Journal
NATURE
Volume 554, Issue 7691, Pages 249-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/nature25456
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Funding
- National Center for Geriatrics and Gerontology [25-24, 26-30]
- Japan Agency for Medical Research and Development, AMED
- UMIN [000016144]
- Alzheimer's Association (US)
- Alzheimer's Drug Discovery Foundation
- Cooperative Research Centre for Mental Health
- CSIRO Science and Industry Endowment Fund
- Dementia Collaborative Research Centres
- Victorian Government Operational Infrastructure Support program
- McCusker Alzheimer's Research Foundation
- National Health and Medical Research Council
- Yulgilbar Foundation
- Grants-in-Aid for Scientific Research [15H02492] Funding Source: KAKEN
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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 disease(1,2), supportive biomarker information is necessary. The only validated methods for identifying amyloid-beta deposition in the brain-the earliest pathological signature of Alzheimer's disease-are amyloid-beta positron-emission tomography (PET) imaging or measurement of amyloid-beta in cerebrospinal fluid. Therefore, a minimally invasive, cost-effective blood-based biomarker is desirable(3,4). Despite much effort(3-7), to our knowledge, no study has validated the clinical utility of blood-based amyloid-beta markers. Here we demonstrate the measurement of high-performance plasma amyloid-beta biomarkers by immunoprecipitation coupled with mass spectrometry. The ability of amyloid-beta precursor protein (APP)(669-711)/amyloid-beta (A beta)(1-42) and A beta(1-40)/A beta(1-42) ratios, and their composites, to predict individual brain amyloid-beta-positive or -negative status was determined by amyloid-beta-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 C-11-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-beta 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-beta-PET burden and levels of A beta(1-42) in cerebrospinal fluid. These results demonstrate the potential clinical utility of plasma biomarkers in predicting brain amyloid-beta 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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