Labor prediction based on the expression patterns of multiple genes related to cervical maturation in human term pregnancy.
PROBLEM: This study explored the possibility of evaluating cervical maturation using swabbed cervical cell samples at term pregnancy, and aimed to develop a novel approach to predict labor onset. METHOD OF STUDY: Women with uncomplicated pregnancies (n=117 from 62 women at term pregnancy) were recruited. Messenger RNA expression levels of cervical cells for ten genes were quantified by qPCR. Principal component analysis (PCA) was conducted, and principal components that significantly contributed to the prediction of days to delivery were determined. RESULTS: PCA demonstrated that 76% of the expression information from the ten genes can be represented by three principal components (PC1-3). By the multiple regression analysis, PC2 and Bishop score but not PC1 or PC3 were significant variables in the prediction of days to delivery. CONCLUSION: These findings support the concurrent assessment of multiple gene activities in cervical cells as a promising approach to predict the initiation of labor.
Duke Scholars
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Related Subject Headings
- Transcriptome
- Regression Analysis
- Prognosis
- Pregnancy
- Predictive Value of Tests
- Obstetrics & Reproductive Medicine
- Labor Onset
- Humans
- Gestational Age
- Gene Expression Regulation
Citation
Published In
DOI
EISSN
Publication Date
Volume
Issue
Location
Related Subject Headings
- Transcriptome
- Regression Analysis
- Prognosis
- Pregnancy
- Predictive Value of Tests
- Obstetrics & Reproductive Medicine
- Labor Onset
- Humans
- Gestational Age
- Gene Expression Regulation