High-resolution metabolomic profiling of Alzheimer's disease in plasma

• Type of Material: Article
• Authors: Megan M. Niedzwiecki, Emory University; Douglas Walker, Emory University; Jennifer Christina Howell, Emory University; Kelly D. Watts, Emory University; Dean P Jones, Emory University; Gary W Miller, Emory University; William Hu, Emory University
• Language: English
• Date: 2019-12-11
• Publisher: Wiley Open Access: Creative Commons Attribution Non-Commercial No Derivatives
• Publication Version: Final Published Version
• Copyright Statement: © 2019 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals, Inc on behalf of American Neurological Association.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): http://dx.doi.org/10.1002/acn3.50956
• Title of Journal or Parent Work: Annals of Clinical and Translational Neurology
• ISSN: 2328-9503
• Volume: 7
• Issue: 1
• Start Page: 36
• End Page: 45
• Grant/Funding Information: This work was funded by National Institute of Environmental Health Sciences grants P30 ES019776 ; and T32 ES012870; National Institute on Aging grants K23 AG042856;, P50 AG025688;, and R21 AG043885.
• Keywords: HEALTH; MASS-SPECTROMETRY; Science & Technology; MILD COGNITIVE IMPAIRMENT; OXIDATIVE STRESS; CEREBROSPINAL-FLUID; Neurosciences & Neurology; CLINICAL-DIAGNOSIS; Life Sciences & Biomedicine; NATIONAL INSTITUTE; PIPERINE; ASSOCIATION; Clinical Neurology; Neurosciences; SERUM
• Research Categories: Health Sciences, Pharmacology; Biology, Neuroscience; Environmental Sciences

Abstract

Background: Alzheimer’s disease (AD) is a complex neurological disorder with contributions from genetic and environmental factors. High-resolution metabolomics (HRM) has the potential to identify novel endogenous and environmental factors involved in AD. Previous metabolomics studies have identified circulating metabolites linked to AD, but lack of replication and inconsistent diagnostic algorithms have hindered the generalizability of these findings. Here we applied HRM to identify plasma metabolic and environmental factors associated with AD in two study samples, with cerebrospinal fluid (CSF) biomarkers of AD incorporated to achieve high diagnostic accuracy. Methods: Liquid chromatography-mass spectrometry (LC–MS)-based HRM was used to identify plasma and CSF metabolites associated with AD diagnosis and CSF AD biomarkers in two studies of prevalent AD (Study 1: 43 AD cases, 45 mild cognitive impairment [MCI] cases, 41 controls; Study 2: 50 AD cases, 18 controls). AD-associated metabolites were identified using a metabolome-wide association study (MWAS) framework. Results: An MWAS meta-analysis identified three non-medication AD-associated metabolites in plasma, including elevated levels of glutamine and an unknown halogenated compound and lower levels of piperine, a dietary alkaloid. The non-medication metabolites were correlated with CSF AD biomarkers, and glutamine and the unknown halogenated compound were also detected in CSF. Furthermore, in Study 1, the unknown compound and piperine were altered in MCI patients in the same direction as AD dementia. Conclusions: In plasma, AD was reproducibly associated with elevated levels of glutamine and a halogen-containing compound and reduced levels of piperine. These findings provide further evidence that exposures and behavior may modify AD risks.