An integrated gene-to-outcome multimodal database for metabolic dysfunction-associated steatotic liver disease

Area of Science:

• Hepatology
• Genomics
• Precision Medicine

Background:

• Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease globally.
• MASLD presents a significant challenge for precision medicine due to its complexity and varied severity.
• Existing research lacks comprehensive, integrated datasets for understanding MASLD progression.

Purpose of the Study:

• To establish a national cohort and open resource (SteatoSITE) for MASLD research.
• To identify gene expression signatures and cellular subpopulations associated with MASLD progression and adverse outcomes.
• To develop a predictive tool for hepatic decompensation events in MASLD patients.

Main Methods:

• Retrospective analysis of a national cohort of 940 histologically defined MASLD patients.
• Generation and analysis of hepatic bulk RNA sequencing data from 668 cases and 39 controls.
• Integration of histopathology, transcriptomics, and longitudinal electronic health record data.

Main Results:

• Development of SteatoSITE, a searchable, open resource for MASLD research.
• Identification of disease-stage-specific gene expression signatures and pathogenic hepatic cell subpopulations.
• Construction of a 15-gene transcriptional risk score with high predictive accuracy for hepatic decompensation (AUCs 0.86-0.83).
• Discovery of thyroid hormone receptor beta regulon activity as a suppressor of MASLD progression.

Conclusions:

• The 15-gene risk score offers a promising tool for predicting adverse outcomes in MASLD.
• SteatoSITE serves as a valuable resource for biomarker and drug development in MASLD.
• Findings facilitate precision medicine strategies for managing MASLD patients.