Systems Biology and Novel Biomarkers for the Early Detection of Diabetic Kidney Disease

Abstract

Diabetic kidney disease is the most common driver of chronic kidney disease (CKD)-associated mortality and kidney replacement therapy. Despite recent therapeutic advances (SGLT2 inhibitors, finerenone), the residual kidney and mortality risk remains high for patients already diagnosed of having CKD (i.e., estimated glomerular filtration rate <60 ml/min/1.73 m2 or urinary albumin:creatinine ratio >30 mg/g). The challenge for the near future is to identify patients at higher risk of developing CKD to initiate therapy before CKD develops (primary prevention of CKD) and to identify patients with CKD and high risk of progression or death, in order to intensify therapy. We now discuss recent advances in biomarkers that may contribute to identify such high-risk individuals for clinical trials of novel primary prevention or treatment approaches for CKD. The most advanced biomarker from a clinical development point of view is the urinary peptidomics classifier CKD273, that integrates prognostic information from 273 urinary peptides and identifies high risk individuals before CKD develops.