期刊
FRONTIERS IN AGING NEUROSCIENCE
卷 12, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fnagi.2020.00212
关键词
Alzheimer disease; beta-amyloid; tau; Montreal Cognitive Assessment; ultrasensitive immunomagnetic reduction
资金
- Department of Nuclear Medicine in Chinese PLA General Hospital
Alzheimer disease (AD) has an insidious onset and heterogeneous clinical symptoms. The well-accepted biomarkers for clinical diagnosis of AD include beta-amyloid (A beta) deposition and pathologic tau level within cerebral spinal fluid (CSF) and imaging AD pathology such as positive emission tomography (PET) imaging of the amyloid-binding agent Pittsburgh compound B (PET-PiB). However, the high expense and invasive nature of these methods highly limit their wide usage in clinic practice. Therefore, it is imperious to develop less expensive and invasive methods, and plasma biomarkers are the premium targets. In the current study, we utilized a single-blind comparison method; all the probable AD cases met the core clinical National Institute on Aging and Alzheimer's Association (NIA-AA) criteria and validated by PET-PiB. We used ultrasensitive immunomagnetic reduction (IMR) assays to measure plasma A beta(42)and total-tau (t-tau) levels, in combination with different variables including A beta 42 x t-tau value, Montreal Cognitive Assessment (MoCA), and Mini Mental State Examination (MMSE). We used logistic regression to analyze the effect of all these variables in the algorism. Our results showed that (1) plasma A beta 42 and t-tau are efficient biomarkers for AD diagnosis using IMR platform, whereas A beta 42 x t-tau value is more efficient for discriminating control and AD; (2) in the control group, A beta 42 level and age demonstrated strong negative correlation; A beta 42 x t-tau value and age demonstrated significant negative correlation; (3) in the AD group, t-tau level and MMSE score demonstrated strong negative correlation; (4) using the model that A beta 42, A beta 42 x t-tau, and MoCA as the variable to generate receiver operating characteristic (ROC) curve, cutoff value = 0.48, sensitivity = 0.973, specificity = 0.982, area under the curve (AUC) = 0.986, offered better categorical efficacy, sensitivity, specificity, and AUC. The multifactor model of plasma A beta 42 and t-tau in combination with MoCA can be a viable model separate health and AD subjects in clinical practice.
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