Preeclampsia is a hypertensive disorder of pregnancy that can lead to multiorgan complications in the mother and fetus. Our study aims to uncover the underlying mechanisms and hub genes between genomic subgroups of preeclampsia. A total of 180 preeclampsia cases from 4 gene profiles were classified into 3 subgroups. Weighted gene coexpression analysis was performed to uncover the genomic characteristics associated with different clinical features. Functional annotation was executed within the significant modules and hub genes were predicted using Cytoscape software. Subsequently, miRNet analysis was performed to identify potential miRNA-mRNA networks. Three key subgroup-specific modules were identified. Patients in subgroup II were found to develop more severe preeclampsia symptoms. Subgroup II, characterized by classical markers, was considered representative of typical preeclampsia patients. Subgroup I was considered as an early stage of preeclampsia with normal-like gene expression patterns. Moreover, subgroup III was a proinflammatory subgroup, which presented immune-related genomic characteristics. Subsequently, miR-34a-5p and miR-106a-5p were found to be correlated with all 3 significant gene modules. This study revealed the transcriptome classification of preeclampsia cases with unique gene expression patterns. Potential hub genes and miRNAs may facilitate the identification of therapeutic targets for preeclampsia in future.
Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.