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- Pablo Cuesta, Pilar Garcés, Nazareth P Castellanos, Maria Eugenia López, Sara Aurtenetxe, Ricardo Bajo, José Angel Pineda-Pardo, Ricardo Bruña, Antonio García Marín, Marisa Delgado, Ana Barabash, Inés Ancín, Jose Antonio Cabranes, Alberto Fernandez, Francisco Del Pozo, Miguel Sancho, Alberto Marcos, Akinori Nakamura, and Fernando Maestú.
- Laboratory of Cognitive and Computational Neuroscience, Center for Biomedical Technology, Complutense University of Madrid and Technical University of Madrid, Spain Department of Basic Psychology II, Complutense University of Madrid, Spain Department of Applied Physics III, Faculty of Physics, Complutense University of Madrid, Madrid, Spain.
- J. Alzheimers Dis. 2015 Jan 1; 44 (2): 493-505.
AbstractThe apolipoprotein E (APOE) ε4 allele constitutes the major genetic risk for the development of late onset Alzheimer's disease (AD). However, its influence on the neurodegeneration that occurs in early AD remains unresolved. In this study, the resting state magnetoencephalography(MEG) recordings were obtained from 27 aged healthy controls and 36 mild cognitive impairment (MCI) patients. All participants were divided into carriers and non-carriers of the ε4 allele. We have calculated the functional connectivity (FC) in the source space along brain regions estimated using the Harvard-Oxford atlas and in the classical bands. Then, a two way ANOVA analysis (diagnosis and APOE) was performed in each frequency band. The diagnosis effect consisted of a diminished FC within the high frequency bands in the MCI patients, affecting medial temporal and parietal regions. The APOE effect produced a decreased long range FC in delta band in ε4 carriers. Finally, the interaction effect showed that the FC pattern of the right frontal-temporal region could be reflecting a compensatory/disruption process within the ε4 allele carriers. Several of these results correlated with cognitive decline and neuropsychological performance. The present study characterizes how the APOE ε4 allele and MCI status affect the brain's functional organization by analyzing the FC patterns in MEG resting state in the sources space. Therefore a combination of genetic, neuropsychological, and neurophysiological information might help to detect MCI patients at higher risk of conversion to AD and asymptomatic subjects at higher risk of developing a manifest cognitive deterioration.
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