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Bioinformatics-Based Acquisition of Alzheimer’s Disease Hub Genes

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Big Data – BigData 2023 (BigData 2023)

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Abstract

OBJECTIVE: To analyze the functions and pathways of differentially expressed genes (DEGs) between Alzheimer’s disease (AD) patients and normal controls using bioinformatics methods, and to screen Hub genes to provide theoretical support for the study of AD pathogenesis and therapeutic targets. METHODS AD-related data microarrays (GSE197505) were obtained from the GEO database, and the data were processed using GEO2R to obtain DEGs. The screened DEGs were enriched for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways, using the Matascape platform. Cytoscape software was utilized to map the PPI network and screen the Hub genes. RESULTS A total of 142 DEGs were screened as down-regulated genes in this study. GO/KEGG analysis showed that these DEGs were involved in biological processes such as positive regulation of cell cycle protein-dependent serine/threonine kinase activity, and PI3K-Akt signaling pathway. Eight Hub genes were finally screened by the PPI network, four of which were validated by the literature. CONCLUSION The results of the bioinformatics network analysis revealed the Hub genes of AD, contributing to a better understanding of the mechanisms of AD and facilitating the discovery of new therapeutic targets.

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Acknowledgements

This work was supported by the Start-up Foundation of Hubei University of Medicine (No. 2019QDJRW02); Cooperative Education Program of the Ministry of Education(No.202101142004); Medical Education Research Project of Chinese Medical Association(No.2020B-N02353).

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Correspondence to Juan Bao .

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Hou, MT., Li, XY., Bao, J. (2023). Bioinformatics-Based Acquisition of Alzheimer’s Disease Hub Genes. In: Zhang, S., Hu, B., Zhang, LJ. (eds) Big Data – BigData 2023. BigData 2023. Lecture Notes in Computer Science, vol 14203. Springer, Cham. https://doi.org/10.1007/978-3-031-44725-9_9

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  • DOI: https://doi.org/10.1007/978-3-031-44725-9_9

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-031-44725-9

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