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The findings further support public smoking bans, researchers say.

Details of the study, which is the first to show that even minimal exposure to tobacco smoke triggers signs of detectable smoking stress in the genomewide gene expression profile of the lung, appear August 20 in the American Journal of Respiratory and Critical Care Medicine.

The technique developed for the study, which analyzed some 372 genes known to be sensitive to smoking, could potentially be used to detect the onset of a number of other nonsmoking related diseases as well.

To diagnose the start of lung disease, “you’d have to follow someone who smokes for many years, but what we have here is a signal that shows up at very low levels,” says Larsson Omberg, a postdoctoral researcher working with Jason Mezey, assistant professor of biological statistics and computational biology at Cornell University.

Ronald Crystal, senior author of the study and chief of pulmonary and critical care medicine at NewYork-Presbyterian/Weill Cornell, analyzed urine (for nicotine and cotinine, the chemical into which the liver breaks down nicotine) and cells from the small airways of the lung of 121 individuals.

Urine nicotine and cotinine levels were used to categorize volunteers as nonsmokers, occasional smokers, or heavy smokers.

The researchers drew upon various methods for analyzing genes quantified by microarray analysis. By combining methods, they created a new process that allowed them to see the effects of smoking on single genes as well as the entire genome at very low levels of exposure.

In volunteers with “low exposure” to smoking, more than one-third of the 372 genes sensitive to smoking were triggered. (Some genes have lower expression and some genes have higher expression when exposed to tobacco smoke).

This smoke stress was observed even when urine nicotine was below detectable levels, and when urine cotinine was just barely above detectable levels.

Heavy smokers triggered more of these genes and the expression of individual genes increased accordingly.
“The model allows us to predict, based on nicotine and cotinine levels, how much a gene may be expressing,” says Omberg. The method also allows analysis of all genes across the genome as one function.

“Using genomewide data, one can extract more subtle patterns of the effects of low levels of exposure,” adds Mezey.

Funding for the study came from grants from the National Institutes of Health, the Flight Attendant’s Medical Research Institute, and the Cornell Center for Comparative and Population Genomics.

More news from Cornell University: www.news.cornell.edu