To facilitate clinical trials of disease-modifying therapies for Alzheimer’s disease, which are expected to be most efficacious at the earliest and mildest stages of the disease1,2, supportive biomarker information is necessary. The only validated methods for identifying amyloid-β deposition in the brain—the earliest pathological signature of Alzheimer’s disease—are amyloid-β positron-emission tomography (PET) imaging or measurement of amyloid-β in cerebrospinal fluid. Therefore, a minimally invasive, cost-effective blood-based biomarker is desirable3,4. Despite much effort3,4,5,6,7, to our knowledge, no study has validated the clinical utility of blood-based amyloid-β markers. Here we demonstrate the measurement of high-performance plasma amyloid-β biomarkers by immunoprecipitation coupled with mass spectrometry. The ability of amyloid-β precursor protein (APP)669–711/amyloid-β (Aβ)1–42 and Aβ1–40/Aβ1–42 ratios, and their composites, to predict individual brain amyloid-β-positive or -negative status was determined by amyloid-β-PET imaging and tested using two independent data sets: a discovery data set (Japan, n = 121) and a validation data set (Australia, n = 252 including 111 individuals diagnosed using 11C-labelled Pittsburgh compound-B (PIB)-PET and 141 using other ligands). Both data sets included cognitively normal individuals, individuals with mild cognitive impairment and individuals with Alzheimer’s disease. All test biomarkers showed high performance when predicting brain amyloid-β burden. In particular, the composite biomarker showed very high areas under the receiver operating characteristic curves (AUCs) in both data sets (discovery, 96.7%, n = 121 and validation, 94.1%, n = 111) with an accuracy approximately equal to 90% when using PIB-PET as a standard of truth. Furthermore, test biomarkers were correlated with amyloid-β-PET burden and levels of Aβ1–42 in cerebrospinal fluid. These results demonstrate the potential clinical utility of plasma biomarkers in predicting brain amyloid-β burden at an individual level. These plasma biomarkers also have cost–benefit and scalability advantages over current techniques, potentially enabling broader clinical access and efficient population screening.
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The NCGG study group thank all participants of the study, clinicians who referred patients, and all the staff who supported the MULNIAD project. We thank N. Sugimoto for conducting statistical analyses, S. Niida and the NCGG Biobank members for the management of plasma samples and M. Kawakage for data monitoring. This study was supported by The Research Funding for Longevity Sciences (25-24 and 26-30) from the National Center for Geriatrics and Gerontology, and partially supported by Research and Development Grants for Dementia from the Japan Agency for Medical Research and Development, AMED. This study is registered under UMIN ID: 000016144. The AIBL study would like to thank all participants of the study and the clinicians who referred participants. The AIBL study (https://aibl.csiro.au/) is a consortium between Austin Health, CSIRO, Edith Cowan University and the Florey Institute, The University of Melbourne. Partial financial support was provided by the Alzheimer’s Association (US), the Alzheimer’s Drug Discovery Foundation, an anonymous foundation, the Cooperative Research Centre for Mental Health, CSIRO Science and Industry Endowment Fund, the Dementia Collaborative Research Centres, the Victorian Government Operational Infrastructure Support program, the McCusker Alzheimer’s Research Foundation, the National Health and Medical Research Council, and the Yulgilbar Foundation. Funding sources had no role in study design, data collection, data analyses or data interpretation.
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Nature Reviews Neurology (2018)