Omics-derived signatures in metabolic dysfunction-associated steatotic liver disease: from molecular characterization to clinical translation.
- 1Department of Hepatobiliary and Pancreatic Surgery, General Surgery Center, the First Hospital of Jilin University, Changchun, Jilin, China.
- 2Department of Hepatology and Gastroenterology, Charité-Universitätsmedizin Berlin, Campus Virchow-Klinikum (CVK) and Campus Charité Mitte (CCM), Berlin, Germany.
Abstract
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent systemic metabolic disorder with heterogeneous clinical trajectories. Although liver biopsy remains the histological reference standard, its invasiveness and limited scalability restrict routine use, while established non-invasive tests mainly capture fibrosis-related structural changes and provide limited insight into molecular heterogeneity, active steatohepatitis and early fibrotic transition. Multi-omics technologies offer a mechanistically informed framework for resolving this heterogeneity. In this Review, we summarize recent advances in genomic, transcriptomic, single-cell and spatial, proteomic, lipidomic and metabolomic signatures and candidate biomarkers in MASLD. Genomic studies define inherited susceptibility and risk enrichment, whereas transcriptomic and spatial approaches reveal disease-associated pathways, cell states and tissue niches. Proteomics provides blood-accessible signals of steatohepatitis activity, matrix remodelling and systemic metabolic risk, while lipidomics and metabolomics capture lipotoxic lipid composition, mitochondrial stress, bile acid dysregulation and gut-liver metabolic perturbation. We further discuss how integrative multi-omics, systems biology and artificial intelligence can organize high-dimensional molecular data into disease modules, molecular subtypes, biomarker signatures and candidate therapeutic nodes. In addition, omics-informed studies of bioactive compounds and precision nutrition illustrate how nutritional modulation may be evaluated through molecular response profiles. Despite promising progress, most omics-derived biomarkers remain limited by cohort specificity, platform dependence, incomplete external validation and unclear clinical thresholds. Future translation will require longitudinal, spatially resolved and clinically anchored integration to support risk stratification, at-risk metabolic dysfunction-associated steatohepatitis detection, fibrosis assessment, treatment-response prediction and precision medicine in MASLD.
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BibTeX
@article{qin2026omicsderived,
title = {{Omics-derived signatures in metabolic dysfunction-associated steatotic liver disease: from molecular characterization to clinical translation.}},
author = {Ziyang Qin and Dulguun Juramt and Yuguo Chen and Yunyi Li and Jiaqi Wei and Hongyu Yang and Lanlan Chen and Wei Qiu},
journal = {Frontiers in medicine},
year = {2026},
month = oct,
doi = {10.3389/fmed.2026.1946657},
url = {https://europepmc.org/article/MED/42953027},
note = {CC BY},
}
RIS
TY - JOUR
TI - Omics-derived signatures in metabolic dysfunction-associated steatotic liver disease: from molecular characterization to clinical translation.
AU - Ziyang Qin
AU - Dulguun Juramt
AU - Yuguo Chen
AU - Yunyi Li
AU - Jiaqi Wei
AU - Hongyu Yang
AU - Lanlan Chen
AU - Wei Qiu
PY - 2026
DA - 2026/10/14
JO - Frontiers in medicine
DO - 10.3389/fmed.2026.1946657
UR - https://europepmc.org/article/MED/42953027
AB - Metabolic dysfunction-associated steatotic liver disease (MASLD) is a highly prevalent systemic metabolic disorder with heterogeneous clinical trajectories. Although liver biopsy remains the histological reference standard, its invasiveness and limited scalability restrict routine use, while established non-invasive tests mainly capture fibrosis-related structural changes and provide limited insight into molecular heterogeneity, active steatohepatitis and early fibrotic transition. Multi-omics technologies offer a mechanistically informed framework for resolving this heterogeneity. In this Review, we summarize recent advances in genomic, transcriptomic, single-cell and spatial, proteomic, lipidomic and metabolomic signatures and candidate biomarkers in MASLD. Genomic studies define inherited susceptibility and risk enrichment, whereas transcriptomic and spatial approaches reveal disease-associated pathways, cell states and tissue niches. Proteomics provides blood-accessible signals of steatohepatitis activity, matrix remodelling and systemic metabolic risk, while lipidomics and metabolomics capture lipotoxic lipid composition, mitochondrial stress, bile acid dysregulation and gut-liver metabolic perturbation. We further discuss how integrative multi-omics, systems biology and artificial intelligence can organize high-dimensional molecular data into disease modules, molecular subtypes, biomarker signatures and candidate therapeutic nodes. In addition, omics-informed studies of bioactive compounds and precision nutrition illustrate how nutritional modulation may be evaluated through molecular response profiles. Despite promising progress, most omics-derived biomarkers remain limited by cohort specificity, platform dependence, incomplete external validation and unclear clinical thresholds. Future translation will require longitudinal, spatially resolved and clinically anchored integration to support risk stratification, at-risk metabolic dysfunction-associated steatohepatitis detection, fibrosis assessment, treatment-response prediction and precision medicine in MASLD.
SN - 2296-858X
ER -