Mendelian randomization study of lipid metabolites reveals causal associations with age-related macular degeneration

Age-related macular degeneration (AMD) is the leading cause of irreversible blindness in the elderly, affecting approximately 8.7 % of individuals over 55 years old. Increasing evidence suggests that lipid metabolism plays a significant role in AMD pathogenesis, yet the causal relationships remain unclear. This study aims to elucidate the causal relationship between lipid metabolites and AMD using Mendelian randomization (MR) methodology.

A two-sample MR analysis was conducted to explore the associations between specific lipid metabolites (such as bile acids, fatty acids, sphingolipids, and steroid hormones) and the incidence of AMD, as well as the potential causal effect of AMD on these lipid metabolites. Genetic variants significantly associated with these lipid metabolites were selected as instrumental variables (IVs). Data for AMD and lipid metabolites were sourced from the IEU GWAS database, covering over 209,000 cases and >16 million single nucleotide polymorphisms (SNPs). The MR analysis employed inverse-variance weighted (IVW), MR-Egger regression, and weighted median methods to estimate causal relationships and address potential pleiotropy and heterogeneity.

IVW analysis revealed significant associations between several lipid metabolites and AMD. Specifically, higher levels of laurate were found to increase the risk of AMD by 3.532 times (OR = 3.532, 95%CI 1.498-8.328, P < 0.010). In contrast, dehydroepiandrosterone sulfate (DHEA-S) (OR = 0.551, 95%CI 0.311-0.977, P = 0.042) and palmitoyl sphingomyelin (OR = 0.213, 95%CI 0.053-0.863, P = 0.030) were protective, with DHEA-S and palmitoyl sphingomyelin levels reducing the risk of AMD by 44.9 % and 78.7 %, respectively. Sensitivity analyses using MR-Egger and weighted median methods supported these findings, highlighting consistent trends across different analytical approaches.

By clarifying these causal relationships, this research aims to provide insights that could inform the development of therapeutic strategies targeting lipid metabolism, ultimately improving outcomes for individuals at risk of AMD.