Journal of inflammation research · 2026
Ferroptosis-Related Diagnostic Biomarkers in Diabetic Kidney Disease: A Multi-Omics and Multi-Cohort Study.
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Li Xu, Hong Huan, Li Hong, Fang Zhenhua, Wang Jie, Wang Xiuli, Sui Xinting, Shadekejiang Halinuer, Liang Mingzhu, Gan Xinyu, Liu Jiaming, Lu Chen
Аннотация
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.