Granular detail about the location and nature of liver cell interactions and the metabolic, inflammatory and fibrogenic pathways driving progressive fibrosis in metabolic dysfunction-associated steatotic liver disease (MASLD) is needed to identify novel therapeutic targets.

We generated Visium spatial transcriptomic data from 33 human liver biopsies across the spectrum of MASLD. Gene expression data were overlaid with histological annotations to integrate spatial molecular and histopathological information, enabling interrogation of disease progression. Differential gene expression, pathway, cellular deconvolution and ligand-receptor interaction analyses were conducted for each annotated anatomical category, with specific protein expression validated using immunohistochemistry staining.

Unsupervised clustering based on gene expression data classified the annotated spots into two main clusters enriched for fibro-inflammatory vs. parenchymal regions. Transcriptomic cellular deconvolution aligned well with manually annotated histopathological features. Fibrotic regions were enriched for genes involved in extracellular matrix/receptor interactions and inflammatory pathways (Benjamini-Hochberg adjusted p values <0.05), underscoring known pathological mechanisms. We also identified immunoglobulin gene induction in late-stage fibrosis, which was spatially associated with a senescence signature, as has previously been reported in aging tissues. Dynamic changes in metabolic gene expression from early to late fibrosis were observed, suggesting MASLD progression is accompanied by a decline in normal liver metabolic function and reprogramming of metabolic fuel utilisation from oxidative to glycolytic metabolism, which may be both a cause and a consequence of senescence.

Taken together, our valuable discovery dataset highlights the complex crosstalk between metabolic perturbations and inflammation underpinning fibrosis progression in MASLD.

Metabolic dysfunction-associated steatotic liver disease (MASLD) has a complex pathogenesis driven by cell and matrix interactions in inflammatory niches. In this study, we identify a senescence signature in fibroinflammatory regions, characterised by high immunoglobulin expression and associated with a shift from oxidative to glycolytic metabolism. We identify spatially co-expressed ligand-receptor pairs, including senescence-associated factors, correlated with progressive fibrosis. This discovery dataset highlights the complex crosstalk between metabolic perturbations and inflammation underpinning fibrosis progression in MASLD and lays the groundwork for future research into the role of senescence in MASLD.