Aging reshapes body-fat distribution and the immune-metabolic environment. Brown adipose tissue (BAT) and subcutaneous fat regulate thermogenesis and energy expenditure, whereas visceral adipose tissue (VAT) promotes chronic inflammation and metabolic decline. Genetic determinants likely influence adipose redistribution, the systemic immunometabolic profile, and progression to hepatic steatosis, advanced fibrosis, cirrhosis, and hepatocellular carcinoma (HCC).
This project aims to define the genetic and molecular determinants of age-related adipose redistribution and their contribution to hepatic and systemic metabolic risk. We will integrate multilayer data, including genome-wide and exome-wide association studies, polygenic scores, high-coverage proteomics, metabolomics (NMR and LC-MS), and compositional imaging using DEXA to assess regional fat and lean mass, and MRI to quantify hepatic fat fraction, visceral and subcutaneous adipose volumes, hepatic iron, and ectopic lipid content. These data will be complemented by routine biochemistry, cytokine panels, and immune profiling.
The research will characterise trajectories of adiposity subtypes derived from anthropometric, proteomic, metabolomic, and imaging measures that define high hepatic-risk phenotypes across aging. It will evaluate how genetic variation in thermogenic and lipid metabolism pathways modifies associations between adiposity patterns, molecular signatures, and imaging phenotypes over time. It will then develop and validate a multilayer predictive model integrating genetics, clinical measures, proteomics, metabolomics, imaging, and immune data to improve prediction of hepatic disease progression. The project aims to enable longitudinal monitoring of systemic and hepatic adipose redistribution and to generate clinically usable predictive models for referral and surveillance.