News Release

Statistical test increases power of genetic studies of complex disease

Old data can be mined to find new genetic associations and gene interactions

Peer-Reviewed Publication

Genetics Society of America

BETHESDA, MD – May 7, 2014 – 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.

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CITATION: 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 at 9 AM EDT at: http://www.genetics.org/content/197/1/337

FUNDING: This study was supported in part by a fellowship from the Edmond J. Safra Center for Bioinformatics at Tel-Aviv University and by Israeli Science Foundation grant 1487/12. It makes use of data generated by the Wellcome Trust Case Control Consortium. A full list of the investigators who contributed to the generation of the data is available from http://www.wtccc.org.uk. Funding for that project was provided by the Wellcome Trust under award 076113.

ABOUT GENETICS: Since 1916, GENETICS has published high quality, original research on a range of topics bearing on inheritance, including population and evolutionary genetics, complex traits, developmental and behavioral genetics, cellular genetics, gene expression, genome integrity and transmission, and genome and systems biology. A peer-reviewed and peer-edited publication of the Genetics Society of America, GENETICS is one of the world's most cited journals in genetics and heredity.

ABOUT GSA: Founded in 1931, the Genetics Society of America (GSA) is the professional scientific society for genetics researchers and educators. The Society's more than 5,000 members worldwide work to deepen our understanding of the living world by advancing the field of genetics, from the molecular to the population level. GSA promotes research and fosters communication through a number of GSA-sponsored conferences including regular meetings that focus on particular model organisms. GSA publishes two peer-reviewed, peer-edited scholarly journals: GENETICS, which has published high quality original research across the breadth of the field since 1916, and G3: Genes|Genomes|Genetics, an open-access journal launched in 2011 to disseminate high quality foundational research in genetics and genomics. The Society also has a deep commitment to education and fostering the next generation of scholars in the field. For more information about GSA, please visit http://www.genetics-gsa.org. Also follow GSA on Facebook at facebook.com/GeneticsGSA and on Twitter @GeneticsGSA.


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