载脂蛋白E
神经影像学
医学
阿尔茨海默病
脑淀粉样血管病
淀粉样蛋白(真菌学)
认知功能衰退
内科学
代理终结点
病理
疾病
痴呆
精神科
作者
Steven J. Kiddle,Madhav Thambisetty,Andrew Simmons,Joanna Riddoch-Contreras,Abdul Hye,Eric Westman,Ian Pike,Malcolm Ward,Caroline Johnston,Michelle K. Lupton,Katie Lunnon,Hilkka Soininen,Iwona Kłoszewska,Magda Tsolaki,Bruno Vellas,Patrizia Mecocci,Simon Lovestone,Stephen J. Newhouse,Richard Dobson,Alzheimer’s Disease Neuroimaging Initiative
出处
期刊:PLOS ONE
[Public Library of Science]
日期:2012-09-24
卷期号:7 (9): e44260-e44260
被引量:82
标识
DOI:10.1371/journal.pone.0044260
摘要
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 ϵ 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.
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