14 research outputs found
Genome-Wide Association Analysis of Ischemic Stroke in Young Adults
Ischemic stroke (IS) is among the leading causes of death in Western countries. There is a significant genetic component to IS susceptibility, especially among young adults. To date, research to identify genetic loci predisposing to stroke has met only with limited success. We performed a genome-wide association (GWA) analysis of early-onset IS to identify potential stroke susceptibility loci. The GWA analysis was conducted by genotyping 1 million SNPs in a biracial population of 889 IS cases and 927 controls, ages 15–49 years. Genotypes were imputed using the HapMap3 reference panel to provide 1.4 million SNPs for analysis. Logistic regression models adjusting for age, recruitment stages, and population structure were used to determine the association of IS with individual SNPs. Although no single SNP reached genome-wide significance (P < 5 × 10−8), we identified two SNPs in chromosome 2q23.3, rs2304556 (in FMNL2; P = 1.2 × 10−7) and rs1986743 (in ARL6IP6; P = 2.7 × 10−7), strongly associated with early-onset stroke. These data suggest that a novel locus on human chromosome 2q23.3 may be associated with IS susceptibility among young adults
Variants at APOE influence risk of deep and lobar intracerebral hemorrhage
Objective Prior studies investigating the association between APOE alleles ε2/ε4 and risk of intracerebral hemorrhage (ICH) have been inconsistent and limited to small sample sizes, and did not account for confounding by population stratification or determine which genetic risk model was best applied. Methods We performed a large-scale genetic association study of 2189 ICH cases and 4041 controls from 7 cohorts, which were analyzed using additive models for ε2 and ε4. Results were subsequently meta-analyzed using a random effects model. A proportion of the individuals (322 cases, 357 controls) had available genome-wide data to adjust for population stratification. Results Alleles ε2 and ε4 were associated with lobar ICH at genome-wide significance levels (odds ratio [OR] = 1.82, 95% confidence interval [CI] = 1.50–2.23, p = 6.6 × 10 −10 ; and OR = 2.20, 95%CI = 1.85–2.63, p = 2.4 × 10 −11 , respectively). Restriction of analysis to definite/probable cerebral amyloid angiopathy ICH uncovered a stronger effect. Allele ε4 was also associated with increased risk for deep ICH (OR = 1.21, 95% CI = 1.08–1.36, p = 2.6 × 10 −4 ). Risk prediction evaluation identified the additive model as best for describing the effect of APOE genotypes. Interpretation APOE ε2 and ε4 are independent risk factors for lobar ICH, consistent with their known associations with amyloid biology. In addition, we present preliminary findings on a novel association between APOE ε4 and deep ICH. Finally, we demonstrate that an additive model for these APOE variants is superior to other forms of genetic risk modeling previously applied. ANN NEUROL 2010Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78478/1/22134_ftp.pd
Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke
Genetic factors have been implicated in stroke risk but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) in ischemic stroke and its subtypes in 3,548 cases and 5,972 controls, all of European ancestry. Replication of potential
signals was performed in 5,859 cases and 6,281 controls. We replicated reported associations between variants close to PITX2 and ZFHX3 with cardioembolic stroke, and a 9p21 locus with large vessel stroke. We identified a novel association for a SNP within the histone deacetylase 9(HDAC9) gene on chromosome 7p21.1 which was associated with large vessel stroke including additional replication in a further 735 cases and 28583 controls (rs11984041, combined P =
1.87×10−11, OR=1.42 (95% CI) 1.28-1.57). All four loci exhibit evidence for heterogeneity of effect across the stroke subtypes, with some, and possibly all, affecting risk for only one subtype. This suggests differing genetic architectures for different stroke subtypes
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Abstract 2597: Centralized and Study-specific Phenotyping in a Large-scale Stroke Genetics Study: An Analysis from the NINDS Stroke Genetics Network (SiGN)
Background:
The Stroke Genetics Network (SiGN) funded by the NINDS aims to identify genetic risk factors in ischemic stroke using whole-genome association studies (GWAS). High quality phenotyping is crucial to successful application of GWAS. As a heterogenous disorder, stroke poses specific challenges. The Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification is a broadly used, but its validity is challenged especially when performed by multiple investigators with differing interpretations of the system. The Causative Classification System for Ischemic Stroke (CCS) system is a new, web-based, and computerized algorithm that integrates clinical, diagnostic, and etiologic stroke characteristics in an evidence-based manner (
ccs.mgh.harvard.edu
) to generate subtypes.
Methods:
In planning the SiGN proposal, a sample of 20 coded charts were collected from a subset of participating studies to assess feasibility of central adjudication and comparability to study-specific TOAST. Two central adjudicators reviewed all records and generated TOAST and CCS subtypes. These were compared to study-specific TOAST subtype and the CCS phenotype generated for SiGN by local trained adjudicators. CCS data is now available for 7134 included cases using both a 5 and a 7 category system as defined in the
table
.
Results:
All 4 phenotypes were available for 115 ischemic stroke cases from 6 studies in SiGN. Basic demographics were 54% women, 63% white, and median age between 65-74.
Table 1
provides the agreement between the various subtypes.
Table 2
describes the types of disagreement.
Conclusions:
Central adjudication with only two adjudicators and curated medical records yielded more consistent subtyping independent of phenotyping system. The agreement for TOAST was higher than published rates by independent groups (∼0.50). In contrast, the agreement for CCS was lower than previously published (0.85-0.95). Site adjudicators' familiarity with TOAST and inexperience with CCS may contribute. Although CCS is an automated algorithm and has a number of user friendly features, our findings suggest that formal training and certification process before starting to use CCS may be worthwhile to achieve optimal benefit from the system