Comprehensive profiling of candidate biomarkers and immune infiltration landscape in metabolic dysfunction-associated steatohepatitis

Metabolism open Pub Date : 2025-04-15 DOI:10.1016/j.metop.2025.100366

Zhangliu Jin , Jianyun Cao , Zhaoxun Liu , Mei Gao , Hailan Liu

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Abstract

Background

The incidence of metabolic dysfunction-associated steatohepatitis (MASH) is increasing, with an incompletely understood pathophysiology involving multiple factors, particularly innate and adaptive immune responses. Given the limited pharmacological treatments available, identification of novel immune metabolic targets is urgently needed. In this study, we aimed to identify hub immune-related genes and potential biomarkers with diagnostic and predictive value for MASH patients.

Methods

The GSE164760 dataset from the Gene Expression Omnibus was utilized for analysis, and the R package was used to identify differentially expressed genes. Immune-related differentially expressed genes (IR-DEGs) were identified by comparing the overlap of differentially expressed genes with well-known immune-related genes. Furthermore, the biological processes and molecular functions of the IR-DEGs were analyzed. To characterize the hub IR-DEGs, we employed a protein-protein interaction network. The diagnostic and predictive values of these hub IR-DEGs in MASH were confirmed using GSE48452 and GSE63067 datasets. Finally, the significance of the hub IR-DEGs was validated using a mouse model of MASH.

Results

A total of 91 IR-DEGs were identified, with 61 upregulated and 30 downregulated genes. Based on the protein-protein interaction network, FN1, RHOA, FOS, PDGFRα, CCND1, PIK3R1, CSF1, and FGF3 were identified as the hub IR-DEGs. Moreover, we found that these hub genes are closely correlated with immune cells. Notably, the validation across two independent cohorts as well as a murine MASH model confirmed their high diagnostic potential.

Conclusion

The hub IR-DEGs, such as FN1, RHOA, FOS, PDGFRα, CCND1, PIK3R1, CSF1, and FGF3, may enhance the diagnosis and prognosis of MASH by modulating immune homeostasis.

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代谢功能障碍相关脂肪性肝炎候选生物标志物和免疫浸润景观的综合分析

代谢功能障碍相关脂肪性肝炎（MASH）的发病率正在增加，涉及多种因素的病理生理学尚不完全清楚，特别是先天和适应性免疫反应。鉴于现有的药物治疗有限，迫切需要鉴定新的免疫代谢靶点。在这项研究中，我们的目的是确定中心免疫相关基因和潜在的生物标志物，对MASH患者具有诊断和预测价值。方法利用基因表达图谱（Gene Expression Omnibus）中的GSE164760数据集进行分析，并利用R包进行差异表达基因的鉴定。通过比较差异表达基因与已知免疫相关基因的重叠，鉴定免疫相关差异表达基因（IR-DEGs）。并对IR-DEGs的生物学过程和分子功能进行了分析。为了表征枢纽IR-DEGs，我们采用了蛋白质-蛋白质相互作用网络。使用GSE48452和GSE63067数据集证实了这些枢纽IR-DEGs在MASH中的诊断和预测价值。最后，利用小鼠MASH模型验证了枢纽IR-DEGs的意义。结果共鉴定出91个ir - deg，其中61个基因上调，30个基因下调。基于蛋白相互作用网络，FN1、RHOA、FOS、PDGFRα、CCND1、PIK3R1、CSF1和FGF3被鉴定为枢纽IR-DEGs。此外，我们发现这些中心基因与免疫细胞密切相关。值得注意的是，通过两个独立队列以及小鼠MASH模型的验证证实了它们的高诊断潜力。结论FN1、RHOA、FOS、PDGFRα、CCND1、PIK3R1、CSF1、FGF3等中枢ir - deg可能通过调节免疫稳态，提高MASH的诊断和预后。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Metabolism open Agricultural and Biological Sciences (General), Endocrinology, Endocrinology, Diabetes and Metabolism

自引率

0.00%

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审稿时长

40 days