Integrating genetics and metabolomics data reveals putative mechanisms for age-related macular degeneration

Abstract

Purpose : Age-related macular degeneration (AMD) is a leading cause of vision loss among the elderly. Understanding the shared genetic components between metabolites and AMD can provide better insights into the pathogenesis of AMD.

Methods : Leveraging large-scale genetic and metabolomic data, we performed genome-wide association studies for 346 plasma metabolites with a median sample size of 6,610 participants in the Nurses’ Health Study, Nurses’ Health Study II, and Health Professionals Follow Up Study (NHS, NHSII, and HPFS). AMD GWAS summary statistics from the International AMD Genomics Consortium with 16,144 advanced AMD cases and 17,832 controls were used to investigate the putative causal associations between metabolites and risk of AMD in a bi-directional two-sample Mendelian randomization (MR) framework and Bayesian genetic colocalization analysis. Finally, we develop a metabolome-wide association study (MWAS) pipeline to identify metabolite-AMD associations.

Results : In the NHS, NHSII, and HPFS, we prioritized 41 putative causal associations between metabolites and AMD. Bayesian colocalization analysis revealed 249 shared common causal variants for metabolites and AMD. In the MWAS, we identified 119 metabolites, of which 39 were further prioritized in MR analysis. Pathway analysis revealed that the identified metabolites were mapped to the glycerophospholipid metabolism pathway.

Conclusions : Our results provide genetic evidence that highlights the contribution of metabolites to AMD risk. The shared causal variants and prioritized causal metabolites provide new insights into the pathogenesis of AMD.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.