Level C· Early human research exploring benefitsCohort StudyEurope PMCOpen access

Identification of Differentially Expressed Genes and Pathways in Non-Diabetic CKD and Diabetic CKD by Integrated Human Transcriptomic Bioinformatics Analysis

Barrios C., Riera M., Rodríguez E., Márquez E., Del Risco J., Pilco M.

Cohort Study on Type 2 Diabetes, Chronic Kidney Disease, Autoimmune Research, published in Int J Mol Sci (2025) — summary generated from the PubMed abstract.

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Level C· Early human research exploring benefitsEvidence level of this study

Early human evidence such as case series or small samples is exploring possible benefits.

  • Level A · Stronger Clinical Evidence
  • Level B · Emerging clinical evidence with positive signals
  • Level C · Early human research exploring benefits
  • Level D · Scientific groundwork from lab and animal studies
  • Emerging · Emerging topic under active research
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This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.

Study type
Cohort Study
Journal
Int J Mol Sci (2025)
Reported sample size
—
Source database
Europe PMC
PMID
40806550
PMCID
PMC12347806
DOI
10.3390/ijms26157421

Abstract (original English)

Chronic kidney disease (CKD) is a heterogeneous condition with various etiologies, including type 2 diabetes mellitus (T2D), hypertension, and autoimmune disorders. Both diabetic CKD (CKD_T2D) and non-diabetic CKD (CKD_nonT2D) share overlapping clinical features, but understanding the molecular mechanisms underlying each subtype and distinguishing diabetic from non-diabetic forms remain poorly defined. To identify differentially expressed genes (DEGs) and enriched biological pathways between CKD_T2D and CKD_nonT2D cohorts, including autoimmune (CKD_nonT2D_AI) and hypertensive (CKD_nonT2D_HT) subtypes, through integrative transcriptomic analysis. Publicly available gene expression datasets from human glomerular and tubulointerstitial kidney tissues were curated and analyzed from GEO and ArrayExpress. Differential expression analysis and Gene Set Enrichment Analysis (GSEA) were conducted to assess cohort-specific molecular signatures. A considerable overlap in DEGs was observed between CKD_T2D and CKD_nonT2D, with CKD_T2D exhibiting more extensive gene expression changes. Hypertensive-CKD shared greater transcriptomic similarity with CKD_T2D than autoimmune-CKD. Key DEGs involved in fibrosis, inflammation, and complement activation-including Tgfb1 , Timp1 , Cxcl6 , and C1qa/B -were differentially regulated in diabetic samples, where GSEA revealed immune pathway enrichment in glom

What this study does not prove

  • • This study does not prove SVF is an approved treatment or a replacement for standard care.

Evidence level

Early human evidence such as case series or small samples is exploring possible benefits.

How we grade evidence
HumansDiabetic NephropathiesDiabetes Mellitus, Type 2Gene Expression ProfilingComputational BiologyGene Expression RegulationRenal Insufficiency, ChronicGene Regulatory NetworksTranscriptome

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