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The functional diversity in factors identified in association withnon-alcoholic fatty liver disease (NAFLD) necessitates the utilization ofholistic approaches to investigate the network properties of NAFLDpathogenesis. We describe the generation of the first mouse-specificmulti-tissue metabolic model, the SteatoNet, to investigate NAFLD-relatedsteatosis, by utilising an object-oriented modelling approach and incorporatingnumerous hepatic metabolic pathways, their interaction with peripheral tissuesand hierarchical feedback regulation at the transcriptional andpost-translational level. The unique validated model is based on steady-stateanalysis of ordinary differential equations that allows investigation ofsystemic behaviour in the absence of estimated kinetic parameters. Modelanalysis indicated the importance of the metabolic flux distribution parameterin controlling metabolite concentration and identified critical focal points inthe network that may play a pivotal role in initiating NAFLD. Albeit requiringexperimental validation, the candidate triggers identified by SteatoNet provideinsight into the network properties of NAFLD and emphasize the promising scopeand potential of SteatoNet as a primary investigative tool for hypothesesgeneration and exploring related metabolic diseases.

SteatoNet- Modelling steatosis identifies candidate systemic flux distribution deregulations