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 ( PC 1‐3). By the multiple regression analysis, PC 2 and Bishop score but not PC 1 or PC 3 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.