Preeclampsia is a grave pregnancy-specific disorder that lacks efficacious biomarkers and treatment modalities. Pyroptosis was reported to be involved in preeclampsia. The objective of this study is to identify the signature of pyroptosis-related gene diagnosis and immune microenvironment in preeclampsia. We identified the differentially expressed genes (DEGs) by analyzing the whole blood gene expression profiles of preeclampsia and healthy control group from the Gene Expression Omnibus (GEO) database. The intersection of DEGs and those related to pyroptosis yielded a set of pyroptosis-related DEGs (PRDEGs). Subsequently, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis and the development of a preeclampsia diagnostic model were conducted. Based on the diagnostic markers retained in the developed diagnostic model, hub genes were identified by protein–protein interaction (PPI) network. These hub genes were utilized to conduct immune cell infiltration analysis and construct molecular subtypes of preeclampsia. By analyzing the whole blood single cell sequencing data from the GEO database, we identified functional activity disparities of characteristic gene sets composed of hub genes between preeclampsia and healthy control. A total of seven PRDEGs were acquired, with four of them, namely NLRP7, TSLP, CHI3L1, and NCR1, exhibiting significant correlation with preeclampsia diagnosis. GO and KEGG aIdentify PRDEGs based on integratednalyses indicated that PRDEGs were significantly enriched in pathways associated with positive regulation of interleukin-10 production, positive regulation of interleukin-8 production and nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway. The immune infiltration analysis showed that the infiltration level of CD4 naïve T cells in healthy individuals was significantly elevated. Clustering based on hub genes expression identified two distinct preeclampsia subtypes with different immune characteristics, emphasising the heterogeneity of the disease. The results of single-cell analysis categorized 80,404 cells into nine distinct clusters. We observed significant variations in immune cell distribution, with monocytes being more prevalent in healthy controls and an increased quantity of Central memory CD4+ T cells in preeclampsia patients, suggesting immune activation. Each cell cluster exhibited unique markers, and diagnostic marker NCR1 was specifically expressed in natural killer cells. This study has identified seven potential PRDEGs, four of which exhibit diagnostic accuracy for preeclampsia. Furthermore, our findings underscored the complexity of the immune landscape in preeclampsia, revealing that the activation of immune cells could play a crucial role in the disease's progression.
Zhang et al. (Mon,) studied this question.