pmol/L MeMP 1 * **

0 2 4 6 hours

Figure 8.3 Concentration MeMP in RBCs pre-incubated with 250 µM thioxanthine or EBSS for 2 h prior to the addition of 250 µM MP. 100 µL of intact RBCs were incubated with either 250µM TX or an equivalent volume of EBSS for 2 h (controls) prior to the addition of 250µM MP. Incubation with TX led to a significant reduction in the concentration of MeMP observed at 4 h (*P = 0.0004) and 6 h (**P = 0.0002). Error bars denote SEM.

2.0

1.5 * 1.0

MeMP pmol/L MeMP 0.5

0.0 MP (250 M) MP (250 M) + Oxy (250 M)

Figure 8.4 Concentration of MeMP at 2 h in RBCs incubated with either 250 µM MP alone or 250 µM MP with 250 µM oxypurinol. In comparison with 100 µL of intact RBCs incubated with 250 µM MP alone, co-incubation with 250 µM MeMP and 250 µM oxypurinol led a significant reduction in the concentration of MeMP observed at 2 h (*P = 0.003). Error bars denote SEM.

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8.3.2 Apparent Km of TPMT and Ki for TX and oxypurinol.

In control experiments using red cell lysates incubated with MP alone the apparent Km and Vmax for RBC TPMT as measured by tandem mass spectrometry was 0.365 mM and 46.02 pmol MeMP/ h/ mgHb respectively (figure 8.5). Co-incubation with TX resulted in a decrease of TPMT activity with an apparent Ki of 0.329 mM (figure 8.6). Similarly, co-incubation with oxypurinol resulted in a decrease of TPMT activity with an apparent Ki of 1.186 mM (figure 8.7). The Ki of TX with respect to RBC TPMT is similar in magnitude to the Km for MP suggesting that this is physiologically relevant.

50 Vmax = 46.02 Km = 0.3653 40 0.15

30 0.10

20 0.05 1/TPMT Activity 1/TPMT 10 -5 0 5 10 15

TPMT (pmol MeMP/h/mg Hb) 1/[MP] mM 0 0 2 4 6 [MP] mM

Figure 8.5 TPMT apparent Km and Vmax for MP in a red blood cell lysate preparation. In red cell lysates incubated with MP alone the apparent Km and Vmax for RBC TPMT as measured by tandem mass spectrometry was 0.365 mM and 46.02 pmol MeMP/ h/ mgHb respectively.

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50 Ki = 0.329 mM Controls 40 0.01mM TX 0.1mM TX 30 0.2mM TX 0.5mM TX 20 1mM TX 2mM TX 10 5mM TX

TPMT (pmol MeMP/h/mg Hb) MeMP/h/mg TPMT(pmol 0 0 2 4 6 [MP] mM

Figure 8.6 Apparent Ki of thioxanthine with respect to RBC TPMT. Co-incubation with MP and TX resulted in a decrease of TPMT activity with an apparent Ki of 0.329 mM as measured by tandem mass spectroscopy. The Ki of TX with respect to RBC TPMT is similar in magnitude to the Km for MP suggesting that this is physiologically relevant.

60 Controls Ki = 1.186 mM Oxypurinol 0.01mM 40 Oxypurinol 0.1mM Oxypurinol 0.2mM Oxypurinol 0.5mM 20 Oxypurinol 1mM Oxypurinol 2mM Oxypurinol 5mM 0 TPMT (pmol MeMP/h/mg Hb) MeMP/h/mg (pmol TPMT 0.0 0.2 0.4 0.6 0.8 1.0 [MP] mM

Figure 8.7 Apparent Ki of oxypurinol with respect to RBC TPMT. Co-incubation with MP and oxypurinol resulted in a decrease of RBC TPMT activity with an apparent Ki of 1.186 mM as measured by tandem mass spectroscopy.

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8.3.3 Urinary TX and oxypurinol levels in IBD patients receiving thiopurine therapy.

In both groups 1 (AZA monotherapy) and 2 (low-dose AZA with allopurinol), all patients exhibited wildtype TPMT activity with a mean TPMT level of 35 pmol MeMP/ h/ mgHb (range, 27-58 ±2.8 SEM) in group 1 and 39 pmol MeMP/ h/ mgHb (range 32-54 ±2.1 SEM) in group 2 (table 8.1). There was no significant difference in RBC TPMT levels between groups 1 and 2 (P = 0.104, Mann-Whitney U- test). In group 1, the prescribed dose of AZA ranged from 100-200 mg/day, with a median normalized dose of 1.87mg/ kg/ day (range, 1.25 – 2.22 mg/ kg, SD ± 0.30). In comparison, the prescribed dose of AZA in group 2 ranged from 12.5 - 67.5 mg/ day, with a median normalised dose of 0.44 mg/ kg/ day (range, 0.14-0.72 mg/kg/day, SD ± 0.16). Nine of the 11 patients in group 2 were also receiving 100 mg allopurinol daily and the remaining 2 were taking 200 mg daily.

The mean TGN levels in groups 1 and 2 were 379 pmol/ 8x108 RBC (± 48.12 SEM) and 349 (± 31.73 SEM) respectively and were not significantly different (P = 0.597, t-test). However, MeMP levels were significantly higher in group 1 (1434 ± 358 SEM pmol/ 8x108 RBC) as compared to group 2 (133 ±50 SEM pmol/ 8x108RBC; P = 0.0002, Mann-Whitney, U-test).

TX and oxypurinol were not detected in spot urine samples collected from the 9 healthy volunteers (Figure 8.8). TX was only seen in the urine of 1 patient receiving AZA monotherapy 4 h after oral dosing. In comparison, TX was detected in the urine of 9 patients receiving AZA and allopurinol combination therapy and mean levels were significantly higher (0.0368 µmol TX / mmol creatinine (± 0.0368 SEM) group 1 versus 0.757 µmol TX / mmol creatinine (± 0.220 SEM) group 2; P = 0.0087, Mann-Whitney U-test). As expected, oxypurinol was not detected in urine samples from patients receiving AZA monotherapy. However, oxypurinol was detected in 10 of the 11 patients receiving combination therapy with AZA and allopurinol, at a mean level of 37.0 µmol oxypurinol / mmol creatinine; (difference between groups, P = 0.0002, Mann-Whitney U-test). There was a significant positive correlation between urinary TX and oxypurinol levels (Spearman r = 0.644, P = 0.0016, 95% CI = 0.281-0.846).

Serial measurements of TX and oxypurinol levels in spot urine samples from a patient with wildtype TPMT activity (32 pmol MeMP/ h/ mgHb), demonstrated that TX was detectable in urine 1 h after oral dosing and reached a maximum at 4 h (1.61 µmol TX / mmol creatinine ). TX was undetectable 20 h after the oral dose. In comparison, urinary oxypurinol levels were maximal after 1 h (40 µmol oxypurinol / mmol creatinine) and remained detectable up to 20 h after oral dosing (figure 8.9).

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Table 8.1: Comparison of controls and IBD patients receiving either AZA monotherapy or AZA combination therapy with allopurinol.

Significance AZA Controls AZA + allopurinol group 1 monotherapy

n = 9 (group 2), n = 11 vs (group 1), n = 10 group 2

% female (n) 88 (8) 60 (6) 36 (4) P = 0.06

38.5 Mean age ± SD 36.3 ± 11.9 37.8 ± 9.40 P = 0.896 ± 11.0

CD : UC : IBD-U NA 8 : 2 : 0 6 : 4 : 1 P = 0.385

Mean TPMT (pmol MeMP/ h/ NA 35.4 ± 2.82 39.2 ± 2.11 P = 0.104 mgHb) ± SEM

Median AZA dose mg/ kg/ day NA 1.87 ± 0.30 0.44 ± 0.16 P = < 0.0001 ± SD

Mean TGN NA 379.5 ± 48.12 349.1 ± 31.73 P = 0.324 (pmol/ 8x108 RBC) ± SEM

Mean MeMP (pmol/ 8x108 RBC) NA 1434.0 ± 358.4 133.4 ± 49.60 P = 0.0002 ± SEM

Mean urinary TX (µmol)/ NA 0.0368 ± 0.0368 0.757 ± 0.220 P = 0.0087 creatinine (mmol) ± SEM

Mean urinary oxypurinol (µmol/ NA 0 36.7 ± 0.007 P = 0.0002 creatinine (mmol) ± SEM

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1.5 P = 0.0087 40

30 1.0

0.5 mol) / Creat (mmol) / mol) Creat

mol) / Creat (mmol) / mol) Creat 10



 TX TX ( 0.0 0 ( Oxy Oxy (mol) / Creat (mmol)

Controls TX (mol) / Creat (mmol) AZA Mono AZA + Allo

Figure 8.8 Urinary thioxanthine (µmol /mmol creatinine) and oxypurinol (µmol /mmol creatinine) concentrations in patients receiving combination therapy (n = 11) versus monotherapy (n = 10) or controls (n = 9). AZA Mono, azathioprine monotherapy; AZA + Allo, azathioprine and allopurinol combination therapy; Error bars denote SEM.

TX(µmol) / Creat (mmol) 2.0 OXY (µmol) / Creat (mmol) 50

40 1.5 30 1.0

20 mol) / Creat (mmol) / mol) Creat

mol) / Creat (mmol) / mol) Creat 0.5 

 10 TX TX ( 0.0 0 ( Oxy 0 5 10 15 20 25 Time (h)

Figure 8.9 Urinary thioxanthine and oxypurinol levels over a 20 h period in a patient receiving AZA and allopurinol combination therapy. Serial measurements of TX and oxypurinol levels in urine from a patient with wildtype TPMT activity (32 pmol MeMP/ h/ mgHb).

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8.4 Discussion

The data confirm that TX is an inhibitor of TPMT activity. In addition, levels of TX are increased in the urine of patients with IBD prescribed combination treatment with oral AZA and allopurinol. Therefore it is proposed that elevated TX levels, leading to inhibition of TPMT, likely explain the dramatic reduction in methylated MP metabolites that are observed in patients receiving combination therapy (181, 390). Furthermore, oxypurinol was shown to reduce the production of MeMP in RBCs by acting as a direct inhibitor of TPMT.

Combination treatment with low dose AZA/MP and allopurinol has been used in the management of patients with IBD to circumvent ADRs associated with thiopurine monotherapy. Indeed experience of this strategy at GSTT in 110 patients, has shown that it reduces the incidence of thiopurine- related side effects, including hepatotoxicity and recaptures treatment response in those with thiopurine hypermethylation (181).

Several authors have previously attempted to explain the paradoxical reduction in MeMP levels following co-therapy with allopurinol and have focussed on the role of the purine salvage enzyme HPRT in converting the thiopurine base analogue to the corresponding nucleotide TIMP. In a study of paediatric patients with non-Hodgkin’s lymphoma given high dose MP infusions (1300 mg/ m2/ day) with or without allopurinol (200 mg/ m2/ day), MeTIMP and TUA levels were significantly lower in the group receiving combination therapy (71). The authors speculated that as allopurinol is also a substrate for HPRT, co-therapy leads to lower rates of conversion of MP to TIMP which can be methylated by TPMT. A contradictory mechanism was proposed by Seinen et al., who observed an increase in HPRT activity after 12 weeks of combination therapy (505), and predicted an increase in TGN levels. However, increased HPRT activity will also lead to increased levels of TIMP, especially in mature red cells which lack IMPDH, and would therefore be predicted to lead to the increased formation of methylated thiopurine metabolites via TPMT. HPRT-centred mechanisms do not therefore adequately explain the marked reduction in MeMP levels observed clinically in patients treated with co-therapy. Moreover, in the experience of the PRL and as also noted by Seinen et al the significant decrease in MeMP levels can be observed by 4 weeks of combination therapy and yet the significant increase in RBC HPRT activity was only observed after 12 weeks of therapy, suggesting an alternative mechanism (506).

Prior to starting AZA/MP clinicians are advised to check the TPMT phenotype or genotype for polymorphisms predicting reduced enzyme activity. Approximately 0.3% of Caucasian individuals are genetically TPMT deficient and accumulate high RBC TGN levels on doses of AZA around 5-10%

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker of normal. This suggests that in those with normal TPMT activity, as much as 95% of the absorbed AZA/MP dose is inactivated through TPMT methylation (507). Furthermore, this predicts that only 5- 10% of the dose is available to XDH/AOX mediated oxidation to form TUA or to enzymes of the purine salvage pathway to form TGNs. On the other hand, when starting allopurinol, a potent XDH inhibitor, a dose reduction of AZA/MP to 25-33% of normal is required suggesting that 66-75% of MP is actually degraded via XDH to form TUA. This implies that there must be an interaction between the two pathways following combination treatment with AZA/MP and allopurinol. The current work confirms that levels of TX are elevated in the urine of patients co-prescribed low dose AZA and allopurinol. This supports a situation whereby intracellular accumulation of this intermediate, which is a potent TPMT inhibitor, provides the link between the two pathways. This explains the observed reduction in MeMP levels and also the rise in TGN levels because both degradation pathways are effectively blocked, hence a greater concentration of MP is available to the purine salvage pathway to form TGNs.

In in-vitro experiments it was found that both TX and oxypurinol inhibited TPMT activity with apparent Ki of 329 µM and 1.186 mM respectively. Using purified kidney TPMT, Deininger et al. previously demonstrated that both 2-hydroxy-MP (TX) and 2,8-dihydroxy-MP (TUA) inhibited TPMT with Ki of 183 µM and 340 µM respectively (508). The difference in the reported Ki for TX with respect to TPMT between our own observations and those of Deininger may be accounted for by differences in the source and purity of the enzyme preparations and the experimental conditions. Indeed, a 10- fold difference in IC50 values has been reported for sulphasalazine, depending on whether recombinant or RBC TPMT was studied (191, 509, 510).

There are a number of mechanisms by which treatment with a combination of low dose AZA/MP and allopurinol may lead to a rise in TX. Firstly, TG derived from the catabolism of TGMP is degraded either by GDA to form TX followed by oxidation to TUA by XDH, or it may be hydroxylated by AOX and then deaminated by GDA, generating 8-hydroxy-TG as an intermediate (106, 107). Therefore blocking XDH activity with allopurinol would lead to a rise in TX levels through blockade of the first TG degradation pathway. Secondly, TX may be formed from oxidation of MP to TX. Levels of the endogenous oxypurines, hypoxanthine and xanthine are elevated following allopurinol monotherapy (511, 512). The reason for this is that XDH catalyzes the oxidative hydroxylation of hypoxanthine to xanthine and then of xanthine to uric acid. Allopurinol is itself oxidised by XDH and the product, oxypurinol, binds tightly to the reduced molybdenum centre of the enzyme, acting as a suicide inhibitor. MP, which is an analogue of hypoxathinine, is converted to TUA via the intermediates TX (major pathway) and 8-hydroxy-MP (minor pathway), with the first oxidation reaction being rate

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker limiting (72). Therefore the addition of allopurinol would be expected to lead to a rise in both MP and TX levels. Indeed, a rise in urinary free MP levels (>4-fold) following co-treatment with allopurinol was previously reported by Rundles et al. and here the data demonstrate a rise in urinary TX levels, which correlates with oxypurinol levels (513).

Finally, it is possible that the first oxidative hydroxylation at the 2-position of MP, forming TX, not only occurs via the action of XDH but also by AOX, which is not inhibited by allopurinol / oxypurinol. However, this is against the findings of Krenitsky et al., who reported that AOX preferentially forms the metabolite 8-hydroxy-MP from MP and those of Rashidi et al., who demonstrated that AOX is mainly involved in the oxidation of TX in combination with XDH to form TUA (72, 514). However, these studies used rabbit and guinea pig derived AOX respectively and therefore the contribution of human AOX to the oxidation of MP and TX remains to be established.

The results support a minor role for oxypurinol in TPMT inhibition. Oxypurinol is also converted in- vivo to the nucleotide analogue oxypurinol riboside monophosphate and the nucleoside oxypurinol 7-riboside, the latter formed through the action of uridine phosphorylase (507, 515). Since oxypurinol riboside monophosphate is chemically similar to TIMP, a known substrate for TPMT, it is possible that binding of this oxypurinol nucleotide may also inhibit TPMT, but this was not tested. The apparent Ki for RBC TPMT using oxypurinol is relatively high and therefore the effect of oxypurinol may not be physiologically relevant. Indeed, the reported Ki for oxypurinol with soluble XDH is almost 3 orders of magnitude lower (230 nM) (516). Furthermore, in unpublished communications reported by Sparrow et al, both allopurinol and oxypurinol did not appear to inhibit either erythrocyte lysate or human liver cytosol TPMT (415). It is possible that the concentration of oxypurinol used in these experiments was not as high as those reported here, which may explain the divergent results.

Another possible reason for the observed reduction in methylated metabolites is simply the lower dose of thiopurine that is continued when allopurinol is initiated. At lower doses of MP, metabolism via the enzymes of the purine salvage pathway may be favoured over catabolism by TPMT, since the Km of TPMT is relatively high in comparison with that of HPRT. In this regard, the Km of MP for purified human kidney and RBC TPMT has been reported as 0.30 mM and 0.32 mM respectively, whereas the Km of MP for RBC HPRT is approximately 17 times lower (0.018 mM) (517-519). In keeping with this, in-vitro studies have shown that the metabolite profile is dependent on the thiopurine dose (98). In liver cytosol preparations exposed to low dose MP (10 µM), the only metabolite detected was TIMP, whereas at high doses of MP (500 µM) a much wider range of metabolites was observed, including; TUA, TX, thioxanthine nucleotide, 8-hydroxy-MP, MeMP, TIMP and TGN. Of

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker interest MeMP was only quantifiable above 50 µM of MP. This is significant since plasma levels of MP at 3 h after oral dosing are only approximately 1 - 2 µM (520). However the concentration of MP in the portal circulation is likely to be much higher.

Finally, allopurinol riboside monophosphate has been shown to inhibit the enzyme GMPR, which is involved in the deamination of guanine monophosphate to inosine monophosphate (305). Studies on the role of GMPR activity on thiopurine metabolism are lacking but, theoretically, reduced GMPR may predict higher TGN levels. Alternatively, recent evidence suggests that both AZA and MP may lead to the induction of IMPDH activity, which is considered the rate limiting step in the formation of guanosine nucleotides by the purine salvage pathway. In this regard, IMPDH was up-regulated in human hepatocytes 24 h after the introduction of AZA/MP (fold induction >2) (263). An increase in IMPDH activity theoretically predicts a rise in TGN levels, whereas low levels of IMPDH activity have been associated with high MeTIMP levels (210).

Combination treatment with low dose AZA/MP and allopurinol is not suitable for all patients. In particular allopurinol has been associated with severe cutaneous ADRs, including Stevens-Johnson Syndrome and toxic epidermal necrolysis. Patients with the HLA-B*5801 allele appear to be at increased risk for such adverse reactions (403). It is therefore tempting to speculate that TX could be used in place of allopurinol, providing direct TPMT inhibition and circumventing the risk of a cutaneous drug reaction. Phase 1 studies to determine the safety of TX as a therapeutic in humans are therefore indicated.

There are limitations to the current study. The in-vitro assays employed RBCs as a source of TPMT activity. However, RBCs are not the target cells of AZA/MP activity and they lack IMPDH activity, which is required for the production of TGNs. Therefore, studying the metabolism of MP using this assay may not fully represent in-vivo metabolism, where most of the methylation is believed to occur in hepatocytes. Furthermore, the number of patients in the in-vivo study was relatively low. However, a post-hoc power calculation has confirmed that the sample size gave sufficient power (85%) to detect a difference between patients receiving AZA monotherapy versus combination treatment.

In summary, the current work demonstrates that TX and to a lesser extent, oxypurinol are inhibitors of TPMT activity. For TX, the Ki for RBC TPMT is similar to the Km for MP and therefore this is likely to be physiologically relevant. We have additionally shown that TX levels are elevated in the urine of patients prescribed combination therapy with a low dose thiopurine and allopurinol. Therefore, our results support the hypothesis that the reduction in MeMP levels observed following co-prescription

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker occurs in part due a rise in TX levels, which inhibits TPMT activity (figure 8.10). This mechanism would also explain the rise in TGN levels observed during therapy as it predicts reduced degradation of MP through both the XDH and TPMT catalysed pathways.

Figure 8.10 Proposed mechanism of allopurinol induced TPMT inhibition.

Summary of key findings:

 Thioxanthine levels are increased in patients receiving AZA and allopurinol combination therapy.  Thioxanthine is an inhibitor of TPMT enzyme activity. This likely explains the dramatic reduction in MeMP levels in patients receiving combination treatment.

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Chapter Nine: Conclusions and future work

In 2001, the director of the Human Genome Project, Dr Francis Collins, claimed that the project’s completion would herald major advances in targeted drug discovery and provide novel opportunities to predict drug responsiveness, which could be used to inform clinical decision making. By 2020 it was envisaged that “the pharmacogenomics approach for predicting drug responsiveness will be standard practice for quite a number of disorders and drugs” (521). Indeed the past decade has enjoyed notable advances in the use of genetic data to guide drug discovery. This is particularly evident in Oncology with the development of drugs targeted around specific mutations, for example the use of Everolimus in HER2-negative breast cancer or Trastuzumab for HER2-positive breast cancer. The identification of new drug targets for common complex diseases identified by genome- wide association studies is also anticipated; however, in comparison with the development of anticancer drugs, progress has been much slower. This is partly because common complex diseases are influenced by multiple environmental and genetic factors, with each gene having a small contribution to the disease. Therefore it is conceivable that the targeted approach to drug discovery, which focuses on specific mutations, will not see the same success in the development of treatments for chronic diseases as it has in cancer. Rather much more of the ‘low-hanging fruit’ will relate to the identification of opportunities to optimise currently available treatments.

The use of genetic information to guide drug therapy decisions is now recognised by the US Food and Drugs Administration (FDA). At present there are over 100 drugs that have recommendations based on pharmacogenetic data in their FDA product label, however in only a few cases has such information translated into widely accepted changes in clinical practice. One example is the use of HLA-B*5701 genotyping prior to the initiation of abacavir in patients with HIV, since this variant is associated with drug-induced hypersensitivity. This approach is supported by a large double-blind, prospective, randomised controlled trial that showed a clear benefit of genetic testing to prevent the hypersensitivity reaction (522). A lack of similar high-quality data concerning genetic markers that predict additional treatment outcomes represents a major barrier in translating their use into clinical practice. This is even true of TPMT genotyping (or phenotyping) for AZA/MP therapy, where the use of pre-treatment testing has not been universally adopted by all disciplines, despite the link between TPMT deficiency and thiopurine toxicity having been recognised since the 1980’s (165, 220, 523).

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9.1 Optimising thiopurine therapy in patients with IBD

Clinical experience in IBD supports the use of pre-treatment TPMT testing to rationalise the starting dose of AZA/MP therapy and this is now recommended by international guidelines (37). However, TPMT testing alone predicts less than 1/3 of thiopurine-induced drug toxicity, suggesting that the situation regarding variation in inter-individual treatment response is complex. (458). In addition this emphasizes a need to identify additional opportunities to optimise treatment strategies. The first of these is afforded by the use of thiopurine metabolite testing, which allows the clinician to detect treatment non-adherence, under-dosing, over-dosing, treatment-refractory and treatment-resistant disease. This is of critical importance in the management of IBD, where the use of thiopurines is increasing and treatment failure may necessitate the use of second-line, less well proven and potentially more toxic therapy.

Thiopurine-resistance, characterised by low TGN levels and high MeMP concentrations, otherwise known as thiopurine hypermethylation, is at present our greatest opportunity to optimise AZA/MP therapy. In particular this is because the skewed drug metabolism can be circumvented and treatment response recaptured by using low dose AZA/MP combined with allopurinol. However, to date little work had been done to characterise thiopurine hypermethylation in patients with IBD.

In this thesis I have explored the impact of thiopurine hypermethylation on clinical outcomes in patients with IBD prescribed AZA/MP. This is shown to occur in 12% of patients and cannot be predicted by prior knowledge of RBC TPMT activity or the weight-normalised dose of thiopurine. Dose escalation in patients with hypermethylation leads to a preferential rise in MeMP, although this occurs without a paradoxical reduction in TGN levels as originally proposed by Dubinsky et al (64). High MeMP concentrations (≥ 5000 pmol/ 8x108 RBC) are associated with an increased risk of hepatotoxicity (8-fold increased risk); however hepatotoxicity is only observed in approximately 10 – 15% of patients with thiopurine hypermethylation. Hepatotoxicity is also encountered in patients with MeMP concentrations below 5000 pmol/ 8x108 RBC, hence additional mechanisms of drug- induced liver injury are suggested.

The majority of patients at risk of thiopurine hypermethylation demonstrated a skewed drug metabolism by 12 weeks of treatment. The data presented here additionally show that a metabolite ratio ≥ 6.17 at 4 weeks of treatment, can identify the majority of these individuals. This is clinically useful and will allow the early identification of patients with thiopurine hypermethylation and an opportunity to intervene with low dose AZA/MP and allopurinol. This is important since thiopurine hypermethylation, defined as a metabolite ratio of MeMP : TGN ≥ 11 : 1, is associated with lower

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker rates of intervention free survival during the first 12 months of thiopurine treatment and thereby an excess of avoidable morbidity. The data provide further evidence that combination treatment with 5-ASAs has little impact on thiopurine hypermethylation and secondly that a TGN level ≥ 240 pmol/ 8x108 RBC is associated with higher rates of successful treatment.

The use of thiopurine metabolite testing to guide treatment decisions in IBD is not universally advocated (158). This is mainly due to a lack of high-quality evidence and contrasts against the wealth of positive experience reported in retrospective case series and small prospective studies. To clarify the situation further two studies are now indicated. Firstly, a prospective randomised controlled trial investigating clinical outcomes in patients with IBD prescribed thiopurines, in which the first arm includes patients where thiopurine doses are adjusted according to standard haematological and biochemical parameters, in comparison with a second arm where thiopurines are optimised according to standard parameters and thiopurine metabolite profiles taken at weeks 4, 12, 24, 36 and 48 of treatment. The primary clinical outcome measure would be 12 month intervention free survival, and the secondary outcomes would be evidence of mucosal healing and the impact on CRP and faecal calprotectin levels. The second trial is a prospective randomised controlled trial investigating clinical outcomes in patients with IBD demonstrating thiopurine hypermethylation (MeMP : TGN ≥ 11 : 1), in which the first arm includes patients who continue to receive standard treatment, in comparison with a second arm where treatment is changed to low dose thiopurine (25-33% of a standard dose) in combination with allopurinol (100mg). The primary outcome measure would be trimesters of intervention free remission over the first 24 months of treatment. Extrapolating from the current data, which demonstrated 15.7% extra treatment failures in patients with thiopurine hypermethylation at 12 months, suggests that such a study would require 109 patients to yield 90% power at an α-level of 0.05 and an effect size of 0.3. This is achievable at a single centre such as GSTT.

9.2 Moving from a candidate gene approach to a genome wide approach to identify novel opportunities to optimise thiopurine therapy in IBD

Testing for polymorphic variation in the TPMT enzyme to explain toxicity related to AZA/MP, remains the best example of a hypothesis driven candidate gene approach that has translated into clinical practice. The reason for this success is that TPMT is the most important enzyme mediating thiopurine degradation and as such it is predicted to have the greatest effect on thiopurine metabolism. However, whilst TPMT is responsible for up to 90% of the drug degradation, polymorphic variation in enzyme activity only explains a fraction of the drug-toxicity. This is because thiopurine metabolism is complex, with end-metabolite concentrations representing the balance

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker between polymorphic variation within and between genes of, and external to, the thiopurine pathway, where the effects of variation at two or more loci may be either additive or divergent. Therefore, it is unlikely that further candidate gene approaches alone, which do not traditionally take account of these effects, will explain more of the variation in inter-individual treatment outcomes. This is evidenced by the conflicting data presented for ITPA, which has further undermined confidence in pharmacogenetics as a tool to guide treatment decisions.

To gain initial experience of pharmacogenetics I used a hypothesis driven candidate gene approach to identify variants associated with thiopurine hypermethylation. Such a marker would be useful to pre-emptively identify patients that would benefit from low dose thiopurine combined with allopurinol therapy. As demonstrated, polymorphic variation in the multi-drug resistance protein 5 (ABCB5, 343 A > G) was associated with thiopurine hypermethylation and in particular high MeMP concentrations. This may provide an explanation for the earlier findings that this variant is associated with a lack of response to thiopurine treatment (329). However, this polymorphism alone only explained 13% of the cases of thiopurine hypermethylation, necessitating the use of alternative genotyping strategies that can account for a greater proportion of the heritability. A genome wide association study using a SNP chip is one such approach.

The results of the first large, well-designed GWAS for complex diseases to employ a SNP chip with good coverage of the human genome, was reported in 2007 by the Wellcome Trust Case Consortium (WTCCC) (342). Since then GWAS has identified over 2000 loci that are significantly and robustly associated with one or more complex traits (524). However, whilst providing some important biological insights, the proportion of total variation explained by GWAS significant variants is typically only 10 – 20%. This is for a number of reasons; firstly, there are additional variants with such small effect sizes that they have not been detected with genome-wide significance (false- negatives); secondly, GWAS is not focused on protein coding regions, which may account for 80 – 90% of all disease-causing mutations; thirdly, not all of the phenotypic variation is explained by genetic factors; fourthly, GWAS relies on LD between genotyped SNPs and ungenotyped causal variants, therefore causal variants, particularly if they are rare variants (MAF < 0.05) may not be captured; finally, the number of discovered variants is strongly correlated with the experimental sample size and therefore at low sample sizes no significant variants may be detected. The latter highlights a need to ensure adequate statistical power in such studies.

In contrast to GWAS, exome-sequencing focuses on protein-coding regions and therefore it is anticipated to capture more functionally relevant variants. These regions account for approximately 1.5% of the 3 billion nucleotides that make-up the human genome. At present a cost-effective and

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker high-throughput alternative to whole-exome sequencing is the use of an exome microarray, which targets putative functional exonic variants selected from 1,000s of individual whole-exome and whole-genome sequences derived from patients of diverse ethnicities with a range of common complex diseases. Hence this technology was selected for use in the current studies.

Using an exome microarray, no single variants from unsupervised testing passed the threshold for genome-wide significance for any of the traits investigated, which included thiopurine hypermethylation, thiopurine response and all thiopurine-induced ADRs, nausea, flu-like symptoms, pancreatitis and hepatotoxicity. There are two main reasons for this, firstly that these are complex traits and the result of interactions between several different loci, each with a small effect, and secondly that the studies were underpowered to detect statistically significant variants. Therefore, the most important piece of further work will be to expand the current cohorts to include 100’s and ideally 1000’s of affected individuals. This will require collaboration with additional centres; however, the difficulty here will be to ensure quality and homogeneity in the phenotypic data. Indeed, a strength of the current study was the time spent on deep phenotyping, which guaranteed accurate calling of clinical outcomes.

Another reason why the exome microarray failed to discover novel SNPs with genome-wide significance is that it only covers variants in the exome region. However, this will miss intronic and promoter region variants, which may also contain regulatory elements. An example of this is the ITPA 124+21 A> C mutation in intron 2, which influences alternative splicing of the gene and therefore enzyme function. The use of whole-genome sequencing is anticipated to account for such variation and provide more a complete picture for the heritability of complex traits. However, at present the cost of such technology remains prohibitive to most large scale studies.

9.3 Exploring thiopurine treatment response using novel whole-pathway analysis

The use of an exome microarray facilitated simultaneous genotyping of 100’s of SNPs within the thiopurine and methylation pathways, which when combined with phenotypic data, allowed the formation of models to explain thiopurine hypermethylation, thiopurine response and thiopurine- induced ADRs. This novel form of entire pathway analysis is anticipated to allow a greater understanding of the heritability of these traits, by taking into account the effect of polymorphisms at multiple loci on thiopurine metabolism.

A model including polymorphic variation in a nucleotide transporter (ABCC4), enzymes with demethylating (ALKBH1 and MGMT), dephosphorylating (NT5E) and deaminating activities (GDA), age and the weight-normalised dose of thiopurine, explained up to 25% of the heritability of

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PhD Thesis Thiopurines in IBD Paul Andrew Blaker thiopurine hypermethylation. In addition, polymorphic variation in a master trans-regulator of TPMT activity, KLF-14 was shown to influence RBC MeMP concentrations.

This work also demonstrated a novel association between polymorphic variation in a subunit of ribonucleotide reductase (RRM2) and clinical response to thiopurines. To date the influence of variation in the activity of ribonucleotide reductase on thiopurine metabolism has not been extensively studied, yet this is a key mediator in the formation of deoxy-thioguanine nucleotides and by inference clinical response.

Using a combination of both unsupervised testing and pathway analysis, I have identified novel variants associated with thiopurine induced ADRs. Genetic variation in adenosine kinase (ADK) and thiopurine importer (SLC28A1) and exporter pumps (ABCB5 and ABCC4) are shown to be involved in the development of ADRs. Of particular interest was the suggestion that polymorphisms in HLA-B and MHC class 1 polypeptide-related sequence B (MICB) are associated with the development of flu- like symptoms, providing first evidence that such hypersensitivity reactions are immune mediated. Furthermore, the discovery that polymorphic variation in interleukin 15 (IL15) is associated with hepatotoxicity, may provide the missing link to explain why only a subset of patients with high MeMP concentrations demonstrate hepatotoxicity.

Each of the markers identified in the above studies now requires validation in independent cohorts. Ideally this should involve sequencing of the 500 kb around these polymorphisms, to allow fine- mapping and ensure capture of the functional variants where SNP-tagging is suspected. In addition, the influence of these polymorphisms on thiopurine metabolism should be confirmed in-vitro to demonstrate causality.

With respect to in-vitro studies, I would firstly investigate the effect of polymorphic variation in RRM2 on thiopurine metabolite profiles, given the strong effect size of this variant. This could be achieved by comparing thiopurine metabolism in HEK 293 cells expressing the RRM2 rs1130609 variant exposed to MP, against HEK 293 cells without this polymorphism. Liquid-chromatography- tandem mass spectrometry could then be used to compare differences in the concentration and ratios of deoxy-TGTP and TGTP between cells. The same techniques could also be applied to the investigation of polymorphic variation in ABCC4, ABCB5 and MGMT, by comparing the ratio of TGNs to MeTIMP concentrations following incubation with MP. This would confirm the involvement of these proteins in the development of thiopurine hypermethylation.

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9.4 How could the genetic markers identified in this thesis be translated into clinical practice?

Once validated, the markers identified by the current work will require investigation in large prospective randomised controlled and double-blinded trials to confirm their use in clinical practice. In this regard it is anticipated that they will form part of a panel of markers that could be assessed to determine if pre-emptive genotyping improves treatment outcomes. Alone the raw genotyping data is unlikely to be useful to the majority of clinicians. For example, it is unrealistic that clinicians will remember what a specific genotype means (e.g. ABCB5 343 A > G) and clinical decision support tools will need to be developed to provide guidance on therapeutic options based on genotype and phenotypic data. As a speculative example a female patient who is homozygous for the ABCB5 rs2301641 and MGMT rs12917 polymorphisms, with wildtype RBC TPMT activity who is prescribed 2mg/kg of AZA, might be predicted to have a 60% increased chance of thiopurine hypermethylation, at which point the clinician may offer primary therapy with low dose AZA/MP and allopurinol. Alternatively, a patient heterozygous for the HLA-B rs2844586 and MICB rs2844496 polymorphisms might have a 70% increased risk of thiopurine-induced flu-like symptoms, in which case treatment with low dose AZA/MP and allopurinol or thioguanine may be offered as first line immunosuppression.

9.5 Resolving the interaction between thiopurines and allopurinol

The final section of this thesis resolves the biochemical mechanism explaining why combination treatment with low dose AZA/MP and allopurinol leads to dramatic reductions in MeMP concentrations. In this regard, excess production of thioxanthine, an intermediate in the thiouric acid degradation pathway, is shown to act as a direct inhibitor of TPMT. Future studies are indicated to determine if thioxanthine could be used as a therapeutic in combination with AZA/MP in place of allopurinol. This may be particularly relevant to patients carrying the HLA-B*5801 variant, who are at increased risk for the development of severe cutaneous reactions to allopurinol. In addition, the mechanism of allopurinol induced TPMT inhibition should be confirmed in mononuclear cells, which are the target cells of thiopurine therapy.

9.6 Concluding remarks

The conclusion of my thesis is that there are further opportunities to optimise the outcomes of patients receiving thiopurines, beyond current clinical practice. The data support the use of thiopurine metabolite monitoring to guide treatment decisions. In particular, identification of thiopurine hypermethylation is important since this is associated with an excess of treatment failures and it can be circumvented with low dose AZA/MP and allopurinol. Whilst the studies

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The pharmacogenetic markers of treatment outcomes presented here are of considerable interest; however their significance needs replication in independent cohorts before they can be accepted into routine clinical practice. Subsequently, the use of biomarker panels predicting treatment outcomes, prior to the start of therapy, would be a major breakthrough, allowing thiopurine treatment strategies to be tailored to the individual and ultimately shortening the time taken to achieve remission whilst minimising toxicity.

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502. Elion GB, Kovensky A, Hitchings GH. Metabolic studies of allopurinol, an inhibitor of xanthine oxidase. Biochemical pharmacology. 1966;15(7):863-80. Epub 1966/07/01. 503. Chocair PR, Duley JA, Cameron JS, Arap S, Ianhez L, Sabbaga E, et al. Does low-dose allopurinol, with azathioprine, cyclosporin and prednisolone, improve renal transplant immunosuppression? Advances in experimental medicine and biology. 1994;370:205-8. Epub 1994/01/01. 504. Ansari A, Elliott T, Baburajan B, Mayhead P, O'Donohue J, Chocair P, et al. Long-term outcome of using allopurinol co-therapy as a strategy for overcoming thiopurine hepatotoxicity in treating inflammatory bowel disease. Alimentary pharmacology & therapeutics. 2008;28(6):734-41. Epub 2009/01/16. 505. Seinen ML, de Boer NK, Smid K, van Asseldonk DP, Bouma G, van Bodegraven AA, et al. Allopurinol enhances the activity of hypoxanthine-guanine phosphoribosyltransferase in inflammatory bowel disease patients during low-dose thiopurine therapy: preliminary data of an ongoing series. Nucleosides, nucleotides & nucleic acids. 2011;30(12):1085-90. Epub 2011/12/03. 506. Seinen ML, van Asseldonk DP, de Boer NK, Losekoot N, Smid K, Mulder CJ, et al. The effect of allopurinol and low-dose thiopurine combination therapy on the activity of three pivotal thiopurine metabolizing enzymes: Results from a prospective pharmacological study. Journal of Crohn's & colitis. 2013. Epub 2013/01/16. 507. Duley JA, Chocair PR, Florin TH. Observations on the use of allopurinol in combination with azathioprine or mercaptopurine. Alimentary pharmacology & therapeutics. 2005;22(11-12):1161-2. Epub 2005/11/25. 508. Deininger M, Szumlanski CL, Otterness DM, Van Loon J, Ferber W, Weinshilboum RM. Purine substrates for human thiopurine methyltransferase. Biochemical pharmacology. 1994;48(11):2135- 8. Epub 1994/11/29. 509. Lewis LD, Benin A, Szumlanski CL, Otterness DM, Lennard L, Weinshilboum RM, et al. Olsalazine and 6-mercaptopurine-related bone marrow suppression: a possible drug-drug interaction. Clinical pharmacology and therapeutics. 1997;62(4):464-75. Epub 1997/11/14. 510. Shipkova M, Niedmann PD, Armstrong VW, Oellerich M, Wieland E. Determination of thiopurine methyltransferase activity in isolated human erythrocytes does not reflect putative in vivo enzyme inhibition by sulfasalazine. Clinical chemistry. 2004;50(2):438-41. Epub 2004/01/31. 511. Rundles RW. Metabolic effects of allopurinol and allo-xanthine. Annals of the rheumatic diseases. 1966;25(6 Suppl):615-20. Epub 1966/11/01. 512. Weir E, Fisher JR. The effect of allopurinol on the excretion of oxypurines by the chick. Biochimica et biophysica acta. 1970;222(2):556-7. Epub 1970/11/24. 513. Rundles RW. Effects of allopurinol on 6-mercaptopurine therapy in neoplastic diseases. Annals of the rheumatic diseases. 1966;25(6 Suppl):655-6. Epub 1966/11/01. 514. Krenitsky TA, Neil SM, Elion GB, Hitchings GH. A comparison of the specificities of xanthine oxidase and aldehyde oxidase. Archives of biochemistry and biophysics. 1972;150(2):585-99. Epub 1972/06/01. 515. Krenitsky TA, Elion GB, Strelitz RA, Hitchings GH. Ribonucleosides of allopurinol and oxoallopurinol. Isolation from human urine, enzymatic synthesis, and characterization. The Journal of biological chemistry. 1967;242(11):2675-82. Epub 1967/06/10. 516. Malik UZ, Hundley NJ, Romero G, Radi R, Freeman BA, Tarpey MM, et al. Febuxostat inhibition of endothelial-bound XO: implications for targeting vascular ROS production. Free radical biology & medicine. 2011;51(1):179-84. Epub 2011/05/11. 517. Woodson LC, Weinshilboum RM. Human kidney thiopurine methyltransferase. Purification and biochemical properties. Biochemical pharmacology. 1983;32(5):819-26. Epub 1983/03/01. 518. Weinshilboum RM, Raymond FA, Pazmino PA. Human erythrocyte thiopurine methyltransferase: radiochemical microassay and biochemical properties. Clinica chimica acta; international journal of clinical chemistry. 1978;85(3):323-33. Epub 1978/05/02.

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519. Lennard L, Hale JP, Lilleyman JS. Red blood cell hypoxanthine phosphoribosyltransferase activity measured using 6-mercaptopurine as a substrate: a population study in children with acute lymphoblastic leukaemia. British Journal of Clinical Pharmacology. 1993;36(4):277-84. Epub 1993/10/01. 520. Endresen L, Lie SO, Storm-Mathisen I, Rugstad HE, Stokke O. Pharmacokinetics of oral 6- mercaptopurine: relationship between plasma levels and urine excretion of parent drug. Therapeutic drug monitoring. 1990;12(3):227-34. Epub 1990/05/01. 521. Collins FS, McKusick VA. Implications of the Human Genome Project for medical science. JAMA : the journal of the American Medical Association. 2001;285(5):540-4. Epub 2001/02/15. 522. Mallal S, Phillips E, Carosi G, Molina JM, Workman C, Tomazic J, et al. HLA-B*5701 screening for hypersensitivity to abacavir. The New England journal of medicine. 2008;358(6):568-79. Epub 2008/02/08. 523. Lennard L, Van Loon JA, Weinshilboum RM. Pharmacogenetics of acute azathioprine toxicity: relationship to thiopurine methyltransferase genetic polymorphism. Clinical pharmacology and therapeutics. 1989;46(2):149-54. Epub 1989/08/01. 524. Visscher PM, Brown MA, McCarthy MI, Yang J. Five years of GWAS discovery. American journal of human genetics. 2012;90(1):7-24. Epub 2012/01/17.

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Appendix 1

List of genes included in the thiopurine pathway

Gene Full name

ABCA1 ATP-binding cassette, sub-family A, member 1 ABCB1 ATP-binding cassette, sub-family B, member 1 ABCB11 ATP-binding cassette, sub-family B, member 11 ABCB5 ATP-binding cassette, sub-family B, member 5 ABCC1 ATP-binding cassette, sub-family C, member 1 ABCC11 ATP-binding cassette, sub-family C, member 11 ABCC2 ATP-binding cassette, sub-family C, member 2 ABCC4 ATP-binding cassette, sub-family C, member 4 ABCC5 ATP-binding cassette, sub-family C, member 5 ABCG2 ATP-binding cassette, sub-family G, member 2 ADA Adenosine deaminase ADK Adenosine kinase AHCY Adenosylhomocysteinase AHCYL1 Adenosylhomocysteinase-like 1 AHCYL2 Adenosylhomocysteinase-like 2 ALKBH1 Alkylation repair homolog 1 ALKBH2 Alkylation repair homolog 2 ALKBH3 Alkylation repair homolog 3 AOX1 Aldehyde oxidase 1 5-aminoimidazole-4-carboxamide ribonucleotide ATIC formyltransferase / IMP cyclohydrolase BHMT Betaine-homocysteine-S-methyltransferase BHMT2 Betaine-homocysteine-S-methyltransferase 2 CANT1 Calcium activated nucleotidase 1 CBS Cystathionine-beta-synthase COMT Catechol-O-methyltransferase CYP1A2 Cytochrome P450 1A2 CYP2C9 Cytochrome P450 2C9 ENTPD1 Ectonucleoside triphosphate diphosphohydrolase 1 GART Phosphoribosylglycinamide formyltransferase GDA Guanine deaminase GMPR Guanosine monophosphate reductase GMPS Guanosine monophosphate synthetase GNMT Glycine-N-methyltransferase GSTA2 Glutathione-S-transferase alpha 2 GSTA3 Glutathione-S-transferase alpha 3 GSTA4 Glutathione-S-transferase alpha 4 GSTA5 Glutathione-S-transferase alpha 5 GSTCD Glutathione-S-transferase, C-terminal domain containing

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Gene Full name

GSTM1 Glutathione-S-transferase mu 1 GSTM2 Glutathione-S-transferase mu 2 GSTM3 Glutathione-S-transferase mu 3 GSTM4 Glutathione-S-transferase mu 4 GSTM5 Glutathione-S-transferase mu 5 GSTO1 Glutathione-S-transferase omega 1 GSTO2 Glutathione-S-transferase omega 2 GSTP1 Glutathione-S-transferase pi 1 GSTT1 Glutathione-S-transferase theta 1 GSTZ1 Glutathione-S-transferase zeta 1 HLA-G Human leukocyte antigen G HNMT Histamine-N-methyltransferase IMPDH1 Inosine-5’-monophosphate dehydrogenase 1 IMPDH2 Inosine-5’-monophosphate dehydrogenase 2 ITPA Inosine triphosphate pyrophosphohydrolase KLF14 Kruppel-like factor 14 MAT1A Methionine adenosyltransferase 1, alpha MGMT 0-6-methylguanine-DNA methyltransferase MGST2 Microsomal glutathione-S-transferase 2 MGST3 Microsomal glutathione-S-transferase 2 MOCOS Molybdenum cofactor sulfurase MTAP Methylthioadenosine phosphorylase MTHFD1 Methylenetetrahydrofolate dehydrogenase 1 MTHFD2 Methylenetetrahydrofolate dehydrogenase 2 MTHFR Methylenetetrahydrofolate reductase MTR 5-methyltetrahydrofolate homocysteine methyltransferase 5-methyltetrahydrofolate homocysteine methyltransferase MTRR reductase NAT1 N-acetyltransferase 1 NAT2 N-acetyltransferase 2 NME1-NME2 NME1-NME2 readthrough NME3 Nucleoside diphosphate kinase 3 NME4 Nucleoside diphosphate kinase 4 NME5 Nucleoside diphosphate kinase 5 NME6 Nucleoside diphosphate kinase 6 NME7 Nucleoside diphosphate kinase 7 NME9 Nucleoside diphosphate kinase 9 NT5C1A 5’-nucleotidase, cystosolic IA NT5C2 5’-nucleotidase, cystosolic II NT5C3 5’-nucleotidase, cystosolic III NT5E 5’-nucleotidase, ecto Protein kinase C and casein kinase substrate in neurones PACSIN1 protein 1

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Gene Full name

PEMT Phosphatidylethanolamine N-methyltransferase PNP Purine nucleoside phosphorylase PPAT Phosphoribosyl pyrophosphate amidotransferase PRPS1L1 Phosphoribosyl pyrophosphate synthetase 1-like 1 RAC1 Ras-related C3 botulinum toxin substrate 1 RRM1 Ribonucleotide reductase M1 RRM2 Ribonucleotide reductase M2 RRM2B Ribonucleotide reductase M2 subunit B SLC25A26 Solute carrier family 25, member 26 SLC28A1 Solute carrier family 28, member 1 SLC28A2 Solute carrier family 28, member 2 SLC28A3 Solute carrier family 28, member 3 SLC29A1 Solute carrier family 29, member 1 SLC29A2 Solute carrier family 29, member 2 SLC29A3 Solute carrier family 29, member 3 SLC29A4 Solute carrier family 29, member 4 SLCO1B1 Solute carrier organic anion transporter family, member 1B1 SLCO1B7 Solute carrier organic anion transporter family, member 1B7 TPMT Thiopurine-S-methyltransferase TYMS Thymidylate synthetase XDH Xanthine dehydrogenase

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List of genes included in the methylation pathway

Gene Full name ADI1 Acireductone dioxygenase ALKBH1 Alkylation repair homolog 3 ALKBH2 Alkylation repair homolog 2 ALKBH3 Alkylation repair homolog 1 AMD1 Adenosylmethionine decarboxylase 1 APIP Methylthioribulose-1-phosphate dehydratase BHMT Betaine-homocysteine-S-methyltransferase BHMT2 Betaine-homocysteine-S-methyltransferase 2 COMT Catechol-O-methyltransferase ENOPH1 Enolase-phosphatase HNMT Histamine-N-methyltransferase IL4I1 Interleukin 4 induced 1 KLF14 Krupple-like factor 14 MAT1A Methionine adenosyltransferase 1, alpha MAT2A Methionine adenosyltransferase 2, alpha MAT2B Methionine adenosyltransferase 2, beta MRI1 Methylthioribose-1-phosphate isomeras MTHFD1 Methylenetetrahydrofolate dehydrogenase 1 MTHFD1L Methylenetetrahydrofolate dehydrogenase 1-like MTHFD2 Methylenetetrahydrofolate dehydrogenase 2 MTHFD2L Methylenetetrahydrofolate dehydrogenase 2-like MTHFS 5,10-methylenetetrahydrofolate synthetase Protein kinase C and casein kinase substrate in PACSIN1 neurones protein 1 PEMT Phosphatidylethanolamine N-methyltransferase SMS Spermine synthase SRM Spermidine synthase TAT Tyrosine aminotransferase TPMT Thiopurine-S-methyltransferase TYMS Thymidylate synthetase

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Appendix 2

Demethylation of methylmercaptopurine by human liver microsomes; a role for CYP1A2 and CYP2C9

Introduction:

TPMT is responsible for the methylation of MP and its correspondent ribonucleotides. Recent literature suggests that this is an irreversible reaction, however in 1959 Sarcione and Stutzman reported that MeMP could also undergo demethylation, with the observation that MP is a urinary metabolite of rats given MeMP (i). Elion et al. later confirmed this finding in man, reporting the presence of TUA in urine from patients receiving MeMP (ii). In 1964 Mazel et al. demonstrated that the liver microsome fraction is likely to be responsible for the demethylation of S-methyl compounds (iii). These are important findings as it suggests flux between TPMT and demethylating enzymes that may partly explain variation in thiopurine metabolite profiles and additionally thiopurine drug interactions. The aim of this study was to confirm demethylation of MeMP in human liver microsomes using state of the art techniques and secondly to determine if particular cytochrome P450 enzymes demethylate MeMP.

Methods:

10 μL of pooled human liver microsomes (Life Technologies, UK) were suspended in 430 μL of 100 mM KH2PO4 buffer at pH 7.4 containing 50 μL of MP (final concentration 1.48 mM). The mixture was pre-incubated in a water bath at 37°C for 5 min, prior to the addition of 10 μL 100mM ß- Nicotinamide adenine dinucleotide 2’-phosphate reduced tetrasodium salt (NADPH; Sigma-Aldrich) or an equal volume of KH2PO4 buffer (controls). After 2 h the reaction was stopped with the addition of 50 μL 50% perchloric acid (PCA). The mixture was spun at 12,000 x g for 2 min and 75 μL of the protein free supernatant removed. 2 μL of the supernatant was injected onto a UPLC system and the concentration of MeMP and MP measured. The experiment was repeated using specific recombinant human cytochromes (CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, CYP3A5) in place of the human liver microsomes.

Results:

In human liver microsomes incubated with MeMP but not NADPH (controls) the concentration of MeMP at 2 h was 1.48 mM /L ±0.01. In preparations incubated with MP and NADPH the average concentration of MeMP at 2 h was significantly lower (1.41 mM/L ±0.02, p=0.02, t-test, figure 1). This suggests that approximately 5.7% of the MeMP dose was converted to other substances. In

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Figure 1 Demethylation of MeMP by human liver microsomes in the absence or presence of the NADPH co-factor. A. Chromatogram showing that in the absence of the NADPH co-factor, there is no MP detected at 2 h following incubation with MeMP. B. Chromatogram showing that in the presence of the NADPH co-factor, MP is detected at 2 h following incubation with MeMP, confirming demethylation of MeMP by human liver microsomes.

Conclusion:

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The results confirm the historical findings that MeMP may undergo demethylation by human liver microsomes and second that this is specifically mediated by CYP1A2 and CYP2C9. However, in-vitro at least this appears to be a minor pathway. Further in-vivo studies are indicated to determine the influence of CYP1A2 and CYP2C9 activity on thiopurine metabolite profiles and therein clinical response.

References: i). Sarcione, E. J and Stutzman, L. A comparison of the metabolism of 6-mercaptopurine and its 6- methyl analog in the rat. Cancer Res. 1960; 20: 387 – 392. ii). Elion, G. B., Callahan, S. W., Hitchings, G. H. The fate of 6-methylthiopurine in man. Proc Amer Ass Cancer Res. 1962; 3: 316. iii). Mazel, P., Henderson, J. F., Axelrod, J. S-demethylation by microsomal enzymes. J Pharmacol Exp Ther. 1964: 143: 1-6.

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