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通过加权基因共表达网络分析鉴定阿尔茨海默病的遗传分子标记和免疫浸润特征

Identification of genetic molecular markers and immune infiltration characteristics of Alzheimer's disease through weighted gene co-expression network analysis.

作者信息

Duan KeFei, Ma Yuan, Tan Jin, Miao Yuyang, Zhang Qiang

机构信息

Department of Geriatrics, Geriatrics Institute, Tianjin Medical University General Hospital, Tianjin, China.

Department of Urology, Tianjin Institute of Urology, The Second Hospital of Tianjin Medical University, Tianjin, China.

出版信息

Front Neurol. 2022 Aug 22;13:947781. doi: 10.3389/fneur.2022.947781. eCollection 2022.

Abstract

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disease that leads to cognitive impairment and memory loss. Currently, the pathogenesis and underlying causative genes of AD remain unclear, and there exists no effective treatment for this disease. This study explored AD-related diagnostic and therapeutic biomarkers from the perspective of immune infiltration by analyzing public data from the NCBI Gene Expression Omnibus database.

METHOD

In this study, weighted gene co-expression network analysis (WGCNA) was conducted to identify modules and hub genes contributing to AD development. A protein-protein interaction network was constructed when the genes in the modules were enriched and examined by Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, a gene network was established using topological WGCNA, from which five hub genes were selected. Logistic regression analysis and receiver operating characteristic curve analysis were performed to explore the clinical value of genes in AD diagnosis. The genes in the core module intersected with the hub genes, and four intersection genes (, and ) were selected. These four genes were enriched by gene set enrichment analysis (GSEA). Finally, an immune infiltration analysis was performed.

RESULTS

The GO/KEGG analysis suggested that genes in the core module played a role in the differentiation and growth of neural cells and in the transmission of neurotransmitters. The GSEA of core genes showed that these four genes were mainly enriched in immune/infection pathways (e.g., cholera infection and infection pathways) and other metabolic pathways. An investigation of immune infiltration characteristics revealed that activated mast cells, regulatory T cells, plasma cells, neutrophils, T follicular helper cells, CD8 T cells, resting memory CD4 T cells, and M1 macrophages were the core immune cells contributing to AD progression. qRT-PCR analysis showed that the ATP6V1D is upregulated in AD.

CONCLUSION

The results of enrichment and immuno-osmotic analyses indicated that immune pathways and immune cells played an important role in the occurrence and development of AD. The selected key genes were used as biomarkers related to the pathogenesis of AD to further explore the pathways and cells, which provided new perspectives on therapeutic targets in AD.

摘要

背景

阿尔茨海默病(AD)是一种导致认知障碍和记忆丧失的进行性神经退行性疾病。目前,AD的发病机制和潜在致病基因仍不清楚,且尚无针对该疾病的有效治疗方法。本研究通过分析来自NCBI基因表达综合数据库的公开数据,从免疫浸润的角度探索与AD相关的诊断和治疗生物标志物。

方法

在本研究中,进行了加权基因共表达网络分析(WGCNA)以识别促进AD发展的模块和枢纽基因。当模块中的基因通过基因本体论(GO)/京都基因与基因组百科全书(KEGG)分析进行富集和检验时,构建了蛋白质-蛋白质相互作用网络。此外,使用拓扑WGCNA建立了一个基因网络,从中选择了五个枢纽基因。进行逻辑回归分析和受试者工作特征曲线分析以探索基因在AD诊断中的临床价值。核心模块中的基因与枢纽基因相交,选择了四个相交基因(、和)。通过基因集富集分析(GSEA)对这四个基因进行了富集。最后,进行了免疫浸润分析。

结果

GO/KEGG分析表明,核心模块中的基因在神经细胞的分化和生长以及神经递质的传递中发挥作用。核心基因的GSEA表明,这四个基因主要富集于免疫/感染途径(如霍乱感染和感染途径)以及其他代谢途径。对免疫浸润特征的研究表明,活化的肥大细胞、调节性T细胞、浆细胞、中性粒细胞、T滤泡辅助细胞、CD8 T细胞、静息记忆CD4 T细胞和M1巨噬细胞是促进AD进展的核心免疫细胞。qRT-PCR分析表明,ATP6V1D在AD中上调。

结论

富集和免疫渗透分析结果表明,免疫途径和免疫细胞在AD的发生和发展中起重要作用。所选关键基因作为与AD发病机制相关的生物标志物,进一步探索其途径和细胞,为AD治疗靶点提供了新的视角。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc2c/9441600/0a6703b5bd1f/fneur-13-947781-g0001.jpg

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