Abstract
We applied Raman spectroscopy to brain and skin tissues from a minipig model of Huntington's disease. Differences were observed between measured spectra of tissues with and without Huntington's disease, for both brain tissue and skin tissue. There are linked to changes in the chemical composition between tissue types. Using machine learning we correctly classified 96% of test spectra as diseased or wild type, indicating that the test would have a similar accuracy when used as a diagnostic tool for the disease. This suggests the technique has great potential in the rapid and accurate diagnosis of Huntington's and other neurodegenerative diseases in a clinical setting.
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