Integrating genetics and metabolomics from multi-ethnic and multi-fluid data reveals putative mechanisms for age-related macular degeneration

• DOI: 10.1016/j.xcrm.2023.101085
• Publication Date: 2023-06-21T14:29:33Z
• Authors: Xikun Han; Ines Lains; Jun Li; Jinglun Li; Yiheng Chen; Bing Yu; Qibin Qi; Eric Boerwinkle; Robert Kaplan; Bharat Thyagarajan; Martha Daviglus; Charlotte E. Joslin; Jianwen Cai; Marta Guasch-Ferré; Deirdre K. Tobias; Eric Rimm; Alberto Ascherio; Karen Costenbader; Elizabeth Karlson; Lorelei Mucci; A. Heather Eliassen; Oana Zeleznik; John Miller; Demetrios G. Vavvas; Ivana K. Kim; Rufino Silva; Joan Miller; Frank Hu; Walter Willett; Jessica Lasky-Su; Peter Kraft; J. Brent Richards; Stuart MacGregor; Deeba Husain; Liming Liang
• Keywords: Mendelian Randomization; Metabolome; Genetic Association; Genome-wide Association Study

Age-related macular degeneration (AMD) is a leading cause of blindness in older adults. Investigating shared genetic components between metabolites and AMD can enhance our understanding its pathogenesis. We conduct metabolite genome-wide association studies (mGWASs) using multi-ethnic metabolomic data from up to 28,000 participants. With bidirectional Mendelian randomization analysis involving 16,144 advanced cases 17,832 controls, we identify 108 putatively causal relationships plasma AMD. These are enriched glycerophospholipid metabolism, lysophospholipid, triradylcglycerol, long chain polyunsaturated fatty acid pathways. Bayesian colocalization customized metabolome-wide approach prioritize putative AMD-associated metabolites. find limited evidence linking urine risk. Our study emphasizes the contribution metabolites, particularly lipid-related pathways genes, risk uncovers numerous associations