ABSTRACT
Functional equilibrium between vaginal microbiota and the host is important for maintaining gynecological and reproductive health. Apart from host genetics, infections, changes in diet, life-style and hygiene status are known to affect this delicate state of equilibrium. More importantly, the gonadal hormones strongly influence the overall structure and function of vaginal microbiota. Several studies have attempted to understand (a) the composition of vaginal microbiota in specific stages of women's reproductive cycle as well as in menopause (b) their association with gonadal hormones, and their potential role in manifestation of specific health conditions (from the perspective of cause/consequence). However, a single study that places, in context, the structural variations of the vaginal microbiome across the entire life-span of women's reproductive cycle and during various stages of menopause is currently lacking. With the objective to obtain a holistic overview of the community dynamics of vaginal micro-environment 'across' various stages of women's reproductive and post-reproductive life-cycle, we have performed a meta-analysis of approximately 1,000 vaginal microbiome samples representing various stages of the reproductive cycle and menopausal states. Objectives of this analysis included (a) understanding temporal changes in vaginal community taxonomic structure and composition as women pass through various reproductive and menopausal stages (b) exploring correlations between the levels of female sex hormones with vaginal microbiome diversity (c) analyzing changes in the pattern of community diversity in cases of dysbiotic conditions such as bacterial vaginosis, and viewing the analyzed changes in the context of a healthy state. Results reveal interesting temporal trends with respect to vaginal microbial community diversity and its pattern of correlation with host physiology. Results indicate significant differences in alpha-diversity and overall vaginal microbial community members in various reproductive and post-reproductive phases. In addition to reinforcing the known influence/role of gonadal hormones in maintaining gynecological health, results indicate how hormonal level perturbations cause/contribute to imbalances in vaginal microbiota. The nature of resulting dysbiotic state and its influence on vaginal health is also analyzed and discussed. Results also suggest that elevated vaginal microbial diversity in pregnancy does not necessarily indicate a state of bacterial infection. The study puts forward a hormone-level driven microbiome diversity hypothesis for explaining temporal patterns in vaginal microbial diversity during various stages of women's reproductive cycle and at menopause.
ABSTRACT
Preterm birth is a leading cause of global neonate mortality. Hospitalization costs associated with preterm deliveries present a huge economic burden. Existing physical/biochemical markers for predicting preterm birth risk are mostly suited for application at mid/late pregnancy stages, thereby leaving very short time (between diagnosis and delivery) for adopting appropriate intervention strategies. Recent studies indicating correlations between pre/full-term delivery and the composition of vaginal microbiota in pregnant women have opened new diagnostic possibilities. In this study, we performed a thorough meta-analysis of vaginal microbiome datasets to evaluate the utility of popular diversity and inequality measures for predicting, at an early stage, the risk of preterm delivery. Results indicate significant differences (in diversity measures) between 'first-trimester' vaginal microbiomes obtained from women with term and preterm outcomes, indicating the potential diagnostic utility of these measures. In this context, we introduce a novel diversity metric that has significantly better diagnostic ability as compared to established diversity measures. The metric enables 'early' and highly accurate prediction of preterm delivery outcomes, and can potentially be deployed in clinical settings for preterm birth risk-assessment. Our findings have potentially far reaching implications in the fight against neonatal deaths due to preterm birth.
