Abstract
BACKGROUND: Alopecia areata is an autoimmune hair loss disorder with an incompletely understood etiology. Although trace elements, serum metabolites, and inflammatory factors are implicated in the disease, the potential causal relationships between these factors and alopecia areata require further investigation. METHODS: This study employed Mendelian randomization (MR), utilizing data from genome-wide association studies, to explore the causal relationships between 15 trace elements, 1400 serum metabolites, and 91 inflammatory factors and alopecia areata. The analysis was conducted using the inverse variance weighted (IVW) method complemented by various sensitivity analyses, including Cochran's Q test, MR-Egger regression intercept test, MR-PRESSO global test, and leave-one-out analysis, to assess the robustness of the results. RESULTS: MR analysis indicated a negative correlation between copper levels and the risk of developing alopecia areata (odds ratio = 0.86, 95% confidence interval: 0.75-0.99, p = 0.041). Additionally, causal relationships were identified between 15 serum metabolites and 6 inflammatory factors and the risk of alopecia areata (IVW, all p values < 0.05). CONCLUSION: This study provides genetic evidence of the relationships between trace elements, serum metabolites, and alopecia areata, underscoring the potential value of targeted therapeutic strategies and preventive measures. Future research should expand to diverse populations and further explore the specific roles of these biomarkers in the disease mechanism.