Published in

American Heart Association, Stroke, 2(49), p. 447-453, 2018

DOI: 10.1161/strokeaha.117.018557

Links

Tools

Export citation

Search in Google Scholar

Intracranial Aneurysm–Associated Single-Nucleotide Polymorphisms Alter Regulatory DNA in the Human Circle of Willis

This paper is available in a repository.
This paper is available in a repository.

Full text: Download

Green circle
Preprint: archiving allowed
Orange circle
Postprint: archiving restricted
Red circle
Published version: archiving forbidden
Data provided by SHERPA/RoMEO

Abstract

Background and Purpose— Genome-wide association studies significantly link intracranial aneurysm (IA) to single-nucleotide polymorphisms (SNPs) in 6 genomic loci. To gain insight into the relevance of these IA-associated SNPs, we aimed to identify regulatory regions and analyze overall gene expression in the human circle of Willis (CoW), on which these aneurysms develop. Methods— We performed chromatin immunoprecipitation and sequencing for histone modifications H3K4me1 and H3K27ac to identify regulatory regions, including distal enhancers and active promoters, in postmortem specimens of the human CoW. These experiments were complemented with RNA sequencing on the same specimens. We determined whether these regulatory regions overlap with IA-associated SNPs, using computational methods. By combining our results with publicly available data, we investigated the effect of IA-associated SNPs on the newly identified regulatory regions and linked them to potential target genes. Results— We find that IA-associated SNPs are significantly enriched in CoW regulatory regions. Some of the IA-associated SNPs that overlap with a regulatory region are likely to alter transcription factor binding, and in proximity to these regulatory regions are 102 genes that are expressed in the CoW. In addition, gene expression in the CoW is enriched for genes related to cell adhesion and the extracellular matrix. Conclusions— CoW regulatory regions link IA-associated SNPs to genes with a potential role in the development of IAs. Our data refine previous predictions on SNPs associated with IA and provide a substantial resource from which candidates for follow-up studies can be prioritized.