Transferability of Ancestry-Specific and Cross-Ancestry CYP2A6 Activity Genetic Risk Scores in African and European Populations

Ahmed El-Boraie, Meghan J Chenoweth, Jennie G Pouget, Neal L Benowitz, Koya Fukunaga, Taisei Mushiroda, Michiaki Kubo, Nicole L Nollen, Lisa Sanderson Cox, Caryn Lerman, Jo Knight, Rachel F Tyndale, Ahmed El-Boraie, Meghan J Chenoweth, Jennie G Pouget, Neal L Benowitz, Koya Fukunaga, Taisei Mushiroda, Michiaki Kubo, Nicole L Nollen, Lisa Sanderson Cox, Caryn Lerman, Jo Knight, Rachel F Tyndale

Abstract

The Nicotine Metabolite Ratio (NMR; 3-hydroxycotinine/cotinine), a highly heritable index of nicotine metabolic inactivation by the CYP2A6 enzyme, is associated with numerous smoking behaviors and diseases, as well as unique cessation outcomes. However, the NMR cannot be measured in nonsmokers, former smokers, or intermittent smokers, for example, in evaluating tobacco-related disease risk. Traditional pharmacogenetic groupings based on CYP2A6 * alleles capture a modest portion of NMR variation. We previously created a CYP2A6 weighted genetic risk score (wGRS) for European (EUR)-ancestry populations by incorporating independent signals from genome-wide association studies to capture a larger proportion of NMR variation. However, CYP2A6 genetic architecture is unique to ancestral populations. In this study, we developed and replicated an African-ancestry (AFR) wGRS, which captured 30-35% of the variation in NMR. We demonstrated model robustness against known environmental sources of NMR variation. Furthermore, despite the vast diversity within AFR populations, we showed that the AFR wGRS was consistent between different US geographical regions and unaltered by fine AFR population substructure. The AFR and EUR wGRSs can distinguish slow from normal metabolizers in their respective populations, and were able to reflect unique smoking cessation pharmacotherapy outcomes previously observed for the NMR. Additionally, we evaluated the utility of a cross-ancestry wGRS, and the capacity of EUR, AFR, and cross-ancestry wGRSs to predict the NMR within stratified or admixed AFR-EUR populations. Overall, our findings establish the clinical benefit of applying ancestry-specific wGRSs, demonstrating superiority of the AFR wGRS in AFRs.

Trial registration: ClinicalTrials.gov NCT00666978 NCT01314001 NCT01836276.

Conflict of interest statement

Conflict of Interest: R.F.T. has consulted for Quinn Emanuel and Ethismos on unrelated topics. All other authors declared no competing interests for this work.

© 2020 The Authors. Clinical Pharmacology & Therapeutics © 2020 American Society for Clinical Pharmacology and Therapeutics.

Figures

Figure 1
Figure 1
Flowchart for the A) Ancestry-specific and B) Cross-ancestry wGRS analyses. The training sets consisted of individuals screened from two trials (PNAT2 and KIS3) and where ancestry was determined through PC clustering analysis to the HapMap3 populations. Variants tested included GWAS independent signals and * alleles from the specified population. For the cross-ancestry wGRS, all ancestry-specific wGRS variants were merged.
Figure 2
Figure 2
Linear regression analyses of the relationship between the wGRS and log-transformed NMR in the A) training set (N=954; combined PNAT2 and KIS3 trials), and B) replication set (N=216; Q2L trial). The wGRS explained A) 32.4% of the variance in log-NMR in the training set and B) 34.3% in the replication set
Figure 3
Figure 3
Tukey box-and-whisker plots of nicotine metabolite ratio (NMR) distributions by genotype grouping. Data from the training set (N=954) is grouped as a function of A) * allele groupings; SM, slow metabolizers; IM, intermediate metabolizers; NM, normal metabolizers(48), V/V, two variant * alleles, B) wGRS scale (1.378–2.332) split into tertiles (T, tertile) and C), weighted genetic risk score (wGRS) scale (1.378–2.332) split into quintiles (Q, quintile)
Figure 4
Figure 4
Principal component analyses showing fine AFR population substructure. Principal components were computed from merging the 1KG AFR subpopulations and the training set (PNAT2+KIS3 AFR) samples. A) 1KG AFR subpopulations and training set (PNAT2+KIS3 AFR) participants plotted. B) 1KG AFR subpopulations plotted only. C) PNAT2 participants split by geographic recruitment sites plotted only. D) KIS3 participants plotted only. (ACB: 1KG African Caribbeans; ASW: 1KG Southwest Americans; LWK: 1KG Luhya; ESN: 1KG Esan; GWD: 1KG Gambian; MSL: 1KG Mende; YRI: 1KG Yoruba). Note: The PNAT2 Toronto site was excluded from the analyses in this Figure to the small sample size (N=14)
Figure 5
Figure 5
End-of-treatment quit rates in the PNAT2 trial by treatment and metabolizer group. Odds ratios (OR) with 95% confidence intervals (CI) comparing the efficacy of varenicline versus the nicotine patch. Metabolizer-by-treatment interaction effects --were evaluated by the ratio of odds ratios (ORR) with 95% CI. (A) NMR stratification (slow: NMRN=838)(22). (B) NMR stratification (slow: NMR<0.31, normal: NMR≥0.31) in the genetically determined AFR and EUR subset of the varenicline and nicotine patch treatment arms (N=679), and (C) AFR wGRS + EUR wGRS stratification (slow: wGRS<2.089 in AFR or 2.140 in EUR, normal: wGRS ≥2.089 in AFR or 2.140 in EUR) in the genetically determined AFR and EUR subset of the varenicline and nicotine patch treatment arms (N=679)

Source: PubMed

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