Abstracto

Urine proteomics identifies biomarkers for diabetic kidney disease

Carole Taylor

Chronic kidney disease (CKD) and end-stage renal disease (ESRD) are most commonly caused by type 2 diabetic kidney disease (ESRD). Although kidney biopsy is the "gold standard" for diagnosing diabetic kidney disease (DKD), it is an intrusive process that can be influenced by sample bias and personal judgement. It would be ideal to develop a non-invasive method to supplement kidney biopsy in the diagnosis and monitoring of DKD progression. We investigated the urine proteomes by liquid chromatography coupled with tandem mass spectrometry (LC– MS/MS) in this cross-sectional investigation, which included uncomplicated diabetes, without diabetes, and follow-up diabetic samples. To discriminate between simple diabetes, DKD, and other CKDs, we created logistic regression models. These findings were confirmed in a separate dataset. Finally, a four-protein classifier identified potential pre-DKD3 patients with DKD3 proteomic markers but no clinical diagnosis. Two putative pre-DKD patients have progressed to DKD3, according to follow-up research on 11 patients. Our findings show that urine proteomics has the potential to be a noninvasive technique for diagnosing DKD and selecting high-risk patients for progression monitoring.