A Weighted Gene Co-Expression Network Analysis for Identifying Hub Genes in Preeclampsia-Induced Intrauterine Growth Restriction

Abstract

Aim: Preeclampsia (PE) and intrauterine growth restriction (IUGR) are two significant obstetrical diseases that cause serious harm to maternal and infant health. Worldwide, PE is the most frequent cause of IUGR;The latter is regarded as a serious complication of PE but its underlying mechanism and molecular biological changes are poorly understood. Thus, few effective medical therapies for its treatment are available. PE and IUGR share the same etiological background but their connections at the molecular level were rarely known. Consequently, it is of urgency to create an effective method to evaluate their molecular signature. The objective of this study was to identify the hub genes related to PE with IUGR (PE-IUGR) by conducting a weighted gene co-expression network analysis (WGCNA). Methods: The GSE147776 data set containing 28 samples of placental tissue (n = 6 with PE-IUGR) was downloaded from the Gene Expression Omnibus database. The gene expression profile was correlated with phenotypic data and analyzed using a WGCNA. Additionally, a WGCNA was used to construct a gene co-expression network, and hub genes were further identified by identifying modules related to the clinical traits of PE-IUGR. Results: Nine genes, i.e., TDRKH, XPOT, AMACR, NBN, ALS2, CLYBL, CENPQ, PCGF6 and COQ3 were obtained by the WGCNA. These were considered the key genes that were likely involved in IUGR in PE. Conclusions: We constructed a co-expression network of PE-IUGR and identified 9 hub genes related to the condition.