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Title: A plasma protein classifier for predicting amyloid burden for preclinical Alzheimer's disease.
Austin Authors: Ashton, Nicholas J;Nevado-Holgado, Alejo J;Barber, Imelda S;Lynham, Steven;Gupta, Veer;Chatterjee, Pratishtha;Goozee, Kathryn;Hone, Eugene;Pedrini, Steve;Blennow, Kaj;Schöll, Michael;Zetterberg, Henrik;Ellis, Kathryn A;Bush, Ashley I;Rowe, Christopher C ;Villemagne, Victor L ;Ames, David;Masters, Colin L ;Aarsland, Dag;Powell, John;Lovestone, Simon;Martins, Ralph;Hye, Abdul
Affiliation: Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
Department of Psychiatry, University of Oxford, Oxford, UK
Proteomics Core Facility, James Black Centre, King's College, London, UK
UK Dementia Research Institute at UCL, London, UK
Department of Molecular Imaging and Therapy, Austin Health, Heidelberg, Victoria, Australia
The Florey Institute, University of Melbourne, VIC, Australia
School of Medical Sciences, Edith Cowan University, Joondalup, WA, Australia
Cooperative Research Centre for Mental Health, Carlton South, VIC, Australia
KaRa Institute of Neurological Diseases, Macquarie Park, NSW, Australia
Department of Biomedical Sciences, Macquarie University, 2109, NSW, Australia
Academic Unit for Psychiatry of Old Age, St. George's Hospital, University of Melbourne, VIC, Australia
National Ageing Research Institute, Parkville, VIC, Australia
Clinical Research Department, Anglicare, Sydney, NSW, Australia
School of Psychiatry and Clinical Neurosciences, University of Western Australia, WA, Australia
School of Medicine, Faculty of Health, Deakin University, 3220 VIC, Australia
Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, Sweden
Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
Issue Date: Feb-2019 2019-02-06
Publication information: Science advances 2019; 5(2): eaau7220
Abstract: A blood-based assessment of preclinical disease would have huge potential in the enrichment of participants for Alzheimer's disease (AD) therapeutic trials. In this study, cognitively unimpaired individuals from the AIBL and KARVIAH cohorts were defined as Aβ negative or Aβ positive by positron emission tomography. Nontargeted proteomic analysis that incorporated peptide fractionation and high-resolution mass spectrometry quantified relative protein abundances in plasma samples from all participants. A protein classifier model was trained to predict Aβ-positive participants using feature selection and machine learning in AIBL and independently assessed in KARVIAH. A 12-feature model for predicting Aβ-positive participants was established and demonstrated high accuracy (testing area under the receiver operator characteristic curve = 0.891, sensitivity = 0.78, and specificity = 0.77). This extensive plasma proteomic study has unbiasedly highlighted putative and novel candidates for AD pathology that should be further validated with automated methodologies.
DOI: 10.1126/sciadv.aau7220
ORCID: 0000-0001-9276-2720
PubMed URL: 30775436
Type: Journal Article
Appears in Collections:Journal articles

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