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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.
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.
Abstract:
Preterm birth (PTB) is a social problem that adversely affects not only the survival rate of the fetus, but also the premature babies and families, so there is an urgent need to find accurate biomarkers. We noted that among causes, eubiosis of the vaginal microbial community to dysbiosis leads to changes in metabolite composition. In this study, short chain fatty acids (SCFAs) representing dysbiosis were derivatized using (N-tert-butyldimethylsilyl-N-methyltrifluoroacetamide, MTBSTFA) and targeted analysis was conducted in extracted organic phases of cervicovaginal fluid (CVF). In residual aqueous CVF, polar metabolites produced biochemistry process were derivatized using methoxyamine and N,O-bis(trimethylsilyl)trifluoroacetamide (BSTFA), and non-targeted analysis were conducted. Nine SCFAs were quantified, and 58 polar metabolites were detected in 90 clinical samples using gas chromatography/mass spectrometry (GC/MS). The criteria of statistical analysis and detection rate of clinical sample for development of PTB biomarkers were presented, and 19 biomarkers were selected based on it, consisting of 1 SCFA, 2 organic acids, 4 amine compounds, and 12 amino acids. In addition, the model was evaluated as a suitable indicator for predicting PTB without distinction between sample collection time. We hope that the developed biomarkers based on microbiota-derived metabolites could provide useful diagnostic biomarkers for actual patients and pre-pregnancy.
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