{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,17]],"date-time":"2026-10-17T16:02:48Z","timestamp":1792252968325,"version":"4.4.0"},"reference-count":51,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,3,24]],"date-time":"2022-03-24T00:00:00Z","timestamp":1648080000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Toxicol."],"abstract":"<jats:p>Several approaches have been used in an attempt to simplify and codify the events that lead to adverse effects of chemicals including systems biology, \u2018omics, <jats:italic>in vitro<\/jats:italic> assays and frameworks such as the Adverse Outcome Pathway (AOP). However, these approaches are generally not integrated despite their complementary nature. Here we propose to integrate toxicogenomics data, systems biology information and AOPs using causal biological networks to define Key Events in AOPs. We demonstrate this by developing a causal subnetwork of 28 nodes that represents the Key Event of regenerative proliferation \u2013 a critical event in AOPs for liver cancer. We then assessed the effects of three chemicals known to cause liver injury and cell proliferation (carbon tetrachloride, aflatoxin B<jats:sub>1<\/jats:sub>, thioacetamide) and two with no known cell proliferation effects (diazepam, simvastatin) on the subnetwork using rat liver gene expression data from the toxicogenomic database Open TG-GATEs. Cyclin D1 (Ccnd1), a gene both causally linked to and sufficient to infer regenerative proliferation activity, was overexpressed after exposures to carbon tetrachloride, aflatoxin B<jats:sub>1<\/jats:sub> and thioacetamide, but not in exposures to diazepam and simvastatin. These results were consistent with known effects on rat livers and liver pathology of exposed rats. Using these approaches, we demonstrate that transcriptomics, AOPs and systems biology can be applied to examine the presence and progression of AOPs in order to better understand the hazards of chemical exposure.<\/jats:p>","DOI":"10.3389\/ftox.2022.786057","type":"journal-article","created":{"date-parts":[[2022,3,29]],"date-time":"2022-03-29T02:58:07Z","timestamp":1648522687000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":25,"title":["Integration of Adverse Outcome Pathways, Causal Networks and \u2018Omics to Support Chemical Hazard Assessment"],"prefix":"10.3389","volume":"4","author":[{"given":"Edward J.","family":"Perkins","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"E. 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