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Disrupted Network Topology in Patients with Stable and Progressive Mild Cognitive Impairment and Alzheimer's Disease

Journal article
Authors Joana B. Pereira
Mite Mijalkov
Ehsan Kakaei
Patricia Mecocci
Bruno Vellas
Magda Tsolaki
Iwona Kłoszewska
Hilka Soininen
Christian Spenger
Simmon Lovestone
Andrew Simmons
Lars Olof Wahlund
Giovanni Volpe
Eric Westman
Published in Cerebral Cortex
Volume 26
Pages 3476-3493
ISSN 10473211
Publication year 2016
Published at
Pages 3476-3493
Language en
Keywords closeness centrality, clustering, modularity, structural covariance networks, transitivity
Subject categories Clinical Medicine

Abstract

© 2016 Published by Oxford University Press. Recent findings suggest that Alzheimer's disease (AD) is a disconnection syndrome characterized by abnormalities in large-scale networks. However, the alterations that occur in network topology during the prodromal stages of AD, particularly in patients with stable mild cognitive impairment (MCI) and those that show a slow or faster progression to dementia, are still poorly understood. In this study, we used graph theory to assess the organization of structural MRI networks in stable MCI (sMCI) subjects, late MCI converters (lMCIc), early MCI converters (eMCIc), and AD patients from 2 large multicenter cohorts: ADNI and AddNeuroMed. Our findings showed an abnormal global network organization in all patient groups, as reflected by an increased path length, reduced transitivity, and increased modularity compared with controls. In addition, lMCIc, eMCIc, and AD patients showed a decreased path length and mean clustering compared with the sMCI group. At the local level, there were nodal clustering decreases mostly in AD patients, while the nodal closeness centrality detected abnormalities across all patient groups, showing overlapping changes in the hippocampi and amygdala and nonoverlapping changes in parietal, entorhinal, and orbitofrontal regions. These findings suggest that the prodromal and clinical stages of AD are associated with an abnormal network topology.

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