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

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Abstract

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.

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Most cited references 67

Record: found
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The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease

Guy M McKhann, David S. Knopman, Howard Chertkow … (2011)

The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of revising the 1984 criteria for Alzheimer's disease (AD) dementia. The workgroup sought to ensure that the revised criteria would be flexible enough to be used by both general healthcare providers without access to neuropsychological testing, advanced imaging, and cerebrospinal fluid measures, and specialized investigators involved in research or in clinical trial studies who would have these tools available. We present criteria for all-cause dementia and for AD dementia. We retained the general framework of probable AD dementia from the 1984 criteria. On the basis of the past 27 years of experience, we made several changes in the clinical criteria for the diagnosis. We also retained the term possible AD dementia, but redefined it in a manner more focused than before. Biomarker evidence was also integrated into the diagnostic formulations for probable and possible AD dementia for use in research settings. The core clinical criteria for AD dementia will continue to be the cornerstone of the diagnosis in clinical practice, but biomarker evidence is expected to enhance the pathophysiological specificity of the diagnosis of AD dementia. Much work lies ahead for validating the biomarker diagnosis of AD dementia. Copyright © 2011. Published by Elsevier Inc.

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Record: found
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“Mini-mental state”

Marshal Folstein, Susan Folstein, Paul McHugh (1975)

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Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living

M P Lawton, E M Brody (1969)

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Author and article information

Contributors

Xiaobei Pan: URI : https://loop.frontiersin.org/people/519581/overviewRole: Role: Role:

Paul C. Donaghy: Role: Role:

Gemma Roberts: Role: Role: Role:

Leonidas Chouliaras: URI : https://loop.frontiersin.org/people/1052141/overviewRole: Role:

John T. O’Brien: Role: Role:

Alan J. Thomas: Role: Role:

Amanda J. Heslegrave: URI : https://loop.frontiersin.org/people/1255252/overviewRole: Role:

Henrik Zetterberg: URI : https://loop.frontiersin.org/people/22853/overviewRole: Role:

Bernadette McGuinness: URI : https://loop.frontiersin.org/people/462606/overviewRole: Role:

Anthony P. Passmore: Role: Role:

Brian D. Green: URI : https://loop.frontiersin.org/people/498336/overviewRole: Role: Role: Role:

Joseph P. M. Kane: URI : https://loop.frontiersin.org/people/2273297/overviewRole: Role: Role: Role: Role: Role: Role:

Journal

Journal ID (nlm-ta): Front Aging Neurosci

Journal ID (iso-abbrev): Front Aging Neurosci

Journal ID (publisher-id): Front. Aging Neurosci.

Title: Frontiers in Aging Neuroscience

Publisher: Frontiers Media S.A.

ISSN (Electronic): 1663-4365

Publication date (Electronic): 04 January 2024

Publication date Collection: 2023

Volume: 15

Electronic Location Identifier: 1326780

Affiliations

[1] ¹School of Biological Sciences, Queen’s University Belfast , Belfast, United Kingdom

[2] ²Translational and Clinical Research Institute, Newcastle University , Newcastle upon Tyne, United Kingdom

[3] ³Department of Psychiatry, University of Cambridge , Cambridge, United Kingdom

[4] ⁴Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology , London, United Kingdom

[5] ⁵Dementia Research Institute, UCL , London, United Kingdom

[6] ⁶Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg , Gothenburg, Sweden

[7] ⁷Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital , Mölndal, Sweden

[8] ⁸Hong Kong Center for Neurodegenerative Diseases , Kowloon, Hong Kong SAR, China

[9] ⁹Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison , Madison, WI, United States

[10] ¹⁰Centre for Public Health, Queen’s University Belfast , Belfast, United Kingdom

Author notes

Edited by: Omar M. El-Agnaf, Hamad bin Khalifa University, Qatar

Reviewed by: Yutaka Oji, Juntendo University, Japan; Matteo Cotta Ramusino, Neurological Institute Foundation Casimiro Mondino (IRCCS), Italy

*Correspondence: Joseph P. M. Kane, joseph.kane@ 123456qub.ac.uk

^†These authors have contributed equally to this work and share last authorship

Article

DOI: 10.3389/fnagi.2023.1326780

PMC ID: 10794326

PubMed ID: 38239488

SO-VID: 1f2de3df-bdf0-4b96-89cd-d72137bc3918

License:

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

History

Date received : 24 October 2023

Date accepted : 11 December 2023

Page count

Figures: 3, Tables: 3, Equations: 0, References: 67, Pages: 13, Words: 8766

Funding

Funded by: Medical Research Council, doi 10.13039/501100000265;

Award ID: W000229

Funded by: Alzheimer’s Research UK, doi 10.13039/501100002283;

Funded by: National Institute for Health Research, doi 10.13039/501100000272;

Funded by: Swedish Research Council, doi 10.13039/501100004359;

Funded by: Alzheimer’s Association

Funded by: Stiftelsen för Gamla Tjänarinnor, doi 10.13039/100010815;

Funded by: European Union’s Horizon 2020 research and innovation program

Funded by: Marie Skłodowska-Curie

Funded by: University College London, doi 10.13039/501100000765;

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This research was funded by an Alzheimer’s Research UK Northern Ireland Network grant and supported by the National Institute for Health Research (NIHR) Newcastle Biomedical Research Centre. PD is supported by the Medical Research Council [grant number MR/W000229/1]. HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2022–01018 and #2019–02397), the European Union’s Horizon Europe research and innovation program under grant agreement No 101053962, Swedish State Support for Clinical Research (#ALFGBG-71320), the Alzheimer Drug Discovery Foundation (ADDF), USA (#201809–2016862), the AD Strategic Fund and the Alzheimer’s Association (#ADSF-21-831376-C, #ADSF-21-831381-C, and #ADSF-21-831377-C), the Bluefield Project, the Olav Thon Foundation, the Erling-Persson Family Foundation, Stiftelsen för Gamla Tjänarinnor, Hjärnfonden, Sweden (#FO2022-0270), the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No 860197 (MIRIADE), the European Union Joint Program – Neurodegenerative Disease Research (JPND2021-00694), the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre, and the UK Dementia Research Institute at UCL (UKDRI-1003).

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section-at-acceptance Alzheimer's Disease and Related Dementias

ScienceOpen disciplines: Neurosciences

Keywords: dementia,lewy body dementia,alzheimer’s disease,metabolomic analyses,biomarkers

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ScienceOpen disciplines: Neurosciences

Keywords: dementia, lewy body dementia, alzheimer’s disease, metabolomic analyses, biomarkers

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

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Karger: Neurology and Neuroscience

Most cited references 67

The diagnosis of dementia due to Alzheimer's disease: Recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease

“Mini-mental state”

Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living

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