The Mediating Role of Immune Cells in the Genetically Predicted Relationship between Gut Microbiota and Puerperal Sepsis: A Mendelian Randomization Study.

INTRODUCTION

The causal relationship between gut microbiota and puerperal sepsis (PS) remains unclear, and there is a lack of in-depth research regarding the potential mediating role of immune cells in this context.

OBJECTIVE

This study aims to investigate the causal relationship between gut microbiota and PS using Mendelian randomization (MR) analysis and to assess the mediating effects of immune cells on the risk of PS onset through mediation analysis.

MATERIALS AND

METHODS

We selected data from large-scale genome-wide association studies (GWAS) involving 473 gut microbiota species, 731 immune cell phenotypes, and PS datasets. Univariate MR (UVMR) analysis was employed to explore the causal relationship between gut microbiota and PS, with the primary statistical method being inverse variance weighting (IVW). Multiple statistical models were applied for sensitivity analysis to minimize the confounding effects of horizontal pleiotropy and heterogeneity. Subsequently, a two-step mediation MR analysis was conducted to evaluate whether immune cells mediate the relationship between gut microbiota and PS.

RESULTS AND DISCUSSION: Analysis using various statistical models indicated that 11 gut microbiota species (e.g., Azorhizobium, Bacillus velezensis, CAG-245 sp000435175, Lentimicrobiaceae, and Providencia) exhibited a causal relationship with PS. Further reverse causal analysis between PS and gut microbiota ruled out the possibility of reverse causality. The two-step mediation MR analysis demonstrated that the percentage of IgD-CD27- B cells (10.26%) and CD62L- monocytes (17.29%) partially mediated the effect of CAG-245 sp000435175 on PS risk.

CONCLUSION

This study provides evidence of a causal relationship between the abundance of certain gut microbiota species and PS, while also revealing a potential mediating role of immune cells. These findings offer valuable theoretical insights into personalized treatment strategies and the development of novel diagnostic biomarkers for PS.