#AI reads Urine# C-X-C Motif Chemokine Ligand 3 as a Potential Biomarker for Diagnosis and Prognosis of Diabetic Kidney Disease

This study aimed to identify potential biomarkers for the diagnosis and prognosis of diabetic kidney disease (DKD). Through artificial intelligence techniques such as weighted gene co-expression network analysis (WGCNA) and machine learning, combined with validation using online databases, human samples, DKD rat models, high glucose-treated HK-2 cells, and other approaches, it was found that C-X-C motif chemokine ligand 3 (CXCL3) was significantly upregulated in the serum, urine, renal tissues, and peripheral blood mononuclear cells (PBMCs) of DKD patients, showing obvious differences compared with healthy controls, patients with type 2 diabetes mellitus, and those with primary glomerulonephritis. The level of urinary CXCL3 was positively correlated with the pathological grade, serum blood urea nitrogen (BUN), serum creatinine, and glycated hemoglobin (HbA1c) in DKD patients, while negatively correlated with the estimated glomerular filtration rate (eGFR). Mechanistically, CXCL3 can promote inflammation and fibrosis in HK-2 cells under high glucose conditions, and its expression is also associated with the infiltration of various immune cells, with a relevant competing endogenous RNA (ceRNA) regulatory network existing. In conclusion, CXCL3 is expected to serve as a potential biomarker for the diagnosis and prognostic evaluation of DKD, as well as a target for intervention.

FASEB J. 2026 Jan 31;40(2):e71443. doi: 10.1096/fj.202502236R.

Youhe Gao

Statement: During the preparation of this work the author(s) used Doubao / AI reading for summarizing the content. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

For earlier AI Reads Urine articles：https://www.keaipublishing.com/en/journals/advances-in-biomarker-sciences-and-technology/ai-reads-urine/