Genome-wide association study reveals a complex genetic architecture underpinning-induced CYP3A4 enzyme activity.

Atypical cytochrome P450 3A4 (CYP3A4) enzyme activity-induced and inhibited-is thought to be the driver of numerous poor or adverse therapeutic responses to up to 50 % of all commonly prescribed drugs. We carried out a genome-wide association study to identify common genetic variants associated with variation in induced CYP3A4 activity. A total of 310 twins were included in this study. Each participant had already completed a 14 days course of St John's Wort to induce CYP3A4, which was quantified through the metabolic ratio of exogenous 3-hydroxyquinine to quinine. We failed to detect any genome-wide significant associations (P < 1 × 10(-8)) with variation in induced CYP3A4 activity although several genomic regions were highlighted which may play minor roles. We report the first GWAS of variation in induced CYP3A4 activity and our preliminary results indicate a complex genetic architecture underpinning induced CYP3A4 enzyme activity.

Genetic epidemiology of induced CYP3A4 activity.

AIM: The cytochrome P450 3A4 (CYP3A4) enzyme is implicated in the metabolism of more than 50% of all prescribed medications and its activity - including induced or inhibited activity - is deemed to be a crucial determinant of interindividual variability in drug disposition, poor therapeutic efficacy, and adverse response to medication. METHODS: We used the classical twin model in conjunction with an induction experiment to uncover the relative contribution of genetic and environmental factors to interindividual variation in induced CYP3A4 activity. A total of 367 healthy twins participated in the study. Each volunteer was administered a potent inducer of CYP3A4 (St John's Wort) for 14 days and the activity of CYP3A4 was quantified through the metabolism of the exogenously administered probe drug quinine sulfate. RESULTS: Baseline and induced CYP3A4 activity were highly variable with a seven-fold and 11-fold difference among our population, respectively. Alcohol consumption, BMI, and smoking were significantly associated with induced CYP3A4 activity, collectively explaining 20% of the variation (P<1×10(-4)). The narrow-sense heritability of induced CYP3A4 activity was estimated at 66%, whereas the remainder of the variation was attributed to unique environmental factors. CONCLUSION: To our knowledge, this is the first genetic epidemiological study of induced CYP3A4 activity. Our results motivate further research to identify common and rarer genetic variants that underpin the heritable component of variation in induced CYP3A4 activity.

Prediction of variability in CYP3A4 induction using a combined 1H NMR metabonomics and targeted UPLC-MS approach.

The activity of Cytochrome P450 3A4 (CYP3A4) enzyme is associated with many adverse or poor therapeutic responses to drugs. We used (1)H NMR-based metabonomics to identify a metabolic signature associated with variation in induced CYP3A4 activity. A total of 301 female twins, aged 45--84, participated in this study. Each volunteer was administered a potent inducer of CYP3A4 (St. John's Wort) for 14 days and the activity of CYP3A4 was quantified through the metabolism of the exogenously administered probe drug quinine sulfate (300 mg). Pre- and postintervention fasting urine samples were used to obtain metabolite profiles, using (1)H NMR spectroscopy, and were analyzed using UPLC--MS to obtain a marker for CYP3A4 induction, via the ratio of 3-hydroxyquinine to quinine (3OH-Q:Q). Multiple linear regression was used to build a predictive model for 3OH-Q:Q values based on the preintervention metabolite profiles. A combination of seven metabolites and seven covariates showed a strong (r = 0.62) relationship with log(3OH-Q:Q). This regression model demonstrated significant (p < 0.00001) predictive ability when applied to an independent validation set. Our results highlight the promise of metabonomics for predicting CYP3A4-mediated drug response.