Bioinformatic Analysis of Apoptosis-Related Genes in Preeclampsia Using Public Transcriptomic and Single-Cell RNA Sequencing Datasets

Lingyan Liu,1– 3,* Xiuling Li,2,3,* Hongfen Yang,2,3 Fei Xu,3,4 Xudong Dong2,3 1Faculty of Life Science and Technology, Kunming University of Science and Technology, Kunming, 650500, People’s Republic of China; 2Department of Obstetrics, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, 650500, People’s Republic of China; 3Medical School, Kunming University of Science and Technology, Kunming, 650500, People’s Republic of China; 4Department of Pain Management, The First People’s Hospital of Yunnan Province, The Affiliated Hospital of Kunming University of Science and Technology, Kunming, 650500, People’s Republic of China*These authors contributed equally to this workCorrespondence: Fei Xu, The First People’s Hospital of Yunnan Province, No. 157 Jinbi Road, Xishan District, Kunming, 650500, People’s Republic of China, Tel +861871-63638625, Email [email protected] Xudong Dong, The First People’s Hospital of Yunnan Province, No. 157 Jinbi Road, Xishan District, Kunming, 650500, People’s Republic of China, Tel +861871-63638625, Email [email protected]: Apoptosis, which is crucial in preeclampsia (PE), affects trophoblast survival and placental function. We used transcriptomics and single-cell RNA sequencing (scRNA-seq) to explore apoptosis-related genes (ARGs) and their cellular mechanisms as potential PE biomarkers.Patients and Methods: All the data included in this study were sourced from public databases. We used scRNA-seq and differential expression analysis, combined with five algorithms from the CytoHubba plugin, to identify ARGs as PE biomarkers. These were integrated into diagnostic nomograms. Mechanistic studies involved enrichment analysis and immune profiling. Biomarker expression was examined at the single-cell level, and verified in clinical samples by RT-qPCR.Results: Cluster of Differentiation 44 (CD44), Macrophage migration inhibitory factor (MIF), PIK3R1, and Toll-like receptor 4 (TLR4) were identified as PE biomarkers. CD44 and TLR4 were down-regulated, while MIF and PIK3R1 were up-regulated. When integrated into the diagnostic nomogram, they showed clinical utility and affected cell functions. In the immune profile of PE, monocytes decreased, resting NK cells increased, and the activities of APC, checkpoint, T-cell co-stimulation, and MHC class I pathways reduced. ScRNA-seq identified 11 cell types, 10 of which were significantly different. Endothelial cell communication with other cell types decreased, while the interaction between common myeloid progenitors (CMP) and villous cytotrophoblasts (VCT) enhanced. The expression levels of CD44, MIF, and PIK3R1 in VCT were significantly different and key to PE. Their decrease in early PE and increase in late PE reflected the placenta’s adaptation to adverse pregnancy conditions.Conclusion: Four ARGs, CD44, MIF, PIK3R1, and TLR4, identified through comprehensive analyses, served as significant biomarkers for PE and offered insights into PE’s cellular mechanisms of PE, providing valuable references for further research. Keywords: preeclampsia, apoptosis, biomarkers, single-cell RNA sequencing, villous cytotrophoblast cells