Gray matter structural covariance networks changes along the Alzheimer's disease continuum

Abstract

Alzheimer's disease (AD) has a long neuropathological accumulation phase before the onset of dementia. Such AD neuropathological deposition between neurons impairs the synaptic communication, resulting in networks disorganization. Our study aimed to explore the evolution patterns of gray matter structural covariance networks (SCNs) along AD continuum. Based on the AT(N) (i.e., Amyloid/Tau/Neurodegeneration) pathological classification system, we classified subjects into four groups using cerebrospinal fluid amyloid-beta 1–42 (A) and phosphorylated tau protein 181 (T). We identified 101 subjects with normal AD biomarkers (A-T-), 40 subjects with Alzheimer's pathologic change (A + T−), 101 subjects with biological AD (A + T+) and 91 AD with dementia (demented subjects with A + T+). We used four regions of interest to anchor default mode network (DMN, medial temporal subsystem and midline core subsystem), salience network (SN) and executive control network (ECN). Finally, we used a multi-regression model-based linear-interaction analysis to assess the SCN changes. Along the disease progression, DMN and SN showed increased structural association at the early stage while decreased structural association at the late stage. Moreover, ECN showed progressively increased structural association as AD neuropathological profiles progress. In conclusion, this study found the dynamic trajectory of SCNs changes along the AD continuum and support the network disconnection hypothesis underlying AD neuropathological progression. Further, SCN may potentially serve as an effective AD biomarker.

Interactions between sleep disturbances and Alzheimer’s disease on brain function: a preliminary study combining the static and dynamic functional MRI

“…For up-to-date information, see http://www.adni-info.org. Similar information was described in a previous study 33 .…”

Application of T1-/T2-Weighted Ratio Mapping to Elucidate Intracortical Demyelination Process in the Alzheimer’s Disease Continuum

“…Also, some recent work proposed the enhanced sensitivity of detecting changes in intracortical signal intensity associated well with the disease, such as multiple sclerosis, Parkinson disease, and normal subject with amyloid accumulation (Granberg et al, 2017; Righart et al, 2017; Yasuno et al, 2017). Thus, given that the T1W/T2W ratio is a clinically easy-to-implement measure, researchers regarded the technique as a parsimonious intracortical myelin marker (Du et al, 2019; Li et al, 2019).…”

“…The novelty and highlights of our investigation include that: (Braak et al, 2006) adopting the latest biological AD diagnosis criteria (Jack et al, 2018). To our best knowledge, except the work of our research team, few neuroimaging studies focusing the AD continuum under the biological research framework (Montal et al, 2017; Li et al, 2019; Kalaria, 2016) and we utilized the clinically accessible T1W/T2W ratio mapping method (Glasser and Van Essen, 2011; Ganzetti et al, 2015). Specifically, we identified 252 subjects in the AD continuum and used both the CSF and amyloid PET to determine the biological profile.…”

Gray Matter Covariance Networks as Classifiers and Predictors of Cognitive Function in Alzheimer’s Disease

“…Our results are somewhat contrasting this assumption in that the potential of SCNs to discriminate between AD and controls was almost identical to that of isolated volumetric measures. So far, five studies have used SCNs as a diagnostic tool to separate AD cases from controls (18,19,(47)(48)(49). They identified multiple SCNs that differ between AD and HC, such as the default mode network, a hippocampal network, the salience network, and the executive control network.…”

“…In healthy subjects, SCN integrity decreases with age (14,15), and relates to impairment of cognitive and motor functions (16,17). In patients with mild cognitive impairment and AD, SCNs containing temporal and limbic regions as well as the precuneus were found to predict the rate of decline in memory over time (13,18,19).…”