Authors
Xu Li, Huan Hong, Hong Li, Zhenhua Fang, Jie Wang, Xiuli Wang, Xinting Sui, Halinuer Shadekejiang, Mingzhu Liang, Xinyu Gan, Jiaming Liu, Chen Lu
Published in
Journal of inflammation research. Volume 19. Pages 603085. Epub Aug 10, 2026.
Abstract
Diabetic kidney disease (DKD) is one of the primary factors leading to end-stage renal disease. Ferroptosis, as a mechanism-related form of programmed cell death, has garnered increasing attention in DKD research. This study aimed to identify and validate ferroptosis-related diagnostic biomarkers for DKD.
Public DKD transcriptomic datasets were analyzed using differential expression analysis, WGCNA, and multiple machine-learning algorithms to identify key ferroptosis-related genes and construct a logistic regression diagnostic model. Candidate biomarkers were validated in Nephroseq V5 platform, a real-world clinical cohort by ELISA, a human kidney single-cell RNA-seq dataset, and an STZ-induced DKD rat model.
Thirty-two ferroptosis-related module-specific differentially expressed genes were identified, from which COL14A1, ACADSB, TYRO3, and ZFP36 were selected as key biomarkers. The four-gene diagnostic model showed strong discriminatory performance in the training dataset and maintained diagnostic value in three independent validation datasets. In the real-world cohort, creatinine-corrected urinary levels of the four corresponding proteins were positively correlated with urinary albumin-to-creatinine ratio and negatively correlated with estimated glomerular filtration rate, and the combined urinary predictor showed high diagnostic performance for DKD. Single-cell analysis revealed cell-type-specific expression patterns, including COL14A1 enrichment in juxtaglomerular/interstitial cells and TYRO3 enrichment in podocytes, with remodeling of TYRO3-associated intercellular communication in DKD. In DKD rat kidneys, Col14a1 and Acsl4 were upregulated, whereas Tyro3 was downregulated, supporting the disease relevance of these markers.
This multi-omics and multi-cohort study identifies COL14A1, ACADSB, TYRO3, and ZFP36 as ferroptosis-related biomarkers associated with DKD renal injury. Their creatinine-corrected urinary protein levels may serve as a promising non-invasive biomarker panel for DKD diagnosis and risk stratification.
PMID:
42602622
Bibliographic data and abstract were imported from PubMed on 15 Aug 2026.
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