Biomarkers of diabetic kidney disease

• Published in: Diabetologia Vol. 61; no. 5; pp. 996 - 1011
• Main Authors: Colhoun, Helen M., Marcovecchio, M. Loredana
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.05.2018; Springer Nature B.V
• Subjects: Albuminuria - diagnosis; Albuminuria - physiopathology; Algorithms; Animals; Biomarkers; Biomarkers - analysis; Clinical trials; Diabetes; Diabetes mellitus; Diabetes Mellitus, Type 1 - complications; Diabetes Mellitus, Type 2 - complications; Diabetic Nephropathies - diagnosis; Diabetic nephropathy; Disease Progression; End-stage renal disease; Epidemiology; Epidermal growth factor receptors; Glomerular Filtration Rate; Human Physiology; Humans; Internal Medicine; Kidney - metabolism; Kidney diseases; Kidney Failure, Chronic - complications; Life span; Lipid metabolism; Medicine; Medicine & Public Health; Metabolic Diseases; Metabolites; Metabolomics; MicroRNAs - metabolism; Prognosis; Programmed Cell Death 1 Ligand 2 Protein - metabolism; Proteomics; Review; Biomarker; Nephropathy; Review; Epidemiology; Diabetic kidney disease
• ISSN: 0012-186X; 1432-0428
• DOI: 10.1007/s00125-018-4567-5

Diabetic kidney disease (DKD) remains one of the leading causes of reduced lifespan in diabetes. The quest for both prognostic and surrogate endpoint biomarkers for advanced DKD and end-stage renal disease has received major investment and interest in recent years. However, at present no novel biomarkers are in routine use in the clinic or in trials. This review focuses on the current status of prognostic biomarkers. First, we emphasise that albuminuria and eGFR, with other routine clinical data, show at least modest prediction of future renal status if properly used. Indeed, a major limitation of many current biomarker studies is that they do not properly evaluate the marginal increase in prediction on top of these routinely available clinical data. Second, we emphasise that many of the candidate biomarkers for which there are numerous sporadic reports in the literature are tightly correlated with each other. Despite this, few studies have attempted to evaluate a wide range of biomarkers simultaneously to define the most useful among these correlated biomarkers. We also review the potential of high-dimensional panels of lipids, metabolites and proteins to advance the field, and point to some of the analytical and post-analytical challenges of taking initial studies using these and candidate approaches through to actual clinical biomarker use.