Identifying spectral markers for the differential diagnosis of dementia in biofluids and buccal cells

Paraskevaidi, Maria, Medeiros-De-morais, Camilo De lelis orcid iconORCID: 0000-0003-2573-787X, Crean, Stjohn orcid iconORCID: 0000-0001-9336-8549 and Martin, Francis L orcid iconORCID: 0000-0001-8562-4944 (2019) Identifying spectral markers for the differential diagnosis of dementia in biofluids and buccal cells. Alzheimer's & Dementia, 15 (7). pp. 1526-1527. ISSN 1552-5260

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Official URL: https://doi.org/10.1016/j.jalz.2019.08.094

Abstract

Background
Estimates of dementia prevalence have shown that 46.8 million people live with the condition worldwide and this is expected to reach 75 million by 2030 (Prince, 2015). Even though these diseases are becoming widely common, there is currently no disease-modifying therapy or at least a definitive diagnostic test that would allow for an early detection (Mangialasche et al., 2010). It is anticipated that preventative and therapeutic strategies will be more efficient in individuals with the disease at a very early stage, before extensive brain damage occurs (Sperling et al., 2011). Vibrational spectroscopic methods generate a characteristic fingerprint of a sample’s status, investigating many biomolecules, such as lipids, proteins and nucleic acids, which is of huge importance when dealing with multifactorial diseases. Previous studies have demonstrated spectroscopy’s ability to detect Alzheimer’s disease (AD) in blood samples (Paraskevaidi et al., 2017; Paraskevaidi et al., 2018a; Paraskevaidi et al., 2018b). Changes related to dementia have been shown to be reflected in the blood circulation as well as other peripheral cell sources. Buccal cells have shown to reflect changes in the brain and have been studied as potential biomarkers for AD and mild cognitive impairment (Francois et al., 2014).

Methods
We have used spectroscopic techniques to detect patients with early- and late-stage dementia. We have correlated the spectral data with relevant clinical and non-clinical information (e.g., age, gender, ethnicity and oral hygiene) and calculated the diagnostic accuracy of the test. Recruitment of more participants is on-going. Buccal swabs are collected to provide a completely non-invasive sampling method.

Results
Accurate segregation between dementing patients and healthy controls has been achieved with high diagnostic accuracy (up to 95%). Spectral markers of disease have been identified.

Conclusions
Our preliminary results show that spectroscopy holds great promise as a diagnostic tool of dementia, indicating the potential for the development of an inexpensive, label-free clinical test. Patient recruitment is still on-going with serial samples collected for monitoring purposes.


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