{"title":"主要药物代谢细胞色素 P450 基因的遗传格局--对群体规模测序数据的最新分析","authors":"Yitian Zhou, Volker M. Lauschke","doi":"10.1038/s41397-022-00288-2","DOIUrl":null,"url":null,"abstract":"Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":"22 5-6","pages":"284-293"},"PeriodicalIF":2.9000,"publicationDate":"2022-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674520/pdf/","citationCount":"15","resultStr":"{\"title\":\"The genetic landscape of major drug metabolizing cytochrome P450 genes—an updated analysis of population-scale sequencing data\",\"authors\":\"Yitian Zhou, Volker M. Lauschke\",\"doi\":\"10.1038/s41397-022-00288-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.\",\"PeriodicalId\":54624,\"journal\":{\"name\":\"Pharmacogenomics Journal\",\"volume\":\"22 5-6\",\"pages\":\"284-293\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2022-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9674520/pdf/\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pharmacogenomics Journal\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.nature.com/articles/s41397-022-00288-2\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GENETICS & HEREDITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pharmacogenomics Journal","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s41397-022-00288-2","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GENETICS & HEREDITY","Score":null,"Total":0}
The genetic landscape of major drug metabolizing cytochrome P450 genes—an updated analysis of population-scale sequencing data
Genes encoding cytochrome P450 enzymes (CYPs) are extremely polymorphic and multiple CYP variants constitute clinically relevant biomarkers for the guidance of drug selection and dosing. We previously reported the distribution of the most relevant CYP alleles using population-scale sequencing data. Here, we update these findings by making use of the increasing wealth of data, incorporating whole exome and whole genome sequencing data from 141,614 unrelated individuals across 12 human populations. We furthermore extend our previous studies by systematically considering also uncharacterized rare alleles and reveal that they contribute between 1.5% and 17.5% to the overall genetically encoded functional variability. By using established guidelines, we aggregate and translate the available sequencing data into population-specific patterns of metabolizer phenotypes. Combined, the presented data refine the worldwide landscape of ethnogeographic variability in CYP genes and aspire to provide a relevant resource for the optimization of population-specific genotyping strategies and precision public health.
期刊介绍:
The Pharmacogenomics Journal is a print and electronic journal, which is dedicated to the rapid publication of original research on pharmacogenomics and its clinical applications.
Key areas of coverage include:
Personalized medicine
Effects of genetic variability on drug toxicity and efficacy
Identification and functional characterization of polymorphisms relevant to drug action
Pharmacodynamic and pharmacokinetic variations and drug efficacy
Integration of new developments in the genome project and proteomics into clinical medicine, pharmacology, and therapeutics
Clinical applications of genomic science
Identification of novel genomic targets for drug development
Potential benefits of pharmacogenomics.