Department of Pancreatobiliary Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Front Immunol. 2024 Mar 8;15:1364442. doi: 10.3389/fimmu.2024.1364442. eCollection 2024.
Non-alcoholic fatty liver disease (NAFLD), which includes simple steatosis (SS) and non-alcoholic steatohepatitis (NASH), is a significant contributor to liver disease on a global scale. The change of immunity-related genes (IRGs) expression level leads to different immune infiltrations. However, the expression of IRGs and possible regulatory mechanisms involved in NAFLD remain unclear. The objective of our research is to investigate crucial genes linked to the development of NAFLD and the transition from SS to NASH.
Dataset GSE89632, which includes healthy controls, SS patients, and NASH patients, was obtained using the GEO database. To examine the correlation between sets of genes and clinical characteristics, we employed weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Hub genes were extracted using a network of protein-protein interactions (PPI) and three different machine learning algorithms. To validate the findings, another dataset that is publicly accessible and mice that were subjected to a high-fat diet (HFD) or MCD diet were utilized. Furthermore, the ESTIMATE algorithm and ssGSEA were employed to investigate the immune landscape in the normal versus SS group and SS versus NASH group, additionally, the relationship between immune infiltration and the expression of hub genes was also examined.
A total of 28 immune related key genes were selected. Most of these genes expressed reverse patterns in the initial and progressive stages of NAFLD. GO and KEGG analyses showed that they were focused on the cytokine related pathways and immune cell activation and chemotaxis. After screening by various algorithms, we obtained two hub genes, including JUN and CCL20. Validation of these findings was confirmed by analyzing gene expression patterns in both the validation dataset and the mouse model. Ultimately, two hub genes were discovered to have a significant correlation with the infiltration of immune cells.
We proposed that there were dynamic changes in the expression levels of IRGs in different stages of NAFLD disease, which led to different immune landscapes in SS and NASH. The findings of our research could serve as a guide for the accurate management of various phases of NAFLD.
非酒精性脂肪性肝病（NAFLD）包括单纯性脂肪变性（SS）和非酒精性脂肪性肝炎（NASH），是全球范围内导致肝病的一个重要因素。免疫相关基因（IRGs）表达水平的变化导致了不同的免疫浸润。然而，NAFLD 中涉及的 IRGs 的表达和可能的调节机制仍不清楚。我们的研究目的是研究与 NAFLD 发展以及从 SS 向 NASH 转变相关的关键基因。
从 GEO 数据库中获取了包含健康对照组、SS 患者和 NASH 患者的数据集 GSE89632。为了研究基因集与临床特征之间的相关性，我们采用了加权基因共表达网络分析（WGCNA）和差异表达分析。使用蛋白质-蛋白质相互作用（PPI）网络和三种不同的机器学习算法提取了枢纽基因。为了验证研究结果，我们还使用了另一个公开的数据集和接受高脂肪饮食（HFD）或 MCD 饮食的小鼠。此外，还使用 ESTIMATE 算法和 ssGSEA 来研究正常与 SS 组以及 SS 与 NASH 组之间的免疫图谱，同时还研究了免疫浸润与枢纽基因表达之间的关系。
共选择了 28 个与免疫相关的关键基因。这些基因中的大多数在 NAFLD 的初始和进展阶段表达相反的模式。GO 和 KEGG 分析表明，它们主要集中在细胞因子相关途径和免疫细胞激活和趋化作用上。通过各种算法筛选后，我们获得了两个枢纽基因，包括 JUN 和 CCL20。通过验证数据集和小鼠模型中的基因表达模式，验证了这些发现。最终，发现两个枢纽基因与免疫细胞的浸润有显著相关性。
我们提出，在 NAFLD 疾病的不同阶段，IRGs 的表达水平存在动态变化，导致 SS 和 NASH 中存在不同的免疫图谱。我们的研究结果可以为 NAFLD 各个阶段的准确管理提供指导。
