揭示阿尔茨海默病的生物标记检测：微阵列分析的计算方法。

IF 2.6 4区生物学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY

3 Biotech Pub Date : 2024-12-01 Epub Date: 2024-11-25 DOI:10.1007/s13205-024-04159-4

Noor Saba Khan, Saumya Choudhary, Mohd Ali, Mohd Shawaz, Benedikt Jakob Lohnes, Nitesh Kumar Poddar

{"title":"揭示阿尔茨海默病的生物标记检测：微阵列分析的计算方法。","authors":"Noor Saba Khan, Saumya Choudhary, Mohd Ali, Mohd Shawaz, Benedikt Jakob Lohnes, Nitesh Kumar Poddar","doi":"10.1007/s13205-024-04159-4","DOIUrl":null,"url":null,"abstract":"Alzheimer's disease (AD) is a major neurodegenerative condition that affects a significant number of people around the world, making understanding the underlying molecular mechanisms fundamental for identifying predictive biomarkers and therapeutic targets for treating AD. Analysis of the gene expression profile GSE5281, consisting of 161 samples (87 AD and 74 control samples) revealed differentially expressed genes (DEGs) used for KEGG screening to connect dysregulated genes to metabolic pathways or other neurological diseases including Parkinson's, prion, and Huntington's and construction of a protein interaction network. Protein-protein interaction (PPI) network and module analysis uncovered the hub genes ACTB, ACTG1, ATP5A1, CCT2, CDC42, EGFR, FN1, GAPDH, GFAP, GRIA1, HSP90AB1, MAPK1, PSMA3, PSMD14, SNAP25, SNCA, SOD1, SOX2, TPI1, and YWHAZ. The analysis revealed a link between dysregulated genes and processes in AD pathology, including the promotion of osteoporosis, an altered nucleotide metabolism, microtubule stability, and the dysfunctionality of the blood-brain barrier (BBB). These targets might be used as predictive biomarkers or to develop curative and preventive therapeutic approaches for treating AD.","PeriodicalId":7067,"journal":{"name":"3 Biotech","volume":"14 12","pages":"311"},"PeriodicalIF":2.6000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11589038/pdf/","citationCount":"0","resultStr":"{\"title\":\"Unveiling biomarker detection in Alzheimer's disease: a computational approach to microarray analysis.\",\"authors\":\"Noor Saba Khan, Saumya Choudhary, Mohd Ali, Mohd Shawaz, Benedikt Jakob Lohnes, Nitesh Kumar Poddar\",\"doi\":\"10.1007/s13205-024-04159-4\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Alzheimer's disease (AD) is a major neurodegenerative condition that affects a significant number of people around the world, making understanding the underlying molecular mechanisms fundamental for identifying predictive biomarkers and therapeutic targets for treating AD. Analysis of the gene expression profile GSE5281, consisting of 161 samples (87 AD and 74 control samples) revealed differentially expressed genes (DEGs) used for KEGG screening to connect dysregulated genes to metabolic pathways or other neurological diseases including Parkinson's, prion, and Huntington's and construction of a protein interaction network. Protein-protein interaction (PPI) network and module analysis uncovered the hub genes ACTB, ACTG1, ATP5A1, CCT2, CDC42, EGFR, FN1, GAPDH, GFAP, GRIA1, HSP90AB1, MAPK1, PSMA3, PSMD14, SNAP25, SNCA, SOD1, SOX2, TPI1, and YWHAZ. The analysis revealed a link between dysregulated genes and processes in AD pathology, including the promotion of osteoporosis, an altered nucleotide metabolism, microtubule stability, and the dysfunctionality of the blood-brain barrier (BBB). These targets might be used as predictive biomarkers or to develop curative and preventive therapeutic approaches for treating AD.\",\"PeriodicalId\":7067,\"journal\":{\"name\":\"3 Biotech\",\"volume\":\"14 12\",\"pages\":\"311\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11589038/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"3 Biotech\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s13205-024-04159-4\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/11/25 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"BIOTECHNOLOGY & APPLIED MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"3 Biotech","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s13205-024-04159-4","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/25 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"BIOTECHNOLOGY & APPLIED MICROBIOLOGY","Score":null,"Total":0}

引用次数: 0

摘要

阿尔茨海默病（AD）是一种严重的神经退行性疾病，影响着全球众多患者，因此了解其潜在的分子机制对于确定预测性生物标记物和治疗目标至关重要。对由 161 个样本（87 个 AD 样本和 74 个对照样本）组成的基因表达谱 GSE5281 进行分析，发现了用于 KEGG 筛选的差异表达基因（DEGs），从而将失调基因与代谢通路或其他神经系统疾病（包括帕金森氏症、朊病毒和亨廷顿氏症）联系起来，并构建了蛋白质相互作用网络。蛋白质-蛋白质相互作用（PPI）网络和模块分析发现了枢纽基因 ACTB、ACTG1、ATP5A1、CCT2、CDC42、表皮生长因子受体、FN1、GAPDH、GFAP、GRIA1、HSP90AB1、MAPK1、PSMA3、PSMD14、SNAP25、SNCA、SOD1、SOX2、TPI1 和 YWHAZ。分析表明，在注意力缺失症病理过程中，调控失调的基因和过程之间存在联系，包括促进骨质疏松症、改变核苷酸代谢、微管稳定性和血脑屏障（BBB）功能障碍。这些靶点可用作预测性生物标志物或开发治疗和预防性治疗方法来治疗艾滋病。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Unveiling biomarker detection in Alzheimer's disease: a computational approach to microarray analysis.

Alzheimer's disease (AD) is a major neurodegenerative condition that affects a significant number of people around the world, making understanding the underlying molecular mechanisms fundamental for identifying predictive biomarkers and therapeutic targets for treating AD. Analysis of the gene expression profile GSE5281, consisting of 161 samples (87 AD and 74 control samples) revealed differentially expressed genes (DEGs) used for KEGG screening to connect dysregulated genes to metabolic pathways or other neurological diseases including Parkinson's, prion, and Huntington's and construction of a protein interaction network. Protein-protein interaction (PPI) network and module analysis uncovered the hub genes ACTB, ACTG1, ATP5A1, CCT2, CDC42, EGFR, FN1, GAPDH, GFAP, GRIA1, HSP90AB1, MAPK1, PSMA3, PSMD14, SNAP25, SNCA, SOD1, SOX2, TPI1, and YWHAZ. The analysis revealed a link between dysregulated genes and processes in AD pathology, including the promotion of osteoporosis, an altered nucleotide metabolism, microtubule stability, and the dysfunctionality of the blood-brain barrier (BBB). These targets might be used as predictive biomarkers or to develop curative and preventive therapeutic approaches for treating AD.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

3 Biotech Agricultural and Biological Sciences-Agricultural and Biological Sciences (miscellaneous)

CiteScore

6.00

自引率

0.00%

发文量

314

期刊介绍： 3 Biotech publishes the results of the latest research related to the study and application of biotechnology to: - Medicine and Biomedical Sciences - Agriculture - The Environment The focus on these three technology sectors recognizes that complete Biotechnology applications often require a combination of techniques. 3 Biotech not only presents the latest developments in biotechnology but also addresses the problems and benefits of integrating a variety of techniques for a particular application. 3 Biotech will appeal to scientists and engineers in both academia and industry focused on the safe and efficient application of Biotechnology to Medicine, Agriculture and the Environment.