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

  • 주제(키워드) cervicovaginal fluid , preterm birth , microbiota , metabolite , dysbiosis
  • 주제(기타) Biochemistry & Molecular Biology
  • 설명문(일반) [Ansari, AbuZar; You, Young-Ah; Park, Sunwha; Kim, Soo Min; Kim, Young Ju] Ewha Womans Univ, Coll Med, Dept Obstet & Gynecol, Seoul 07984, South Korea; [Ansari, AbuZar; You, Young-Ah; Park, Sunwha; Kim, Soo Min; Kim, Young Ju] Ewha Womans Univ, Coll Med, Ewha Med Res Inst, Seoul 07984, South Korea; [Lee, Heeyeon; Jung, Youngae; Hwang, Geum-Sook] Korea Basic Sci Inst, Western Seoul Ctr, Integrated Metabol Res Grp, Seoul 03759, South Korea; [Lee, Heeyeon] Ewha Womans Univ, Dept Pharm, Seoul 03760, South Korea; [Jung, Youngae] Ewha Womans Univ, Dept Life Sci, Seoul 03760, South Korea; [Hwang, Geum-Sook] Ewha Womans Univ, Dept Chem & Nano Sci, Seoul 03760, South Korea
  • 등재 SCIE, SCOPUS
  • OA유형 Green Published, gold
  • 발행기관 MDPI
  • 발행년도 2020
  • 총서유형 Journal
  • URI http://www.dcollection.net/handler/ewha/000000174644
  • 본문언어 영어
  • Published As http://dx.doi.org/10.3390/metabo10090349
  • PubMed https://pubmed.ncbi.nlm.nih.gov/32867268

초록/요약

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.

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