Background and Aim: Metabolic dysfunction-associated steatotic liver disease (MASLD) affects approximately one-quarter of the world’s population. MASLD results in substantial morbidity, mortality, and healthcare expenditure. Our aim is to discover metabolomic and proteomic predictors of MASLD, define clinical and molecular features of MASLD in special populations, and describe metabolomic and proteomic predictors of comorbidities including cardiovascular disease in individuals with MASLD.
We plan to phenotype MASLD using hepatic steatosis index and fatty liver index, requiring waist circumference and basic laboratory values.
By utilizing comprehensive UK Biobank data, we aim to address the following research questions:
1) Metabolomics:
a. Can specific blood metabolite profiles predict presence or development of cardiovascular diseases in individuals with MASLD?
b. Can specific blood metabolite profiles predict MASLD in high-risk populations including people with HIV?
2) Proteomics:
a. Can specific plasma proteomic signatures predict the presence of hepatic steatosis?
b. Which proteomic markers can robustly predict liver-related events independently or in conjunction with other clinical data?
c. Can plasma proteomic signatures predict cardiovascular disease in individuals with MASLD?
3) Clinical Data:
a. How effectively can integrated models that combine clinical and proteomic data predict the presence of hepatic steatosis compared to traditional risk factors alone?