Mendelian Randomization Analysis Reveals Iron as a Potential Contributor to Male Infertility.

Abstract

Purpose: This study explores whether certain trace elements are genetically linked to male infertility by using large-scale genetic data and a method called Mendelian randomization (MR), which helps infer causal relationships.

Materials and methods: We obtained genetic data related to trace minerals and iron metabolism from three databases: the IEU Open GWAS, UK Biobank, and FinnGen Biobank. We used standard MR analysis tools to evaluate the relationship between genetic variants associated with trace elements and the risk of male infertility. The main analysis was performed using a statistical approach called the inverse variance-weighted method. Heterogeneity, horizontal pleiotropy, and potential outliers in the MR analysis results were evaluated.

Results: The analysis suggested that higher genetically predicted iron levels may increase the risk of male infertility (odds ratio, 2.917; 95% confidence interval: 1.232-6.911; p=0.015). No similar associations were found for other elements such as copper, selenium, zinc, potassium, magnesium, calcium, ferritin, transferrin saturation, or total iron-binding capacity. The results were consistent across different analyses, with no signs of bias or genetic confounding.

Conclusions: This study provides genetic support for a possible causal role of iron in male infertility. Further research, including clinical and experimental studies, is needed to confirm these findings.