ArticleFrontiers in immunology2026
Mitochondrial dysfunction and immune microenvironment in gestational diabetes mellitus: insights from bioinformatics analysis and experimental validation.
Article in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Gestational diabetes mellitus (GDM) is a pregnancy-related disorder characterized by inflammatory dysregulation that disrupts maternal-fetal immune homeostasis, yet the contribution of mitochondrial dysfunction to this pro-inflammatory state remains incompletely understood. Methods: This study combined transcriptomic data obtained from the GEO repository and mitochondrial gene lists from MitoCarta3.0 to pinpoint mitochondrial-related genes (Mito-RGs) exhibiting differential expression in GDM. Machine learning algorithms, including the least absolute shrinkage and selection operator (LASSO), random forest (RF), and extreme gradient boosting (XGBoost), were applied to identify hub Mito-RGs. Gene set variation analysis (GSVA) and gene set enrichment analysis (GSEA) were performed to identify enriched pathways in various cell types. A predictive nomogram for GDM was developed based on Mito-RGs scores. Experimental validation was conducted in human placental tissues and a GDM mouse model to confirm hub gene expression. Results: DHRS2, STX17, and TIMM44 were identified as hub Mito-RGs involved in GDM. Scores based on these genes formed the basis of a nomogram with strong predictive performance for GDM. Single-cell RNA sequencing data indicated that GDM placental tissues exhibited higher proportions of epithelial cells, macrophages, and NK cells, alongside a significant reduction in tissue stem cells. Glycolysis and hypoxia-related pathways were enriched in epithelial and stem cells, whereas inflammatory and immune-activation pathways were predominantly enriched in macrophages, indicating pro-inflammatory remodeling of the placental immune microenvironment. Immunohistochemistry confirmed significantly elevated DHRS2 protein levels in placentas from GDM patients and GDM mouse models. Conclusions: These findings emphasize the critical impact of mitochondrial dysfunction on the pro-inflammatory reprogramming of the placental immune microenvironment in GDM, providing potential targets for anti-inflammatory and immunometabolic interventions.
Indexed as
Identifiers
What Socratic 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 Socratic graph.