Genomewide Association Studies in Pharmacogenomics

Abstract

The increasing availability of genotype data linked with information about drug-response phenotypes has enabled genomewide association studies (GWAS) that uncover genetic determinants of drug response. GWAS have discovered associations between genetic variants and both drug efficacy and adverse drug reactions. Despite these successes, the design of GWAS in pharmacogenomics (PGx) faces unique challenges. In this review, we analyze the last decade of GWAS in PGx. We review trends in publications over time, including the drugs and drug classes studied and the clinical phenotypes used. Several data sharing consortia have contributed substantially to the PGx GWAS literature. We anticipate increased focus on biobanks and highlight phenotypes that would best enable future PGx discoveries.

Figure 1

Statistics of pharmacogenomics (PGx) genomewide association studies (GWAS) performed from 2008 through June 2020. (a) The total number of publications studying PGx each year. (b) The percent of all GWAS published that study PGx in the GWAS Catalog. (c) The cohort size of PGx GWAS (blue) compared to the cohort size of all other GWAS (red), derived from the GWAS Catalog. The year of publication is derived from PubMed which may differ from the actual publication date. Publications were queried from GWAS Catalog on March 27, 2021.

Figure 2

(a) Number of newly discovered drug response associations each year that had not previously been identified (P < 5 × 10^‐8) or in linkage disequilibrium with a previously identified variant (R ² < 0.5). Colors represent Anatomical Therapeutic Chemical (ATC) groups. Only the top nine ATC groups ranked by number of unique associations are shown. All other ATC groups are grouped into “Other.” (b) The sixteen most studied ATC groups using genomewide association studies (GWAS) and whether response or adverse drug reactions (ADRs) were the focus of the study. Colors represent whether the study had significant findings (p < 5 × 10^‐8). All ATC groups not in the top 16 are grouped into “Other.” The large number of vaccine associations discovered in 2012 were derived mostly from a single publication studying side effects of the smallpox vaccine. PGx, pharmacogenomics.

Figure 3

Gene‐drug associations identified using genomewide association studies (GWAS). Associations included in this figure were identified through the reported associations in GWAS Catalog. Each point represents a reported association between a gene region, plus 50 kilobases upstream and downstream, and a drug response measured phenotype. The variant with the lowest P value within the locus from any study was selected. The most specific drug or drug class was selected based on Anatomical Therapeutic Chemical (ATC) code. For example, studies of general statin use are not included because there are studies specifically for rosuvastatin and simvastatin. The letters on the right side of the figure represent ATC level 1 code of the drug’s ATC code. Absence of a dot means that there was no study that reported an association for that drug‐gene pair for that specific drug in GWAS Catalog. Only drugs and genes with at least one association are shown. Neighboring genes may share associations if they are within 50 kilobases. Circles indicate variants that are reported by GWAS Catalog to be in coding regions (e.g., missense variants), diamonds indicate variants in noncoding regions (e.g., intronic). For example, warfarin: single‐nucleotide polymorphisms in noncoding region of CYP2C8 (diamond), coding region of CYP2C9 (circle), coding region of CYP4F2 (circle), and noncoding region of VKORC1 (diamond), are significantly associated with warfarin response (blue color diamond or circle) at P < 5 × 10^‐8. PGx, pharmacogenomics.

Figure 4

Pharmacogenomics (PGx) genomewide association studies (GWAS) populations from 2008 to 2020 show European bias in study participants. Each color represents an ancestral population. (a) Discovery cohort size for PGx GWAS over time. Dot size is correlated with study size. (b) Percentage of total PGx GWAS participants in discovery cohorts belonging to each ancestral population over time. (c) The percentage of PGx GWAS focusing on each ancestral population over time. (d) Percent of all PGx GWAS participants in discovery cohorts based on their ancestral population. (e) Percent of all PGx GWAS participants in replication cohorts based on their ancestral population.

Figure 5

Impactful consortia and cohorts in pharmacogenomics (PGx) genomewide association studies (GWAS). Each row represents a single cohort, consortia, or institution, and its length of the bar in the right‐most part of the figure represents the number of published GWAS data from that cohort has contributed to (a single publication may contain more than one GWAS). Colors represent drug Anatomical Therapeutic Chemical (ATC) groups. Dots on the left side of the figure represent the annual publication frequency of each consortium or cohort. Larger dots indicate more publications. Abbreviations: CHS: Cardiovascular Health Study; Rotterdam: Rotterdam studies; AGES: Age, Gene, Environment, Susceptibility; PEAR: Pharmacogenomic Evaluation of Antihypertensive Responses; PROSPER: Prospective study of Pravastatin in the Elderly at Risk; CATIE: Clinical Antipsychotic Trials of Intervention Effectiveness; FHS: Framingham Heart Study; SJCRH: St. Jude Children's Research Hospital; BioVU: Vanderbilt University Biobank; CAMP: Childhood Asthma Management Program; CARE: Childhood Asthma Research and Education; GERA: Genetic Epidemiology Research on Adult Health and Aging; MESA: Multi‐Ethnic Study of Atherosclerosis; STAR*D: Sequenced Treatment Alternatives to Relieve Depression; ARIC: Atherosclerosis Risk in Communities; CALGB: Cancer and Leukemia Group B.