Copyright ©The Author(s) 2015. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Nephrol. Feb 6, 2015; 4(1): 57-73
Published online Feb 6, 2015. doi: 10.5527/wjn.v4.i1.57
Biomarkers in chronic kidney disease, from kidney function to kidney damage
Salvador Lopez-Giacoman, Magdalena Madero
Salvador Lopez-Giacoman, Magdalena Madero, Division of Nephrology, National Heart Institute, 14000 México City, México
Author contributions: All authors contributed to this work.
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:
Correspondence to: Magdalena Madero, MD, Division of Nephrology, National Heart Institute, Juan Badiano No. 1, Tlalpan, D.F., 14000 México City, México.
Telephone: +52-55-55736902 Fax: +52-55-55737716
Received: July 30, 2014
Peer-review started: July 30, 2014
First decision: September 16, 2014
Revised: October 28, 2014
Accepted: November 7, 2014
Article in press: November 10, 2014
Published online: February 6, 2015

Chronic kidney disease (CKD) typically evolves over many years, with a long latent period when the disease is clinically silent and therefore diagnosis, evaluation and treatment is based mainly on biomarkers that assess kidney function. Glomerular filtration rate (GFR) remains the ideal marker of kidney function. Unfortunately measuring GFR is time consuming and therefore GFR is usually estimated from equations that take into account endogenous filtration markers like serum creatinine (SCr) and cystatin C (CysC). Other biomarkers such as albuminuria may precede kidney function decline and have demonstrated to have strong associations with disease progression and outcomes. New potential biomarkers have arisen with the promise of detecting kidney damage prior to the currently used markers. The aim of this review is to discuss the utility of the GFR estimating equations and biomarkers in CKD and the different clinical settings where these should be applied. The CKD-Epidemiology Collaboration equation performs better than the modification of diet in renal disease equation, especially at GFR above 60 mL/min per 1.73 m2. Equations combining CysC and SCr perform better than the equations using either CysC or SCr alone and are recommended in situations where CKD needs to be confirmed. Combining creatinine, CysC and urine albumin to creatinine ratio improves risk stratification for kidney disease progression and mortality. Kidney injury molecule and neutrophil gelatinase-associated lipocalin are considered reasonable biomarkers in urine and plasma to determine severity and prognosis of CKD.

Keywords: Chronic kidney disease, Estimated glomerular filtration rate, Kidney damage, New biomarkers, MicroRNA

Core tip: Until more accurate equations are developed the chronic kidney disease (CKD) epidemiology collaboration appears to be superior to other glomerular filtration rate (GFR) estimating equations. In circumstances where CKD requires confirmation estimated GFR based on the combined creatinine-cystatin C equation is recommended. The recent advances in molecular biology have resulted in promising biomarkers for CKD detection and prognosis; however more research is needed before applying them into clinical practice.