The power of genome-wide association studies (GWAS) to detect genetic influences on human disease can be substantially increased using a statistical testing framework reported in the May issue of the journal Genetics.
Despite the proliferation of GWAS, the associations found so far have largely failed to account for the known effects of genes on complex disease—the problem of "missing heritability." Standard approaches also struggle to find combinations of multiple genes that affect disease risk in complex ways (known as genetic interactions).
The new framework enhances the ability to detect genetic associations and interactions by taking advantage of data from other genomic studies of the same population. Such information is increasingly abundant for many human populations.
The authors demonstrated that their method improves performance over standard approaches. They also re-examined real GWAS data to find promising new candidates for genetic interactions that affect bipolar disorder, coronary artery disease, Crohn's disease, and rheumatoid arthritis.
"We think practically everyone who's ever done a case-control GWAS could benefit from reanalyzing their data in this way," said author Saharon Rosset, associate professor of statistics at Tel Aviv University.
"This paper offers a significant advance in mapping genes involved in disease. The approach makes use of available data to substantially improve the ability to identify genetic components of disease," said Mark Johnston, Editor-in-Chief of the journal Genetics.
Explore further: Gene combinations and interactions affect risk of Crohn's disease
More information: S. Kaufman and S. Rosset. Exploiting Population Samples to Enhance Genome-Wide Association Studies of Disease. Genetics May 2014 197:337-349 DOI: 10.1534/genetics.114.162511 Available online May 7, 2014. http://ift.tt/1uAgC0v
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The power of genome-wide association studies (GWAS) to detect genetic influences on human disease can be substantially increased using a statistical testing framework reported in the May issue of the journal Genetics.
Despite the proliferation of GWAS, the associations found so far have largely failed to account for the known effects of genes on complex disease—the problem of "missing heritability." Standard approaches also struggle to find combinations of multiple genes that affect disease risk in complex ways (known as genetic interactions).
The new framework enhances the ability to detect genetic associations and interactions by taking advantage of data from other genomic studies of the same population. Such information is increasingly abundant for many human populations.
The authors demonstrated that their method improves performance over standard approaches. They also re-examined real GWAS data to find promising new candidates for genetic interactions that affect bipolar disorder, coronary artery disease, Crohn's disease, and rheumatoid arthritis.
"We think practically everyone who's ever done a case-control GWAS could benefit from reanalyzing their data in this way," said author Saharon Rosset, associate professor of statistics at Tel Aviv University.
"This paper offers a significant advance in mapping genes involved in disease. The approach makes use of available data to substantially improve the ability to identify genetic components of disease," said Mark Johnston, Editor-in-Chief of the journal Genetics.
Explore further: Gene combinations and interactions affect risk of Crohn's disease
More information: S. Kaufman and S. Rosset. Exploiting Population Samples to Enhance Genome-Wide Association Studies of Disease. Genetics May 2014 197:337-349 DOI: 10.1534/genetics.114.162511 Available online May 7, 2014. http://ift.tt/1uAgC0v
Medical Xpress on facebook
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Gene combinations and interactions affect risk of Crohn's disease
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A statistical model accounting for dozens of different genes in combination—and the interactions between them—is an important step forward in understanding the genetic factors affecting the risk of Crohn's disease (CD), ...
Study ties ABCC9 anomalies, sulfonylurea exposure to HS-Aging
Apr 29, 2014
A genome-wide association study (GWAS) led by Peter Nelson, MD, PhD, of the Sanders-Brown Center on Aging at the University of Kentucky, and David Fardo, PhD, of UK's Department of Biostatistics, has provided new insight ...
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Oct 24, 2013
An international research consortium led by investigators at Massachusetts General Hospital (MGH) and the University of Chicago has answered several questions about the genetic background of obsessive-compulsive disorder ...
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Apr 07, 2014
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May 02, 2014
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