In Vivo Stable Isotope Labeling and Quantitative Mass Spectrometry Imaging of Aβ Plaque Deposition in Human Alzheimer’s
Detailed Non-Technical Summary
Our goal is to measure, for the first time in human Alzheimer’s disease (AD) brain, the rate of plaque pathology using the most advanced imaging technology. We have developed an advanced imaging protocol called SILK-SIMS, which enables us to image and measure plaque growth at the nanometer level; which this allows us to see structures much smaller than cells and measure the growth during life. Plaque growth is measured with a label given to patients (like a dye which tags newly made plaque), which we then image with SILK-SIMS, noting both the location and amount of the new growth of the plaque. We aim to measure plaque growth, using SILK-SIMS imaging, in the brain of people with mild to severe cases of AD and compare these measurements to those taken from patients without dementia. These findings will enable us to model how fast AD pathology occurs in the living human brain.
This research is unique in that we will be providing the first direct measures of plaque growth rates in the human AD brain by utilizing cutting-edge methodologies never before leveraged in the AD field. The outcomes of this study will provide new insights in order to better understand AD amyloid pathology, which can accelerate drug development and inform clinical trials. In addition, we will have established a blueprint for the investigation of other devastating neurodegenerative diseases, such as Parkinson’s disease, frontal-temporal dementia, and amyotrophic lateral sclerosis (ALS; also known as Lou Gehrig's disease).
Paterson RW, Gabelle A, Lucey BP, Barthélemy NR, Leckey CA, Hirtz C, Lehmann S, Sato C, Patterson BW, West T, Yarasheski K, Rohrer JD, Wildburger NC, Schott JM, Karch CM, Wray S, Miller TM, Elbert DL, Zetterberg H, Fox NC, Bateman RJ. SILK studies - capturing the turnover of proteins linked to neurodegenerative diseases. Nat Rev Neurol. 2019 Jun 20. doi: 10.1038/s41582-019-0222-0. [Epub ahead of print] Review. PubMed PMID: 31222062.
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