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    Rights statement: This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Chemical Neuroscience, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acschemneuro.8b00198

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Raman spectroscopy to diagnose Alzheimer's disease and dementia with Lewy bodies in blood

Research output: Contribution to journalJournal article

Published
  • Maria Paraskevaidi
  • Camilo Morais
  • D. Halliwell
  • David Mann
  • David Allsop
  • Pierre Martin-Hirsch
  • Francis L. Martin
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<mark>Journal publication date</mark>2018
<mark>Journal</mark>ACS Chemical Neuroscience
Issue number11
Volume9
Number of pages9
Pages (from-to)2786–2794
Publication statusPublished
Early online date4/06/18
Original languageEnglish

Abstract

Accurate identification of Alzheimer's disease (AD) is still of major clinical importance considering the current lack of noninvasive and low-cost diagnostic approaches. Detection of early stage AD is particularly desirable as it would allow early intervention or recruitment of patients into clinical trials. There is also an unmet need for discrimination of AD from dementia with Lewy bodies (DLB), as many cases of the latter are misdiagnosed as AD. Biomarkers based on a simple blood test would be useful in research and clinical practice. Raman spectroscopy has been implemented to analyze blood plasma of a cohort that consisted of early stage AD, late-stage AD, DLB, and healthy controls. Classification algorithms achieved high accuracy for the different groups: early stage AD vs healthy with 84% sensitivity, 86% specificity; late-stage AD vs healthy with 84% sensitivity, 77% specificity; DLB vs healthy with 83% sensitivity, 87% specificity; early-stage AD vs DLB with 81% sensitivity, 88% specificity; late-stage AD vs DLB with 90% sensitivity, 93% specificity; and lastly, early-stage AD vs late-stage AD 66% sensitivity and 83% specificity. G-score values were also estimated between 74% and 91%, demonstrating that the overall performance of the classification model was satisfactory. The wavenumbers responsible for differentiation were assigned to important biomolecules, which can serve as a panel of biomarkers. These results suggest a cost-effective, blood-based test for neurodegeneration in dementias.

Bibliographic note

This document is the Accepted Manuscript version of a Published Work that appeared in final form in ACS Chemical Neuroscience, copyright © American Chemical Society after peer review and technical editing by the publisher. To access the final edited and published work see https://pubs.acs.org/doi/10.1021/acschemneuro.8b00198