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Classification and prediction of clinical diagnosis of Alzheimer's disease based on MRI and plasma measures of α-/γ-tocotrienols and γ-tocopherol.
MedLine Citation:
PMID:  23343471     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
OBJECTIVES: The aim of this study was to evaluate the accuracy of combined structural magnetic resonance imaging (MRI) measures and plasma levels of vitamin E forms, including all eight natural vitamin E congeners (four tocopherols and four tocotrienols) and markers of vitamin E oxidative/nitrosative damage, in differentiating individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI) from cognitively intact control (CTL) subjects. SUBJECTS AND DESIGN: Overall, 81 patients with AD, 86 with MCI and 86 CTL individuals were enrolled from the longitudinal multicentre AddNeuroMed study. MRI and plasma vitamin E data were acquired at baseline. MRI scans were analysed using Freesurfer, an automated segmentation scheme which generates regional volume and cortical thickness measures. Orthogonal partial least squares to latent structures (OPLS), a multivariate data analysis technique, was used to analyse MRI and vitamin E measures in relation to AD and MCI diagnosis. RESULTS: The joint evaluation of MRI and plasma vitamin E measures enhanced the accuracy of differentiating individuals with AD and MCI from CTL subjects: 98.2% (sensitivity 98.8%, specificity 97.7%) for AD versus CTL and 90.7% (sensitivity 91.8%, specificity 89.5%) for MCI versus CTL. This combination of measures also identified 85% of individuals with MCI who converted to clinical AD at follow-up after 1 year. CONCLUSIONS: Plasma levels of tocopherols and tocotrienols together with automated MRI measures can help to differentiate AD and MCI cases from CTL subjects, and to prospectively predict MCI conversion to AD. Our results suggest the potential role of nutritional biomarkers detected in plasma - tocopherols and tocotrienols - as indirect indicators of AD pathology, and the utility of a multimodality approach. © 2013 The Association for the Publication of the Journal of Internal Medicine.
Authors:
Francesca Mangialasche; Eric Westman; Miia Kivipelto; J-Sebastian Muehlboeck; Roberta Cecchetti; Mauro Baglioni; Roberto Tarducci; Gianni Gobbi; Piero Floridi; Hilkka Soininen; Iwona Kłoszewska; Magda Tsolaki; Bruno Vellas; Christian Spenger; Simon Lovestone; Lars-Olof Wahlund; Andrew Simmons; Patrizia Mecocci;
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-1-24
Journal Detail:
Title:  Journal of internal medicine     Volume:  -     ISSN:  1365-2796     ISO Abbreviation:  J. Intern. Med.     Publication Date:  2013 Jan 
Date Detail:
Created Date:  2013-1-24     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  8904841     Medline TA:  J Intern Med     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
Copyright Information:
© 2013 The Association for the Publication of the Journal of Internal Medicine.
Affiliation:
Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden; Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy.
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