Chronic liver diseases (CLD), including MASLD/MASH, alcohol-related liver disease, viral hepatitis, autoimmune liver diseases, and cholestatic disorders, represent a major global health burden. Despite advances in therapeutics and non-invasive diagnostics, clinical management remains challenged by substantial inter-individual variability in disease progression, treatment response, and risk of complications such as cirrhosis and hepatocellular carcinoma (HCC). Traditional staging systems and biochemical markers often fail to capture the biological heterogeneity underlying these conditions. In recent years, rapid developments in multi-omics technologies, circulating biomarkers, advanced imaging modalities, and artificial intelligence (AI)-based modeling have opened new avenues toward precision hepatology. These innovations are reshaping our understanding of disease mechanisms and offering opportunities for improved patient stratification and personalized therapeutic approaches.
The goal of this Research Topic is to address the need for clinically applicable precision medicine tools in chronic liver disease. While numerous biomarkers and predictive models have been proposed, their integration into routine care remains limited due to insufficient validation, lack of standardization, and gaps between translational research and real-world implementation.
This collection aims to gather high-quality evidence that advances risk stratification, early detection of progressive disease, prediction of treatment response, and identification of patients at high risk for decompensation or HCC. Particular emphasis will be placed on studies that bridge molecular discoveries and clinical applicability, including multi-omics integration, non-invasive biomarkers, digital health tools, and AI-driven prediction models.
By fostering interdisciplinary contributions—from basic science to clinical and computational research—this Research Topic seeks to promote scalable, reproducible, and patient-centered precision approaches capable of transforming the management of chronic liver disease across diverse healthcare settings.
This Research Topic welcomes contributions addressing precision medicine approaches in chronic liver disease, including but not limited to:
-Genomic, transcriptomic, proteomic, metabolomic, and multi-omics biomarkers. -Non-invasive biomarkers of fibrosis, inflammation, and disease progression. -Liquid biopsy and circulating biomarkers. -Imaging biomarkers, radiomics, and digital pathology. -AI-based risk prediction and patient stratification tools. -Biomarkers predicting therapeutic response in MASLD/MASH, ALD, viral hepatitis, and autoimmune liver diseases. -Risk prediction models for cirrhosis complications and HCC. -Real-world validation and implementation studies.
We welcome Original Research Articles, Systematic Reviews, Meta-Analyses, Narrative Reviews, Brief Research Reports, and Translational Studies that provide mechanistic insights or demonstrate clinical applicability.
Article types and fees
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Brief Research Report
Case Report
Classification
Clinical Trial
Community Case Study
Conceptual Analysis
Curriculum, Instruction, and Pedagogy
Data Report
Editorial
Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.
Article types
This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:
Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.