A computational model of inflammation reveals crosstalk among energy metabolism, oxidative stress, insulin, and cytokines in hepatocytes during early MASLD progression.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is one of the most prevalent liver disorders, affecting approximately one-third of the global adult population. The disease begins with hepatic fat accumulation (steatosis) and can progress to inflammation, fibrosis, and hepatocellular carcinoma. To elucidate the complex mechanisms underlying MASLD, we have developed a novel mathematical model that integrates glucose and lipid metabolisms, oxidative stress, insulin signaling and insulin resistance, and cytokines functions. We demonstrated that variations in extracellular fatty acid and lactate levels, along with changes in the activities of key glycolytic and triglyceride-synthesizing enzymes observed in actual patients, exert a substantial impact on oxidative stress and subsequent cellular damage. Moreover, this model enabled us to evaluate daily metabolic dynamics associated with protein expression patterns specific to steatotic livers. Importantly, it also allowed simulation of cytokine release from hepatocytes into the bloodstream (autocrine and endocrine effects) and the impact of locally elevated cytokines concentrations derived from immune cells (paracrine effects). Our model revealed the dynamics of the early stages of MASLD progression in response to alterations in blood metabolite levels, hepatic enzyme activities, insulin profiles, and cytokine patterns. Furthermore, we identified specific combinations of these factors that may mitigate hepatic fat accumulation or oxidative stress, highlighting the importance of patient-specificity. This study presents the first mechanistic framework grounded in experimental data to describe the crosstalk among hepatic metabolism, insulin, and cytokines, serving as a powerful tool for elucidating disease mechanisms and developing therapeutic strategies.