Gene Expression Network Analysis Identifies Potential Targets for Prevention of Preeclampsia

Abstract

Objective Preeclampsia (PE) is a pregnancy-specific multisystem disease as well as an important cause of maternal and perinatal death. This study aimed to analyze the placental transcriptional data and clinical information of PE patients available in the published database and predict the target genes for prevention of PE. Methods The clinical information and corresponding RNA data of PE patients were downloaded from the GEO database. Cluster analysis was performed to examine the correlation between different genotyping genes and clinical manifestations. Then, bioinformatic approaches including GO, KEGG, WGCNA, and GSEA were employed to functionally characterize candidate target genes involved in pathogenesis of PE. Results Two PE datasets GSE60438 and GSE75010 were obtained and combined, thereby providing the data of 205 samples in total (100 non-PE and 105 PE samples). After eliminating the batch effect, we grouped and analyzed the integrated data, and further performed GSEA analysis. It was found that the genes in group 1 and group 2 were different from those in normal samples. Moreover, WGCNA analysis revealed that genes in group 1 were up-regulated in turquoise module, including SASH1 , PIK3CB and FLT-1 , while genes in group 2 were up-regulated in the blue and brown modules. We further conducted GO and KEGG pathway enrichment analyses and found that the differential genes in turquoise module were mainly involved in biological processes such as small molecular catabolic process, while being highly enriched in pathways, including MAPK signaling pathway and Rap1 signaling pathway. Conclusion FLT-1 was conventionally used to predict PE risk, and sFLT-1 could also be used as an indicator to evaluate PE treatment effect. As a candidate biomarker for predicting PE, SASH1 may participate in proliferation, migration, invasion and epithelial mesenchymal transformation of human trophoblast cells by regulating MAPK pathway and Rap1 signaling pathway, thus affecting the progression of PE. The mechanism allowing PIK3CB to regulate PE development was not clear, while the gene could be another candidate biomarker for PE risk prediction. This is an exploratory study and our findings were still required verification in further studies.

Transcriptomics-Based Subphenotyping of the Human Placenta Enabled by Weighted Correlation Network Analysis in Early-Onset Preeclampsia With and Without Fetal Growth Restriction

“…Strengths of the present study include the availability of rich clinical phenotyping data for trait correlation analysis, integration with data from other studies to assess reproducibility, the separate consideration of VT and DB samples, and the use of gestational age-matched preterm controls in additional to term controls. The application of WGCNA as means for gene and preeclampsia sample classification has garnered increased research focus [31][32][33] , and it will be of interest to see how this approach may be further used for molecular subphenotyping of this syndrome in the near future.…”

MicroRNAs: key regulators of the trophoblast function in pregnancy disorders

“…Among them, the JNK/p38MAPK pathway is mainly related to inflammation and cell apoptosis, while the ERK pathway is related to cell invasion, proliferation, migration, and differentiation. Studies have discovered that MAPK pathway plays an important role in regulating the biological function of trophoblasts [ 159 ], especially in trophoblast cell migration and invasion [ 160 ]. Recently, accumulating studies suggest that fibroblast growth factors (FGFs) have many physiological functions.…”