Partial least squares-based gene expression analysis in preeclampsia

Preeclampsia is major cause of maternal and fetal morbidity and mortality. Currently, the etiology of preeclampsia is unclear. In this study, we investigated differences in gene expression between preeclampsia patients and controls using partial least squares-based analysis, which is more suitable than routine analysis. Expression profile data were downloaded from the Gene Expression Omnibus database. A total of 503 genes were found to be differentially expressed, including 248 downregulated genes and 255 overexpressed genes. Network analysis identified 5 hub genes, including UBB, PIK3R1, MAPRE1, VEGFA, and ITGB1. Three of these, PIK3R1, VEGFA, and ITGB1, are known to be associated with preeclampsia or preeclampsia-related biological processes. Our findings shed light on expression signatures of preeclampsia patients that can be used as theoretical support in future therapeutic studies.