Yvonne S Gloor, Médéric Mouterde, Jean Terrier, Camille Lenoir, Pauline Gosselin, Victoria Rollason, Jean-Luc Reny, Sotiria Boukouvala, Said Al-Yahyaee, Getnet Yimer, Viktor Černý, Estella S Poloni, Caroline F Samer, Youssef Daali
{"title":"使用日内瓦鸡尾酒进行细胞色素 P450 表型分析可提高住院病人的代谢能力预测。","authors":"Yvonne S Gloor, Médéric Mouterde, Jean Terrier, Camille Lenoir, Pauline Gosselin, Victoria Rollason, Jean-Luc Reny, Sotiria Boukouvala, Said Al-Yahyaee, Getnet Yimer, Viktor Černý, Estella S Poloni, Caroline F Samer, Youssef Daali","doi":"10.1111/bcp.16368","DOIUrl":null,"url":null,"abstract":"<p><strong>Aims: </strong>Liver cytochromes (CYPs) play an important role in drug metabolism but display a large interindividual variability resulting both from genetic and environmental factors. Most drug dose adjustment guidelines are based on genetics performed in healthy volunteers. However, hospitalized patients are not only more likely to be the target of new prescriptions and drug treatment modifications than healthy volunteers, but will also be more subject to polypharmacy, drug-drug interactions, or to suffer from disease or inflammation affecting CYP activities.</p><p><strong>Methods: </strong>We compared predicted phenotype based on genetic data and measured phenotype using the Geneva cocktail to determine the extent of drug metabolizing enzyme variability in a large population of hospitalized patients (>500) and healthy young volunteers (>300). We aimed to assess the correlation between predicted and measured phenotype in the two populations.</p><p><strong>Results: </strong>We found that, even in cases where the genetically predicted metabolizer group correlates well with measured CYP activity at group level, this prediction lacks accuracy for the determination of individual metabolizer capacities. Drugs can have a profound impact on CYP activity, but even after combining genetic and drug treatment information, the activity of a significant proportion of extreme metabolizers could not be explained.</p><p><strong>Conclusions: </strong>Our results support the use of measured metabolic ratios in addition to genotyping for accurate determination of individual metabolic capacities to guide personalized drug prescription.</p>","PeriodicalId":9251,"journal":{"name":"British journal of clinical pharmacology","volume":" ","pages":""},"PeriodicalIF":3.1000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cytochrome P450 phenotyping using the Geneva cocktail improves metabolic capacity prediction in a hospitalized patient population.\",\"authors\":\"Yvonne S Gloor, Médéric Mouterde, Jean Terrier, Camille Lenoir, Pauline Gosselin, Victoria Rollason, Jean-Luc Reny, Sotiria Boukouvala, Said Al-Yahyaee, Getnet Yimer, Viktor Černý, Estella S Poloni, Caroline F Samer, Youssef Daali\",\"doi\":\"10.1111/bcp.16368\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Aims: </strong>Liver cytochromes (CYPs) play an important role in drug metabolism but display a large interindividual variability resulting both from genetic and environmental factors. Most drug dose adjustment guidelines are based on genetics performed in healthy volunteers. However, hospitalized patients are not only more likely to be the target of new prescriptions and drug treatment modifications than healthy volunteers, but will also be more subject to polypharmacy, drug-drug interactions, or to suffer from disease or inflammation affecting CYP activities.</p><p><strong>Methods: </strong>We compared predicted phenotype based on genetic data and measured phenotype using the Geneva cocktail to determine the extent of drug metabolizing enzyme variability in a large population of hospitalized patients (>500) and healthy young volunteers (>300). We aimed to assess the correlation between predicted and measured phenotype in the two populations.</p><p><strong>Results: </strong>We found that, even in cases where the genetically predicted metabolizer group correlates well with measured CYP activity at group level, this prediction lacks accuracy for the determination of individual metabolizer capacities. Drugs can have a profound impact on CYP activity, but even after combining genetic and drug treatment information, the activity of a significant proportion of extreme metabolizers could not be explained.</p><p><strong>Conclusions: </strong>Our results support the use of measured metabolic ratios in addition to genotyping for accurate determination of individual metabolic capacities to guide personalized drug prescription.</p>\",\"PeriodicalId\":9251,\"journal\":{\"name\":\"British journal of clinical pharmacology\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-12-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"British journal of clinical pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1111/bcp.16368\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"British journal of clinical pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1111/bcp.16368","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Cytochrome P450 phenotyping using the Geneva cocktail improves metabolic capacity prediction in a hospitalized patient population.
Aims: Liver cytochromes (CYPs) play an important role in drug metabolism but display a large interindividual variability resulting both from genetic and environmental factors. Most drug dose adjustment guidelines are based on genetics performed in healthy volunteers. However, hospitalized patients are not only more likely to be the target of new prescriptions and drug treatment modifications than healthy volunteers, but will also be more subject to polypharmacy, drug-drug interactions, or to suffer from disease or inflammation affecting CYP activities.
Methods: We compared predicted phenotype based on genetic data and measured phenotype using the Geneva cocktail to determine the extent of drug metabolizing enzyme variability in a large population of hospitalized patients (>500) and healthy young volunteers (>300). We aimed to assess the correlation between predicted and measured phenotype in the two populations.
Results: We found that, even in cases where the genetically predicted metabolizer group correlates well with measured CYP activity at group level, this prediction lacks accuracy for the determination of individual metabolizer capacities. Drugs can have a profound impact on CYP activity, but even after combining genetic and drug treatment information, the activity of a significant proportion of extreme metabolizers could not be explained.
Conclusions: Our results support the use of measured metabolic ratios in addition to genotyping for accurate determination of individual metabolic capacities to guide personalized drug prescription.
期刊介绍:
Published on behalf of the British Pharmacological Society, the British Journal of Clinical Pharmacology features papers and reports on all aspects of drug action in humans: review articles, mini review articles, original papers, commentaries, editorials and letters. The Journal enjoys a wide readership, bridging the gap between the medical profession, clinical research and the pharmaceutical industry. It also publishes research on new methods, new drugs and new approaches to treatment. The Journal is recognised as one of the leading publications in its field. It is online only, publishes open access research through its OnlineOpen programme and is published monthly.