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The role of novel biomarkers in predicting diabetic nephropathy: a review

 

Authors Uwaezuoke SN

Received 3 June 2017

Accepted for publication 18 July 2017

Published 17 August 2017 Volume 2017:10 Pages 221—231

DOI https://doi.org/10.2147/IJNRD.S143186

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Colin Mak

Peer reviewer comments 2

Editor who approved publication: Professor Pravin Singhal

Abstract: Diabetic nephropathy (DN) is one of the microvascular complications of the kidney arising commonly from type 1 diabetes mellitus (T1DM), and occasionally from type 2 diabetes mellitus (T2DM). Microalbuminuria serves as an early indicator of DN risk and a predictor of its progression as well as cardiovascular disease risk in both T1DM and T2DM. Although microalbuminuria remains the gold standard for early detection of DN, it is not a sufficiently accurate predictor of DN risk due to some limitations. Thus, there is a paradigm shift to novel biomarkers which would help to predict DN risk early enough and possibly prevent the occurrence of end-stage kidney disease. These new biomarkers have been broadly classified into glomerular biomarkers, tubular biomarkers, biomarkers of inflammation, biomarkers of oxidative stress, and miscellaneous biomarkers which also include podocyte biomarkers, some of which are also considered as tubular and glomerular biomarkers. Although they are potentially useful for the evaluation of DN, current data still preclude the routine clinical use of majority of them. However, their validation using high-quality and large longitudinal studies is of paramount importance, as well as the subsequent development of a biomarker panel which can reliably predict and evaluate this renal microvascular disease. This paper aims to review the predictive role of these biomarkers in the evaluation of DN.
Keywords: type 1 diabetes mellitus, renal microvascular complication, microalbuminuria, end-stage kidney disease, biomarker panel

 


摘要视频链接Role of novel biomarkers in predicting diabetic nephropathy