biostudies-literatureGonzalez Hernandez MAProvince of South Holland23362https://www.ebi.ac.uk/biostudies/studies/S-EPMC11458909biostudies-literatureUnknown14(1)The incidence of MASLD and MASH-associated fibrosis is rapidly increasing worldwide. Drug therapy is hampered by large patient variability and partial representation of human MASH fibrosis in preclinical models. Here, we investigated the mechanisms underlying patient heterogeneity using a discovery dataset and validated in distinct human transcriptomic datasets, to improve patient stratification and translation into subgroup specific patterns. Patient stratification was performed using weighted gene co-expression network analysis (WGCNA) in a large public transcriptomic discovery dataset (n = 216). Differential expression analysis was performed using DESeq2 to obtain differentially expressed genes (DEGs). Ingenuity Pathway analysis was used for functional annotation. The discovery dataset Scientific reportsIdentifying patient subgroups in MASLD and MASH-associated fibrosis: molecular profiles and implications for drug development.PMC11458909DOS-2020-0008054Morrison MCvan Westen GJPVerschuren LHanemaaijer RCaspers MPMvan den Berg JTCoornaert BGonzalez Hernandez MAVenhorst JfalseIdentifying patient subgroups in MASLD and MASH-associated fibrosis: molecular profiles and implications for drug development.The incidence of MASLD and MASH-associated fibrosis is rapidly increasing worldwide. Drug therapy is hampered by large patient variability and partial representation of human MASH fibrosis in preclinical models. Here, we investigated the mechanisms underlying patient heterogeneity using a discovery dataset and validated in distinct human transcriptomic datasets, to improve patient stratification and translation into subgroup specific patterns. Patient stratification was performed using weighted gene co-expression network analysis (WGCNA) in a large public transcriptomic discovery dataset (n = 216). Differential expression analysis was performed using DESeq2 to obtain differentially expressed genes (DEGs). Ingenuity Pathway analysis was used for functional annotation. The discovery dataset 2024-01-01T00:00:00Z2024 Oct2026-06-01T06:58:15.312Z2025-04-06T22:25:13.143ZS-EPMC114589093937549810.1038/s41598-024-74098-w