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Gray Matter Structural Covariance Networks Changes along the Alzheimer's Disease Continuum
Kaicheng li1, Xiao Luo1, Qingze Zeng1, Peiyu Huang1, Yong Zhang2, and Min-Ming Zhang1

1The 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

[1] Zhu H., Zhou P., Alcauter S., Chen Y., Cao H., Tian M., Ming D., Qi H., Wang X., Zhao X., He F., Ni H., Gao W. (2016) Changes of intranetwork and internetwork functional connectivity in Alzheimer's disease and mild cognitive impairment. J Neural Eng 13, 046008.

[2] Seeley WW Menon V, Schatzberg AF, Keller J, Glover GH, Kenna H, Reiss AL, Greicius MD (2007) Dissociable intrinsic connectivity networks for salience processing and executive control. J Neurosci 27, 2349-2356.

[3] Brier MR Thomas JB, Snyder AZ, Benzinger TL, Zhang D, Raichle ME, Holtzman DM, Morris JC, Ances BM (2012) Loss of intranetwork and internetwork resting state functional connections with Alzheimer’s disease progression. J Neurosci 32, 8890–8899.

[4] Matura S., Prvulovic D., Butz M., Hartmann D., Sepanski B., Linnemann K., Oertel-Knochel V., Karakaya T., Fusser F., Pantel J., van de Ven V. (2014) Recognition memory is associated with altered resting-state functional connectivity in people at genetic risk for Alzheimer's disease. Eur J Neurosci 40, 3128-3135.

[5] Supekar K Menon V, Rubin D, Musen M, Greicius MD. (2008) Network analysis of intrinsic functional brain connectivity in Alzheimer's disease. PLoS Comput Biol 4, e1000100.

[6] Zhou J., Greicius M. D., Gennatas E. D., Growdon M. E., Jang J. Y., Rabinovici G. D., Kramer J. H., Weiner M., Miller B. L., Seeley W. W. (2010) Divergent network connectivity changes in behavioural variant frontotemporal dementia and Alzheimer's disease. Brain 133, 1352-1367.

[7] Schultz AP Chhatwal JP, Hedden T, Mormino EC, Hanseeuw BJ, Sepulcre J, Huijbers W, LaPoint M, Buckley RF, Johnson KA, Sperling RA (2017) Phases of Hyperconnectivity and Hypoconnectivity in the Default Mode and Salience Networks Track with Amyloid and Tau in Clinically Normal Individuals. J Neurosci 37, 4323-4331.

[8] Miller E. K. (2000) The prefrontal cortex and cognitive control. Nat Rev Neurosci 1, 59-65. [9] Grady CL McIntosh AR, Beig S, Keightley ML, Burian H, Black SE (2003) Evidence from functional neuroimaging of a compensatory prefrontal network in Alzheimer's disease. J Neurosci 23, 986-993.

[10] Lin P. H., Tsai S. J., Huang C. W., Mu-En L., Hsu S. W., Lee C. C., Chen N. C., Chang Y. T., Lan M. Y., Chang C. C. (2016) Dose-dependent genotype effects of BDNF Val66Met polymorphism on default mode network in early stage Alzheimer's disease. Oncotarget 7, 54200-54214.

Figures

Figure 1 Patterns of structural association within group (A) the target seeds; (B) structural covariance networks (Z-statistic maps [p < 0.01, corrected with a false discovery rate with extended cluster voxels > 100]). All the results were projected on a standard brain template.

Difference of Gray Matter SCN between subjects in AD continuum and controls (subjects at Stage 0). (A) As for DMN medial temporal subsystem, subjects at Stage 2 showed an increased structural association between the EC and MTG; subjects at Stage 3 showed a decreased structural association between the EC and MTG as well as SFG . (B) As for SN, subjects at Stage 1 showed an increased structural association between FIC and precuneus; subjects at Stage 3 showed decreased association between FIC and the inferior temporal gyrus. (C) As for ECN, subjects at Stage 1 and Stage 3 showed an increased structural association in the SFG.

Demographic and neuropsychological data in subjects along the AD continuum

Proc. Intl. Soc. Mag. Reson. Med. 27 (2019)
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