Cell-Type Deconvolution Reveals Dynamic Changes in MASLD

Area of Science:

• Hepatology
• Genomics
• Immunology

Background:

• Metabolic-associated steatotic liver disease (MASLD) is a prevalent liver disorder.
• Progression to metabolic-associated steatohepatitis (MASH) involves fibrosis and inflammation, lacking effective treatments.
• Understanding cellular dynamics is crucial for elucidating MASH mechanisms.

Purpose of the Study:

• To conduct a comprehensive analysis of cell type proportions across the MASLD to MASH spectrum.
• To investigate cellular dynamics in relation to fibrosis and Non-Alcoholic Fatty Liver Disease Activity Score (NAS) staging.
• To explore the utility of cell type proportions in improving fibrosis staging classification.

Main Methods:

• Utilized MuSiC deconvolution on two bulk RNA sequencing datasets.
• Analyzed cell type proportions across MASLD and MASH spectrum, including fibrosis and NAS staging.
• Integrated cell type proportion data with transcriptomic profiles for machine learning models.

Main Results:

• Identified distinct proportional trends in 10 cell types, including hepatocytes, cholangiocytes, hepatic stellate cells, endothelial cells, Kupffer cells, TREM2+ macrophages, and plasma B cells.
• Demonstrated that integrating cell type proportions with transcriptomic data significantly enhanced random forest model performance for fibrosis staging.
• Revealed specific cellular dynamics associated with MASLD progression.

Conclusions:

• Cellular dynamics play a critical role in MASLD progression to MASH.
• Comprehensive cell type analysis provides deeper insights into disease mechanisms.
• Findings may inform the development of novel therapeutic strategies for MASH.