Harvard School of Public Health research has found that detailed knowledge about your genetic makeup—the interplay between genetic variants and other genetic variants, or between genetic variants and environmental risk factors—may only change your estimated disease prediction risk for three common diseases by a few percentage points.
It is the first study to revisit claims in previous research that including such information in risk models would eventually help doctors either prevent or treat diseases.
“While identifying a synergistic effect between even a single genetic variant and another risk factor is known to be extremely challenging and requires studies with a very large number of individuals, the benefit of such discovery for risk prediction purpose might be very limited,” said lead author Hugues Aschard, research fellow in the Department of Epidemiology.
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Scientists have long hoped that using genetic information gleaned from the Human Genome Project and other genetic research could improve disease risk prediction enough to help aid in prevention and treatment.
Aschard and his co-authors, including senior author Peter Kraft, Harvard School of Public Health associate professor of epidemiology, examined whether disease risk prediction would improve for breast cancer, type 2 diabetes, and rheumatoid arthritis if they included the effect of synergy in their statistical models. But they found no significant effect by doing so. “Statistical models of synergy among genetic markers are not ‘game changers’ in terms of risk prediction in the general population,” said Aschard.
“Overall, our findings suggest that the potential complexity of genetic and environmental factors related to disease will have to be understood on a much larger scale than initially expected to be useful for risk prediction. The road to efficient genetic risk prediction, if it exists, is likely to be long,” said Aschard.
The American Journal of Human Genetics, online May 24, 2012 “Inclusion of Gene-Gene and Gene-Environment Interactions Unlikely to Dramatically Improve Risk Prediction for Complex Diseases,” Hugues Aschard, Jinbo Chen, Marilyn C. Cornelis, Lori B. Chibnik, Elizabeth W. Karlson, Peter Kraft
Support for the study was from the National Institutes of Health through the National Institute of Diabetes and Digestive and Kidney Diseases and the National Institute of Arthritis and Musculoskeletal and Skin Diseases, and from the Fondation Bettencourt–Schueller.