ObjectiveTo investigate whether there is a causal relationship between reproductive history (number of children, age at first birth) and the risk of hormone-related cancers (breast, endometrial, and ovarian) in women. MethodsUnivariate and multivariate Mendelian randomization (MR) methods were used to investigate the causal effects of the number of children (childlessness in infertile women and number of children ever born in fertile women) and age at first birth on three hormone-related cancers. The inverse variance weighting method was used for the primary analysis, and sensitivity analyses and reliability tests were used to ensure the reliability of the results. ResultsUnivariate MR showed that infertile women had a higher risk of breast cancer compared with fertile women (OR=1.07, 95%CI 1.05 to 1.09, P<0.001). Multivariate MR showed that among fertile women, after accounting for the effect of age at first birth, higher number of children ever born may be associated with lower risk of breast cancer (OR=0.61, 95%CI 0.43 to 0.85, P<0.01). Neither univariate nor multivariate MR found a causal relationship between age at first birth and hormone-related cancers, and no causal relationship was found between the number of children ever born and endometrial and ovarian cancers; sensitivity analyses and reliability tests demonstrated that the results were unlikely to be affected by heterogeneity and horizontal pleiotropy. ConclusionThe more children a normal woman has, the lower her risk of breast cancer. Infertile women face a higher risk of breast cancer.
Objective To explore the causal relationship between gut microbiota and urinary tract infections using data from genome-wide association studies. Methods The gut microbiota data were sourced from the MiBioGen consortium, comprising genetic variables from 18 340 individuals. UTI data (ieu-b-5.65) were derived from the UK Biobank. Six methods including inverse variance weighted (IVW), Mendelian randomization (MR)-Egger, maximum likelihood, simple mode, weighted mode, and weighted median were employed for two-sample MR analysis on these datasets. Additionally, MR-PRESSO was used to detect and correct for heterogeneity and outliers in the analysis. Cochran's Q test and leave-one-out analysis were applied to assess potential heterogeneity and multiple effects. Furthermore, reverse MR analysis was conducted to investigate causal relationships between UTI and gut microbiota. Results According to IVW method analysis results, bacterial genera Eggerthella (OR=1.08, 95%CI 1.01 to 1.16, P=0.034) and Ruminococcaceae (UCG005) (OR=1.10, 95%CI 1.01 to 1.20, P=0.022) were found to increase the risk of UTI, while Defluviitaleaceae (UCG011) (OR=0.90, 95%CI 0.82 to 0.99, P=0.022) appeared to decrease it. Reverse MR analysis did not reveal a significant effect of UTI on these three bacterial genera. Our study found no evidence of heterogeneity or pleiotropy based on the results of Cochran’s Q test, MR-Egger, and MR-PRESSO global test. Conclusion In this MR study, we demonstrate a causal association between Eggerthella, Ruminococcaceae, Defluvitalaceae and the risk of urinary tract infections.