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

• Published in: NeuroImage clinical Vol. 23; p. 101828
• Main Authors: Li, Kaicheng, Luo, Xiao, Zeng, Qingze, Huang, Peiyu, Shen, Zhujing, Xu, Xiaojun, Xu, Jingjing, Wang, Chao, Zhou, Jiong, Zhang, Minming
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier Inc 01.01.2019; Elsevier
• Subjects: Aged; Aged, 80 and over; Alzheimer Disease - diagnostic imaging; Alzheimer Disease - psychology; Alzheimer's disease continuum; Amyloid; AT(N) classification system; Cross-Sectional Studies; CSF; Disease Progression; Female; Gray Matter - diagnostic imaging; Gray matter structural covariance; Humans; Magnetic Resonance Imaging - trends; Male; Nerve Net - diagnostic imaging; Positron-Emission Tomography - trends; Radiology; Regular; Tau protein; Gray matter structural covariance; AT(N) classification system; Alzheimer's disease continuum; Amyloid; Tau protein; CSF
• ISSN: 2213-1582; 2213-1582
• DOI: 10.1016/j.nicl.2019.101828

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-beta1–42 (A) and phosphorylated tau protein181 (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. •To explore the AD continuum accurately by using the latest ATN classification system (based on neuropathological biomarkers).•Using SCNs analysis to reflect the brain network changes, which may further lead to cognition alternations in AD.•Results supported network disconnection hypothesis and showed a dynamic trajectory of SCNs changes along the AD continuum.