ArticlePloS one2014
Characterization of chemically induced liver injuries using gene co-expression modules.
Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed, 32 citations in OpenAlex.
- Evolution of artificial intelligence and machine learning in DILI toxicogenomics: from descriptive profiling to mechanistic insights.Frontiers in pharmacology · 2026Review
- A systems-level integration of liver-kidney transcriptomics and genome-scale metabolic models reveals organ-specific injury mechanisms.Frontiers in toxicology · 2026Article
- Quantifying liver-toxic responses from dose-dependent chemical exposures using a rat genome-scale metabolic model.Toxicological sciences : an official journal of the Society of Toxicology · 2025Article
- Probing Liver Injuries Induced by Thioacetamide in Human In Vitro Pooled Hepatocyte Experiments.International journal of molecular sciences · 2024Article
- High-Throughput Transcriptomics Differentiates Toxic versus Non-Toxic Chemical Exposures Using a Rat Liver Model.International journal of molecular sciences · 2023Article
- Assessing Kidney Injury Induced by Mercuric Chloride in Guinea Pigs with In Vivo and In Vitro Experiments.International journal of molecular sciences · 2023Article
- Transcriptomic profiling in canines and humans reveals cancer specific gene modules and biological mechanisms common to both species.PLoS computational biology · 2021Article
- TOXPANEL: A Gene-Set Analysis Tool to Assess Liver and Kidney Injuries.Frontiers in pharmacology · 2021Article
- Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.Scientific reports · 2020Article
- A Novel Open Access Web Portal for Integrating Mechanistic and Toxicogenomic Study Results.Toxicological sciences : an official journal of the Society of Toxicology · 2019Article
- Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets.PloS one · 2019Article
- Deep Neural Network Models for Predicting Chemically Induced Liver Toxicity Endpoints From Transcriptomic Responses.Frontiers in pharmacology · 2019Article
- Assessing Chemical-Induced Liver InjuryFrontiers in genetics · 2019Article
- Developments in toxicogenomics: understanding and predicting compound-induced toxicity from gene expression data.Molecular omics · 2018Review
- Toxicogenomic module associations with pathogenesis: a network-based approach to understanding drug toxicity.The pharmacogenomics journal · 2018Article
- Embracing the Dark Side: Computational Approaches to Unveil the Functionality of Genes Lacking Biological Annotation in Drug-Induced Liver Injury.Frontiers in genetics · 2018Article
- Network and Pathway Analysis of Toxicogenomics Data.Frontiers in genetics · 2018Article
- Identification of the Toxicity Pathways Associated With Thioacetamide-Induced Injuries in Rat Liver and Kidney.Frontiers in pharmacology · 2018Article
- Network-based analysis of transcriptional profiles from chemical perturbations experiments.BMC bioinformatics · 2017Article
- Mining kidney toxicogenomic data by using gene co-expression modules.BMC genomics · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver injuries due to ingestion or exposure to chemicals and industrial toxicants pose a serious health risk that may be hard to assess due to a lack of non-invasive diagnostic tests. Mapping chemical injuries to organ-specific damage and clinical outcomes via biomarkers or biomarker panels will provide the foundation for highly specific and robust diagnostic tests. Here, we have used DrugMatrix, a toxicogenomics database containing organ-specific gene expression data matched to dose-dependent chemical exposures and adverse clinical pathology assessments in Sprague Dawley rats, to identify groups of co-expressed genes (modules) specific to injury endpoints in the liver. We identified 78 such gene co-expression modules associated with 25 diverse injury endpoints categorized from clinical pathology, organ weight changes, and histopathology. Using gene expression data associated with an injury condition, we showed that these modules exhibited different patterns of activation characteristic of each injury. We further showed that specific module genes mapped to 1) known biochemical pathways associated with liver injuries and 2) clinically used diagnostic tests for liver fibrosis. As such, the gene modules have characteristics of both generalized and specific toxic response pathways. Using these results, we proposed three gene signature sets characteristic of liver fibrosis, steatosis, and general liver injury based on genes from the co-expression modules. Out of all 92 identified genes, 18 (20%) genes have well-documented relationships with liver disease, whereas the rest are novel and have not previously been associated with liver disease. In conclusion, identifying gene co-expression modules associated with chemically induced liver injuries aids in generating testable hypotheses and has the potential to identify putative biomarkers of adverse health effects.
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.