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Evaluating the Sensitivity and Specificity of Promising Circulating Biomarkers to Diagnose Liver Injury in Humans.

Authors :
Llewellyn HP
Vaidya VS
Wang Z
Peng Q
Hyde C
Potter D
Wang J
Zong Q
Arat S
Martin M
Masek-Hammerman K
Warner R
Johnson K
Kullak-Ublick GA
Aithal GP
Dear JW
Ramaiah SK
Source :
Toxicological sciences : an official journal of the Society of Toxicology [Toxicol Sci] 2021 Apr 27; Vol. 181 (1), pp. 23-34.
Publication Year :
2021

Abstract

Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and postmarketing. The objective of this study was to evaluate the diagnostic performance of promising biomarkers of liver injury-glutamate dehydrogenase (GLDH), cytokeratin-18 (K18), caspase-cleaved K18 (ccK18), osteopontin (OPN), macrophage colony-stimulating factor (MCSF), MCSF receptor (MCSFR), and microRNA-122 (miR-122) in comparison to the traditional biomarker alanine aminotransferase (ALT). Biomarkers were evaluated individually and as a multivariate model in a cohort of acetaminophen overdose (n = 175) subjects and were further tested in cohorts of healthy adults (n = 135), patients with liver damage from various causes (n = 104), and patients with damage to the muscle (n = 74), kidney (n = 40), gastrointestinal tract (n = 37), and pancreas (n = 34). In the acetaminophen cohort, a multivariate model with GLDH, K18, and miR-122 was able to detect DILI more accurately than individual biomarkers alone. Furthermore, the three-biomarker model could accurately predict patients with liver injury compared with healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract, and kidney. Expression of K18, GLDH, and miR-122 was evaluated using a database of transcriptomic profiles across multiple tissues/organs in humans and rats. K18 mRNA (Krt18) and MiR-122 were highly expressed in liver whereas GLDH mRNA (Glud1) was widely expressed. We performed a comprehensive, comparative performance assessment of 7 promising biomarkers and demonstrated that a 3-biomarker multivariate model can accurately detect liver injury.<br /> (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Details

Language :
English
ISSN :
1096-0929
Volume :
181
Issue :
1
Database :
MEDLINE
Journal :
Toxicological sciences : an official journal of the Society of Toxicology
Publication Type :
Academic Journal
Accession number :
33483742
Full Text :
https://doi.org/10.1093/toxsci/kfab003