Journal
MOLECULAR PSYCHIATRY
Volume 19, Issue 4, Pages 519-526Publisher
SPRINGERNATURE
DOI: 10.1038/mp.2013.40
Keywords
Alzheimer's disease; amyloid beta; blood biomarkers
Funding
- CSIRO Flagship Collaboration Fund
- Science and Industry Endowment Fund (SIEF)
- Edith Cowan University (ECU)
- Mental Health Research institute (MHRI)
- Alzheimer's Australia (AA)
- National Ageing Research Institute (NARI)
- Austin Health
- CogState
- Hollywood Private Hospital
- Sir Charles Gardner Hospital
- National Health and Medical Research Council (NHMRC)
- Dementia Collaborative Research Centres programme (DCRC)
- McCusker Alzheimer's Research Foundation
- Government of Victoria
- National Health and Medical Research Council training fellowship
- Edith Cowan University
- NHMRC
- Australian Fellowship
- Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant) [U01 AG024904]
- National Institute on Aging
- National Institute of Biomedical Imaging and Bioengineering
- Canadian Institutes of Health Research is providing funds ADNI clinical sites in Canada
- Foundation for the National Institutes of Health
- NIH [P30 AG010129, K01 AG030514]
- Abbott
- Alzheimer's Association
- Alzheimer's Drug Discovery Foundation
- Amorfix Life Sciences
- AstraZeneca
- Bayer HealthCare
- BioClinica
- Biogen Idec
- Bristol-Myers Squibb Company
- Eisai
- Elan Pharmaceuticals
- Eli Lilly and Company
- F Hoffmann-La Roche and its affiliated company Genentech
- GE Healthcare
- Innogenetics, NV
- Janssen Alzheimer Immunotherapy Research and Development
- Johnson & Johnson Pharmaceutical Research Development
- Medpace
- Merck Co.
- Meso Scale Diagnostics
- Novartis Pharmaceuticals Corporation
- Pfizer
- Servier
- Synarc and Takeda Pharmaceutical Company
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Dementia 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 A beta (extracellular beta-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 A beta accumulation, therefore, providing a platform for developing a population-based screen.
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