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Xenobiotic\u2010induced tissue injury has been extensively studied from both classical histopathological and biochemical perspectives. Here, we introduce a machine\u2010learning approach to analyze toxicological response. Unsupervised characterization of physiological and histological changes in a large toxicogenomic dataset revealed nine discrete toxin\u2010induced 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\u2010body signaling through Gdf15 and Igf1, suggesting strategies for therapeutic intervention that may be broadly relevant to human disease.<\/jats:p>","DOI":"10.15252\/msb.20188636","type":"journal-article","created":{"date-parts":[[2019,2,19]],"date-time":"2019-02-19T15:55:12Z","timestamp":1550591712000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Unsupervised identification of disease states from high\u2010dimensional physiological and histopathological profiles"],"prefix":"10.1038","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8540-9785","authenticated-orcid":false,"given":"Kenichi","family":"Shimada","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Timothy J","family":"Mitchison","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2019,2,19]]},"reference":[{"key":"BFMSB188636_CR1","doi-asserted-by":"crossref","first-page":"e112193","DOI":"10.1371\/journal.pone.0112193","volume":"9","author":"MDM AbdulHameed","year":"2014","unstructured":"AbdulHameed MDM, Tawa GJ, Kumar K, Ippolito DL, Lewis JA, Stallings JD, Wallqvist A (2014) Systems level analysis and identification of pathways\u00a0and networks associated with liver fibrosis. 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