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• W3081807611 abstract "Alzheimer’s disease (AD) is the most common type of dementia and creates a significant burden on society. As a result, the investigation of hub genes for the discovery of potential therapeutic targets and candidate biomarkers is warranted. In this study, we used the ComBat method to merge three gene expression datasets of AD from the Gene Expression Omnibus (GEO). During combined analysis, we identified 850 differentially expressed genes (DEGs) from the temporal cortex of AD and cognitively normal (CN) samples. We performed weighted gene co-expression network analysis (WGCNA) to construct gene co-expression networks incorporating these DEGs to identify key modules and hub genes. We found the green module as the key module associated with AD and 19 hub genes in the key module. According to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses, identified DEGs were mostly enriched in synapse function, and green module genes were mostly related to learning and memory. We selected five seldomly reported genes, AP3B2, GABRD, GPR158, KIAA0513, and MAL2, for further investigation of correlations with β-secretase activity and Aβ42 levels in AD samples of different Braak stages. We found that all five hub genes had significant negative associations with β-secretase activity, and that AP3B2 and KIAA0513 had significant negative associations with Aβ42 levels. We tested the differential expressions of the five hub genes in two AD GEO datasets from the blood, and found that KIAA0513 was significantly up-regulated in both MCI and AD samples and was able to differentiate MCI and AD from CN in the two datasets. In conclusion, these five novel vulnerable genes were involved in AD progression and KIAA0513 was a promising candidate biomarker for early diagnosis of AD." @default.
• W3081807611 created "2020-09-08" @default.
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• W3081807611 date "2020-08-28" @default.
• W3081807611 modified "2023-10-15" @default.
• W3081807611 title "Identification of KIAA0513 and Other Hub Genes Associated With Alzheimer Disease Using Weighted Gene Coexpression Network Analysis" @default.
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• W3081807611 doi "https://doi.org/10.3389/fgene.2020.00981" @default.
• W3081807611 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/7483929" @default.
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