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Evaluating the sensitivity and specificity of promising circulating biomarkers to diagnose liver injury in humans


Llewellyn, Heather P; Vaidya, Vishal S; Wang, Zhenyu; Peng, Qinghai; Hyde, Craig; Potter, David; Wang, Jianying; Zong, Qing; Arat, Seda; Martin, Matt; Masek-Hammerman, Katherine; Warner, Roscoe; Johnson, Kent; Kullak-Ublick, Gerd A; Aithal, Guruprasad P; Dear, James W; Ramaiah, Shashi K (2021). Evaluating the sensitivity and specificity of promising circulating biomarkers to diagnose liver injury in humans. Toxicological Sciences:Online ahead of print.

Abstract

Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and post marketing. 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 to healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract and kidney. Expression of K18, GLDH ad 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 seven promising biomarkers and demonstrated that a three-biomarker multivariate model can accurately detect liver injury.

Abstract

Early diagnosis of drug-induced liver injury (DILI) continues to be a major hurdle during drug development and post marketing. 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 to healthy volunteers or patients with damage to muscle, pancreas, gastrointestinal tract and kidney. Expression of K18, GLDH ad 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 seven promising biomarkers and demonstrated that a three-biomarker multivariate model can accurately detect liver injury.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Hospital Zurich > Clinic for Clinical Pharmacology and Toxicology
Dewey Decimal Classification:610 Medicine & health
Uncontrolled Keywords:Toxicology
Language:English
Date:23 January 2021
Deposited On:19 Feb 2021 15:47
Last Modified:19 Feb 2021 15:47
Publisher:Oxford University Press
ISSN:1096-0929
OA Status:Closed
Free access at:Publisher DOI. An embargo period may apply.
Publisher DOI:https://doi.org/10.1093/toxsci/kfab003

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Content: Accepted Version
Language: English
Filetype: PDF - Registered users only until 23 January 2022
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Embargo till: 2022-01-23