ArticleMolecular systems biology2019
Unsupervised identification of disease states from high-dimensional physiological and histopathological profiles.
Article in Molecular systems biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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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.
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Who cites it
11 citing papers in PubMed.
- Type A and DFrontiers in cellular and infection microbiology · 2026Article
- Apoptotic signatures allow early and rapid screening of drug-induced liver injury to accelerate drug discovery.Communications medicine · 2025Article
- Growth differentiation factor-15 is an IFN-γ regulated mediator of infection-induced weight loss and the hepatic FGF21 response.Brain, behavior, and immunity · 2024Article
- Molecular basis of GDF15 induction and suppression by drugs in cardiomyocytes and cancer cells toward precision medicine.Scientific reports · 2023Article
- Emerging Roles of Growth Differentiation Factor 15 in Immunoregulation and Pathogenesis.Journal of immunology (Baltimore, Md. : 1950) · 2023Review
- The Impact of Helminth Coinfection on Innate and Adaptive Immune Resistance and Disease Tolerance during Toxoplasmosis.Journal of immunology (Baltimore, Md. : 1950) · 2022Article
- Article
- Review
- Activation of the hypothalamic-pituitary-adrenal axis by exogenous and endogenous GDF15.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- GDF15: A Hormone Conveying Somatic Distress to the Brain.Endocrine reviews · 2020Review
- Unsupervised identification of disease states from high-dimensional physiological and histopathological profiles.Molecular systems biology · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
The liver and kidney in mammals play central roles in protecting the organism from xenobiotics and are at high risk of xenobiotic-induced injury. Xenobiotic-induced tissue injury has been extensively studied from both classical histopathological and biochemical perspectives. Here, we introduce a machine-learning approach to analyze toxicological response. Unsupervised characterization of physiological and histological changes in a large toxicogenomic dataset revealed nine discrete toxin-induced disease states, some of which correspond to known pathology, but others were novel. Analysis of dynamics revealed transitions between disease states at constant toxin exposure, mostly toward decreased pathology, implying induction of tolerance. Tolerance correlated with induction of known xenobiotic defense genes and decrease of novel ferroptosis sensitivity biomarkers, suggesting ferroptosis as a druggable driver of tissue pathophysiology. Lastly, mechanism of body weight decrease, a known primary marker for xenobiotic toxicity, was investigated. Combined analysis of food consumption, body weight, and molecular biomarkers indicated that organ injury promotes cachexia by whole-body signaling through Gdf15 and Igf1, suggesting strategies for therapeutic intervention that may be broadly relevant to human disease.
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Registered trials
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