Omics-based Decoding of Metabolic Dysfunction-associated Fatty Liver Disease: From Pathogenesis to Clinical Translation

Abstract

Metabolic dysfunction-associated fatty liver disease (MAFLD) is a multifactorial disorder driven by complex interactions among genetic, epigenetic, transcriptional, proteomic, metabolic, and microbiome factors. Single-omics technologies have provided valuable insights into disease mechanisms, yet each layer captures only a partial view of MAFLD pathogenesis. Recent advances in multi-omics integration allow systematic dissection of molecular networks, cell differentiation trajectories, intercellular communication, and spatial organization, revealing causal links between molecular alterations and tissue phenotypes. Horizontal integration connects different omic layers within the same biological state, while longitudinal integration captures dynamic changes across disease stages. Emerging spatial transcriptomics, proteomics, and metabolomics techniques further enable in situ mapping of cellular and molecular heterogeneity, uncovering spatially defined pathogenic niches and regulatory hubs. Collectively, these integrated approaches offer a multidimensional framework for understanding MAFLD progression, identifying potential biomarkers, and guiding precision therapeutic strategies. Future efforts should focus on standardized multi-omics pipelines, interdisciplinary collaboration, and functional validation to translate these insights into clinical applications.