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Exome Sequencing and Array-Based Comparative Genomic Hybridisation Analysis of Preferential 6-Methylmercaptopurine Producers

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Exome Sequencing and Array-Based Comparative Genomic Hybridisation Analysis of Preferential 6-Methylmercaptopurine Producers The Pharmacogenomics Journal (2015) 15, 414–421 © 2015 Macmillan Publishers Limited All rights reserved 1470-269X/15 www.nature.com/tpj ORIGINAL ARTICLE Exome sequencing and array-based comparative genomic hybridisation analysis of preferential 6-methylmercaptopurine producers EW Chua1,2, S Cree1, ML Barclay3,4, K Doudney5, K Lehnert6, A Aitchison1 and MA Kennedy1 Preferential conversion of azathioprine or 6-mercaptopurine into methylated metabolites is a major cause of thiopurine resistance. To seek potentially Mendelian causes of thiopurine hypermethylation, we recruited 12 individuals who exhibited extreme therapeutic resistance while taking azathioprine or 6-mercaptopurine and performed whole-exome sequencing (WES) and copy- number variant analysis by array-based comparative genomic hybridisation (aCGH). Exome-wide variant filtering highlighted four genes potentially associated with thiopurine metabolism (ENOSF1 and NFS1), transport (SLC17A4) or therapeutic action (RCC2). However, variants of each gene were found only in two or three patients, and it is unclear whether these genes could influence thiopurine hypermethylation. Analysis by aCGH did not identify any unusual or pathogenic copy-number variants. This suggests that if causative mutations for the hypermethylation phenotype exist they may be heterogeneous, occurring in several different genes, or they may lie within regulatory regions not captured by WES. Alternatively, hypermethylation may arise from the involvement of multiple genes with small effects. To test this hypothesis would require recruitment of large patient samples and application of genome-wide association studies. The Pharmacogenomics Journal (2015) 15, 414–421; doi:10.1038/tpj.2015.9; published online 10 March 2015 INTRODUCTION retrospective study (n = 1879), 2.5% of New Zealand individuals Azathioprine and 6-mercaptopurine structurally resemble endo- receiving thiopurine treatment were found to have a very high 8 genous purines, differing from the latter at the sixth carbon atom, 6-MMP/6-TGN ratio of 4100. The role of TPMT in thiopurine 8,9 where the substituent is replaced by a sulfhydryl-based functional hypermethylation is uncertain, and involvement of other 10,11 group. Hence, these compounds are categorically designated genes has not been firmly established. Overall, the mechan- ‘thiopurines’. Intracellularly, azathioprine and 6-mercaptopurine isms underlying such metabolite shunting remain unclear. are converted by successive metabolic steps into 6-thioguanine Whole-exome sequencing (WES), which enables simultaneous nucleotides (6-TGN), which are mis-incorporated into DNA during sequencing of all protein-coding regions within the genome, has fi DNA synthesis, disrupting the process and causing cytotoxicity.1 identi ed several novel pharmacogenetic markers such as those involved in the response to clopidogrel,12 escitalopram,13 Other pathways competing with the formation of 6-TGN include 14 15 methylation or oxidation of 6-mercaptopurine, mediated by clozapine and anticancer agents (pazopanib and everolimus). thiopurine methyltransferase (TPMT) and xanthine dehydrogenase We set out to investigate the possible genetic basis of metabolite (XDH) respectively, as illustrated in Figure 1. Historically, use of shunting observed in a group of patients who exhibited resistance fl towards thiopurine therapy, by using WES technology. These thiopurine compounds in in ammatory bowel disease has been ‘ ’ noted particularly for its steroid-sparing effects,2,3 despite patients are referred to as extreme shunters in this report. Our 4 main aim was to test whether this phenotype was a Mendelian potentially fatal immunosuppressive complications. trait due to mutation of a gene involved in thiopurine metabolism, Interindividual variability in response to thiopurine compounds transport or function. has been studied extensively. In addition to TPMT, new pharmaco- genetic markers are emerging.5 However, much of the variability still eludes current understanding in pharmacogenetics. Thera- MATERIALS AND METHODS peutic monitoring in individuals receiving thiopurine therapy is Patient recruitment achieved by determining the relative concentrations of 6-TGN and 6-methylmercaptopurine (6-MMP),6 and dose adjustment can help This study was approved by the Southern Health and Disability Ethics Committee, New Zealand. A total of 12 patients who had 6-MMP/6-TGN improve drug response and minimise potential treatment 4 fi 7 ratios 100 while on thiopurine therapy were identi ed from a previous toxicity. Individuals who preferentially methylate thiopurine local study.8 These patients reported European descent, with the exception compounds into 6-MMP, as evidenced by a high 6-MMP/6-TGN of one male who reported mixed ancestry. Potential participants were ratio (420), are predicted to have a non-favourable response. In a contacted first by mail and were required to indicate interest to participate 1Carney Centre for Pharmacogenomics and Department of Pathology, University of Otago Christchurch, Christchurch, New Zealand; 2Faculty of Pharmacy, Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia; 3Department of Clinical Pharmacology, Christchurch Hospital, Canterbury District Health Board, Christchurch, New Zealand; 4Department of Medicine, University of Otago Christchurch, Christchurch, New Zealand; 5Molecular Pathology, Canterbury Health Laboratories, Christchurch, New Zealand and 6School of Biological Sciences, University of Auckland, Auckland, New Zealand. Correspondence: Professor MA Kennedy, Carney Centre for Pharmacogenomics, University of Otago Christchurch, Christchurch, New Zealand. E-mail: [email protected] Received 16 June 2014; revised 15 January 2014; accepted 28 January 2015; published online 10 March 2015 Exome sequencing analysis of 6-methylmercaptopurine overproducers EW Chua et al 415 Figure 1. A simplified representation of major thiopurine metabolic pathways (adapted from Zaza et al.32). Table 1. Candidate genes with involvement in thiopurine transport, by filling in and returning an enclosed form. Face-to-face interviews were subsequently conducted to obtain written consent and collect relevant metabolism or therapeutic action medical history. The study information sheet and consent form included procedures for handling of incidental findings, which would be followed- Candidate genes Ref. up in consultation with a clinical geneticist. DNA was extracted from Thiopurine transport, metabolism or target: ABCC4, ABCC5, 32 peripheral blood leukocytes using a KingFisher Flex Magnetic Particle ADA, ADK, AHCY, AOX1, GART, GMPS, GSTA1, GSTA2, GSTM1, Processor, as per the manufacturer’s instructions (Thermo Fisher Scientific, HPRT1, IMPDH1, ITPA, NT5E, PPAT, PRPS1, RAC1, SLC28A2, Waltham, MA, USA). SLC28A3, SLC29A1, SLC29A2, TPMT, XDH Genes identified through gene expression profiling: CD1D, 11 TPMT activity CTSS, DEF8, FAM46A, FAM156A, FAR1, GNB4, HVCN1, IMPDH2, Available TPMT activity data were also documented for each participant. A LAP3, MAP3K1, PLCB2, SLX1A, SMAP2,TGOLN2,TOX4,TUSC2,UBE2A Synthesis of S-adenosylmethionine: TYMS, MAT1A, MAT2A, previous study had established the normal range of TPMT activity to be 33–35 9.3-17.6 IU ml − 1 in the local New Zealand population.16 The distribution of MTHFR Molybdenum cofactor activity: MOCOS 36 TPMT activity among New Zealand individuals is similar to that in other 37 populations.17 Modulation of TPMT activity: PACSIN2 Efflux of methylated metabolite: ABCB5 38 Others: GDA, MTAP, NT5C2 39 Exome sequencing Whole-exome enrichment and sequencing was done by New Zealand Abbreviation: TPMT, thiopurine methyltransferase. Genomics Ltd. (Dunedin, New Zealand). Twelve TruSeq (Illumina, San Diego, CA, USA) DNA libraries were prepared and sequenced on one lane of a HiSeq 2000 (Illumina) to produce paired-end reads that were 100 The reduced variant file was annotated using SeattleSeq Annotation 138 nucleotides long. (accessible at http://snp.gs.washington.edu/SeattleSeqAnnotation138/),27 build 9.02 (updated on 20 April 2014). The annotated file was then Quality control, sequence reads alignment and variant calling successively filtered based on the Combined Annotation-Dependent 18 Depletion (CADD) C scores, which include functional and conservation Sequence reads were aligned by Burrows-Wheeler Aligner v0.7.4 to the 28 human GRCh37.p13 reference assembly and processed with SAMtools metrics, and population MAFs documented in the HapMap and Exome v0.1.1919 and Picard v0.96 (http://picard.sourceforge.net). Reads originating Variant Server (EVS) databases. CADD C scores cannot be generated for from PCR duplicates were removed with Picard before and after local indels; as a result, this group of variants were treated separately and were filtered by their Genomic Evolutionary Rate Profiling (GERP) scores,29 in realignment around potential insertions/deletions (indels) with the 30 20 accordance with the recommended cut-off value. Other functional Genome Analysis Toolkit (GATK, v2.7.1). Illumina base quality scores 31 were recalibrated with GATK in the final alignments. Single-nucleotide annotations, including the PolyPhen-2 predictions, were also considered. variants (SNVs) and indels were called simultaneously via local de novo assembly of haplotypes using GATK’s HaplotypeCaller tool.21 Joint variant Candidate-gene analysis calling and variant quality score recalibration were supported by adding A comprehensive list of 52 candidate genes was compiled from a literature exome alignments from 24
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