Causal effects of genetically determined metabolites on androgenetic alopecia: A two‐sample Mendelian randomization analysis

Abstract

AbstractBackgroundAndrogenic alopecia (AGA) is the most common non‐scarring alopecia disorder. Given its increasing incidence and onset during adolescence, AGA significantly impacts both the physical and psychological well‐being of affected individuals. Emerging evidence suggests a pivotal role of metabolites in AGA. This study aims to elucidate the causal relationship between metabolites and AGA using Mendelian randomization (MR) analysis.MethodsWe conducted a two‐sample Mendelian randomization (TSMR) analysis based on a genome‐wide association study (GWAS) to assess the causality of 452 metabolites on AGA. The main approach employed for inferring causal effects was inverse variance weighted (IVW), which was complemented by MR‐Egger regression, weighted median, as well as MR pleiotropy residual sum and outlier (MR‐PRESSO) approaches. Additionally, sensitivity analyses were performed to ensure result robustness. Single nucleotide polymorphisms (SNPs) were selected as instrumental variables (IVs) in GWAS dataset comprising 452 metabolites.ResultsNotably, we identified Scyllo‐inositol and Alpha‐ketoglutarate as the most potent protective factors against AGA, while Heme* and 2‐palmitoylglycerophosphocholine* emerged as significant risk factors for AGA. Furthermore, sensitivity analysis revealed no heterogeneity in these findings.ConclusionsOverall, our research suggests a potential causal link between metabolites and AGA, offering a more comprehensive insight into the pathogenesis of AGA and present additional strategies for prevention and treatment.