The online version of this article (doi:10.1186/s13195-017-0248-8) contains supplementary material, which is available to authorized users.
Plasma β-amyloid (Aβ) is a potential candidate for an Alzheimer’s disease (AD) biomarker because blood is an easily accessible bio-fluid, which can be collected routinely, and Aβ is one of the major hallmarks of AD pathogenesis in the brain. However, the association between plasma Aβ levels and AD diagnosis is still unclear due to the instability and inaccurate measurements of plasma Aβ levels in the blood of patients with AD. If a consistent value of plasma Aβ from the blood can be obtained, this might help determine whether plasma Aβ is a potential biomarker for AD diagnosis.
We predicted the brain amyloid deposit by measuring the plasma Aβ levels. This cross-sectional study included 353 participants (215 cognitively normal, 79 with mild cognitive impairment, and 59 with AD dementia) who underwent Pittsburgh-compound B positron emission tomography (PiB-PET) scans. We treated a mixture of protease inhibitors and phosphatase inhibitors (MPP) and detected plasma Aβ42 and Aβ40 (MPP-Aβ42 and MPP-Aβ40) in a stable manner using xMAP technology.
MPP-Aβ40 and MPP-Aβ42/40 (MPP-Aβs) were significantly different between subjects with positive amyloid deposition (PiB+) and those with negative amyloid deposition (PiB–) (P < 0.0001). Furthermore, MPP-Aβ40 (P < 0.0001, r = 0.23) and MPP-Aβ42/40 ratio (P < 0.0001, r = –0.23) showed significant correlation with global PiB deposition (standardized uptake value ratio). In addition, our integrated multivariable (MPP-Aβ42/40, gender, age, and apolipoprotein E genotypes) logistic regression model proposes a new standard for the prediction of cerebral amyloid deposition.
MPP-Aβ might be one of the potential blood biomarkers for the prediction of PiB-PET positivity in the brain.
Additional file 1: is a figure showing the experimental flow chart. (DOCX 37 kb)13195_2017_248_MOESM1_ESM.docx
Additional file 2 is a table presenting demographic data of the complete study cohort. (DOCX 58 kb)13195_2017_248_MOESM2_ESM.docx
Additional file 3: is a figure showing clinical and pathological states of the study cohort: (a) SUVR of subjects (*P < 0.05 and ***P < 0.001, ANOVA followed by Tukey’s multiple comparison test), (b) MMSE z score (*P < 0.05, ANOVA followed by Tukey’s multiple comparison test), and (c) CDR score (***P < 0.001, ANOVA followed by Tukey’s multiple comparison test). (DOCX 67 kb)13195_2017_248_MOESM3_ESM.docx
Additional file 4: is a table presenting demographic data of subjects for Proof-of-concept (POC) experiments in the study. (XLSX 11 kb)13195_2017_248_MOESM4_ESM.xlsx
Additional file 5: is a figure showing MPP-Aβs and aging: (a) CN– show significantly higher MPP-Aβ42 and MPP-Aβ42/40 ratio than YC (***P < 0.001, unpaired t test) and (b) MPP-Aβ42 and MPP-Aβ42/40 ratio show significant association with aging (***P < 0.0001, r = 0.40 for MPP-Aβ42; ***P < 0.0001, r = 0.33 for MPP-Aβ42/40 ratio; Pearson’s correlation). (XLSX 11 kb)13195_2017_248_MOESM5_ESM.xlsx
Additional file 6: is a table presenting demographic data of young-middle-aged controls. (XLSX 10 kb)13195_2017_248_MOESM6_ESM.xlsx
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