Variants in the CHRNA5–CHRNA3–CHRNB4 Region of Chromosome 15 Predict Gastrointestinal Adverse Events in the Transdisciplinary Tobacco Use Research Center Smoking Cessation Trial

Abstract

Introduction Reducing adverse events from pharmacologic treatment is an important goal of precision medicine and identifying genetic predictors of adverse events is a step toward this goal. In 2012, King et al. reported associations between genetic variants and adverse events in a placebo-controlled smoking cessation trial of varenicline and bupropion. Strong associations were found between gastrointestinal adverse events and 11 variants in the CHRNA5–CHRNA3–CHRNB4 region of chromosome 15, a region repeatedly associated with smoking-related phenotypes. Our goal was to replicate, in an independent sample, the impact of variants in the CHRNA5–CHRNA3–CHRNB4 region on gastrointestinal adverse events and to extend the analyses to adherence and smoking cessation. Methods The University of Wisconsin Transdisciplinary Tobacco Use Research Center (TTURC) conducted a multiarmed, placebo-controlled smoking cessation trial of bupropion and nicotine replacement therapy that included 985 genotyped European-ancestry participants. We evaluated relationships between our key variables using logistic regression. Results Gastrointestinal adverse events were experienced by 31.6% TTURC participants. Each of the CHRNA5–CHRNA3–CHRNB4 associations from the King et al. study was found in TTURC, with the same direction of effect. Neither these variants nor the gastrointestinal adverse events themselves were associated with adherence to medication or successful smoking cessation. Conclusions Variants in the CHRNA5–CHRNA3–CHRNB4 region of chromosome 15 are associated with gastrointestinal adverse events in smoking cessation. Additional independent variants in this region strengthen the association. The consistency between the results of these two independent studies supports the conclusion that these findings reflect biological response to the use of smoking cessation medication. Implications The fact that our findings from the TTURC smoking cessation trial support the independent findings of King et al. suggest that associations of variants in the CHRNA5–CHRNA3–CHRNB4 region of chromosome 15 with gastrointestinal adverse events while taking medications for smoking cessation reflect biology. However, although adherence to medication was a strong predictor of successful smoking cessation in TTURC, neither adverse events nor the genetic variants associated with them predicted either adherence or successful cessation in this study. Thus, although we should strive to minimize adverse events during treatment, we should not expect that to increase successful smoking cessation substantially.

Genetic Variant in CHRNA5 and Response to Varenicline and Combination Nicotine Replacement in a Randomized Placebo‐Controlled Trial

“…For example, medication adherence did not vary meaningfully with medication type and genotype. This is consistent with existing findings in another trial 10 …”

“…This is consistent with existing findings in another trial. 10 Though replication is needed, it is important to note that the medication X gene interaction among African American smokers in this study may be clinically meaningful. The efficacy of varenicline is much higher (40%) than that of cNRT (0%) for smokers…”

“…8 One approach would be to identify genetic moderators of smoking treatment effectiveness or adverse effects and then use such information to inform treatment application. 3,9,10 Multiple large meta-analyses, including our own, have identified genetic markers that predict heaviness of smoking and smoking cessation, most notably near the cholinergic receptor nicotinic alpha 5 subunit (CHRNA5). [11][12][13][14] In particular, the coding variant rs16969968 changes an amino acid (aspartic acid to asparagine) in CHRNA5.…”

“…Precision medicine initiatives have the goal of using individual differences such as genotypes to guide treatment so as to improve health outcomes 8 . One approach would be to identify genetic moderators of smoking treatment effectiveness or adverse effects and then use such information to inform treatment application 3,9,10 …”