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Core Liver Homeostatic Co-Expression Networks Are Preserved But Respond to Perturbations in an Organism- and Disease-Specific Manner Publisher Pubmed



Esmaili S1, 2 ; Langfelder P3 ; Belgard TG4 ; Vitale D1 ; Azardaryany MK1 ; Alipour Talesh G1 ; Ramezanimoghadam M1 ; Ho V1 ; Dvorkin D4 ; Dervish S5 ; Gloss BS5 ; Gronbaek H6 ; Liddle C1 ; George J1
Authors
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Authors Affiliations
  1. 1. Storr Liver Centre, Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Sydney, NSW, Australia
  2. 2. Liver and Pancreatobiliary Diseases Research Center, Digestive Disease Research Institute, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
  3. 3. The Jane and Terry Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, United States
  4. 4. The Bioinformatics CRO, Niceville, FL, United States
  5. 5. Westmead Research Hub, Westmead Institute for Medical Research, Sydney, NSW, Australia
  6. 6. Department of Hepatology and Gastroenterology, Aarhus University Hospital, Aarhus, Denmark

Source: Cell Systems Published:2021


Abstract

Findings about chronic complex diseases are difficult to extrapolate from animal models to humans. We reason that organs may have core network modules that are preserved between species and are predictably altered when homeostasis is disrupted. To test this idea, we perturbed hepatic homeostasis in mice by dietary challenge and compared the liver transcriptome with that in human fatty liver disease and liver cancer. Co-expression module preservation analysis pointed to alterations in immune responses and metabolism (core modules) in both human and mouse datasets. The extent of derailment in core modules was predictive of survival in the cancer genome atlas (TCGA) liver cancer dataset. We identified module eigengene quantitative trait loci (module-eQTL) for these predictive co-expression modules, targeting of which may resolve homeostatic perturbations and improve patient outcomes. The framework presented can be used to understand homeostasis at systems levels in pre-clinical models and in humans. A record of this paper's transparent peer review process is included in the supplemental information. © 2021 The Authors
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