Researchers at Weill Cornell Medical College and Cornell University’s Ithaca campus have developed a new computational method to study genetic and environmental interactions and how they affect disease risk.
The research was published January 7 in American Journal of Human Genetics, It makes finding these reactions less difficult and demonstrates their importance in determining BMI and diabetes risk.
“Our study demonstrates that your genes are important, that the environment matters, and that interaction between them can increase the risk of disease,” said co-lead author Dr. Olivier Element, a professor of computational genomics in computational biomedicine and professor of physiology. And Biophysics, Assistant Director of His Royal Highness Prince Al Waleed Bin Talal Bin Abdulaziz Al Saud Institute for Computational Biomedicine, and Director of the Carel and Israel Englander Institute for Precision Medicine at Weill Cornell Medicine.
Lead author Andrew Marderstein, a PhD student at Weill Cornell Graduate School of Medical Sciences, who has researched both in the lab of Dr. Element in New York City and Dr. Andrew Clark, said that studying the interactions between the environment and genes usually creates a major computational challenge in a laboratory in Ithaca, which enabled him immediate access to computational biology and population health expertise.
“The interaction between genotype and environment can be thought of as a situation in which some genotypes are more sensitive to environmental insults than others,” said Dr. Clark, co-lead author and professor of population genetics in the Department of Molecular Biology and Jacob Gould Schurman. Genetics at the College of Arts and Sciences and Nancy Family Investigator and Peter Minnig at Cornell University. “These are precisely those situations where changes in diet or other exposures may have the greatest improvement in health, but only for a subset of individuals.”
The millions of genetic variants, or inherited genetic differences found between individuals in a population, different lifestyle and environmental factors, such as smoking, exercise, and different eating habits, can be analyzed for combined effects in many ways. When researchers test interactions between genes and the environment, they typically analyze millions of data points in a binary fashion, which means that they evaluate one genetic variant and its interaction with one environmental factor at a time. Marderstein said this type of analysis can get labor intensive.
The new computational method prioritizes and assesses a smaller number of variants in the genome – or the whole set of genetic material in the body – to genetic interactions and the environment. “We condensed a problem with analyzing 10 million different genetic variants for analyzing dozens of variants in different regions of the genome,” Marderstein said.
While a standard genetic correlation study might look at whether a single genetic variant can lead to a mean change in body mass index (BMI), this study evaluated genetic variants associated with individuals with higher or lower body mass index (BMI). The researchers found that looking for sections of DNA associated with variation in a human trait, called the quantitative variation trait locus or vQTL, enabled them to more easily recognize the interactions of the genetic environment. Notably, the values of vQTLs associated with BMI were also most likely associated with diseases with significant environmental impacts.
Another area of study in which the new computational method might be useful, Marderstein said, is determining how an individual responds to a particular drug based on interactions of the genetic environment. Analyzing social determinants of health, that is, an individual’s environmental and social conditions, such as poverty level and educational attainment, is a third area of interest to researchers, according to Dr. Element.
In general, scientists in the field of precision medicine know that they can sequence a person’s DNA, as well as evaluate environmental factors such as air quality and physical activity, to better understand whether an individual is at risk of developing a specific disease. “The idea at the end of the day is to use these concepts in the clinic,” said Dr. Element. “This is part of the evolution of precision medicine, as we can now sequence someone’s genome very easily and then analyze all the variants in the genetic landscape that correlate with the risk of developing certain conditions.”
Olivier Element is a stockholder in OneThreeBiotech, a company that uses artificial intelligence-driven biology to accurately predict new potential therapies and to identify the biological mechanisms underlying drug efficacy. Dr.. Element is a shareholder in Volastra Therapeutics, a company that aims to extend the lives of cancer patients by leveraging unique insights into chromosomal instability.
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