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

Pharmacogenomics. 2018 Dec;19(18):1383-1394. doi: 10.2217/pgs-2018-0081. Epub 2018 Nov 16.

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.

Keywords: CYP2A6; nicotine metabolism; polygenic risk scores; smoking cessation.

Publication types

  • Meta-Analysis
  • Research Support, N.I.H., Extramural

MeSH terms

  • Adult
  • Biomarkers / metabolism
  • Female
  • Genome-Wide Association Study / methods
  • Humans
  • Male
  • Middle Aged
  • Multifactorial Inheritance / genetics*
  • Nicotine / metabolism*
  • Risk
  • Smoking / genetics*
  • Smoking Cessation / methods
  • Tobacco Use Disorder / genetics*

Substances

  • Biomarkers
  • Nicotine

Grant support