Spatial Metabolomics for Deciphering Immune–Metabolic Niches Driving Fibrosis Progression in Metabolic Dysfunction–Associated Steatotic Liver Disease.

Background:
Metabolic dysfunction-associated steatotic liver disease (MASLD) affects nearly one-third of adults worldwide and is the leading cause of chronic liver disease. Progression to metabolic dysfunction-associated steatohepatitis (MASH) is characterized by inflammation and fibrosis, with fibrosis stage being the strongest predictor of adverse clinical outcomes. Conventional metabolomics cannot resolve metabolic heterogeneity within liver tissue. Spatial metabolomics, particularly mass spectrometry imaging (MSI), enables in situ mapping of metabolites while preserving tissue architecture, providing new insight into localized metabolic remodeling during fibrogenesis.

Methods:
A structured evidence synthesis of studies published between 2022 and 2026 was conducted. Primary studies using imaging MSI, spatial multi-omics and integrated transcriptomics in MASLD were critically reviewed. No original experimental data were generated.

Results:
Recent studies show that fibrosis develops within distinct immune metabolic niches rather than uniformly across the liver. Spatial MSI identified localized accumulation of very long chain phospholipids and oxidative lipid species in fibrotic regions. Spatial lipidomics further demonstrated zonal redistribution of triglycerides, sphingolipids, ceramides, and fatty acids during MASH progression, particularly in periportal fibrotic areas. Integrated spatial analyses revealed close association between activated hepatic stellate cells, endothelial cells, extracellular matrix remodeling, and lipid-associated macrophages. Additional findings include altered bile acid and amino acid metabolism, oxidative stress and ferroptosis-related lipid remodeling. However, most studies remain limited by small cohorts, restricted metabolite coverage and limited clinical validation.

Discussion:
Current evidence supports spatially organized immune metabolic interactions as drivers of fibrosis progression. Integrating spatial metabolomics with single-cell and spatial transcriptomics may improve mechanistic understanding, but standardized analytical workflows and larger longitudinal studies are needed.

Conclusion:
Spatial metabolomics provides a promising framework for investigating fibrosis-associated metabolic remodeling in MASLD. Although disease-specific metabolic niches have emerged as potential biomarker candidates, their translation into precision medicine requires rigorous validation in well-designed clinical studies.