Evaluating the causal effects of circulating metabolic biomarkers on Alzheimer's disease

Background: The diagnosis and treatment of Alzheimer's disease (AD) is challenging due to the complexity of its pathogenesis. Although research suggests a link between circulating metabolites and AD, their causal relationship is not fully understood. Methods: Based on publicly available genome-wide association study data, we investigated the causative relationship between AD (7759 cases and 334,740 controls) and 233 traits describing circulating metabolites (136,016 participants) using a two-sample Mendelian randomization (MR) method. We adopted the inverse variance weighted approach as the priority and performed sensitivity analyses with MR-Egger intercept method and Cochran's Q test. Results: The overall causal effect of circulating metabolic traits on AD was significantly higher than the inverse effect (beta: 0.15 ± 0.42 vs. 0.04 ± 0.07; p < 0.05). A total of 72 circulating metabolic traits (odd ratio (OR): 1.16–2.48) had a significant positive causal effect on AD, while a total of 16 circulating metabolic traits with significant negative causal effects on AD were detected (OR: 0.38–0.88). AD had a significant positive causal effect (OR: 1.02–1.17) on 142 circulating metabolic traits and a negative causal effect (OR: 0.87–0.99) on 43 circulating metabolic traits. Circulating metabolites that have a bi-directional causative relationship with AD mainly include apolipoprotein B levels, total cholesterol levels, total triglycerides levels, and omega-6 fatty acids levels. Conclusion: The causative relationship between AD and the circulating metabolic traits is complex and bidirectional. Analyzing metabolites causally involved in the development of AD may provide clues for identifying preventive and therapeutic targets for this disorder.