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Gray Matter Structural Covariance Networks Changes along the Alzheimer's Disease Continuum1The 2nd Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou, China, 2GE Healthcare Shanghai, Shanghai, China
Synopsis
Alzheimer’s disease (AD) is a clinical-pathologic entity with a long pathological phase before the dementia onset. The latest ATN classification system is a effective tool in AD research and can provide a more accurate AD stages. Here, we aim to explore the evolution patterns of gray matter structural covariance networks (SCNs) along AD continuum by using the ATN classification system.
Introduction
Defined as a clinical-pathologic entity, the Alzheimer’s disease (AD) has a long pathological phase before the dementia onset. Previous studies regarded AD as a disconnection disease and suggested that the cognitive decline was a consequence of structural and functional connectivity disruptions. However, the trajectory of structural network connectivity changes along AD continuum is still unclear. Therefore, our study aimed to explore the evolution patterns of gray matter structural covariance networks (SCNs) along AD continuum.Methods
We used the latest ATN classification system to divide subjects into four stages based on cerebrospinal fluid (CSF) amyloid-beta 1–42 (A) and phosphorylated tau protein 181 (T). Combined with cognitive status, we included 101 pre-dementia AD individuals with normal CSF (Stage 0, A-T-), 40 pre-dementia AD individuals with positive amyloid pathology (Stage 1, A+T−), 101 pre-dementia AD individuals with both abnormal CSF (Stage 2, A+T+) and 91 AD patients with both abnormal CSF (Stage 3, A+T+). We used four ROIs (left posterior cingulate cortex, right entorhinal cortex, frontoinsular and dorsolateral prefrontal cortex) to anchor default mode network (DMN), salience network (SN) and executive control network (ECN). Finally, we assessed the SCN alternations using a multi-regression model-based linear-interaction analysis.Results
Along with disease progresses, DMN (medial temporal subsystem) showed initially increased structural association between the entorhinal cortex (EC) and middle temporal gyrus (MTG) and subsequently decreased association with MTG and superior frontal gyrus. Moreover, SN firstly showed an increased structural association between frontoinsular and precuneus and subsequently decreased association in the inferior temporal gyrus along the disease continuum. Regarding ECN, we found an increased structural association between the dorsolateral prefrontal cortex and prefrontal regions in subjects with abnormal CSF.Discussion
AD is a network degeneration disease, with pathologies expand along functional networks, consequently leading to failure of these networks. Thereinto, DMN, SN and ECN cooperate with each other to maintain cognitive abilities including memory, and executive function [1, 2]. Here, we found initially increased then decreased structural association in both DMN and SN. This result is in line with previous functional studies [3, 4]. Combining with pathological classification, the increased association may be the initial network response to amyloid pathology which works as a compensatory mechanism [5, 6], and further decreased connectivity will follow in the presence of neurodegeneration [7]. On the other hand, ECN guides decision-making by integrating external information and storing internal representations [2, 8]. It is always recruited as a compensatory network associated with cognitive reservation in AD patients [9]. Our data support the idea by finding a continuously increased association in ECN. Conclusively, DMN, SN and ECN showed interactive and dynamic changes with the pathology progress. Regarding the increased structural association, it may be a harmful compensation at the expense of the neuron damage. Stronger covariance strength between the seed and peak clusters indicated more intra-network connections to maintain cognition [10]. We assumed this compensation would finally be unsustainable as AD progress. As for the decreased structural association, it reflects the inconsistency GM loss between two regions. Such an asynchronous structural change matched the functional changes to some extent and provided supplementary information.Conclusion
Our results proved the network disconnection hypothesis in AD and showed a dynamic trajectory of SCNs changes along the AD continuum. Specifically, during the disease progression, DMN and SN showed the initial phase of hyperconnectivity and then hypoconnectivity. However, ECN showed the potential compensatory role in AD patients. Besides, our study suggested SCN may serve as an effective biomarker for AD progression tracking.Acknowledgements
No acknowledgement found.References
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