Candidate biomarkers for the diagnosis and prognosis of drug-induced liver injury: An international collaborative effort.
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AuthorsChurch, Rachel J
Kullak-Ublick, Gerd A
Bonkovsky, Herbert L
Fontana, Robert J
Goepfert, Jens C
King, Nicholas M P
Schomaker, Shelli J
Andrade, Raul J
van Bömmel, Florian
Watkins, Paul B
MetadataShow full item record
CitationCandidate biomarkers for the diagnosis and prognosis of drug-induced liver injury: An international collaborative effort. 2019, 69(2):760-773 Hepatology
AbstractCurrent blood biomarkers are suboptimal in detecting drug-induced liver injury (DILI) and predicting its outcome. We sought to characterize the natural variabilty and performance characteristics of 14 promising DILI biomarker candidates. Serum or plasma from multiple cohorts of healthy volunteers (n = 192 and n = 81), subjects who safely took potentially hepatotoxic drugs without adverse effects (n = 55 and n = 92) and DILI patients (n = 98, n = 28, and n = 143) were assayed for microRNA-122 (miR-122), glutamate dehydrogenase (GLDH), total cytokeratin 18 (K18), caspase cleaved K18, glutathione S-transferase α, alpha-fetoprotein, arginase-1, osteopontin (OPN), sorbitol dehydrogenase, fatty acid binding protein, cadherin-5, macrophage colony-stimulating factor receptor (MCSFR), paraoxonase 1 (normalized to prothrombin protein), and leukocyte cell-derived chemotaxin-2. Most candidate biomarkers were significantly altered in DILI cases compared with healthy volunteers. GLDH correlated more closely with gold standard alanine aminotransferase than miR-122, and there was a surprisingly wide inter- and intra-individual variability of miR-122 levels among healthy volunteers. Serum K18, OPN, and MCSFR levels were most strongly associated with liver-related death or transplantation within 6 months of DILI onset. Prediction of prognosis among DILI patients using the Model for End-Stage Liver Disease was improved by incorporation of K18 and MCSFR levels. Conclusion: GLDH appears to be more useful than miR-122 in identifying DILI patients, and K18, OPN, and MCSFR are promising candidates for prediction of prognosis during an acute DILI event. Serial assessment of these biomarkers in large prospective studies will help further delineate their role in DILI diagnosis and management.
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