Novel functional network-level glymphatic clearance associated with network connectivity in human
Presented During:
Tuesday, June 25, 2024: 12:00 PM - 1:15 PM
COEX
Room:
Grand Ballroom 104-105
Poster No:
2088
Submission Type:
Abstract Submission
Authors:
YIFEI LI1, Xiao Zhu1, Ying Zhou1, Yaode He1, Xuting Zhang1, Tingxia Zhang1, Ziyu Zhou1, Mengmeng Fang1, Jianzhong Sun1, Min Lou1
Institutions:
1Zhejiang University, Hangzhou, Zhejiang
First Author:
Co-Author(s):
Introduction:
How brain extraordinary activity coordinates its complex clearance system is a fundamental question in systems neuroscience (Yeo BT et al., 2011; Mollon JD et al., 2022). Serving a role in waste clearance, glymphatic system is critical to brain health and cognitive performance (Hablitz LM et al., 2021). But how it relates with functional network within cortical regions remains elusive. Moreover, non-invasive regional assessment for glymphatic system is lacking (Kamagata K et al., 2021). Therefore, we aimed to unravel the characteristics of network-level glymphatic function and validate a potential regional assessment (i.e., free-water) for glymphatic clearance. We further explore whether network-level glymphatic clearance was integrated with network connectome.
Methods:
This retrospective study included two prospective 3.0-T MRI cohorts. In Cohort 1, serial T1-weighted imaging was performed in participants before and at multiple timepoints after intrathecal injection of contrast. Cortical networks were defined based on 400-parcel Schaefer atlas (Schaefer400). Network-based glymphatic characteristics included 1) glymphatic clearance function, signal percentage change from baseline to 39 hours, and 2) glymphatic heterogeneity, the standard deviation of 39 hours percentage change within each network. Considering the disease effect, we compared glymphatic dynamics across three subgroups (i.e., neurodegenerative, peripheral neuropathy, and encephalitis). Gene set enrichment analysis was conducted to investigate the transcriptomic profile of 30 brain cell-types related with glymphatic clearance using Allen Human Brain Atlas. We further analyzed the relationship of glymphatic clearance characteristics with aging and sleep quality. Network free-water was estimated by a bi-tensor model based on DTI. In Cohort 2, participants with cerebral small vessel disease (CSVD) underwent multi-modal MRI were enrolled. Structural and functional connectomes were constructed based on DTI and functional MRI after preprocessing, respectively. To validate the main findings with Schaefer400, we also used another functionally-defined atlas, Craddock atlas with 450 clusters (CC450). False Discovery Rate (FDR) was used to correct for multiple comparisons.
Results:
In Cohort 1, 84 participants were enrolled (50% female; mean age, 58 years ± 14 [SD]). Glymphatic clearance function was both region- and network-specific. Spatially, a stable glymphatic dynamics pattern was recognized even under different disease. In regions exhibiting better glymphatic clearance competence, genes related to astrocytes, endothelial cells, pericytes and two types of excitatory cells were significantly enriched. Impaired network-level clearance function among all networks was associated with ageing and sleep disturbance, while increased network-level heterogeneity only associated with ageing. Network-level free-water positively associated with glymphatic clearance function across all networks. In Cohort 2, 557 participants were enrolled (49% female; mean age, 62 years ± 9 [SD]). Network-level free-water was negatively correlated with intra-network structural and functional connectivity. The above main results were also replicated on CC450 atlas in sensitivity analysis.
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Conclusions:
Our understanding about how glymphatic system contributes to brain homeostasis is evolving. Here, by using Glymphatic MRI, we provide network-based glymphatic features with its genetic underpinnings in human. Network-level free-water, consistent with its glymphatic clearance function, provides a promising tool for future investigations, and was proved to be relevant with network connectivity properties in a large cohort of CSVD participants. Our findings open a novel perspective to investigate network-based clearance function and further highlight a necessity for studies on interplay among glymphatic system, neuronal demand, and network integrity.
Lifespan Development:
Aging
Neuroanatomy, Physiology, Metabolism and Neurotransmission:
Anatomy and Functional Systems 1
Cortical Anatomy and Brain Mapping 2
Novel Imaging Acquisition Methods:
Imaging Methods Other
Physiology, Metabolism and Neurotransmission :
Neurophysiology of Imaging Signals
Keywords:
Aging
Cortex
Sleep
Systems
Other - glymphatic
1|2Indicates the priority used for review
Provide references using author date format
Mollon JD. (2022), 'What kind of network is the brain?', Trends in Cognitive Science, vol. 26, no. 4, pp. 312-324.
Hablitz LM. (2021), 'The Glymphatic System: A Novel Component of Fundamental Neurobiology', Journal of Neuroscience, vol. 41, no. 37, pp. 7698-7711.
Kamagata K. (2022), 'Association of MRI Indices of Glymphatic System With Amyloid Deposition and Cognition in Mild Cognitive Impairment and Alzheimer Disease', Neurology, vol. 99, no. 24, pp. e2648-2660.
Schaefer A (2018), 'Local-Global Parcellation of the Human Cerebral Cortex from Intrinsic Functional Connectivity MRI', Cerebral Cortex, vol. 28, no. 9, pp. 3095-3114.
Craddock RC (2012), 'A whole brain fMRI atlas generated via spatially constrained spectral clustering', Human Brain Mapping, vol. 33, no. 8, pp. 1914-1928.