Drug-induced liver injury (DILI) diagnosis and classification (hepatocellular, cholestatic, and mixed) relies on traditional clinical biomarkers (eg ALT and ALP), despite limitations such as extrahepatic interferences, narrow dynamic ranges, and low mechanistic value. microRNAs may be very useful for complementing traditional DILI biomarkers but most studies in this direction have considered only paracetamol poisoning. Thus the value of microRNAs (miRNAs) as biomarkers for idiosyncratic DILI has not yet been demonstrated. In this study, we first examined the effect of model cholestatic drugs on the human hepatocyte miRNome by RNAseq and RT-qPCR. Results demonstrated that chlorpromazine, cyclosporin A, and ANIT induced (miR-21-3p, -21-5p, -22-3p, -27a-5p, -1260b, -34a-5p, and -98-5p) and repressed (-122-5p, -192-5p, -30c-5p, -424-5p, and -16-5p) specific miRNAs in sandwich-cultured upcyte hepatocytes. However, no common signature was found for cholestatic drugs. Next we investigated the levels of these miRNA in human serum and found that most were also significantly altered in cholestatic/mixed DILI patients upon hospital/ambulatory admission. However, miR-122-5p, -192-5p, -34a-5p, and -22-3p demonstrated a much more significant induction in patients with hepatocellular DILI, thus revealing better specificity for hepatocellular damage. Time-course analyses demonstrated that -1260b and -146 had a very similar profile to ALP, but with wider dynamic ranges, while -16-5p and -451a showed a negative correlation. Conversely, -122-5p and -192-5p correlated with ALT but with wider dynamic ranges and faster recoveries. Finally, the 122/451a and 122/16 ratios showed excellent prediction performances in both the study [area under the receiver operating characteristic curve (AUROC) >0.93] and the validation cohort (AUROC > 0.82), and can, therefore, be postulated for the first time as circulating miRNA biomarkers for idiosyncratic DILI.
Keywords: drug-induced cholestasis; drug-induced liver injury; human hepatocyte; microRNA; predictive biomarker; serum.
© The Author(s) 2019. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org.