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Volume 22, Issue 6
  • ISSN: 1570-1611
  • E-ISSN: 1875-6212

Abstract

Background

Alzheimer's disease (AD) plays a prominent role as the most common form of dementia. Moreover, the traditional mechanism of AD does not explain the microvascular damage observed in about 25-30 years between the onset of AD, which results in late application treatment that inhibits or delays neurodegeneration.

Objective

Our objective was to identify differentially expressed genes in human brain samples associated with vascular disruption in AD.

Methods

We analyzed 1633 post-mortem brain samples in the GEO database and, after applying clinical and bioinformatic exclusion criteria, worked with 581 prefrontal and frontal samples. All datasets were analyzed using GEO2R from NCBI. We identified common genes using the Venny tool, and their metabolic relevance associated with AD and the vascular system was analyzed using MetaboAnalyst tools.

Results

Our bioinformatic analysis identified PRKCB, MAP2K2, ADCY1, GNA11, GNAQ, PRKACB, KCNMB4, CALD1, and GNAS as potentially involved in AD pathogenesis. These genes are associated with signal transductions, cell death signaling, and cytoskeleton, suggesting potential modulation of cellular physiology, including endoplasmic reticulum and mitochondrial activity.

Conclusion

This study generates hypotheses regarding the roles of novel genes over critical pathways relevant to AD and its relation with vascular dysfunction. These findings suggest potential new targets for further investigation into the pathogenesis of dementia and AD.

© 2024 Bentham Science Publishers
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2024-06-20
2024-11-16

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/content/journals/cvp/10.2174/0115701611298073240612050741
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Identification of Vascular Genes Differentially Expressed in the Brain of Patients with Alzheimer's Disease
Curr. Vasc. Pharmacol. 22, 404 (2024); https://doi.org/10.2174/0115701611298073240612050741
/content/journals/cvp/10.2174/0115701611298073240612050741
/content/journals/cvp/10.2174/0115701611298073240612050741
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  • Article Type:     Research Article
Keyword(s): Alzheimer; bioinformatics; DEG; dementia; genes; vascular

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