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
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AI plain-English summaryOne 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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