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Vanderbilt Researchers Tackle the Analysis Challenges of Multiple-Gene Interactions

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Jason Moore and his colleagues at Vanderbilt University are planning to release a free software package in early August that can identify multiple-gene interactions responsible for common diseases.

The software, based on a statistical technique Moore developed called Multifactor-Dimensionality Reduction, collapses the “high-dimensional space” required to analyze genetic information from multiple genes in large patient sets.

Moore explained that the automated method looks at multi-locus genotype combinations within a population and pools those determined to be at high risk into one group and those at low risk into another group. This effectively reduces the genotype predictors to a single one-dimensional variable, which is then evaluated for its ability to predict disease status through cross-validation and permutation testing.

The Vanderbilt researchers tested the method on data compiled on 200 women with breast cancer and 200 women without the disease. Studying 10 functional polymorphisms in five genes involved in estrogen metabolism on an individual basis gave no indication of cancer risk. However, when Moore and his team applied MDR to look at combinations of gene variants, they found that women with four specific polymorphisms were significantly more likely to develop breast cancer than those with fewer of these gene variants.

“To the best of our knowledge, this is the first time that such a multiple-gene interaction has been identified,” said Moore. The team recently published the results of their study in the American Journal of Human Genetics.

Very few single-gene mutations have been found responsible for common diseases, so Moore and his colleagues think their approach will be of great interest to researchers seeking multiple-gene risk factors. Moore said the technique could also be used to simplify microarray data analysis, an approach he is just beginning to explore.

Moore estimated MDR would be capable of analyzing interactions among as many as 20 genes.

The MDR software will be freely available to academic and non-profit users. While Vanderbilt intends to charge commercial organizations, the price scale hasn’t been finalized yet. It runs on Unix, Linux, and Sun Solaris operating systems.

Moore said he’s had about five requests for the software so far, which will be available at http://phg. mc.vanderbilt.edu/Software/MDR.

— BT

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