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

Serotonergic receptor gene polymorphism and response to selective serotonin reuptake inhibitors in ethnic Malay patients with first episode of major depressive disorder

The polymorphisms of the 5HTR1A and 5HTR2A receptor genes (rs6295C/G and rs6311G/A) have been evaluated for association with SSRI treatment outcome in various populations with different results. The present study was carried out to determine the association between genotypes of HTR1A-rs6295 and HTR2A-rs6311 with SSRI treatment outcome among the ethnic Malay patients diagnosed with first-episode major depressive disorder (MDD). The patients were recruited from four tertiary hospitals in the Klang Valley region of Malaysia. Predefined efficacy phenotypes based on 25% (partial early response) and 50% (clinical efficacy response) reduction in Montgomery Asberg Depression Rating Scale-self Rated score (MADRS-S) were adopted for assessment of treatment efficacy in this study. Self-reporting for adverse effects (AE) was documented using the Patient Rated Inventory of Side Effect (PRISE) after treatment with SSRI for up to 6 weeks. Adjusted binary logistic regression between genotypes of the polymorphism obtained using sequencing technique with the treatment outcome phenotypes was performed. The 142 patients recruited were made up of 96 females (67.6%) and 46 males (32.4%). Clinical efficacy and Partial early response phenotypes were not significantly associated with genotypes of HTR1A and HTR2A polymorphism. The GG genotype of HTR2A polymorphism has decreased odds for dizziness (CNS) and increased odds for poor concentration. The GA genotype increases the odd for excessive sweating, diarrhoea, constipation and blurred vision. The CC genotype of HTR1A-rs6295 decreases the odd for nausea/vomiting and increases the odd for anxiety. Thus, some genotypes of HTR1A and HTR2A polymorphism were associated with SSRI treatment outcomes in ethnic Malay MDD patients.

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.

Polymorphisms in genes related to the hypothalamic-pituitary-adrenal axis and antidepressant response - Systematic review

OBJECTIVE

Around 50% of depressed patients do not respond to antidepressants. Evidence from familial studies suggests a genetic component to this. This study investigated whether patients with polymorphisms in genes related to the hypothalamic-pituitary-adrenal (HPA) axis were less likely to respond to antidepressants.

METHOD

EMBASE, MEDLINE, PsycINFO, and the Cochrane Library were searched. Inclusionary criteria were: 1) patients with depression, 2) study of HPA axis-related candidate genes, 3) at least four weeks of antidepressants, and 4) assessment of depressive symptoms dividing patients into non-responders and responders.

RESULTS

Nineteen studies were identified. Non-responders and responders did not differ in single nucleotide polymorphisms (SNPs) in genes encoding arginine vasopressin. Findings were equivocal regarding genes encoding the FK506 binding protein 5 and glucocorticoid and mineralocorticoid receptors. Specific SNPs and haplotypes within genes related to corticotropin-releasing hormone (CRHBP, CRHR1) and melanocortins (POMC) predicted non-responder status.

CONCLUSIONS

Replication studies and additional investigations exploring gene x environment and drug x environment interactions are necessary before pharmacological treatments may be adjusted based on a patient's genetic profile.

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.

Peripheral biomarkers of major depression and antidepressant treatment response: Current knowledge and future outlooks

BACKGROUND

In recent years, we have accomplished a deeper understanding about the pathophysiology of major depressive disorder (MDD). Nevertheless, this improved comprehension has not translated to improved treatment outcome, as identification of specific biologic markers of disease may still be crucial to facilitate a more rapid, successful treatment. Ongoing research explores the importance of screening biomarkers using neuroimaging, neurophysiology, genomics, proteomics, and metabolomics measures.

RESULTS

In the present review, we highlight the biomarkers that are differentially expressed in MDD and treatment response and place a particular emphasis on the most recent progress in advancing technology which will continue the search for blood-based biomarkers.

LIMITATIONS

Due to space constraints, we are unable to detail all biomarker platforms, such as neurophysiological and neuroimaging markers, although their contributions are certainly applicable to a biomarker review and valuable to the field.

CONCLUSIONS

Although the search for reliable biomarkers of depression and/or treatment outcome is ongoing, the rapidly-expanding field of research along with promising new technologies may provide the foundation for identifying key factors which will ultimately help direct patients toward a quicker and more effective treatment for MDD.

Suggested Biomarkers for Major Depressive Disorder

Currently, the diagnosis of major depressive disorder (MDD) mainly relies on clinical examination and subjective evaluation of depressive symptoms. There is no non-invasive, quantitative test available today for the diagnosis of MDD. In MDD, exploration of biomarkers will be helpful in diagnosing the disorder as well as in choosing a treatment, and predicting the treatment response. In this article, it is aimed to review the findings of suggested biomarkers such as growth factors, cytokines and other inflammatory markers, oxidative stress markers, endocrine markers, energy balance hormones, genetic and epigenetic features, and neuroimaging in MDD and to evaluate how these findings contribute to the pathophysiology of MDD, the prediction of treatment response, severity of the disorder, and identification of subtypes. Among these, the findings related to the brain-derived neurotrophic factor, the hypothalamo-pituitary-adrenal axis, cytokines, and neuroimaging may be strong candidates for being biomarkers MDD, and may provide critical information in understanding biological etiology of depression. Although the findings are not sufficient yet, we think that the results of epigenetic studies will also provide very important contributions to the biomarker research in MDD. The availability of biomarkers in MDD will be an advancement that will facilitate the diagnosis of the disorder, treatment choices in the early stages, and prediction of the course of the disorder.

GWAS-based machine learning approach to predict duloxetine response in major depressive disorder

Major depressive disorder (MDD) is one of the most prevalent psychiatric disorders and is commonly treated with antidepressant drugs. However, large variability is observed in terms of response to antidepressants. Machine learning (ML) models may be useful to predict treatment outcomes. A sample of 186 MDD patients received treatment with duloxetine for up to 8 weeks were categorized as "responders" based on a MADRS change >50% from baseline; or "remitters" based on a MADRS score ≤10 at end point. The initial dataset (N = 186) was randomly divided into training and test sets in a nested 5-fold cross-validation, where 80% was used as a training set and 20% made up five independent test sets. We performed genome-wide logistic regression to identify potentially significant variants related to duloxetine response/remission and extracted the most promising predictors using LASSO regression. Subsequently, classification-regression trees (CRT) and support vector machines (SVM) were applied to construct models, using ten-fold cross-validation. With regards to response, none of the pairs performed significantly better than chance (accuracy p > .1). For remission, SVM achieved moderate performance with an accuracy = 0.52, a sensitivity = 0.58, and a specificity = 0.46, and 0.51 for all coefficients for CRT. The best performing SVM fold was characterized by an accuracy = 0.66 (p = .071), sensitivity = 0.70 and a sensitivity = 0.61. In this study, the potential of using GWAS data to predict duloxetine outcomes was examined using ML models. The models were characterized by a promising sensitivity, but specificity remained moderate at best. The inclusion of additional non-genetic variables to create integrated models may improve prediction.

Genome-wide association studies of placebo and duloxetine response in major depressive disorder

We investigated variants associated with treatment response in depressed patients treated with either the antidepressant duloxetine or placebo using a genome-wide approach. Our sample (N=391) included individuals aged 18-75 years, diagnosed with major depressive disorder and treated with either duloxetine or placebo for up to 8 weeks. We conducted genome-wide associations for treatment response as operationalized by percentage change in Montgomery-Åsberg Depression Rating Scale score from baseline, as well as mixed models analyses across five time points. In the placebo-treated subsample (N=205), we observed a genome-wide association with rs76767803 (β=0.69, P=1.25 × 10^-8) upstream of STAC1. STAC1 rs76767803 was also associated with response using mixed model analysis (χ²=3.95; P=0.001). In the duloxetine-treated subsample (N=186), we observed suggestive associations with ZNF385D (rs4261893; β=-0.46, P=1.55 × 10^-5), NCAM1 (rs2303377; β=0.45, P=1.76 × 10^-5) and MLL5 (rs117986340; β=0.91, P=3.04 × 10^-5). Our findings suggest that a variant upstream of STAC1 is associated with placebo response, which might have implications for treatment optimization, clinical trial design and drug development.

Consensus paper of the WFSBP Task Force on Genetics: Genetics, epigenetics and gene expression markers of major depressive disorder and antidepressant response

Major depressive disorder (MDD) is a heritable disease with a heavy personal and socio-economic burden. Antidepressants of different classes are prescribed to treat MDD, but reliable and reproducible markers of efficacy are not available for clinical use. Further complicating treatment, the diagnosis of MDD is not guided by objective criteria, resulting in the risk of under- or overtreatment. A number of markers of MDD and antidepressant response have been investigated at the genetic, epigenetic, gene expression and protein levels. Polymorphisms in genes involved in antidepressant metabolism (cytochrome P450 isoenzymes), antidepressant transport (ABCB1), glucocorticoid signalling (FKBP5) and serotonin neurotransmission (SLC6A4 and HTR2A) were among those included in the first pharmacogenetic assays that have been tested for clinical applicability. The results of these investigations were encouraging when examining patient-outcome improvement. Furthermore, a nine-serum biomarker panel (including BDNF, cortisol and soluble TNF-α receptor type II) showed good sensitivity and specificity in differentiating between MDD and healthy controls. These first diagnostic and response-predictive tests for MDD provided a source of optimism for future clinical applications. However, such findings should be considered very carefully because their benefit/cost ratio and clinical indications were not clearly demonstrated. Future tests may include combinations of different types of biomarkers and be specific for MDD subtypes or pathological dimensions.

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.

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.

Genetic variation in IL-1β, IL-2, IL-6, TSPO and BDNF and response to duloxetine or placebo treatment in major depressive disorder

AIM

This study investigated polymorphisms of five inflammatory-related genes for association with duloxetine and placebo response in patients with major depression.

PATIENTS & METHODS

Twenty SNPs in IL-1β, IL-2, IL-6, TSPO and BDNF were genotyped in major depressive disorder patients treated with either duloxetine (n = 215) or placebo (n = 235) for up to 8 weeks. Treatment response was measured with the Montgomery-Åsberg Depression Rating Scale.

RESULTS

IL-6 variants rs2066992 and rs10242595 were nominally associated with response to duloxetine (p = 0.047 and p = 0.028, respectively). Notably, the variant rs2066992 was also associated with placebo response (p = 0.026). However, none of our results remained significant after correction for multiple testing.

CONCLUSION

Our findings tentatively suggest that IL-6 variants play a role in duloxetine and placebo response, which warrants further investigation.

Pharmacogenetics of major depressive disorder: top genes and pathways toward clinical applications

The pharmacogenetics of antidepressants has been not only a challenging but also frustrating research field since its birth in the 1990s. Indeed, great expectations followed the first evidence of familiar aggregation of antidepressant response. Despite the progress from candidate gene studies to genome-wide association studies (GWAS), results fell out the expectations and they were often inconsistent. Anyway, the cumulative evidence supports the involvement of some genes and molecular pathways in antidepressant efficacy. The best single genes are SLC6A4, HTR2A, BDNF, GNB3, FKBP5, ABCB1, and cytochrome P450 genes (CYP2D6 and CYP2C19). Molecular pathways involved in inflammation and neuroplasticity show the greatest support. The first studies evaluating benefits of genotype-guided antidepressant treatments provided encouraging results and confirmed the relevance of SLC6A4, HTR2A, ABCB1, and cytochrome P450 genes. Further progress in genotyping and data analysis would allow to move forward and complete the understanding of antidepressant pharmacogenetics and its translation into clinical applications.

Pharmacogenetics and analgesic effects of antidepressants in chronic pain management

Antidepressants are widely administered to chronic pain patients, but there is large interindividual variability in their efficacy and adverse effect rates that may be attributed to genetic factors. Studies have attempted to determine the impact of genetic polymorphisms in enzymes and transporters that are involved in antidepressant pharmacokinetics, for example, cytochrome P450 and P-gp. The impacts of genetic polymorphisms in the targets of antidepressants, such as the serotonin receptor or transporter, the noradrenaline transporter and the COMT and monoamine oxydase enzymes, have also been described. This manuscript discusses the current knowledge of the influence of genetic factors on the plasma concentrations, efficacy and adverse effects of the major antidepressants used in pain management.

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.

PPP3CC gene: a putative modulator of antidepressant response through the B-cell receptor signaling pathway

Antidepressant pharmacogenetics represents a stimulating, but often discouraging field. The present study proposes a combination of several methodologies across three independent samples. Genes belonging to monoamine, neuroplasticity, circadian rhythm and transcription factor pathways were investigated in two samples (n=369 and 88) with diagnosis of major depression who were treated with antidepressants. Phenotypes were response, remission and treatment-resistant depression. Logistic regression including appropriate covariates was performed. Genes associated with outcomes were investigated in the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) genome-wide study (n=1861). Top genes were further studied through a pathway analysis. In both original samples, markers associated with outcomes were concentrated in the PPP3CC gene. Other interesting findings were particularly in the HTR2A gene in one original sample and the STAR*D. The B-cell receptor signaling pathway proved to be the putative mediator of PPP3CC's effect on antidepressant response (P=0.03). Among innovative candidates, PPP3CC, involved in the regulation of immune system and synaptic plasticity, seems promising for further investigation.

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.

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.

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.

HTR2A gene-child abuse interaction and association with a history of suicide attempt among Caucasian depressed psychiatric inpatients

BACKGROUND

The serotonin transporter gene polymorphism (5HTTLPR) has been associated with vulnerability for depression after exposure to stressful life event as well as with difference in treatment response to SSRI. Although the A/A genotype of the serotonin receptor SNP (rs7997012) was associated with better citalopram response than the G/G in the STAR⁎D sample, the effects of this SNP in the moderation of child abuse history on the characteristics of mental illnesses are not well understood. We examined if there are similar gene-environment interaction with the SNP.

METHODS

Retrospective chart review of 250 Caucasian depressed psychiatric inpatients, who had genotype for rs7997012. Subjects with each genotype were subcategorized into 2 groups with/without history of child abuse. The history of suicide attempts of each group was compared.

RESULTS

A trend for an interaction was found between the HTR2A genotype and child abuse history influencing the prevalence of suicide attempts. Although each genotype did not show significant difference in the risk of suicide attempt when there was no abuse history, the A carriers (A/A+A/G) showed significantly higher rate of suicide attempt compared to the G/G when there is a history of child abuse (48.4% versus 22.7% respectively, p=0.0050). The likelihood ratio test from the logistic model showed a trend for an interaction between the A/A genotype and abuse history (Odds Ratio 2.10, χ(2)=2.49, p=0.11).

LIMITATIONS

Retrospective study design and small sample size with borderline significance.

CONCLUSIONS

Our findings showed a potential interaction between the HTR2A gene and stressful life events.

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.

Catechol-O-methyltransferase genotype as modifier of superior responses to venlafaxine treatment in major depressive disorder

Responses to venlafaxine treatment in major depressive disorder were stratified by COMT genotypes (Val158Met, rs4680) in a randomized, double-blind, placebo-controlled clinical trial. Improvements in depression scores among subjects with Val/Val genotypes were larger than those in Met/Met genotypes, suggesting that venlafaxine may alter noradrenergic flux differentially according to COMT activity.

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.

Potential role of membrane-bound COMT gene polymorphisms in female depression vulnerability

BACKGROUND

Several polymorphic variants within the catechol-O-methyltransferase (COMT) gene locus have been associated with a number of diverse psychiatric phenotypes including affective disorders. COMT enzyme participates in metabolic pathways involving brain catecholamines, as well as steroid hormones such as estrogens. Given the suggested mood enhancing role of estrogens and the higher prevalence of depression in women, we set out to investigate the potential impact of functional COMT genetic variants on depression and anxiety symptoms in a homogeneous female community sample.

METHODS

We genotyped three common polymorphisms within the COMT gene in a rural female population isolate (n=391) interviewed for the presence of lifetime major depression episodes and generalized anxiety disorder. Furthermore, well validated self-rated questionnaires were administered evaluating state depressive symptoms and neuroticism personality trait. Single-marker and haplotype association analyses were performed.

RESULTS

Two highly correlated markers located in the membrane-bound (MB) COMT promoter region (rs2020917, rs737865) were significantly associated with both self-rated and clinician-rated depressive symptomatology. We did not detect any robust association with generalized anxiety disorder or neuroticism. Exploratory haplotype analysis examining the two promoter markers in combination with the extensively studied val 158met polymorphism (rs4680) did not provide any further support for the contribution of this variant in depressive mood.

LIMITATIONS

The relative small sample size should be considered a limitation of this study.

CONCLUSIONS

Our results provide promising evidence that MB-COMT specific genetic variation may represent an as yet unrecognized genetic factor that influences predisposition to depression amongst females.

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.

Evaluation of genetic models for response in a randomized clinical trial of duloxetine in major depressive disorder

In self-identified white patients with major depressive disorder (N=126) treated with open-label duloxetine (60-120 mg/d), a significant association of (P=0.020) of a composite risk score (based on SLC6A2 rs5569 [G1287A] AA, HTR1A rs6295 [C(-1019)G] GG, and COMT rs174697 AA/AG) with 17-item Hamilton Depression Rating Scale total score change from baseline to 12 weeks was observed.

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.

Psychiatric pharmacogenomics in pediatric psychopharmacology

This article provides an overview of where psychiatric pharmacogenomic testing stands as an emerging clinical tool in modern psychotropic prescribing practice, specifically in the pediatric population. This practical discussion is organized around the state of psychiatric pharmacogenomics research when choosing psychopharmacologic interventions in the most commonly encountered mental illnesses in youth. As with the rest of the topics on psychopharmacology for children and adolescents in this publication, a clinical vignette is presented, this one highlighting a clinical case of a 16 year old genotyped during hospitalization for recalcitrant depression.

Oxytocin and catechol-O-methyltransferase receptor genotype predict the length of the first stage of labor

OBJECTIVE

We aimed to identify genetic factors that influence the rate of the first stage of labor.

STUDY DESIGN

We prospectively enrolled 233 laboring nulliparous parturients. Demographic, clinical, and genetic data were collected. We evaluated the influence of population and individual variability using a nonlinear mixed effects model.

RESULTS

Parturients who were homozygous for "G" at oxytocin receptor gene rs53576 transitioned to active labor later and thus had slower labor. Catechol-O-methyltransferase rs4633 genotype TT was associated with slower latent phase labor. Labor induction with prostaglandin was associated with faster labor, and request for meperidine was associated with slower labor. Birthweight was related inversely to the rate of the active phase.

CONCLUSION

There are demographic, clinical, and genetic factors that influence an individual's rate of labor progress. This information could be used in automated form to improve the prediction of the length of the first stage of labor.

Citalopram versus other anti-depressive agents for depression

BACKGROUND

Recent US and UK clinical practice guidelines recommend that second-generation antidepressants should be considered amongst the best first-line options when drug therapy is indicated for a depressive episode. Systematic reviews have already highlighted some differences in efficacy between second-generation antidepressants. Citalopram, one of the first selective serotonin reuptake inhibitors (SSRI) introduced in the market, is one of these antidepressant drugs that clinicians use for routine depression care.

OBJECTIVES

To assess the evidence for the efficacy, acceptability and tolerability of citalopram in comparison with tricyclics, heterocyclics, other SSRIs and other conventional and non-conventional antidepressants in the acute-phase treatment of major depression.

SEARCH METHODS

We searched The Cochrane Collaboration Depression, Anxiety and Neurosis Controlled Trials Register and the Cochrane Central Register of Controlled Trials up to February 2012. No language restriction was applied. We contacted pharmaceutical companies and experts in this field for supplemental data.

SELECTION CRITERIA

Randomised controlled trials allocating patients with major depression to citalopram versus any other antidepressants.

DATA COLLECTION AND ANALYSIS

Two reviewers independently extracted data. Information extracted included study characteristics, participant characteristics, intervention details and outcome measures in terms of efficacy (the number of patients who responded or remitted), patient acceptability (the number of patients who failed to complete the study) and tolerability (side-effects).

MAIN RESULTS

Thirty-seven trials compared citalopram with other antidepressants (such as tricyclics, heterocyclics, SSRIs and other antidepressants, either conventional ones, such as mirtazapine, venlafaxine and reboxetine, or non-conventional, like hypericum). Citalopram was shown to be significantly less effective than escitalopram in achieving acute response (odds ratio (OR) 1.47, 95% confidence interval (CI) 1.08 to 2.02), but more effective than paroxetine (OR 0.65, 95% CI 0.44 to 0.96) and reboxetine (OR 0.63, 95% CI 0.43 to 0.91). Significantly fewer patients allocated to citalopram withdrew from trials due to adverse events compared with patients allocated to tricyclics (OR 0.54, 95% CI 0.38 to 0.78) and fewer patients allocated to citalopram reported at least one side effect than reboxetine or venlafaxine (OR 0.64, 95% CI 0.42 to 0.97 and OR 0.46, 95% CI 0.24 to 0.88, respectively).

AUTHORS' CONCLUSIONS

Some statistically significant differences between citalopram and other antidepressants for the acute phase treatment of major depression were found in terms of efficacy, tolerability and acceptability. Citalopram was more efficacious than paroxetine and reboxetine and more acceptable than tricyclics, reboxetine and venlafaxine, however, it seemed to be less efficacious than escitalopram. As with most systematic reviews in psychopharmacology, the potential for overestimation of treatment effect due to sponsorship bias and publication bias should be borne in mind when interpreting review findings. Economic analyses were not reported in the included studies, however, cost effectiveness information is needed in the field of antidepressant trials.

European Group for the Study of Resistant Depression (GSRD)--where have we gone so far: review of clinical and genetic findings

The primary objective of this review is to give an overview of the main findings of the European multicenter project "Patterns of Treatment Resistance and Switching Strategies in Affective Disorder", performed by the Group for the Study of Resistant Depression (GSRD). The aim was to study methodological issues, operational criteria, clinical characteristics, and genetic variables associated with treatment resistant depression (TRD), that is failure to reach response after at least two consecutive adequate antidepressant trials. The primary findings of clinical variables associated with treatment resistance include comorbid anxiety disorders as well as non-response to the first antidepressant received lifetime. Although there is a plethora of hints in textbooks that switching the mechanism of action should be obtained in case of nonresponse to one medication, the results of the GSRD challenge this notion by demonstrating in retrospective and prospective evaluations that staying on the same antidepressant mechanism of action for a longer time is more beneficial than switching, however, when switching is an option there is no benefit to switch across class. The GSRD candidate gene studies found that metabolism status according to cytochrome P450 gene polymorphisms may not be helpful to predict response and remission rates to antidepressants. Significant associations with MDD and antidepressant treatment response were found for COMT SNPs. Investigating the impact of COMT on suicidal behaviour, we found a significant association with suicide risk in MDD patients not responding to antidepressant treatment, but not in responders. Further significant associations with treatment response phenotypes were found with BDNF, 5HTR2A and CREB1. Additional investigated candidate genes were DTNBP1, 5HT1A, PTGS2, GRIK4 and GNB3.

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.

Gene-environment interaction in major depression and antidepressant treatment response

Response to antidepressants is interindividually variable. It has been suggested that this variability is a direct consequence of etiological heterogeneity. Therefore, the same genes, environments, and gene-environment interactions implicated in different etiological pathways to depression may also predict response to treatment. This article reviews the evidence relevant to this hypothesis by first outlining the roles of genes, environments, and gene-environment interplay in the etiology of depression, and then considering the same factors in treatment response. Environmental exposures, such as childhood maltreatment, are potent predictors of both depression and treatment response. Although alone genetic factors have failed to consistently predict either phenotype, several polymorphisms have been shown to moderate the effects of environmental adversity on the development of depression and treatment response. These findings suggest that the dissection of etiological pathways to depression may provide the key to understanding and predicting response to antidepressants.

Major depressive disorder: new clinical, neurobiological, and treatment perspectives

In this Seminar we discuss developments from the past 5 years in the diagnosis, neurobiology, and treatment of major depressive disorder. For diagnosis, psychiatric and medical comorbidity have been emphasised as important factors in improving the appropriate assessment and management of depression. Advances in neurobiology have also increased, and we aim to indicate genetic, molecular, and neuroimaging studies that are relevant for assessment and treatment selection of this disorder. Further studies of depression-specific psychotherapies, the continued application of antidepressants, the development of new treatment compounds, and the status of new somatic treatments are also discussed. We address two treatment-related issues: suicide risk with selective serotonin reuptake inhibitors, and the safety of antidepressants in pregnancy. Although clear advances have been made, no fully satisfactory treatments for major depression are available.

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.

Association of catechol-O-methyltransferase variants with duloxetine response in major depressive disorder

Single-nucleotide and diplotype associations with 17-item Hamilton Depression Rating Scale (HAMD(17)) total score changes were examined, based on catechol-O-methyltransferase (COMT) rs165599 status in duloxetine-treated, self-identified white patients with major depressive disorder. COMT rs165737 and a diplotype containing COMT rs165599 and COMT rs165737 were associated with HAMD(17) total score changes.

Glucocorticoids as predictors of treatment response in depression

INTRODUCTION

Glucocorticoids and the stress hormone system have been implicated in the pathophysiology of depression and in the mechanism of action of antidepressant response. Many studies have investigated this system in an effort to predict response to antidepressant treatment. The purpose of this review is to evaluate the evidence for using glucocorticoid-related measures for personalized treatment of depression.

METHODS

We conducted a MEDLINE search from 1966 through 2010 and examined English-language studies reporting on the use of endocrine challenge tests and genetic polymorphisms in genes regulating the stress hormone system as predictors of antidepressant response.

RESULTS

While measures of glucocorticoid levels using endocrine tests, as well polymorphisms in genes regulating the stress hormone system, show associations with response to antidepressant treatment, these measures will need to be combined with other variables, including clinical information and other biological measures, to realize the goal of highly predictive and clinically relevant biomarkers.

DISCUSSION

The glucocorticoid system is potentially of great use in predicting antidepressant response. New combinations of biomarkers including these measures should be tested to develop clinically relevant predictors.

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.

The association of single nucleotide polymorphisms in the catechol-O-methyltransferase gene and pain scores in female patients with major depressive disorder

We tested the hypothesis that single nucleotide polymorphisms (SNPs) in the catechol-O-methyltransferase (COMT) gene are associated with baseline pain levels in patients with major depressive disorder (MDD). Pain levels were quantified using a visual analog scale (VAS) for pain. Data from 159 female and 93 male self-reported white patients with MDD were analyzed. The associations between a haplotype previously associated with pain sensitivity created using COMT SNPs rs6269, rs4633, rs4818, and rs4680, and the proportion of female patients with "Pain While Awake" and "Overall Pain" at baseline were statistically significant (P < .05). In male patients, no statistically significant associations between COMT haplotypes and baseline pain scores were seen. The rs165599 SNP, which has previously been associated with response of depressive symptoms to treatment in patients with MDD, did not impact baseline pain in either gender. In conclusion, baseline pain levels appear to be associated with the COMT pain sensitivity haplotype in female patients with MDD.

PERSPECTIVE

This article presents associations of the COMT pain sensitivity haplotype and baseline pain levels in female patients with MDD. This finding could potentially help clinicians who seek to assess how genetic polymorphisms may contribute to a patient's pain experience.

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.

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.