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.
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.
Authors: Cara L Carty; Petra Buzková; Myriam Fornage; Nora Franceschini; Shelley Cole; Gerardo Heiss; Lucia A Hindorff; Barbara V Howard; Sue Mann; Lisa W Martin; Ying Zhang; Tara C Matise; Ross Prentice; Alexander P Reiner; Charles Kooperberg Journal: Circ Cardiovasc Genet Date: 2012-03-08
Authors: Tiago Krug; João Paulo Gabriel; Ricardo Taipa; Benedita V Fonseca; Sophie Domingues-Montanari; Israel Fernandez-Cadenas; Helena Manso; Liliana O Gouveia; João Sobral; Isabel Albergaria; Gisela Gaspar; Jordi Jiménez-Conde; Raquel Rabionet; José M Ferro; Joan Montaner; Astrid M Vicente; Mário Rui Silva; Ilda Matos; Gabriela Lopes; Sofia A Oliveira Journal: J Cereb Blood Flow Metab Date: 2012-03-28 Impact factor: 6.200
Authors: Mar Matarin; Javier Simon-Sanchez; Hon-Chung Fung; Sonja Scholz; J Raphael Gibbs; Dena G Hernandez; Cynthia Crews; Angela Britton; Fabienne Wavrant De Vrieze; Thomas G Brott; Robert D Brown; Bradford B Worrall; Scott Silliman; L Douglas Case; John A Hardy; Stephen S Rich; James F Meschia; Andrew B Singleton Journal: Neurogenetics Date: 2008-02-21 Impact factor: 2.660
Authors: Jacklyn N Hellwege; Pamela J Hicks; Nicholette D Palmer; Maggie C Y Ng; Barry I Freedman; Donald W Bowden Journal: J Diabetes Metab Date: 2011-10-20