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Diagnosis-Independent Alzheimer Disease Biomarker Signature in Cognitively Normal Elderly People

De Meyer, Geert; Shapiro, Fred; Vanderstichele, Hugo; Vanmechelen, Eugeen; Engelborghs, Sebastiaan; De Deyn, Peter Paul; Coart, Els; Hansson, Oskar LU ; Minthon, Lennart LU and Zetterberg, Henrik, et al. (2010) In Archives of Neurology 67(8). p.949-956
Abstract
Objective: To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis. Design: Mixture modeling approach. Setting: Alzheimer's Disease Neuroimaging Initiative database. Patients or Other Participants: Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment. Main Outcome Measures: Cerebrospinal fluid derived p-amyloid protein 1-42, total tau protein, and phosphorylated tau(181p) protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed. Results: Using the US... (More)
Objective: To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis. Design: Mixture modeling approach. Setting: Alzheimer's Disease Neuroimaging Initiative database. Patients or Other Participants: Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment. Main Outcome Measures: Cerebrospinal fluid derived p-amyloid protein 1-42, total tau protein, and phosphorylated tau(181p) protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed. Results: Using the US Alzheimer's Disease Neuroimaging Initiative data set, a cerebrospinal fluid beta-amyloid protein 1-42/phosphorylated tau(181P) biomarker mixture model identified 1 feature linked to AD, while the other matched the "healthy" status. The AD signature was found in 90%, 72%, and 36% of patients in the AD, mild cognitive impairment, and cognitively normal groups, respectively. The cognitively normal group with the AD signature was enriched in apolipoprotein E 64 allele carriers. Results were validated on 2 other data sets. In 1 study consisting of 68 autopsy-confirmed AD cases, 64 of 68 patients (94% sensitivity) were correctly classified with the AD feature. In another. data set with patients (n=57) with mild cognitive impairment followed up for 5 years, the model showed a sensitivity of 100% in patients progressing to AD. Conclusions: The mixture modeling approach, totally independent of clinical AD diagnosis, correctly classified patients with AD. The unexpected presence of the AD signature in more than one-third of cognitively normal subjects suggests that AD pathology is active and detectable earlier than has heretofore been envisioned. (Less)
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published
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Archives of Neurology
volume
67
issue
8
pages
949 - 956
publisher
American Medical Association
external identifiers
  • wos:000280809000006
  • scopus:77955453909
ISSN
0003-9942
language
English
LU publication?
yes
id
d9c33533-69f8-4d85-9d2a-b1bf87a3693f (old id 1677176)
alternative location
http://archneur.ama-assn.org/cgi/content/short/67/8/949
date added to LUP
2010-09-21 15:33:06
date last changed
2018-07-08 03:17:23
@article{d9c33533-69f8-4d85-9d2a-b1bf87a3693f,
  abstract     = {Objective: To identify biomarker patterns typical for Alzheimer disease (AD) in an independent, unsupervised way, without using information on the clinical diagnosis. Design: Mixture modeling approach. Setting: Alzheimer's Disease Neuroimaging Initiative database. Patients or Other Participants: Cognitively normal persons, patients with AD, and individuals with mild cognitive impairment. Main Outcome Measures: Cerebrospinal fluid derived p-amyloid protein 1-42, total tau protein, and phosphorylated tau(181p) protein concentrations were used as biomarkers on a clinically well-characterized data set. The outcome of the qualification analysis was validated on 2 additional data sets, 1 of which was autopsy confirmed. Results: Using the US Alzheimer's Disease Neuroimaging Initiative data set, a cerebrospinal fluid beta-amyloid protein 1-42/phosphorylated tau(181P) biomarker mixture model identified 1 feature linked to AD, while the other matched the "healthy" status. The AD signature was found in 90%, 72%, and 36% of patients in the AD, mild cognitive impairment, and cognitively normal groups, respectively. The cognitively normal group with the AD signature was enriched in apolipoprotein E 64 allele carriers. Results were validated on 2 other data sets. In 1 study consisting of 68 autopsy-confirmed AD cases, 64 of 68 patients (94% sensitivity) were correctly classified with the AD feature. In another. data set with patients (n=57) with mild cognitive impairment followed up for 5 years, the model showed a sensitivity of 100% in patients progressing to AD. Conclusions: The mixture modeling approach, totally independent of clinical AD diagnosis, correctly classified patients with AD. The unexpected presence of the AD signature in more than one-third of cognitively normal subjects suggests that AD pathology is active and detectable earlier than has heretofore been envisioned.},
  author       = {De Meyer, Geert and Shapiro, Fred and Vanderstichele, Hugo and Vanmechelen, Eugeen and Engelborghs, Sebastiaan and De Deyn, Peter Paul and Coart, Els and Hansson, Oskar and Minthon, Lennart and Zetterberg, Henrik and Blennow, Kaj and Shaw, Leslie and Trojanowski, John Q.},
  issn         = {0003-9942},
  language     = {eng},
  number       = {8},
  pages        = {949--956},
  publisher    = {American Medical Association},
  series       = {Archives of Neurology},
  title        = {Diagnosis-Independent Alzheimer Disease Biomarker Signature in Cognitively Normal Elderly People},
  volume       = {67},
  year         = {2010},
}