A multimodal approach to stratification and prognostication in metabolic dysfunction-associated steatotic liver disease (MASLD)

Over the next 3.5-years, I will be adopting a hybrid experimental-computational approach to stratify patients with metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD).

Affecting more than 1 in 3 adults, MASLD is a leading cause of liver-related morbidity and mortality worldwide. MASLD is particularly challenging to study due to its complex pathogenesis, associated comorbidities, and heterogeneous progression to clinical outcomes. Clinical phenotypes in MASLD are likely shaped by a variable mix of genetic, environmental, and immunological factors, and further modified by associated comorbidities and polypharmacy.

Overall, patients experience very different disease trajectories, but we currently lack biomarkers to categorise them and offer personalised clinical care.

Exploiting SteatoSITE (a retrospective multimodal MASLD database comprised of 940 histologically-defined patients covering the complete disease severity spectrum) and additional external validation cohorts, I plan to develop tissue and circulating biomarkers to define novel MASLD sub-phenotype(s) at risk of hepatic or extra-hepatic adverse clinical outcomes. To achieve this, I will use a range of techniques including tissue characterisation (e.g., multiplex immunohistochemistry, spatial transcriptomics), measurement of serum markers, and bioinformatics/risk prediction modelling.

These results will pave the way for early and effective patient stratification and disease prognostication, as well as uncovering actionable therapeutic targets.