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A blood-based predictor for neocortical Aβ burden in Alzheimer’s disease: results from the AIBL study

Abstract

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 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.

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Acknowledgements

Core funding for the study was provided by the CSIRO Flagship Collaboration Fund, and the Science and Industry Endowment Fund (SIEF) in partnership with 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. The study also receives funding from the National Health and Medical Research Council (NHMRC), the Dementia Collaborative Research Centres programme (DCRC), The McCusker Alzheimer’s Research Foundation and Operational Infrastructure Support from the Government of Victoria. Faux NG is supported by a National Health and Medical Research Council training fellowship. Laws SM is supported by research fellowships from Edith Cowan University. Bush AI is supported by the NHMRC by a programme grant and an Australian Fellowship. We wish to thank the participants in AIBL for their commitment and dedication to help in advance research into the early detection and causation of AD, and the clinicians who referred patients to the study. Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: 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. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organisation is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuroimaging at the University of California, Los Angeles. This research was also supported by NIH grants P30 AG010129 and K01 AG030514.

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Correspondence to S C Burnham.

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We declare that Colin L Masters and Ashley I Bush are consultants with Prana Biotechnology. Further, a patent has been filed covering the biomarker algorithm from this work and our institutions may benefit from commercialisation of this patent.

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Burnham, S., Faux, N., Wilson, W. et al. A blood-based predictor for neocortical Aβ burden in Alzheimer’s disease: results from the AIBL study. Mol Psychiatry 19, 519–526 (2014). https://doi.org/10.1038/mp.2013.40

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