Combining genetic proxies of drug targets and time-to-event analyses from longitudinal observational data to identify target patient populations

BACKGROUND: Human genetics is an important tool for identifying genes as potential drug targets, and the extensive genetic study of cardiovascular disease provides an opportunity to leverage genetics to match specific patient populations to specific drug targets to improve prioritization of patient selection for clinical studies. METHODS: We selected well described genetic variants in the region of PCSK9 (rs11591147 and rs562556), ADRB1 (rs7076938), ACE (rs4968782 and rs4363), GLP1R (rs10305492) and ABCC8 (rs757110) for use as proxies for the effects of drugs. Time-to-event analyses were utilized to evaluate their effects on atrial fibrillation (AF) and heart failure (HF) death and/or re-hospitalization using real-world longitudinal dataset. To mitigate the effect of confounding factors for cardiovascular (CV) outcomes, we employed propensity score matching. RESULTS: After matching, a genetic proxy for PCSK9 inhibition (rs11591147) improved survival from CV death/heart transplant in individuals following a diagnosis of ischemic heart disease (Hazard Ratio (HR) 0.78, P = 0.03). A genetic proxy for beta-blockade (rs7076938) improved freedom from rehospitalization or death in individuals with AF (HR 0.92, P = 0.001), and a genetic proxy of ACE inhibition (rs7076938) improved freedom from rehospitalization for HF or death (HR 0.8, P = 0.017) and AF (HR 0.85, P = 0.0014). A protective variant in GLP1R (rs10305492) showed decreased risk of developing HF or CV death after diagnosis of ischemic heart disease (HR = 0.82, P = 0.031) and a protective variant in ABCC8 (rs757110) showed decreased risk of CV mortality since ischemic disease diagnosis (HR = 0.88, P = 0.04) and decreased risk of AF in diabetic patients with ischemic heart disease (HR = 0.68, P = 0.001). Notably, despite smaller cohort sizes after matching, we often observed numerically smaller HRs and reduced P, indicating more pronounced effects and increased statistical association. However, not all genetic proxies replicated known treatment effects. CONCLUSIONS: Genetic proxies for well-known drugs corroborate findings from clinical trials in cardiovascular disease. Our results demonstrate a useful analytical approach that leverages genetic evidence from a large cohort with longitudinal outcomes data to effectively select patient populations where specific drug targets may be most effective.