Knowing genetic makeup may not significantly improve disease risk prediction

May 24, 2012

Harvard School of Public Health (HSPH) researchers have 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, which is typically not enough to make a difference in prevention or treatment plans. 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.

The study appears online May 24, 2012 and will appear in the June 8, 2012 print issue of The American Journal of Human Genetics.

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. Others have been skeptical that such "personalized medicine" will be of clinical benefit. Still others have argued that there will be benefits in the future, but that current risk prediction algorithms underperform because they don't allow for potential synergistic effects—the interplay of multiple genetic risk markers and environmental factors—instead focusing only on individual genetic markers.

Aschard and his co-authors, including senior author Peter Kraft, HSPH 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.

The researchers conducted a simulation study by generating a broad range of possible statistical interactions among common environmental exposures and common genetic risk markers related to each of the three diseases. Then they estimated whether such interactions would significantly boost disease prediction risk when compared with models that didn't include these interactions since, to date, using individual genetic markers in such predictions has provided only modest improvements.

For breast cancer, the researchers considered 15 common genetic variations associated with disease risk and environmental factors such as age of first menstruation, age at first birth, and number of close relatives who developed breast cancer. For type 2 diabetes, they looked at 31 genetic variations along with factors such as obesity, smoking status, physical activity, and family history of the disease. For rheumatoid arthritis, they also included 31 genetic variations, as well as two environmental factors: smoking and breastfeeding.

But, for each of these disease models, researchers calculated that the increase in risk prediction sensitivity—when considering the potential interplay between various genetic and environmental factors—would only be between 1% and 3% at best.

"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.

"For most people, your doctor's advice before seeing your genetic test for a particular disease will be exactly the same as after seeing your tests," added Kraft.

Still, Aschard and his co-authors recommend further study of gene-gene and gene-environmental interactions because it can provide important clues, if not about , at least about disease causes—which could in turn lead to improved treatment and prevention strategies.

Marilyn Cornelis, research associate in the Department of Nutrition at HSPH, was also a co-author on the study.

Explore further: A hidden architecture: Researchers use novel methods to uncover gene mutations for common diseases

More information: "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, The American Journal of Human Genetics, online May 24, 2012

Related Stories

A hidden architecture: Researchers use novel methods to uncover gene mutations for common diseases

March 25, 2012
Human geneticists have long debated whether the genetic risk of the most common medical conditions derive from many rare mutations, each conferring a high degree of risk in different people, or common differences throughout ...

Recommended for you

Genome analysis with near-complete privacy possible, say researchers

August 17, 2017
It is now possible to scour complete human genomes for the presence of disease-associated genes without revealing any genetic information not directly associated with the inquiry, say Stanford University researchers.

Science Says: DNA test results may not change health habits

August 17, 2017
If you learned your DNA made you more susceptible to getting a disease, wouldn't you work to stay healthy?

Genetic variants found to play key role in human immune system

August 16, 2017
It is widely recognized that people respond differently to infections. This can partially be explained by genetics, shows a new study published today in Nature Communications by an international collaboration of researchers ...

Phenotype varies for presumed pathogenic variants in KCNB1

August 16, 2017
(HealthDay)—De novo KCNB1 missense and loss-of-function variants are associated with neurodevelopmental disorders, with or without seizures, according to a study published online Aug. 14 in JAMA Neurology.

Active non-coding DNA might help pinpoint genetic risk for psychiatric disorders

August 16, 2017
Northwestern Medicine scientists have demonstrated a new method of analyzing non-coding regions of DNA in neurons, which may help to pinpoint which genetic variants are most important to the development of schizophrenia and ...

Evolved masculine and feminine behaviors can be inherited from social environment

August 15, 2017
The different ways men and women behave, passed down from generation to generation, can be inherited from our social environment - not just from genes, experts have suggested.

0 comments

Please sign in to add a comment. Registration is free, and takes less than a minute. Read more

Click here to reset your password.
Sign in to get notified via email when new comments are made.