Genetic Evidence for Causal Effects of Blood Metabolites on Age-Related Macular Degeneration and its Subtypes

Age-related macular degeneration (AMD) is a predominant cause of permanent vision impairment among older individuals. Despite available treatments for advanced disease, a comprehensive understanding of the pathogenesis, specifically the pivotal causal pathways, remains elusive. This study aims to assess the causal effects of 1400 serum metabolites and their ratios on 3 AMD subtypes using Mendelian randomization (MR).

This study leveraged an integrated MR analytical framework to systematically investigate the causal relationships of 1400 circulating metabolites and metabolite ratios with 3 AMD subtypes: early, dry, and wet AMD. The robustness and consistency of the findings were validated via comprehensive sensitivity analyses, alongside assessments for heterogeneity and horizontal pleiotropy.

Of the 1400 metabolites and metabolite ratios examined, inverse variance weighting identified 77, 62, and 80 metabolites with statistically significant causal associations with early, dry, wet AMD, respectively. Most of these associations demonstrated consistency across complementary MR methodologies. Furthermore, most of the identified metabolites did not show significant evidence of heterogeneity or horizontal pleiotropy. Notably, among lipid classes, glycerophosphoethanolamine (GPE) metabolites consistently exhibited protective effects.

Multiple metabolite classes, including glycerophospholipids, fatty acids, steroid hormones, and energy metabolism intermediates, are involved in AMD pathogenesis. These findings confirm that metabolic dysregulation is the principal driver of AMD at the causal level, in addition to revealing heterogeneous effect sizes of distinct metabolic pathways across disease subtypes. This study reveals potential molecular targets for developing strategies based on metabolism for AMD prevention, diagnosis, and precision therapeutics.

This work bridges fundamental metabolic discoveries to clinical application by identifying causal metabolites as novel therapeutic targets and informing strategies specific to disease subtypes for precision medicine and diagnostics in AMD.