The causal relationship between serum metabolites and the development of infertility: A Mendelian randomization analysis.

Authors

Yinuo Zhang, Sicheng Ma, Tingyu Wang, Jing Hu, Yizhe Gao, Wenlin Yu, Wenbang Liu, Yifei Wang, Chenming Zhang, Zixue Sun

Published in

Medicine. Volume 105. Issue 32. Pages e49674. Aug 07, 2026.

Abstract

Infertility is a complex and sensitive phenomenon experienced by many couples worldwide. Our study investigated the causal effects of 486 serum metabolites on infertility using a Mendelian randomization (MR) approach, providing insights into the etiology of infertility and available treatments. Genetic data for these serum metabolites were obtained from the Metabolomics genome-wide association study server. Infertility data were obtained from the Finnish Genome Project Consortium, version R9. Three different methods were used to explore causal effects in the MR analysis. Heterogeneity was tested using Cochran Q test. Gene fold accumulation between single nucleotide polymorphisms and outcomes was explored using MR-Egger regression and MR-Pleiotropy RESidual Sum and Outlier. We obtained a total of 19 serum metabolites causally associated with male infertility, of which 9 were protective factors and 10 were risk factors. Three serum metabolites consistently showed a strong causal association with male infertility in all MR methods. We also obtained 29 serum metabolites causally associated with female infertility, of which 15 were protective factors and 14 were risk factors. Among all complementary MR methods, 5 serum metabolites showed a strong causal association with female infertility. Cochran Q test showed no heterogeneity. MR-Egger intercept test and MR-Pleiotropy RESidual Sum and Outlier global test showed no cross-sectional pleiotropy. Of the 486 serum metabolites, a total of 19 were found to be causally associated with male infertility. Of these, 1 was identified as a risk factor and 2 as protective factors. 29 metabolites were causally associated with female infertility. Of these, 1 was identified as a risk factor and 4 as protective factors.

PMID:
42566588
Bibliographic data and abstract were imported from PubMed on 08 Aug 2026.

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