Bioinformatics analysis and hub genes prediction of Alzheimer's disease RNA sequencing data
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1. Pharmacy School, Guangxi University of Chinese Medicine;2. Pharmacy School, Xuzhou Medical University

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R541.1

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    Abstract:

    Objective: To uncover the key genes and biological process of Alzheimer's disease by RNA sequencing data analysis. Methods: Initially, GSE125050 RNA sequencing data was obtained from the GEO database. After quality control and filtration, data were conducted genes differentially expression analysis by edgeR. Gene enrichment analysis of GO and KEGG were performed on differentially expression genes (DEGs) by Matescape database. Genes set enrichment analyses (GSEA) were performed on the biologically significant genes set. Protein-protein interaction network was constructed using neuron DEGs, to identify hub genes in protein level. Results: The number of differentially expression genes from neuron, myeloid, astrocyte, endothelial samples was 561, 491, 223, 3 072, respectively. Neuron's DEGs were significantly correlated with G alpha (s) signaling events and keratinization. Endothelial DEGs were significantly enriched at olfactory signaling pathway. GSEA showed neuron differential expression was related to activation of immune response. TLR8, FCGR2A, CD19, LCK, CD2, CD40, ITGAM were screened out by PPI network as hub genes. Conclusion: TLR8, FCGR2A, CD19, LCK, CD2, CD40, ITGAM may play a significant role in neuroinflammation in AD occurrence.

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Zhang Fan, Zhong Siran, Yang Siman, Wei Yuting, Huang Jinlan, Wu Dengpan, Zhong Zhenguo. Bioinformatics analysis and hub genes prediction of Alzheimer's disease RNA sequencing data[J]. Journal of Chongqing Medical University,2021,46(5):539-545

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  • Received:September 29,2019
  • Revised:
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  • Online: June 28,2023
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