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Identification of a blood-based biomarker panel for classification of Alzheimer's disease.
MedLine Citation:
PMID:  21466745     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
An ideal diagnostic test for Alzheimer's disease (AD) should be non-invasive and easily applicable. Thus, there is a clear need to search for biomarkers in blood. In the present study, we have used multivariate data analysis [support vector machine (SVM)] to investigate whether a blood-based biomarker panel allows discrimination between AD patients and healthy controls at the individual level. We collected a total of 155 serum samples from individuals with early AD and age-matched healthy controls and measured serum levels of 24 markers involved in several biological pathways by ELISA. The dataset was randomly split into a training set for predictor discovery and classification training and a test set for class prediction of blinded samples (3:1 ratio) to evaluate the chosen predictors and parameters. After selection of a feature group of the three most discriminative parameters (cortisol, von Willebrand factor, oxidized LDL antibodies) in the training set, the application of SVM to the training/independent test dataset resulted in an 81.7%/87.1% correct classification for AD and control subjects. In conclusion, we identified a panel of three blood markers, which allowed SVM-based distinguishing of AD patients from healthy controls on a single-subject classification level with clinically relevant accuracy and validity. Blood-based biomarkers might have utility in AD diagnostics as screening tool before further classification with CSF biomarkers and imaging. Future studies should examine whether blood-based biomarkers may also be useful to differentiate AD patients from other dementias.
Authors:
Christoph Laske; Thomas Leyhe; Elke Stransky; Nadine Hoffmann; Andreas J Fallgatter; Janko Dietzsch
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2011-4-5
Journal Detail:
Title:  The international journal of neuropsychopharmacology / official scientific journal of the Collegium Internationale Neuropsychopharmacologicum (CINP)     Volume:  -     ISSN:  1469-5111     ISO Abbreviation:  -     Publication Date:  2011 Apr 
Date Detail:
Created Date:  2011-4-6     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9815893     Medline TA:  Int J Neuropsychopharmacol     Country:  -    
Other Details:
Languages:  ENG     Pagination:  1-9     Citation Subset:  -    
Affiliation:
Department of Psychiatry and Psychotherapy, University of Tuebingen, Tuebingen, Germany.
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