Preeclampsia (PE) is a complex, hypertensive disorder of pregnancy. In the past, many studies have tried to find robust biomarkers and effective treatments for PE.Design and Method:
Seven gene expression profiles (GSE10588, GSE25906, GSE30186, GSE35574, GSE43942, GSE44711 and GSE60438) related to human preeclampsia from the Gene Expression Omnibus (GEO) database, were included in our analysis. After pre-processing and batch effects removal of the data, we built two final datasets, control profile and case profile, encompassing 189 normotensive placentas and 138 PE samples, respectively. Using weighted gene co-expression network analysis (WGCNA), we identified modules of co-expressed genes distinguishing normal placentas from PE conditions. Pathway analysis of these modules was carried out to highlight pathways that may be involved in the development of PE.Results:
Using WGCNA, we identified six lowly preserved modules between normal placentas and PE conditions. These modules are mainly related to MAPK signaling pathway, VEGF signaling pathway, Jak-STAT signaling pathway, Tight junction, Gap junction, focal adhesion, Regulation of actin cytoskeleton, Fatty acid elongation in mitochondria, Aminoacyl-tRNA biosynthesis, Cell cycle and Spliceosome.Conclusions:
Using this pool and systems biology approach, we identified several gene modules which may play roles in the PE conditions.