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

Jiang, Zhenyu; Zhou, Yi; Zhou, Lu; Li, Shaowei; Wang, Bangmao

doi:10.1155/2021/7561645

Cited by 14 publications

(10 citation statements)

References 54 publications

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“…Rac1, the small GTPbinding protein, is required for saturated fatty acids (SFA)stimulated MLK3-dependent JNK activation in hepatocytes (34). SOCS3, as a suppressor of cytokine signaling, is considered to promote insulin resistance by inhibiting insulin and leptin signaling during the inflammatory response (35). However, the relationship between the expression of these genes and NASH fibrosis was not clear.…”

Section: Discussionmentioning

confidence: 99%

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

Wang

Wang²,

Liu³

et al. 2023

Front. Immunol.

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BackgroundThe 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.MethodsSingle 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).ResultsCompared 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.ConclusionsOur 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.

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Section: Discussionmentioning

confidence: 99%

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

Wang

Wang²,

Liu³

et al. 2023

Front. Immunol.

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“…Zeng et al used similar methods, but a different dataset to find the hub genes in NAFLD ( Zeng et al, 2021 ). Other bioinformatic tools, such as immune infiltration analysis, were also used in combination with DEG to explore the molecular mechanisms of NASH ( Jiang et al, 2021 ). The key genes found in these studies require further preclinical and clinical investigation.…”

Section: Discussionmentioning

confidence: 99%

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

Meng

Xiong

2022

Front. Genet.

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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.

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“…4H and 4I). We conducted a thorough search on the PubMed website to identify nine pertinent articles related to NASH [23][24][25][26][27][28][29][30][31]. From these articles, we meticulously extracted a total of 43 essential genes directly associated with NASH.…”

Section: Construction Of An Fers Model With 8 Hub Genes For Nash Diag...mentioning

confidence: 99%

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

Dai,

Yuan,

Jiang

et al. 2023

Preprint

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Background Ferroptosis, an iron-dependent mode of cellular demise, precipitates the accumulation of lipid peroxides and perturbation of vital metabolic routes, culminating in hepatic impairment. However, the pivotal genes governing the contribution of ferroptosis to the pathogenesis of nonalcoholic steatohepatitis (NASH) remain elusive, necessitating a thorough and profound investigation. Methods Employing sophisticated machine learning techniques, pivotal ferroptosis hub genes were meticulously identified, culminating in the formulation of a comprehensive ferroptosis-related score (FeRS) model. Sequentially, correlation analyses were harnessed to unravel intricate associations linking the ferroptosis hub genes with immune function scores, as well as distinct immune cell subpopulations. Results An FeRS model, encompassing a set of eight central ferroptosis hub genes, was meticulously fashioned, exhibiting profound diagnostic efficacy within the training dataset and across seven independent testing datasets. Among these genes, ZFP36 emerged as a key hub within the FeRS. Moreover, ZFP36 and IL6 revealed substantial positive correlations with immune function scores and various subsets of immune cells. In contrast, GRIA3 and FADS2 exhibit the opposite pattern. Conclusions The pivotal role of the ferroptosis-related gene ZFP36 in the context of NASH comes to the fore, as its diminished expression serves to propel the trajectory of restrain the infiltration of immune components within the NASH milieu.

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

Cited by 14 publications

References 54 publications

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

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

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

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

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