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      Genome-Wide Association Analysis of Ischemic Stroke in Young Adults

      * , * , , , § , § , * , , ** , ** , ** , †† , †† , †† , ‡‡ , §§ , ‡‡ , *** , ††† , ‡‡‡ , ‡‡‡ , §§§ , **** , †††† , ‡‡‡‡ , **** , †††† , ‡‡‡‡ , **** , †††† , ‡‡‡‡ , †††† , **** , †††† , ‡‡‡‡ , **** , †††† , ‡‡‡‡ , §§§§ , , , * , 1

      G3: Genes|Genomes|Genetics

      Genetics Society of America

      epidemiology, genetics, brain infarction, FMNL2

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          Abstract

          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.

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          Most cited references 30

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          PLINK: a tool set for whole-genome association and population-based linkage analyses.

          Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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            Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment.

            The etiology of ischemic stroke affects prognosis, outcome, and management. Trials of therapies for patients with acute stroke should include measurements of responses as influenced by subtype of ischemic stroke. A system for categorization of subtypes of ischemic stroke mainly based on etiology has been developed for the Trial of Org 10172 in Acute Stroke Treatment (TOAST). A classification of subtypes was prepared using clinical features and the results of ancillary diagnostic studies. "Possible" and "probable" diagnoses can be made based on the physician's certainty of diagnosis. The usefulness and interrater agreement of the classification were tested by two neurologists who had not participated in the writing of the criteria. The neurologists independently used the TOAST classification system in their bedside evaluation of 20 patients, first based only on clinical features and then after reviewing the results of diagnostic tests. The TOAST classification denotes five subtypes of ischemic stroke: 1) large-artery atherosclerosis, 2) cardioembolism, 3) small-vessel occlusion, 4) stroke of other determined etiology, and 5) stroke of undetermined etiology. Using this rating system, interphysician agreement was very high. The two physicians disagreed in only one patient. They were both able to reach a specific etiologic diagnosis in 11 patients, whereas the cause of stroke was not determined in nine. The TOAST stroke subtype classification system is easy to use and has good interobserver agreement. This system should allow investigators to report responses to treatment among important subgroups of patients with ischemic stroke. Clinical trials testing treatments for acute ischemic stroke should include similar methods to diagnose subtypes of stroke.
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              A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants.

              Identifying the genetic variants that increase the risk of type 2 diabetes (T2D) in humans has been a formidable challenge. Adopting a genome-wide association strategy, we genotyped 1161 Finnish T2D cases and 1174 Finnish normal glucose-tolerant (NGT) controls with >315,000 single-nucleotide polymorphisms (SNPs) and imputed genotypes for an additional >2 million autosomal SNPs. We carried out association analysis with these SNPs to identify genetic variants that predispose to T2D, compared our T2D association results with the results of two similar studies, and genotyped 80 SNPs in an additional 1215 Finnish T2D cases and 1258 Finnish NGT controls. We identify T2D-associated variants in an intergenic region of chromosome 11p12, contribute to the identification of T2D-associated variants near the genes IGF2BP2 and CDKAL1 and the region of CDKN2A and CDKN2B, and confirm that variants near TCF7L2, SLC30A8, HHEX, FTO, PPARG, and KCNJ11 are associated with T2D risk. This brings the number of T2D loci now confidently identified to at least 10.
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                Author and article information

                Contributors
                Role: Communicating editor
                Journal
                G3 (Bethesda)
                ggg
                ggg
                ggg
                G3: Genes|Genomes|Genetics
                Genetics Society of America
                2160-1836
                1 November 2011
                November 2011
                : 1
                : 6
                : 505-514
                Affiliations
                [* ]Department of Medicine
                []Department of Neurology, and
                [§ ]Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland 21201
                []Department of Neurology, Veterans Affairs Medical Center, Baltimore, Maryland 21201
                [** ]Department of Biostatistics, University of Washington, Seattle, Washington 98195
                [†† ]Center for Inherited Disease Research, Johns Hopkins University School of Medicine, Baltimore, Maryland 21224
                [‡‡ ]Department of Neurology, Mayo Clinic, Jacksonville, Florida 32224
                [§§ ]Department of Neurology, Mayo Clinic, Rochester, Minnesota 55905
                [*** ]Laboratory of Neurogenetics, National Institute of Aging and
                [§§§§ ]National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland 20892
                [††† ]Center for Public Health Genomics
                [‡‡‡ ]Department of Public Health Sciences, and
                [§§§ ]Department of Neurology, University of Virginia, Charlottesville, Virginia 22908
                [**** ]Center for Human Genetic Research and
                [†††† ]Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts 02114
                [‡‡‡‡ ]Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts 02142
                Author notes

                Supporting information is available online at http://www.g3journal.org/lookup/suppl/doi:10.1534/g3.111.001164/-/DC1

                Reference number in dbGaP: phs000292.v1.p1.

                IRB number: University of Maryland HCR-HP-00041214.

                [1 ]Corresponding author: Department of Medicine, University of Maryland School of Medicine, 660 W. Redwood St., Howard Hall Room 492, Baltimore, MD 21201. E-mail: bmitchel@ 123456medicine.umaryland.edu
                Article
                GGG_001164
                10.1534/g3.111.001164
                3276159
                22384361
                Copyright © 2011 Cheng et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License ( http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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                Genetics

                brain infarction, epidemiology, genetics, fmnl2

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