MegaMASLD: An interactive platform for exploring stratified transcriptomic signatures in MASLD progression

Abstract

Liver transcriptomic data from patients with metabolic dysfunction-associated steatotic liver disease (MASLD) offers valuable resource for deciphering pathogenic molecular drivers. Here, we performed a Mega-analysis of MASLD Liver Transcriptomes (MegaMASLD) which reanalysed raw RNAseq data of over 800 livers in a standardized and integrative manner, aiming to unravel druggable molecular events in MASLD. Our analysis revealed a progressive transcriptomic shift predominantly associated with immunopathologies during MASLD progression. The differential transcriptomes produced a MASLD gene signature useful for quantitative assessment of MASLD severity but failed to faithfully recapitulate the exact histological staging. Instead, a histologic-independent unsupervised clustering analysis predicted a high-risk group prone to develop metabolic dysfunction-associated steatohepatitis (MASH), characterized by aberrant changes in humoral immune response and antibody repertoires. These findings were supported by another histologic-independent pseudotime analysis, which also identified several potentially targetable molecular switches, including FGFR, PDGFR, PAK, PRKG1 and CAMK kinase families, activated at various transitory phases of MASLD. The robust analysis has enabled risk stratification and deepened our understanding of the dynamic molecular events driving MASLD, thereby offering new options to enhance precision medicine of MASLD. An online web tool featuring MegaMASLD is available at https://bioanalytics-hs.shinyapps.io/MegaMASLD/.