A polygenic risk score-based analysis of gene-drug interactions in relation to type 2 diabetes risk.

Abstract

Statin usage is associated with a higher risk of developing type 2 diabetes (T2D); however, statins have been shown to be safe and effective at lowering the risk of cardiovascular disease and are a widely used first line therapy. Therefore, it is critical to understand the underlying mechanisms of the association between statin usage and T2D, including gene- environment interactions. This study’s primary objective was to examine interactions between a T2D polygenic risk score (PRS) and statin usage on T2D risk. A secondary objective was to investigate interactions between statin usage and sex on T2D risk. This study utilized data from n=360,989 participants of the UK Biobank (UKB) without prevalent diabetes at baseline. Multiple logistic regression models were fit to test for multiplicative interaction between statin usage at baseline and measures of T2D PRS while controlling for various other covariates. Evidence for the interaction between statin usage at baseline and standard T2D PRS was not found (p = 0.125, and p = 0.481 for the PRS treated as a decile and standardized continuous value, respectively). When the data is subset by genetic sex the association of statin usage with T2D risk for females is (OR 1.86, 95% C.I 1.68, 2.06) and for males (OR 1.69, 95% C.I 1.58, 1.82) with the interaction estimate for statin usage and genetic sex (male) having p = .050. Future research on interactions between statin usage and genetic variants should examine interactions of statin usage with pathway- or cluster-specific T2D- related genetic variants such as variants contained in partitioned polygenic risk scores, while possible differential sex-based effects of statins on T2D risk may warrant fitting separate models dichotomized by sex.