单位：[1]Medical School of Chinese People’s Liberation Army, Beijing, China[2]Department of Neurology, The 2nd Medical Center,National Clinical Research Center for Geriatric Disease, Chinese People’s Liberation Army General Hospital, Beijing, China[3]Health Service Department of the Guard Bureau of the Joint Staff Department, Joint Staff of the Central MilitaryCommission of Chinese PLA, Beijing, China[4]Department of Neurology, Lishilu Outpatient, Jingzhong Medical District,Chinese People’s Liberation Army General Hospital, Beijing, China[5]The Psycho Department of Beijing Geriatric Hospital,Beijing, China[6]Department of Neurology, Beijing Friendship Hospital, Capital Medical University, Beijing, China,临床科室神经内科神经内科首都医科大学附属北京友谊医院[7]Department of Neurology, Air Force Medical Center, Chinese People’s Liberation Army, Beijing, China[8]Departmentof Geriatrics, The Second Hospital of Hebei Medical University, Shijiazhuang, China[9]National Engineering Research Centerfor Protein Drugs, Beijing, China
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.
基金：
Department of Nuclear Medicine in Chinese PLA General Hospital
第一作者单位：[1]Medical School of Chinese People’s Liberation Army, Beijing, China[2]Department of Neurology, The 2nd Medical Center,National Clinical Research Center for Geriatric Disease, Chinese People’s Liberation Army General Hospital, Beijing, China[3]Health Service Department of the Guard Bureau of the Joint Staff Department, Joint Staff of the Central MilitaryCommission of Chinese PLA, Beijing, China
共同第一作者：
通讯作者：
通讯机构：[1]Medical School of Chinese People’s Liberation Army, Beijing, China[2]Department of Neurology, The 2nd Medical Center,National Clinical Research Center for Geriatric Disease, Chinese People’s Liberation Army General Hospital, Beijing, China
推荐引用方式(GB/T 7714)：
Jiao Fubin,Yi Fang,Wang Yuanyuan,et al.The Validation of Multifactor Model of Plasma A beta(42) and Total-Tau in Combination With MoCA for Diagnosing Probable Alzheimer Disease[J].FRONTIERS in AGING NEUROSCIENCE.2020,12:doi:10.3389/fnagi.2020.00212.
APA：
Jiao, Fubin,Yi, Fang,Wang, Yuanyuan,Zhang, Shouzi,Guo, Yanjun...&Wang, Luning.(2020).The Validation of Multifactor Model of Plasma A beta(42) and Total-Tau in Combination With MoCA for Diagnosing Probable Alzheimer Disease.FRONTIERS in AGING NEUROSCIENCE,12,
MLA：
Jiao, Fubin,et al."The Validation of Multifactor Model of Plasma A beta(42) and Total-Tau in Combination With MoCA for Diagnosing Probable Alzheimer Disease".FRONTIERS in AGING NEUROSCIENCE 12.(2020)
