OBJECTIVES: Single nucleotide variations (SNVs) in the cytochrome P450 (CYP) gene family are a primary cause of interindividual differences in therapeutic effects and adverse reactions to drugs. However, we still lack important information on the extent of CYP polymorphisms at the population level. Here, we developed a comprehensive data set of SNVs in all 57 human CYP genes by integrating data from two extensive population sequencing projects and analyzed the distribution of SNVs in different subpopulations. MATERIALS AND METHODS: CYP genetic variants derived from the NHLBI and 1000 Genomes project were classified by variant type, frequency, and ethnic origins. The genetic variability of CYP genes was normalized on the basis of nonlinear regression and the total number of genetic variations was estimated by the derived formulas. RESULTS: In total, we detected 6165 SNVs, of which many were novel. The vast majority (83.2%) of all SNVs in coding regions were very rare (minor allele frequency <0.1%). On the basis of the regression analysis, the total number of genetic variations in human CYP genes was calculated to be 3.4 × 10 and 4.8 × 10 for a population size of one million in Europeans and Africans, respectively. CONCLUSION: Our results suggest that the variant spectrum of human CYP genes is extensive and only a fraction of SNVs has been characterized to date. Moreover, the multitude of very rare novel sequence variants indicates that the commonly used SNV platforms are not satisfactory for determining the true genotype, which is critical information for personalized treatment with drugs influenced by CYP polymorphisms.
OBJECTIVES: Single nucleotide variations (SNVs) in the cytochrome P450 (CYP) gene family are a primary cause of interindividual differences in therapeutic effects and adverse reactions to drugs. However, we still lack important information on the extent of CYP polymorphisms at the population level. Here, we developed a comprehensive data set of SNVs in all 57 humanCYP genes by integrating data from two extensive population sequencing projects and analyzed the distribution of SNVs in different subpopulations. MATERIALS AND METHODS:CYP genetic variants derived from the NHLBI and 1000 Genomes project were classified by variant type, frequency, and ethnic origins. The genetic variability of CYP genes was normalized on the basis of nonlinear regression and the total number of genetic variations was estimated by the derived formulas. RESULTS: In total, we detected 6165 SNVs, of which many were novel. The vast majority (83.2%) of all SNVs in coding regions were very rare (minor allele frequency <0.1%). On the basis of the regression analysis, the total number of genetic variations in humanCYP genes was calculated to be 3.4 × 10 and 4.8 × 10 for a population size of one million in Europeans and Africans, respectively. CONCLUSION: Our results suggest that the variant spectrum of humanCYP genes is extensive and only a fraction of SNVs has been characterized to date. Moreover, the multitude of very rare novel sequence variants indicates that the commonly used SNV platforms are not satisfactory for determining the true genotype, which is critical information for personalized treatment with drugs influenced by CYP polymorphisms.
Authors: Caroline F Thorn; Michelle Whirl-Carrillo; Houda Hachad; Julie A Johnson; Ellen M McDonagh; Mark J Ratain; Mary V Relling; Stuart A Scott; Russ B Altman; Teri E Klein Journal: Clin Pharmacol Ther Date: 2019-01 Impact factor: 6.875
Authors: Julie-Anne Tanner; Andy Z Zhu; Katrina G Claw; Bhagwat Prasad; Viktoriya Korchina; Jianhong Hu; HarshaVardhan Doddapaneni; Donna M Muzny; Erin G Schuetz; Caryn Lerman; Kenneth E Thummel; Steven E Scherer; Rachel F Tyndale Journal: Pharmacogenet Genomics Date: 2018-01 Impact factor: 2.089
Authors: Meghan J Chenoweth; Jennifer J Ware; Andy Z X Zhu; Christopher B Cole; Lisa Sanderson Cox; Nikki Nollen; Jasjit S Ahluwalia; Neal L Benowitz; Robert A Schnoll; Larry W Hawk; Paul M Cinciripini; Tony P George; Caryn Lerman; Joanne Knight; Rachel F Tyndale Journal: Addiction Date: 2017-11-02 Impact factor: 6.526
Authors: Najmeh Ahangari; Mohammad Doosti; Majid Ghayour Mobarhan; Amirhossein Sahebkar; Gordon A Ferns; Alireza Pasdar Journal: Ann Med Date: 2020-08-24 Impact factor: 4.709