Single-Cell Transcriptome Analysis of the Circle of Willis in a Mouse Cerebral Aneurysm Model

The circle of Willis (CoW) is the most common location for aneurysms to form in humans. Although the major cell types of the intracranial vasculature are well known, the heterogeneity and relative contributions of the different cells in healthy and aneurysmal vessels have not been well characterized. Here, we present the first comprehensive analysis of the lineage heterogeneity and altered transcriptomic profiles of vascular cells from healthy and aneurysmal mouse CoW using single-cell RNA sequencing.

Cerebral aneurysms (CAs) were induced in adult male mice using an elastase model. Single-cell RNA sequencing was then performed on CoW samples obtained from animals that either had aneurysms form or rupture 14 days post-induction. Sham-operated animals served as controls.

Unbiased clustering analysis of the transcriptional profiles from >3900 CoW cells identified 19 clusters representing ten cell lineages: vascular smooth muscle cells, endothelial cells fibroblasts, pericytes and immune cells (macrophages, T and B lymphocytes, dendritic cells, mast cells, and neutrophils). The 5 vascular smooth muscle cell subpopulations had distinct transcriptional profiles and were classified as proliferative, stress-induced senescent, quiescent, inflammatory-like, or hyperproliferative. The transcriptional signature of the metabolic pathways of ATP generation was found to be downregulated in 2 major vascular smooth muscle cell clusters when CA was induced. Aneurysm induction led to significant expansion of the total macrophage population, and this expansion was further increased with rupture. Both inflammatory and resolution-phase macrophages were identified, and a massive spike of neutrophils was seen with CA rupture. Additionally, the neutrophil-to-lymphocyte ratio (NLR), which originated from CA induction mirrored what happens in humans.

Our data identify CA disease-relevant transcriptional signatures of vascular cells in the CoW and is searchable via a web-based R/shiny interface.