Abstract 198: Endovascular Biopsy

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Abstract

Introduction: Cerebral aneurysms affect 1-6% of the population and their rupture carries significant mortality and morbidity. The paucity of data related to histopathological features of aneurysms stems largely from the risks associated with aneurysm tissue collection. We set out to establish a feasible technique to isolate viable endothelial cells (EC) and to characterize the differences in genetic expression (GE) between iliac arterial cells vs. aneurysm cells and non-ruptured vs. ruptured aneurysm cells.

Methods: 10 patients (5 non-ruptured and 5 ruptured) undergoing aneurysm treatment were enrolled under IRB approval. ECs from aneurysms and iliac arteries were sampled using an appropriately sized coil and a 0.035 “J” wire respectively. Coils and wires were processed via FACS and single cell qPCR to quantify expression of 48 genes implicated in EC function and aneurysm pathogenesis. Mixed models were performed using each GE level as the outcome with multiple predictors. Unsupervised cluster analysis including: hierarchical heat-map clustering, K-medoids, principle components, cART, and self-organizing maps (SOM) were used to find cell clusters based on coordinately expressed GE.

Results: 437 FACS-sorted cells were collected and 319 demonstrated CD31, CD34 and CD105 triple-positive expression. Of these, 94 were aneurysmal cells. The average number of extracted aneurysm cells per patient was 9.4 (1-24, median 6.5) with a trend for higher cell yields from ruptured aneurysms (p = 0.116). Mixed model analyses revealed a history of smoking showed the strongest associations with GE (median p-value 0.104 with 11/48 analyses p < 0.05); 5 genes significantly predicted rupture status (median p-value 0.363 with 5/48 analyses p < 0.05); and one gene significantly differentiated cell type (median p-value 0.557, with 1/48 analyses p < 0.05). SOM analysis revealed clustered GE profiles suggestive of distinct functional EC sub-populations.

Conclusion: Cerebral endovascular sampling is a safe and reliable means for targeted cell collection for genetic analysis. Smoking was strongly associated with GE levels. Our analysis provides evidence that GE levels may be associated with cell type and rupture status.

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