Characterization of renal biomarkers for use in clinical trials: effect of preanalytical processing and qualification using samples from subjects with diabetes
Authors Brott D, Furlong ST, Adler S, Hainer JW, Arani R, Pinches M, Rossing P, Chaturvedi N
Received 6 December 2014
Accepted for publication 3 February 2015
Published 22 June 2015 Volume 2015:9 Pages 3191—3198
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 3
Editor who approved publication: Professor Shu-Feng Zhou
David A Brott,1 Stephen T Furlong,1 Scott H Adler,1 James W Hainer,2 Ramin B Arani,2 Mark Pinches,3 Peter Rossing,4–6 Nish Chaturvedi7
On behalf of the DIRECT Programme Steering Committee
1Enabling Safety Sciences, 2AstraZeneca Pharmaceuticals, Wilmington, DE, USA; 3Drug Safety and Metabolism, AstraZeneca Pharmaceuticals, Alderley Park, UK; 4Steno Diabetes Center, Gentofte, Denmark; 5Aarhus University, Aarhus, Denmark, 6University of Copenhagen, Denmark; 7Institute of Cardiovascular Sciences, University College London, London, UK
Background: Identifying the potential for drug-induced kidney injury is essential for the successful research and development of new drugs. Newer and more sensitive preclinical drug-induced kidney injury biomarkers are now qualified for use in rat toxicology studies, but biomarkers for clinical studies are still undergoing qualification. The current studies investigated biomarkers in healthy volunteer (HV) urine samples with and without the addition of stabilizer as well as in urine from patients with normoalbuminuric diabetes mellitus (P-DM).
Methods: Urine samples from 20 male HV with stabilizer, 69 male HV without stabilizer, and 95 male DM without stabilizer (39 type 1 and 56 type 2) were analyzed for the following biomarkers using multiplex assays: α-1-microglobulin (A1M), β-2-microglobulin, calbindin, clusterin, connective tissue growth factor (CTGF), creatinine, cystatin-C, glutathione s-transferase α (GSTα), kidney injury marker-1 (KIM-1), microalbumin, neutrophil gelatinase-associated lipocalin, osteopontin, Tamm–Horsfall urinary glycoprotein (THP), tissue inhibitor of metalloproteinase 1, trefoil factor 3 (TFF3), and vascular endothelial growth factor.
Results: CTGF and GSTα assays on nonstabilized urine were deemed nonoptimal (>50% of values below assay lower limits of quantification). “Expected values” were determined for HV with stabilizer, HV without stabilizer, and P-DM without stabilizer. There was a statistically significant difference between HV with stabilizer compared to HV without stabilizer for A1M, CTGF, GSTα, and THP. DM urine samples differed from HV (without stabilizer) for A1M CTGF, GSTα, KIM-1, microalbumin, osteopontin, and TFF3. A1M also correctly identified HV and DM with an accuracy of 89.0%.
Summary: These studies: 1) determined that nonstabilized urine can be used for assays under qualification; and 2) documented that A1M, CTGF, GSTα, KIM-1, microalbumin, osteopontin, and TFF3 were significantly increased in urine from P-DM. In addition, the 89.0% accuracy of A1M in distinguishing P-DM from HV may allow this biomarker to be used to monitor efficacy of potential renal protective agents.
Keywords: drug development, healthy volunteers, kidney
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