Raman spectroscopy of blood serum for Alzheimer's disease diagnostics: specificity relative to other types of dementia

Abstract

The key moment for efficiently and accurately diagnosing dementia occurs during the early stages. This is particularly true for Alzheimer's disease (AD). In this proof-of-concept study, we applied near infrared (NIR) Raman microspectroscopy of blood serum together with advanced multivariate statistics for the selective identification of AD. We analyzed data from 20 AD patients, 18 patients with other neurodegenerative dementias (OD) and 10 healthy control (HC) subjects. NIR Raman microspectroscopy differentiated patients with more than 95% sensitivity and specificity. We demonstrated the high discriminative power of artificial neural network (ANN) classification models, thus revealing the high potential of this developed methodology for the differential diagnosis of AD. Raman spectroscopic, blood-based tests may aid clinical assessments for the effective and accurate differential diagnosis of AD, decrease the labor, time and cost of diagnosis, and be useful for screening patient populations for AD development and progression. Multivariate data analysis of blood serum Raman spectra allows for the differentiation between patients with Alzheimer's disease, other types of dementia and healthy individuals.

Keywords: Alzheimer's disease; Raman spectroscopy; artificial neural networks; blood serum; differential diagnosis.

Figure 1

Average and difference Raman spectra of human blood serum. (A) An average Raman spectrum of human blood serum obtained for healthy controls. Difference average spectra (purple lines) and spectral variations around the mean (+/-2 STD) for: (B) moderate Alzheimer's dementia and other dementia; (C) moderate Alzheimer's dementia and healthy controls; (D) moderate and mild Alzheimer's dementia cohorts; (E) mild Alzheimer's dementia and other dementia; (F) mild Alzheimer's dementia and healthy controls.

Figure 2

Raman spectral regions and bands identified by Genetic Algorithm (GA) as providing the highest discriminatory power between the serum samples. (A) Alzheimer's dementia versus healthy controls; (B) Alzheimer's dementia versus other dementias. The GA regions highlighted in red on the total average spectrum of the human blood serum (blue).