The limits of genome-wide methods for pharmacogenomic testing

Abstract

Objective The goal of pharmacogenomics is the translation of genomic discoveries to individualized patient care. Recent advances in the means to survey human genetic variation are fundamentally transforming our understanding of the genetic basis of interindividual variation in therapeutic response. The goal of this study was to systematically evaluate high-throughput genotyping technologies for their ability to assay variation in pharmacogenetically important genes (pharmacogenes). These platforms are either being proposed for or are already widely used for clinical implementation; therefore, knowledge of coverage of pharmacogenes on these platforms would serve to better evaluate current or proposed pharmacogenetic association studies. Method Among the genes included in our study are drug metabolizing enzymes, transporters, receptors, and drug targets, of interest to the entire pharmacogenetic community. We considered absolute and LD-informed coverage, minor allele frequency spectrum and functional annotation for a Caucasian population. We also examined the effect of linkage disequilibrium, effect size and cohort size on power to detect SNP associations. Results In our analysis of 253 pharmacogenes, we found that no platform showed more than 85% coverage of these genes (after accounting for LD). Furthermore the lack of coverage showed a dramatic increase at minor allele frequencies of less than 20%. Even after accounting for LD, only 30% of missense polymorphisms (which are enriched for low frequency alleles) were covered by HapMap with still lower coverage on the other platforms. Conclusion We have conducted the first systematic evaluation of the Axiom Genomic Database, Omni 2.5M and the DMET chip. This study is the first to utilize the 1000 Genomes Project to present a comprehensive evaluative framework. Our results provide a much-needed assessment of microarray-based genotyping and next-generation sequencing technologies’ ability to survey fully the variation in genes of particular interest to the pharmacogenetics community. Our findings demonstrate the limitations of genome-wide methods and the challenges of implementing pharmacogenomic tests into the clinical context.

The Future of Warfarin Pharmacogenetics in under-represented Minority Groups

“…However, the use of GWAS in African–American individuals also has its limitations. A recent publication by our laboratory interrogated the coverage of approximately 250 pharmacogenes (i.e., genes important in pharmacogenomics) on several different high-throughput genotyping platforms [76]. We also investigated the coverage of these pharmacogenes in the HapMap Project, which is commonly used as the reference set for SNP imputation in GWAS, compared with the 1000 Genomes Project data, which were generated through deeper sequencing and provide greater SNP coverage.…”

Challenges to Integrating Pharmacogenetic Testing into Medication Therapy Management

“…27 Health professionals involved in the delivery of PGx testing may include the laboratorian, prescriber, pharmacist, and potentially a genetic counselor. With development of new and cheaper testing technologies, 29,30 it is possible that patients’ genetic predisposition for a panel of drugs will be ascertained through a single test and results consulted as new medications are prescribed.…”

Genome-Wide Approaches in Pharmacogenomics: Heritability Estimation and Pharmacoethnicity as Primary challenges

“…Prior to the advances in high-throughput genome-wide technologies [16], pharmacogenetic studies focused primarily on candidate genes within a priori implicated pathways. In general, classic pharmacogenetic studies were restricted to pharmacologic traits in which a small number of variants (frequently, in a single candidate gene) had a large effect on drug response [17].…”