Pharmacogenetics of response to statins

Abstract

The 3-hydroxy-3-methylglutaryl coenzyme A (HMG CoA) reductase inhibitors (statins) are among the most commonly prescribed drugs worldwide. On average, statins improve lipid profiles and have been shown to have ancillary beneficial effects on inflammation, platelet activity, and endothelial function. However, variability in drug response exists regardless of the measured phenotype, and genetic variability may be a contributing factor. Recently, there has been an interesting shift in statin pharmacogenetic studies. Novel study designs have been employed and nontraditional candidate genes have been investigated in relation to both lipid and nonlipid responses to statins. This review outlines earlier pharmacogenetic studies and highlights newly published findings that expand on previous work. Furthermore, a framework is provided in which the necessary next steps in research are described, with the ultimate goal of translating pharmacogenetic findings into clinically meaningful changes in patient care.

Figure 1

Schematic of prospective genotype-stratified pharmacogenetic study. Informed consent, initial eligibility determination, and samples for genotyping are obtained at the prescreening visit. Subjects with needed genotypes are asked to return to meet biochemistry inclusion criteria. In this scenario, wild-type homozygous (A/A) and variant homozygous subjects (B/B) will be enrolled to maximize likelihood of seeing genotype effects. If eligible, participants are given statins, and protein biomarkers are measured and compared by genotype groups at the end of study. An alternative iteration (dashed lines) includes a parallel placebo arm or employs a crossover design within genotype groups.

Figure 2

Integrative approach to statin pharmacogenetics. Any of a number of methodologic approaches can be taken to identify genetic associations with drug response, including candidate single nucleotide polymorphism (canSNP), haplotype tag SNP (tSNP), putative functional SNP (pfSNP), family linkage, or whole genome analyses (WGA). Furthermore, putative causal SNPs or haplotypes can be identified or validated by in silico and in vitro analyses. Replication studies for any positive associations should be performed, and both test and replication datasets should be deposited in a publicly available, curated database such as the Pharmacogenetics and Pharmacogenomics Knowledge Base (http://www.pharmgkb.org). The described interplay requires increasingly sophisticated bioinformatics tools.