title: 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.
authors: Cell Biophysics Group, Institute of Biophysics, Imaging and Optical Science, School of Life Sciences, University of Nottingham, University Park Nottingham, United Kingdom.
authors: Joanna L
authors: JL
authors: Richens
authors: Cell Biophysics Group, Institute of Biophysics, Imaging and Optical Science, School of Life Sciences, University of Nottingham, University Park Nottingham, United Kingdom.
authors: Kelly-Ann
authors: KA
authors: Vere
authors: Institute of Biophysics, Imaging and Optical Science, University of Nottingham, University Park Nottingham, United Kingdom.
authors: Roger A
authors: RA
authors: Light
authors: School of Computer Science, University of Nottingham, Jubilee Campus Nottingham, United Kingdom ; Advanced Data Analysis Centre, University of Nottingham Nottingham, United Kingdom.
authors: Daniele
authors: D
authors: Soria
authors: School of Computer Science, University of Nottingham, Jubilee Campus Nottingham, United Kingdom ; Advanced Data Analysis Centre, University of Nottingham Nottingham, United Kingdom.
authors: Jonathan
authors: J
authors: Garibaldi
authors: Oxford Project to Investigate Memory and Ageing (OPTIMA), University Department of Physiology, Anatomy and Genetics, University of Oxford Oxford, United Kingdom.
authors: A David
authors: AD
authors: Smith
authors: Oxford Project to Investigate Memory and Ageing (OPTIMA), University Department of Physiology, Anatomy and Genetics, University of Oxford Oxford, United Kingdom.
authors: Donald
authors: D
authors: Warden
authors: Oxford Project to Investigate Memory and Ageing, Nuffield Department of Clinical Medicine, John Radcliffe Hospital Oxford, United Kingdom.
authors: Gordon
authors: G
authors: Wilcock
authors: Department of Neurology, Nottingham University Hospitals NHS Trust, Queen's Medical Centre Nottingham, United Kingdom.
authors: Nin
authors: N
authors: Bajaj
authors: School of Life Sciences, Translational Cell Sciences - Human Genetics Group, University of Nottingham, Queen's Medical Centre Nottingham, United Kingdom.
authors: Kevin
authors: K
authors: Morgan
authors: Cell Biophysics Group, Institute of Biophysics, Imaging and Optical Science, School of Life Sciences, University of Nottingham, University Park Nottingham, United Kingdom.
authors: Paul
authors: P
authors: O'Shea
keywords: Alzheimer’s disease; biomarker; blood plasma; cerebrospinal fluid