B1948
Title: Phenotypic heterogeneity at drug target genes for mechanistic insights: Cis-multivariable Mendelian randomization
Authors: Stephen Burgess - University of Cambridge (United Kingdom) [presenting]
Abstract: Phenotypic heterogeneity at genomic loci encoding drug targets can be exploited by multivariable Mendelian randomization to provide insight into the pathways by which pharmacological interventions may affect disease risk. However, statistical inference in such investigations may be poor if overdispersion heterogeneity in measured genetic associations is unaccounted for. A novel extension for two-sample multivariable Mendelian randomization is then developed that accounts for overdispersion heterogeneity in dimension-reduced genetic associations. The empirical focus is to use genetic variants in the GLP1R gene region to understand the mechanism by which GLP1R agonism affects coronary artery disease (CAD) risk. Colocalization analyses indicate that distinct variants in the GLP1R gene region are associated with body mass index and type 2 diabetes. Multivariable Mendelian randomization analyses that were corrected for overdispersion heterogeneity suggest that bodyweight lowering rather than type 2 diabetes liability lowering effects of GLP1R agonism are more likely contributing to reduced CAD risk. Tissue-specific analyses prioritised brain tissue as the most likely to be relevant for CAD risk, of the tissues considered. The multivariable Mendelian randomization approach illustrated is deemed to be widely applicable to better understand mechanisms linking drug targets to disease outcomes, and hence to guide drug development efforts.
