Integrative Multi‐Omics Analysis Elucidates the Progressive Disease Landscape and Reveals Dynamic Protein Biomarkers forSurveillance
Source: PubMed Central Open Access, NCBI / U.S. National Library of Medicine
ABSTRACT Metabolic dysfunction‐associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, encompassing a continuum ranging from simple steatosis to steatohepatitis, hepatic fibrosis, and cirrhosis. Despite the complex and heterogeneous pathogenesis, effective therapeutic targets remain elusive. In this study, we sought to identify and validate critical genes implicated in MASLD progression through multi‐omics integration and machine learning algorithms. Analysis revealed considerable activation of lipid metabolism, oxidative stress, and inflammation‐related pathways throughout disease progression, with notable upregulation ofandand downregulation of. These expression patterns were consistently verified across in vivo and in vitro models. Functional assays indicated thatknockdown oroverexpression substantially attenuated hepatocellular lipid accumulation, alleviated oxidative stress and inflammatory responses, and suppressed key lipogenic gene expression. Collectively, these findings elucidate key molecular axes in MASLD progression and provide mechanistic insights and theoretical foundations for the development of targeted therapies. Integrated transcriptomic, single‐cell, pseudotime, cell–cell communication, human tissue, and in vivo analyses define a dynamic four‐gene axis across the MASLD continuum. Progressivedownregulation and,, andupregulation link metabolic dysfunction to disease progression, whileknockdown oroverexpression mitiga
Abstract
ABSTRACT Metabolic dysfunction‐associated steatotic liver disease (MASLD) is the most prevalent chronic liver disease worldwide, encompassing a continuum ranging from simple steatosis to steatohepatitis, hepatic fibrosis, and cirrhosis. Despite the complex and heterogeneous pathogenesis, effective therapeutic targets remain elusive. In this study, we sought to identify and validate critical genes implicated in MASLD progression through multi‐omics integration and machine learning algorithms. Analysis revealed considerable activation of lipid metabolism, oxidative stress, and inflammation‐related pathways throughout disease progression, with notable upregulation ofandand downregulation of. These expression patterns were consistently verified across in vivo and in vitro models. Functional assays indicated thatknockdown oroverexpression substantially attenuated hepatocellular lipid accumulation, alleviated oxidative stress and inflammatory responses, and suppressed key lipogenic gene expression. Collectively, these findings elucidate key molecular axes in MASLD progression and provide mechanistic insights and theoretical foundations for the development of targeted therapies. Integrated transcriptomic, single‐cell, pseudotime, cell–cell communication, human tissue, and in vivo analyses define a dynamic four‐gene axis across the MASLD continuum. Progressivedownregulation and,, andupregulation link metabolic dysfunction to disease progression, whileknockdown oroverexpression mitigates hepatocellular lipid accumulation, oxidative stress, and inflammation. graphical