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- Title
Plasma Based Markers of [<sup>11</sup>C] PiB-PET Brain Amyloid Burden.
- Authors
Kiddle, Steven John; Thambisetty, Madhav; Simmons, Andrew; Riddoch-Contreras, Joanna; Hye, Abdul; Westman, Eric; Pike, Ian; Ward, Malcolm; Johnston, Caroline; Lupton, Michelle Katharine; Lunnon, Katie; Soininen, Hilkka; Kłoszewska, Iwona; Tsolaki, Magda; Vellas, Bruno; Mecocci, Patrizia; Lovestone, Simon; Newhouse, Stephen; Dobson, Richard; Bush, Ashley I.
- Abstract
Changes in brain amyloid burden have been shown to relate to Alzheimer's disease pathology, and are believed to precede the development of cognitive decline. There is thus a need for inexpensive and non-invasive screening methods that are able to accurately estimate brain amyloid burden as a marker of Alzheimer's disease. One potential method would involve using demographic information and measurements on plasma samples to establish biomarkers of brain amyloid burden; in this study data from the Alzheimer's Disease Neuroimaging Initiative was used to explore this possibility. Sixteen of the analytes on the Rules Based Medicine Human Discovery Multi-Analyte Profile 1.0 panel were found to associate with [11C]-PiB PET measurements. Some of these markers of brain amyloid burden were also found to associate with other AD related phenotypes. Thirteen of these markers of brain amyloid burden -- c-peptide, fibrinogen, alpha-1-antitrypsin, pancreatic polypeptide, complement C3, vitronectin, cortisol, AXL receptor kinase, interleukin-3, interleukin-13, matrix metalloproteinase-9 total, apolipoprotein E and immunoglobulin E -- were used along with co-variates in multiple linear regression, and were shown by cross-validation to explain >30% of the variance of brain amyloid burden. When a threshold was used to classify subjects as PiB positive, the regression model was found to predict actual PiB positive individuals with a sensitivity of 0.918 and a specificity of 0.545. The number of APOE ∈ 4 alleles and plasma apolipoprotein E level were found to contribute most to this model, and the relationship between these variables and brain amyloid burden was explored.
- Subjects
AMYLOID; ALZHEIMER'S disease research; GLYCOPROTEINS; BIOMARKERS; REGRESSION analysis; BRAIN imaging
- Publication
PLoS ONE, 2012, Vol 7, Issue 9, p1
- ISSN
1932-6203
- Publication type
Article
- DOI
10.1371/journal.pone.0044260