Predicting the Risk of Preterm Birth Throughout Pregnancy Based on a Novel Transcriptomic Signature.

Objective: This study focused on the prediction of preterm birth (PTB). It aimed to identify the transcriptomic signature essential for the occurrence of PTB and evaluate its predictive value in early, mid, and late pregnancy and in women with threatened preterm labor (TPTL). Methods: Blood transcriptome data of pregnant women were obtained from the Gene Expression Omnibus database. The activity of biological signatures was assessed using gene set enrichment analysis and single-sample gene set enrichment analysis. The correlation among molecules in the interleukin 6 (IL6) signature and between IL6 signaling activity and the gestational week of delivery and latent period were evaluated by Pearson correlation analysis. The effects of molecules associated with the IL6 signature were fitted using logistic regression analysis; the predictive value of both the IL6 signature and IL6 alone were evaluated using receiver operating characteristic curves and pregnancy maintenance probability was assessed using Kaplan-Meier analysis. Differential analysis was performed using the DEseq2 and limma algorithms. Results: Circulatory IL6 signaling activity increased significantly in cases with preterm labor than in those with term pregnancies (normalized enrichment score (NES) = 1.857, Conclusion: Our findings suggest that the IL6 signature may predict PTB, even in early pregnancy (although the predictive power is relatively weak in mid pregnancy) and is particularly effective in symptomatic women. These findings may contribute to the development of an effective predictive and monitoring system for PTB, thereby reducing maternal and fetal risk.