Transcriptomic analysis of fetal membranes reveals pathways involved in preterm birth

Abstract

AbstractPreterm birth (PTB), defined as infant delivery before 37 weeks of completed gestation, results of the interaction of both genetic and environmental components and constitutes a complex multifactorial syndrome. Transcriptome analysis of PTB has proved challenging because of the multiple causes of PTB and the numerous maternal and fetal gestational tissues that must interact to facilitate parturition. A common pathway of labor and PTB may be the activation of fetal membranes. In this work, chorioamnion membranes from severe preterm and term fetus were analyzed using RNA sequencing. A total of 270 genes were differentially expressed (DE): 252 were up-regulated and 18 were down-regulated in the severe preterm compared to the term births. We found great gene expression homogeneity in the control samples, and not in severe preterm samples. In this work, we identified up-regulated pathways that were previously suggested as leading to PTB like immunological and inflammatory paths. New pathways that were not identified in preterm like the hemopoietic path appeared up-regulated in preterm membranes. A group of 18 down-regulated genes discriminates between term and severe preterm cases. These genes potentially characterize a severe preterm transcriptome pattern and therefore are candidate genes for understanding the syndrome. Some of the down-regulated genes are involved in the nervous system, morphogenesis (WNT-1, DLX5, PAPPA2) and ion channel complexes (KCNJ16, KCNB1), making them good candidates as biomarkers of PTB.The identification of this DE gene pattern may help to develop a multi-gene disease classifier. These markers were generated in an admixtured South American population where PTB has a high incidence. Since genetic background may impact differentially in different populations it is mandatory to include populations like South American and African ones that are usually excluded from high throughput approaches. These classifiers should be compared to those in other populations to get a global landscape of PTB.