{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T17:46:07Z","timestamp":1773510367965,"version":"3.50.1"},"reference-count":118,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T00:00:00Z","timestamp":1739836800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key R&D Plan Projects in Kunshan City","award":["KSF202105"],"award-info":[{"award-number":["KSF202105"]}]},{"DOI":"10.13039\/501100018556","name":"Suzhou Science and Technology Project","doi-asserted-by":"crossref","award":["SKY2023197"],"award-info":[{"award-number":["SKY2023197"]}],"id":[{"id":"10.13039\/501100018556","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Clinical Research Project of Gusu School of Nanjing Medical University","award":["GSKY20240202"],"award-info":[{"award-number":["GSKY20240202"]}]},{"name":"Key Social Development Project of Jiangsu Province","award":["BE2021660"],"award-info":[{"award-number":["BE2021660"]}]}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS ONE"],"abstract":"<jats:sec id=\"sec001\">\n<jats:title>Background<\/jats:title>\n<jats:p>Since its emergence in 2019, COVID-19 has become a global epidemic. Several studies have suggested a link between Alzheimer\u2019s disease (AD) and COVID-19. However, there is little research into the mechanisms underlying these phenomena. Therefore, we conducted this study to identify key genes in COVID-19 associated with AD, and evaluate their correlation with immune cells characteristics and metabolic pathways.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec002\">\n<jats:title>Methods<\/jats:title>\n<jats:p>Transcriptome analyses were used to identify common biomolecular markers of AD and COVID-19. Differential expression analysis and weighted gene co-expression network analysis (WGCNA) were performed on gene chip datasets (GSE213313, GSE5281, and GSE63060) from AD and COVID-19 patients to identify genes associated with both conditions. Gene ontology (GO) enrichment analysis identified common molecular mechanisms. The core genes were identified using machine learning. Subsequently, we evaluated the relationship between these core genes and immune cells and metabolic pathways. Finally, our findings were validated through single-cell analysis.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec003\">\n<jats:title>Results<\/jats:title>\n<jats:p>The study identified 484 common differentially expressed genes (DEGs) by taking the intersection of genes between AD and COVID-19. The black module, containing 132 genes, showed the highest association between the two diseases according to WGCNA. GO enrichment analysis revealed that these genes mainly affect inflammation, cytokines, immune-related functions, and signaling pathways related to metal ions. Additionally, a machine learning approach identified eight core genes. We identified links between these genes and immune cells and also found a association between EIF3H and oxidative phosphorylation.<\/jats:p>\n<\/jats:sec>\n<jats:sec id=\"sec004\">\n<jats:title>Conclusion<\/jats:title>\n<jats:p>This study identifies shared genes, pathways, immune alterations, and metabolic changes potentially contributing to the pathogenesis of both COVID-19 and AD.<\/jats:p>\n<\/jats:sec>","DOI":"10.1371\/journal.pone.0317915","type":"journal-article","created":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T18:32:23Z","timestamp":1739903543000},"page":"e0317915","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":3,"title":["Identification of biomarkers in Alzheimer\u2019s disease and COVID-19 by bioinformatics combining single-cell data analysis and machine learning 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