Characterization of renal biomarkers for use in clinical trials: Effect of preanalytical processing and qualification using samples from subjects with diabetes

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Characterization of renal biomarkers for use in clinical trials : Effect of preanalytical processing and qualification using samples from subjects with diabetes. / DIRECT Programme Steering Committee.

I: Drug Design, Development and Therapy, Bind 9, 22.06.2015, s. 3191-3198.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

DIRECT Programme Steering Committee 2015, 'Characterization of renal biomarkers for use in clinical trials: Effect of preanalytical processing and qualification using samples from subjects with diabetes', Drug Design, Development and Therapy, bind 9, s. 3191-3198. https://doi.org/10.2147/DDDT.S78792

APA

DIRECT Programme Steering Committee (2015). Characterization of renal biomarkers for use in clinical trials: Effect of preanalytical processing and qualification using samples from subjects with diabetes. Drug Design, Development and Therapy, 9, 3191-3198. https://doi.org/10.2147/DDDT.S78792

Vancouver

DIRECT Programme Steering Committee. Characterization of renal biomarkers for use in clinical trials: Effect of preanalytical processing and qualification using samples from subjects with diabetes. Drug Design, Development and Therapy. 2015 jun. 22;9:3191-3198. https://doi.org/10.2147/DDDT.S78792

Author

DIRECT Programme Steering Committee. / Characterization of renal biomarkers for use in clinical trials : Effect of preanalytical processing and qualification using samples from subjects with diabetes. I: Drug Design, Development and Therapy. 2015 ; Bind 9. s. 3191-3198.

Bibtex

@article{2e25ec2ffbc04e9a8b72309377487d9b,
title = "Characterization of renal biomarkers for use in clinical trials: Effect of preanalytical processing and qualification using samples from subjects with diabetes",
abstract = "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",
author = "Brott, {David A.} and Furlong, {Stephen T.} and Adler, {Scott H.} and Hainer, {James W.} and Arani, {Ramin B.} and Mark Pinches and Peter Rossing and Nish Chaturvedi and {DIRECT Programme Steering Committee}",
year = "2015",
month = jun,
day = "22",
doi = "10.2147/DDDT.S78792",
language = "English",
volume = "9",
pages = "3191--3198",
journal = "Drug Design, Development and Therapy",
issn = "1177-8881",
publisher = "Dove Medical Press Ltd",

}

RIS

TY - JOUR

T1 - Characterization of renal biomarkers for use in clinical trials

T2 - Effect of preanalytical processing and qualification using samples from subjects with diabetes

AU - Brott, David A.

AU - Furlong, Stephen T.

AU - Adler, Scott H.

AU - Hainer, James W.

AU - Arani, Ramin B.

AU - Pinches, Mark

AU - Rossing, Peter

AU - Chaturvedi, Nish

AU - DIRECT Programme Steering Committee

PY - 2015/6/22

Y1 - 2015/6/22

N2 - 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.

AB - 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.

KW - Drug development

KW - Healthy volunteers

KW - Kidney

UR - http://www.scopus.com/inward/record.url?scp=84933074501&partnerID=8YFLogxK

U2 - 10.2147/DDDT.S78792

DO - 10.2147/DDDT.S78792

M3 - Journal article

C2 - 26124642

AN - SCOPUS:84933074501

VL - 9

SP - 3191

EP - 3198

JO - Drug Design, Development and Therapy

JF - Drug Design, Development and Therapy

SN - 1177-8881

ER -

ID: 257058431