Use of polygenic risk scores of nicotine metabolism in predicting smoking behaviors.
- Authors
- Chen, Li-Shiun; Hartz, Sarah M; Baker, Timothy B; Ma, Yinjiao; L Saccone, Nancy; Bierut, Laura J
- Year
- 2018
- Journal
- Pharmacogenomics
- PMID
- 30442082
- DOI
- 10.2217/pgs-2018-0081
- PMCID
- PMC6562697
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 (R range: 9.2-16%; minimum p = 7.6 × 10). The GWAS top hit variant rs56113850 significantly predicted nicotine metabolism biomarkers (R range: 14-17%; minimum p = 4.4 × 10). 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.
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External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Considerations, Caveats, and Suggestions for the Use of Polygenic Scores for Social and Behavioral Traits. | Non AL et al. | — | 2024 | → |
| Considerations for the application of polygenic scores to clinical care of individuals with substance use disorders. | Kember RL et al. | — | 2024 | → |
| A scoping review of smoking cessation pharmacogenetic studies to advance future research across racial, ethnic, and ancestral populations. | Prom-Wormley EC et al. | — | 2023 | → |
| Genomic medicine to reduce tobacco and related disorders: Translation to precision prevention and treatment. | Chen LS et al. | — | 2023 | → |
| Genotyping, characterization, and imputation of known and novel CYP2A6 structural variants using SNP array data. | Langlois AWR et al. | — | 2023 | → |
| The Promise of Polygenic Risk Prediction in Smoking Cessation: Evidence From Two Treatment Trials. | Bray M et al. | — | 2022 | → |
| Ancestry may confound genetic machine learning: Candidate-gene prediction of opioid use disorder as an example. | Hatoum AS et al. | — | 2021 | → |
| Evaluating the genetic effects of sex hormone traits on the development of mental traits: a polygenic score analysis and gene-environment-wide interaction study in UK Biobank cohort. | Liang X et al. | — | 2021 | → |
| Genome-wide association study of letrozole plasma concentrations identifies non-exonic variants that may affect CYP2A6 metabolic activity. | Hertz DL et al. | — | 2021 | → |
| Multi-Polygenic Analysis of Nicotine Dependence in Individuals of European Ancestry. | Risner VA et al. | — | 2021 | → |
| Review and Consensus on Pharmacogenomic Testing in Psychiatry. | Bousman CA et al. | — | 2021 | → |
| Transferability of Ancestry-Specific and Cross-Ancestry CYP2A6 Activity Genetic Risk Scores in African and European Populations. | El-Boraie A et al. | — | 2021 | → |
| Evaluation of a weighted genetic risk score for the prediction of biomarkers of CYP2A6 activity. | El-Boraie A et al. | — | 2020 | → |