Исследования здорового старения

Исследования здорового старения
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ISSN: 2261-7434


Significant age-related alterations in the blood plasma metabolome of noncognitively impaired healthy elderly subjects

Xiaobei Pan, Peter Passmore, Stewart F. Graham, Stephen Todd, Bernadette McGuinness, Brian D. Green

Background: Age is a major risk factor for most common neurodegenerative diseases. Although an increased research focus on diseases of aging, there is little information regarding the metabolite changes in the aging blood in healthy older adults. Such information could help us to understand neurocognitive changes associated with aging and also further improve the validity and reproducibility of future metabolite biomarkers for neurodegenerative diseases. Materials and

Methods: The purpose of this study was to assess how the metabolomic profiles of noncognitively impaired elderly participants changes with aging. Using a targeted liquid chromatography-mass spectrometry/MS metabolomics approach, this study examined 17 noncognitively impaired elderly participants (T0; 78.10 ± 6.30 y; mini-mental state exam = 29.29 ± 0.85) and the same 17 subjects were followed-up ∼5 years later (T5; 83.29 ± 6.13 y; mini-mental state exam =27.47 ± 1.62).

Results: The concentrations of 187 plasma metabolites determined were used to build a partial least squares-discriminant model which found that metabolomic profiles taken 5 years (T5) from baseline (T0) were distinctly different (R2= 0.95; Q2 =0.90). When metabolites levels at T5 were compared with T0, 68 of the 73 phosphatidylcholines, 25 of the 40 acylcarnitines, and 2 of the 14 lysophosphatidylcholines were increased, whereas 3 of the 14 lysophosphatidylcholines and 2 of the 14 sphingomyelins were decreased. Moreover, 20 of the 42 amino acids concentrations were significantly different between the 2 time points. Fourteen amino acids were increased at T5, whereas 6 amino acids were decreased.

Conclusions: The plasma metabolome changes with age in elderly, noncognitively impaired subjects, and this could aid in developing valid and sensitive metabolite biomarkers for human disease.