Topologically Convergent and Divergent Structural Connectivity Patterns between Patients with Remitted Geriatric Depression and Amnestic Mild Cognitive Impairment

Abstract

Alzheimer's disease (AD) can be conceptualized as a disconnection syndrome. Both remitted geriatric depression (RGD) and amnestic mild cognitive impairment (aMCI) are associated with a high risk for developing AD. However, little is known about the similarities and differences in the topological patterns of white matter (WM) structural networks between RGD and aMCI. In this study, diffusion tensor imaging and deterministic tractography were used to map the human WM networks of 35 RGD patients, 38 aMCI patients, and 30 healthy subjects. Furthermore, graph theoretical methods were applied to investigate the alterations in the global and regional properties of the WM network in these patients. First, both the RGD and aMCI patients showed abnormal global topology in their WM networks (i.e., reduced network strength, reduced global efficiency, and increased absolute path length) compared with the controls, and there were no significant differences in these global network properties between the patient groups. Second, similar deficits of the regional and connectivity characteristics in the WM networks were primarily found in the frontal brain regions of RGD and aMCI patients compared with the controls, while a different nodal efficiency of the posterior cingulate cortex and several prefrontal brain regions were also observed between the patient groups. Together, our study provides direct evidence for the association of a great majority of convergent and a minority of divergent connectivity of WM structural networks between RGD and aMCI patients, which may lead to increasing attention in defining a population at risk of AD.

Cognitive impairment with and without depression history: an analysis of white matter microstructure

“…Our findings are consistent with previous research showing topological alterations to white matter networks in patients with remitted late-life depression (R-LLD) and no MCI and those with aMCI. 31 Significant decrements in regional connectivity were shown in both patient groups compared with the control group; however, results showed altered connectivity characteristics between the posterior cingulate gyrus and prefrontal regions between the patient groups. While it is widely accepted that MCI is a predementia syndrome, 1,6 it is unclear whether MD is an independent risk factor for or an early symptom of dementia.…”

Disrupted White Matter Network and Cognitive Decline in Type 2 Diabetes Patients

“…A threshold selection can reduce the risk of false-positive connections due to noise or the limitations in the deterministic tractography and can simultaneously ensure the size of the largest connected component (i.e., 90) in the networks [24]. Bai et al reported that this 'thresholding' procedure did not significantly influence their results after they evaluated the effects of different thresholds on the network analysis by setting threshold values of the fiber number ranging from 1 to 5 [24]. In the present study, we performed the similar analysis and confirmed their results (Supplementary Figure 1).…”

A significant risk factor for poststroke depression: the depression-related subnetwork

“…In addition, structural brain network interactions can be quantified using brain graphs 7,8 in which neuroanatomical regions are defined as a set of nodes and DTI-derived white matter connections act as interconnecting edges. 7 Using this approach, a disruption of neural topology has been shown in several brain diseases, [9][10][11] including those occurring in chronic stroke patients. 12 Here, we evaluated 3 markers of brain-damage severity: lesion index, fractional anisotropy (FA) reduction and brain structural networks.…”