Impact of seed amplification assay and surface-enhanced Raman spectroscopy combined approach on the clinical diagnosis of Alzheimer's disease.
Alzheimer’s disease
Amyloid-β protein
Seed amplification assay
Surface-enhanced Raman spectroscopy
Journal
Translational neurodegeneration
ISSN: 2047-9158
Titre abrégé: Transl Neurodegener
Pays: England
ID NLM: 101591861
Informations de publication
Date de publication:
12 07 2023
12 07 2023
Historique:
received:
21
03
2023
accepted:
12
06
2023
medline:
14
7
2023
pubmed:
13
7
2023
entrez:
12
7
2023
Statut:
epublish
Résumé
The current diagnosis of Alzheimer's disease (AD) is based on a series of analyses which involve clinical, instrumental and laboratory findings. However, signs, symptoms and biomarker alterations observed in AD might overlap with other dementias, resulting in misdiagnosis. Here we describe a new diagnostic approach for AD which takes advantage of the boosted sensitivity in biomolecular detection, as allowed by seed amplification assay (SAA), combined with the unique specificity in biomolecular recognition, as provided by surface-enhanced Raman spectroscopy (SERS). The SAA-SERS approach supported by machine learning data analysis allowed efficient identification of pathological Aβ oligomers in the cerebrospinal fluid of patients with a clinical diagnosis of AD or mild cognitive impairment due to AD. Such analytical approach can be used to recognize disease features, thus allowing early stratification and selection of patients, which is fundamental in clinical treatments and pharmacological trials.
Sections du résumé
BACKGROUND
The current diagnosis of Alzheimer's disease (AD) is based on a series of analyses which involve clinical, instrumental and laboratory findings. However, signs, symptoms and biomarker alterations observed in AD might overlap with other dementias, resulting in misdiagnosis.
METHODS
Here we describe a new diagnostic approach for AD which takes advantage of the boosted sensitivity in biomolecular detection, as allowed by seed amplification assay (SAA), combined with the unique specificity in biomolecular recognition, as provided by surface-enhanced Raman spectroscopy (SERS).
RESULTS
The SAA-SERS approach supported by machine learning data analysis allowed efficient identification of pathological Aβ oligomers in the cerebrospinal fluid of patients with a clinical diagnosis of AD or mild cognitive impairment due to AD.
CONCLUSIONS
Such analytical approach can be used to recognize disease features, thus allowing early stratification and selection of patients, which is fundamental in clinical treatments and pharmacological trials.
Identifiants
pubmed: 37438825
doi: 10.1186/s40035-023-00367-9
pii: 10.1186/s40035-023-00367-9
pmc: PMC10337059
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
35Informations de copyright
© 2023. The Author(s).
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