Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Uncovering key markers and therapeutic targets for renal fibrosis in diabetic kidney disease through bulk and single-cell RNA sequencing

4 Jul 2025

Abstract excerpt

BACKGROUND: Diabetic kidney disease (DKD) is the major cause of chronic kidney failure, with tubulointerstitial fibrosis playing a crucial role in disease development. Identifying fibrosis-related genes is crucial for improving diagnosis and developing novel therapies due to the necessity for early detection and effective treatments. METHODS: Genes associated with fibrosis were identified by WGCNA, and a...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Chronic Kidney Disease and Diabetes
Share to Ferroptosis and cancer prognosis
Share to Single-cell and spatial transcriptomics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 40615901
DOI: 10.1186/s12967-025-06554-8

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 3 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Uncovering key markers and therapeutic targets for renal fibrosis in diabetic kidney disease through bulk and single-cell RNA sequencingPMID 40615901Read ↗

Identification and validation of immune and cuproptosis - related genes for diabetic nephropathy by WGCNA and machine learningSemantic proximity Read ↗

Characterizing hub biomarkers for post-transplant renal fibrosis and unveiling their immunological functions through RNA sequencing and advanced machine learning techniquesSemantic proximity Read ↗

Identification of diagnostic biomarkers for diabetes nephropathy by multi-chip integrated bioinformatics combining machine-learning strategies and mendelian randomizationSemantic proximity Read ↗

Identification and validation of immune-related biomarkers and potential regulators and therapeutic targets for diabetic kidney diseaseSemantic proximity Read ↗

Novel insights into the disease transcriptome of human diabetic glomeruli and tubulointerstitiumSemantic proximity Read ↗

NET‐Related Gene as Potential Diagnostic Biomarkers for Diabetic Tubulointerstitial InjurySemantic proximity Read ↗

Single-cell RNA and transcriptome sequencing profiles identify immune-associated key genes in the development of diabetic kidney diseaseSemantic proximity Read ↗

ALOX5, a novel diagnostic and prognostic marker associated with immune cells and ferroptosis in diabetic kidney diseaseSemantic proximity Read ↗

Construction of a neural network diagnostic model for renal fibrosis and investigation of immune infiltration characteristicsSemantic proximity Read ↗

Scissor–CIBERSORTx Deconvolution Reveals Functional Heterogeneity of CTAL/aTAL Cells and Associated Biomarkers in Renal FibrosisSemantic proximity Read ↗

CTSS and CD53: Emerging m6A methylation markers in diabetic kidney disease pathogenesis and their clinical implicationsSemantic proximity Read ↗

Identification of immune microenvironment and PANoptosis-related biomarkers in diabetic kidney disease: PSMB8 and PSMB9Semantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.