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

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.

Serum-based differentiation between multiple sclerosis and amyotrophic lateral sclerosis by Random Forest classification of FTIR spectra

“…Besides being an established tool in analytical chemistry, FTIR spectroscopy is being established as a tool to address key questions in biology and medicine. In particular, FTIR spectroscopy is emerging as a tool to distinguish diseased samples from healthy ones [11][12][13][14][15][16][17][18][19][20][21] which is paving the way for FTIR spectroscopy to become a clinical diagnosis tool.…”

Tutorial: multivariate classification for vibrational spectroscopy in biological samples

“…In biological applications, the first pre-processing usually consist of truncating the biofingerprint region: 1800-900 cm -1 for IR data 5 , 2000 to 500 cm -1 for Raman 5 , and 900 to 2600 nm for NIR 44 . This removes spectral artefacts such as water and CO2 absorptions present in other parts of the IR spectrum, and additional baseline distortions that may be present in the spectrum 42 .…”

“…For example, the extended multiplicative signal correction (EMSC) algorithm has been reported to neutralise variability caused by paraffin signal and allow selection of unique spectral features related to the sample composition in vibrational spectroscopy 49,50 ; independent component analysis (ICA) and non-negatively constrained least squares (NCLS) are also common methods of digital de-waxing for vibrational spectroscopy 49,51,52 . Glass contributions are reduced in the high-wavenumber region of the mid-IR spectrum, thus allowing spectral data analysis within the region between ~2500-3800 cm -1 53 ; and can be reduced in NIR spectroscopy by subtracting the glass spectrum from the sample spectrum and by working in the wavelength range of 1850-2150 nm 44 .…”

Near-infrared spectroscopy of blood plasma with chemometrics towards HIV discrimination during pregnancy

“…Mass spectrometry and nuclear magnetic resonance (NMR) are the most common spectrometric techniques due to their relatively good sensitivity and specificity to detect diseases, although they carry an elevated cost and require a complex experimental setup 6 . Near-infrared (NIR) spectroscopy is a spectrometric technique that explores high-energy vibrational modes of molecular chemical bonds, generating a sample spectrochemical spectrum in the region between 750 to 2500 nm 7 – 9 . This technique employs relatively simple and low-cost instrumentation when compared to mass spectrometry, NMR or even mid-infrared spectroscopy, and is widely available in portable handheld devices for in-field analysis.…”

“…NIR together with chemometric methods has played an increasingly important role in the field of medical and biological analysis, through quickly detecting pathological conditions, even at very early stages. Previous studies have demonstrated the clinical applications of using NIR spectroscopy in biological samples such as to detect Alzheimer’s disease in blood plasma with 93% of accuracy, 88% of sensibility and 96% of specificity 9 ; to differentiate strains of Klebsiella pneumonia producing and non-producing carbapenemase 10 ; and for the identification of Aedes aegypti mosquitoes infected by the Zika virus 11 . It was also used with HIV, however, with others goals that were not the discrimination between infected and healthy groups 7 .…”