The etiological risk factors for hepatocellular carcinoma (HCC) and its precursor lesion (cirrhosis) in the US have dramatically changed in the past decade from predominantly active chronic viral hepatitis (hepatitis B and C) to Metabolic (dysfunction) Associated Fatty Liver Disease (MAFLD). Given the high prevalence of the metabolic disorders (e.g., obesity and diabetes) that define MAFLD and their chronic incurable nature, the focus on HCC prevention related to MAFLD is paramount. Prevention of HCC requires better understanding of the determinants of this risk, and the consequent construction of models and tools for risk stratification. We propose to leverage data, biospecimens and infrastructure of the Texas HCC Consortium (THCCC) Cohort, the largest US-based active prospective cohort study of cirrhosis patients, of whom 80% is estimated to have MAFLD. We propose expanding and extending the follow-up of the THCCC cohort to >5000 patients with >350 incident HCC cases. Our study in Project 1 has the following Specific Aims: 1. Identify metabolic risk factors for HCC in a large contemporary prospective cohort of patients with cirrhosis. We will examine associations of existing and novel metabolic candidate markers including (1) MAFLD phenotypic features: body mass index, waist-to-hip ratio, triglyceride level, HDL cholesterol level, diabetes, and markers of insulin resistance, (2) select novel metabolic biomarker candidates identified using metabolomic and lipidomic assays of samples from a discovery case-control study nested within THCCC, and (3) suspected molecular markers of metabolic dysfunction (e.g., serum adipokines level, pro/anti-inflammatory cytokines). 2. Identify demographic, lifestyle features, genetic risk factors, and liver imaging markers associated with the risk of developing HCC among patients with cirrhosis. We will examine associations of the risk of HCC with candidate risk factors/markers i.e., (1) demographic (age, race/ethnicity, sex) and lifestyle (smoking, physical activity) features, (2) a polygenic risk score based on established genetic markers of MAFLD (PNPLA3, TM6SF3, MBOAT7, NCAN, PP1R3B), and (3) novel quantitative imaging markers of body fat (skin-to-liver- capsule distance) and liver fat (hepatorenal index) estimated from radiomic analyses of liver ultrasound images. 3. Develop and optimize adaptive risk indices for predicting risk of progression to HCC among patients with cirrhosis. We will develop a set of adaptive models including (a) a ‘basic’ index that combines demographic and lifestyle predictors with phenotypic metabolic predictors, (b) add blood-based markers (e.g., a polygenic risk score, metabolic risk score) to the ‘basic’ index, and (c) add liver ultrasound radiomics indices. We will assess the performance characteristics of the risk prediction indices The risk prediction index will have important translational implications to the comparative cost effectiveness of HCC prevention (e.g., chemopreventio...