Bar Ofri, Vagios Stylianos, Barkai Omer, Elshirbini Joseph, Souter Irene, Xu Jiawu, James Kaitlyn, Bormann Charles, Mitsunami Makiko, Chavarro Jorge E, Foessleitner Philipp, Kwon Douglas S, Yassour Moran, Mitchell Caroline
Department of Obstetrics and Gynecology, Massachusetts General Hospital, Boston, MA, USA.
Department of Microbiology and Molecular Genetics, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
NPJ Biofilms Microbiomes. 2025 Jun 5;11(1):95. doi: 10.1038/s41522-025-00732-8.
Humans are the only species with a commensal Lactobacillus-dominant vaginal microbiota. Reproductive tract microbes have been linked to fertility outcomes, as has intrauterine inflammation, suggesting immune response may mediate adverse outcomes. In this pilot study, we compared vaginal microbiota composition and immune marker concentrations between patients with unexplained or male factor infertility (MFI), as a control. We applied a supervised machine learning algorithm that integrated microbiome and inflammation data to predict pregnancy outcomes.Twenty-eight participants provided vaginal swabs at three IVF cycle time points; 18 achieved pregnancy. Pregnant participants had lower microbial diversity and inflammation. Among them, MFI cases had higher diversity but lower inflammation than those with unexplained infertility. Our model showed the highest prediction accuracy at time point 2 of the IVF cycle. These findings suggest that vaginal microbiota and inflammation jointly impact fertility and can inform predictive tools in reproductive medicine.
人类是唯一拥有以共生乳酸杆菌为主导的阴道微生物群的物种。生殖道微生物与生育结果有关，子宫内炎症也是如此，这表明免疫反应可能介导不良后果。在这项初步研究中，我们比较了不明原因或男性因素不育（MFI）患者（作为对照）之间的阴道微生物群组成和免疫标志物浓度。我们应用了一种监督式机器学习算法，该算法整合了微生物组和炎症数据来预测妊娠结局。28名参与者在三个体外受精周期时间点提供了阴道拭子；18人成功怀孕。怀孕的参与者微生物多样性和炎症水平较低。其中，MFI病例比不明原因不孕的病例具有更高的多样性但更低的炎症水平。我们的模型在体外受精周期的时间点2显示出最高的预测准确性。这些发现表明，阴道微生物群和炎症共同影响生育能力，并可为生殖医学中的预测工具提供信息。
