ArticleIBRO neuroscience reports2025
Exploration and validation of biomarkers for Alzheimer's disease based on GEO database.
Article in IBRO neuroscience reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- Multi-omics exploration of chaperone-mediated immune-proteostasis crosstalk in vascular dementia and identification of diagnostic biomarkers.Frontiers in immunology · 2025Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objectives: The purpose of this study is to leverage bioinformatics techniques to identify differentially expressed genes in Alzheimer's disease (AD), explore potential biomarkers for its early diagnosis, and provide new insights for the early diagnosis and treatment of AD. Methods: Two Alzheimer's disease-associated datasets, GSE66351 and GSE153712, were obtained from the Gene Expression Omnibus (GEO) database. Differential methylation analysis was conducted on the raw data utilizing the R programming language. Key genes were discerned by integrating LASSO regression, Pearson correlation analysis, and protein-protein interaction network analysis (PPI). Furthermore, the functional roles of these genes were investigated via Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses. To assess their causal association with AD, a Mendelian randomization analysis was performed. Results: In two AD datasets, we identified a total of 387 overlapping differential methylation sites, which mapped to 297 genes. The GO enrichment analysis indicated that these genes are involved in a range of biological processes, such as signal transduction, cell cycle regulation, as well as the function of neuronal cell bodies and synapses. Furthermore, KEGG pathway analysis uncovered that these genes play crucial roles in the PI3K-Akt and TGF-beta signaling pathways. By utilizing a combination of LASSO, Pearson correlation analysis, and PPI network interaction analysis, we have identified five pivotal genes: Conclusions: This study not only confirmed the known genes linked to AD but, more significantly, revealed the potential connection between the
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