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.
Highlights
Technological advances in medical diagnostics and therapeutics in the last decade have greatly reduced the burden of several life-threatening diseases affecting young children[1]
Results indicate that women with preterm delivery outcomes tend to have lesser diversity in their vaginal microbiome during their first 15–20 weeks of pregnancy as compared to women with term delivery outcomes
This clearly indicates significant differences between vaginal microbiome samples obtained from women with term or preterm delivery (PTD) outcomes
Summary
Technological advances in medical diagnostics and therapeutics in the last decade have greatly reduced the burden of several life-threatening diseases affecting young children[1]. The success of these intervention approaches is dependent on identification of high-risk subjects as early as possible during pregnancy[3] Given this context, diagnostic markers (physical and/or biochemical) that can accurately indicate, at an early stage of pregnancy, the possibility of progression towards a preterm delivery outcome assume a lot of significance[10,11]. The consistent presence of species belonging to known bacterial pathogens such as Gardenerella, Atopobium, Ureaplasma, etc., (with certain abundance) in samples grouping into a preterm delivery associated CST, has fuelled a lot of research focus in this direction[37] Reports from these efforts indicate subtle differences in alpha-diversity metrics ( with respect to species diversity and evenness measures) between taxonomic profiles obtained from vaginal microbiome samples taken from preterm and full-term subjects[38,40]
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