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

Abstract

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.

Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data

“…Our results are consistent with an MRI study performed by Pereira et al (30) that found in two large, multicenter cohorts a progressive degradation in the connectivity of brain functional networks in patient groups having the same characteristics as in our study, including MCI converters followed up for 1 and 3 y. The most striking similarity with our study was the finding of a progressive increase in modularity with severity of the disease, suggesting a degradation of whole-brain networks into segregated components.…”

A more randomly organized grey matter network is associated with deteriorating language and global cognition in individuals with subjective cognitive decline

“…In the dementia stages of AD grey matter networks seem to show a more random topology, as indicated by a reduced normalized clustering (i.e., gamma) and/or normalized path length (i.e., lambda) (He, Chen, & Evans, 2008;Pereira et al, 2016;Tijms et al, 2013a;Yao et al, 2010). In the present study we investigated whether a more random grey matter network organization is associated with early cognitive changes in individuals with SCD.…”

“…Although, the biological meaning of structural similarities is not yet fully understood, grey matter similarity has been demonstrated to be associated with synchronized maturation between brain regions (Alexander‐Bloch and Bullmore, ; Alexander‐Bloch, Raznahan, Bullmore, & Giedd, b; Andrews, Halpern, & Purves, ), which might be reflected by a higher degree of clustering. Previous cross‐sectional studies have demonstrated that alterations of grey matter network parameters are associated with disease severity (Pereira et al, ; Tijms et al, ; Yao et al, ; Zhou and Lui, ) and with the degree of cognitive impairment in AD (Tijms et al, ). A group‐based network study suggested that grey matter networks that more resemble randomly organized networks are associated with future progression to dementia in individuals with mild cognitive impairment (Pereira et al, 2016).…”

“…Previous cross-sectional studies have demonstrated that alterations of grey matter network parameters are associated with disease severity (Pereira et al, 2016;Tijms et al, 2013a;Yao et al, 2010;Zhou and Lui, 2013) and with the degree of cognitive impairment in AD (Tijms et al, 2014). A group-based network study suggested that grey matter networks that more resemble randomly organized networks are associated with future progression to dementia in individuals with mild cognitive impairment (Pereira et al, 2016). Grey matter networks may start to become more randomly organized in early, preclinical stages of the disease , and in particular lower values of the clustering coefficient seem to be associated with faster clinical progression in AD .…”

Complex Brain Network Analysis and Its Applications to Brain Disorders: A Survey

“…Moreover, they found decreased small-world index in AD. Pereira et al [97] constructed structural brain networks of stable MCI (sMCI) patients, late MCI converters (lMCIc), early MCI converters (eMCIc), and AD patients to investigate topology structure across groups. They found that, compared with the HC group, all patient groups exhibited increased path length, reduced transitivity, and increased modularity, and the patient group showed decreased smallworld index.…”