Newsroom
RESEARCH TRIANGLE PARK, N.C. – Using a novel statistical method that considers environmental interactions, like cigarette smoking, to better understand genetic risk factors for lung disease, a study led by RTI International in collaboration with the National Institute of Environmental Health Sciences, identified new gene regions related to lung function.
Measuring lung function provides an important clinical tool for diagnosing and evaluating the severity of lung diseases such as chronic obstructive pulmonary disease (COPD), the third leading cause of death in the United States.
The study, published in the December issue of PLOS Genetics, scanned genetic variants across the genome and identified three gene regions not previously known to be related to lung function. Unlike previous genome-wide studies that considered only the genetic main effects, the researchers used the newly developed joint meta-analysis method to simultaneously test genetic main effects and gene-environment interactions in relation to two clinically important lung function measures.
The research team, composed of 90 investigators across the United States and Europe, analyzed the results of more than 50,000 participants of European descent from 19 independent study cohorts. Dana Hancock, Ph.D., a genetic epidemiologist at RTI was the first author of the study, and Stephanie London, M.D., Dr.P.H., senior investigator at NIEHS, was senior author.
“The well-documented and consistent negative effect of cigarette smoking on lung function makes it a good candidate for this type of analysis.” Hancock said. “Genetic factors may have subtle, yet different effects on lung function depending on smoking exposure.”
The new approach allows researchers to take into account the interaction between genetic and environmental risk factors, which could lead to a better understanding of the complex nature of disease.
According to the authors, the study represents the largest and most comprehensive analysis to date of gene-by-smoking interaction in relation to any lung-related trait.
“This work highlights the usefulness of employing novel methods for incorporating gene-environment interaction in genome-wide association studies,” Hancock said. “We were able to identify genetic regions associated with a complex trait that had been missed when considering only the genetic main effects.”
