ArticleMedical science monitor : international medical journal of experimental and clinical research2020
Screening and Identification of Potential Peripheral Blood Biomarkers for Alzheimer's Disease Based on Bioinformatics Analysis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
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- Identification of Autophagy-Related Biomarkers and Diagnostic Model in Alzheimer's Disease.Genes · 2024Article
- Cortical lipid metabolic pathway alteration of early Alzheimer's disease and candidate drugs screen.European journal of medical research · 2024Article
- Integration of single-cell sequencing with machine learning and Mendelian randomization analysis identifies the NAP1L1 gene as a predictive biomarker for Alzheimer's disease.Frontiers in aging neuroscience · 2024Article
- Exploring autophagy-related prognostic genes of Alzheimer's disease based on pathway crosstalk analysis.Bosnian journal of basic medical sciences · 2022Article
- New Drug Design Avenues Targeting Alzheimer's Disease by Pharmacoinformatics-Aided Tools.Pharmaceutics · 2022Review
- Effects of Metformin on Modulating the Expression of Brain-related Genes of APP/PS1 Transgenic Mice based on Single Cell Sequencing.Current Alzheimer research · 2022Article
- A Diagnostic Model for Alzheimer's Disease Based on Blood Levels of Autophagy-Related Genes.Frontiers in aging neuroscience · 2022Article
- Peripheral Blood Biomarkers CXCL12 and TNFRSF13C Associate with Cerebrospinal Fluid Biomarkers and Infiltrating Immune Cells in Alzheimer Disease.Journal of molecular neuroscience : MN · 2021Article
- Identification of key genes and pathways of BMP-9-induced osteogenic differentiation of mesenchymal stem cells by integrated bioinformatics analysis.Journal of orthopaedic surgery and research · 2021Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia worldwide; however, the molecular mechanisms underlying its pathogenesis remain unclear. The present study aimed to discover some potential peripheral blood biomarkers for early detection of patients with AD. MATERIAL AND METHODS Publicly available AD datasets - GSE18309 and GSE97760 - were obtained from the Gene Expression Omnibus database, and limma package from Bioconductor was employed to search for differently expressed genes (DEGs). Weighted correlation network analysis was performed to identify DEGs with highly synergistic changes, and functional annotation of DEGs was performed using gene set enrichment analysis and Metascape. STRING and Cytoscape were used to construct protein-protein interaction networks and analyze the most significant hub genes. Thereafter, the Comparative Toxicogenomics Database (CTD) was used to identify hub genes associated with AD pathology, and Connectivity Map was used to screen small molecule drugs for AD. Finally, hub genes coupled with corresponding predicted miRNAs involved in AD were assessed via TargetScan, and functional annotation of predicted miRNAs was performed using DIANA database. RESULTS Our analyses revealed 5042 DEGs; based on functional analyses, these DEGs were mainly associated with oligosaccharide lipid intermediate biosynthetic process, cyclin binding, signaling pathways regulating pluripotency of ubiquitin mediated proteolysis, and extracellular matrix-receptor interaction. UBB, UBA52, SRC, MMP9, VWF, GP6, and PF4 were identified as the hub genes. The CTD showed that these hub genes are closely related with AD or cognition impairment. CONCLUSIONS The identified hub genes and corresponding miRNAs might be useful as potential peripheral blood biomarkers of AD.
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