UvA-DARE (Digital Academic Repository) Precision medicine in childhood asthma The role of genetic variations in treatment response Farzan, N. Publication date 2019 Document Version Final published version License Other Link to publication Citation for published version (APA): Farzan, N. (2019). Precision medicine in childhood asthma: The role of genetic variations in treatment response. General rights It is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), other than for strictly personal, individual use, unless the work is under an open content license (like Creative Commons). Disclaimer/Complaints regulations If you believe that digital publication of certain material infringes any of your rights or (privacy) interests, please let the Library know, stating your reasons. In case of a legitimate complaint, the Library will make the material inaccessible and/or remove it from the website. Please Ask the Library: https://uba.uva.nl/en/contact, or a letter to: Library of the University of Amsterdam, Secretariat, Singel 425, 1012 WP Amsterdam, The Netherlands. You will be contacted as soon as possible. UvA-DARE is a service provided by the library of the University of Amsterdam (https://dare.uva.nl) Download date:04 Oct 2021 Precision Medicine in Childhood Asthma The role of genetic variations in treatment response Niloufar Farzan Precision Medicine in Childhood Asthma The role of genetic variations in treatment response Niloufar Farzan 1 Het printen van dit proefschrift werd mede mogelijk gemaakt door AMC Amsterdam en Longfonds (Lungfoundation Nertherlands). Printed by: Ipskamp Precision Medicine in Childhood Asthma: The role of genetic variations in treatment response 2019 Niloufar Farzan, Amsterdam. 2 Precision Medicine in Childhood Asthma The role of genetic variations in treatment response ter verkrijging van de graad van doctor aan de Universiteit van Amsterdam op gezag van de Rector Magnificus prof. dr. ir. K.I.J. Maex ten overstaan van een door het College voor Promoties ingestelde commissie, in het openbaar te verdedigen in de Agnietenkapel op dinsdag 12 februari 2019, te 10.00 uur door Niloufar Farzan geboren te Tabriz 3 PROMOTIECOMMISSIE Promotor prof. dr. A.H. Maitland-van der Zee AMC-UvA Copromotor dr. S.J.H. Vijverberg AMC-UvA Overige leden: prof. dr. E.H.D. Bel AMC-UvA prof. dr. P.J. Sterk AMC-UvA dr. S.W.J. Terheggen AMC-UvA prof. dr. G. Bartlett-Esquilant McGill University, Montreal Canada prof. dr. B. Wilffert Rijksuniversiteit Groningen Faculteit der Geneeskunde 4 Table of contents Chapter 1: General introduction 7 Chapter 2: Reviewing evidence of (pharmaco)genomics effects in asthma 19 Chapter 2.1: The use of pharmacogenomics, epigenomics, and transcriptomics to improve 21 childhood asthma management: Where do we stand? Chapter 2.2: Pharmacogenomics of inhaled corticosteroids and leukotriene modifiers: 45 a systematic review Chapter 3: Pharmacogenomics in childhood asthma 113 Chapter 3.1: Rationale and design of the multi-ethnic Pharmacogenomics in Childhood 115 Asthma Consortium Chapter 3.2: 17q21 variant increases risk of exacerbations in asthmatic children despite using 145 inhaled corticosteroids Chapter 3.3: Genome-wide association study of inhaled corticosteroid response in 171 African-admixed children with asthma Chapter 4: Risk factors associated with asthma exacerbations despite ICS use 213 Chapter 4.1: Risk factors of asthma exacerbations in asthmatic children treated with ICS: 215 is there an added value of genetic risk factors? Chapter 5: Cost-effectiveness of pharmacogenetic-guided treatment 251 Chapter 5.1: Cost-effectiveness of genotyping before starting LABA therapy in asthmatic 253 children and young adults. Chapter 6: General discussion 277 Scientific Summary & samenvatting 311 Appendices 326 5 6 CHAPTER 1 General Introduction 7 Evolution of disease management towards precision medicine Since prehistoric times, humans have used natural products such as extracts from plants, animals and even microorganisms to treat different diseases (1). However, only since the 19th century, pharmacology evolved as an independent principle when scientists began to develop and apply experiments to understand physiological mechanisms and drug actions (1). These advances were followed by the technological breakthroughs and development of synthetic techniques at the beginning of the 20th century which revolutionized the pharmaceutical industry (1). However, parallel to the development of highly effective pharmacological agents, evidence started to pile up regarding the inter- and intraindividual variability in response to most drugs (2). Studies show that response to most drugs ranges between 50 and 75 percent (2). This fact has triggered scientists to find out why an effective and safe medication for one group of patients has a decreased or an exaggerated effect in another group. Decades of research have shown that factors such as age (3), gender (4), diet (5) and concomitant disease or medication use (6) can influence response to treatment. Additionally, over the past three decades advances in genomic technologies have helped scientists discover the role of genomic variations in treatment response (7,8). Altogether, these findings indicated that a combination of clinical, environmental and genomic factors could result in treatment response heterogeneity. In fact, this idea has ultimately paved the way for a new era in medicine called Precision Medicine (9). According to National Institutes of Health (NIH), precision medicine is "an emerging approach for disease treatment and prevention that takes into account individual variability in genes, environment, and lifestyle for each person" (9). The ultimate aim of precision medicine is to increase health on the population level by preventing diseases and giving the right treatment to the right patient at the right time (9). Pharmacogenomics The study of the relation between variations in the genome and response to a specific medication in terms of efficacy and safety is called pharmacogenomics/pharmacogenetics (10). Although these two terms are used interchangeably, their definitions differ. Pharmacogenetics mainly refers to genes determining drug metabolism, pharmaco- genomics, on the other hand, studies all genes in the genome that might determine drug response (11). In this thesis, we will use the term pharmacogenomics. 8 Single Nucleotide Polymorphisms (SNPs), the most abundant genetic variations in the genome, are the most commonly investigated genetic variations in pharmacogenomics studies (12). A SNP is a single base pair change at a specific position in the DNA sequence that results in different alleles (12). The human genome contains approximately 10 million SNPs (13). SNPs can occur in both protein-coding and non-coding regions that might contain enhancers and promoters (13). SNPs that fall within the protein-coding regions might change the amino acid sequence which can subsequently result in an altered amount or function of the protein. SNPs within the non-coding regions may modify the expression of one or several genes (13). Any alterations in gene expression amount or function of the protein could ultimately influence the mechanisms related to absorption, distribution, metabolism or excretion/elimination (ADME) of the drug (pharmacokinetics) or target (mostly receptors) of the drugs (pharmacodynamics) (14). These alterations subsequently can influence the efficacy of the drug and treatment response (12,15). In pharmacogenomics studies, the association between genetic variations and treatment response is typically investigated by two main approaches: hypothesis-driven and hypothesis-generating approaches (16). The most common hypothesis-driven pharmaco- genomics studies are candidate gene studies (16). In these studies, ‘candidate genes’ are often selected based on prior knowledge of the biological mechanisms related to the disease or drug signaling pathway. The number of pre-selected SNPs can range from one to several hundred (16). In contrast to hypothesis-driven approaches, in hypothesis-generating approaches usually, thousands or even millions of SNPs are studied simultaneously without pre-selection (16). Hypothesis-generating approaches are suitable for identifying (novel) genetic markers in complex diseases and traits where not only genes but also environmental factors, gene- gene interactions, and gene-environment interactions play a role in the development of disease (17). Genome-Wide Association Studies (GWAS) are one of these high throughput methods that study 500,000 to millions of common SNPs (frequency 5%) across the genome (18). The SNPs that are not assayed on the genotyping chips, can be estimated using reference panels and based on the knowledge about the correlation between a large set of SNPs (linkage disequilibrium). This process which is called genotype imputation increases the number of common variants with great precision (17). The result of the pharmacogenomics studies could ultimately help to predict patients’ response to treatment based on their genetic makeup and could help to select the optimal drug and dose for each patient. Several clinical trials have shown promising results for 9 genotype-guided dosing algorithms of anticoagulants such as acenocoumarol, phencopromon, and warfarin (19,20) and genotype-guided drug selection for carbamazepine (an anti-epileptic drug) (21) and abacavir (an antiretroviral drug) (22). Pharmacogenomic