Genotyping of CYP2C19, the enzyme that metabolizes the antidepressant escitalopram (Lexapro, Forest Laboratories), can inform therapeutic responsiveness to the drug and assist in personalizing antidepressant therapy, new research shows.
Swedish investigators analyzed escitalopram serum concentrations from 2087 patients who had undergone genotyping for the CYP2C19 gene. They compared genotypes associated with either rapid or poor metabolism of CYP2C19 to a reference group of individuals who metabolized escitalopram normally.
They found that escitalopram concentrations were significantly decreased in the subgroup of rapid metabolizers and were significantly increased in the subgroups of poor metabolizers, compared to the reference group.
In comparison with the reference group, a higher percentage of patients in the ultrarapid and poor metabolizer subgroups switched from escitalopram to another antidepressant within 1 year, suggesting higher rates of medication failure among those who switched.
“Escitalopram is currently the most used antidepressant, and, indeed, because of the millions of patients treated worldwide, our data very nicely illustrate the benefit of individualized drug therapy,” said Magus Ingelman-Sundberg, PhD, BScMed, professor and head, Section of Pharmacogenetics, Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden, who led the study together with Prof Espen Molden.
“This will save money and increase overall effect of the therapy,” he told Medscape Medical News.
The study was published online January 12 in the American Journal of Psychiatry.
Clinical Relevance Unclear
High interindividual variation in escitalopram metabolism can lead either to very high or very low serum levels, potentially increasing the incidence of side effects or leading to insufficient therapeutic levels. Both scenarios can result in therapeutic failure, the authors write.
The hepatic cytochrome P450 (CYP) enzyme CYP2C19 is responsible for the initial biotransformation of escitalopram, and the “highly polymorphic” CYP2C19 gene and its genotypes determine the enzymatic capacity of CYP2C19.
Previous studies that explored the effect of CYP2C19 on escitalopram exposure and treatment success “produced conflicting findings and failed to determine reliably whether CYP2C19 is a clinically relevant feature in escitalopram.” Problems in those studies included small sample size, flexible-dosing protocols, and insufficient monitoring of escitalopram concentrations.
To investigate the contribution of CYP2C19 polymorphism to escitalopram exposure, the researchers studied 2087 CYP2C19-genotyped, escitalopram-treated patients drawn from a therapeutic drug-monitoring database.
They also investigated the extent to which patients with different CYP2C19 genotypes were prone to switching from escitalopram to other antidepressants, which the investigators regarded as suggesting therapeutic failure.
Patients were divided into categories on the basis of their CYP2C19 genotype-defined capacity to metabolize escitalopram. Those lacking a functional CYP2C19 allele (CYP2C19Null/Null) were categorized as poor metabolizers.
Intermediate metabolizers (CYP2C1*1/Null and CYP2C19*17/Null) carried one loss-of-function allele. This category also included the CYP2C19Null/*17 genotype “because the CYP2C19Null allele has a much greater impact on phenotype than the gain-of-function CYP2C19*17 allele,” the authors explain.
Normal metabolizers who were homozygous for the wild-type CYP2C19*1 allele were referred to as “extensive” metabolizers (CYP2C19*1/*1) and represented the reference genotype.
Those carrying CYP2C19*1/*17 or CYP2C19*17/*17 were regarded as ultrarapid metabolizers.
The researchers compared steady-state serum concentrations of escitalopram between the subgroups. Concentrations were normalized to the standard 10-mg/day dosage prior to the statistical analysis.
The effect of CYP2C19 genotype on escitalopram concentration was estimated using a multivariate mixed-model analysis, with age and sampling time as covariates, in order to account for the variable number of measurements per patient.
Therapeutic Failure in Outliers
The serum concentration of escitalopram differed between the CYP2C19 genotype-defined subgroups. Mean estimates for escitalopram serum concentration were significantly greater among the poor and intermediate metabolizers, compared with the extensive metabolizers (3.3 times greater for the poor metabolizers, and 1.6 times (Null/*1) and 1.4 times (Null/*17) greater for the intermediate metabolizers (P < .001).
Mean escitalopram serum concentrations were significantly lower among the ultrarapid metabolizers, by approximately 10% in those carrying CYP2C19*1/*17 (P < .003) and 20% in those carrying CYP2C19*17/*17 (P < .002), compared with the extensive metabolizers.
Age and sampling time were found to be “significant nongenetic covariates in explaining individual variability in escitalopram serum concentration,” the authors report.
In patients younger than 50 years, the concentration remained fairly constant. A “pronounced increase” was observed in patients older than 65 years.
The proportion of patients with subtherapeutic serum escitalopram levels increased with CYP2C19 metabolic capacity.
Compared with the reference group (ie, patients homozygous for CYP2C19*1), which comprised 20.1% of patients with subtherapeutic levels, the proportion of patients with escitalopram serum concentrations <25 nM was significantly lower among the poor and intermediate metabolizers and was significantly higher among the ultrarapid metabolizers (P < .001 and P < .003, respectively).
Compared with the extensive metabolizers, the odds ratio estimates for the incidence of concentrations <25 nM were 0.20 (CYP2C19Null/*1) and 0.44 (CYP2C19Null/*17) for the intermediate metabolizer subgroups and 1.5 (CYP2C19*1/*17) and 1.7 (CYP2C19*17/*17) for the ultrarapid metabolizers.
The researchers extended their analysis by comparing the subgroups regarding patients who switched from escitalopram to another antidepressant within 1 year after the last therapeutic drug monitoring analysis of escitalopram.
The 1-year switch frequency was 11.8% in the extensive metabolizer reference group. By contrast, the rate at which the poor as well as the ultrarapid metabolizers switched from escitalopram to another antidepressant was significantly higher (odds ratios: 3.3 [P < .001] for the poor metabolizers, 1.6 [P = .003] for the CYP2C19*1/*17 subgroup, and 3.0 [P < 0.001] for the CYP2C19*17/*17 subgroup).
“Interestingly, the fraction of patients who switched to another antidepressant within 1 year formed a U-shaped curve, with higher rates of drug switch among the patients with the lowest and highest metabolic capacity,” the authors comment.
“In patients lacking active CYP2C19 enzyme, an initial escitalopram dose of 10 mg is functionally equal to about 40 mg because of the lack of metabolism,” said Dr Ingelman-Sundberg.
“Many patients starting with escitalopram treatment suffer from increased anxiety the first weeks of treatment, and it is likely that with this very high dose, they switched medicines because of these adverse effects by the far-too-high level of the drug,” he said.
By contrast, “patients carrying gain-of-function allele simply do not reach therapeutically relevant concentrations and therefore switch medicine because of lack of effect.”
He acknowledged being “surprised” by the study findings. In particular, he was surprised “that so high a fraction of patients in total, most carrying the gain of function CYP2C19*17 allele, did not achieve pharmacologically active escitalopram levels under standard treatment.”
Additionally, he was surprised “by the high — threefold — increase of drug switching in CYP2C19 genotype outlier groups, the poor metabolizers and the ultrarapid metabolizers.”
Preemptive Testing?
Commenting on the study for Medscape Medical News, Daniel J. Mueller, MD, PhD, head, Pharmacogenetics Research Clinic, Center for Addiction and Mental Health, Toronto, Ontario, Canada, said that the study “shows, in a much larger number and in a convincing way, what other studies have shown, which is that altered metabolism of the CYP2C19 gene affects treatment response to escitalopram.”
He noted that in this study population, impaired metabolizers were considered outliers, whereas in other populations, impaired metabolism is more common.
“Approximately 30% of South Asians have impaired metabolism,” he observed.
The study “is arguing that if patients would do genetic tests up front, their physicians could potentially identify those less likely to respond, because escitalopram is so highly dependent on CYP2C19 functioning,” he said.
He pointed out that the findings of the study would suggest that every psychiatrist should have all patients undergo genetic testing before being prescribed antidepressants.
“However, although the paper implies that information about the genotype should be used to determine treatment if it is available, it should not be assumed that everyone will be aware of this relationship, nor will everyone know where to get the test and, ultimately, who will pay for it,” he pointed out.
Studies such as these should therefore motivate further investigation of the cost-benefit analysis of conducting widespread genetic testing to inform medication decisions, he said.
Nevertheless, Dr Ingelman-Sundberg said the take-home message of the study is that clinicians should “investigate the CYP2C19 genotype of their patients before prescribing escitalopram and some other SSRIs [selective serotonin reuptake inhibitors] and make dose adjustment for more successful therapy.”
The study was supported by grants from the Swedish Research Council, the European Union’s Horizon 2020 research and innovation program, the Swedish Brain Foundation, and the South-Eastern Norway Regional Health Authority. Dr Molden has received honoraria from Lundbeck for teaching psychopharmacology to physicians. The other study authors and Dr Mueller have disclosed no relevant financial relationships.
Am J Psychiatry. Published online January 12, 2018. Abstract
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