ArticleDiabetes, metabolic syndrome and obesity : targets and therapy2025
Identification of Shared Biomarkers in Chronic Kidney Disease and Diabetic Nephropathy Using Single-Cell Sequencing.
Article in Diabetes, metabolic syndrome and obesity : targets and therapy, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Nanohydrogels for Diabetic Wound Healing: Mechanisms, Applications, and Future Perspectives.International journal of nanomedicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chronic kidney disease (CKD) and diabetic nephropathy (DN) represent significant renal health challenges, with overlapping pathogenic mechanisms. This study evaluated shared biomarkers in CKD and DN through single-cell sequencing, aiming to identify potential diagnostic and therapeutic targets and provide new insights into their common pathogenesis. Methods: In this study, single-cell RNA sequencing was performed on nine columns of human blood samples, including three control cases, three CKD cases, and three DN cases. Following sequencing, single-cell analysis was conducted to identify different cell types. Differential expression analysis was then performed to compare the disease samples (CKD and DN) with control samples, resulting in the identification of differentially expressed genes (DEGs). The intersection of DEGs between the disease samples and the control samples was extracted, and a Protein-Protein Interaction (PPI) network was constructed using these intersecting genes, with biomarkers identified through the STRING database. Additionally, Gene Set Enrichment Analysis and GeneMANIA were applied to explore the potential mechanisms underlying these biomarkers. Results: Findings revealed elevated IRF7 expression within dendritic cells (DC), while MX1 showed specifically elevated expression in both DN and CKD samples. MX1 and IRF7 exhibited notable high expression in DC. Four biomarkers were all enriched in the Oxidative Phosphorylation pathway in CKD, and in DN, they were all enriched in the FcγR Mediated Phagocytosis pathway. STAT1 and ISG15 were widely expressed across macrophages, monocytes, NK cells, and NK T cells. In conclusion, the four biomarkers were expressed differently in the disease and control groups of different immune cells. Conclusion: Our study successfully identified MX1, IRF7, STAT1, and ISG15 as shared biomarkers in CKD and DN, revealing their distinct expression patterns and potential roles in disease mechanisms.
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.