Network-Based Analysis Reveals Novel Biomarkers in Peripheral Blood of Patients With Preeclampsia

Abstract

WGCNA is a potent systems biology approach that explains the connection of gene expression based on a microarray database, which facilitates the discovery of disease therapy targets or potential biomarkers. Preeclampsia is a kind of pregnancy-induced hypertension caused by complex factors. The disease’s pathophysiology, however, remains unknown. The focus of this research is to utilize WGCNA to identify susceptible modules and genes in the peripheral blood of preeclampsia patients. Obtain the whole gene expression data of GSE48424 preeclampsia patients and normal pregnant women from NCBI’s GEO database. WGCNA is used to construct a gene co-expression network by calculating correlation coefficients between modules and phenotypic traits, screening important modules, and filtering central genes. To identify hub genes, we performed functional enrichment analysis, pathway analysis, and protein-protein interaction (PPI) network construction on key genes in critical modules. Then, the genetic data file GSE149437 and clinical peripheral blood samples were used as a validation cohort to determine the diagnostic value of these key genes. Nine gene co-expression modules were constructed through WGCNA analysis. Among them, the blue module is significantly related to preeclampsia and is related to its clinical severity. Thirty genes have been discovered by using the intersection of the genes in the blue module and the DEGs genes as the hub genes. It was found that HDC, MS4A2, and SLC18A2 scored higher in the PPI network and were identified as hub genes. These three genes were also differentially expressed in peripheral blood validation samples. Based on the above three genes, we established the prediction model of peripheral blood markers of preeclampsia and drew the nomogram and calibration curve. The ROC curves were used in the training cohort GSE48424 and the validation cohort GSE149437 to verify the predictive value of the above model. Finally, it was confirmed in the collected clinical peripheral blood samples that MS4A2 was differentially expressed in the peripheral blood of early-onset and late-onset preeclampsia, which is of great significance. This study provides a new biomarker and prediction model for preeclampsia.

Adverse outcomes of preeclampsia: From mother to baby, pregnancy to postpartum

“…One article reported that adrenomedullin (ADM) mRNA significantly decreased in maternal circulation up to 10-12 weeks before term PE Frontiers in Physiology frontiersin.org onset (Whigham et al, 2019). Another study validated several genes in a test cohort based on bioinformatic analysis of GEO databases and identified three genes (HDC, MS4A2, SLC18A2) differentially expressed in late-onset PE (Lin et al, 2022). A few microRNA studies were performed to identify candidate biomarkers associated with late-onset PE and term PE (Winger et al, 2015;Mavreli et al, 2020;Whigham et al, 2020).…”

Potential biomarkers for late-onset and term preeclampsia: A scoping review

“…One article reported that adrenomedullin (ADM) mRNA significantly decreased in maternal circulation up to 10-12 weeks before term PE Frontiers in Physiology frontiersin.org onset (Whigham et al, 2019). Another study validated several genes in a test cohort based on bioinformatic analysis of GEO databases and identified three genes (HDC, MS4A2, SLC18A2) differentially expressed in late-onset PE (Lin et al, 2022). A few microRNA studies were performed to identify candidate biomarkers associated with late-onset PE and term PE (Winger et al, 2015;Mavreli et al, 2020;Whigham et al, 2020).…”

Pathophysiological impact of CXC and CX3CL1 chemokines in preeclampsia and gestational diabetes mellitus

“…A recent bioinformatic study found that the hub gene (most closely associated with disease) CXCL6 functions as a PE biomarker and prediction model in patients ( Lin et al, 2022 ). MicroRNA (MiR-101) was shown to be considerably reduced in PE placentas and was found to be involved in the regulation of several apoptotic proteins under endoplasmic reticulum stress ( Zou et al, 2014 ).…”