Metabolic-dysfunction associated liver disease (MASLD, before NAFLD), is a multifactorial chronic inflammatory disease that is prevalent in 1 of 4 individuals with a significant personal, socioeconomic and healthcare burden, especially at the later, more severe inflammatory stage of disease - non alcoholic steatohepatitis (NASH) or MASH. Despite the severe negative impact of the disease on society, MASLD remains difficult to diagnose and treat. The molecular mechanisms underlying the transition from health to fatty liver to MASH remain poorly understood due to the lack of models that faithfully reflect the complexity of human disease. Hence, Halt-RONIN aims to uncover the early triggers of disease initiation and complex mechanistic drivers of disease progression by implementing a systems biology approach with integrative disease modelling resulting in opportunities for the improvement of the existing detection methods, providing a blueprint to inform personalized intervention strategies and drug discovery for MASLD. To achieve this goal, Halt-RONIN will combine experimental data from advanced in vitro and in vivo models with multimodal data from extensive human MAFLD cohorts and biobanks and use in silico machine learning approaches, to discover new biomarkers and molecular targets specific to each stage of the health-to-disease transition. By validating preclinical experimental findings with real-world data, Halt-RONIN will allow for the discovery of novel biomarkers and molecular targets that are specific to the individual patient’s pathology. Consequently, healthcare professionals will gain the tools and knowledge required to diagnose and establish guidelines for the prevention and treatment of inflammation-driven health to disease. As such, in the long-term Halt-RONIN will decrease the number of MAFLD patients who progress into MASH and provide disease-modifying strategies to improve patient outcomes.
