RESUMO
Background: Late-onset Alzheimer's disease (LOAD) represents a growing health burden. Previous studies suggest that blood metabolite levels influence risk of LOAD. Objective: We used a genetics-based study design which may overcome limitations of other epidemiological studies to assess the influence of metabolite levels on LOAD risk. Methods: We applied Mendelian randomization (MR) to evaluate bi-directional causal effects using summary statistics from the largest genome-wide association studies (GWAS) of 249 blood metabolites (nâ=â115,082) and GWAS of LOAD (ncaseâ=â21,982, ncontrolâ=â41,944). Results: MR analysis of metabolites as exposures revealed a negative association of genetically-predicted glutamine levels with LOAD (Odds Ratio (OR)â=â0.83, 95% CIâ=â0.73, 0.92) that was consistent in multiple sensitivity analyses. We also identified a positive association of genetically-predicted free cholesterol levels in small LDL (ORâ=â1.79, 95% CIâ=â1.36, 2.22) on LOAD. Using genetically-predicted LOAD as the exposure, we identified associations with phospholipids to total lipids ratio in large LDL (ORâ=â0.96, 95% CIâ=â0.94, 0.98), but not with glutamine, suggesting that the relationship between glutamine and LOAD is unidirectional. Conclusions: Our findings support previous evidence that higher circulating levels of glutamine may be a target for protection against LOAD.