Abstract
Accurate identification of Alzheimer’s disease (AD) is still of major clinical importance considering the current lack of non-invasive and low-cost diagnostic approaches. Detection of early-stage AD is particularly desirable as it would allow early intervention and/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 analyse 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 74-91%, 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 biomarker for neurodegeneration in dementias.
Original language | English |
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Journal | ACS Chemical Neuroscience |
Volume | 9 |
DOIs | |
Publication status | Published - 4 Jun 2018 |
Research Beacons, Institutes and Platforms
- Manchester Institute for Collaborative Research on Ageing