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Age-dependent brain responses to mechanical stress determine resilience in a chronic lymphatic drainage impairment model
Zachary Gursky, Zohaib Nisar Khan, Sunil Koundal, Ankita Bhardwaj, Joaquin Caceres Melgarejo, Kaiming Xu, Xinan Chen, Hung-Mo Lin, Xianfeng Gu, Hedok Lee, Jonathan Kipnis, Yoav Dori, Allen Tannenbaum, Laura Santambrogio, Helene Benveniste
Zachary Gursky, Zohaib Nisar Khan, Sunil Koundal, Ankita Bhardwaj, Joaquin Caceres Melgarejo, Kaiming Xu, Xinan Chen, Hung-Mo Lin, Xianfeng Gu, Hedok Lee, Jonathan Kipnis, Yoav Dori, Allen Tannenbaum, Laura Santambrogio, Helene Benveniste
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Research Article Immunology Neuroscience

Age-dependent brain responses to mechanical stress determine resilience in a chronic lymphatic drainage impairment model

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Abstract

The outflow of ‘dirty’ brain fluids from the glymphatic system drains via the meningeal lymphatic vessels to the lymph nodes in the neck, primarily the deep cervical lymph nodes (dcLN). However, it is unclear whether dcLN drainage is essential for normal cerebral homeostasis. Using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and computational fluid dynamics, we studied the impact of long-term mechanical stress from compromised dcLN drainage on brain solute and fluid outflow in anesthetized rats. We found that in young, but not middle-aged, rats, impairment of dcLN drainage was linked to moderately increased intracranial pressure and the emergence of extracranial perivenous drainage, with no evidence of hydrocephalus at any age. Surprisingly, both age groups showed enhanced brain solute clearance despite reduced glymphatic influx. CSF proteomic analysis revealed cellular stress in the form of low-grade inflammation and upregulation of pathways associated with neurodegeneration and blood brain barrier leakage in the rats with impaired lymphatic drainage. Our findings highlight that dcLN drainage is indeed a prerequisite for normal cerebral homeostasis in the rat and reveal the brain’s age-dependent compensatory responses to chronic impairment of its lymphatic drainage pathways.

Authors

Zachary Gursky, Zohaib Nisar Khan, Sunil Koundal, Ankita Bhardwaj, Joaquin Caceres Melgarejo, Kaiming Xu, Xinan Chen, Hung-Mo Lin, Xianfeng Gu, Hedok Lee, Jonathan Kipnis, Yoav Dori, Allen Tannenbaum, Laura Santambrogio, Helene Benveniste

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Figure 4

Inflammatory and degenerative signature in the CSF of young rats with compromised dcLN drainage.

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Inflammatory and degenerative signature in the CSF of young rats with co...
(A) Graphical abstract summarizing quantitative mass spectrometry–based proteomics with stable isotope–containing isobaric tags (MS3 notch method). (B) PEAKS analysis with Q-module generated hierarchically clustered heat map from c-dcLN (n = 3) and sham (n = 3) rats. The relative protein abundance in the 2 conditions is shown for the protein groups that passed the filters for protein identification (–log (P value) > 13 for protein ID, corresponding to P < 0.05 by ANOVA) and showed significant changes (P < 0.05 by ANOVA/t tests). The full list of proteins is reported in Supplemental Table 2. Positive values reflect fold increases (red color), and negative values reflect fold decreases (blue color). (C) Unsupervised 2D principal component analysis (2D-PCA) score plot generated from the analysis of CSF identified proteome listed in Supplemental Table 2 from sham (green) and c-dcLN (red), with principal components 1 (PC1) and 2 (PC2) accounting for 56.6% and 14.98% of the variance. (D) Volcano plot illustrating the significance of protein expression ratios in c-dcLN/sham. Statistically significant proteins (P < 0.05 by ANOVA) are highlighted in red for 2-fold up-regulated and in blue for 2-fold down-regulated proteins. These proteins are indexed in Supplemental Table 2. (E) IPA analysis–based enrichment of top pathways (P < 0.05 by Fisher’s exact test with Benjamini-Hochberg correction) observed in c-dcLN/sham. (F) Quantitative analysis of protein expression profiles and IPA assigned z score function to all eligible canonical biochemical and cellular pathways: where z < 2 (in blue shades) represents significant downregulation while z > 2.0 (in orange shades) represents a significant upregulation (Supplemental Table 2).

Copyright © 2026 American Society for Clinical Investigation
ISSN: 0021-9738 (print), 1558-8238 (online)

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