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A two-sample mendelian randomization analysis investigates associations between gut microbiota and infertility

Observational studies have provided evidence of a correlation between alterations in gut microbiota composition and infertility. However, concrete proof supporting the causal relationship is still lacking. We performed a Mendelian randomization study to assess whether genetically gut microbiota comp...

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Detalles Bibliográficos
Autores principales: Li, Taozhi, Shao, Wenbo, Wang, Yukun, Zhou, Rui, Yun, Zhangjun, He, Yalin, Wu, Yu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10349861/
https://www.ncbi.nlm.nih.gov/pubmed/37454180
http://dx.doi.org/10.1038/s41598-023-38624-6
Descripción
Sumario:Observational studies have provided evidence of a correlation between alterations in gut microbiota composition and infertility. However, concrete proof supporting the causal relationship is still lacking. We performed a Mendelian randomization study to assess whether genetically gut microbiota composition influences the risk of infertility. The genetic data pertaining to gut microbiota were obtained from a genome-wide association study meta-analysis, which was conducted among 24 cohorts (18,340 participants) from the international MiBioGen consortium. By the primary method of assessing causality, we have identified 2 family taxa, 2 genus taxa, and 1 order taxa that were linked to a low risk of male infertility, while 1 genus taxa were associated with a high risk of male infertility. Furthermore, we have discovered 6 genus taxa, 1 phylum taxa, 1 class taxa, 1 order taxa, and 1 family taxa that were associated with a low risk of female infertility, while 1 genus taxa were linked to a high risk of female infertility. This study successfully confirmed that there was a causal link between gut microbiota and infertility. The identification of these specific strains through genetic prediction offers a valuable insight for early diagnosis, prevention, and treatment of infertility.