Influence of the CYP2D6*4 polymorphism on dose, switching and discontinuation of antidepressants

Association of CYP2D6 and CYP2C19 metabolizer status with switching and discontinuing antidepressant drugs: an exploratory study

BACKGROUND

Tailoring antidepressant drugs (AD) to patients' genetic drug-metabolism profile is promising. However, literature regarding associations of ADs' treatment effect and/or side effects with drug metabolizing genes CYP2D6 and CYP2C19 has yielded inconsistent results. Therefore, our aim was to longitudinally investigate associations between CYP2D6 (poor, intermediate, and normal) and CYP2C19 (poor, intermediate, normal, and ultrarapid) metabolizer-status, and switching/discontinuing of ADs. Next, we investigated whether the number of perceived side effects differed between metabolizer statuses.

METHODS

Data came from the multi-site naturalistic longitudinal cohort Netherlands Study of Depression and Anxiety (NESDA). We selected depression- and/or anxiety patients, who used AD at some point in the course of the 9 years follow-up period (n = 928). Medication use was followed to assess patterns of AD switching/discontinuation over time. CYP2D6 and CYP2C19 alleles were derived using genome-wide data of the NESDA samples and haplotype data from the PharmGKB database. Logistic regression analyses were conducted to investigate the association of metabolizer status with switching/discontinuing ADs. Mann-Whitney U-tests were conducted to compare the number of patient-perceived side effects between metabolizer statuses.

RESULTS

No significant associations were observed of CYP metabolizer status with switching/discontinuing ADs, nor with the number of perceived side effects.

CONCLUSIONS

We found no evidence for associations between CYP metabolizer statuses and switching/discontinuing AD, nor with side effects of ADs, suggesting that metabolizer status only plays a limited role in switching/discontinuing ADs. Additional studies with larger numbers of PM and UM patients are needed to further determine the potential added value of pharmacogenetics to guide pharmacotherapy.

Estimation of the benefit from pre-emptive genotyping based on the nationwide cohort data in South Korea

Genetic variants affect drug responses, making pre-emptive genotyping crucial for averting serious adverse events (SAEs) and treatment failure. However, assessing the benefits of pre-emptive genotyping based on genetic distribution, drug exposure, and demographics is challenging. This study aimed to estimate the population-level benefits of pre-emptive genotyping in the Korean population using nationwide cohort data. We reviewed actionable gene-drug combinations recommended by both the Clinical Pharmacogenomics Implementation Consortium (CPIC) and the Dutch Pharmacogenetics Working Group (DPWG) as of February 2022, identifying high-risk phenotypes. We collected reported risk reduction from genotyping and standardized it into population attributable risks. Healthcare reimbursement costs for SAEs and treatment failures were obtained from the Health Insurance Review and Assessment Service Statistics in 2021. The benefits of pre-emptive genotyping for a specific group were determined by multiplying drug exposure from nationwide cohort data by individual genotyping benefits. We identified 31 gene-drug-event pairs, with CYP2D6 and CYP2C19 demonstrating the greatest benefits for both male and female patients. Individuals aged 65-70 years had the highest individual benefit from pre-emptive genotyping, with $84.40 for men and $100.90 for women. Pre-emptive genotyping, particularly for CYP2D6 and CYP2C19, can provide substantial benefits.

Relative synonymous codon usage and codon pair analysis of depression associated genes

Depression negatively impacts mood, behavior, and mental and physical health. It is the third leading cause of suicides worldwide and leads to decreased quality of life. We examined 18 genes available at the genetic testing registry (GTR) from the National Center for Biotechnological Information to investigate molecular patterns present in depression-associated genes. Different genotypes and differential expression of the genes are responsible for ensuing depression. The present study, investigated codon pattern analysis, which might play imperative roles in modulating gene expression of depression-associated genes. Of the 18 genes, seven and two genes tended to up- and down-regulate, respectively, and, for the remaining genes, different genotypes, an outcome of SNPs were responsible alone or in combination with differential expression for different conditions associated with depression. Codon context analysis revealed the abundance of identical GTG-GTG and CTG-CTG pairs, and the rarity of methionine-initiated codon pairs. Information based on codon usage, preferred codons, rare, and codon context might be used in constructing a deliverable synthetic construct to correct the gene expression level of the human body, which is altered in the depressive state. Other molecular signatures also revealed the role of evolutionary forces in shaping codon usage.

Beyond the label: current evidence and future directions for the interrelationship between electronic cigarettes and mental health

Electronic cigarette use has dramatically increased over the last decade. With this recent technological development and wide range of constituents in various products, putative adverse effects on the brain and body have been largely unexplored. Here, we review current evidence linking electronic nicotine cigarette use with potential health consequences and provide evidence supporting an association between drug use and depression in humans. We also examine the biological effects of individual constituents in electronic cigarette aerosols, which include labeled ingredients, such as propylene glycol, vegetable glycerin, nicotine, and flavorants, as well as unlabeled ingredients found in the aerosols, such as carbonyls and heavy metals. Lastly, we examine the effects of electronic cigarette use on endogenous metabolism via changes in cytochrome P450 enzymes, which can thereby impact therapeutic outcomes. While the current evidence offers insight into the potential effects of electronic cigarette use on biological processes, further studies are necessary to determine the long-term clinical relevance of aerosol inhalation.

CYP2D6 pharmacogenetics and phenoconversion in personalized medicine

INTRODUCTION

CYP2D6 contributes to the metabolism of approximately 20-25% of drugs. However, CYP2D6 is highly polymorphic and different alleles can lead to impacts ranging from null to increase in activity. Moreover, there are commonly used drugs that potently inhibit the CYP2D6, thus causing 'phenoconversion' which can convert the genotypic normal metabolizer into phenotypic poor metabolizer. Despite growing literature on the clinical implications of non-normal CYP2D6 genotype and phenoconversion on patient-related outcomes, implementation of CYP2D6 pharmacogenetics and phenoconversion to guide prescribing is rare. This review focuses on providing the clinical importance of CYP2D6 pharmacogenetics and phenoconversion in precision medicine and summarizes the challenges and approaches to implement these into clinical practice.

AREAS COVERED

A literature search was performed using PubMed and clinical studies documenting the effects of CYP2D6 genotypes and/or CYP2D6 inhibitors on pharmacokinetics, pharmacodynamics or treatment outcomes of CYP2D6-metabolized drugs, and studies on implementation challenges and approaches.

EXPERT OPINION

Considering the extent and impact of genetic polymorphisms of CYP2D6, phenoconversion by the comedications, and contribution of CYP2D6 in drug metabolism, CYP2D6 pharmacogenetics is essential to ensure drug safety and efficacy. Utilization of proper guidelines incorporating both CYP2D6 pharmacogenetics and phenoconversion in clinical care assists in optimizing drug therapy.

Opioid-Related Genetic Polymorphisms of Cytochrome P450 Enzymes after Total Joint Arthroplasty: A Focus on Drug-Drug-Gene Interaction with Commonly Coprescribed Medications

Pharmacogenomic testing, together with the early detection of drug-drug-gene interactions (DDGI) before initiating opioids, can improve the selection of dosage and reduce the risk of adverse drug interactions and therapeutic failures following Total Joint Arthroplasty. The variants of CYP genes can mediate DDGI. Orthopedic surgeons should become familiar with the genetic aspect of opioid use and abuse, as well as the influence of the patient genetic makeup in opioid selection and response, and polymorphic variants in pain modulation.

Pharmacogenetic profiling and individualised therapy in the treatment of degenerative spinal conditions

Patients presenting with degenerative spinal changes are often poor surgical candidates due to associated co-morbidities, frailty, or sarcopenia. Additionally, surgeries of a degenerative spine can prove difficult due to the distortion of normal surgical anatomy. Therefore, many patients are managed conservatively with a variety of modalities, including over-the-counter and prescription medications. Nevertheless, several patients do not experience adequate relief from pain with analgesic medications, precipitating multiple hospital visits, and usage of resources. As a result, back pain is regarded as a major economic burden, with total costs of associated treatment exceeding $100 billion annually. Pharmacogenetics is a relatively novel method of evaluating an individual's response to analgesic medications, through analysis of germline polymorphisms. It entails obtaining a genetic sample, often via buccal swab or peripheral blood sample, and genetic analysis achieved through either polymerase chain reaction +/- Sanger sequencing, microassays, restriction length fragment polymorphism analysis, or genetic library preparation and next generation sequencing. The potential efficacy of pharmacogenetic analysis has been highlighted across several specialities to date. However, a paucity of evidence exists regarding spine surgery populations. Nevertheless, regular prospective pharmacogenetic analysis may ultimately prove beneficial when concerning degenerative spinal cohorts due to aforementioned surgical and economic considerations. The purpose of this narrative review is to outline how metaboliser profile variants affect the pharmacokinetics of specific analgesia used to treat back pain, and to discuss the current potential and limitations of employing regular pharmacogenetic analysis for spine surgery populations with degenerative conditions.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

Pharmacogenetics of Praziquantel Metabolism: Evaluating the Cytochrome P450 Genes of Zimbabwean Patients During a Schistosomiasis Treatment

Schistosomiasis is a parasitic disease infecting over 236 million people annually, with the majority affected residing on the African continent. Control of this disease is reliant on the drug praziquantel (PZQ), with treatment success dependent on an individual reaching PZQ concentrations lethal to schistosomes. Despite the complete reliance on PZQ to treat schistosomiasis in Africa, the characterization of the pharmacogenetics associated with PZQ metabolism in African populations has been sparse. We aimed to characterize genetic variation in the drug-metabolising cytochrome P450 enzymes (CYPs) and determine the association between each variant and the efficacy of PZQ treatment in Zimbabwean patients exposed to Schistosoma haematobium infection. Genomic DNA from blood samples of 114 case-control Zimbabweans infected with schistosomes were sequenced using the CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP3A4, and CYP3A5 genes as targets. Bioinformatic tools were used to identify and predict functional effects of detected single nucleotide polymorphisms (SNPs). A random forest (RF) model was then used to assess SNPs most predictive of PZQ efficacy, with a misclassification rate of 29%. SNPs were detected across all six genes, with 70 SNPs identified and multiple functional changes to the CYP enzymes predicted. Only four SNPs were significantly associated with PZQ efficacy using χ² tests, with rs951840747 (OR: 3.61, p = 0.01) in the CYP1A2 gene having the highest odds of an individual possessing this SNP clearing infection, and rs6976017 (OR: 2.19, p = 0.045) of CYP3A5 determined to be the most predictive of PZQ efficacy via the RF. Only the rs28371702 (CC) genotype (OR: 2.36, p = 0.024) of CYP2D6 was significantly associated with an unsuccessful PZQ treatment. This study adds to the genomic characterization of the diverse populations in Africa and identifies variants relevant to other pharmacogenetic studies crucial for the development and usage of drugs in these populations.

The Future of Personalized Medicine in Space: From Observations to Countermeasures

The aim of personalized medicine is to detach from a “one-size fits all approach” and improve patient health by individualization to achieve the best outcomes in disease prevention, diagnosis and treatment. Technological advances in sequencing, improved knowledge of omics, integration with bioinformatics and new in vitro testing formats, have enabled personalized medicine to become a reality. Individual variation in response to environmental factors can affect susceptibility to disease and response to treatments. Space travel exposes humans to environmental stressors that lead to physiological adaptations, from altered cell behavior to abnormal tissue responses, including immune system impairment. In the context of human space flight research, human health studies have shown a significant inter-individual variability in response to space analogue conditions. A substantial degree of variability has been noticed in response to medications (from both an efficacy and toxicity perspective) as well as in susceptibility to damage from radiation exposure and in physiological changes such as loss of bone mineral density and muscle mass in response to deconditioning. At present, personalized medicine for astronauts is limited. With the advent of longer duration missions beyond low Earth orbit, it is imperative that space agencies adopt a personalized strategy for each astronaut, starting from pre-emptive personalized pre-clinical approaches through to individualized countermeasures to minimize harmful physiological changes and find targeted treatment for disease. Advances in space medicine can also be translated to terrestrial applications, and vice versa. This review places the astronaut at the center of personalized medicine, will appraise existing evidence and future preclinical tools as well as clinical, ethical and legal considerations for future space travel.

CYP2D6 and CYP3A4 variants influence the risk and outcome of COVID-19 infection among rheumatoid arthritis patients maintained on hydroxychloroquine

OBJECTIVES

Hydroxychloroquine (HCQ) has been used as an off label for the management of coronavirus disease (Covid-19) infection with other drugs. However, different genetic variants can affect the metabolism of HCQ leading to inter-individual differences in its efficacy. In this study, we investigated the effects of variants in CYP2D6, CYP3A4 and CYP3A5 on the risk of Covid-19 infection among patients receiving HCQ for controlling rheumatoid arthritis (RA).

METHODS

A total of 60 patients were genotyped for CYP2D6*2XN, CYP2D6*4, CYP3A4*1B and CYP3A5*2. They were receiving HCQ for the treatment of RA. The patients were evaluated clinically for fever and dry cough, radiologically via chest computed tomography (CT) and immunologically via anti-Covid-19 IgG and IgM titers.

RESULTS

Variants in CYP2D6 significantly affected the grade of ground glass (CYP2D6*4 AA carriers showed the higher risk for grade 3) and the risk of positive anti-Covid-19 IgM (CYP2D6*2XN CC and CYP3A4*1B AA had the lowest risk), the duration of HCQ, the use of corticosteroids or gender did not affect the Covid-19 status significantly.

CONCLUSIONS

In general, the outcome of the studied patients receiving HCQ was good (no deaths, no intubation needed). CYP2D6 variants could affect the outcome of Covid-19 infection.

Impact of Drug-Gene-Interaction, Drug-Drug-Interaction, and Drug-Drug-Gene-Interaction on (es)Citalopram Therapy: The PharmLines Initiative

We explored the association between CYP2C19/3A4 mediated drug-gene-interaction (DGI), drug-drug-interaction (DDI) and drug-drug-gene-interaction (DDGI) and (es)citalopram dispensing course. A cohort study was conducted among adult Caucasians from the Lifelines cohort (167,729 participants) and linked dispensing data from the IADB.nl database as part of the PharmLines Initiative. Exposure groups were categorized into (es)citalopram starters with DGI, DDI and DDGI. The primary outcome was drug switching and/or dose adjustment, and the secondary was early discontinuation after the start of (es)citalopram. Logistic regression modeling was applied to estimate adjusted odd ratios with their confidence interval. We identified 316 (es)citalopram starters with complete CYP2C19/3A4 genetic information. The CYP2C19 IM/PM and CYP3A4 NM combination increased risks of switching and/or dose reduction (OR: 2.75, 95% CI: 1.03–7.29). The higher effect size was achieved by the CYP2C19 IM/PM and CYP3A4 IM combination (OR: 4.38, 95% CI: 1.22–15.69). CYP2C19/3A4 mediated DDIs and DDGIs showed trends towards increased risks of switching and/or dose reduction. In conclusion, a DGI involving predicted decreased CYP2C19 function increases the need for (es)citalopram switching and/or dose reduction which might be enhanced by co-presence of predicted decreased CYP3A4 function. For DDI and DDGI, no conclusions can be drawn from the results.

Pharmacogenomics for Primary Care: An Overview

Most of the prescribing and dispensing of medicines happens in primary care. Pharmacogenomics (PGx) is the study and clinical application of the role of genetic variation on drug response. Mounting evidence suggests PGx can improve the safety and/or efficacy of several medications commonly prescribed in primary care. However, implementation of PGx has generally been limited to a relatively few academic hospital centres, with little adoption in primary care. Despite this, many primary healthcare providers are optimistic about the role of PGx in their future practice. The increasing prevalence of direct-to-consumer genetic testing and primary care PGx studies herald the plausible gradual introduction of PGx into primary care and highlight the changes needed for optimal translation. In this article, the potential utility of PGx in primary care will be explored and on-going barriers to implementation discussed. The evidence base of several drug-gene pairs relevant to primary care will be outlined with a focus on antidepressants, codeine and tramadol, statins, clopidogrel, warfarin, metoprolol and allopurinol. This review is intended to provide both a general introduction to PGx with a more in-depth overview of elements relevant to primary care.

Linking Pharmacogenomic Information on Drug Safety and Efficacy with Ethnic Minority Populations

Numerous prescription drugs’ labeling contains pharmacogenomic (PGx) information to aid health providers and patients in the safe and effective use of drugs. However, clinical studies for such PGx biomarkers and related drug doses are generally not conducted in diverse ethnic populations. Thus, it is urgently important to incorporate PGx information with genetic characteristics of racial and ethnic minority populations and utilize it to promote minority health. In this project a bioinformatics approach was developed to enhance the collection of PGx information related to ethnic minorities to pave the way toward understanding the population-wide utility of PGx information. To address this challenge, we first gathered PGx information from drug labels. Second, we extracted data on the allele frequency information of genetic variants in ethnic minority groups from public resources. Then, we collected published research articles on PGx biomarkers and related drugs for reference. Finally, the data were integrated and formatted to build a new PGx database containing information on known drugs and biomarkers for ethnic minority groups. This database provides scientific information needed to evaluate available PGx information to enhance drug dose selection and drug safety for ethnic minority populations.

Pharmacogenetic Implications for Antidepressant Pharmacotherapy in Late-Life Depression: A Systematic Review of the Literature for Response, Pharmacokinetics and Adverse Drug Reactions

Affecting up to 15% of older adults, late-life depression (LLD) is characterized by the occurrence of depressive symptoms after the age of 50-65 years and maybe pathophysiologically distinct from depression in younger adults. Therefore, LLD is challenging to treat, and predictive genetic testing might be essential to improve treatment in this vulnerable population. The current review aims to provide a summary of the literature exploring genetic associations with antidepressant treatment outcomes in late-life. We conducted a systematic search of three integrated electronic databases. We identified 29 articles investigating genetic associations with antidepressant treatment outcomes, pharmacokinetic parameters, and adverse drug reactions in older adults. Given the small number of investigations conducted in older adults, it is difficult to conclude the presence or absence of genetic associations with the outcomes of interest. In sum, the most substantial amount of evidence exists for the CYP2D6 metabolizer status, SLC6A4 5-HTTLPR, and BDNF rs6265. These findings are consistent in the literature when not restricting to older adults, suggesting that similar treatment recommendations may be provided for older adults regarding genetic variation, such as those outlined for CYP2D6 by the Clinical Pharmacogenetics Implementation Consortium. Nonetheless, further studies are required in well-characterized samples, including genome-wide data, to validate if similar treatment adjustments are appropriate in older adults, given that there appear to be significant effects of genetic variation on antidepressant treatment factors.

Prescribed Doses of CYP2D6-Metabolized Drugs and Hemodynamic Responses in Relation to CYP2D6 Genotype Among Older Patients Exposed to Polypharmacy

Background

Many drugs with dose-dependent effects on hemodynamic variables are metabolized by cytochrome P450 2D6 (CYP2D6). The aim of this study was to compare prescribed dosages and hemodynamic responses of such drugs in relation to pharmacogenetic variability in CYP2D6 metabolism among patients aged ≥ 70 years exposed to polypharmacy.

Materials and Methods

We included 173 patients with detailed information about drug use. The patients were retrospectively subjected to CYP2D6 genotyping, which comprised the most common variant alleles encoding reduced, absent, or increased CYP2D6 metabolism. In order to compare dosages across different CYP2D6-metabolized drugs, all prescribed daily doses were harmonized to the ‘percent of a daily defined dose’ (DDD). The mean harmonized DDD was compared between genotype-predicted normal metabolizers (NMs) and patients with reduced or absent CYP2D6 enzyme activity, defined as intermediate or poor metabolizers (IMs/PMs). Blood pressure, pulse, and patient proportions with orthostatism and bradycardia were also compared between genotype subgroups.

Results

The genotype-predicted phenotype subgroups comprised 79 NMs (45.7%), 75 IMs (43.4%), and 16 PMs (9.2%). There were no differences in dosing of CYP2D6 substrates between NMs and IMs/PMs (p = 0.76). A higher proportion of CYP2D6 IMs/PMs experienced orthostatism (p = 0.03), while there were no significant subgroup differences for the other hemodynamic variables.

Conclusion

In this real-life clinical setting of patients aged ≥ 70 years, dosing of CYP2D6 substrates were not adjusted according to genotype-predicted CYP2D6 metabolism. The increased occurrence of orthostatism in patients with reduced/absent CYP2D6 metabolism may indicate that individualized dosing based on genotype has the potential to prevent adverse effects in these vulnerable patients.

Electronic supplementary material

The online version of this article (10.1007/s40266-020-00763-0) contains supplementary material, which is available to authorized users.

Targeted ultra-deep sequencing of a South African Bantu-speaking cohort to comprehensively map and characterize common and novel variants in 65 pharmacologically-related genes

Supplemental Digital Content is available in the text.

Background

African populations are characterised by high genetic diversity, which provides opportunities for discovering and elucidating novel variants of clinical importance, especially those affecting therapeutic outcome. Significantly more knowledge is however needed before such populations can take full advantage of the advances in precision medicine. Coupled with the need to concisely map and better understand the pharmacological implications of genetic diversity in populations of sub-Sharan African ancestry, the aim of this study was to identify and characterize known and novel variants present within 65 important absorption, distribution, metabolism and excretion genes.

Patients and methods

Targeted ultra-deep next-generation sequencing was used to screen a cohort of 40 South African individuals of Bantu ancestry.

Results

We identified a total of 1662 variants of which 129 are novel. Moreover, out of the 1662 variants 22 represent potential loss-of-function variants. A high level of allele frequency differentiation was observed for variants identified in this study when compared with other populations. Notably, on the basis of prior studies, many appear to be pharmacologically important in the pharmacokinetics of a broad range of drugs, including antiretrovirals, chemotherapeutic drugs, antiepileptics, antidepressants, and anticoagulants. An in-depth analysis was undertaken to interrogate the pharmacogenetic implications of this genetic diversity.

Conclusion

Despite the new insights gained from this study, the work illustrates that a more comprehensive understanding of population-specific differences is needed to facilitate the development of pharmacogenetic-based interventions for optimal drug therapy in patients of African ancestry.

Defining screening panel of functional variants of CYP1A1, CYP2C9, CYP2C19, CYP2D6, and CYP3A4 genes in Serbian population

Plethora of drugs and toxic substances is metabolized by cytochrome P450 enzymes (CYP450). These enzymes are coded by highly variable genes abundant with single nucleotide variants (SNVs) and small insertions/deletions (indels) that affect the functionality of the enzymes, increasing or decreasing their activity. CYP genes genotyping, followed by haplotype inference, provides substrate specific metabolic phenotype prediction. This is crucial in pharmacogenetics and applicable in molecular autopsy. However, high number of alleles in CYP450 superfamily and interethnic variability in frequency distribution require precise gene panel customization. To estimate informativeness of SNVs and alleles in CYP gene families 1, 2, and 3, associated with metabolic alterations, 500 unrelated individuals from 5 regions of Serbia were genotyped using TaqMan assays to determine frequencies of CYP2C9 *2 and *3, CYP2C19 *2 and *17 alleles, four variants in CYP2D6 (rs3892097, rs1065852, rs28371725, rs28371706) gene, and CYP3A4*1B allele. In addition, CYP1A1 rs4646903 and rs1048943 (m1 and m2) variants were genotyped by RFLP. Our results showed that frequencies of tested variants in Serbian population corresponded to general European population and somewhat differed from neighboring populations. SNV rs1065852, the main contributor to non-functional CYP2D6 *4, significantly departed from Hardy-Weinberg equilibrium. With the exception of rs28371706 in CYP2D6 and rs2740574 in CYP3A4, which were very rare in our sample, all other tested variants in CYP2 family are informative and appropriate for pharmacogenetic testing, molecular autopsy, and medico-legal genetic analyses.

Update on the pharmacogenomics of pain management

Pharmacogenomics is the study of genetic variants that impact drug effects through changes in a drug’s pharmacokinetics and pharmacodynamics. Pharmacogenomics is being integrated into clinical pain management practice because variants in individual genes can be predictive of how a patient may respond to a drug treatment. Pain is subjective and is considered challenging to treat. Furthermore, pain patients do not respond to treatments in the same way, which makes it hard to issue a consistent treatment regimen for all pain conditions. Pharmacogenomics would bring consistency to the subjective nature of pain and could revolutionize the field of pain management by providing personalized medical care tailored to each patient based on their gene variants. Additionally, pharmacogenomics offers a solution to the opioid crisis by identifying potentially opioid-vulnerable patients who could be recommended a nonopioid treatment for their pain condition. The integration of pharmacogenomics into clinical practice creates better and safer healthcare practices for patients. In this article, we provide a comprehensive history of pharmacogenomics and pain management, and focus on up to date information on the pharmacogenomics of pain management, describing genes involved in pain, genes that may reduce or guard against pain and discuss specific pain management drugs and their genetic correlations.

Pharmacogenetics of Antidepressants: from Genetic Findings to Predictive Strategies

The constantly growing contribution of depressive disorders to the global disease statistics calls for a growth of treatment effectiveness and optimization. Antidepressants are the most frequently prescribed medicines for depressive disorders. However, development of a standardized pharmacotherapeutic approach is burdened by the genomic heterogeneity, lack of reliable predictive biomarkers and variability of the medicines metabolism aggravated by multiple side effects of antidepressants. According to modern assessments up to 20 % of the genes expressed in our brain are involved in the pathogenesis of depression. Large-scale genetic and genomic research has found a number of potentially prognostic genes. It has also been proven that the effectiveness and tolerability of antidepressants directly depend on the variable activity of the enzymes that metabolize medicines. Almost all modern antidepressants are metabolized by the cytochrome P450 family enzymes. The most promising direction of research today is the GWAS (Genome-Wide Association Study) method that is aimed to link genomic variations with phenotypical manifestations. In this type of research genomes of depressive patients with different phenotypes are compared to the genomes of the control group containing same age, sex and other parameters healthy people. Notably, regardless of the large cohorts of patients analyzed, none of the GWA studies conducted so far can reliably reproduce the results of other analogous studies. The explicit heterogeneity of the genes associated with the depression pathogenesis and their pleiotropic effects are strongly influenced by environmental factors. This may explain the difficulty of obtaining clear and reproducible results. However, despite any negative circumstances, the active multidirectional research conducted today, raises the hope of clinicians and their patients to get a whole number of schedules how to achieve remission faster and with guaranteed results

An economic model of the cost-utility of pre-emptive genetic testing to support pharmacotherapy in patients with major depression in primary care

The pharmacokinetics of many antidepressants (tricyclic antidepressants (TCA) or selective serotonin re-uptake inhibitors (SSRI)) are influenced by the highly polymorphic CYP2D6 enzyme. Therefore, pharmacogenetics could play an important role in the treatment of depressive patients. The potential cost-utility of screening patients is however still unknown. Therefore, a Markov model was developed to compare the strategy of screening for CYP2D6 and subsequently adjust antidepressant treatment according to a patient's metabolizer profile of poor, extensive, or ultra metabolizer, with the strategy of no screening ('one size fits all' principle). Each week a patient had a probability of side effects, which was followed by dosage titration or treatment switching. After 6 weeks treatment effect was evaluated followed by treatment adjustments if necessary, with a total time horizon of the model of 12 weeks. The analysis was performed from a societal perspective. The strategy of screening compared with no screening resulted in incremental costs of €91 (95 percentiles: €39; €152) more expensive but also more effect with 0.001 quality adjusted life years (QALYs) (95 percentiles: 0.001; 0.002) gain. The incremental cost-effectiveness ratio (ICER) was therefore €77,406 per QALY gained, but varied between €22,500 and €377,500 depending on the price of screening and productivity losses. According to our model, we cannot unequivocally conclude that screening for CYP2D6 in primary care patients using antidepressants is be cost-effective, as the results are surrounded by large uncertainty. Therefore, information from ongoing studies should be used to reduce these uncertainties.

Value of Supportive Care Pharmacogenomics in Oncology Practice

Genomic medicine provides opportunities to personalize cancer therapy for an individual patient. Although novel targeted therapies prolong survival, most patients with cancer continue to suffer from burdensome symptoms including pain, depression, neuropathy, nausea and vomiting, and infections, which significantly impair quality of life. Suboptimal management of these symptoms can negatively affect response to cancer treatment and overall prognosis. The effect of genetic variation on drug response-otherwise known as pharmacogenomics-is well documented and directly influences an individual patient's response to antiemetics, opioids, neuromodulators, antidepressants, antifungals, and more. The growing body of pharmacogenomic data can now guide clinicians to select the safest and most effective supportive medications for an individual patient with cancer from the very first prescription. This review outlines a theoretical patient case and the implications of using pharmacogenetic test results to personalize supportive care throughout the cancer care continuum.

IMPLICATIONS FOR PRACTICE

Integration of palliative medicine into the cancer care continuum has resulted in increased quality of life and survival for patients with many cancer types. However, suboptimal management of symptoms such as pain, neuropathy, depression, and nausea and vomiting continues to place a heavy burden on patients with cancer. As demonstrated in this theoretical case, pharmacogenomics can have a major effect on clinical response to medications used to treat these conditions. Recognizing the value of supportive care pharmacogenomics in oncology and application into routine practice offers an objective choice for the safest and most effective treatment compared with the traditional trial and error method.

Cytochrome P450 genotype-guided drug therapies: An update on current states

Over the past 2 decades, knowledge of the role and clinical value of pharmacogenetic markers has expanded so that individualized pre-emptive therapy based on genetic background of patients could be within reach for clinical implementation. This is evidenced from the frequent updating of drug labels that incorporates pharmacogenetic information (where compelling data become available) by the regulatory agencies (such as the US FDA), and the periodical publication of guidelines of specific therapeutic recommendations based on the results of pharmacogenetic tests by the pharmacogenetics working groups or consortiums of professional bodies. Clinical relevance of the cytochrome P450 (CYP) polymorphism related to dose, effectiveness and/or toxicity of key drugs are presented in this review, including that of warfarin, clopidogrel, tricyclic antidepressants, and proton pump inhibitors. Prospect for routine clinical application of CYP genotyping before prescribing drugs is still currently unclear due to challenges and barriers associated with availability of well-defined and validated pharmacogenetic studies, the interpretation, result reporting and potential error of genotype testing, involvement of non-genetic factors, and other patient's demographic and disease conditions. Further studies to provide additional supporting clinical data and acceleration of pharmacogenetic testing standards and techniques should help improve the evidence base needed for clinical utility and hence move the implementation of genotype-guided therapy in clinical practice a step closer to reality.

Pharmacokinetics, Safety, and Tolerability of Vortioxetine Following Single- and Multiple-Dose Administration in Healthy Japanese Adults

Three phase 1 randomized single-center studies assessed the pharmacokinetics, safety, and tolerability of vortioxetine after single- and multiple-dose administration in healthy Japanese adults. Study 1 assessed the pharmacokinetics of vortioxetine after administration of single rising doses to men and multiple doses to men and women; study 2 evaluated vortioxetine pharmacokinetics in elderly adults; and study 3 assessed food effects on vortioxetine pharmacokinetics in healthy men. The primary end points included pharmacokinetic parameters of vortioxetine and incidence of adverse events (AEs). Across all studies, 130 participants were randomized and 128 participants completed the studies. Vortioxetine was absorbed and eliminated from plasma slowly, and exposure to vortioxetine increased in an almost dose-proportional manner. No clinically significant differences in the pharmacokinetics of vortioxetine or its metabolites were observed between the sexes in young and elderly adults. Study 3 demonstrated that vortioxetine and its metabolites had similar pharmacokinetics when administered in the fasted and fed states. Importantly, vortioxetine was safe and tolerated, with incidence of AEs comparable to that of placebo. No deaths or serious AEs leading to trial discontinuation were observed. Overall, vortioxetine pharmacokinetics, safety, and tolerability in Japanese adults were comparable to reports in non-Japanese populations.

Pharmacogenetic testing for the guidance of psychiatric treatment: a multicenter retrospective analysis

OBJECTIVE

We investigated the association between clinical outcome and the recommendations of a pharmacogenetic test (Neuropharmagen) in patients with a variety of psychiatric conditions whose previous treatment regimen had failed.

METHODS

This retrospective, naturalistic, multicenter study included adult psychiatric patients (depression, psychosis, anxiety, bipolar, etc.) who had been seen at 3 private clinics. All patients had received pharmacogenetic testing (Neuropharmagen) and were classified depending on whether or not their post-test treatment regimen followed the test recommendations. Clinical severity was assessed with the Clinical Global Impression of Severity (CGI-S) at baseline (pre-test) and 3-month follow-up, and adverse events were recorded.

RESULTS

182 patients were available for analysis. After multivariate adjustment, patients whose treatment followed the test recommendations had odds of improvement about 4 times greater than patients whose treatment did not follow the recommendations (adjusted OR=3.86, 95%CI 1.36-10.95; p=0.011). Importantly, psychiatric diagnosis did not significantly affect the odds of improvement. Also, in the subpopulation with baseline CGI-S score >3 (N=170), the rate of stabilization at follow-up (defined as CGI-S≤3) was significantly higher in patients whose treatment followed the pharmacogenetic recommendations (p=0.033). There was no apparent difference in the incidence of adverse events (6 patients in each group).

CONCLUSIONS

Non-drug naïve patients whose treatment followed the recommendations of pharmacogenetic testing were more likely to improve their condition than patients whose treatment did not. These results are consistent with previous clinical research on depressed patients, and this study also suggests that this benefit can be extended to psychiatric conditions other than depression.

Association between CYP2D6 Genotypes and the Risk of Antidepressant Discontinuation, Dosage Modification and the Occurrence of Maternal Depression during Pregnancy

Importance: Polymorphic expression of drug metabolizing enzymes affects the metabolism of antidepressants, and thus can contribute to drug response and/or adverse events. Pregnancy itself can affect CYP2D6 activity with profound variations determined by CYP2D6 genotype. Objective: To investigate the association between CYP2D6 genotype and the risk of antidepressant discontinuation, dosage modification, and the occurrence of maternal CYP2D6, Antidepressants, Depression during pregnancy. Setting: Data from the Organization of Teratology Information Specialists (OTIS) Antidepressants in Pregnancy Cohort, 2006-2010, were used. Women were eligible if they were within 14 completed weeks of pregnancy at recruitment and exposed to an antidepressant or having any exposures considered non-teratogenic. Main Outcomes and Measures: Gestational antidepressant usage was self-reported and defined as continuous/discontinued use, and non-use; dosage modification was further documented. Maternal depression and anxiety were measured every trimester using the telephone interviewer-administered Edinburgh Postnatal Depression Scale and the Beck Anxiety Inventory, respectively. Saliva samples were collected and used for CYP2D6 genotype analyses. Logistic regression models were used to calculate crude and adjusted odds ratios (OR) with 95% confidence intervals. Results: A total of 246 pregnant women were included in the study. The majority were normal metabolizers (NM, n = 204, 83%); 3.3% (n = 8) were ultrarapid metabolizers (UM), 5.7% (n = 14) poor metabolizers (PM), and 8.1% (n = 20) intermediate metabolizers (IM). Among study subjects, 139 women were treated with antidepressants at the beginning of pregnancy, and 21 antidepressant users (15%) discontinued therapy during pregnancy. Adjusting for depressive symptoms, and other potential confounders, the risk of discontinuing antidepressants during pregnancy was nearly four times higher in slow metabolizers (poor or intermediate metabolizers) compared to those with a faster metabolism rate (normal or ultrarapid metabolizers), aOR = 3.57 (95% CI: 1.15-11.11). Predicted CYP2D6 metabolizer status did not impact dosage modifications. Compared with slow metabolizers, significantly higher proportion of women in the fast metabolizer group had depressive symptom in the first trimester (19.81 vs. 5.88%, P = 0.049). Almost 21% of treated women remained depressed during pregnancy (14.4% NM-UM; 6.1% PM-IM). Conclusions and Relevance: Prior knowledge of CYP2D6 genotype may help to identify pregnant women at greater risk of antidepressant discontinuation. Twenty percent of women exposed to antidepressants during pregnancy remained depressed, indicating an urgent need for personalized treatment of depression during pregnancy.

The burden and management of cytochrome P450 2D6 (CYP2D6)-mediated drug-drug interaction (DDI): co-medication of metoprolol and paroxetine or fluoxetine in the elderly

PURPOSE

Metoprolol and paroxetine/fluoxetine are inevitably co-prescribed because cardiovascular disorders and depression often coexist in the elderly. This leads to CYP2D6-mediated drug-drug interactions (DDI). Because systematic evaluations are lacking, we assessed the burden of metoprolol-paroxetine/fluoxetine interaction in the elderly and how these interactions are managed in Dutch community pharmacies.

METHOD

Dispensing data were collected from the University of Groningen pharmacy database (IADB.nl, 1999-2014) for elderly patients (≥60 years) starting beta-blockers and/or antidepressants. Based on the two main DDI alert systems (G-Standard and Pharmabase), incidences were divided between signalled (metoprolol-fluoxetine/paroxetine) and not-signalled (metoprolol-alternative antidepressants and alternative beta-blockers-paroxetine/fluoxetine) combinations. Incident users were defined as patients starting at least one signalled or a non-signalled combination. G-Standard signalled throughout the study period, whereas Pharmabase stopped after 2005.

RESULTS

A total of 1763 patients had 2039 metoprolol-paroxetine/fluoxetine co-prescriptions, despite DDI alert systems, and about 57.3% were signalled. The number of metoprolol-alternative antidepressant combinations (incidences = 3150) was higher than alternative beta-blocker-paroxetine/fluoxetine combinations (incidences = 1872). Metoprolol users are more likely to be co-medicated with an alternative antidepressant (incidences = 2320) than paroxetine/fluoxetine users (incidences = 1232) are. The number of paroxetine/fluoxetine users co-prescribed with alternative beta-blockers was comparable to those co-medicated with metoprolol (about 50%). Less than 5% of patients received a substitute therapy after using metoprolol-paroxetine/fluoxetine. Most of the metoprolol users (90%) received a low dose (mean DDD = 0.47) regardless whether they were prescribed paroxetine/fluoxetine.

CONCLUSION

Despite the signalling software, metoprolol-paroxetine/fluoxetine combinations are still observed in the elderly population. The clinical impact of these interactions needs further investigation. Copyright © 2017 John Wiley & Sons, Ltd.

Pharmacogenetics and Imaging-Pharmacogenetics of Antidepressant Response: Towards Translational Strategies

Genetic variation underlies both the response to antidepressant treatment and the occurrence of side effects. Over the past two decades, a number of pharmacogenetic variants, among these the SCL6A4, BDNF, FKBP5, GNB3, GRIK4, and ABCB1 genes, have come to the forefront in this regard. However, small effects sizes, mixed results in independent samples, and conflicting meta-analyses results led to inherent difficulties in the field of pharmacogenetics translating these findings into clinical practice. Nearly all antidepressant pharmacogenetic variants have potentially pleiotropic effects in which they are associated with major depressive disorder, intermediate phenotypes involved in emotional processes, and brain areas affected by antidepressant treatment. The purpose of this article is to provide a comprehensive review of the advances made in the field of pharmacogenetics of antidepressant efficacy and side effects, imaging findings of antidepressant response, and the latest results in the expanding field of imaging-pharmacogenetics studies. We suggest there is mounting evidence that genetic factors exert their impact on treatment response by influencing brain structural and functional changes during antidepressant treatment, and combining neuroimaging and genetic methods may be a more powerful way to detect biological mechanisms of response than either method alone. The most promising imaging-pharmacogenetics findings exist for the SCL6A4 gene, with converging associations with antidepressant response, frontolimbic predictors of affective symptoms, and normalization of frontolimbic activity following antidepressant treatment. More research is required before imaging-pharmacogenetics informed personalized medicine can be applied to antidepressant treatment; nevertheless, inroads have been made towards assessing genetic and neuroanatomical liability and potential clinical application.

Identifying genetic loci affecting antidepressant drug response in depression using drug-gene interaction models

Antidepressants are often only moderately successful in decreasing the severity of depressive symptoms. In part, antidepressant treatment response in patients with depression is genetically determined. However, although a large number of studies have been conducted aiming to identify genetic variants associated with antidepressant drug response in depression, only a few variants have been repeatedly identified. Within the present review, we will discuss the methodological challenges and limitations of the studies that have been conducted on this topic to date (e.g., 'treated-only design', statistical power) and we will discuss how specifically drug-gene interaction models can be used to be better able to identify genetic variants associated with antidepressant drug response in depression.

Personalizing supportive care in oncology patients using pharmacogenetic-driven treatment pathways

Cancer patients frequently suffer from disease- and treatment-related pain, nausea and depression, which severely reduces patients' quality of life. It is critical that clinicians are aware of drug-gene interactions and recognize the utility of applying pharmacogenetic information to personalize and improve supportive care. Pharmacogenetic-based algorithms may enhance clinical outcomes by allowing the clinician to select the 'least genetically vulnerable' drug. This review summarizes clinically relevant drug-gene interactions and presents pharmacogenetic-driven treatment pathways for depression, nausea/vomiting and pain. Ideally, this review provides a resource for clinicians to consult when selecting pharmacotherapy for a patient who presents with limited pharmacogenetic test results, with the hope of better controlling burdensome symptoms and improving the quality of life for cancer patients.

Polymorphism in CYP2D6 and CYP2C19, members of the cytochrome P450 mixed-function oxidase system, in the metabolism of psychotropic drugs

Numerous studies in the field of psychopharmacological treatment have investigated the possible contribution of genetic variability between individuals to differences in drug efficacy and safety, motivated by the wide individual variation in treatment response. Genomewide analyses have been conducted in several large-scale studies on antidepressant drug response. However, no consistent findings have emerged from these studies. In a recent meta-analysis of genomewide data from the three studies capturing common variation for association with symptomatic improvement and remission revealed the absence of any strong genetic association and failed to replicate results of individual studies in the pooled data. However, there are good reasons to consider the possible importance of pharmacogenetic variants separately. These variants explain a large portion of the manifold variability in individual drug metabolism. More than 20 psychotropic drugs have now been relabelled by the FDA adding information on polymorphic drug metabolism and therapeutic recommendations. Furthermore, dose recommendations for polymorphisms in drug metabolizing enzymes, first and foremost CYP2D6 and CYP2C19, have been issued with the advice to reduce the dosage in poor metabolizers to 50% or less (in eight cases), or to choose an alternative treatment. Beside the well-described role in hepatic drug metabolism, these enzymes are also expressed in the brain and play a role in biotransformation of endogenous substrates. These polymorphisms may therefore modulate brain metabolism and affect the function of the neural substrates of cognition and emotion.

Clinical validity of cytochrome P450 metabolism and serotonin gene variants in psychiatric pharmacotherapy

Adverse events, response failures and medication non-compliance are common in patients receiving medications for the treatment of mental illnesses. A systematic literature review assessed whether pharmacokinetic (PK) or pharmacodynamic (PD) responses to 26 commonly prescribed antipsychotic and antidepressant medications, including efficacy or side effects, are associated with nucleotide polymorphisms in eight commonly studied genes in psychiatric pharmacotherapy: CYP2D6, CYP2C19, CYP2C9, CYP1A2, CYP3A4, HTR2C, HTR2A, and SLC6A4. Of the 294 publications included in this review, 168 (57%) showed significant associations between gene variants and PK or PD outcomes. Other studies that showed no association often had insufficient control for confounding variables, such as co-medication use, or analysis of medications not substrates of the target gene. The strongest gene-outcome associations were for the PK profiles of CYP2C19 and CYP2D6 (93% and 90%, respectively), for the PD associations between HTR2C and weight gain (57%), and for SLC6A4 and clinical response (54%), with stronger SLC6A4 response associations for specific drug classes (60-83%). The preponderance of evidence supports the validity of analyzing nucleotide polymorphisms in CYP and pharmacodynamic genes to predict the metabolism, safety, or therapeutic efficacy of psychotropic medications commonly used for the treatment of depression, schizophrenia, and bipolar illness.

Towards the implementation of CYP2D6 and CYP2C19 genotypes in clinical practice: update and report from a pharmacogenetic service clinic

Genetic testing may help to improve treatment outcomes in order to avoid non-response or severe side effects to psychotropic medication. Most robust data have been obtained for gene variants in CYP2D6 and CYP2C19 enzymes for antipsychotics and antidepressant treatment. We reviewed original articles indexed in PubMed from 2008-2013 on CYP2D6 and CYP2C19 gene variants and treatment outcome to antidepressant or antipsychotic medication. We have started providing CYP2D6 and CYP2C19 genotype information to physicians and conducted a survey where preliminary results are reported. Studies provided mixed results regarding the impact of CYP2D6 and CYP2C19 gene variation on treatment response. Plasma levels were mostly found associated with CYP metabolizer status. Higher occurrence/severity of side effects were reported in non-extensive CYP2D6 or CYP2C19 metabolizers. Results showed that providing genotypic information is feasible and generally well accepted by both patients and physicians. Although currently available studies are limited by small sample sizes and infrequent plasma drug level assessment, research to date indicates that CYP2D6 and CYP2C19 testing may be beneficial particularly for non-extensive metabolizing patients. In summary, clinical assessment of CYP2D6 and CYP2C19 metabolizer status is feasible, well accepted and optimizes drug treatment in psychiatry.

Do we need pharmacogenetics to personalize antidepressant therapy?

This review examines the role of drug metabolism and drug target polymorphism in determining the clinical response to antidepressants. Even though antidepressants are the most effective available treatment for depressive disorders, there is still substantial need for improvement due to the slow onset of appreciable clinical improvement and the association with side effects. Moreover, a substantial group of patients receiving antidepressant therapy does not achieve remission or fails to respond entirely. Even if the large variation in antidepressant treatment outcome across individuals remains poorly understood, one possible source of this variation in treatment outcome are genetic differences. The review focuses on a few polymorphisms which have been extensively studied, while reporting a more comprehensive reference to the existing literature in table format. It is relatively easy to predict the effect of polymorphisms in drug metabolizing enzymes, such as cytochromes P450 2D6 (CYP2D6) and cytochrome P450 2C19 (CYP2C19), which may be determined in the clinical context in order to explain or prevent serious adverse effects. The role of target polymorphism, however, is much more difficult to establish and may be more relevant for disease susceptibility and presentation rather than for response to therapy.

Does pharmacogenetic testing for CYP450 2D6 and 2C19 among patients with diagnoses within the schizophrenic spectrum reduce treatment costs?

The effect of pharmacogenetic testing for CYP450 2D6 and 2C19 on treatment costs have not yet been documented. This study used Danish patient registers to calculate healthcare costs of treating patients with diagnoses within the schizophrenic spectrum for 1 year with or without pharmacogenetic testing for polymorphisms in the genes for the CYP2D6 and CYP2C19 enzymes. In a randomized, controlled trial, stratified with respect to metabolizer genotype, 104 patients were assigned to treatment based on pharmacogenetic testing and 103 patients to treatment as usual. Random exclusion of extensive and intermediate metabolizers was used to increase the frequency of extreme metabolizers (poor metabolizers and ultrarapid metabolizers for CYP2D6) to 20% in both groups. Cost differences were analysed at several levels including (i) overall healthcare expenditure, (ii) psychiatric hospital cost (iii) nonpsychiatric hospital cost, (iv) primary care spending and (v) pharmaceuticals. Statistically significant differences in costs of psychiatric care dependent on metabolizer status were found between intervention groups. Pharmacogenetic testing significantly reduced costs among the extreme metabolizers (poor metabolizers and ultrarapid metabolizers) to 28%. Use of primary care services and pharmaceuticals was also affected by the intervention.This study confirms earlier findings that extreme metabolizers (poor and ultrarapid metabolizers) incur higher costs than similar patients with a normal metabolizer genotype. However, this study shows that these excess costs can be reduced by pharmacogenetic testing. Pharmacogenetic testing for CYP2D6 and CYP2C19 could thus be considered as a means of curtailing high psychiatric treatment costs among extreme metabolizers.

Influence of CYP2D6 and CYP2C19 gene variants on antidepressant response in obsessive-compulsive disorder

Numerous studies have reported on pharmacogenetics of antidepressant response in depression. In contrast, little is known of response predictors in obsessive-compulsive disorder (OCD), a disorder with among the lowest proportion of responders to medication (40-60%). Our study is the largest investigation to date (N=184) of treatment response and side effects to antidepressants in OCD based on metabolizer status for CYP2D6 and CYP2C19. We observed significantly more failed medication trials in CYP2D6 non-extensive compared with extensive metabolizers (P=0.007). CYP2D6 metabolizer status was associated with side effects to venlafaxine (P=0.022). There were nonsignificant trends for association of CYP2D6 metabolizer status with response to fluoxetine (P=0.056) and of CYP2C19 metabolizer status with response to sertraline (P=0.064). Our study is the first to indicate that CYP genes may have a role in antidepressant response in OCD. More research is required for a future clinical application of genetic testing, which could lead to improved treatment outcomes.

Opioids for chronic pain: new evidence, new strategies, safe prescribing

In the United States, the prevalence and burden of chronic pain is large and still growing. Older adults (aged ≥65 years) make up a large portion of the population with chronic pain, and their presentation, diagnosis, and treatment tends to be more complicated because of age-related physiological changes and comorbidities. Guidelines on treating patients with severe back pain recommend opioids as an option for those who do not find adequate pain relief from acetaminophen or nonsteroidal anti-inflammatory drugs (NSAIDs). For older adult patients at higher risk for NSAID-related adverse effects, such as those who have gastrointestinal or cardiovascular disease, diabetes mellitus, or who are taking low-dose aspirin, opioids are recommended instead. Opioids may also be an appropriate option for patients with neuropathic pain who have not achieved adequate analgesia from maximum doses of first- and second-line antineuropathic agents. Still, opioids are not appropriate for all patients; rather, a differential diagnosis, consideration of other comorbidities, and the potential for opioid-related adverse effects and substance abuse are required to confirm the value of opioid treatment for each individual. For nonresponders to opioid therapy, opioid rotation should be considered before discontinuation is pursued.

Genetic variability of drug-metabolizing enzymes: the dual impact on psychiatric therapy and regulation of brain function

Polymorphic drug-metabolizing enzymes (DMEs) are responsible for the metabolism of the majority of psychotropic drugs. By explaining a large portion of variability in individual drug metabolism, pharmacogenetics offers a diagnostic tool in the burgeoning era of personalized medicine. This review updates existing evidence on the influence of pharmacogenetic variants on drug exposure and discusses the rationale for genetic testing in the clinical context. Dose adjustments based on pharmacogenetic knowledge are the first step to translate pharmacogenetics into clinical practice. However, also clinical factors, such as the consequences on toxicity and therapeutic failure, must be considered to provide clinical recommendations and assess the cost-effectiveness of pharmacogenetic treatment strategies. DME polymorphisms are relevant not only for clinical pharmacology and practice but also for research in psychiatry and neuroscience. Several DMEs, above all the cytochrome P (CYP) enzymes, are expressed in the brain, where they may contribute to the local biochemical homeostasis. Of particular interest is the possibility of DMEs playing a physiological role through their action on endogenous substrates, which may underlie the reported associations between genetic polymorphisms and cognitive function, personality and vulnerability to mental disorders. Neuroimaging studies have recently presented evidence of an effect of the CYP2D6 polymorphism on basic brain function. This review summarizes evidence on the effect of DME polymorphisms on brain function that adds to the well-known effects of DME polymorphisms on pharmacokinetics in explaining the range of phenotypes that are relevant to psychiatric practice.

Fetal serotonin reuptake inhibitor antidepressant exposure: maternal and fetal factors

Prenatal serotonin reuptake inhibitor exposure is common and neonatal outcomes vary greatly, often leading to confusion about whether to use or even continue antenatal use of these antidepressants. Importantly, some but not all infants are affected, which raises questions about how maternal drug metabolism contributes to fetal drug exposure. To address this key question, our paper reviews the role of key maternal, fetal, and placental pharmacokinetic, metabolic, and genetic factors that affect the extent of fetal drug exposure. Considering the role of these factors may further our understanding of variables that may assist in optimizing maternal psychopharmacotherapy during pregnancy and neonatal outcomes.

Role of cytochrome P450 genotype in the steps toward personalized drug therapy

Genetic polymorphism for cytochrome 450 (P450) enzymes leads to interindividual variability in the plasma concentrations of many drugs. In some cases, P450 genotype results in decreased enzyme activity and an increased risk for adverse drug effects. For example, individuals with the CYP2D6 loss-of-function genotype are at increased risk for ventricular arrhythmia if treated with usual does of thioridazine. In other cases, P450 genotype may influence the dose of a drug required to achieve a desired effect. This is the case with warfarin, with lower doses often necessary in carriers of a variant CYP2C9*2 or *3 allele to avoid supratherapeutic anticoagulation. When a prodrug, such as clopidogrel or codeine, must undergo hepatic biotransformation to its active form, a loss-of-function P450 genotype leads to reduced concentrations of the active drug and decreased drug efficacy. In contrast, patients with multiple CYP2D6 gene copies are at risk for opioid-related toxicity if treated with usual doses of codeine-containing analgesics. At least 25 drugs contain information in their US Food and Drug Administration-approved labeling regarding P450 genotype. The CYP2C9, CYP2C19, and CYP2D6 genes are the P450 genes most often cited. To date, integration of P450 genetic information into clinical decision making is limited. However, some institutions are beginning to embrace routine P450 genotyping to assist in the treatment of their patients. Genotyping for P450 variants may carry less risk for discrimination compared with genotyping for disease-associated variants. As such, P450 genotyping is likely to lead the way in the clinical implementation of pharmacogenomics. This review discusses variability in the CYP2C9, CYP2C19, and CYP2D6 genes and the implications of this for drug efficacy and safety.

Pharmacogenetics and the pharmacological management of depression

Depression is a chronic disease seen in many healthcare settings. Current pharmacological treatment options are successful in two-thirds of patients. One CYP450 enzyme, CYP2D6, is responsible for the metabolism of 30% of all drugs including many antidepressants. Phenotypes of metabolizer status affect antidepressant treatment outcomes and adverse drug reactions.

Antidepressant treatment and altered CYP2D6 activity: are pharmacokinetic variations clinically relevant?

BACKGROUND

Many currently used antidepressants are substrates of the cytochrome P450 (CYP) 2D6 enzyme. In patients who experience variations in the activity of this enzyme (e.g., CYP2D6 poor and ultrarapid metabolizers [PMs and UMs]), whether caused by genetic polymorphisms or concomitant administration of a CYP2D6 inhibitor (i.e., phenoconversion), the pharmacokinetics, and hence the effects, of CYP2D6 substrate antidepressants can be altered.

METHODS

This literature review describes the clinical and empirical evidence indicating that alterations in CYP2D6 activity can negatively affect treatment outcomes in patients receiving antidepressant pharmacotherapies that are CYP2D6 substrates.

RESULTS

Based on results from a small, prospective trial, a population analysis, and a pooled analysis, CYP2D6 PMs treated with agents dependent on CYP2D6 metabolism to form an active metabolite can experience a decline in antidepressant effect. Based on a population analysis and two case studies, CYP2D6 UMs treated with antidepressants that are CYP2D6 substrates and administered in a pharmacologically active form do not experience an antidepressant effect due to the agent being too rapidly eliminated from the body. Conversely, based on prospective trials, population analyses, and case studies, phenotypic and phenoconverted CYP2D6 PMs can experience an increase in concentration-dependent adverse events due to the agent being eliminated too slowly from the body.

CONCLUSIONS

Despite these examples, few large-scale, prospective trials exploring the effect of altered CYP2D6 metabolism on antidepressant outcomes have been conducted. Future clinical trials of CYP2D6-dependent antidepressants should be designed to allow for stratification of treatment outcomes by CYP2D6 metabolizer status.