Hyperspectral Raman imaging of neuritic plaques and neurofibrillary tangles in brain tissue from Alzheimer's disease patients. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Michael, Ralph; Lenferink, Aufried; Vrensen, Gijs; Gelpi, Ellen; Barraquer, Rafael; Otto, Cees
• Is Part Of: Scientific reports. Volume 7:Issue 1(2017)
• Page Start: 1
• Page End: 11
• Publication Date: 2017-12
• Subjects: Natural history -- Research -- Periodicals; Biology -- Research -- Periodicals; Physical sciences -- Research -- Periodicals; Earth sciences -- Research -- Periodicals; Environmental sciences -- Research -- Periodicals; 502.85
• DOI: 10.1038/s41598-017-16002-3
• Languages: English
• ISSNs: 2045-2322

Abstract

Abstract Neuritic plaques and neurofibrillary tangles are crucial morphological criteria for the definite diagnosis of Alzheimer's disease. We evaluated 12 unstained frontal cortex and hippocampus samples from 3 brain donors with Alzheimer's disease and 1 control with hyperspectral Raman microscopy on samples of 30 × 30 µm. Data matrices of 64 × 64 pixels were used to quantify different tissue components including proteins, lipids, water and beta-sheets for imaging at 0.47 µm spatial resolution. Hierarchical cluster analysis was performed to visualize regions with high Raman spectral similarities. The Raman images of proteins, lipids, water and beta-sheets matched with classical brain morphology. Protein content was 2.0 times, the beta-sheet content 5.6 times and Raman broad-band autofluorescence was 2.4 times higher inside the plaques and tangles than in the surrounding tissue. The lipid content was practically equal inside and outside. Broad-band autofluorescence showed some correlation with protein content and a better correlation with beta-sheet content. Hyperspectral Raman imaging combined with hierarchical cluster analysis allows for the identification of neuritic plaques and neurofibrillary tangles in unstained, label-free slices of human Alzheimer's disease brain tissue. It permits simultaneous quantification and distinction of several tissue components such as proteins, lipids, water and beta-sheets.