Comprehensive analysis of endoplasmic reticulum-related and secretome gene expression profiles in the progression of non-alcoholic fatty liver disease

Spatial and Single-Cell Transcriptomics Reveals the Regional Division of the Spatial Structure of MASH Fibrosis

OBJECTIVE

To elucidate the regional distribution of metabolic dysfunction-associated steatohepatitis (MASH) fibrosis within the liver and to identify potential therapeutic targets for MASH fibrosis.

METHODS

Liver sections from healthy controls, patients with simple steatosis and MASH patients were analysed using spatial transcriptomics integrated with single-cell RNA-seq.

RESULTS

Spatial transcriptomics analysis of liver tissues revealed that the fibrotic region (Cluster 9) was primarily distributed in lobules, with some fibrosis also found in the surrounding area. Integration of the single-cell-sequencing data set (GSE189175) showed a greater proportion of inflammatory cells (Kupffer cells and T cells) and myofibroblasts in MASH. Six genes, showing high- or low-specific expression in Cluster 9, namely, ADAMTSL2, PTGDS, S100A6, PPP1R1A, ASS1 and G6PC, were identified in combination with pathology. The average expression levels of ADAMTSL2, PTGDS and S100A6 on the pathological HE staining map were positively correlated with the increase in the degree of fibrosis and aligned strongly with the distribution of fibrosis. ADAMTSL2+ myofibroblasts play a role in TNF signalling pathways and in the production of ECM structural components. Pseudotime analysis indicated that in the early stages of MASH, infiltration by T cells and Kupffer cells triggers a significant inflammatory response. Subsequently, this inflammation leads to the activation of hepatic stellate cells (HSCs), transforming them into myofibroblasts and promoting the development of liver fibrosis.

CONCLUSION

This study is the first to characterise lineage-specific changes in gene expression, subpopulation composition, and pseudotime analysis in MASH fibrosis and reveals potential therapeutic targets for this condition.

SR-A3 suppresses AKT activation to protect against MAFLD by inhibiting XIAP-mediated PTEN degradation

Scavenger receptor class A member 3 (SR-A3) is implicated in metabolic diseases; however, the relationship between SR-A3 and metabolic dysfunction-associated fatty liver disease (MAFLD) has not been documented. Here, we show that hepatic SR-A3 expression is significantly reduced in human and animal models in the context of MAFLD. Genetic inhibition of SR-A3 in hamsters elicits hyperlipidemia, hyperglycemia, insulin resistance, and hepatic steatosis under chow-diet condition, yet escalates in diet-induced MAFLD. Mechanistically, SR-A3 ablation enhances E3 ligase XIAP-mediated proteasomal ubiquitination of PTEN, leading to AKT hyperactivation. By contrast, hepatic overexpression of human SR-A3 is sufficient to attenuate metabolic disorders in WT hamsters fed a high-fat-high-cholesterol diet and ob/ob mice via suppressing the XIAP/PTEN/AKT axis. In parallel, pharmacological intervention by PTEN agonist oroxin B or lipid lowering agent ezetimibe differentially corrects MAFLD in hamsters.

Pemigatinib suppresses liver fibrosis and subsequent osteodystrophy in mice

BACKGROUND

Liver fibrosis could lead to serious secondary diseases, including osteodystrophy. The interaction between liver and bone has not been fully elucidated, thus existing therapies for osteodystrophy secondary to liver fibrosis are often ineffective. FGF23 was initially found as an endocrine regulator of phosphate homeostasis, but recently, its involvement in fibrosis has been suggested. In this study, we hypothesized that the FGF23 level increases with liver injury, which in turn induces liver fibrosis and osteodystrophy.

METHODS

Liver fibrosis model mice were generated via carbon tetrachloride administration and bile duct ligation. Fibrosis was assessed using Masson trichrome staining and hydroxyproline assay. The bone structure was evaluated using dual-energy x-ray absorptiometry and microcomputed tomography. Human HSC lines LX-2 and primary rat HSCs were used for in vitro analyses.

RESULTS

Carbon tetrachloride-induced and bile duct ligation-induced liver injury increased the serum FGF23 level compared with that in control mice. RNA sequencing analysis of FGF23-treated LX-2 showed that FGF23 promotes the production of matrisome, which helps in forming the extracellular matrix. The FGF receptor antagonist pemigatinib alleviated carbon tetrachloride-induced and bile duct ligation-induced liver fibrosis and the deleterious alterations in bone density and microstructure in mice.

CONCLUSIONS

The serum FGF23 level increased with liver injury, and FGF23 promoted liver fibrosis. Moreover, pemigatinib alleviated liver fibrosis and hepatic osteodystrophy. These findings suggest that FGF23 mediates the communication between the liver and bone and that FGF23 may be a new therapeutic target for liver fibrosis and subsequent osteodystrophy.

Multiple Machine Learning Identifies Key Gene PHLDA1 Suppressing NAFLD Progression

Non-alcoholic fatty liver disease (NAFLD) poses a serious global health threat, with its progression mechanisms not yet fully understood. While several molecular markers for NAFLD have been developed in recent years, a lack of robust evidence hampers their clinical application. Therefore, identifying novel and potent biomarkers would directly aid in the prediction, prevention, and personalized treatment of NAFLD. We downloaded NAFLD-related datasets from the Gene Expression Omnibus (GEO). Differential expression analysis and functional analysis were initially conducted. Subsequently, Weighted Gene Co-expression Network Analysis (WGCNA) and multiple machine learning strategies were employed to screen and identify key genes, and the diagnostic value was assessed using Receiver Operating Characteristic (ROC) analysis. We then explored the relationship between genes and immune cells using transcriptome data and single-cell RNA sequencing (scRNA-seq) data. Finally, we validated our findings in cell and mouse NAFLD models. We obtained 23 overlapping differentially expressed genes (DEGs) across three NAFLD datasets. Enrichment analysis revealed that DEGs were associated with Apoptosis, Parathyroid hormone synthesis, secretion and action, Colorectal cancer, p53 signaling pathway, and Biosynthesis of unsaturated fatty acids. After employing machine learning strategies, we identified one gene, pleckstrin homology like domain family A member 1 (PHLDA1), downregulated in NAFLD and showing high diagnostic accuracy. CIBERSORT analysis revealed significant associations of PHLDA1 with various immune cells. Single-cell data analysis demonstrated downregulation of PHLDA1 in NAFLD, with PHLDA1 exhibiting a significant negative correlation with macrophages. Furthermore, we found PHLDA1 to be downregulated in an in vitro hepatic steatosis cell model, and overexpression of PHLDA1 significantly reduced lipid accumulation, as well as the expression of key molecules involved in hepatic lipogenesis and fatty acid uptake, such as FASN, SCD-1, and CD36. Additionally, gene set enrichment analysis (GSEA) pathway enrichment analysis suggested that PHLDA1 may influence NAFLD progression through pathways such as Cytokine Cytokine Receptor Interaction, Ecm Receptor Interaction, Parkinson's Disease, and Ribosome pathways. Our conclusions were further validated in a mouse model of NAFLD. Our study reveals that PHLDA1 inhibits the progression of NAFLD, as overexpression of PHLDA1 significantly reduces lipid accumulation in cells and markedly decreases the expression of key molecules involved in liver lipogenesis and fatty acid uptake. Therefore, PHLDA1 may emerge as a novel potential target for future prediction, diagnosis, and targeted prevention of NAFLD.

Identification and validation of hub genes expressed in ulcerative colitis with metabolic dysfunction-associated steatotic liver disease

Objective

Ulcerative colitis (UC) and metabolic dysfunction-associated steatotic liver disease (MASLD) are closely intertwined; however, the precise molecular mechanisms governing their coexistence remain unclear.

Methods

We obtained UC (GSE75214) and MASLD (GSE151158) datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were acquired by the 'edgeR' and 'limma' packages of R. We then performed functional enrichment analysis of common DEGs. Hub genes were selected using the cytoHubba plugin and validated using GSE87466 for UC and GSE33814 for MASLD. Immunohistochemistry was employed to validate the hub genes' expression in clinical samples. Immune infiltration and gene set enrichment analyses of the hub genes were performed. Finally, we estimated the Spearman's correlation coefficients for the clinical correlation of the core genes.

Results

Within a cohort of 26 differentially regulated genes in both UC and MASLD, pathways involving cytokine-mediated signaling, cell chemotaxis, and leukocyte migration were enriched. After further validation, CXCR4, THY1, CCL20, and CD2 were identified as the hub genes. Analysis of immune infiltration patterns highlighted an association between elevated pivotal gene expression and M1 macrophage activation. Immunohistochemical staining revealed widespread expression of pivotal genes in UC- and MASLD-affected tissues. Furthermore, significant correlations were observed between the increased expression of hub genes and biochemical markers, such as albumin and prothrombin time.

Conclusion

This bioinformatics analysis highlights CXCR4, THY1, CCL20, and CD2 as crucial genes involved in the co-occurrence of UC and MASLD, providing insights into the underlying mechanisms of these two conditions.

Identification of Basement Membrane Genes and Related Molecular Subtypes in Nonalcoholic Fatty Liver Disease

Basement membranes (BMs) are widely distributed and highly specialized extracellular matrix (ECM). The goal of this study was to explore novel genes associated with nonalcoholic fatty liver disease (NAFLD) from the perspective of BMs. Sequencing results of 304 liver biopsy samples about NAFLD were systematically obtained from the Gene Expression Omnibus (GEO) database. Biological changes during NAFLD progression and hub BM-associated genes were investigated by differential gene analysis and weighted gene co-expression network analysis (WGCNA), respectively. The nonalcoholic steatohepatitis (NASH) subgroups were identified based on hub BM-associated genes expression, as well as the differences in Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways and immune microenvironment between different subgroups were compared. Extracellular matrix (ECM) seems to play an important role in the development of NAFLD. Three representative BM-associated genes (ADAMTS2, COL5A1, and LAMC3) were finally identified. Subgroup analysis results suggested that there were significant changes in KEGG signaling pathways related to metabolism, extracellular matrix, cell proliferation, differentiation, and death. There were also changes in macrophage polarization, neutrophils, and dendritic cells abundance, and so on. In conclusion, the present study identified novel potential BM-associated biomarkers and further explored the heterogeneity of NASH that might provide new insights into the diagnosis, assessment, management, and personalized treatment of NAFLD.

Integrative network-based analysis on multiple Gene Expression Omnibus datasets identifies novel immune molecular markers implicated in non-alcoholic steatohepatitis

Introduction

Non-alcoholic steatohepatitis (NASH), an advanced subtype of non-alcoholic fatty liver disease (NAFLD), has becoming the most important aetiology for end-stage liver disease, such as cirrhosis and hepatocellular carcinoma. This study were designed to explore novel genes associated with NASH.

Methods

Here, five independent Gene Expression Omnibus (GEO) datasets were combined into a single cohort and analyzed using network biology approaches.

Results

11 modules identified by weighted gene co-expression network analysis (WGCNA) showed significant association with the status of NASH. Further characterization of four gene modules of interest demonstrated that molecular pathology of NASH involves the upregulation of hub genes related to immune response, cholesterol and lipid metabolic process, extracellular matrix organization, and the downregulation of hub genes related to cellular amino acid catabolic, respectively. After DEGs enrichment analysis and module preservation analysis, the Turquoise module associated with immune response displayed a remarkably correlation with NASH status. Hub genes with high degree of connectivity in the module, including CD53, LCP1, LAPTM5, NCKAP1L, C3AR1, PLEK, FCER1G, HLA-DRA and SRGN were further verified in clinical samples and mouse model of NASH. Moreover, single-cell RNA-seq analysis showed that those key genes were expressed by distinct immune cells such as microphages, natural killer, dendritic, T and B cells. Finally, the potential transcription factors of Turquoise module were characterized, including NFKB1, STAT3, RFX5, ILF3, ELF1, SPI1, ETS1 and CEBPA, the expression of which increased with NASH progression.

Discussion

In conclusion, our integrative analysis will contribute to the understanding of NASH and may enable the development of potential biomarkers for NASH therapy.