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

Heather P Llewellyn,Vishal S Vaidya,Zhenyu Wang,Kent Johnson,Qinghai Peng,David Potter,Roscoe Warner,Gerd A Kullak-Ublick,Seda Arat,Craig Hyde,James W Dear,Qing Zong,Shashi K Ramaiah,Jianying Wang,Katherine Masek-Hammerman,Guruprasad P Aithal,Matt Martin

doi:10.1093/toxsci/kfab003

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.

Highlights

75 Drug-induced liver injury (DILI) is a major concern for patients, clinicians, regulatory76 agencies and drug makers, as it is the leading cause of acute liver failure among77 patients referred for liver transplantation (Bernal and Wendon 2014; Przybylak and78 Cronin 2012)
Idiosyncratic and intrinsic DILI have different pathophysiologies, many biomarkers likely overlap in their ability to detect DILI
Using baseline (T1) data to train the model with Glutamate dehydrogenase (GLDH), K18 and miR-122, the composite score produced by this model was highly correlated (R = 0.921) with measured ALT activity (Figure 1B). The model was tested at the second timepoint (T2) (Figure 1C) and validated at the third timepoint (T3) (Figure 1D)

Summary

Introduction

75 Drug-induced liver injury (DILI) is a major concern for patients, clinicians, regulatory76 agencies and drug makers, as it is the leading cause of acute liver failure among77 patients referred for liver transplantation (Bernal and Wendon 2014; Przybylak and78 Cronin 2012). 75 Drug-induced liver injury (DILI) is a major concern for patients, clinicians, regulatory. 76 agencies and drug makers, as it is the leading cause of acute liver failure among. The annual incidence of DILI is about 14-24 per 100,000 people. An overdose of 80 acetaminophen (APAP/paracetamol) is the most common cause of DILI and acute liver. DILI is a leading cause of 82 compound attrition during drug development, and drug withdrawals and restrictions after. 87 and specific translational biomarkers for diagnosis and prognosis of DILI in humans. the Food and Drug Administration (FDA) has a renewed interest to expand guidance on biomarker research to determine hepatotoxic liability of drugs and avenues for biomarker regulatory qualification opportunities

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