Jump to main content
Jump to site search


Blood-based near-infrared spectroscopy for the rapid low-cost detection of Alzheimer's disease

Author affiliations

Abstract

Alzheimer's disease (AD) is currently under-diagnosed and is predicted to affect a great number of people in the future, due to the unrestrained aging of the population. An accurate diagnosis of AD at an early stage, prior to (severe) symptomatology, is of crucial importance as it would allow the subscription of effective palliative care and/or enrolment into specific clinical trials. Today, new analytical methods and research initiatives are being developed for the on-time diagnosis of this devastating disorder. During the last decade, spectroscopic techniques have shown great promise in the robust diagnosis of various pathologies, including neurodegenerative diseases and dementia. In the current study, blood plasma samples were analysed with near-infrared (NIR) spectroscopy as a minimally-invasive method to distinguish patients with AD (n = 111) from non-demented volunteers (n = 173). After applying multivariate classification models (principal component analysis with quadratic discriminant analysis – PCA-QDA), AD individuals were correctly identified with 92.8% accuracy, 87.5% sensitivity and 96.1% specificity. Our results show the potential of NIR spectroscopy as a simple and cost-effective diagnostic tool for AD. Robust and early diagnosis may be a first step towards tackling this disease by allowing timely intervention.

Graphical abstract: Blood-based near-infrared spectroscopy for the rapid low-cost detection of Alzheimer's disease

Back to tab navigation

Supplementary files

Publication details

The article was received on 30 Jun 2018, accepted on 14 Aug 2018 and first published on 15 Aug 2018


Article type: Paper
DOI: 10.1039/C8AN01205A
Citation: Analyst, 2018, Advance Article
  •   Request permissions

    Blood-based near-infrared spectroscopy for the rapid low-cost detection of Alzheimer's disease

    M. Paraskevaidi, C. L. M. Morais, D. L. D. Freitas, K. M. G. Lima, D. M. A. Mann, D. Allsop, P. L. Martin-Hirsch and F. L. Martin, Analyst, 2018, Advance Article , DOI: 10.1039/C8AN01205A

Search articles by author

Spotlight

Advertisements