Bioinformatic analysis of the SPs and NFTs proteomes unravel putative biomarker candidates for Alzheimer's disease

Aging is the main risk factor for the appearance of age‐related neurodegenerative diseases, including Alzheimer's disease (AD). AD is the most common form of dementia, characterized by the presence of senile plaques (SPs) and neurofibrillary tangles (NFTs), the main histopathological hallmarks...

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Published in:Proteomics (Weinheim) 2023-08, Vol.23 (15), p.e2200515-n/a
Main Authors: Ferreira, Maria J. Cardoso, Soares Martins, Tânia, Alves, Steven R., Rosa, Ilka Martins, Vogelgsang, Jonathan, Hansen, Niels, Wiltfang, Jens, da Cruz e Silva, Odete A. B., Vitorino, Rui, Henriques, Ana Gabriela
Format: Article
Language:English
Subjects:
Alzheimer's disease
Amyloid
Biological activity
Biomarkers
Dementia disorders
Fibrils
kinases
Knowledge representation
Lesions
Literature reviews
Neurodegenerative diseases
Neurofibrillary tangles
phosphatases
Proteins
Proteomes
Risk factors
Senile plaques
Tau protein
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Summary:Aging is the main risk factor for the appearance of age‐related neurodegenerative diseases, including Alzheimer's disease (AD). AD is the most common form of dementia, characterized by the presence of senile plaques (SPs) and neurofibrillary tangles (NFTs), the main histopathological hallmarks in AD brains. The core of these deposits are predominantly amyloid fibrils in SPs and hyperphosphorylated Tau protein in NFTs, but other molecular components can be found associated with these pathological lesions. Herein, an extensive literature review was carried out to obtain the SPs and NFTs proteomes, followed by a bioinformatic analysis and further putative biomarker validation. For SPs, 857 proteins were recovered, and, for NFTs, 627 proteins of which 375 occur in both groups and represent the common proteome. Gene Ontology (GO) enrichment analysis permitted the identification of biological processes and the molecular functions most associated with these lesions. Analysis of the SPs and NFTs common proteins unraveled pathways and molecular targets linking both histopathological events. Further, validation of a putative phosphotarget arising from the in silico analysis was performed in serum‐derived extracellular vesicles from AD patients. This bioinformatic approach contributed to the identification of putative molecular targets, valuable for AD diagnostic or therapeutic intervention.
ISSN:1615-9853
1615-9861
DOI:10.1002/pmic.202200515