Servikal Mikrobiyota Disbiyozu, Servikal Yetersizliğin Bir Sürücüsüdür

Özet (abstract)

Cervical incompetence (CIC) represents a significant cause of preterm birth globally. Clinical symptoms of CIC are typically delayed until mid-to-late pregnancy, thereby imposing challenges in CIC diagnosis. There is evidence that the microbiota contributes pivotal roles in reproductive health. By comparing the microbial structure and assembly between 30 CIC patients and 30 healthy controls, we found a close correlation between endocervical microbiota dysbiosis and CIC pathogenesis. The CIC group exhibited increased ɑ-diversity and significant alterations in microbial community composition, characterized by decreased relative abundances of Actinobacteria and Firmicutes. Functional characterization revealed a broad reduction in microbial metabolic potential in patients with CIC. NetShift network analysis identified 22 pivotal driver taxa, including Lactobacillus and Gardnerella species that triggered the progression to dysbiosis. Notably, a machine learning diagnostic model achieved 83.3% accuracy in clinical diagnosis based on the abundances of 10 biomarkers. These findings provide critical insights into microbial-mediated regulation of the cervical microenvironment by elucidating how specific microbial members and their metabolic potentials contribute to CIC pathogenesis. The diagnosis model offers a new paradigm for diagnosis using microbial biomarkers and reveals potential therapeutic targets via the intervention of driver taxa, thereby establishing innovative strategies to improve pregnancy outcomes.

Yazarların özeti; kaynağından alınmıştır. Microorganisms, 2026 · DOI ↗