A new study involving data from more than 20,000 individuals has uncovered several DNA sequences linked to impaired pulmonary function. The research, an analysis that combined the results of several smaller studies, provides insight into the mechanisms involved in reaching full lung capacity. The findings may ultimately lead to better understanding of lung function and diseases like asthma and chronic obstructive pulmonary disease (COPD), the fourth leading cause of death in the United States.
"We have known for a while that genetic factors put some people at risk for lower lung function -a factor in COPD and a risk for early mortality. But, we did not know which specific genetic regions were involved," said Stephanie London, M.D., Dr.P.H., senior investigator at the National Institute of Environmental Health Sciences (NIEHS), part of National Institutes of Health (NIH), and a senior author on the paper. "These findings point to specific gene regions."
Impaired lung function is a hallmark of COPD and other lung diseases. But it is also linked to mortality from a wide range of other diseases, including cardiovascular disease and cancer. So knowing some of the genes involved is a first step toward understanding the relationship between lung function and mortality, as well as developing new interventions to manage lung diseases.
"Leveraging our investment in collecting these samples has led to new findings and will help focus future research efforts," said James P. Kiley, Ph.D., director of the Division of Lung Diseases at the National Heart, Lung, and Blood Institute (NHLBI).
To conduct the analysis that is published online in the Dec. 13, 2009 issue of Nature Genetics, the researchers used data from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. CHARGE is an ongoing study - a group of groups - that combines genome-wide association study (GWAS) results from several population-based studies. Pooling data from many studies gives much greater power to find the specific genes involved than looking at any one study alone.
The GWAS approach involves measuring hundreds of thousands of genetic variants, in thousands of individuals, in hopes of finding novel genetic variations associated with specific diseases or conditions.