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Neurol."],"abstract":"<jats:sec><jats:title>Background<\/jats:title><jats:p>Alzheimer's disease (AD) is a progressive neurodegenerative disease that leads to cognitive impairment and memory loss. Currently, the pathogenesis and underlying causative genes of AD remain unclear, and there exists no effective treatment for this disease. This study explored AD-related diagnostic and therapeutic biomarkers from the perspective of immune infiltration by analyzing public data from the NCBI Gene Expression Omnibus database.<\/jats:p><\/jats:sec><jats:sec><jats:title>Method<\/jats:title><jats:p>In this study, weighted gene co-expression network analysis (WGCNA) was conducted to identify modules and hub genes contributing to AD development. A protein\u2013protein interaction network was constructed when the genes in the modules were enriched and examined by Gene Ontology (GO)\/Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Furthermore, a gene network was established using topological WGCNA, from which five hub genes were selected. Logistic regression analysis and receiver operating characteristic curve analysis were performed to explore the clinical value of genes in AD diagnosis. The genes in the core module intersected with the hub genes, and four intersection genes (<jats:italic>ATP2A2, ATP6V1D, CAP2<\/jats:italic>, and <jats:italic>SYNJ1<\/jats:italic>) were selected. These four genes were enriched by gene set enrichment analysis (GSEA). Finally, an immune infiltration analysis was performed.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>The GO\/KEGG analysis suggested that genes in the core module played a role in the differentiation and growth of neural cells and in the transmission of neurotransmitters. The GSEA of core genes showed that these four genes were mainly enriched in immune\/infection pathways (e.g., cholera infection and <jats:italic>Helicobacter pylori<\/jats:italic> infection pathways) and other metabolic pathways. An investigation of immune infiltration characteristics revealed that activated mast cells, regulatory T cells, plasma cells, neutrophils, T follicular helper cells, CD8 T cells, resting memory CD4 T cells, and M1 macrophages were the core immune cells contributing to AD progression. qRT-PCR analysis showed that the ATP6V1D is upregulated in AD.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusion<\/jats:title><jats:p>The results of enrichment and immuno-osmotic analyses indicated that immune pathways and immune cells played an important role in the occurrence and development of AD. The selected key genes were used as biomarkers related to the pathogenesis of AD to further explore the pathways and cells, which provided new perspectives on therapeutic targets in AD.<\/jats:p><\/jats:sec>","DOI":"10.3389\/fneur.2022.947781","type":"journal-article","created":{"date-parts":[[2022,8,22]],"date-time":"2022-08-22T05:27:01Z","timestamp":1661146021000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["Identification of genetic molecular markers and immune infiltration characteristics of Alzheimer's disease through weighted gene co-expression network analysis"],"prefix":"10.3389","volume":"13","author":[{"given":"KeFei","family":"Duan","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Tan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuyang","family":"Miao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,8,22]]},"reference":[{"key":"B1","article-title":"StatPearls [Internet]","volume-title":"Dementia","author":"Emmady","year":"2021"},{"key":"B2","doi-asserted-by":"publisher","first-page":"112","DOI":"10.1186\/s13195-018-0438-z","article-title":"Secondary prevention of Alzheimer's dementia: neuroimaging contributions","volume":"10","author":"Ten Kate","year":"2018","journal-title":"Alzheimers Res Ther."},{"key":"B3","doi-asserted-by":"publisher","first-page":"951","DOI":"10.1016\/S1474-4422(20)30314-8","article-title":"Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementias","volume":"19","author":"Ch\u00e9telat","year":"2020","journal-title":"Lancet Neurol."},{"key":"B4","doi-asserted-by":"publisher","first-page":"262","DOI":"10.3760\/cma.j.cn112150-20210916-00902","article-title":"[Application guidelines and research progress of biomarkers for Alzheimer's disease]","volume":"56","author":"Wang","year":"2022","journal-title":"Zhonghua Yu Fang Yi Xue Za Zhi"},{"key":"B5","doi-asserted-by":"publisher","first-page":"414","DOI":"10.1038\/s41588-019-0358-2","article-title":"Alzheimer Disease Genetics Consortium (ADGC),; European Alzheimer's Disease Initiative (EADI),; Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium (CHARGE),; Genetic and Environmental Risk in AD\/Defining Genetic, Polygenic and Environmental Risk for Alzheimer's Disease Consortium (GERAD\/PERADES). 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