ArticleDrug design, development and therapy2015
Characterization of renal biomarkers for use in clinical trials: effect of preanalytical processing and qualification using samples from subjects with diabetes.
Article in Drug design, development and therapy, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 20 citations in OpenAlex.
- Article
- Trefoil factor 3 can stimulate Th17 cell response in the development of type 2 diabetes mellitus.Scientific reports · 2024Article
- The Promise of Systems Biology for Diabetic Kidney Disease.Advances in chronic kidney disease · 2018Review
- Comparative validation of a microcapsule-based immunoassay for the detection of proteins and nucleic acids.PloS one · 2018Article
- The ZDSD rat: a novel model of diabetic nephropathy.American journal of translational research · 2017Article
- Osteopontin as a discriminating marker for pancreatic cancer and chronic pancreatitis.Cancer biomarkers : section A of Disease markers · 2016Article
- Urinary Markers of Tubular Injury in Early Diabetic Nephropathy.International journal of nephrology · 2016Review
Corrections and comments
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Authors and funding
9 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIdentifying 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).
methodsUrine 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 bio-markers 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.
resultsCTGF 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.
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