Unmasking insulin resistance triggering mechanisms using microphysiological two-organ systems as in vitro disease models of metabolic syndrome and non-alcoholic fatty liver disease

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Insulin resistance is one of the key factors for non-alcoholic fatty liver disease (NAFLD) and metabolic syndrome development and progression. Both diseases have an immense societal and economic impact. However, the biological mechanisms triggering the onset of the diseases are still poorly understood. NAFLD is assumed to be triggered by hepatic insulin resistance, possibly resulting from adipose tissue lipolysis dysregulation. The study of the crosstalk between liver and adipose tissue is thus essential for the understanding of insulin resistance triggering events but is limited by the availability of suitable models. Hence, the aim of this proposal is to establish a two-organ-on-a-chip-model and to utilize it to study liver-adipose tissue crosstalk and understand how hepatic and adipocyte insulin resistance develop and influence each other. In order to study the molecular mechanisms of inter-tissue communication and overcome the complexity and non-human nature of animal models, an innovative organ-on-a-chip system using a flexible connection technology will be utilized to culture hepatocytes and adipocytes in connected systems. Human stem cell derived adipocyte- and hepatocytes-like cells with the same genetic background will be cultured in this system and characterized regarding their metabolic competence. The cell’s functional characterization, transcriptomic and metabolomic analysis, upon pharmacological induction of insulin resistance, will allow to unravel its molecular triggering mechanisms in vitro. The same approach will be applied to patient-specific cells creating a patient-specific physiopatological in vitro model under distinct nutrient mixtures. This project is a highly innovative multidisciplinary approach that uses organ-on-a-chip technology for in vitro disease modeling to study the triggering molecular mechanisms and possibly identify potential biomarkers and/or pharmacological and non-pharmacological targets of high impact diseases.