Background
Chronic liver disease represents a growing global health challenge, affecting millions of patients worldwide and serving as a leading cause of morbidity and mortality. Our previous research discovered genes which give survival advantages to liver cells. How these genes influence liver biology and contribute to the progression of disease in patients remains a major unknown.
Novelty and Importance
The promise of precision medicine will be largely reliant on uncovering the relationships between different patient genotypes and clinical data to stratify patients and design bespoke treatments. This project represents a pioneering approach to precision medicine in liver disease by devising a secure data integration platform to combine deep multi-omics profiling and large-scale longitudinal Electronic Health Records (EHR). This interdisciplinary approach will enable the identification of patient subgroups with distinct molecular signatures, informing targeted therapeutic strategies and biomarker development.
Aims and Objectives
The project will generate highly curated single cell and spatial genomics datasets from patient biopsies. Working with the Cogstack team, relevant EHR data will be converted via the Observational Medical Outcomes Partnership (OMOP) Common Data Model enabling standardised analysis. Patient cohorts will be stratified to identify over-represented clinical features and disease progression patterns, using objective metrics such as the fibrosis score. Key project objectives include: (1) risk stratification of patients with liver disease using standardised clinical metrics and progression rates, (2) identification of representative patient cohorts for comprehensive multi-omics profiling and (3) integration of genomic variants and transcriptomic signature data to define novel molecular disease subtypes.