Please use this identifier to cite or link to this item: https://ahro.austin.org.au/austinjspui/handle/1/11754
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dc.contributor.authorSamantha C, Samantha C-
dc.contributor.authorFaux, N G-
dc.contributor.authorWilson, W-
dc.contributor.authorLaws, Simon M-
dc.contributor.authorAmes, David-
dc.contributor.authorBedo, J-
dc.contributor.authorBush, Ashley I-
dc.contributor.authorDoecke, James D-
dc.contributor.authorEllis, Kathryn A-
dc.contributor.authorHead, R-
dc.contributor.authorJones, G-
dc.contributor.authorKiiveri, H-
dc.contributor.authorMartins, Ralph N-
dc.contributor.authorRembach, Alan-
dc.contributor.authorRowe, Christopher C-
dc.contributor.authorSalvado, Olivier-
dc.contributor.authorMacaulay, S Lance-
dc.contributor.authorMasters, Colin L-
dc.contributor.authorVillemagne, Victor L-
dc.date.accessioned2015-05-16T01:22:52Z
dc.date.available2015-05-16T01:22:52Z
dc.date.issued2013-04-30-
dc.identifier.citationMolecular Psychiatry 2013; 19(4): 519-26en
dc.identifier.otherPUBMEDen
dc.identifier.urihttps://ahro.austin.org.au/austinjspui/handle/1/11754en
dc.description.abstractDementia is a global epidemic with Alzheimer's disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aβ (extracellular β-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aβ accumulation, therefore, providing a platform for developing a population-based screen.en
dc.language.isoenen
dc.subject.otherAgeden
dc.subject.otherAged, 80 and overen
dc.subject.otherAlzheimer Disease.blood.genetics.pathologyen
dc.subject.otherAmyloid beta-Peptides.metabolismen
dc.subject.otherAniline Compounds.diagnostic useen
dc.subject.otherApolipoproteins E.geneticsen
dc.subject.otherChemokine CCL3.blooden
dc.subject.otherCohort Studiesen
dc.subject.otherCullin Proteinsen
dc.subject.otherFemaleen
dc.subject.otherHumansen
dc.subject.otherInterleukin-17en
dc.subject.otherMaleen
dc.subject.otherNeocortex.metabolism.radionuclide imagingen
dc.subject.otherPancreatic Polypeptideen
dc.subject.otherPositron-Emission Tomographyen
dc.subject.otherPredictive Value of Testsen
dc.subject.otherROC Curveen
dc.subject.otherThiazoles.diagnostic useen
dc.titleA blood-based predictor for neocortical Aβ burden in Alzheimer's disease: results from the AIBL study.en
dc.typeJournal Articleen
dc.identifier.journaltitleMolecular psychiatryen
dc.identifier.affiliationAcademic Unit for Psychiatry of Old Age, Department of Psychiatry, The University of Melbourne, Kew, Victoria, Australiaen
dc.identifier.affiliationCSIRO Preventative Health Flagship: Mathematics, Informatics and Statistics, Herston, QLD, Australiaen
dc.identifier.affiliationCSIRO Preventative Health Flagship: Health and Life Sciences, Urrbrae, SA, Australiaen
dc.identifier.affiliationCSIRO Preventative Health Flagship: Information and Communication Technology, Herston, QLD, Australiaen
dc.identifier.affiliationVictorian Research Laboratory, National ICT of Australia (NICTA), Melbourne, Victoria, Australiaen
dc.identifier.affiliationCSIRO Preventative Health Flagship: Mathematics, Informatics and Statistics, Perth, WA, Australiaen
dc.identifier.affiliationCSIRO Preventative Health Flagship: Mathematics, Informatics and Statistics, North Ryde, NSW, Australiaen
dc.identifier.affiliationMental Health Research Institute (MHRI), The University of Melbourne, Parkville, Victoria, Australiaen
dc.identifier.affiliationCSIRO Preventative Health Flagship: Materials Science and Engineering, Parkville, Victoria, Australiaen
dc.identifier.affiliationDepartment of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, Victoria, Australiaen
dc.identifier.affiliationAcademic Unit for Psychiatry of Old Age, Department of Psychiatry, The University of Melbourne, Kew, Victoria, Australiaen
dc.identifier.affiliationDepartment of Medicine, Austin Health, The University of Melbourne, Heidelberg, VIC, Australiaen
dc.identifier.affiliationNational Ageing Research Institute, Parkville, VIC, Australiaen
dc.identifier.affiliationSir James McCusker Alzheimer's Disease Research Unit, Hollywood Private Hospital, Perth, WA, Australiaen
dc.identifier.affiliationCentre of Excellence for Alzheimer's Disease Research & Care, School of Medical Sciences, Edith Cowan University, Joondalup, WA, Australiaen
dc.identifier.affiliationDepartment of Nuclear Medicine and Centre for PET, Austin Health, Heidelberg, VIC, Australiaen
dc.identifier.doi10.1038/mp.2013.40en
dc.description.pages519-26en
dc.relation.urlhttps://pubmed.ncbi.nlm.nih.gov/23628985en
dc.contributor.corpauthorAlzheimer’s Disease Neuroimaging Initiativeen
dc.contributor.corpauthorAustralian Imaging, Biomarkers and Lifestyle Study Research Groupen
dc.type.contentTexten
dc.type.austinJournal Articleen
local.name.researcherMasters, Colin L
item.openairetypeJournal Article-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.cerifentitytypePublications-
item.languageiso639-1en-
crisitem.author.deptMolecular Imaging and Therapy-
crisitem.author.deptThe Florey Institute of Neuroscience and Mental Health-
crisitem.author.deptMolecular Imaging and Therapy-
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