The Influence of Demographics and Vascular Risk Factors on Glymphatic Function Measured by Diffusion Along Perivascular Space

Assessing glymphatic function using in-vivo imaging method is of great value for understanding its contribution to major brain diseases. In the present study, we aim to validate the association between a variety of risk factors and a potential index of glymphatic function—Diffusion Tensor Image Anal...

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Bibliographic Details
Main Authors: Yao Zhang, Ruiting Zhang, Yongquan Ye, Shuyue Wang, Yeerfan Jiaerken, Hui Hong, Kaicheng Li, Qingze Zeng, Xiao Luo, Xiaopei Xu, Xinfeng Yu, Xiao Wu, Wenke Yu, Minming Zhang, Peiyu Huang
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-07-01
Series:Frontiers in Aging Neuroscience
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Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2021.693787/full
Description
Summary:Assessing glymphatic function using in-vivo imaging method is of great value for understanding its contribution to major brain diseases. In the present study, we aim to validate the association between a variety of risk factors and a potential index of glymphatic function—Diffusion Tensor Image Analysis Along the Perivascular Space (ALPS index). We enrolled 142 subjects from communities and performed multi-modality magnetic resonance imaging scans. The ALPS index was calculated from diffusion tensor imaging data, and its associations with demographic factors, vascular factors were investigated using regression analyses. We found that the ALPS index was negatively associated with age (β = −0.284, p < 0.001). Compared to males, females had significantly higher ALPS index (β = −0.243, p = 0.001). Hypertensive subjects had significantly lower ALPS index compared to non-hypertensive subjects (β = −0.189, p = 0.013). Furthermore, venous disruption could decrease ALPS index (β = −0.215, p = 0.003). In general, our results are in consistent with previous conceptions and results from animal studies about the pathophysiology of glymphatic dysfunction. Future studies utilizing this method should consider introducing the above-mentioned factors as important covariates.
ISSN:1663-4365