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Practical detection of a definitive biomarker panel for Alzheimer's disease; comparisons between matched plasma and cerebrospinal fluid

Abstract:
Previous mass spectrometry analysis of cerebrospinal fluid (CSF) has allowed the identification of a panel of molecular markers that are associated with Alzheimer's disease (AD). The panel comprises Amyloid beta, Apolipoprotein E, Fibrinogen alpha chain precursor, Keratin type I cytoskeletal 9, Serum albumin precursor, SPARC-like 1 protein and Tetranectin. Here we report the development and implementation of immunoassays to measure the abundance and diagnostic capacity of these putative biomarkers in matched lumbar CSF and blood plasma samples taken in life from individuals confirmed at post-mortem as suffering from AD (n = 10) and from screened 'cognitively healthy' subjects (n = 18). The inflammatory components of Alzheimer's disease were also investigated. Employment of supervised learning techniques permitted examination of the interrelated expression patterns of the putative biomarkers and identified inflammatory components, resulting in biomarker panels with a diagnostic accuracy of 87.5% and 86.7% for the plasma and CSF datasets respectively. This is extremely important as it offers an ideal high-throughput and relatively inexpensive population screening approach. It appears possible to determine the presence or absence of AD based on our biomarker panel and it seems likely that a cheap and rapid blood test for AD is feasible.
Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MSD
Department:
Pharmacology
Role:
Author


Publisher:
e-Century Publishing
Journal:
International Journal of Molecular Epidemiology and Genetics More from this journal
Volume:
5
Issue:
2
Pages:
53-70
Publication date:
2014-01-01
Acceptance date:
2014-03-18
EISSN:
1948-1756
Pmid:
24959311


Language:
English
Keywords:
Pubs id:
pubs:469886
UUID:
uuid:944f2a1d-f8d0-4c80-b1d4-91f7a7eaf4be
Local pid:
pubs:469886
Source identifiers:
469886
Deposit date:
2016-12-18

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