A Mendelian randomization-based drug repurposing pipeline

Drug repurposing offers the opportunity to identify promising drug targets efficiently using existing data, but there are currently limitations to these efforts; there is a particular need for versatile, but rigorous high-throughput approaches. As such, we developed a flexible, high-throughput, Mendelian randomization (MR)-based drug repurposing pipeline with three stages: 1) MR-based identification, 2) MR-based validation and prioritization, and 3) application. This pipeline can be applied to a broad range of clinical characteristics and diagnoses, including binary and continuous traits. Along with this flexibility, it offers rigorous quality control and validation. In Stage 1, the pipeline conducts MR analyses to identify proteins as potential drug targets (exposures) for a specified trait/condition (outcome). The MR analysis includes quality control steps, such as testing for heterogeneity, horizontal pleiotropy, and Bayesian colocalization. In Stage 2, MR analysis with quality control is conducted with significant results from Stage 1 (exposures) for either the same (external cohort only) or a related outcome. Drug 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 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 assessed causal effects on LDL-C and triglycerides levels from the GLGC (Stage 1) and validated lipids-associated targets with a large coronary artery disease GWAS (Stage 2). Stage 3 mapped 6 proteins that interact with approved drugs, highlighting drug repurposing opportunities.