Rasmussen‐Torvik, Laura J.

Genetic variation can affect drug response in multiple ways, although it remains unclear how rare genetic variants affect drug response. The electronic Medical Records and Genomics (eMERGE) Network, collaborating with the Pharmacogenomics Research Network, began eMERGE‐PGx, a targeted sequencing study to assess genetic variation in 82 pharmacogenes critical for implementation of “precision medicine.” The February 2015 eMERGE‐PGx data release includes sequence‐derived data from ∼5,000 clinical subjects. We present the variant frequency spectrum categorized by variant type, ancestry, and predicted function. We found 95.12% of genes have variants with a scaled Combined Annotation‐Dependent Depletion score above 20, and 96.19% of all samples had one or more Clinical Pharmacogenetics Implementation Consortium Level A actionable variants. These data highlight the distribution and scope of genetic variation in relevant pharmacogenes, identifying challenges associated with implementing clinical sequencing for drug treatment at a broader level, underscoring the importance for multifaceted research in the execution of precision medicine.

Abstract To identify novel genetic loci influencing interindividual variation in red blood cell (RBC) traits in African-Americans, we conducted a genome-wide association study (GWAS) in 2315 individuals, divided into discovery (n = 1904) and replication (n = 411) cohorts. The traits included hemoglobin concentration (HGB), hematocrit (HCT), RBC count, mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), and mean corpuscular hemoglobin concentration (MCHC). Patients were participants in the electronic MEdical Records and GEnomics (eMERGE) network and underwent genotyping of ~1.2 million single-nucleotide polymorphisms on the Illumina Human1M-Duo array. Association analyses were performed adjusting for age, sex, site, and population stratification. Three loci previously associated with resistance to malaria—HBB (11p15.4), HBA1/HBA2 (16p13.3), and G6PD (Xq28)—were associated (P ≤ 1 × 10−6) with RBC traits in the discovery cohort. The loci replicated in the replication cohort (P ≤ 0.02), and were significant at a genome-wide significance level (P < 5 × 10−8) in the combined cohort. The proportions of variance in RBC traits explained by significant variants at these loci were as follows: rs7120391 (near HBB) 1.3% of MCHC, rs9924561 (near HBA1/A2) 5.5% of MCV, 6.9% of MCH and 2.9% of MCHC, and rs1050828 (in G6PD) 2.4% of RBC count, 2.9% of MCV, and 1.4% of MCH, respectively. We were not able to replicate loci identified by a previous GWAS of RBC traits in a European ancestry cohort of similar sample size, suggesting that the genetic architecture of RBC traits differs by race. In conclusion, genetic variants that confer resistance to malaria are associated with RBC traits in African-Americans.

OBJECTIVE Elevated fasting glucose level is associated with increased carotid intima-media thickness (IMT), a measure of subclinical atherosclerosis. It is unclear if this association is causal. Using the principle of Mendelian randomization, we sought to explore the causal association between circulating glucose and IMT by examining the association of a genetic risk score with IMT. RESEARCH DESIGN AND METHODS The sample was drawn from the Atherosclerosis Risk in Communities (ARIC) study and included 7,260 nondiabetic Caucasian individuals with IMT measurements and relevant genotyping. Components of the fasting glucose genetic risk score (FGGRS) were selected from a fasting glucose genome-wide association study in ARIC. The score was created by combining five single nucleotide polymorphisms (SNPs) (rs780094 [GCKR], rs560887 [G6PC2], rs4607517 [GCK], rs13266634 [SLC30A8], and rs10830963 [MTNR1B]) and weighting each SNP by its strength of association with fasting glucose. IMT was measured through bilateral carotid ultrasound. Mean IMT was regressed on the FGGRS and on the component SNPs, individually. RESULTS The FGGRS was significantly associated (P = 0.009) with mean IMT. The difference in IMT predicted by a 1 SD increment in the FGGRS (0.0048 mm) was not clinically relevant but was larger than would have been predicted based on observed associations between the FFGRS, fasting glucose, and IMT. Additional adjustment for baseline measured glucose in regression models attenuated the association by about one third. CONCLUSIONS The significant association of the FGGRS with IMT suggests a possible causal association of elevated fasting glucose with atherosclerosis, although it may be that these loci influence IMT through nonglucose pathways.