gms | German Medical Science

Kongress Medizin und Gesellschaft 2007

17. bis 21.09.2007, Augsburg

Genomewide Association Studies: Recent Advances and Potential Implications

Meeting Abstract

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  • Joel N. Hirschhorn - Children’s Hospital/Harvard Medical School and Broad Institute of Harvard and MIT, Boston, MA, USA

Kongress Medizin und Gesellschaft 2007. Augsburg, 17.-21.09.2007. Düsseldorf: German Medical Science GMS Publishing House; 2007. Doc07gmds156

The electronic version of this article is the complete one and can be found online at:

Published: September 6, 2007

© 2007 Hirschhorn.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( You are free: to Share – to copy, distribute and transmit the work, provided the original author and source are credited.



Most common diseases and quantitative traits are complex multifactorial traits with substantial genetic components. To date, the underlying genetic factors have remained largely elusive, in part because each causal variant only accounts for a small fraction of variation in the population. Genetic association studies offer a potentially powerful approach to identifying sequence variants that are common in the population and have modest effects on disease susceptibility or quantitative traits. However, to maximize the chances of success and avoid false leads, careful attention to detail is required when performing and interpreting association studies. We have helped characterize the sources of inconsistency in association studies and have developed tools to minimize population stratification, one of the potential causes of false positive associations.

Genomewide association studies have recently become feasible, and permit a comprehensive search for genetic variation (particularly common variation) that contributes to common disease and quantitative traits. The first round of whole genome association studies has identified dozens of genes and pathways that influence disease susceptibility but were previously unsuspected as being important in pathogenesis, thereby expanding our understanding of disease and human biology. As participants in the Diabetes Genetics Initiative of Broad, Lund and Novartis, we successfully applied this approach to identify common genetic variants that influence type 2 diabetes, height and other quantitative traits. We are currently collaborating with several groups to perform well-powered surveys of the genome for common variants that influence obesity (measured as body mass index) or height in the general population. Finally, it is important to appreciate both the potential and the obstacles for translating genetic discoveries into improvements in clinical practice.