Pilot Study of Renal Urinary Biomarkers for Diagnosis of CKD of Uncertain Etiology

Buddhi N.T.W. Fernando1,7, Asfa Alli-Shaik2,7, Rusiru K.D. Hemage1, Zeid Badurdeen1,Thilini W.Hettiarachchi1, Hemalika T.K. Abeysundara3, Thilak D.J. Abeysekara1,Abdul Wazil4, Saman Rathnayake5, Jayantha Gunaratne2,6 and Nishantha Nanayakkara4

1Centre for Education, Research and Training on Kidney Diseases (CERTKiD), Faculty of Medicine, University of Peradeniya, Sri Lanka

 2Institute of Molecular and Cell Biology, Proteos, Singapore

3Department of Statistics and Computer Science, Faculty of Science, University of Peradeniya Sri Lanka

 4Transplant and Dialysis Unit, Teaching Hospital, Kandy, Sri Lanka

5Teaching Hospital, Kandy, Sri Lanka and 6Yong Loo Lin School of Medicine, National University of Singapore, Singapore

Introduction:

Chronic kidney disease of uncertain etiology (CKDu), an emerging chronic kidney disease (CKD) subtype, contributes to significant morbidity and mortality in certain tropical countries. Although several indicators of CKDu have been previously suggested, sensitive and specific tests to detect early disease or predict disease progression are currently unavailable. This study focused on evaluating 8 renal urinary markers, namely neutrophil gelatinase-associated lipocalin (NGAL), Kidney Injury Molecule-1 (KIM1), cystatin C (CST3), beta 2 microglobulin (B2M), osteopontin (OPN), alpha 1 microglobulin (A1M),tissue inhibitor of metalloproteinase 1 (TIMP1), and retinol binding protein 4 (RBP4), with the hypothesis that these have distinct expression patterns in patients with CKDu.

Methods:

A cross-sectional study was conducted with 5 study groups comprising subjects from CKDu, endemic CKD, nonendemic CKD, and endemic healthy and nonendemic healthy controls. The urinary levels of the 8 selected renal biomarkers were quantified using multiplex biomarker assay, and the data were subjected to systematic analysis using logistic regression algorithm aiming to extract the best marker combination that could distinctly identify the disease groups noninvasively from the healthy controls.

Results:

A 3-marker signature panel comprising A1M, KIM1, and RBP4 was identified to represent the best minimum marker combination for differentiating all CKD categories, including CKDu, from healthy controls with an overall sensitivity of $0.867 and specificity $0.765. The marker combination comprising OPN, KIM1, and RBP4 showed high predictive performance for distinguishing patients with CKDu from patients with CKD with both sensitivity and specificity $0.93, which was superior to any existing noninvasive indicator.

Conclusion:

In all, our systematic evaluation of urinary markers previously linked to CKD, in general, allowed identification of exclusive marker panel combination for early diagnosis and confirmation of CKDu.

Kidney Int Rep (2019) 4, 1401–1411; https://doi.org/10.1016/j.ekir.2019.07.009

KEYWORDS: chronic kidney disease of uncertain etiology; early diagnosis; urinary biomarkers

©2019 International Society of Nephrology. Published by Elsevier Inc. This is an open access article under the CC BYNC-ND license

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