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- Ay, Hakan, et al.
(författare)
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Pathogenic Ischemic Stroke Phenotypes in the NINDS-Stroke Genetics Network
- 2014
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Ingår i: Stroke. - 0039-2499. ; 45:12, s. 3589-3596
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND AND PURPOSE: NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. METHODS: Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. RESULTS: The distribution of pathogenic categories varied by study, age, sex, and race (P<0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69-0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70-0.75). CONCLUSIONS: This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.
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| 2. |
- Woo, Daniel, et al.
(författare)
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Meta-Analysis of Genome-Wide Association Studies Identifies 1q22 as a Susceptibility Locus for Intracerebral Hemorrhage.
- 2014
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Ingår i: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297. ; 94:4, s. 511-521
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Tidskriftsartikel (refereegranskat)abstract
- Intracerebral hemorrhage (ICH) is the stroke subtype with the worst prognosis and has no established acute treatment. ICH is classified as lobar or nonlobar based on the location of ruptured blood vessels within the brain. These different locations also signal different underlying vascular pathologies. Heritability estimates indicate a substantial genetic contribution to risk of ICH in both locations. We report a genome-wide association study of this condition that meta-analyzed data from six studies that enrolled individuals of European ancestry. Case subjects were ascertained by neurologists blinded to genotype data and classified as lobar or nonlobar based on brain computed tomography. ICH-free control subjects were sampled from ambulatory clinics or random digit dialing. Replication of signals identified in the discovery cohort with p < 1 × 10(-6) was pursued in an independent multiethnic sample utilizing both direct and genome-wide genotyping. The discovery phase included a case cohort of 1,545 individuals (664 lobar and 881 nonlobar cases) and a control cohort of 1,481 individuals and identified two susceptibility loci: for lobar ICH, chromosomal region 12q21.1 (rs11179580, odds ratio [OR] = 1.56, p = 7.0 × 10(-8)); and for nonlobar ICH, chromosomal region 1q22 (rs2984613, OR = 1.44, p = 1.6 × 10(-8)). The replication included a case cohort of 1,681 individuals (484 lobar and 1,194 nonlobar cases) and a control cohort of 2,261 individuals and corroborated the association for 1q22 (p = 6.5 × 10(-4); meta-analysis p = 2.2 × 10(-10)) but not for 12q21.1 (p = 0.55; meta-analysis p = 2.6 × 10(-5)). These results demonstrate biological heterogeneity across ICH subtypes and highlight the importance of ascertaining ICH cases accordingly.
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