Development of a New Biomarker Model for Predicting Preterm Birth in Cervicovaginal Fluid

Ji-Youn Lee1, Sumin Seo1, Bohyun Shin1

  • 1College of Pharmacy, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Korea.

Metabolites
|August 25, 2022
PubMed

Insights

Accurate biomarkers for preterm birth (PTB) are needed. This study identified 19 potential biomarkers, including short-chain fatty acids and amino acids, from vaginal fluid metabolites to predict PTB risk.

Area of Science:

  • Biochemistry
  • Microbiology
  • Clinical Diagnostics

Background:

  • Preterm birth (PTB) poses significant risks to infant survival and family well-being, necessitating improved diagnostic tools.
  • Vaginal microbial community shifts from eubiosis to dysbiosis correlate with altered metabolite profiles, suggesting potential biomarkers.

Purpose of the Study:

  • To identify and validate novel biomarkers for predicting preterm birth (PTB) using metabolite analysis of cervicovaginal fluid (CVF).
  • To develop a predictive model for PTB risk assessment based on microbiota-derived metabolites.

Main Methods:

  • Targeted and non-targeted analysis of short-chain fatty acids (SCFAs) and polar metabolites in 90 clinical CVF samples using gas chromatography/mass spectrometry (GC/MS).
  • Derivatization techniques including MTBSTFA for SCFAs and methoxyamine/BSTFA for polar metabolites.
  • Statistical analysis and detection rate criteria were applied to select biomarkers.

Main Results:

  • Nine SCFAs and 58 polar metabolites were quantified or detected.
  • Nineteen biomarkers were selected, comprising 1 SCFA, 2 organic acids, 4 amine compounds, and 12 amino acids.
  • A predictive model demonstrated suitability for PTB prediction, irrespective of sample collection timing.

Conclusions:

  • The identified biomarkers, derived from microbiota-associated metabolites, show promise for accurate PTB prediction.
  • These findings could lead to valuable diagnostic tools for patients and pre-pregnancy risk assessment.

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