Abstract
The purpose of this study was to identify hub genes closely correlated with Alzheimer's disease (AD) and their association with immune cell infiltration. In this work, 119 overlapping differentially expressed genes (DEGs) were obtained from GSE5281 and GSE122063 datasets through differential expression analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on the 119 DEGs, revealing some important biological functions and key pathways. AD immune cell infiltration analysis revealed a significant difference in the proportion of immune cells between the AD group and the control group. Finally, correlation analysis between target hub genes and immune cells indicated that GFAP had a positive or negative correlation with some specific immune cells. Our results provided useful clues, which will help to explain the molecular mechanism of AD and search for precise prognostic markers and potential therapeutic targets.
Highlights
Alzheimer’s disease (AD) is a degenerative disease of the central nervous system that occurs in old age and pre-old age and is characterized by progressive cognitive dysfunction and behavioral impairment [1, 2]
A new generation of high-throughput sequencing technologies and the development of genomics have produced a wealth of disease gene expression data and clinical information already stored in many public databases [16,17,18]. is provides a new idea and theoretical basis for indepth understanding of the pathogenesis and biological characteristics of diseases through bioinformatics analysis
Datasets GSE5281 and GSE122063 were downloaded from Gene Expression Omnibus (GEO) database. e former included 87 AD brain tissue and 74 normal tissue samples, while the latter included 92 AD brain tissue and 44 normal tissue samples
Summary
Alzheimer’s disease (AD) is a degenerative disease of the central nervous system that occurs in old age and pre-old age and is characterized by progressive cognitive dysfunction and behavioral impairment [1, 2]. It is the most common type of dementia and one of the most common chronic diseases in old age [3], accounting for about 50% to 70% of dementia in old age [4, 5]. A new generation of high-throughput sequencing technologies and the development of genomics have produced a wealth of disease gene expression data and clinical information already stored in many public databases [16,17,18]. is provides a new idea and theoretical basis for indepth understanding of the pathogenesis and biological characteristics of diseases through bioinformatics analysis
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