LAUSR

Abstract Human genetics offers the potential to inform on the viability of therapeutic targets through the identification of associations between naturally occurring genetic variants and clinical outcomes. Whole Exome Sequencing (WES) enables comprehensive analysis of protein coding variants, which can directly link genes to disease or related traits. We hypothesized that large-scale WES analysis could retrospectively (a) confirm the efficacy and (b) predict the side effects of known drugs for type 2 diabetes (T2D) or related metabolic traits. We analyzed WES data for 20,341 T2D cases and 23,981 controls with additional lipid, body mass index (BMI), and blood pressure (BP) measurements. Eight sets of curated genes were either (a) targeted by a medication for T2D (8 genes), hypercholesterolemia (13 genes), obesity (6 genes), or high BP (41 genes); or (b) targeted by a medication with a known side effect of T2D (8 genes), hypercholesterolemia (54 genes), obesity (230 genes), or elevated BP (126 genes). Rare variant gene-level burden tests were conducted for each gene and trait, and then a Mann-Whitney U test was used to assess whether each set of genes exhibited in aggregate stronger-than-expected gene-level associations for its corresponding trait. We observed several significant set-level associations for gene sets defined on the basis of drug primary effects, including for known T2D drug targets (T2D p = 0.002300) and for known cholesterol drug targets (total cholesterol p = 0.003790; low-density lipoprotein p = 0.00835). However, significant gene-level associations were not observed between known obesity drug targets and BMI (p = 0.3418) or between known BP targets and BP (p = 0.1597). When analyzing gene sets defined on the basis of drug side effects, we observed a significant set-level hypercholesterolemia association for targets of drugs with a side effect of hypercholesterolemia (p = 0.01614), but did not observe a significant set-level BMI association for genes targeted by drugs with a side effect of obesity (p = 0.6577) or a significant set-level BP association for genes targeted by drugs with a side effect of elevated BP (p = 0.3551). This analysis demonstrates the feasibility of current exome sequence sample sizes to predict primary and secondary side effects of drugs related to T2D or lipid traits, and suggests that drugs related to BMI or BP may be more challenging to validate with existing WES data. Drugs initially approved for a non-cholesterol and non-diabetes indication, but whose target demonstrates a significant association with lipids or T2D in our data, may be potential candidates for drug repurposing.