ArticleJournal of inflammation research2025
Bioinformatic Analysis of Apoptosis-Related Genes in Preeclampsia Using Public Transcriptomic and Single-Cell RNA Sequencing Datasets.
Article in Journal of inflammation research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- The recent advancements of single-cell RNA sequencing in pre-eclampsia.Frontiers in medicine · 2026Review
- Complement as a driver of immune-vascular heterogeneity across preeclampsia subtypes: toward a precision medicine framework.Frontiers in immunology · 2026Review
- Exploring histone acetylation in ischemic stroke: CREBBP and CKAP4 as candidate biomarkers linked to histone acetylation networks.Frontiers in pharmacology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.