Back

Stretch and flow at the gliovascular interface: high-fidelity modelling of the mechanics of astrocyte endfeet

Causemann, M.; Enger, R.; Rognes, M. E.

2025-05-08 neuroscience
10.1101/2025.05.08.652799 bioRxiv
Show abstract

Astrocyte endfeet form a near-continuous sheath around the brains vasculature, defining the perivascular spaces (PVS) that are crucial for brain fluid flow and solute transport. Yet, their precise physiological role remains poorly understood. Using 3D electron microscopy data, we created a high-fidelity poroelastic computational model of an arteriole segment with surrounding endfeet and parenchyma to investigate tissue displacement and fluid flow within the PVS, endfeet, and extracellular space (ECS) in response to blood vessel pulsations. Our model predicts that arteriole dilations compress the PVS while expanding the overall endfoot sheath volume due to tangential stretch. Moreover, fluid exchange primarily occurs through inter-endfoot gaps, driven by pressure differences, rather than across the aquaporin-4 (AQP4) rich endfoot membrane. PVS stiffness critically modulates these dynamics: increased stiffness of the PVS, for instance, due to vessel pathology or aging, would minimize or even reverse fluid exchange at the gliovascular interface. While AQP4 mediated water movement has a negligible impact on pulsation-driven mechanics, it significantly enhances osmotically driven fluid flow. Overall, our findings elucidate the complex balance of forces governing gliovascular mechanics and suggest that PVS composition strongly influences endfoot-parenchymal fluid exchange. SignificancePerivascular spaces, formed by astrocyte endfeet wrapping the vasculature, are high-conduit pathways for brain fluid flow and clearance. Vascular pulsations drive this flow, but the resulting mechanical interactions at the gliovascular interface remain largely unknown. We introduce a computational model of the solid and fluid mechanics here, using realistic geometries to capture intricate astrocyte morphology at the subcellular level. Our simulations reveal that changes in perivascular composition - associated with aging or neurodegenerative diseases - fundamentally alter mechanical coupling, potentially impeding fluid transport. This work provides a mechanistic framework for understanding brain clearance and constitutes a foundational model for computational studies of mechanical forces in the nervous system.

Published in Proceedings of the National Academy of Sciences (predicted rank #12) · training set

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

1
Fluids and Barriers of the CNS
28 papers in training set
Top 0.1%
22.6%
2
PLOS Computational Biology
1863 papers in training set
Top 1%
19.1%
3
The Journal of Physiology
150 papers in training set
Top 0.2%
9.2%
50% of probability mass above
4
eLife
5828 papers in training set
Top 15%
7.5%
5
Acta Biomaterialia
92 papers in training set
Top 0.4%
4.5%
6
Development
497 papers in training set
Top 2%
3.5%
7
Nature Communications
5641 papers in training set
Top 41%
2.2%
8
iScience
1154 papers in training set
Top 12%
2.2%
9
Scientific Reports
3612 papers in training set
Top 52%
1.8%
10
Glia
81 papers in training set
Top 0.7%
1.8%
11
Cell Reports
1498 papers in training set
Top 18%
1.8%
Proceedings of the National Academy of Sciences · published here
2444 papers in training set
Top 27%
1.8%
13
Journal of The Royal Society Interface
235 papers in training set
Top 3%
1.4%
14
Advanced Science
286 papers in training set
Top 6%
1.4%
15
Developmental Cell
196 papers in training set
Top 3%
1.2%
16
Biophysical Journal
631 papers in training set
Top 4%
0.9%
17
Science Advances
1243 papers in training set
Top 29%
0.9%
18
PLOS ONE
5266 papers in training set
Top 60%
0.9%
19
Current Biology
665 papers in training set
Top 9%
0.9%
20
Communications Biology
993 papers in training set
Top 28%
0.9%
21
Philosophical Transactions of the Royal Society B: Biological Sciences
72 papers in training set
Top 2%
0.6%
22
eneuro
439 papers in training set
Top 8%
0.6%
23
PRX Life
42 papers in training set
Top 1%
0.6%