SNPs associated with human stroke risk have been identified in the intergenic region between Forkhead family transcription factors FOXF2 and FOXQ1 , but we lack a mechanism for the association. FoxF2 is expressed in vascular mural pericytes and is important for maintaining pericyte number and stabilizing small vessels in zebrafish. The stroke-associated SNPs are located in a previously unknown transcriptional enhancer for FOXF2 , functional in human cells and zebrafish. We identify critical enhancer regions for FOXF2 gene expression, including binding sites occupied by transcription factors ETS1, RBPJ, and CTCF. rs74564934, a stroke-associated SNP adjacent to the ETS1 binding site, decreases enhancer function, as does mutation of RPBJ sites. rs74564934 is significantly associated with the increased risk of any stroke, ischemic stroke, small vessel stroke, and elevated white matter hyperintensity burden in humans. Foxf2 has a conserved function cross-species and is expressed in vascular mural pericytes of the vessel wall. Thus, stroke-associated SNPs modulate enhancer activity and expression of a regulator of vascular stabilization, FOXF2 , thereby modulating stroke risk.

Images contain a wealth of information that is often under analyzed in biological studies. Developmental models of vascular disease are a powerful way to quantify developmentally regulated vessel phenotypes to identify the roots of the disease process. We present vessel Metrics, a software tool specifically designed to analyze developmental vascular microscopy images that will expedite the analysis of vascular images and provide consistency between research groups. We developed a segmentation algorithm that robustly quantifies different image types, developmental stages, organisms, and disease models at a similar accuracy level to a human observer. We validate the algorithm on confocal, lightsheet, and two photon microscopy data in zebrafish. The tool accurately segments data taken by multiple scientists on varying microscopes. We validate vascular parameters such as vessel density, network length, and diameter, across developmental stages, genetic mutations, and drug treatments, and show a favorable comparison to other freely available software tools. Vessel Metrics reduces the time to analyze experimental results, improves repeatability within and between institutions, and expands the percentage of a given vascular network analyzable in experiments.