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Identification of Potential Biomarkers in the Cervicovaginal Fluid by Metabolic Profiling for Preterm Birth

Title
Identification of Potential Biomarkers in the Cervicovaginal Fluid by Metabolic Profiling for Preterm Birth
Authors
Ansari, AbuZarLee, HeeyeonYou, Young-AhJung, YoungaePark, SunwhaKim, Soo MinHwang, Geum-SookKim, Young Ju
Ewha Authors
김영주유영아황금숙
SCOPUS Author ID
김영주scopus; 유영아scopus; 황금숙scopus
Issue Date
2020
Journal Title
METABOLITES
ISSN
2218-1989JCR Link
Citation
METABOLITES vol. 10, no. 9
Keywords
cervicovaginal fluidpreterm birthmicrobiotametabolitedysbiosis
Publisher
MDPI
Indexed
SCIE; SCOPUS WOS
Document Type
Article
Abstract
During pregnancy, dysbiosis in the vaginal microbiota directly affects the metabolic profiles, which might impact preterm birth (PTB). In this study, we performed cervicovaginal fluid (CVF) metabolic profiling using nuclear magnetic resonance (NMR) spectroscopy and identified the metabolic markers for predicting PTB. In this nested case-control study, 43 South Korean pregnant women with PTB (n = 22), and term birth (TB; n = 21) were enrolled with their demographic profiles, and CVF samples were collected by vaginal swabs. The PTB group had two subgroups based on post-CVF sampling birth: PTB less than (PTB < 7 d) and more than 7 days (PTB >= 7 d). We observed significant differences in the gestational age at birth (GAB), cervical length (CL), and neonatal birth weight among the groups. The principal component analysis (PCA), and partial least square discriminant analysis (PLS-DA) scatter plot showed the separation between the PTB < 7 d group, and the TB group. Out of 28 identified metabolites, acetone, ethanol, ethylene glycol, formate, glycolate, isopropanol, methanol, and trimethylamine N-oxide (TMAO) were significantly increased in the PTB group compared with the TB group. The ROC curve analysis revealed that the acetone, ethylene glycol, formate, glycolate, isopropanol, methanol, and TMAO had the best predictive values for PTB. Additionally, the correlation analysis of these metabolites showed a strong negative correlation with GAB and CL. These metabolites could be beneficial markers for the clinical application of PTB prediction.
DOI
10.3390/metabo10090349
Appears in Collections:
의과대학 > 의학과 > Journal papers
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