Active Digestion, Kidneys & Other Organs Brain & Nervous System

halt-RONIN: Discovering chronic inflammation biomarkers that define key stages in the Healthy-to-NASH (non-alcoholic steatohepatitis) transition to inform early prevention and treatment strategies

In plain English

AI plain-English summary

One in four people worldwide carry a silent liver condition that can turn into an incurable inflammatory disease, yet doctors have no reliable way to predict who will progress. Non-alcoholic fatty liver disease (NAFLD) starts as harmless fat buildup but can escalate to non-alcoholic steatohepatitis (NASH)—a severe inflammatory stage that causes liver scarring, cancer, and organ failure. The transition is poorly understood because existing lab models fail to capture human disease complexity. This project combines data from advanced cell and animal models with thousands of human patient samples, then applies machine learning to identify molecular biomarkers that mark each stage of the health-to-disease transition. If successful, Halt-RONIN will produce a diagnostic blueprint that distinguishes early fatty liver from dangerous NASH using simple blood tests. This would allow doctors to intervene with lifestyle changes or targeted drugs before irreversible damage occurs, and give pharmaceutical companies validated molecular targets for new treatments. The work is primarily fundamental science—uncovering the mechanistic drivers of a poorly understood disease process—but its direct output is a practical tool for earlier detection and personalised prevention strategies in a condition that currently has no approved therapies.

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Non-alcoholic fatty liver disease (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). Despite the severe negative impact of the disease on society, NAFLD remains difficult to diagnose and treat. Additionally, the molecular mechanisms underlying the transition from health to fatty liver to NASH 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 NAFLD. To achieve this goal, Halt-RONIN will combine experimental data from advanced in vitro and in vivo models with multimodal data from extensive human NAFLD 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 no project summary

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Related Research

Grants with similar aims, by meaning.

Discovering chronic inflammation biomarkers that define key stages in the Healthy-to-NASH (non-alcoholic steatohepatitis) transition to inform early prevention and treatment strategies
Investigating the inflammation-driven health-to-disease phase in the NAFLD-to-NASH transition
new statistical methodologies and 'big data' analysis strategies in NAFL and NASH
Multi-modal non-invasive biomarker screening for high-risk undiagnosed liver disease
Novel approach to model Non-Alcoholic Fatty Liver Disease using human Pluripotent Stem Cells.

Original classification

EU-Funded

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