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基于综合生物信息学的阿尔茨海默病相关DNA甲基化差异基因鉴定及其诊断意义

Identification of Differential Genes of DNA Methylation Associated With Alzheimer's Disease Based on Integrated Bioinformatics and Its Diagnostic Significance.

作者信息

Chen Fan, Wang Na, He Xiaping

机构信息

School of Basic Medical Sciences, Dali University, Dali, China.

出版信息

Front Aging Neurosci. 2022 May 9;14:884367. doi: 10.3389/fnagi.2022.884367. eCollection 2022.

DOI:10.3389/fnagi.2022.884367
PMID:35615586
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9125150/
Abstract

BACKGROUND

Alzheimer's disease (AD) is a common neurodegenerative disease. The pathogenesis is complex and has not been clearly elucidated, and there is no effective treatment. Recent studies have demonstrated that DNA methylation is closely associated with the pathogenesis of AD, which sheds light on investigating potential biomarkers for the diagnosis of early AD and related possible therapeutic approaches.

METHODS

Alzheimer's disease patients samples and healthy controls samples were collected from two datasets in the GEO database. Using LIMMA software package in R language to find differentially expressed genes (DEGs). Afterward, DEGs have been subjected to enrichment analysis of GO and KEGG pathways. The PPI networks and Hub genes were created and visualized based on the STRING database and Cytoscape. ROC curves were further constructed to analyze the accuracy of these genes for AD diagnosis.

RESULTS

Analysis of the GSE109887 and GSE97760 datasets showed 477 significant DEGs. GO and KEGG enrichment analysis showed terms related to biological processes related to these genes. The top ten Hub genes were found on the basis of the PPI network using the CytoHubba plugin, and the AUC areas of these top ranked genes were all greater than 0.7, showing satisfactory diagnostic accuracy.

CONCLUSION

The study identified the top 10 Hub genes associated with AD-related DNA methylation, of which , and have high diagnostic accuracy and excellent AD biomarker potential.

摘要

背景

阿尔茨海默病（AD）是一种常见的神经退行性疾病。其发病机制复杂，尚未完全阐明，且尚无有效治疗方法。最近的研究表明，DNA甲基化与AD的发病机制密切相关，这为研究早期AD诊断的潜在生物标志物及相关可能的治疗方法提供了线索。

方法

从GEO数据库的两个数据集中收集阿尔茨海默病患者样本和健康对照样本。使用R语言中的LIMMA软件包查找差异表达基因（DEG）。随后，对DEG进行GO和KEGG通路的富集分析。基于STRING数据库和Cytoscape创建并可视化PPI网络和枢纽基因。进一步构建ROC曲线以分析这些基因对AD诊断的准确性。

结果

对GSE109887和GSE97760数据集的分析显示有477个显著的DEG。GO和KEGG富集分析显示了与这些基因相关的生物过程相关术语。使用CytoHubba插件在PPI网络的基础上发现了前十个枢纽基因，这些排名靠前的基因的AUC面积均大于0.7，显示出令人满意的诊断准确性。

结论

该研究确定了与AD相关DNA甲基化相关的前10个枢纽基因，其中， 和 具有较高的诊断准确性和出色的AD生物标志物潜力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/30c253292f09/fnagi-14-884367-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/1360eeb4fb56/fnagi-14-884367-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/84e74f64cf43/fnagi-14-884367-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/26fd980d785d/fnagi-14-884367-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/8f8b918b848c/fnagi-14-884367-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/7630c8cc7346/fnagi-14-884367-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/6ad54a9b1ffd/fnagi-14-884367-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/30c253292f09/fnagi-14-884367-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/1360eeb4fb56/fnagi-14-884367-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/84e74f64cf43/fnagi-14-884367-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/26fd980d785d/fnagi-14-884367-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/8f8b918b848c/fnagi-14-884367-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/7630c8cc7346/fnagi-14-884367-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/6ad54a9b1ffd/fnagi-14-884367-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/755d/9125150/30c253292f09/fnagi-14-884367-g007.jpg

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