Novel Methodology for Alzheimer's Disease Biomarker Identification in Plasma using Hyperspectral Microscopy

Abstract

Alzheimer's disease (AD) is a gradually progressive neurocognitive disorder (NCD) with a preclinical phase where the patient can be asymptomatic for many years. The detection of AD in its earliest stages is one of the most active areas in Alzheimer's science. This early diagnosis could potentially allow for early intervention and improved prognosis, once effective treatment is available. This paper proposes a novel methodology based on spectral unmixing for the identification of biomarkers in plasma samples using visual and near infrared (VNIR) hyperspectral microscopy (HSM). The study was performed using ten drop plasma samples from 10 patients (5 control and 5 case subjects affected by NCD) captured with HSM at two different magnifications: 5× and 20×. This data was processed, and a statistical analysis of the abundance estimation was performed to identify relevant endmembers to differentiate case and control groups. The results suggest the potential of HSM and plasma samples as a cost-effective early diagnosis tool.