Cytokines are molecules that act as signals between cells. The authors were examining the cytokine IL 10, which is involved in the development of various tumors.

"In breast cancer risk, IL-10 may be a two-edged sword," Dr. Langsenlehner said. "On one hand, higher IL-10 levels could facilitate development of cancer by supporting tumor escape from the immune response. On the other hand, the anti-angiogenic effects of IL-10 are supposed to prevent or reduce tumor growth and spread."

Specifically, the Austrian team examined a particular genetic arrangement, or haplotype, in the promoter region of the gene, which has been associated with increased IL-10 expression. The researchers call this the TCATA haplotype.

In a study comparing 500 women with breast cancer against 500 health controls, they found that breast cancer patients were significantly less likely to have two versions of the TCATA haplotype.

"Our study suggests that high levels of IL-10 may be protective against breast cancer," Dr. Langsenlehner said. "The mechanism for this remains to be determined, but may likely include anti-angiogenic functions of IL-10. If this result can be confirmed in additional studies, determination of IL 10 genotypes may help to obtain a more precise individual breast cancer risk profile."

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The new HSPH analysis method, which uses just one dataset, bypasses the multiple comparison problem altogether by first estimating how much genetics can explain a specific trait within a population, and then tracing the roots of the trait back to candidate SNPs that would explain that "genetic effect size." To test their methodology, the research team ran simulation studies using data from the Childhood Asthma Management Program (CAMP) Genetics Ancillary Study based at Channing Laboratory, Brigham and Women's Hospital, in Boston and data from a joint study conducted by the Mayo Clinic College of Medicine and Affymetrix. The results of the simulation studies suggested that the new approach outperformed the traditional approach by factors up to 100.

Besides dealing away with the multiple comparison problem, the HSPH technique offers another feature that is highly attractive to geneticists-the methodology appears to be able to find multiple SNPs involved in a single disease or trait.

"Many biomedical scientists today are interested in complex phenotypes, such as risk for unhealthy levels of body mass index, blood pressure, or cholesterol," said HSPH Assistant Professor of Biostatistics Christoph Lange, who is senior author on the paper. "Yet until now, no statistical tool existed that would allow researchers to look at several thousand disease genes and successfully identify those small number of genes that influence such complex traits."

The HSPH methodology is part of an analysis software program called PBAT, freely available at biostat.harvard/~clange/default.htm. The program was developed by Lange and HSPH Professor Nan Laird.

The CAMP Genetics Ancillary Study is supported by the National Heart, Lung, and Blood Institute. The joint study conducted by the Mayo Clinic College of Medicine and Affymetrix was supported by the Mayo Clinic Genomic Center and Comprehensive Cancer Center and by the National Institutes of Health (NIH). The NIH provided additional funding for the HSPH research.

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