Published in

Nicotine & Tobacco Research, 2022

DOI: 10.1093/ntr/ntac043

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The promise of polygenic risk prediction in smoking cessation: Evidence from two treatment trials

Distributing this paper is prohibited by the publisher
Distributing this paper is prohibited by the publisher

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Abstract

Abstract Introduction Tobacco use disorder is a complex behavior with a strong genetic component. Genome-wide association studies (GWAS) on smoking behaviors allows for the creation of polygenic risk scores (PRSs) to approximate genetic vulnerability. However, the utility of smoking-related PRSs in predicting smoking cessation in clinical trials remains unknown. Methods We evaluated the association between polygenic risk scores and bioverified smoking abstinence in a meta-analysis of two randomized, placebo-controlled smoking cessation trials. PRSs of smoking behaviors were created using the GWAS and Sequencing Consortium of Alcohol and Nicotine use (GSCAN) consortium summary statistics. We evaluated the utility of using individual PRS of specific smoking behavior vs. combined genetic risk that combines PRS of all four smoking behaviors. Study participants came from the Transdisciplinary Tobacco Use Research Centers (TTURC) Study (1,091 smokers of European descent), and the Genetically Informed Smoking Cessation Trial (GISC) Study (501 smokers of European descent). Results PRS of later age of smoking initiation (OR [95% CI]: 1.20, [1.04-1.37], p=0.0097) was significantly associated with bioverified smoking abstinence at end of treatment. In addition, the combined PRS of smoking behaviors also significantly predicted bioverified smoking abstinence (OR [95% CI] 0.71 [0.51-0.99], p=0.045). Conclusions PRS of later age at smoking initiation may be useful in predicting smoking cessation at the end of treatment. A combined PRS may be a useful predictor for smoking abstinence by capturing the genetic propensity for multiple smoking behaviors. Implications There is a potential for polygenic risk scores to inform future clinical medicine, and a great need for evidence on whether these scores predict clinically meaningful outcomes. Our meta-analysis provides early evidence for potential utility of using polygenic risk scores to predict smoking cessation amongst smokers undergoing quit attempts, informing further work to optimize use of polygenic risk scores in clinical care.