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Use of polygenic risk scores of nicotine metabolism in predicting smoking behaviors.


ABSTRACT: AIM:This study tests whether polygenic risk scores (PRSs) for nicotine metabolism predict smoking behaviors in independent data. MATERIALS & METHODS:Linear regression, logistic regression and survival analyses were used to analyze nicotine metabolism PRSs and nicotine metabolism, smoking quantity and smoking cessation. RESULTS:Nicotine metabolism PRSs based on two genome wide association studies (GWAS) meta-analyses significantly predicted nicotine metabolism biomarkers (R2 range: 9.2-16%; minimum p = 7.6 × 10-8). The GWAS top hit variant rs56113850 significantly predicted nicotine metabolism biomarkers (R2 range: 14-17%; minimum p = 4.4 × 10-8). There was insufficient evidence for these PRSs predicting smoking quantity and smoking cessation. CONCLUSION:Results suggest that nicotine metabolism PRSs based on GWAS meta-analyses predict an individual's nicotine metabolism, so does use of the top hit variant. We anticipate that PRSs will enter clinical medicine, but additional research is needed to develop a more comprehensive genetic score to predict smoking behaviors.

SUBMITTER: Chen LS 

PROVIDER: S-EPMC6562697 | biostudies-literature | 2018 Dec

REPOSITORIES: biostudies-literature

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Use of polygenic risk scores of nicotine metabolism in predicting smoking behaviors.

Chen Li-Shiun LS   Hartz Sarah M SM   Baker Timothy B TB   Ma Yinjiao Y   L Saccone Nancy N   Bierut Laura J LJ  

Pharmacogenomics 20181116 18


<h4>Aim</h4>This study tests whether polygenic risk scores (PRSs) for nicotine metabolism predict smoking behaviors in independent data.<h4>Materials & methods</h4>Linear regression, logistic regression and survival analyses were used to analyze nicotine metabolism PRSs and nicotine metabolism, smoking quantity and smoking cessation.<h4>Results</h4>Nicotine metabolism PRSs based on two genome wide association studies (GWAS) meta-analyses significantly predicted nicotine metabolism biomarkers (R<  ...[more]

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