A Mendelian randomization-based drug repurposing pipeline: application to lipid traits and coronary artery disease.

Drug repurposing can efficiently identify promising therapeutic targets using existing data; however, current approaches have important limitations. There is a particular need for high-throughput approaches that are both versatile and rigorous. As such, we developed a flexible, high-throughput, Mendelian randomization (MR)-based drug repurposing pipeline with three stages: 1) MR-based protein target identification, 2) MR-based validation and prioritization, and 3) drug target mapping. This pipeline can be applied to a broad range of binary and continuous traits and incorporates quality control measures such as testing for heterogeneity, horizontal pleiotropy, and Bayesian colocalization. In Stage 1, the pipeline conducts MR analyses to identify proteins with putative causal effects on a specified trait or condition. In Stage 2, targets with significant associations in Stage 1 are evaluated using MR for either the same outcome in an external cohort or a related outcome. Targets with a consistent direction of association in Stages 1 and 2 are then assessed in Stage 3, which queries DGIdb, a database of druggable therapeutic targets, to identify repurposing candidates. To demonstrate the utility and flexibility of this pipeline, we applied it to atherosclerotic cardiovascular disease. Using UKB-PPP cis-pQTLs as instruments for 2,923 circulating proteins, we identified 72 proteins associated with LDL-C and 75 with triglyceride levels from the GLGC (Stage 1). Of these, 18 lipid-associated targets were also associated with coronary artery disease (Stage 2). Drug target mapping identified 5 proteins targeted by approved drugs, highlighting potential repurposing opportunities (Stage 3).