Huang J, Shi W, Zhang J, et al. Genomic indicators in the blood predict drug-induced liver injury. Pharmacogenomics J 2010 Aug;10(4):267-277.
PMID 20676066
doi 10.1038/tpj.2010.33
http://www.nature.com/tpj/journal/v10/n4/abs/tpj201033a.html
http://www.nature.com/tpj/journal/v10/n4/full/tpj201033a.html
http://www.nature.com/tpj/journal/v10/n4/pdf/tpj201033a.pdf
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Original Article
The Pharmacogenomics Journal (2010) 10, 267–277; doi:10.1038/tpj.2010.33
Genomic indicators in the blood predict drug-induced liver injury
J Huang1,8,12, W Shi2,12, J Zhang3,12, J W Chou4,13, R S Paules5, K Gerrish5, J Li4,14, J Luo3, R D Wolfinger6, W Bao6, T-M Chu6, Y Nikolsky2, T Nikolskaya2,11, D Dosymbekov7, M O Tsyganova7, L Shi8, X Fan1,8, J C Corton9, M Chen8, Y Cheng1, W Tong8, H Fang10 and P R Bushel4
. 1Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
. 2GeneGO, St Joseph, MI, USA
. 3Department of Bioinformatics, Systems Analytics, Waltham, MA, USA
. 4Biostatistics Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
. 5Microarray Group, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
. 6Genomics Division, SAS, Cary, NC, USA
. 7Vavilov Institute for General Genetics, Russian Academy of Sciences, Moscow, Russia
. 8Center for Toxicoinformatics, National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA
. 9National Health and Environmental Effects Research Laboratory, US Environmental Protection Agency, Research Triangle Park, NC, USA
. 10Division of Bioinformatics, Z-Tech Corporation, ICF International Company at NCTR/Food and Drug Administration, Jefferson, AR, USA
. 11Systems Biology Laboratory, Institute for General Genetics, Moscow, Russia
Correspondence: Dr PR Bushel, Biostatistics Branch, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709, USA. E-mail: bushel@niehs.nih.gov
12These authors contributed equally to this work.
13Current address: Department of Biostatistical Sciences, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, USA.
14Current address: Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, 130 Mason Farm Road, Chapel Hill, NC 27599, USA.
Received 22 November 2009; Revised 28 February 2010; Accepted 25 April 2010.
Abstract
Genomic biomarkers for the detection of drug-induced liver injury (DILI) from blood are urgently needed for monitoring drug safety. We used a unique data set as part of the Food and Drug Administration led MicroArray Quality Control Phase-II (MAQC-II) project consisting of gene expression data from the two tissues (blood and liver) to test cross-tissue predictability of genomic indicators to a form of chemically induced liver injury. We then use the genomic indicators from the blood as biomarkers for prediction of acetaminophen-induced liver injury and show that the cross-tissue predictability of a response to the pharmaceutical agent (accuracy as high as 92.1%) is better than, or at least comparable to, that of non-therapeutic compounds. We provide a database of gene expression for the highly informative predictors, which brings biological context to the possible mechanisms involved in DILI. Pathway-based predictors were associated with inflammation, angiogenesis, Toll-like receptor signaling, apoptosis, and mitochondrial damage. The results show for the first time and support the hypothesis that genomic indicators in the blood can serve as potential diagnostic biomarkers predictive of DILI.
Keywords: prediction; acetaminophen; blood; cross-tissue; liver injury; microarray gene expression
© 2010 Nature Publishing Group, a division of Macmillan Publishers Limited.