Pharmacogenetics-guided dose modifications of antidepressants

Pharmacist assessment of drug-gene interactions and drug-induced phenoconversion in major depressive disorder: a case report

BACKGROUND

Response to antidepressant therapy is highly variable among individuals. Pharmacogenomic (PGx) testing presents an opportunity to guide drug selection while optimizing therapy outcomes and/or decreasing the risk for toxicity.

CASE PRESENTATION

A patient with multiple comorbidities, including severe major depressive disorder (MDD), experienced adverse drug events and undesirable response to multiple antidepressant medications (i.e., bupropion, escitalopram, and venlafaxine). A clinical pharmacist assessed significant drug-gene, drug-drug, and drug-drug-gene interactions as well as other clinical factors to provide recommendations for antidepressant therapy optimization.

CONCLUSION

This case highlights the importance of PGx testing and the key role of pharmacists in identifying and mitigating drug-related problems and optimizing drug therapy in patients with MDD.

Protocol for a pharmacogenetic study of antidepressants: characterization of drug-metabolizing profiles of cytochromes CYP2D6 and CYP2C19 in a Sardinian population of patients with major depressive disorder

The effectiveness of antidepressants shows high interindividual variability ranging from full symptomatologic remission to treatment-resistant depression. Many factors can determine the variation in the clinical response, but a fundamental role is played by genetic variation within the genes encoding for the enzymes most involved in the metabolism of antidepressant drugs: the CYP2D6 and CYP2C19 isoforms of the cytochrome P450 system. This study is poised to clarify whether the different metabolizing phenotypes related to CYP2D6 and CYP2C19 could have an impact on the clinical efficacy of antidepressants and whether the frequency of these phenotypes of metabolization shows differences in the population of Sardinian patients compared to other Caucasian populations. The sample is being recruited from patients followed-up and treated at the Psychiatric Unit of the Department of Medical Science and Public Health, University of Cagliari and the University Hospital Agency of Cagliari (Italy). The study design includes three approaches: (1) a pharmacogenetic analysis of 80 patients diagnosed with MDD resistant to antidepressant treatment compared to 80 clinically responsive or remitted patients; (2) a prospective arm (N = 30) of the study where we will test the impact of genetic variation within the CYP2D6 and CYP2C19 genes on clinical response to antidepressants and on their serum levels and (3) the assessment of the socio-economic impact of antidepressant therapies, and estimation of the cost-effectiveness of the pharmacogenetic test based on CYP genes.

Pharmacogenetic Testing of Cytochrome P450 Drug Metabolizing Enzymes in a Case Series of Patients with Prader-Willi Syndrome

Prader-Willi syndrome (PWS) is associated with co-morbid psychiatric symptoms (disruptive behavior, anxiety, mood disorders, and psychosis) often requiring psychotropic medications. In this clinical case series of 35 patients with PWS, pharmacogenetic testing was obtained to determine allele frequencies predicting variations in activity of cytochrome (CYP) P450 drug metabolizing enzymes 2D6, 2B6, 2C19, 2C9, 3A4, and 1A2. Results were deidentified, collated, and analyzed by PWS genetic subtype: 14 deletion (DEL), 16 maternal uniparental disomy (UPD) and 5 DNA-methylation positive unspecified molecular subtype (PWS Unspec). Literature review informed comparative population frequencies of CYP polymorphisms, phenotypes, and substrate specificity. Among the total PWS cohort, extensive metabolizer (EM) activity prevailed across all cytochromes except CYP1A2, which showed greater ultra-rapid metabolizer (UM) status (p < 0.05), especially among UPD. Among PWS genetic subtypes, there were statistically significant differences in metabolizing status for cytochromes 2D6, 2C19, 2C9, 3A4 and 1A2 acting on substrates such as fluoxetine, risperidone, sertraline, modafinil, aripiprazole, citalopram, and escitalopram. Gonadal steroid therapy may further impact metabolism of 2C19, 2C9, 3A4 and 1A2 substrates. The status of growth hormone treatment may affect CYP3A4 activity with gender specificity. Pharmacogenetic testing together with PWS genetic subtyping may inform psychotropic medication dosing parameters and risk for adverse events.

Treatment Adequacy and Adherence as Predictors of Depression Response in Primary Care

OBJECTIVE

Primary care is the de facto mental health system in the United States where physicians treat large numbers of depressed older adults with antidepressant medication. This study aimed to examine whether antidepressant dosage adequacy and patient adherence are associated with depression response among middle-aged and older adults prescribed with antidepressants by their primary care provider.

DESIGN

A secondary analysis was conducted on a sample drawn from a randomized controlled trial comparing Treatment as Usual to Treatment Initiation Program, an adherence intervention. Treatment Initiation Program improved adherence but not depression compared to Treatment as Usual (Sirey et al., 2017). For this analysis, we examined dosing adequacy and adherence at 6 and 12 weeks as predictors of depression response in both groups at 12 and 24 weeks.

SETTING

Primary care practices.

PARTICIPANTS

One hundred eighty-seven older adults with depression prescribed an antidepressant for depression by their primary care provider.

MEASUREMENTS

Depression response was defined as 50% reduction on the Hamilton Rating Scale for Depression. Adherence was defined as taking 80% of doses at follow-up interviews (6 and 12 weeks). Patient-reported dosage and duration of antidepressant therapy was collected using the Composite Antidepressant Score (adequacy score of >3) at follow-up.

RESULTS

Greater adherence, but not receipt of adequate dosage, was associated with higher likelihood of treatment response at both 12 (Odds ratio (OR) = 2.63; 95% Confidence Interval (CI), 1.19-5.84) and 24 weeks (OR = 3.09; 95% CI, 1.46-6.55).

CONCLUSION

As physicians prescribe antidepressants to the diverse group of adults seen in primary care, special attention to patients' views and approach to adherence may improve depression outcomes.

Pharmacogenomic Testing in Psychiatry: Ready for Primetime?

Pharmacogenomic testing in clinical psychiatry has grown at an accelerated pace in the last few years and is poised to grow even further. Despite robust evidence lacking regarding efficacy in clinical use, there continues to be growing interest to use it to make treatment decisions. We intend this article to be a primer for a clinician wishing to understand the biological bases, evidence for benefits, and pitfalls in clinical decision-making. Using clinical vignettes, we elucidate these headings in addition to providing a perspective on current relevance, what can be communicated to patients, and future research directions. Overall, the evidence for pharmacogenomic testing in psychiatry demonstrates strong analytical validity, modest clinical validity, and virtually no evidence to support clinical use. There is definitely a need for more double-blinded randomized controlled trials to assess the use of pharmacogenomic testing in clinical decision-making and care, and until this is done, they could perhaps have an adjunct role in clinical decision-making but minimal use in leading the initial treatment plan.

Drug-Drug Interactions in Prostate Cancer Treatment

Polypharmacy is associated with an increased risk of drug-drug interactions (DDIs), which can cause serious and debilitating drug-induced adverse events. With a steadily aging population and associated increasing multimorbidity and polypharmacy, the potential for DDIs becomes considerably important. Prostate cancer (PCa) is the most common cancer in men and occurs mostly in elderly men in the Western world. Therefore, the aim of this review is to give an overview of DDIs in PCa therapy to better understand pharmacodynamic and pharm kinetic side effects as well as their interactions with other medications. Last, we explore potential future strategies, which might help to optimize treatment and reduce adverse events patients with polypharmacy and PCa.

Pharmacogenomics for personalized pain medicine

Pharmacogenomics aims to unravel the way that human genetic variation affects drug efficacy and toxicity. Genome-wide association studies and candidate gene findings suggest that genetic approaches may help choose the most appropriate drug and dosage while preventing adverse drug reactions (ADRs). Pain is an unpleasant feeling that usually results from tissue damage. The management of different types of pain (acute, chronic, inflammatory, neuropathic, or cancer) is challenging. Currently, drug intervention is the first-line therapy for resolving pain. However, differences in drug efficacy between individuals are common with pain medications. Moreover, some patients experience ADRs after being treated with specific pain drugs. This review discusses the use of drugs for pain management in the context of the recent pharmacogenomic studies on ADRs and drug efficacy.

The usefulness of genotyping cytochrome P450 enzymes in the treatment of depression

INTRODUCTION

Pharmacogenomics, which is derived from genome-wide association studies (GWAS), and pharmacogenetics, which involves candidate gene association studies (CGASs), are proving increasingly useful in personalized cancer care. Research in psychiatric applications has primarily involved genetic polymorphisms of P450 CYP enzymes, which mediate oxidative metabolism, particularly CYP2D6, which is involved in the metabolism of at least 30 psychotropic medications. This work has been supplemented by genotyping of proteins for the drug efflux pump P-glycoprotein (P-gp), serotonin receptors, and the serotonin reuptake pump.

AREAS COVERED

This review covers principles of pharmacogenetics and pharmacogenomics, previous analyses of pharmacokinetic and pharmacodynamics studies, newer studies of the predictive value of genetic testing in the treatment of depression, obstacles to implementation of genetic testing in predicting treatment response and side effects, and suggestions for future research.

EXPERT OPINION

Studies of multiple genes have produced some positive results in groups of patients, but genetic testing does not yet seem to be applicable to choosing medications for a specific patient.

Pharmacogenomics in early-phase clinical development

Pharmacogenomics (PGx) offers the promise of utilizing genetic fingerprints to predict individual responses to drugs in terms of safety, efficacy and pharmacokinetics. Early-phase clinical trial PGx applications can identify human genome variations that are meaningful to study design, selection of participants, allocation of resources and clinical research ethics. Results can inform later-phase study design and pipeline developmental decisions. Nevertheless, our review of the clinicaltrials.gov database demonstrates that PGx is rarely used by drug developers. Of the total 323 trials that included PGx as an outcome, 80% have been conducted by academic institutions after initial regulatory approval. Barriers for the application of PGx are discussed. We propose a framework for the role of PGx in early-phase drug development and recommend PGx be universally considered in study design, result interpretation and hypothesis generation for later-phase studies, but PGx results from underpowered studies should not be used by themselves to terminate drug-development programs.

Polymorphic cytochrome P450 enzymes (CYPs) and their role in personalized therapy

The cytochrome P450 (CYP) enzymes are major players in drug metabolism. More than 2,000 mutations have been described, and certain single nucleotide polymorphisms (SNPs) have been shown to have a large impact on CYP activity. Therefore, CYPs play an important role in inter-individual drug response and their genetic variability should be factored into personalized medicine. To identify the most relevant polymorphisms in human CYPs, a text mining approach was used. We investigated their frequencies in different ethnic groups, the number of drugs that are metabolized by each CYP, the impact of CYP SNPs, as well as CYP expression patterns in different tissues. The most important polymorphic CYPs were found to be 1A2, 2D6, 2C9 and 2C19. Thirty-four common allele variants in Caucasians led to altered enzyme activity. To compare the relevant Caucasian SNPs with those of other ethnicities a search in 1,000 individual genomes was undertaken. We found 199 non-synonymous SNPs with frequencies over one percent in the 1,000 genomes, many of them not described so far. With knowledge of frequent mutations and their impact on CYP activities, it may be possible to predict patient response to certain drugs, as well as adverse side effects. With improved availability of genotyping, our data may provide a resource for an understanding of the effects of specific SNPs in CYPs, enabling the selection of a more personalized treatment regimen.

Consistency of drug-drug and gene-drug interaction information in US FDA-approved drug labels

AIM

To characterize concordance between clinically relevant drug-drug interactions (DDIs) related to CYP2C19, CYP2D6 and CYP2C9 and their analogous gene-drug interactions (GDIs) in US FDA-approved drug labeling.

METHODS

We selected prototypical CYP2C19, CYP2D6 and CYP2C9 inhibitors and abstracted all respective interacting drugs via a tertiary resource used in the clinical setting. We then selected only CYP2C19, CYP2D6 and CYP2C9 metabolism-related DDIs requiring enhanced clinical monitoring, dose adjustment or use of alternative drugs. Labeling and management strategies on DDIs and GDIs were compared.

RESULTS

Among the drug labels with DDI information, 73% of them describe the analogous GDI. Of the 65 drug labels, 43 and 17% had specific management recommendations for DDIs and GDIs, respectively. In general, GDI management recommendations were concordant with DDI management recommendations in terms of specific dose adjustments or use of alternative drugs.

CONCLUSION

The FDA has recognized genetic differences in drug metabolism where clinically relevant DDIs trigger dose adjustment or use of alternative drugs.

Importance of pharmacogenetics in the treatment of children with attention deficit hyperactive disorder: a case report

This case report highlights the importance of pharmacogenetic testing in the treatment of attention deficit hyperactive disorder (ADHD). A 6-year-old boy diagnosed with ADHD was prescribed methylphenidate 5 mg twice daily (7 am and noon) and the family was compliant with administration of this medication. On the first day of treatment, the patient had an adverse reaction, becoming disobedient, more mischievous, erratic, resistant to discipline, would not go to sleep until midnight, and had a poor appetite. The All-In-One PGX (All-In-One Pharmacogenetics for Antipsychotics test for CYP2D6, CYP2C19, and CYP2C9) was performed using microarray-based and real-time polymerase chain reaction techniques. The genotype of our patient was identified to be CYP2D6*2/*10, with isoforms of the enzyme consistent with a predicted cytochrome P450 2D6 intermediate metabolizer phenotype. Consequently, the physician adjusted the methylphenidate dose to 2.5 mg once daily in the morning. At this dosage, the patient had a good response without any further adverse reactions. Pharmacogenetic testing should be included in the management plan for ADHD. In this case, cooperation between the medical team and the patients’ relatives was key to successful treatment.

Personalized medicine in major depressive disorder -- opportunities and pitfalls

The sequencing of the human genome in the early days of this millennium was greeted with great fanfare as this accomplishment was expected to revolutionize medicine and result in individualized treatments based on the genetic make-up of the patient. The ultimate promise of personalized medicine would be fulfilled with the identification of disease biomarkers that would be widely available for use in diagnosis and treatment. Progress, however, has been slow in providing disease biomarkers or approved diagnostic tests. This is true for major depressive disorder (MDD), despite its prevalence in the general population and the widespread acceptance of its biological basis. Studies using strategies like genome-wide association and candidate gene analyses have identified a number of possible biomarkers of MDD, including serum levels of neurotrophic factors, inflammatory cytokines and HPA axis hormones, but none have proven sufficiently powerful for clinical use. The lack of biologically based tests available for use in identifying patients with MDD is a significant impediment to personalized and more effective treatment, because it means diagnosis continues to be driven by subjective symptoms. While genetic studies of MDD have not yet led to diagnostic and treatment biomarkers, progress in determining the role of the genome in drug metabolism heralds the first effort in personalized prescribing for the antidepressants. The FDA suggested and approved genotyping tests for common variants of drug metabolism genes, such as the cytochrome p450s. By using these tests a physician can select an appropriate antidepressant for a given patient, as differences in clearance, half-life, and peak blood concentrations are controlled by genetic variability in drug metabolism. Personalization in drug choice can be achieved because these tests: (1) identify responders and non-responders; (2) provide alerts to possible adverse drug events; and (3) help optimize dose. Improved ways of diagnosing and prescribing effective treatments for MDD are needed, as the available methods are inadequate and symptom based. In the foreseeable future, further interrogation of the genome may serve as the basis for development of new personalized medicine strategies for diagnosis and treatment of MDD.

Imaging genetics: implications for research on variable antidepressant drug response

Genetic variation of SLC6A4, HTR1A, MAOA, COMT and BDNF has been associated with depression, variable antidepressant drug responses as well as impacts on brain regions of emotion processing that are modulated by antidepressants. Pharmacogenetic studies are using psychometric outcome measures of drug response and are hampered by small effect sizes that might be overcome by the use of intermediate endophenotypes of drug response, which are suggested by imaging studies. Such an approach will not only tighten the relationship between genes and drug response, but also yield new insights into the neurobiology of depression and individual drug responses. This article provides a comprehensive overview of pharmacogenetic, imaging genetics and drug response studies, utilizing imaging techniques within the context of antidepressive drug therapy.

Effect of cytochrome P450 enzyme polymorphisms on pharmacokinetics of venlafaxine

This study examines the relationship between blood concentrations of venlafaxine and its active metabolite, O-desmethyl venlafaxine (ODV), and genetic variants of the cytochrome P450 enzymes CYP2D6 and CYP2C19 in human subjects. Trough blood concentrations were measured at steady state in patients treated with venlafaxine extended release in a clinical practice setting. CYP2D6 and CYP2C19 genotypes were converted to activity scores based on known activity levels of the two alleles comprising a genotype. After adjusting for drug dose and gender effects, higher CYP2D6 and CYP2C19 activity scores were significantly associated with lower venlafaxine concentrations (P < 0.001 for each). Only CYP2D6 was associated with the concentration of ODV (P < 0.001), in which genotypes with more active alleles were associated with higher ODV concentrations. The sum of venlafaxine plus ODV concentration showed the same pattern as venlafaxine concentrations with CYP2D6 and CYP2C19 genotypes with higher activity scores being associated with a lower venlafaxine plus ODV concentration (2D6 P = 0.01; 2C19 P < 0.001). Because allelic variants in both CYP2D6 and CYP2C19 influence the total concentration of the active compounds venlafaxine and ODV, both CYP2D6 and CYP2C19 genotypes should be considered when using pharmacogenomic information for venlafaxine dose alterations.

Genome-wide association studies in pharmacogenomics

Genome-wide association (GWA) studies for pharmacogenomics-related traits are increasingly being performed to identify loci that affect either drug response or susceptibility to adverse drug reactions. Until now, only the largest effects have been detected, partly because of the challenges of obtaining large numbers of cases for pharmacogenomic studies. Since 2007, a range of pharmacogenomics GWA studies have been published that have identified several interesting and novel associations between drug responses or reactions and clinically relevant loci, showing the value of this approach.

Drug-drug interactions that reduce the formation of pharmacologically active metabolites: a poorly understood problem in clinical practice

Drug-drug interactions can lead to reduced efficacy of medical treatment. Therapeutic failure may for instance result from combined treatment with an inhibitor of the specific pathway that is responsible for the generation of pharmacologically active drug metabolites. This problem may be overlooked in clinical practice. Several examples of drugs will be discussed -clopidogrel, losartan, tamoxifen and codeine - to illustrate differences in the potential impact on drug treatment in clinical practice. We conclude that the combined use of cytochrome P450-blocking serotonin reuptake inhibitors and tamoxifen or codeine should be avoided, whereas the situation is much more complex regarding the use of proton pump inhibitors together with clopidogrel, and the evidence regarding cytochrome P450 inhibitor-dependent activation of losartan is inconclusive.

A generalist's guide to treating patients with depression with an emphasis on using side effects to tailor antidepressant therapy

This review provides a guide to the primary care physician for diagnosing and managing depression. To identify relevant articles, a PubMed search (ending date parameter, October 15, 2009) was conducted using the keywords depression, antidepressants, side effects, adverse effects, weight gain, sexual dysfunction, and sleep disturbance, and the reference lists of relevant articles were hand searched. This review explores the challenges in diagnosing depression that will and will not respond to antidepressants (ADs) and describes the value of 2-question screening instruments followed by in-depth questioning for positive screening results. It underscores the implications of veiled somatic presentations in which underlying depression is missed, leading to fruitless and expensive medical work-ups. Following this survey of the difficulties in diagnosing depression, the 4 options generalists have for treating a patient with depression are discussed: watchful waiting, antidepressant therapy, psychotherapy, and psychiatric referral. This review proposes that physicians, once they decide to prescribe, use AD side effects to advantage by selecting medications to minimize negative and maximize positive possibilities, thereby improving adherence. It focuses on the 3 most troubling adverse effects-sleep disturbance, sexual dysfunction, and weight gain. It provides AD-prescribing principles to assist primary care physicians in successfully managing depression and appropriately referring patients to a psychiatrist. Antidepressant therapy is not a panacea for treating patients with depression. An approach blending enlightened observation, medications, and psychotherapy often helps depressed patients recover to their former baselines.

Understanding Personalized Medicine in Rheumatoid Arthritis: A Clinician's Guide to the Future

Personalized medicine refers to the utilization of technologies at the molecular level to understand disease processes and improve health outcomes. In rheumatoid arthritis (RA) some factors associated with disease outcome have been identified. These factors have not yet been integrated into a clinically useful tool to predict disease outcome in individual patients. Developments in pharmacogenomics are moving the field forward quite rapidly. Genetic variants, which may have a role in drug metabolism mediating either drug response or toxicity, have been identified for both traditional disease modifying antirheumatic drugs and biologic agents. Choosing a medication based on a patient's characteristics (sociodemographic, clinical, genetic) will result in better utilization of resources and better clinical outcomes. The ethical, political, and legal implications of personalized medicine need to be considered as well.