A team led by researchers at Washington University in St. Louis has shown that genetic variants associated with nicotine dependence and smoking quantity are also predictive of whether patients will benefit from the use of smoking cessation medications.
The group published results from a study of two cohorts — one from a previous community-based cross-sectional study of smokers quitting on their own and another from a randomized comparative effectiveness trial of smoking cessation treatment — in the American Journal of Psychiatry last month.
Overall, the researchers found that smokers with a high-risk genetic variant haplotype were less likely to succeed in quitting on their own and more likely to respond to drug treatment using bupropion, nicotine replacement, or both, than those with a low-risk haplotype. Adding treatment reduced the high-risk group's risk of cessation failure, while those with a low-risk haplotype did similarly well at quitting regardless of pharmacotherapy.
Li-Shiun Chen, the study's first author and an assistant professor of psychiatry at the Washington University School of Medicine, told PGx Reporter this week that the group's results suggest that genetic variants in the CHRNA5-CHRNA2-CHRNB4 region can be used to personalize smoking-cessation therapy by identifying those patients who are likely to benefit from nicotine replacement and bupropion treatment, and saving those who are not likely to benefit from unnecessary pharmacotherapy and associated side effects.
"More data needs to be collected supporting the implementation of these findings," Chen said. "But … we believe that the prescription of the medication needs to be personalized based on the genetic makeup of the patient."
In the initial study, the group only looked at nicotine replacement therapy and bupropion, but Chen said the researchers are now working to see if the same genetic variants show a similar association with another smoking cessation treatment, Pfizer's Chantix (varenicline), Chen said.
The researchers are also exploring whether additional genetic markers might help predict patients' response to one medication over another, as well as whether variants can predict smokers' response to counseling.
"Our overall goal is to [be able to] tailor medication versus counseling, and if medication is needed, to know which one," said Chen.
In 2000, the CDC's Morbidity and Mortality Weekly Report estimated that the annual number of pharmacologically assisted cessation attempts increased from less than 2 million in 1984 to more than 8 million in 1998 in the US. Some estimates have predicted that smoking cessation therapies could make up $2.4 billion market in 2012.
In the recent AJP study, Chen's group analyzed the association between variants in the chromosome region 15q25 with smokers' success in quitting in two study cohorts.
"In the past few years in large-scale genetic studies we have identified several genetic markers that [are associated with] increased risk for heavy smoking and nicotine dependence, with the most robust findings in a nicotine receptor gene on chromosome 15," Chen said.
"So then our question was, 'Do the genetic risks we know are prominent in smoking affect a person's ability to quit?' We were hoping to understand how the genetics could be useful to [guide treatment]."
In the first patient group — 5,216 subjects from the Atherosclerosis Risk in Communities study — the researchers matched patients' CHRNA5-CHRNA2-CHRNB4 haplotypes to their age at smoking cessation, finding that those with a high-risk haplotype had an average quit time that was two years later than those in the two lower-risk haplotype groups.
"This is clinically significant in that we can use the marker to predict people's difficulty quitting," Chen said. "These high-risk variant people would be exposed to nicotine two years longer on average, so that is important to know."
In the second analysis — of a 1,073-patient cohort from a randomized placebo-controlled trial comparing treatments using nicotine replacement, bupropion, or combinations of the two — the researchers matched subjects' haplotypes to how long they were able to maintain their quit status before relapsing.
Overall, 47 percent of the trial participants were abstinent eight weeks after their quit date, the group reported. Haplotypes did not predict abstinence across the placebo and treatment groups, but depended, rather, on treatment condition.
"We saw that for individuals with the high-risk genetic variant, these people were less likely to quit successfully on their own without medication, but with medication, they were three times more likely to quit successfully."
Those with the low-risk genetic variant, meantime, "were more likely to quit on their own and the medications really didn't help them at all," Chen said.
"This is very important, not only for identifying patients who should get medication," Chen said, "but also for those patients who can quit on their own and don't benefit from medication, especially certain patients who could potentially get side effects, like those who are pregnant, or with heart disease, or other conditions where these medications are not really as benign."
"We would want to identify these people and avoid giving them extra medication that could potentially [harm them]."
Interestingly, the researchers did not measure an association between haplotypes and differences in abstinence among the different treatment regimes in the trial. Those with a high-risk haplotype had poorer abstinence, mediated by medication, regardless of whether they received nicotine replacement, or bupropion, or both.
According to Chen, the study's findings are a stepping stone toward the goal of personalizing therapy for those hoping to quit smoking. The results suggest that the biological effects of the three haplotypes that the group tracked, affect both smoking quantity and the ability to quit, and that pharmacologic treatments are more likely to be effective for those who are genetically predisposed to have difficulty quitting.
In the future, the group hopes to also establish genetic markers that can help predict which patients will do better on one smoking cessation drug versus another, Chen said.