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Labor prediction based on the expression patterns of multiple genes related to cervical maturation in human term pregnancy
Author(s) -
Samejima Taiki,
Nagamatsu Takeshi,
Schust Danny J.,
Iriyama Takayuki,
Sayama Seisuke,
Sonoda Masaki,
Komatsu Atsushi,
Kawana Kei,
Osuga Yutaka,
Fujii Tomoyuki
Publication year - 2017
Publication title -
american journal of reproductive immunology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.071
H-Index - 97
eISSN - 1600-0897
pISSN - 1046-7408
DOI - 10.1111/aji.12711
Subject(s) - pregnancy , principal component analysis , gene , gene expression , andrology , biology , medicine , term (time) , bioinformatics , obstetrics , genetics , computer science , artificial intelligence , physics , quantum mechanics
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.