4.7 Article

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

Journal

SCIENTIFIC REPORTS
Volume 13, Issue 1, Pages -

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41598-023-38624-6

Keywords

-

Ask authors/readers for more resources

Observational studies have found a correlation between gut microbiota composition and infertility, but there is still a lack of concrete proof for the causal relationship. A Mendelian randomization study was conducted, using genetic data from a genome-wide association study meta-analysis, to assess if gut microbiota composition influences the risk of infertility. The study confirmed a causal link between gut microbiota and infertility, and the identification of specific strains through genetic prediction provides valuable insight for early diagnosis, prevention, and treatment of 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 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.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available