High performance plasma amyloid-β biomarkers for Alzheimer’s disease

匹兹堡化合物B 正电子发射断层摄影术 疾病 脑脊液 阿尔茨海默病 医学 淀粉样蛋白(真菌学) 生物标志物 阿尔茨海默病神经影像学倡议 神经影像学 病理 肿瘤科 淀粉样前体蛋白 内科学 化学 核医学 生物化学 精神科
作者
Akinori Nakamura,Naoki Kaneko,Victor L. Villemagne,Takashi Kato,James D. Doecke,Vincent Doré,Christopher Fowler,Qiao‐Xin Li,Ralph N. Martins,Christopher C. Rowe,Taisuke Tomita,Katsumi Matsuzaki,Kenji Ishii,Kazunari Ishii,Yutaka Arahata,Shinichi Iwamoto,Kengo Ito,Koichi Tanaka,Colin L. Masters,Katsuhiko Yanagisawa
出处
期刊:Nature [Nature Portfolio]
卷期号:554 (7691): 249-254 被引量:1423
标识
DOI:10.1038/nature25456
摘要

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, 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 desirable. Despite much effort, 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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