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Evaluation of a weighted genetic risk score for the prediction of biomarkers of CYP2A6 activity.

  • Author(s): El-Boraie, Ahmed
  • Taghavi, Taraneh
  • Chenoweth, Meghan J
  • Fukunaga, Koya
  • Mushiroda, Taisei
  • Kubo, Michiaki
  • Lerman, Caryn
  • Nollen, Nicole L
  • Benowitz, Neal L
  • Tyndale, Rachel F
  • et al.

Published Web Location

https://onlinelibrary.wiley.com/doi/abs/10.1111/adb.12741
No data is associated with this publication.
Creative Commons 'BY-NC-SA' version 4.0 license
Abstract

The nicotine metabolite ratio (NMR; 3-hydroxycotinine/cotinine) is an index of CYP2A6 activity. CYP2A6 is responsible for nicotine's metabolic inactivation and variation in the NMR/CYP2A6 is associated with several smoking behaviors. Our aim was to integrate established alleles and novel genome-wide association studies (GWAS) signals to create a weighted genetic risk score (wGRS) for the CYP2A6 gene for European-ancestry populations. The wGRS was compared with a previous CYP2A6 gene scoring approach designed for an alternative phenotype (C2/N2; cotinine-d2/(nicotine-d2 + cotinine-d2)). CYP2A6 genotypes and the NMR were assessed in European-ancestry participants. The wGRS training set included N = 933 smokers recruited to the Pharmacogenetics of Nicotine Addiction and Treatment clinical trial [NCT01314001]. The replication cohort included N = 196 smokers recruited to the Quit 2 Live clinical trial [NCT01836276]. Comparisons between the two CYP2A6 phenotypes and with fractional clearance were made in a laboratory-based pharmacokinetic study (N = 92 participants). In both the training and replication sets, the wGRS, which included seven CYP2A6 variants, explained 33.8% (P < 0.001) of the variance in NMR, providing improved predictive power to the NMR phenotype when compared with other CYP2A6 gene scoring approaches. NMR and C2/N2 were strongly correlated to nicotine clearance (ρ = 0.70 and ρ = 0.79, respectively; P < 0.001), and to one another (ρ = 0.82; P < 0.001); however reduced function genotypes occurred in slow NMR but throughout C2/N2. The wGRS was able to predict smoking quantity and nicotine intake, to discriminate between NMR slow and normal metabolizers (AUC = 0.79; P < 0.001), and to replicate previous NMR-stratified cessation outcomes showing unique treatment outcomes between metabolizer groups.

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