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  • IOS Press  (1)
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    In: Journal of Alzheimer's Disease, IOS Press, Vol. 89, No. 2 ( 2022-09-13), p. 605-622
    Abstract: Background: Aging is a risk factor for several pathologies as Alzheimer’s disease (AD). Great interest exists, therefore, in discovering diagnostic biomarkers and indicators discriminating biological aging and health status. To this aim, omic investigations of biological matrices, as saliva, whose sampling is easy and non-invasive, offer great potential. Objective: Investigate the salivary proteome through a statistical comparison of the proteomic data by several approaches to highlight quali-/quantitative variations associated specifically either to aging or to AD occurrence, and, thus, able to classify the subjects. Methods: Salivary proteomic data of healthy controls under-70 (adults) and over-70 (elderly) years old, and over-70 AD patients, obtained by liquid chromatography/mass spectrometry, were analyzed by multiple Mann-Whitney test, Kendall correlation, and Random-Forest (RF) analysis. Results: Almost all the investigated proteins/peptides significantly decreased in relation to aging in elderly subjects, with or without AD, in comparison with adults. AD subjects exhibited the highest levels of α-defensins, thymosin β4, cystatin B, S100A8 and A9. Correlation tests also highlighted age/disease associated differences. RF analysis individuated quali-/quantitative variations in 20 components, as oxidized S100A8 and S100A9, α-defensin 3, P-B peptide, able to classify with great accuracy the subjects into the three groups. Conclusion: The findings demonstrated a strong change of the salivary protein profile in relation to the aging. Potential biomarkers candidates of AD were individuated in peptides/proteins involved in antimicrobial defense, innate immune system, inflammation, and in oxidative stress. RF analysis revealed the feasibility of the salivary proteome to discriminate groups of subjects based on age and health status.
    Type of Medium: Online Resource
    ISSN: 1387-2877 , 1875-8908
    Language: Unknown
    Publisher: IOS Press
    Publication Date: 2022
    detail.hit.zdb_id: 2070772-1
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