Changes in functional and structural brain connectome along the Alzheimer’s disease continuum

Abstract

The aim of this study was two-fold: (i) to investigate structural and functional brain network architecture in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), stratified in converters (c-aMCI) and non-converters (nc-aMCI) to AD; and to assess the relationship between healthy brain network functional connectivity and the topography of brain atrophy in patients along the AD continuum. Ninety-four AD patients, 47 aMCI patients (25 c-aMCI within 36 months) and 53 age- and sex-matched healthy controls were studied. Graph analysis and connectomics assessed global and local, structural and functional topological network properties and regional connectivity. Healthy topological features of brain regions were assessed based on their connectivity with the point of maximal atrophy (epicenter) in AD and aMCI patients. Brain network graph analysis properties were severely altered in AD patients. Structural brain network was already altered in c-aMCI patients relative to healthy controls in particular in the temporal and parietal brain regions, while functional connectivity did not change. Structural connectivity alterations distinguished c-aMCI from nc-aMCI cases. In both AD and c-aMCI, the point of maximal atrophy was located in left hippocampus (disease-epicenter). Brain regions most strongly connected with the disease-epicenter in the healthy functional connectome were also the most atrophic in both AD and c-aMCI patients. Progressive degeneration in the AD continuum is associated with an early breakdown of anatomical brain connections and follows the strongest connections with the disease-epicenter. These findings support the hypothesis that the topography of brain connectional architecture can modulate the spread of AD through the brain.

Feature Selection and Combination of Information in the Functional Brain Connectome for Discrimination of Mild Cognitive Impairment and Analyses of Altered Brain Patterns

“…Components of the brain functional connectome, including functional connections and graph theory topological metrics, have become important imaging markers for exploring brain networks and predicting the classification of neurodegenerative diseases (Biswal et al, 2010;Wang et al, 2013;Filippi et al, 2018). The functional connectome systematically depicts global graph metrics (i.e., small world, modularity, global efficiency), nodal graph metrics (i.e., degree, participant coefficient, shortest path length), and functional connections of the network.…”

“…The functional connectome systematically depicts global graph metrics (i.e., small world, modularity, global efficiency), nodal graph metrics (i.e., degree, participant coefficient, shortest path length), and functional connections of the network. It provides a novel approach for revealing altered brain network patterns (delEtoile and Adeli, 2017; Khazaee et al, 2017;Filippi et al, 2018). Given the large numbers of network features in the brain connectome, the Student's t-test (Qiao et al, 2016;Li W. et al, 2019) and sparse methods such as least absolute shrinkage and selection operator (LASSO) have been applied to select the critical features of brain networks (Wee et al, 2014;Li Y. et al, 2019).…”

Effective and Accurate Diagnosis of Subjective Cognitive Decline Based on Functional Connection and Graph Theory View

“…At present, a growing number of neuroimaging studies have suggested that patients with SCD show atrophy of gray matter volume, degeneration of white matter fiber structure, and reduction of spontaneous functional activity in the frontal, lateral temporal, and parietal cortices ( Fan et al, 2018 ; Shu et al, 2018 ; Lin et al, 2019 ). The brain connectome, including functional connections and graph theory topological metrics, is based on functional network and has attracted increasing attention owing to the complex brain network mechanism and various diagnostic information ( Biswal et al, 2010 ; delEtoile and Adeli, 2017 ; Filippi et al, 2018 ; Gao et al, 2020 ). In a series of resting-state functional brain network researches, Wang Y. et al (2013) compared the functional connections among individuals with SCD, MCI, and normal controls (NCs) and found that the strength of the functional connection between the default mode network (DMN) and right hippocampus in the SCD group was stronger than that in the MCI group but weaker than that in the NCs.…”

Network-based atrophy modelling in the common epilepsies: a worldwide ENIGMA study

“…Complementing the nodal stress hypothesis, in which patterns of cortical atrophy and hub regions appear spatially concomitant, disease epicenter mapping can identify one or more specific regions-or epicenters-whose connectivity profile may play a central role in the whole-brain manifestation of focal and generalized epilepsies (Filippi et al, 2020;Raj et al, 2012;Shafiei et al, 2019;Zeighami et al, 2015;Zhou et al, 2012). Among common epilepsies, application of these models to TLE and IGE is justified as both syndromes have been associated with pathophysiological anomalies in mesiotemporal and subcortico-cortical networks and represent conceptual extremes of a focal to generalized continuum of epilepsy subtypes (Bernhardt et al, 2013;Bernhardt et al, 2009a;Keller et al, 2014;O'Muircheartaigh et al, 2012;Weng et al, 2020).…”