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Genetic architecture of white matter hyperintensities differs in hypertensive and nonhypertensive ischemic stroke.

Stroke | 2015

Epidemiological studies suggest that white matter hyperintensities (WMH) are extremely heritable, but the underlying genetic variants are largely unknown. Pathophysiological heterogeneity is known to reduce the power of genome-wide association studies (GWAS). Hypertensive and nonhypertensive individuals with WMH might have different underlying pathologies. We used GWAS data to calculate the variance in WMH volume (WMHV) explained by common single nucleotide polymorphisms (SNPs) as a measure of heritability (SNP heritability [HSNP]) and tested the hypothesis that WMH heritability differs between hypertensive and nonhypertensive individuals.

Pubmed ID: 25550368 RIS Download

Research resources used in this publication

None found

Antibodies used in this publication

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Associated grants

  • Agency: NINDS NIH HHS, United States
    Id: K23 NS064052
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS042733
  • Agency: NINDS NIH HHS, United States
    Id: U01 NS069208
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS039987
  • Agency: Medical Research Council, United Kingdom
    Id: G0900295
  • Agency: Wellcome Trust, United Kingdom
    Id: 084724
  • Agency: Wellcome Trust, United Kingdom
    Id: 095626
  • Agency: NINDS NIH HHS, United States
    Id: R01 NS082285

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This is a list of tools and resources that we have found mentioned in this publication.


MRIcron (tool)

RRID:SCR_002403

Software tool as a cross-platform NIfTI format image viewer. Used for viewing and exporting of brain images. MRIcroGL is a variant of MRIcron.

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IMPUTE2 (tool)

RRID:SCR_013055

A computer program for phasing observed genotypes and imputing missing genotypes.

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MRIcro Software (tool)

RRID:SCR_008264

MRIcro allows Windows and Linux computers view medical images. It is a standalone program, but includes tools to complement SPM (software that allows neuroimagers to analyze MRI, fMRI and PET images). MRIcro allows efficient viewing and exporting of brain images. In addition, it allows neuropsychologists to identify regions of interest (ROIs, e.g. lesions). MRIcro can create Analyze format headers for exporting brain images to other platforms. Some features of MRIcro are: - Converts medical images to SPM friendly Analyze format. - View Analyze format images (big or little endian). - Create Analyze format headers (big or little endian). - Create 3D regions of interest (with computed volume & intensity). - Overlap multiple regions of interest. - Rotate images to match SPM template images. - Export images to BMP, JPEG, PNG or TIF format. - Yoked images: linked viewing of multiple images (e.g. view same coordinates of PET and MRI scans). Users familiar with other Windows programs will find that this software is fairly straightforward to use. Resting the mouse cursor over a button will cause a text hint to appear over the button. However, a tutorial with a step by step guide of how to use MRIcro with SPM is available.

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PLINK (tool)

RRID:SCR_001757

Open source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.

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1000 Genomes Project and AWS (tool)

RRID:SCR_008801

A dataset containing the full genomic sequence of 1,700 individuals, freely available for research use. The 1000 Genomes Project is an international research effort coordinated by a consortium of 75 companies and organizations to establish the most detailed catalogue of human genetic variation. The project has grown to 200 terabytes of genomic data including DNA sequenced from more than 1,700 individuals that researchers can now access on AWS for use in disease research free of charge. The dataset containing the full genomic sequence of 1,700 individuals is now available to all via Amazon S3. The data can be found at: http://s3.amazonaws.com/1000genomes The 1000 Genomes Project aims to include the genomes of more than 2,662 individuals from 26 populations around the world, and the NIH will continue to add the remaining genome samples to the data collection this year. Public Data Sets on AWS provide a centralized repository of public data hosted on Amazon Simple Storage Service (Amazon S3). The data can be seamlessly accessed from AWS services such Amazon Elastic Compute Cloud (Amazon EC2) and Amazon Elastic MapReduce (Amazon EMR), which provide organizations with the highly scalable compute resources needed to take advantage of these large data collections. AWS is storing the public data sets at no charge to the community. Researchers pay only for the additional AWS resources they need for further processing or analysis of the data. All 200 TB of the latest 1000 Genomes Project data is available in a publicly available Amazon S3 bucket. You can access the data via simple HTTP requests, or take advantage of the AWS SDKs in languages such as Ruby, Java, Python, .NET and PHP. Researchers can use the Amazon EC2 utility computing service to dive into this data without the usual capital investment required to work with data at this scale. AWS also provides a number of orchestration and automation services to help teams make their research available to others to remix and reuse. Making the data available via a bucket in Amazon S3 also means that customers can crunch the information using Hadoop via Amazon Elastic MapReduce, and take advantage of the growing collection of tools for running bioinformatics job flows, such as CloudBurst and Crossbow.

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IMPUTE (tool)

RRID:SCR_009245

Software application for estimating (imputing) unobserved genotypes in SNP association studies. The program is designed to work seamlessly with the output of the genotype calling program CHIAMO and the population genetic simulator HAPGEN, and it produces output that can be analyzed using the program SNPTEST. (entry from Genetic Analysis Software)

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