title: Genetic epidemiology of induced CYP3A4 activity.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Twin Research and Genetic Epidemiology, St Thomas' Hospital, London, UK.
authors.forename: Nilufer
authors.initials: N
authors.lastname: Rahmioglu
authors.forename: James
authors.initials: J
authors.lastname: Heaton
authors.forename: Gail
authors.initials: G
authors.lastname: Clement
authors.forename: Raj
authors.initials: R
authors.lastname: Gill
authors.forename: Gabriela
authors.initials: G
authors.lastname: Surdulescu
authors.forename: Karolina
authors.initials: K
authors.lastname: Zlobecka
authors.forename: Dylan
authors.initials: D
authors.lastname: Hodgkiss
authors.forename: Yongmin
authors.initials: Y
authors.lastname: Ma
authors.forename: Robert C
authors.initials: RC
authors.lastname: Hider
authors.forename: Norman W
authors.initials: NW
authors.lastname: Smith
authors.forename: Kourosh R
authors.initials: KR
authors.lastname: Ahmadi
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000428:Alcohol Drinking / Q000235:genetics / Q000378:metabolism; D054316:Biomarkers, Pharmacological; D015992:Body Mass Index; D051544:Cytochrome P-450 CYP3A / Q000235:genetics* / Q000378:metabolism*; D005260:Female; D006801:Humans; D020902:Hypericum; D008875:Middle Aged; D008957:Models, Genetic; D010936:Plant Extracts / Q000008:administration & dosage / Q000494:pharmacology*; D011802:Quinidine / Q000031:analogs & derivatives / Q000652:urine; D011803:Quinine / Q000494:pharmacology / Q000652:urine; D012907:Smoking / Q000235:genetics / Q000378:metabolism; D011795:Surveys and Questionnaires
chemical_list: D054316:Biomarkers, Pharmacological; D010936:Plant Extracts; C013569:3-hydroxyquinidine; D011803:Quinine; D051544:Cytochrome P-450 CYP3A; C510163:CYP3A4 protein, human; D011802:Quinidine