Identification of Key Genes and Immune Infiltrate in Nonalcoholic Steatohepatitis: A Bioinformatic Analysis

Exposure to PFAS chemicals induces sex-dependent alterations in key rate-limiting steps of lipid metabolism in liver steatosis

Toxicants with the potential to bioaccumulate in humans and animals have long been a cause for concern, particularly due to their association with multiple diseases and organ injuries. Per- and polyfluoro alkyl substances (PFAS) and polycyclic aromatic hydrocarbons (PAH) are two such classes of chemicals that bioaccumulate and have been associated with steatosis in the liver. Although PFAS and PAH are classified as chemicals of concern, their molecular mechanisms of toxicity remain to be explored in detail. In this study, we aimed to identify potential mechanisms by which an acute exposure to PFAS and PAH chemicals can induce lipid accumulation and whether the responses depend on chemical class, dose, and sex. To this end, we analyzed mechanisms beginning with the binding of the chemical to a molecular initiating event (MIE) and the consequent transcriptomic alterations. We collated potential MIEs using predictions from our previously developed ToxProfiler tool and from published steatosis adverse outcome pathways. Most of the MIEs are transcription factors, and we collected their target genes by mining the TRRUST database. To analyze the effects of PFAS and PAH on the steatosis mechanisms, we performed a computational MIE-target gene analysis on high-throughput transcriptomic measurements of liver tissue from male and female rats exposed to either a PFAS or PAH. The results showed peroxisome proliferator-activated receptor (PPAR)-α targets to be the most dysregulated, with most of the genes being upregulated. Furthermore, PFAS exposure disrupted several lipid metabolism genes, including upregulation of fatty acid oxidation genes (Acadm, Acox1, Cpt2, Cyp4a1-3) and downregulation of lipid transport genes (Apoa1, Apoa5, Pltp). We also identified multiple genes with sex-specific behavior. Notably, the rate-limiting genes of gluconeogenesis (Pck1) and bile acid synthesis (Cyp7a1) were specifically downregulated in male rats compared to female rats, while the rate-limiting gene of lipid synthesis (Scd) showed a PFAS-specific upregulation. The results suggest that the PPAR signaling pathway plays a major role in PFAS-induced lipid accumulation in rats. Together, these results show that PFAS exposure induces a sex-specific multi-factorial mechanism involving rate-limiting genes of gluconeogenesis and bile acid synthesis that could lead to activation of an adverse outcome pathway for steatosis.

Metabolic Dysfunction-Associated Steatotic Liver Disease in a Dish: Human Precision-Cut Liver Slices as a Platform for Drug Screening and Interventions

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a growing healthcare problem with limited therapeutic options. Progress in this field depends on the availability of reliable preclinical models. Human precision-cut liver slices (PCLSs) have been employed to replicate the initiation of MASLD, but a comprehensive investigation into MASLD progression is still missing. This study aimed to extend the current incubation time of human PCLSs to examine different stages in MASLD. Healthy human PCLSs were cultured for up to 96 h in a medium enriched with high sugar, high insulin, and high fatty acids to induce MASLD. PCLSs displayed hepatic steatosis, characterized by accumulated intracellular fat. The development of hepatic steatosis appeared to involve a time-dependent impact on lipid metabolism, with an initial increase in fatty acid uptake and storage, and a subsequent down-regulation of lipid oxidation and secretion. PCLSs also demonstrated liver inflammation, including increased pro-inflammatory gene expression and cytokine production. Additionally, liver fibrosis was also observed through the elevated production of pro-collagen 1a1 and tissue inhibitor of metalloproteinase-1 (TIMP1). RNA sequencing showed that the tumor necrosis factor alpha (TNFα) signaling pathway and transforming growth factor beta (TGFβ) signaling pathway were consistently activated, potentially contributing to the development of inflammation and fibrosis. In conclusion, the prolonged incubation of human PCLSs can establish a robust ex vivo model for MASLD, facilitating the identification and evaluation of potential therapeutic interventions.

Machine learning-based integration identifies the ferroptosis hub genes in nonalcoholic steatohepatitis

BACKGROUND

Ferroptosis, is characterized by lipid peroxidation of fatty acids in the presence of iron ions, which leads to cell apoptosis. This leads to the disruption of metabolic pathways, ultimately resulting in liver dysfunction. Although ferroptosis is linked to nonalcoholic steatohepatitis (NASH), understanding the key ferroptosis-related genes (FRGs) involved in NASH remains incomplete. NASH may be targeted therapeutically by identifying the genes responsible for ferroptosis.

METHODS

To identify ferroptosis-related genes and develop a ferroptosis-related signature (FeRS), 113 machine-learning algorithm combinations were used.

RESULTS

The FeRS constructed using the Generalized Linear Model Boosting algorithm and Gradient Boosting Machine algorithms exhibited the best prediction performance for NASH. Eight FRGs, with ZFP36 identified by the algorithms as the most crucial, were incorporated into in FeRS. ZFP36 is significantly enriched in various immune cell types and exhibits significant positive correlations with most immune signatures.

CONCLUSION

ZFP36 is a key FRG involved in NASH pathogenesis.

Identification and validation of disulfidptosis-associated molecular clusters in non-alcoholic fatty liver disease

Objective: Non-alcoholic fatty liver disease (NAFLD) is the most prevalent liver disease in the world, and its pathogenesis is not fully understood. Disulfidptosis is the most recently reported form of cell death and may be associated with NAFLD progression. Our study aimed to explore the molecular clusters associated with disulfidptosis in NAFLD and to construct a predictive model. Methods: First, we analyzed the expression profile of the disulfidptosis regulators and immune characteristics in NAFLD. Using 104 NAFLD samples, we investigated molecular clusters based on differentially expressed disulfidptosis-related genes, along with the related immune cell infiltration. Cluster-specific differentially expressed genes were then identified by using the WGCNA method. We also evaluated the performance of four machine learning models before choosing the optimal machine model for diagnosis. Nomogram, calibration curves, decision curve analysis, and external datasets were used to confirm the prediction effectiveness. Finally, the expression levels of the biomarkers were assessed in a mouse model of a high-fat diet. Results: Two differentially expressed DRGs were identified between healthy and NAFLD patients. We revealed the expression profile of DRGs in NAFLD and the correlation with 22 immune cells. In NAFLD, two clusters of molecules connected to disulfidptosis were defined. Significant immunological heterogeneity was shown by immune infiltration analysis among the various clusters. A significant amount of immunological infiltration was seen in Cluster 1. Functional analysis revealed that Cluster 1 differentially expressed genes were strongly linked to energy metabolism and immune control. The highest discriminatory performance was demonstrated by the SVM model, which had a higher area under the curve, relatively small residual and root mean square errors. Nomograms, calibration curves, and decision curve analyses were used to show how accurate the prediction of NAFLD was. Further analysis revealed that the expression of three model-related genes was significantly associated with the level of multiple immune cells. In animal experiments, the expression trends of DDO, FRK and TMEM19 were consistent with the results of bioinformatics analysis. Conclusion: This study systematically elucidated the complex relationship between disulfidptosis and NAFLD and developed a promising predictive model to assess the risk of disease in patients with disulfidptosis subtypes and NAFLD.

Bioinformatics analysis to reveal the potential comorbidity mechanism in psoriasis and nonalcoholic steatohepatitis

PURPOSE

An increasing amount of evidence suggests that psoriasis and nonalcoholic steatohepatitis (NASH) may occur simultaneously, whereas the underlying mechanisms remain unclear. Our research aims to explore the potential comorbidity mechanism in psoriasis and nonalcoholic steatohepatitis.

MATERIALS AND METHODS

The expression profiles of psoriasis (GSE30999, GSE13355) and NASH (GSE24807, GSE17470) were downloaded from GEO datasets. Next, common differently expressed genes (DEGs) of psoriasis and NASH were investigated. Then, GO and KEGG enrichment, protein interaction network (PPI) construction, and hub gene identification for DEGs were performed. Finally, immune cells expression, target genes predicted by common miRNAs, and transcription factors interaction analysis for hub genes were carried out.

RESULTS

Twenty DEGs were identified in totally. GO analysis revealed response to the virus was the most enriched term, and hepatitis C and coronavirus disease-COVID-19 infection-associated pathways were mainly enriched in KEGG. A total of eight hub genes were collected, including IFIT1, IFIT3, OAS1, HPGDS, IFI27, IFI44, CXCL10, IRF9, and 11 TFs were predicted. Then, neutrophils and monocytes were identified as immune cells that express the most hub genes. Moreover, five common miRNAs for psoriasis and NASH and one common miRNAs (hsa-miR-1305)-mRNAs (CHL1, MBNL2) network were presented.

CONCLUSION

CHL1 and MBNL2 may participate in the process of psoriasis and NASH via regulating hsa-miR-1305, and together with eight hub genes may be potential therapeutic targets for future treatment for the co-occurrence of these two diseases. This comprehensive bioinformatic analysis provides new insights on molecular pathogenesis and identification of potential therapeutic targets for the co-occurrence of them.

Sodium cholate ameliorates nonalcoholic steatohepatitis by activation of FXR signaling

Non-alcoholic steatohepatitis (NASH) has become a major cause of liver transplantation and liver-associated death. The gut-liver axis is a potential therapy for NASH. Sodium cholate (SC) is a choleretic drug whose main component is bile acids and has anti-inflammatory, antifibrotic, and hepatoprotective effects. This study aimed to investigate whether SC exerts anti-NASH effects by the gut-liver axis. Mice were fed with an high-fat and high-cholesterol (HFHC) diet for 20 weeks to induce NASH. Mice were daily intragastric administrated with SC since the 11th week after initiation of HFHC feeding. The toxic effects of SC on normal hepatocytes were determined by CCK8 assay. The lipid accumulation in hepatocytes was virtualized by Oil Red O staining. The mRNA levels of genes were determined by real-time quantitative PCR assay. SC alleviated hepatic injury, abnormal cholesterol synthesis, and hepatic steatosis and improved serum lipid profile in NASH mice. In addition, SC decreased HFHC-induced hepatic inflammatory cell infiltration and collagen deposition. The target protein-protein interaction network was established through Cytoscape software, and NR1H4 [farnesoid x receptor (FXR)] was identified as a potential target gene for SC treatment in NASH mice. SC-activated hepatic FXR and inhibited CYP7A1 expression to reduce the levels of bile acid. In addition, high-dose SC attenuated the abnormal expression of cancer markers in NASH mouse liver. Finally, SC significantly increased the expression of FXR and FGF15 in NASH mouse intestine. Taken together, SC ameliorates steatosis, inflammation, and fibrosis in NASH mice by activating hepatic and intestinal FXR signaling so as to suppress the levels of bile acid in NASH mouse liver and intestine.

Characteristic gene expression in the liver monocyte-macrophage-DC system is associated with the progression of fibrosis in NASH

Background

The monocyte-macrophage-dendritic cell (DC) (MMD) system exerts crucial functions that may modulate fibrogenesis in nonalcoholic steatohepatitis (NASH). In this study, we explored the cell characteristics, distribution and developmental trajectory of the liver MMD system in NASH mice with fibrosis and clarified characteristic genes of the MMD system involved in liver fibrosis progression in NASH mice and patients.

Methods

Single cells in liver tissue samples from NASH and normal mice were quantified using single-cell RNA sequencing (scRNA-seq) analysis. Differentially expressed genes (DEGs) in the MMD system by pseudotime analysis were validated by tyramide signal amplification (TSA)-immunohistochemical staining (IHC) and analyzed by second harmonic generation (SHG)/two-photon excitation fluorescence (TPEF).

Results

Compared with control mice, there were increased numbers of monocytes, Kupffer cells, and DCs in two NASH mouse models. From the transcriptional profiles of these single cells, we identified 8 monocyte subsets (Mono1-Mono8) with different molecular and functional properties. Furthermore, the pseudotime analysis showed that Mono5 and Mono6 were at the beginning of the trajectory path, whereas Mono2, Mono4, Kupffer cells and DCs were at a terminal state. Genes related to liver collagen production were at the late stage of this trajectory path. DEGs analysis revealed that the genes Fmnl1 and Myh9 in the MMD system were gradually upregulated during the trajectory. By TSA-IHC, the Fmnl1 and Myh9 expression levels were increased and associated with collagen production and fibrosis stage in NASH mice and patients.

Conclusions

Our transcriptome data provide a novel landscape of the MMD system that is involved in advanced NASH disease status. Fmnl1 and Myh9 expression in the MMD system was associated with the progression of NASH fibrosis.

Identification of Hub Genes Associated With Non-alcoholic Steatohepatitis Using Integrated Bioinformatics Analysis

Background and aims: As a major cause of liver disease worldwide, non-alcoholic fatty liver disease (NAFLD) comprises non-alcoholic fatty liver (NAFL) and non-alcoholic steatohepatitis (NASH). Due to the high prevalence and poor prognosis of NASH, it is critical to understand its mechanisms. However, the etiology and mechanisms remain largely unknown. In addition, the gold standard for the diagnosis of NASH is liver biopsy, which is an invasive procedure. Therefore, there is a pressing need to develop noninvasive tests for NASH diagnosis. The goal of the study is to discover key genes involved in NASH development and investigate their value as noninvasive biomarkers.

Methods: The Gene Expression Omnibus (GEO) database was used to obtain two datasets encompassing NASH patients and healthy controls. We used weighted gene co-expression network analysis (WGCNA) and differential expression analysis in order to investigate the association between gene sets and clinical features, as well as to discover co-expression modules. A protein-protein interaction (PPI) network was created to extract hub genes. The results were validated using another publicly available dataset and mice treated with a high-fat diet (HFD) and carbon tetrachloride (CCl4).

Results: A total of 24 differentially co-expressed genes were selected by WGCNA and differential expression analysis. KEGG analysis indicated most of them were enriched in the focal adhesion pathway. GO analysis showed these genes were mainly enriched in circadian rhythm, aging, angiogenesis and response to drug (biological process), endoplasmic reticulum lumen (cellular component), and protein binding (molecular function). As a result, eight genes (JUN, SERPINE1, GINS2, TYMS, HMMR, IGFBP2, BIRC3, TNFRSF12A) were identified as hub genes. Finally, three genes were found significantly changed in both the validation dataset and the mouse model.

Conclusion: Our research discovered genes that have the potential to mediate the process of NASH and might be useful diagnostic biomarkers for the disorder.