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Publication Detail
Metabolic correlates of late midlife cognitive outcomes: findings from the 1946 British Birth Cohort
  • Publication Type:
    Journal article
  • Authors:
    Green R, Lord J, Xu J, Maddock J, Kim M, Dobson R, Legido-Quigley C, Wong A, Richards M, Proitsi P
  • Publisher:
    Oxford University Press (OUP)
  • Publication date:
  • Journal:
    Brain Communications
  • Volume:
  • Issue:
  • Article number:
  • Status:
  • Print ISSN:
  • Language:
  • Keywords:
    metabolomics, dementia, cognition, epidemiology, network analysis
  • Notes:
    © The Author(s) (2022). Published by Oxford University Press on behalf of the Guarantors of Brain. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
Investigating associations between metabolites and late midlife cognitive function could reveal potential markers and mechanisms relevant to early dementia. Here, we systematically explored the metabolic correlates of cognitive outcomes measured across the seventh decade of life, while untangling influencing life course factors. Using levels of 1019 metabolites profiled by liquid chromatography–mass spectrometry (age 60–64), we evaluated relationships between metabolites and cognitive outcomes in the British 1946 Birth Cohort (N = 1740). We additionally conducted pathway and network analyses to allow for greater insight into potential mechanisms, and sequentially adjusted for life course factors across four models, including sex and blood collection (Model 1), Model 1 + body mass index and lipid medication (Model 2), Model 2 + social factors and childhood cognition (Model 3) and Model 3 + lifestyle influences (Model 4). After adjusting for multiple tests, 155 metabolites, 10 pathways and 5 network modules were associated with cognitive outcomes. Of the 155, 35 metabolites were highly connected in their network module (termed ‘hub’ metabolites), presenting as promising marker candidates. Notably, we report relationships between a module comprised of acylcarnitines and processing speed which remained robust to life course adjustment, revealing palmitoylcarnitine (C16) as a hub (Model 4: β = −0.10, 95% confidence interval = −0.15 to −0.052, P = 5.99 × 10−5). Most associations were sensitive to adjustment for social factors and childhood cognition; in the final model, four metabolites remained after multiple testing correction, and 80 at P < 0.05. Two modules demonstrated associations that were partly or largely attenuated by life course factors: one enriched in modified nucleosides and amino acids (overall attenuation = 39.2–55.5%), and another in vitamin A and C metabolites (overall attenuation = 68.6–92.6%). Our other findings, including a module enriched in sphingolipid pathways, were entirely explained by life course factors, particularly childhood cognition and education. Using a large birth cohort study with information across the life course, we highlighted potential metabolic mechanisms associated with cognitive function in late midlife, suggesting marker candidates and life course relationships for further study.
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