Erik Joas, Lina Jonsson, Alexander Viktorin, Erik Smedler, Erik Pålsson, Guy M. Goodwin, Mikael Landén
{"title":"CYP2C19 多态性对双相情感障碍患者抗抑郁药处方模式和治疗后出现的躁狂症的影响","authors":"Erik Joas, Lina Jonsson, Alexander Viktorin, Erik Smedler, Erik Pålsson, Guy M. Goodwin, Mikael Landén","doi":"10.1038/s41397-022-00294-4","DOIUrl":null,"url":null,"abstract":"Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005–2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04–1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05–2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.","PeriodicalId":54624,"journal":{"name":"Pharmacogenomics Journal","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2022-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9925376/pdf/","citationCount":"0","resultStr":"{\"title\":\"Effect of CYP2C19 polymorphisms on antidepressant prescription patterns and treatment emergent mania in bipolar disorder\",\"authors\":\"Erik Joas, Lina Jonsson, Alexander Viktorin, Erik Smedler, Erik Pålsson, Guy M. 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We used Swedish national registry data 2005–2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04–1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05–2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. 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Effect of CYP2C19 polymorphisms on antidepressant prescription patterns and treatment emergent mania in bipolar disorder
Antidepressant medication is used extensively to treat bipolar depression despite uncertain efficacy. The cytochrome P450 (CYP) 2C19 enzyme metabolize several antidepressants, and polymorphisms in the corresponding gene CYP2C19 influence plasma concentration and hence treatment outcomes in major depressive disorder. Here, we investigate if CYP2C19 polymorphisms are associated with antidepressant treatment patterns and the risk of mania when antidepressants are used in bipolar disorder. Two single nucleotide polymorphisms (rs4244285 and rs12248560) were used to classify 5019 bipolar disorder patients into CYP2C19 metabolic phenotypes ranging from poor to ultra-rapid metabolizers. We used Swedish national registry data 2005–2017 on dispensed medications and inpatient care to estimate risks for early-treatment persistence, treatment discontinuation, switching to a new antidepressant medication, and mania within 3 months of treatment initiation in patients treated with citalopram, escitalopram, sertraline, amitriptyline, and clomipramine. Metabolic phenotypes of CYP2C19 were not robustly associated with the investigated treatment outcomes based on dispense patterns. Slower metabolism was associated with an increased risk of treatment emergent mania for sertraline (hazard ratio [HR] = 1.3, 95% CI = 1.04–1.62, p = 0.02) and the tricyclic antidepressants amitriptyline and clomipramine (HR = 1.46, 95% CI = 1.05–2.02, p = 0.024). In a large study of the impact of CYP2C19 metabolic phenotypes on antidepressant treatment of bipolar depression, we found an association between slower CYP2C19 metabolism and higher risk of treatment emergent mania, which is a step towards personalized risk assessments. There were, however, no clear associations with early treatment persistence, treatment discontinuation, and switching to a new antidepressant.
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.