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Usage Information

Complement C3a receptor–mediated vascular dysfunction: a complex interplay between aging and neurodegeneration
Kanchan Bhatia, Saif Ahmad, Adam Kindelin, Andrew F. Ducruet
Kanchan Bhatia, Saif Ahmad, Adam Kindelin, Andrew F. Ducruet
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Commentary

Complement C3a receptor–mediated vascular dysfunction: a complex interplay between aging and neurodegeneration

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Abstract

Vascular dysfunction resulting in compromised blood-brain barrier (BBB) integrity is evident in aging and disease. Although the complement C3a/C3a receptor (C3a/C3aR) axis influences normal brain aging and disease progression, the mechanisms governing endothelial C3aR–mediated neurovascular inflammation and BBB permeability remain unexplored. In this issue of the JCI, Propson et al. investigated endothelial C3a/C3aR signaling in normal, aged, and neurodegenerative mouse models. Endothelial C3aR signaling modulated age-dependent increases in VCAM1, initiated peripheral lymphocyte infiltration, and enhanced microglial activity. Increased calcium release downstream of C3aR signaling disrupted the vascular endothelial cadherin (VE-cadherin) junctions, increased BBB permeability, and degraded vascular structure and function. Mice lacking C3aR (C3ar1–/–) and mice treated with a C3aR antagonist showed attenuated age-related microglial reactivity and neurodegeneration. These results confirm that complement-mediated signaling impacts vascular health and BBB function in normal aging and neurodegenerative disease, suggesting that complement inhibitors represent a therapeutic option for cerebral microvascular dysfunction.

Authors

Kanchan Bhatia, Saif Ahmad, Adam Kindelin, Andrew F. Ducruet

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Usage data is cumulative from November 2024 through November 2025.

Usage JCI PMC
Text version 656 102
PDF 136 24
Figure 228 1
Citation downloads 93 0
Totals 1,113 127
Total Views 1,240
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Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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