Causal Relationship between Gut Microbiota and Aneurysm: A Mendelian Randomization Study.

Abstract

Introduction: Observational studies have suggested a possible relationship between gut microbiota (GM) and aneurysm development. However, the nature of this association remains unclear due to the inherent limitations of observational research, such as reverse causation and confounding factors. To address this knowledge deficit, this study aimed to investigate and establish a causal link between GM and aneurysm development.

Methods: Summary statistics regarding GM and aneurysms were collected from relevant genome-wide association studies. Two samples were used in mendelian randomization (MR). The principal MR technique utilized was inverse-variance weighting, a technique renowned for producing reliable causal effect estimations. Additional MR methods, including weighted median (WM), MR-Egger, MR-PRESSO, and simple mode methods, were employed to ensure the robustness of the aforementioned association and investigate potential biases. Sensitivity analyses were performed to determine the consistency of the MR findings.

Results: Varying associations were observed between specific microbial taxa and the different aneurysms analyzed. A negative correlation was observed between aortic aneurysm (AA) and Lentisphaerae, Lentisphaeria, and Victivallales. Conversely, the genus FamilyXIIIUCG001 exhibited an increased risk association. Regarding abdominal AA, Victivallaceae showed a reduced risk, and Bilophila and Catenibacterium were associated with an increased risk. For thoracic AA, negative and positive correlations were observed with Lentisphaerae and Turicibacter, respectively. Lastly, in the case of cerebral aneurysm (CA), Firmicutes and Haemophilus were associated with a decreased risk, and Lachnoclostridium demonstrated an increased risk of association.

Conclusion: Our research has established causal relationships between specific GM components and various aneurysms. The obtained knowledge may aid in the development of microbiome-based interventions and the identification of novel biomarkers for targeted prevention strategies.