Abstract
BACKGROUND: Metabolic disorders have been hypothesized to be associated with female-pattern hair loss. However, ambiguity persists regarding the causality and directionality of the relationship between blood metabolites and female hair loss patterns. METHODS: To evaluate the causal relationship between 1400 blood metabolites and female pattern hair loss, we conducted a bidirectional Mendelian randomization analysis using publicly available summary data from genome-wide association studies. The primary analyses employed the inverse variance weighted method supplemented by the weighted median, MR-Egger, and weighted mode approaches. To control for multiple testing, the false discovery rate method was applied to adjust P values. The leave-one-out method was employed for the sensitivity analysis. Heterogeneity was evaluated using Cochran's Q value, whereas horizontal pleiotropy was assessed using MR-Egger intercept and MR-PRESSO. Additionally, metabolic pathway analysis was performed for the metabolites that demonstrated significant correlations. We further performed colocalization analysis to delve into the underlying causality. RESULTS: After rigorous selection, 23 metabolites and 4 metabolic ratios were associated with female-pattern hair loss. There were no noticeable outliers, horizontal pleiotropy, or heterogeneity. Metabolic pathway analysis identified one significant pathway: fructose/mannose metabolism (P < 0.05). In the reverse analysis, dimethylglycine was identified as overlapping with the forward analysis results, thereby removing it from the final analysis. CONCLUSION: Through integration of genomic and metabolomic data, we identified blood metabolites that may be associated with the development of female pattern hair loss. Our findings provide novel insights into the pathogenic mechanisms of this condition. These findings have significant implications for early diagnosis, preventive measures, and treatment.