Abstract
BACKGROUND & AIMS: Metabolic-associated steatotic liver disease (MASLD) is among the most prevalent liver disorders worldwide, with many patients progressing to metabolic-associated steatohepatitis (MASH) characterized by fibrosis and inflammation. The current lack of effective treatments for MASH highlights the urgent need to deepen our understanding of its underlying mechanisms. Examining cellular dynamics - specifically, changes in cell type proportions across disease stages - offers a promising avenue for gaining such insights. However, previous deconvolution analyses have been limited to a few cell types, and a comprehensive analysis encompassing diverse cell populations and their unique subtypes has yet to be conducted. METHODS: In this study, we employed MuSiC deconvolution to analyze two bulk RNA sequencing datasets spanning the MASL to MASH spectrum across both fibrosis staging and Non-Alcoholic Fatty Liver Disease Activity Score (NAS) staging. RESULTS: Our analysis reveals distinct proportional trends in 10 different cell types, including hepatocytes, cholangiocytes, two subpopulations of hepatic stellate cells, endothelial cells, and immune cells such as kupffer cells, TREM2+ macrophages, and plasma B cells. In addition to deconvolution analysis, we integrated cell type proportion data with transcriptomic profiles, significantly enhancing the performance of random forest models in classifying fibrosis stages compared to using transcriptomic data alone. CONCLUSIONS: The study's findings highlight critical cellular dynamic changes across MASLD progression, advancing our understanding of the disease mechanisms and potentially informing the development of more effective therapeutic strategies.