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Copyright ©The Author(s) 2016. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Diabetes. Jul 25, 2016; 7(14): 290-301
Published online Jul 25, 2016. doi: 10.4239/wjd.v7.i14.290
Early detection of diabetic kidney disease: Present limitations and future perspectives
Chih-Hung Lin, Yi-Cheng Chang, Lee-Ming Chuang
Chih-Hung Lin, Yi-Cheng Chang, Lee-Ming Chuang, Department of Internal Medicine, National Taiwan University Hospital, Taipei 100, Taiwan
Chih-Hung Lin, Lee-Ming Chuang, Graduate Institute of Clinical Medicine, College of Medicine, National Taiwan University, Taipei 100, Taiwan
Yi-Cheng Chang, Graduate Institute of Medical Genomics and Proteomics, College of Medicine, National Taiwan University, Taipei 100, Taiwan
Yi-Cheng Chang, Institute of Biomedical Science, Academia Sinica, Taipei 115, Taiwan
Author contributions: Lin CH and Chang YC drafted the manuscript and tables; Chuang LM conceived the outlines and approved the final manuscript.
Conflict-of-interest statement: The authors declare no conflict of interest.
Open-Access: This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
Correspondence to: Dr. Lee-Ming Chuang, MD, PhD, Department of Internal Medicine, National Taiwan University Hospital, 7, Chung Shan S. Rd, Taipei 100, Taiwan. leeming@ntu.edu.tw
Telephone: +886-2-23123456 Fax: +886-2-23938859
Received: March 28, 2016
Peer-review started: March 28, 2016
First decision: May 16, 2016
Revised: May 29, 2016
Accepted: June 27, 2016
Article in press: June 29, 2016
Published online: July 25, 2016
Processing time: 116 Days and 4.9 Hours
Abstract

Diabetic kidney disease (DKD) is one of the most common diabetic complications, as well as the leading cause of chronic kidney disease and end-stage renal disease around the world. To prevent the dreadful consequence, development of new assays for diagnostic of DKD has always been the priority in the research field of diabetic complications. At present, urinary albumin-to-creatinine ratio and estimated glomerular filtration rate (eGFR) are the standard methods for assessing glomerular damage and renal function changes in clinical practice. However, due to diverse tissue involvement in different individuals, the so-called “non-albuminuric renal impairment” is not uncommon, especially in patients with type 2 diabetes. On the other hand, the precision of creatinine-based GFR estimates is limited in hyperfiltration status. These facts make albuminuria and eGFR less reliable indicators for early-stage DKD. In recent years, considerable progress has been made in the understanding of the pathogenesis of DKD, along with the elucidation of its genetic profiles and phenotypic expression of different molecules. With the help of ever-evolving technologies, it has gradually become plausible to apply the thriving information in clinical practice. The strength and weakness of several novel biomarkers, genomic, proteomic and metabolomic signatures in assisting the early diagnosis of DKD will be discussed in this article.

Keywords: Diabetic kidney disease; Early diagnosis; Genomics; Biomarkers

Core tip: Estimated glomerular filtration rate (eGFR) and albuminuria are currently the standard method for detecting diabetic kidney disease (DKD). Creatinine-based GFR estimates are affected by muscle mass and diet pattern, as well as the formula chosen. Albuminuria majorly reflects glomerular dysfunction, and is less sensitive to tubulointerstitial and vascular damages. These facts limit the application of eGFR and albuminuria in the early diagnosis of DKD, especially in heterogeneous type 2 diabetic patients. Through the assistance of genetic information for screening of susceptible patients, together with novel biomarkers to reflect diverse renal tissue damage, early diagnosis of DKD could be facilitated.