Publication

Differences in plasma metabolites related to Alzheimer's disease, APOE ε4 status, and ethnicity

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Last modified
  • 05/15/2025
Type of Material
Authors
    Badri Vardarajan, Vagelos College of Physicians and SurgeonsVrinda Kalia, Columbia UniversityJennifer Manly, Vagelos College of Physicians and SurgeonsAdam Brickman, Vagelos College of Physicians and SurgeonsDolly Reyes-Dumeyer, Vagelos College of Physicians and SurgeonsRafael Lantigua, New York Presbyterian HospitalIuliana Ionita-Laza, Columbia University Irving Medical CenterDean Jones, Emory UniversityGary Miller, Emory UniversityRichard Mayeux, Vagelos College of Physicians and Surgeons
Language
  • English
Date
  • 2020-01-01
Publisher
  • Alzheimer's Association
Publication Version
Copyright Statement
  • © 2020 Alzheimer's Association.
License
Final Published Version (URL)
Title of Journal or Parent Work
Volume
  • 6
Issue
  • 1
Start Page
  • e12025
End Page
  • e12025
Grant/Funding Information
  • WHICAP. Data collection and sharing for this project was supported by the Washington Heights‐Inwood Columbia Aging Project (WHICAP, PO1AG07232, R01AG037212, RF1AG054023, and R56AG063908) funded by the National Institute on Aging (NIA) and by the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant Number UL1TR001873.
  • The metabolomics work was supported by U2C ES030163 and R01 ES023839.
Supplemental Material (URL)
Abstract
  • Introduction: We investigated metabolites in plasma to capture systemic biochemical changes associated with Alzheimer's disease (AD). Methods: Metabolites in plasma were measured in 59 AD cases and 60 healthy participants of African American (AA), Caribbean Hispanic (CH), and non-Hispanic white (NHW) ancestry using untargeted liquid-chromatography–based ultra-high-resolution mass spectrometry. Metabolite differences between AD and healthy, ethnic groups and apolipoprotein E gene (APOE) ε4 status were analyzed. Untargeted network analysis identified pathways enriched in AD-associated metabolites. Results: A total of 5929 annotated metabolites were measured. Partial least squares discriminant analysis (PLS-DA) inferred that AD clustered separately from healthy controls (area under the curve [AUC] = 0.9816); discriminating pathways included glycerophospholipid, sphingolipid, and non-essential amino acid (alanine, aspartate, glutamate) metabolism. Metabolic features in AA clustered differently from CH and NHW (AUC = 0.9275), and differed between APOE ε4 carriers and non-carriers (AUC = 0.9972). Discussion: Metabolites, specifically lipids, were associated with AD, APOE ε4, and ethnic group. Metabolite profiling can identify perturbed AD pathways, but genetic and ancestral background need to be considered.
Author Notes
  • Correspondence: Richard Mayeux, MD, Taub Institute for Research on, Alzheimer's Disease and the Aging Brain, 630 West 168th Street, New York, NY 10032. Email: rpm2@columbia.edu
Keywords
Research Categories
  • Gerontology
  • Biology, Neuroscience
  • Environmental Sciences
  • Biology, Biostatistics

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