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New statistical method links multiple genes to common complex diseases

Now that the human genome has been mapped, one of the biggest challenges facing human geneticists is identifying groups of genes that collectively conspire to make some individuals particularly susceptible to a number of common diseases, including breast cancer, cardiovascular disease and depression.

Disentangling genetic predisposition from environmental factors is a highly complex process. So far geneticists have been able to do so only for a limited number of cases like cystic fibrosis that are caused by mutations in a single gene. Where more than two genes are involved, however, traditional methods of analysis have floundered because it has proven impractical to acquire genetic information from the large number of subjects required.

Now, however, a group of researchers at the Vanderbilt University Medical Center and the Vanderbilt-Ingram Cancer Center report that they have developed an alternative statistical approach to this problem. The technique, called Multifactor Dimensionality Reduction, can identify multiple gene interactions using data from a reasonable number of patients. Writing in the July issue of the American Journal of Human Genetics, the researchers report that they have used this technique successfully to identify four DNA sequence variations in three genes that work together to heighten a womans risk of breast cancer.

"For some time we have known that a persons susceptibility to a number of common, complex diseases is not determined by a single gene, but by a number of genes working together," says Jason H. Moore, assistant professor of molecular physiology and biophysics, who led the research effort. "But, to the best of our knowledge, this is the first time that such a multiple-gene interaction has been identified."

Co-author and Professor of Pathology Fritz Parl, who has been studying the relation between estrogen and breast cancer for a number of years, predicts that this new approach will be widely
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Contact: David F. Salisbury
david.salisbury@vanderbilt.edu
615-343-6803
Vanderbilt University
27-Jun-2001


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