Influence of the tyrosine hydroxylase val81met polymorphism and catechol-O-methyltransferase val158met polymorphism on the antidepressant effect of milnacipran

Tools for optimising pharmacotherapy in psychiatry (therapeutic drug monitoring, molecular brain imaging and pharmacogenetic tests): focus on antidepressants

Objectives: More than 40 drugs are available to treat affective disorders. Individual selection of the optimal drug and dose is required to attain the highest possible efficacy and acceptable tolerability for every patient.Methods: This review, which includes more than 500 articles selected by 30 experts, combines relevant knowledge on studies investigating the pharmacokinetics, pharmacodynamics and pharmacogenetics of 33 antidepressant drugs and of 4 drugs approved for augmentation in cases of insufficient response to antidepressant monotherapy. Such studies typically measure drug concentrations in blood (i.e. therapeutic drug monitoring) and genotype relevant genetic polymorphisms of enzymes, transporters or receptors involved in drug metabolism or mechanism of action. Imaging studies, primarily positron emission tomography that relates drug concentrations in blood and radioligand binding, are considered to quantify target structure occupancy by the antidepressant drugs in vivo. Results: Evidence is given that in vivo imaging, therapeutic drug monitoring and genotyping and/or phenotyping of drug metabolising enzymes should be an integral part in the development of any new antidepressant drug.Conclusions: To guide antidepressant drug therapy in everyday practice, there are multiple indications such as uncertain adherence, polypharmacy, nonresponse and/or adverse reactions under therapeutically recommended doses, where therapeutic drug monitoring and cytochrome P450 genotyping and/or phenotyping should be applied as valid tools of precision medicine.

Effect of catechol-O-methyltransferase Val(108/158)Met polymorphism on antidepressant efficacy of fluvoxamine

Rationale

The catechol-O-methyltransferase (COMT) enzyme inactivates catecholamines, and the COMT Val(108/158)Met polymorphism (rs4680) influences the enzyme activity. Recent clinical studies found a significant effect of rs4680 on antidepressant response to fluoxetine and paroxetine, but several other studies were negative. No study considered drug plasma levels as possible nuisance covariate.

Objectives

We studied the effect of rs4680 on response to fluvoxamine antidepressant monotherapy.

Patients and methods

Forty-one consecutively admitted inpatients affected by a major depressive episode in course of major depressive disorder were administered fluvoxamine for 6 weeks. Changes in severity of depression were assessed with weekly Hamilton Depression ratings and analyzed with repeated measures ANOVA in the context of General Linear Model, with rs4680 and fluvoxamine plasma levels as factors.

Results

rs4680 significantly interacted with time in affecting antidepressant response to fluvoxamine, with outcome being inversely proportional to the enzyme activity: better effects in Met-carriers, worse effects in Val/Val homozygotes. The effect became significant at the fourth week of treatment, and influence final response rates. Fluvoxamine plasma levels had marginal effects on outcome.

Conclusions

This is the first study that reports a positive effect of rs4680 on response to fluvoxamine, and the third independent report of its influence on response to selective 5-HT reuptake inhibitors (SSRIs). Our findings support the hypothesis that factors affecting catecholaminergic neurotransmission might contribute to shape the individual response to antidepressants irrespective of their primary molecular target.

Association between COMT gene Val108/158Met and antidepressive treatment response: A meta-analysis

Multiple antidepressive treatment methods are widely used in the clinic, but different patients showed considerable differences in response to the same treatment. The catechol-O-methyltransferase (COMT) rs4680 polymorphism is involved in the antidepressive treatment reaction; however, the results in different studies are inconsistent. Thus, we performed a meta-analysis to explore the association of the COMT rs4680 polymorphism with the treatment response in major depressive disorder (MDD) patients. An online search was performed through PubMed, EMBASE and the Cochrane library up to December 2018. The odds ratios (ORs), 95% confidence intervals (95% CI) and heterogeneity were calculated in four genetic models. Subgroup analysis and Galbraith plot were carried out to detect the potential source of heterogeneity. Sensitivity and publication bias analyses were performed to identify the reliability of the results. A total of 11 studies involving 2845 individuals were included in this meta-analysis. The results of the subgroup analysis indicated that patients who carried the G allele had remission or a better response to electroconvulsive therapy (ECT) in four genetic models. Excluding the studies that might lead to heterogeneity, overall ORs were recalculated, and no obvious association between rs4680 polymorphism and therapeutic reaction was detected in the allelic, recessive and additive models. In the dominant model, COMT rs4680 variants showed significant associations with antidepressive treatment, but the result was highly dependent on the individual study. In addition, the patients with the GG or AG + GG genotype in comparison to AA were associated with a better response to ECT treatment. However, due to the small number of studies using ECT treatment, we suggest that more research should be performed to verify this result.

Systems pharmacogenomics - gene, disease, drug and placebo interactions: a case study in COMT

Disease, drugs and the placebos used as comparators are inextricably linked in the methodology of the double-blind, randomized controlled trial. Nonetheless, pharmacogenomics, the study of how individuals respond to drugs based on genetic substrate, focuses primarily on the link between genes and drugs, while the link between genes and disease is often overlooked and the link between genes and placebos is largely ignored. Herein, we use the example of the enzyme catechol-O-methyltransferase to examine the hypothesis that genes can function as pharmacogenomic hubs across system-wide regulatory processes that, if perturbed in andomized controlled trials, can have primary and combinatorial effects on drug and placebo responses.

Genetic variants in major depressive disorder: From pathophysiology to therapy

In spite of promising preclinical results there is a decreasing number of new registered medications in major depression. The main reason behind this fact is the lack of confirmation in clinical studies for the assumed, and in animals confirmed, therapeutic results. This suggests low predictive value of animal studies for central nervous system disorders. One solution for identifying new possible targets is the application of genetics and genomics, which may pinpoint new targets based on the effect of genetic variants in humans. The present review summarizes such research focusing on depression and its therapy. The inconsistency between most genetic studies in depression suggests, first of all, a significant role of environmental stress. Furthermore, effect of individual genes and polymorphisms is weak, therefore gene x gene interactions or complete biochemical pathways should be analyzed. Even genes encoding target proteins of currently used antidepressants remain non-significant in genome-wide case control investigations suggesting no main effect in depression, but rather an interaction with stress. The few significant genes in GWASs are related to neurogenesis, neuronal synapse, cell contact and DNA transcription and as being nonspecific for depression are difficult to harvest pharmacologically. Most candidate genes in replicable gene x environment interactions, on the other hand, are connected to the regulation of stress and the HPA axis and thus could serve as drug targets for depression subgroups characterized by stress-sensitivity and anxiety while other risk polymorphisms such as those related to prominent cognitive symptoms in depression may help to identify additional subgroups and their distinct treatment. Until these new targets find their way into therapy, the optimization of current medications can be approached by pharmacogenomics, where metabolizing enzyme polymorphisms remain prominent determinants of therapeutic success.

Progress in Elucidating Biomarkers of Antidepressant Pharmacological Treatment Response: A Systematic Review and Meta-analysis of the Last 15 Years

BACKGROUND

Antidepressant drugs are widely prescribed, but response rates after 3 months are only around one-third, explaining the importance of the search of objectively measurable markers predicting positive treatment response. These markers are being developed in different fields, with different techniques, sample sizes, costs, and efficiency. It is therefore difficult to know which ones are the most promising.

OBJECTIVE

Our purpose was to compute comparable (i.e., standardized) effect sizes, at study level but also at marker level, in order to conclude on the efficacy of each technique used and all analyzed markers.

METHODS

We conducted a systematic search on the PubMed database to gather all articles published since 2000 using objectively measurable markers to predict antidepressant response from five domains, namely cognition, electrophysiology, imaging, genetics, and transcriptomics/proteomics/epigenetics. A manual screening of the abstracts and the reference lists of these articles completed the search process.

RESULTS

Executive functioning, theta activity in the rostral Anterior Cingular Cortex (rACC), and polysomnographic sleep measures could be considered as belonging to the best objectively measured markers, with a combined d around 1 and at least four positive studies. For inter-category comparisons, the approaches that showed the highest effect sizes are, in descending order, imaging (combined d between 0.703 and 1.353), electrophysiology (0.294-1.138), cognition (0.929-1.022), proteins/nucleotides (0.520-1.18), and genetics (0.021-0.515).

CONCLUSION

Markers of antidepressant treatment outcome are numerous, but with a discrepant level of accuracy. Many biomarkers and cognitions have sufficient predictive value (d ≥ 1) to be potentially useful for clinicians to predict outcome and personalize antidepressant treatment.

Blood-based biomarkers predicting response to antidepressants

Major depressive disorder is a common, serious and in some cases, life-threatening condition and affects approximately 350 million people globally. Although there is effective treatment available for it, more than 50% of the patients fail to respond to the first antidepressant they receive. The selection of a distinct treatment is still exclusively based on clinical judgment without incorporating lab-derived objective measures. However, there is growing evidence of biomarkers that it helps to improve diagnostic processes and treatment algorithms. Here genetic markers and blood-based biomarkers of the monoamine pathways, inflammatory pathways and the hypothalamic-pituitary-adrenal (HPA) axis are reviewed. Promising findings arise from studies investigating inflammatory pathways and immune markers that may identify patients suitable for anti-inflammatory based treatment regimes. Next, an early normalization of a disturbed HPA axis or depleted neurotrophic factors may predict stable treatment response. Genetic markers within the serotonergic system may identify patients who are vulnerable because of stressful life events, but evidence for guiding treatment regimes still is inconsistent. Therefore, there is still a great need for studies investigating and validating biomarkers for the prediction of treatment response to facilitate the treatment selection and shorten the time to remission and thus provide personalized medicine in psychiatry.

COMT Val(158) Met genotype is associated with reward learning: a replication study and meta-analysis

Identifying mechanisms through which individual differences in reward learning emerge offers an opportunity to understand both a fundamental form of adaptive responding as well as etiological pathways through which aberrant reward learning may contribute to maladaptive behaviors and psychopathology. One candidate mechanism through which individual differences in reward learning may emerge is variability in dopaminergic reinforcement signaling. A common functional polymorphism within the catechol-O-methyl transferase gene (COMT; rs4680, Val(158) Met) has been linked to reward learning, where homozygosity for the Met allele (linked to heightened prefrontal dopamine function and decreased dopamine synthesis in the midbrain) has been associated with relatively increased reward learning. Here, we used a probabilistic reward learning task to asses response bias, a behavioral form of reward learning, across three separate samples that were combined for analyses (age: 21.80 ± 3.95; n = 392; 268 female; European-American: n = 208). We replicate prior reports that COMT rs4680 Met allele homozygosity is associated with increased reward learning in European-American participants (β = 0.20, t = 2.75, P < 0.01; ΔR(2) = 0.04). Moreover, a meta-analysis of 4 studies, including the current one, confirmed the association between COMT rs4680 genotype and reward learning (95% CI -0.11 to -0.03; z = 3.2; P < 0.01). These results suggest that variability in dopamine signaling associated with COMT rs4680 influences individual differences in reward which may potentially contribute to psychopathology characterized by reward dysfunction.

Serotonin pathway polymorphisms and the treatment of major depressive disorder and anxiety disorders

While antidepressants are widely used to treat major depressive disorder and anxiety disorders, only half of the patients will respond to antidepressant treatment and only a third of patients will experience a remission of symptoms. Identification of genetic biomarkers that predict antidepressant treatment response could thus greatly improve current clinical practice by providing guidance on which drug to use for which patient. Most antidepressant drugs for the treatment of depression and anxiety disorders have effects on the serotonergic neurotransmitter system; thus, genetic polymorphisms in the genes involved in this pathway represent logical candidates for investigation. This article reviews recent findings on the pharmacogenetics of antidepressant drugs with a focus on serotonergic pathway polymorphisms and discusses future clinical applications.

Bcl1 polymorphism of the glucocorticoid receptor gene and treatment response to milnacipran and fluvoxamine in Japanese patients with depression

BACKGROUND

Polymorphisms in the glucocorticoid receptors (GRs) have been widely studied with rather less emphasis on relating their differences with possible pharmacological treatment outcomes. The purpose of this study was to investigate whether Bcl1 polymorphisms of GRs are associated with the antidepressant effect of milnacipran, a serotonin noradrenaline reuptake inhibitor (SNRI), and fluvoxamine, a selective serotonin reuptake inhibitor (SSRI), in Japanese patients with depression.

METHODS

Patients were prescribed either milnacipran (n = 98) or fluvoxamine (n = 95). The severity of depression was assessed with the Montgomery-Åsberg Depression Rating Scale (MADRS) at 0, 1, 2, 4 and 6 weeks of treatment.

RESULTS

Both agents were similarly effective in reducing MADRS scores in 6 weeks. In all subjects receiving milnacipran or fluvoxamine, our data showed no significant interaction between Bcl1 polymorphisms and therapeutic effects. However, when milnacipran- and fluvoxamine-treated subjects were analyzed independently, patients with G allele in Bcl1 polymorphism had a significantly better response to fluvoxamine than those with C/C genotype. On the other hand, no significant relationship was found between treatment response to milnacipran and Bcl1 polymorphism.

CONCLUSION

Bcl1 polymorphism may be one of the genetic factors in predicting treatment response to SSRI but not SNRI in Japanese patients with depression.

Promoter variation in the catechol-O-methyltransferase gene is associated with remission of symptoms during fluvoxamine treatment for major depression

We investigated the association between remission of depressive symptoms in fluvoxamine treatment and catechol-O-methyltransferase (COMT) gene. Sixteen SNPs in the COMT gene were investigated in 123 outpatients with major depression. Three single nucleotide polymorphisms located in the 5' region were associated with remission in fluvoxamine-treated outpatients with moderate to severe depression.

Are there meaningful biomarkers of treatment response for depression?

During the past decades, the prevalence of affective disorders has been on the rise globally, with only one out of three patients achieving remission in acute treatment with antidepressants. The identification of physiological markers that predict treatment course proves useful in increasing therapeutic success. On the basis of well-documented, recent findings in depression research, we highlight and discuss the most promising biomarkers for antidepressant therapy response. These include genetic variants and gene expression profiles, proteomic and metabolomic markers, neuroendocrine function tests, electrophysiology and imaging techniques. Ultimately, this review proposes an integrative use of biomarkers for antidepressant treatment outcome.

Construction of drug network based on side effects and its application for drug repositioning

Drugs with similar side-effect profiles may share similar therapeutic properties through related mechanisms of action. In this study, a drug-drug network was constructed based on the similarities between their clinical side effects. The indications of a drug may be inferred by the enriched FDA-approved functions of its neighbouring drugs in the network. We systematically screened new indications for 1234 drugs with more than 2 network neighbours, 36.87% of the drugs achieved a performance score of Normalized Discounted Cumulative Gain in the top 5 positions (NDCG@5)≥0.7, which means most of the known FDA-approved indications were well predicted at the top 5 positions. In particular, drugs for diabetes, obesity, laxatives and antimycobacterials had extremely high performance with more than 80% of them achieving NDCG@5≥0.7. Additionally, by manually checking the predicted 1858 drug-indication pairs with Expression Analysis Systematic Explorer (EASE) score≤10⁻⁵ (EASE score is a rigorously modified Fisher exact test p value), we found that 80.73% of such pairs could be verified by preclinical/clinical studies or scientific literature. Furthermore, our method could be extended to predict drugs not covered in the network. We took 98 external drugs not covered in the network as the test sample set. Based on our similarity criteria using side effects, we identified 41 drugs with significant similarities to other drugs in the network. Among them, 36.59% of the drugs achieved NDCG@5≥0.7. In all of the 106 drug-indication pairs with an EASE score≤0.05, 50.94% of them are supported by FDA approval or preclinical/clinical studies. In summary, our method which is based on the indications enriched by network neighbors may provide new clues for drug repositioning using side effects.

From pharmacogenetics to pharmacogenomics: the way toward the personalization of antidepressant treatment

OBJECTIVE

Major depressive disorder is the most common psychiatric disorder, worldwide, yet response and remission rates are still unsatisfactory. The identification of genetic predictors of antidepressant (AD) response could provide a promising opportunity to improve current AD efficacy through the personalization of treatment. The major steps and findings along this path are reviewed together with their clinical implications and limitations.

METHOD

We systematically reviewed the literature through MEDLINE and Embase database searches, using any word combination of "antidepressant," "gene," "polymorphism," "pharmacogenetics," "genome-wide association study," "GWAS," "response," and "adverse drug reactions." Experimental works and reviews published until March 2012 were collected and compared.

RESULTS

Numerous genes pertaining to several functional systems were associated with AD response. The more robust findings were found for the following genes: solute carrier family 6 (neurotransmitter transporter), member 4; serotonin receptor 1A and 2A; brain-derived neurotrophic factor; and catechol-O-methyltransferase. Genome-wide association studies (GWASs) provided many top markers, even if none of them reached genome-wide significance.

CONCLUSIONS

AD pharmacogenetics have not produced any knowledge applicable to routine clinical practice yet, as results were mainly inconsistent across studies. Despite this, the rising awareness about methodological deficits of past studies could allow for the identication of more suitable strategies, such as the integration of the GWAS approach with the candidate gene approach, and innovative methodologies, such as pathway analysis and study of depressive endophenotypes.

Pharmacogenetics of antidepressant drugs: an update after almost 20 years of research

Major depressive disorder (MDD) is an emergent cause of personal and socio-economic burden, both for the high prevalence of the disorder and the unsatisfying response rate of the available antidepressant treatments. No reliable predictor of treatment efficacy and tolerance in the single patient is available, thus drug choice is based on a trial and error principle with poor clinical efficiency. Among modulators of treatment outcome, genetic polymorphisms are thought to explain a significant share of the inter-individual variability. The present review collected the main pharmacogenetic findings primarily about antidepressant response and secondly about antidepressant induced side effects, and discussed the main strengths and limits of both candidate and genome-wide association studies and the most promising methodological opportunities and challenges of the field. Despite clinical applications of antidepressant pharmacogenetics are not available yet, previous findings suggest that genotyping may be applied in the clinical practice. In order to reach this objective, further rigorous pharmacogenetic studies (adequate sample size, study of better defined clinical subtypes of MDD, adequate covering of the genetic variability), their combination with the results obtained through complementary methodologies (e.g., pathway analysis, epigenetics, transcriptomics, and proteomics), and finally cost-effectiveness trials are required.

Pharmacogenetics in major depression: a comprehensive meta-analysis

A number of candidate gene studies focused on major depression (MD) and antidepressant (AD) efficacy have been carried out, but results mainly remain inconclusive. We performed a comprehensive meta-analysis of published candidate gene studies focused on AD efficacy in MD to evaluate the cumulative evidence. A random-effect model was applied to study the polymorphisms with genotypic counts available from at least three independent studies. On the base of previous evidence, the analysis was stratified by ethnicity (Caucasian, Asian, and other/mixed), and AD class (SSRIs and mixed/other ADs). Genotypic data were available for 16 polymorphisms in 11 genes. After the exclusion of 5-HTTLPR in SLC6A4 included in another recent meta-analysis, 15 polymorphisms in 11 genes were included in the present meta-analysis (BDNF rs6265, SLC6A4 STin2, HTR1A rs6295, HTR2A rs6311, rs6313 and rs7997012, HTR6 rs1805054, TPH1 rs1800532, SLC6A2 rs5569, COMT rs4680, GNB3 rs5443, FKBP5 rs1360780 and rs3800373, and ABCB1 rs1045642 and rs2032582). Our results suggested that BDNF rs6265 (Val66Met) heterozygous genotype was associated with better SSRIs response compared to the homozygous genotypes, particularly in Asians (OR=1.53, 95%CI 1.12-2.07, p=0.007). SLC6A4 STin2, HTR2A rs6311 and rs7997012, GNB3 rs5443, FKBP5 rs1360780 and rs3800373, and ABCB1 rs2032582 showed associations with AD efficacy, but these results were highly dependent on one or two single studies. In conclusion, our findings suggested the BDNF Val66Met as the best single candidate involved in AD response, with a selective effect on SSRI treatment. Our overall results supported no major effect of any single gene variant on AD efficacy.

No effect of serotoninergic gene variants on response to interpersonal counseling and antidepressants in major depression

OBJECTIVE

Gene variants within the serotonin pathway have been associated with major depressive disorder (MDD) treatment outcomes, however a possible different modulation on pharmacological or psychological treatments has never been investigated.

METHODS

One hundred sixty MDD patients were partially randomized to either inter-personal counseling (IPC) or antidepressants. The primary outcome was remission at week 8. Five serotonergic polymorphisms were investigated (COMT rs4680, HTR1A rs6295, HTR2A rs2224721, HTR2A rs7997012 and SLC6A4 rs421417).

RESULTS

IPC (n=43) and antidepressant (n=117) treated patients did not show any difference in remission rates at week 8 (corrected for baseline severity, age and center). None of the studied gene variants impacted on response and remission rates at week 8 neither in the IPC nor in the antidepressant group. An analysis of the whole sample showed a trend of association between rs7997012 AA genotype and a better treatment outcome.

CONCLUSION

Our study confirms that IPC is an effective psychological intervention comparable to antidepressants in mild-moderate MDD. Polymorphisms related to the serotonin system did not exert a major effect on clinical outcomes in none of the treatment groups.

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.

Variation in the catechol-O-methyltransferase (COMT) gene and treatment response to venlafaxine XR in generalized anxiety disorder

Antidepressant drugs are the preferred choice for the treatment of generalized anxiety disorder (GAD). However, the choice of pharmacotherapy is determined on a trial-and-error basis, as the underlying mechanisms of treatment response are unknown. We examined whether the COMT gene, which has been known to play a role in antidepressant treatment response in major depressive disorder (MDD), has a pharmacogenetic effect in antidepressant treatment response in GAD. In our study, 156 patients diagnosed with GAD received venlafaxine XR treatment as part of an 18-month relapse prevention study. Genotypes were obtained for the COMT functional variant rs4680 (Val158Met) for all patients; however, pharmacogenetic analysis was only conducted for the European American population (n=112). We found no significant association between our primary Hamilton Anxiety Scale outcome measure and rs4680. However, we did find a nominally significant allelic association between this variant and a secondary treatment outcome measure (CGI-I) in our European American population (n=112). Furthermore, we show a slight dominant effect of the A-allele with the CGI-I measure in the European American population indicating a possible pharmacogenetic role of rs4680 in antidepressant treatment outcome in GAD. Further studies in a larger population are needed to confirm this effect.

Pharmacogenetics of antidepressant drugs: current clinical practice and future directions

While antidepressants are widely used to treat mood and anxiety disorders, only half of the patients will respond to antidepressant treatment and only one-third of patients experience a full remission of symptoms. The identification of genetic biomarkers that predict antidepressant-treatment response can improve current clinical practice. This is an emerging field known as pharmacogenetics, which comprises of genetic studies on both the pharmacokinetics and pharmacodynamics of treatment response. Recent studies on antidepressant-treatment response have focused on both aspects of pharmacogenetics research, identifying new candidate genes that may predict better treatment response for patients. This paper reviews recent findings on the pharmacogenetics of antidepressant drugs and future clinical applications. Ultimately, these studies should lead to the use of genetic testing to guide the use of antidepressants in clinical practice.

Recurrence of bipolar mania is associated with catechol-O-methyltransferase Val(108/158)Met polymorphism

BACKGROUND

Catechol-O-methyltransferase (COMT) inactivates catecholamines, and a G-A transition in the COMT gene (rs4680) influences the enzyme activity and the interaction between cortical and subcortical dopaminergic neurotransmission. In patients affected by bipolar disorder rs4680 can influence antidepressant response and the propensity to develop psychotic symptoms, with the Met/Met genotype exerting a protective role. The same genotype could influence other dopamine-associated psychopathological features, such as mania.

METHODS

We genotyped rs4680 in a sample of 163 patients affected by bipolar disorder type I, and assessed the personal history of recurrence of the illness.

RESULTS

We observed a significant association between homozygosis for the rs4680 COMT low-activity variant and a reduced recurrence of manic, but not depressive, episodes during the course of the illness.

CONCLUSIONS

We suggest that rs4680 could be an inheritable aspect of the mechanisms of dopamine regulation that influence the individual susceptibility of patients with bipolar disorder to develop manic episodes of illness.

Pharmacogenetics of antidepressants

Up to 60% of depressed patients do not respond completely to antidepressants (ADs) and up to 30% do not respond at all. Genetic factors contribute for about 50% of the AD response. During the recent years the possible influence of a set of candidate genes as genetic predictors of AD response efficacy was investigated by us and others. They include the cytochrome P450 superfamily, the P-glycoprotein (ABCB1), the tryptophan hydroxylase, the catechol-O-methyltransferase, the monoamine oxidase A, the serotonin transporter (5-HTTLPR), the norepinephrine transporter, the dopamine transporter, variants in the 5-hydroxytryptamine receptors (5-HT1A, 5-HT2A, 5-HT3A, 5-HT3B, and 5-HT6), adrenoreceptor beta-1 and alpha-2, the dopamine receptors (D2), the G protein beta 3 subunit, the corticotropin releasing hormone receptors (CRHR1 and CRHR2), the glucocorticoid receptors, the c-AMP response-element binding, and the brain-derived neurotrophic factor. Marginal associations were reported for angiotensin I converting enzyme, circadian locomotor output cycles kaput protein, glutamatergic system, nitric oxide synthase, and interleukin 1-beta gene. In conclusion, gene variants seem to influence human behavior, liability to disorders and treatment response. Nonetheless, gene × environment interactions have been hypothesized to modulate several of these effects.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Personalized medicine for depression: can we match patients with treatments?

OBJECTIVE

Response to specific depression treatments varies widely among individuals. Understanding and predicting that variation could have great benefits for people living with depression.

METHOD

The authors describe a conceptual model for identifying and evaluating evidence relevant to personalizing treatment for depression. They review evidence related to three specific treatment decisions: choice between antidepressant medication and psychotherapy, selection of a specific antidepressant medication, and selection of a specific psychotherapy. They then discuss potential explanations for negative findings as well as implications for research and clinical practice.

RESULTS

Many previous studies have examined general predictors of outcome, but few have examined true moderators (predictors of differential response to alternative treatments). The limited evidence indicates that some specific clinical characteristics may inform the choice between antidepressant medication and psychotherapy and the choice of specific antidepressant medication. Research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the choice between medication and psychotherapy, the selection of specific medication, or the selection of a specific psychotherapy.

CONCLUSIONS

While individuals vary widely in response to specific depression treatments, the variability remains largely unpredictable. Future research should focus on identifying true moderator effects and should consider how response to treatments varies across episodes. At this time, our inability to match patients with treatments implies that systematic follow-up assessment and adjustment of treatment are more important than initial treatment selection.

Catechol O-methyltransferase pharmacogenomics and selective serotonin reuptake inhibitor response

We applied a systematic pharmacogenetic approach to investigate the role of genetic variation in the gene encoding catechol O-methyltransferase (COMT) in individual variation in selective serotonin reuptake inhibitor (SSRI) response among depressed patients. In all, 23 single-nucleotide polymorphisms (SNPs) in COMT were genotyped using DNA from the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study (N=1914). One SNP, rs13306278, located in the distal promoter region of COMT, showed significant association with remission in White non-Hispanic (WNH) subjects (P=0.038). Electromobility shift assay for rs13306278 showed alternation in the ability of the variant sequence to bind nuclear proteins. A replication study was performed using samples from the Mayo Clinic Pharmacogenetics Research Network Citalopram/Escitalopram Pharmacogenomic study (N=422) that demonstrated a similar trend for association. Our findings suggest that novel genetic markers in the COMT distal promoter may influence SSRI response phenotypes.

Association between catechol-O-methyltransferase Val(108/158)Met polymorphism and psychotic features of bipolar disorder

BACKGROUND

Catechol-O-methyltransferase (COMT) inactivates catecholamines, and a G-A transition in the COMT gene (rs4680) influences the enzyme activity and the interaction between cortical and subcortical dopaminergic neurotransmission. Studies in healthy participants and in patients affected by schizophrenia suggested that rs4680 can influence the propensity to develop psychotic symptoms, with the Met low-activity allele exerting a protective role. Previous studies in bipolar patients reported non-significant trends in the same direction.

METHODS

We genotyped rs4680 in a sample of 467 patients affected by bipolar disorder type I with or without a previous illness episode with psychotic features (DSM-IV criteria: delusions or hallucinations).

RESULTS

We observed a significant association between homozygosis for the rs4680 COMT low-activity variant and a reduced risk of experiencing illness episodes with psychotic features during the course of the illness. The Met/Met genotype was more common among patients without psychotic features, and while in the non-psychotic group the Val/Val genotype had a distribution similar to Met/Met, in the group of patients who experienced episodes with psychotic symptoms the proportion of Val/Val homozygotes was the double of Met/Met.

CONCLUSIONS

We suggest that rs4680 could be an inheritable aspect of the mechanisms of dopamine regulation that could influence the individual susceptibility of patients with bipolar disorder to develop psychotic symptoms.

Pharmacogenetics of antidepressive treatment

The search of the genetic predictors of response to antidepressants is a rapidly expanding field. A large number of clinical studies are reporting partly inconsistent results. Emerging new results focus on new candidate single nucleotide polymorphisms--particularly in the 5HT2a-receptor gene and the gene coding for the co-chaperone FKBP5. The impact of the 5HTTLPR polymorphism on therapeutic outcome and side effects under treatment with SSRIs has to be viewed in a more complex manner than previously proposed. All replicable genetic associations display only a very modest effect. Despite of enormous research efforts, currently pharmacogenetics of therapeutic effects and of side effects of antidepressants are unable to guide decisions on the selection of the most beneficial drug for an individual patient.

Review and meta-analysis of antidepressant pharmacogenetic findings in major depressive disorder

This systematic review summarizes pharmacogenetic studies on antidepressant response and side effects. Out of the 17 genes we reviewed, 8 genes were entered into the meta-analysis (SLC6A4, HTR1A, HTR2A, TPH1, gene encoding the beta-3 subunit, brain-derived neurotrophic factor (BDNF), HTR3A and HTR3B). TPH1 218C/C genotype (7 studies, 754 subjects) was significantly associated with a better response (odds ratio, OR=1.62; P=0.005) with no heterogeneity between ethnicities. A better response was also observed in subjects with the Met variant within the BDNF 66Val/Met polymorphism (4 studies, 490 subjects; OR=1.63, P=0.02). Variable number of tandem repeats polymorphism within intron 2 (STin2) 12/12 genotype showed a trend toward a better response in Asians (STin2: 5 studies, 686 subjects; OR=3.89, P=0.03). As for side effects, pooled ORs of serotonin transporter gene promoter polymorphism (5-HTTLPR) l (9 studies, 2642 subjects) and HTR2A -1438G/G (7 studies, 801 subjects) were associated with a significant risk modulation (OR=0.64, P=0.0005) and (OR=1.91, P=0.0006), respectively. Interestingly, this significance became more robust when analyzed with side effect induced by selective serotonin reuptake inhibitors only (5-HTTLPR: P=0.0001, HTR2A: P<0.0001). No significant result could be observed for the other variants. These results were not corrected for multiple testing in each variant, phenotype and subcategory. This would have required a Bonferroni significance level of P<0.0023. Although some heterogeneity was present across studies, our finding suggests that 5-HTTLPR, STin2, HTR1A, HTR2A, TPH1 and BDNF may modulate antidepressant response.

Catechol-O-methyltransferase val108/158met genotype, major depressive disorder and response to selective serotonin reuptake inhibitors in major depressive disorder

The functional val108/158met polymorphism of the COMT gene (rs4680) was evaluated in major depressive disorder (MDD), and in the treatment response to antidepressants in MDD. We could not demonstrate any significant difference in the distribution of this COMT single-nucleotide polymorphism (SNP) in the treatment response to selective serotonin reuptake inhibitors or between patients with MDD and control subjects.

The promise and reality of pharmacogenetics in psychiatry

Existing psychotropic medications for the treatment of mental illnesses, including antidepressants, mood stabilizers, and antipsychotics, are clinically suboptimal. They are effective in only a subset of patients or produce partial responses, and they are often associated with debilitating side effects that discourage adherence. There is growing enthusiasm in the promise of pharmacogenetics to personalize the use of these treatments to maximize their efficacy and tolerability; however, there is still a long way to go before this promise becomes a reality. This article reviews the progress that has been made in research toward understanding how genetic factors influence psychotropic drug responses and the challenges that lie ahead in translating the research findings into clinical practices that yield tangible benefits for patients with mental illnesses.

Enhancing outcomes from major depression: using antidepressant combination therapies with multifunctional pharmacologic mechanisms from the initiation of treatment

Traditional guidelines call for treatment of major depression with a sequence of single antidepressants. Augmentation with a second agent generally only occurs when the first agent is well tolerated and when it also provides at least some symptomatic improvement on its own. Since this standard approach leads to low rates of attaining and sustaining remission by the first agent, with diminishing returns for each subsequent agent, there is growing dissatisfaction with this approach to the treatment of major depression. One new trend is to attempt to enhance the rates of sustained remission from a major depressive episode by combining two therapeutic agents from the very initiation of treatment of a major depressive episode.

Traditional treatment of major depression begins with a single “first line” antidepressant, and if it does not work or is not tolerated, trying another and then another. Unfortunately, this strategy results in disappointing remission rates for the first antidepressant (Figure 1), and disappointing rates of maintaining any improvement that is attained by this first agent because of high relapse rates over the next year despite continuing treatment with the first antidepressant (Figure 2A). And that is the good news. The bad news is that with each subsequent antidepressant treatment administered remission rates are progressively reduced (Figure 1). For those patients who do improve, they are progressively less likely to sustain their therapeutic gains despite continuing to take the drug that led to their initial improvement (Figure 2).

Application of pharmacogenomics to clinical problems in depression

The goal of this article is to review the literature for evidence supporting an association between polymorphisms within drug target genes and clinical outcomes for treating depression, with a purpose to identify a research area having the most promising potential to be introduced into clinical settings, and thus, discussing the perspectives of genotyping in antidepressant therapy. A total of 67 articles were identified. Polymorphic sites within the serotonin transporter gene promoter, 5-HTTLPR, were the most studied polymorphisms. All except three articles were designed as cohort studies. The other three articles included two meta-analyses and one decision-analytic model. The main finding from these meta-analyses was that the l variant was associated with a better response to selective serotonin reuptake inhibitors. The main conclusion from the decision-analytic model study was that performing genetic testing before prescribing antidepressant treatment may lead to greater numbers of patients experiencing remission early in treatment. Clinical outcomes of genotyping this polymorphism were evaluated by improvement of depression score, odds ratio and absolute risk reduction.

Pharmacogenomics of antidepressant drugs

While antidepressant pharmacotherapy is an effective treatment of depression, it is still hampered by the slow onset of appreciable clinical improvement and a series of side effects. Moreover, a substantial group of patients does not achieve remission or fails to respond at all. One possible source accounting for these variations in treatment outcome are genetic differences. In recent years a number of pharmacogenetic studies on antidepressant drugs have been published. This manuscript summarizes findings related to the pharmacogenetics of genes involved in the pharmacokinetics as well as pharmacodynamics of antidepressants to date. Illustrated by examples from current candidate gene- and whole genome association studies, this manuscript critically discusses aspects of pharmacogenetic studies in antidepressant response related to study design and clinical relevance.

Variation in catechol-O-methyltransferase is associated with duloxetine response in a clinical trial for major depressive disorder

BACKGROUND

The study objective was to evaluate variations in genes implicated in antidepressant mechanism of action for association with response to duloxetine treatment in major depressive disorder (MDD).

METHODS

We assessed response over 6 weeks in 250 duloxetine-treated Caucasian patients in a randomized, double-blind study of patients with MDD. Single nucleotide polymorphisms (SNPs) were genotyped in 19 candidate genes selected based on evidence for involvement in antidepressant mechanism of action. Primary analysis examined baseline to end point reduction in the 17-item Hamilton Depression Rating Scale (HAMD17) total score, using a set-based test for association for each gene. Follow-up analyses examined individual SNPs within any significant gene for association with reduction in HAMD17 and 30-item Inventory of Depressive Symptomatology-Clinician Rated (IDS-C-30).

RESULTS

After correction for multiple comparisons, only COMT was associated with change in HAMD17 (experiment wide p = .018). Peak association was detected with rs165599 (p = .006), which accounted for approximately 3% of variance in HAMD17 change and >4% of variance in IDS-C-30 change (p = .001). The least-squared mean change (SE) in HAMD17 score by rs165599 genotype was -10.8 (1.2), -8.7 (.6), and -6.5 (.7) for patients with GG, GA, and AA genotypes, respectively. For SNPs in serotonin 2A receptor (HTR2A) previously associated with citalopram response, including rs7997012, no significant evidence of association with duloxetine response was identified.

CONCLUSIONS

Single nucleotide polymorphisms in COMT were associated with symptom change in duloxetine-treated patients with MDD. If replicated, the magnitude of the COMT genotype effect is of clinical relevance.

The catechol-O-methyltransferase Val(108/158)Met polymorphism affects antidepressant response to paroxetine in a naturalistic setting

RATIONALE

The noradrenergic and dopaminergic systems are targets for antidepressants and are stimulated by serotonergic antidepressant drugs. The COMT enzyme inactivates catecholamines, and the COMT Val(108/158)Met polymorphism (rs4680) influences the enzyme activity. Clinical studies on the effect of rs4680 on antidepressant response gave contrasting results.

OBJECTIVES

We studied the effect of rs4680 on response to paroxetine antidepressant monotherapy at doses administered upon clinical need.

MATERIALS AND METHODS

Fifty-five consecutively referred outpatients affected by a major depressive episode without psychotic features in course of major depressive disorder were administered paroxetine at a mean daily dose of 31.64 mg for 1 month. Changes in severity of depression were assessed with weekly Hamilton depression ratings and analyzed with repeated measures analysis of variance in the context of general linear model, taking into account potential confounding variables (age, sex, number of previous illness episodes, duration of current episode and paroxetine daily dose).

RESULTS

rs4680 significantly interacted with time in affecting antidepressant response to paroxetine, with outcome being inversely proportional to the enzyme activity: better effects in Met/Met homozygotes, worse effects in Val/Val homozygotes and intermediate effects in heterozygotes. The effect became significant at the third week of treatment. Paroxetine daily dose was proportional to baseline severity, but did not influence outcome.

CONCLUSIONS

This is the first study that reports a positive effect of rs4680 on response to selective serotonin reuptake inhibitors monotherapy in a Caucasian sample. Our findings support the hypothesis that factors affecting catecholaminergic neurotransmission might contribute to shape the individual response to antidepressants.

Common genetic, clinical, demographic and psychosocial predictors of response to pharmacotherapy in mood and anxiety disorders

The aim of this study is to summarize available knowledge about common genetic, clinical, demographic and psychosocial predictors of response to pharmacotherapy in mood and anxiety disorders. A literature search was carried out by using MEDLINE and references of selected articles. The search included articles published up to March 2008. The main genetic finding concerns the serotonin transporter gene promoter polymorphisms, the long variant of which seems to be related to a positive response to therapy in mood disorders and could also have a role in the treatment of anxiety disorders. Among other predictors, the main factors common to both classes of disorder are comorbid axis II disorders and early onset of illness, which are related to a worse response to therapy and concomitant good physical conditions, absence of earlier treatments, early administration and response to therapies, and higher self- directedness, which is related to a better outcome. Many common predictors have been identified and these seem to be related to features covering the totality of patients that go beyond specific characteristics of single disorders. Possible limitations and suggestions for future research based on a more integrated vision of human complexity are discussed.

Improving the prediction of treatment response in depression: integration of clinical, cognitive, psychophysiological, neuroimaging, and genetic measures

Antidepressants are important in the treatment of depression, and selective serotonin reuptake inhibitors are first-line pharmacologic options. However, only 50% to 70% of patients respond to first treatment and <40% remit. Since depression is associated with substantial morbidity, mortality, and family burden, it is unfortunate and demanding on health resources that patients must remain on their prescribed medications for at least 4 weeks without knowing whether the particular antidepressant will be effective. Studies have suggested a number of predictors of treatment response, including clinical, psychophysiological, neuroimaging, and genetics, each with varying degrees of success and nearly all with poor prognostic sensitivity and specificity. Studies are yet to be conducted that use multiple measures from these different domains to determine whether sensitivity and specificity can be improved to predict individual treatment response. It is proposed that a focus on standardized testing methodologies across multiple testing modalities and their integration will be crucial for translation of research findings into clinical practice.