Association of Metabolomics With Incidence of Age-Related Macular Degeneration: The UK Biobank Study.

Abstract

Purpose: The purpose of this study was to identify serum metabolites associated with age-related macular degeneration (AMD) incidence and investigate whether metabolite profiles enhance AMD risk prediction.

Methods: In a prospective cohort study involving 240,317 UK Biobank participants, we assessed the associations of 168 metabolites with AMD incidence using Cox hazards models. Principal component analysis (PCA) captured 90% of the variance in metabolites. These principal components (PCs) were added to the Cox models, with the first PC selected to evaluate model performance using receiver operating characteristic (ROC) curves.

Results: During a median follow-up of 13.69 years, 5199 (2.16%) participants developed AMD. After accounting for demographic, lifestyle, multimorbidity, socioeconomic factors, and genetic predispositions to AMD, 42 metabolites were associated with AMD incidence. Very-low-density lipoprotein (VLDL)-related particles, low-density lipoprotein (LDL)-related particles, three additional lipids particles, and albumin were associated with decreased AMD incidence, whereas glucose increased the risk of AMD incidence. Compared to those in the lowest quartile, individuals in the highest quartile of protective metabolite scores exhibited lower risk of AMD incidence (hazard ratio [HR] = 0.869, 95% confidence interval [CI] = 0.803-0.940, false discovery rate [FDR]-adjusted P = 1.44 × 10-3). However, the AMD-associated metabolites did not enhance predictive performance (both areas under the curve [AUC] = 0.776).

Conclusions: Our findings reveal significant associations between specific metabolites and AMD incidence, highlighting the roles of lipoprotein subclasses, cholesterol subtypes, apolipoproteins, glucose, and albumin. Although metabolomics did not improve risk prediction, certain biomarkers may serve as promising therapeutic targets.