Applications of Mendelian randomization to the discovery and validation of blood biomarkers in cardiometabolic disease

Abstract

Peripheral blood biomarkers can inform clinical care and drug development. Establishing causality between biomarker and disease is often critical for such applications, but epidemiological studies are limited due to biases from confounding and reverse causation. Mendelian randomization analysis leverages random inheritance of genetic variants at conception to mimic properties of randomized studies and estimate unconfounded effects between biomarker and disease, or vice-versa. This thesis demonstrates the utility of Mendelian randomization as a complementary tool to elucidate observational studies, predict drug safety and repurposing opportunities, and improve diagnostic biomarkers for cardiometabolic diseases. First, we characterized the hypothesized relationship between lipoprotein(a) and atrial fibrillation. We demonstrated both observed and genetically predicted lipoprotein(a) levels were associated with higher risk of atrial fibrillation across multiple independent cohorts. Importantly, risk was partly mediated independent of atherosclerotic cardiovascular disease, a known consequence of elevated lipoprotein(a) and itself a risk factor for atrial fibrillation. Next, we explored the lifelong effects of endogenous testosterone across a comprehensive set of 461 health outcomes in 161,268 males from the UK Biobank cohort. Using Mendelian randomization analysis, we found higher testosterone had beneficial effects on body composition and bone mineral density but adverse effects on prostate cancer, androgenic alopecia, spinal stenosis, and hypertension. Finally, we applied Mendelian randomization with the intention of discovering biomarkers caused by disease, which are expected to represent markers of early disease. As a proof-of-concept, we applied this framework to identify biomarkers associated with genetic predisposition to kidney function among 238 biomarkers measured in the ORIGIN trial. We discovered reduced kidney function caused increased trefoil factor 3 and showed its addition to models with known risk factors improved discrimination of incident early-stage chronic kidney disease. Taken together, Mendelian randomization identified biomarkers that warrant further study, with promising implications for screening, prevention, and treatment of different cardiometabolic diseases.