Cervicovaginal microbiota and metabolome predict preterm birth risk in an ethnically diverse cohort

Bibliographic Details
Title: Cervicovaginal microbiota and metabolome predict preterm birth risk in an ethnically diverse cohort
Authors: Flavia Flaviani, Natasha L. Hezelgrave, Tokuwa Kanno, Erica M. Prosdocimi, Evonne Chin-Smith, Alexandra E. Ridout, Djuna K. von Maydell, Vikash Mistry, William G. Wade, Andrew H. Shennan, Konstantina Dimitrakopoulou, Paul T. Seed, A. James Mason, Rachel M. Tribe
Source: JCI Insight, Vol 6, Iss 16 (2021)
Publisher Information: American Society for Clinical investigation, 2021.
Publication Year: 2021
Collection: LCC:Medicine
Subject Terms: Microbiology, Reproductive biology, Medicine
More Details: The syndrome of spontaneous preterm birth (sPTB) presents a challenge to mechanistic understanding, effective risk stratification, and clinical management. Individual associations between sPTB, self-reported ethnic ancestry, vaginal microbiota, metabolome, and innate immune response are known but not fully understood, and knowledge has yet to impact clinical practice. Here, we used multi–data type integration and composite statistical models to gain insight into sPTB risk by exploring the cervicovaginal environment of an ethnically heterogenous pregnant population (n = 346 women; n = 60 sPTB < 37 weeks’ gestation, including n = 27 sPTB < 34 weeks). Analysis of cervicovaginal samples (10–15+6 weeks) identified potentially novel interactions between risk of sPTB and microbiota, metabolite, and maternal host defense molecules. Statistical modeling identified a composite of metabolites (leucine, tyrosine, aspartate, lactate, betaine, acetate, and Ca2+) associated with risk of sPTB < 37 weeks (AUC 0.752). A combination of glucose, aspartate, Ca2+, Lactobacillus crispatus, and L. acidophilus relative abundance identified risk of early sPTB < 34 weeks (AUC 0.758), improved by stratification by ethnicity (AUC 0.835). Increased relative abundance of L. acidophilus appeared protective against sPTB < 34 weeks. By using cervicovaginal fluid samples, we demonstrate the potential of multi–data type integration for developing composite models toward understanding the contribution of the vaginal environment to risk of sPTB.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2379-3708
Relation: https://doaj.org/toc/2379-3708
DOI: 10.1172/jci.insight.149257
Access URL: https://doaj.org/article/2cb446a32e994b038f2a02ad6794749e
Accession Number: edsdoj.2cb446a32e994b038f2a02ad6794749e
Database: Directory of Open Access Journals
More Details
ISSN:23793708
DOI:10.1172/jci.insight.149257
Published in:JCI Insight
Language:English