Methodological approaches to the pharmacogenomics of statins

Abstract

Cardiovascular drugs are abundantly prescribed to reduce risk of cardiovascular disease. Treatment with these (and other) drugs is often ineffective, and/or is accompanied by adverse drug reactions (ADRs). This can partially be explained by factors such as gender, age, concomitant drug use and environmental factors. To a certain extent, genetic variability may contribute to the variability in response to cardiovascular drugs as reviewed in chapter 2.1. Aside from some well established examples (e.g. coumarins and CYP2C9, VKORC1), several genetic markers have been identified that were shown to affect cardiovascular drug response in more than one study, but many more genetic markers have been proposed, but not replicated. Numerous explanations have been proposed to contribute to the lack of reproducibility of many findings. In chapter 2.2, we described some of the methodological and statistical issues within study design, gene and single nucleotide polymorphism (SNP) selection and data analysis that should be considered in future pharmacogenomic research. We elaborate on some of the pros and cons of a study that uses a candidate gene approach versus a study that uses a genome-wide association study (GWAS) approach. Furthermore, we discussed both conventional data analysis and several innovative approaches that deal with testing many variables and the human biological complexity. We contributed to the knowledge about genetic determinants of the effectiveness of statins in reducing the risk of cardiovascular events in chapter 3, chapter 4, and chapter 5. We collected data for an observational retrospective case control study enriched with genetic information. The advantages of this study design were the relatively low costs and efforts, the feasibility to include a large amount of cases, and that it reflects everyday clinical care. Different methodological approaches were used for the studies described. Chapter 3 focuses on one or two SNPs within a candidate gene for modification of statin effectiveness, whereas chapter 4 describes studies that consider all common variability in candidate genes within a certain pathway for the pharmacogenetics of statins. SNPs from a cardiovascular gene-centric 50K SNP array were tested for their influence on statin responsiveness in chapter 5. The most promising findings include interactions found between statin treatment and SNPs in the ADAMTS1 and PCSK9 gene. In addition, SNPs in other genes such as SCARB1, ABCB1, SLCO1B1, F5, F7, and GNB3 require additional investigation. Although statins are generally well tolerated, muscular side effects are often experienced by patients and may be related to genetics as reviewed in chapter 6.1. The SLCO1B1 T521C variant was subject of a study on discontinuation in two independent populations, an event that is in line with suffering from ADRs. Compatible with previous findings we found a small increase in risk of statin discontinuation for variant allele carriers in one, but not the other study. Finally, chapter 7 provides a general discussion of our findings in a broader perspective, including the implications for clinical practice and recommendations for future research. We advocate that randomized clinical trials should not be the golden standard that warrants clinical implication of a pharmacogenetic interactions when conclusive evidence from observational research is already available