Affiliation:
1. Imperial College London
2. Charnley Fold, Lancashire and South Cumbria NHS Foundation Trust
3. Federal Institute of Science and Technology of Sertão Pernambucano – Campus Floresta
4. University of Central Lancashire (UCLan)
Abstract
Abstract
Background: As general ageing increases, a higher global prevalence of dementia increases in likelihood. Alzheimer’s disease is predicted to triple in cases by 2050, becoming a global concern with heavy impact on socio-economic levels.
Although numerous biomarkers have been explored, their clinical performance, especially in early stages, is limited. Current diagnostic approaches also necessitate the use of invasive procedures or laborious and expensive imaging techniques.
A rapid, low-cost and non-invasive test for the detection of Alzheimer’s disease could be used for the effective identification of individuals that would need referral for further testing. Oral cavity-derived samples, including saliva and buccal mucosal cells, are considered rich sources of biomarkers for Alzheimer’s disease since they can reflect peripheral changes and correlate well with the disease state.
Methods: We assessed the potential of attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy as a diagnostic tool for Alzheimer’s disease using oral buccal cells.
Findings: After spectroscopic analysis and use of machine learning algorithms, this approach achieved 76% sensitivity and 100% specificity (area under the curve (AUC): 88%) in differentiating patients with Alzheimer’s disease from age-matched healthy controls.
Conclusion: We demonstrate that spectroscopic analysis of buccal cells could detect patients with Alzheimer’s disease with high diagnostic accuracy. Such a test has the potential to provide a non‐invasive, rapid and cost-effective alternative to current CSF and blood sampling procedures. An earlier diagnosis of Alzheimer’s disease and timely intervention are expected to impact on the disease progression.
Publisher
Research Square Platform LLC
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