A genome-wide genotyping study in patients with ischaemic stroke: initial analysis and data release

Abstract

Background: Despite evidence of a genetic role in stroke, the identification of common genetic risk factors for this devastating disorder remains problematic. We aimed to identify any common genetic variability exerting a moderate to large effect on risk of ischaemic stroke, and to generate publicly available genome-wide genotype data to facilitate others doing the same.

Methods: We applied a genome-wide high-density single-nucleotide-polymorphism (SNP) genotyping approach to a cohort of samples with and without ischaemic stroke (n=278 and 275, respectively), and did an association analysis adjusted for known confounders in a final cohort of 249 cases and 268 controls. More than 400,000 unique SNPs were assayed.

Findings: We produced more than 200 million genotypes in 553 unique participants. The raw genotypes of all the controls have been posted publicly in a previous study of Parkinson's disease. From this effort, results of genotype and allele association tests have been publicly posted for 88% of stroke patients who provided proper consent for public release. Preliminary analysis of these data did not reveal any single locus conferring a large effect on risk for ischaemic stroke.

Interpretation: The data generated here comprise the first phase of a genome-wide association analysis in patients with stroke. Release of phase I results generated in these publicly available samples from each consenting individual makes this dataset a valuable resource for data-mining and augmentation.

Figure. STRUCTURE results on cases and controls

276 autosomal markers were analysed using STRUCTURE (version 2.1) to determine if there was substantial population substructure within or between the cases and controls. Shown in both the upper and lower panels are triangle and bar plots with the number of assumed populations set to 3 and 2 respectively. In triangle plots, cases are red and controls are blue, and in the bar plot cases are group 2 and controls group 1. Analysis of all 259 cases and 269 controls (panel A) shows 11 samples clustering outside of the main group. These 11 outlier samples are self-reported African American patients (ten cases and one control). Panel B shows the results of analysis using STRUCTURE following removal of these 11 samples; these results show that there is a lack of substantial population substructure in this cohort and this was the cohort used for the final analysis.