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Plasma metabolites distinguish dementia with Lewy bodies from Alzheimer’s disease: a cross-sectional metabolomic analysis

Lookup NU author(s): Dr Paul Donaghy, Dr Gemma Roberts, Professor John O'Brien, Professor Alan ThomasORCiD



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Copyright © 2024 Pan, Donaghy, Roberts, Chouliaras, O’Brien, Thomas, Heslegrave, Zetterberg, McGuinness, Passmore, Green and Kane.Background: In multifactorial diseases, alterations in the concentration of metabolites can identify novel pathological mechanisms at the intersection between genetic and environmental influences. This study aimed to profile the plasma metabolome of patients with dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), two neurodegenerative disorders for which our understanding of the pathophysiology is incomplete. In the clinical setting, DLB is often mistaken for AD, highlighting a need for accurate diagnostic biomarkers. We therefore also aimed to determine the overlapping and differentiating metabolite patterns associated with each and establish whether identification of these patterns could be leveraged as biomarkers to support clinical diagnosis. Methods: A panel of 630 metabolites (Biocrates MxP Quant 500) and a further 232 metabolism indicators (biologically informative sums and ratios calculated from measured metabolites, each indicative for a specific pathway or synthesis; MetaboINDICATOR) were analyzed in plasma from patients with probable DLB (n = 15; age 77.6 ± 8.2 years), probable AD (n = 15; 76.1 ± 6.4 years), and age-matched cognitively healthy controls (HC; n = 15; 75.2 ± 6.9 years). Metabolites were quantified using a reversed-phase ultra-performance liquid chromatography column and triple-quadrupole mass spectrometer in multiple reaction monitoring (MRM) mode, or by using flow injection analysis in MRM mode. Data underwent multivariate (PCA analysis), univariate and receiving operator characteristic (ROC) analysis. Metabolite data were also correlated (Spearman r) with the collected clinical neuroimaging and protein biomarker data. Results: The PCA plot separated DLB, AD and HC groups (R2 = 0.518, Q2 = 0.348). Significant alterations in 17 detected metabolite parameters were identified (q ≤ 0.05), including neurotransmitters, amino acids and glycerophospholipids. Glutamine (Glu; q = 0.045) concentrations and indicators of sphingomyelin hydroxylation (q = 0.039) distinguished AD and DLB, and these significantly correlated with semi-quantitative measurement of cardiac sympathetic denervation. The most promising biomarker differentiating AD from DLB was Glu:lysophosphatidylcholine (lysoPC a 24:0) ratio (AUC = 0.92; 95%CI 0.809–0.996; sensitivity = 0.90; specificity = 0.90). Discussion: Several plasma metabolomic aberrations are shared by both DLB and AD, but a rise in plasma glutamine was specific to DLB. When measured against plasma lysoPC a C24:0, glutamine could differentiate DLB from AD, and the reproducibility of this biomarker should be investigated in larger cohorts.

Publication metadata

Author(s): Pan X, Donaghy PC, Roberts G, Chouliaras L, O'Brien JT, Thomas AJ, Heslegrave AJ, Zetterberg H, McGuinness B, Passmore AP, Green BD, Kane JPM

Publication type: Article

Publication status: Published

Journal: Frontiers in Aging Neuroscience

Year: 2024

Volume: 15

Online publication date: 04/01/2024

Acceptance date: 11/12/2023

Date deposited: 29/01/2024

ISSN (electronic): 1663-4365

Publisher: Frontiers Media SA


DOI: 10.3389/fnagi.2023.1326780


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Funder referenceFunder name
Alzheimer’s Research UK Northern Ireland Network
Medical Research Council
National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre