Background: Recent studies had provided evidence that the gut microbiota is associated with sepsis. However, the potential causal relationship remained unclear.
Methods: The present study aimed to explore the causal effects between gut microbiota and sepsis by performing Mendelian randomization (MR) analysis utilizing publicly accessible genome-wide association study (GWAS) summary-level data. Gut microbiota GWAS (N = 18,340) were obtained from the MiBioGen study and GWAS-summary-level data for sepsis were gained from the UK Biobank (sepsis, 10,154 cases; 452,764 controls). Two strategies were used to select genetic variants, i.e., single nucleotide polymorphisms (SNPs) below the locus-wide significance level (1 × 10-5) and the genome-wide statistical significance threshold (5 × 10-8) were chosen as instrumental variables (IVs). The inverse variance weighted (IVW) was used as the primary method for MR study, supplemented by a series of other methods. Additionally, a set of sensitivity analysis methods, including the MR-Egger intercept test, Mendelian randomized polymorphism residual and outlier (MR-PRESSO) test, Cochran's Q test, and leave-one-out test, were carried out to assess the robustness of our findings.
Results: Our study suggested that increased abundance of Deltaproteobacteria, Desulfovibrionales, Catenibacterium, and Hungatella were negatively associated with sepsis risk, while Clostridiaceae1, Alloprevotella, LachnospiraceaeND3007group, and Terrisporobacter were positively correlated with the risk of sepsis. Sensitivity analysis revealed no evidence of heterogeneity and pleiotropy.
Conclusion: This study firstly found suggestive evidence of beneficial or detrimental causal associations of gut microbiota on sepsis risk by applying MR approach, which may provide valuable insights into the pathogenesis of microbiota-mediated sepsis and strategies for sepsis prevention and treatment.
Keywords: Mendelian randomization; causal inference; genetics; gut microbiota; sepsis.
Copyright © 2023 Chen, Zeng, Zhao, Tang, Lei, Wan, Deng and Liu.