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

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.