ArticleThe pharmacogenomics journal2010
Genomic indicators in the blood predict drug-induced liver injury.
Article in The pharmacogenomics journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Blood toxicogenomics reveals potential biomarkers for management of idiosyncratic drug-induced liver injury.Frontiers in genetics · 2025Article
- Bridging organ transcriptomics for advancing multiple organ toxicity assessment with a generative AI approach.NPJ digital medicine · 2024Article
- A computational framework to in silico screen for drug-induced hepatocellular toxicity.Toxicological sciences : an official journal of the Society of Toxicology · 2024Article
- The Promise of AI for DILI Prediction.Frontiers in artificial intelligence · 2021Review
- Toxicogenomics: A 2020 Vision.Trends in pharmacological sciences · 2019Review
- Metabolic network-based predictions of toxicant-induced metabolite changes in the laboratory rat.Scientific reports · 2018Article
- Hepatitis E Virus Induces Hepatocyte Apoptosis via Mitochondrial Pathway in Mongolian Gerbils.Frontiers in microbiology · 2018Article
- The FDA's Experience with Emerging Genomics Technologies-Past, Present, and Future.The AAPS journal · 2016Review
- Characterization of Conserved Toxicogenomic Responses in Chemically Exposed Hepatocytes across Species and Platforms.Environmental health perspectives · 2016Article
- Gamma-Glutamylcysteine Ethyl Ester Protects against Cyclophosphamide-Induced Liver Injury and Hematologic Alterations via Upregulation of PPAROxidative medicine and cellular longevity · 2016Article
- Toxicogenomics profiling of bone marrow from rats treated with topotecan in combination with oxaliplatin: a mechanistic strategy to inform combination toxicity.Frontiers in genetics · 2015Article
- Molecular mechanisms of hepatic apoptosis.Cell death & disease · 2014Review
- Identification of metabolites, clinical chemistry markers and transcripts associated with hepatotoxicity.PloS one · 2014Article
- Blood transcriptomics: applications in toxicology.Journal of applied toxicology : JAT · 2013Review
- Analysis of the transcriptome in molecular epidemiology studies.Environmental and molecular mutagenesis · 2013Review
- Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data.Toxicological sciences : an official journal of the Society of Toxicology · 2012Article
- Identification of Identical Transcript Changes in Liver and Whole Blood during Acetaminophen Toxicity.Frontiers in genetics · 2012Article
- The impact of classification of interest on predictive toxicogenomics.Frontiers in genetics · 2012Article
- Clinical implementation of RNA signatures for pharmacogenomic decision-making.Pharmacogenomics and personalized medicine · 2011Article
- The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models.Nature biotechnology · 2010Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
23 authors.
Funding
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.