Details

Autor(en) / Beteiligte

• 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
• Kloszewska, Iwona
• Tsolaki, Magda
• Vellas, Bruno
• Mecocci, Patrizia
• Lovestone, Simon
• Newhouse, Stephen
• Dobson, Richard
• Bush, Ashley I.

Titel

Plasma based markers of [11C] PiB-PET brain amyloid burden

Ist Teil von

• PloS one, 2012-09, Vol.7 (9), p.e44260-e44260

Ort / Verlag

United States: Public Library of Science

Erscheinungsjahr

2012

Quelle

MEDLINE

Beschreibungen/Notizen

• 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 [(11)C]-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 [Symbol: see text] 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.