Sexually dimorphic effect of catechol-O-methyltransferase val158met polymorphism on clinical response to fluoxetine in major depressive patients

Omics approaches open new horizons in major depressive disorder: from biomarkers to precision medicine

Major depressive disorder (MDD) is a recurrent episodic mood disorder that represents the third leading cause of disability worldwide. In MDD, several factors can simultaneously contribute to its development, which complicates its diagnosis. According to practical guidelines, antidepressants are the first-line treatment for moderate to severe major depressive episodes. Traditional treatment strategies often follow a one-size-fits-all approach, resulting in suboptimal outcomes for many patients who fail to experience a response or recovery and develop the so-called "therapy-resistant depression". The high biological and clinical inter-variability within patients and the lack of robust biomarkers hinder the finding of specific therapeutic targets, contributing to the high treatment failure rates. In this frame, precision medicine, a paradigm that tailors medical interventions to individual characteristics, would help allocate the most adequate and effective treatment for each patient while minimizing its side effects. In particular, multi-omic studies may unveil the intricate interplays between genetic predispositions and exposure to environmental factors through the study of epigenomics, transcriptomics, proteomics, metabolomics, gut microbiomics, and immunomics. The integration of the flow of multi-omic information into molecular pathways may produce better outcomes than the current psychopharmacological approach, which targets singular molecular factors mainly related to the monoamine systems, disregarding the complex network of our organism. The concept of system biomedicine involves the integration and analysis of enormous datasets generated with different technologies, creating a "patient fingerprint", which defines the underlying biological mechanisms of every patient. This review, centered on precision medicine, explores the integration of multi-omic approaches as clinical tools for prediction in MDD at a single-patient level. It investigates how combining the existing technologies used for diagnostic, stratification, prognostic, and treatment-response biomarkers discovery with artificial intelligence can improve the assessment and treatment of MDD.

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers

BACKGROUND

The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation.

METHODS

We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values.

RESULTS

A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response.

CONCLUSIONS

The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

Polymorphisms of COMT and CREB1 are associated with treatment-resistant depression in a Chinese Han population

Genetic factors play a crucial role for the pathophysiology of treatment-resistant depression (TRD). It has been established that Catechol-O-methyltransferase (COMT) and cyclic amp-response element-binding protein (CREB) are associated with antidepressant response. The aim of this study was to explore the association between single nucleotide polymorphisms (SNPs) in COMT and CREB1 genes and TRD in a Chinese population. We recruited 181 patients with major depressive disorder (MDD) and 80 healthy controls, including 81 TRD patients. Depressive symptoms were assessed with the Hamilton Depression Rating Scale-17 (HDRS). Genotyping was performed using mass spectrometry. Genetic analyses were conducted by PLINK Software. The distribution of COMT SNP rs4818 allele and genotypes were significantly different between TRD and controls. Statistical differences in allele frequencies were observed between TRD and non-TRD groups, including rs11904814 and rs6740584 in CREB1 gene, rs4680 and rs4818 in COMT gene. There were differences in the distribution of HDRS total scores among different phenotypes of CREB1 rs11904814, CREB1 rs6740584, COMT rs4680 and rs4818. Gene-gene interaction effect of COMT-CREB1 (rs4680 × rs6740584) revealed significant epistasis in TRD. There findings indicate that COMT and CREB1 polymorphisms influence the risk of TRD and affect the severity of depressive symptoms of MDD.

Genetic Markers for Later Remission in Response to Early Improvement of Antidepressants

Planning subsequent treatment strategies based on early responses rather than waiting for delayed antidepressant action can be helpful. We identified genetic markers for later non-remission in patients exhibiting poor early improvement using whole-exome sequencing data of depressive patients treated in a naturalistic manner. Among 1000 patients, early improvement at 2 weeks (reduction in Hamilton Depression Rating Scale [HAM-D] score ≥ 20%) and remission at 12 weeks (HAM-D score ≤ 7) were evaluated. Gene- and variant-level analyses were conducted to compare patients who did not exhibit early improvement and did not eventually achieve remission (n = 126) with those who exhibited early improvement and achieved remission (n = 385). Genes predicting final non-remission in patients who exhibited poor early improvement (COMT, PRNP, BRPF3, SLC25A40, and CGREF1 in males; PPFIBPI, LZTS3, MEPCE, MAP1A, and PFAS in females; ST3GAL5 in the total population) were determined. Among the significant genes, variants in the PRNP (rs1800014), COMT (rs6267), BRPF3 (rs200565609), and SLC25A40 genes (rs3213633) were identified. However, interpretations should be made cautiously, as complex pharmacotherapy involves various genes and pathways. Early detection of poor early improvement and final non-remission based on genetic risk would be helpful for decision-making in a clinical setting.

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.

Systems Approach to Identify Common Genes and Pathways Associated with Response to Selective Serotonin Reuptake Inhibitors and Major Depression Risk

Despite numerous studies on major depressive disorder (MDD) susceptibility, the precise underlying molecular mechanism has not been elucidated which restricts the development of etiology-based disease-modifying drug. Major depressive disorder treatment is still symptomatic and is the leading cause of (~30%) failure of the current antidepressant therapy. Here we comprehended the probable genes and pathways commonly associated with antidepressant response and MDD. A systematic review was conducted, and candidate genes/pathways associated with antidepressant response and MDD were identified using an integrative genetics approach. Initially, single nucleotide polymorphisms (SNPs)/genes found to be significantly associated with antidepressant response were systematically reviewed and retrieved from the candidate studies and genome-wide association studies (GWAS). Also, significant variations concerning MDD susceptibility were extracted from GWAS only. We found 245 (Set A) and 800 (Set B) significantly associated genes with antidepressant response and MDD, respectively. Further, gene set enrichment analysis revealed the top five co-occurring molecular pathways (p ≤ 0.05) among the two sets of genes: Cushing syndrome, Axon guidance, cAMP signaling pathway, Insulin secretion, and Glutamatergic synapse, wherein all show a very close relation to synaptic plasticity. Integrative analyses of candidate gene and genome-wide association studies would enable us to investigate the putative targets for the development of disease etiology-based antidepressant that might be more promising than current ones.

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.

Treatment of Depression in Women

Women are more likely than men to experience depression throughout the life span. Sex differences in neurochemistry and brain structure, as well as societal factors may contribute to women's increased likelihood of depression. Pharmacological research targeting depression has historically excluded women, leading to a knowledge gap regarding effective antidepressant treatment in women. Antidepressant pharmacokinetics and pharmacodynamics are clearly different in men and women, necessitating a thoughtful approach to their prescription and management. Hormone changes associated with the menstrual cycle, pregnancy, and menopause also contribute to differences in depression and effective antidepressant use in women. Finally, it is important to consider potential interactions between antidepressant drugs and medications specifically used by women (oral contraceptives, tamoxifen, and estrogen).

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.

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.

Understanding the pharmacogenetics of selective serotonin reuptake inhibitors

INTRODUCTION

The genetic background of antidepressant response represents a unique opportunity to identify biological markers of treatment outcome. Encouraging results alternating with inconsistent findings made antidepressant pharmacogenetics a stimulating but often discouraging field that requires careful discussion about cumulative evidence and methodological issues.

AREAS COVERED

The present review discusses both known and less replicated genes that have been implicated in selective serotonin reuptake inhibitors (SSRIs) efficacy and side effects. Candidate genes studies and genome-wide association studies (GWAS) were collected through MEDLINE database search (articles published till January 2014). Further, GWAS signals localized in promising genetic regions according to candidate gene studies are reported in order to assess the general comparability of results obtained through these two types of pharmacogenetic studies. Finally, a pathway enrichment approach is applied to the top genes (those harboring SNPs with p < 0.0001) outlined by previous GWAS in order to identify possible molecular mechanisms involved in SSRI effect.

EXPERT OPINION

In order to improve the understanding of SSRI pharmacogenetics, the present review discusses the proposal of moving from the analysis of individual polymorphisms to genes and molecular pathways, and from the separation across different methodological approaches to their combination. Efforts in this direction are justified by the recent evidence of a favorable cost-utility of gene-guided antidepressant treatment.

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.

Mechanisms of antidepressant resistance

Depression is one of the most frequent and severe mental disorder. Since the discovery of antidepressant (AD) properties of the imipramine and then after of other tricyclic compounds, several classes of psychotropic drugs have shown be effective in treating major depressive disorder (MDD). However, there is a wide range of variability in response to ADs that might lead to non response or partial response or in increased rate of relapse or recurrence. The mechanisms of response to AD therapy are poorly understood, and few biomarkers are available than can predict response to pharmacotherapy. Here, we will first review markers that can be used to predict response to pharmacotherapy, such as markers of drug metabolism or blood-brain barrier (BBB) function, the activity of specific brain areas or neurotransmitter systems, hormonal dysregulations or plasticity, and related molecular targets. We will describe both clinical and preclinical studies and describe factors that might affect the expression of these markers, including environmental or genetic factors and comorbidities. This information will permit us to suggest practical recommendations and innovative treatment strategies to improve therapeutic outcomes.

Prediction of the time-course pattern of remission in depression by using clinical, neuropsychological, and genetic variables

BACKGROUND

The prediction of remission in pharmacologically-treated MDD patients has been scarcely studied. The goal of our work is to study the possible effect of clinical variables, neuropsychological performance, and the 5HTTLPR, the rs25531 of the SLC6A4 gene, and the val108/58Met of the COMT gene polymorphisms on the prediction of the speed of remission in MDD patients.

METHODS

Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluoxetine treatment.

RESULTS

From this original sample 51 patients were considered as remitters at the end of week 12. Thirteen out of those showed a rapid response pattern, 24 showed an oscillating response pattern, and 14 showed a slow response pattern. The following variable combination is capable of showing a statistically significant relationship with the pattern of remission of patients with MDD: initial Hamilton score, age at first depressive episode, AG and GG alleles of the val108/58Met COMT polymorphism, Stroop PC, and SWM Strategy.

LIMITATIONS

We have a slightly small sample size, which came to prominence during the data analysis since we were working with 3 subgroups. In this study, the placebo effect has not been controlled.

DISCUSSION

Our data suggest that the patients with MDD who remit after a 12-week treatment with fluoxetine show one of the following time-course patterns: a rapid symptomatic improvement, or a slow or oscillating pattern of remission. A combination of clinical, neuropsychological, and genetic variables allows us to predict these response patterns.

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.

Human biomarkers of rapid antidepressant effects

Mood disorders such as major depressive disorder and bipolar disorder--and their consequent effects on the individual and society--are among the most disabling and costly of all medical illnesses. Although a number of antidepressant treatments are available in clinical practice, many patients still undergo multiple and lengthy medication trials before experiencing relief of symptoms. Therefore a tremendous need exists to improve current treatment options and to facilitate more rapid, successful treatment in patients suffering from the deleterious neurobiological effects of ongoing depression. Toward that end, ongoing research is exploring the identification of biomarkers that might be involved in prevention, diagnosis, treatment response, severity, or prognosis of depression. Biomarkers evaluating treatment response will be the focus of this review, given the importance of providing relief to patients in a more expedient and systematic manner. A novel approach to developing such biomarkers of response would incorporate interventions with a rapid onset of action--such as sleep deprivation or intravenous drugs (e.g., ketamine or scopolamine). This alternative translational model for new treatments in psychiatry would facilitate shorter studies, improve feasibility, and increase higher compound throughput testing for these devastating disorders.

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.

Fluoxetine pharmacogenetics in child and adult populations

Although fluoxetine is useful in the treatment of major depression, 30-40 % of the patients do not respond to therapy. The response seems to be influenced by certain genes which are involved in the drug's pharmacodynamics and pharmacokinetics. The present study reviews the literature on genetic contributions to fluoxetine response in children and adults, and concludes that the different polymorphisms of CYP2D6 and CYP2C9 may influence the blood concentrations of fluoxetine. If the childhood dose is adjusted for weight, differences between children and adults are unlikely. As regards the genes that influence the drug's pharmacodynamics, polymorphisms of SLC6A4, HTR1A and MAO-A seem to be involved in the response to fluoxetine, while the genes COMT, CRHR1, PDEA1, PDEA11 GSK3B and serpin-1 also seem to play a role. Comparison of different studies reveals that the results are not always consistent, probably due to methodological differences. Other factors such as gender or ethnicity may also influence treatment response.

Prediction of remission of depression with clinical variables, neuropsychological performance, and serotonergic/dopaminergic gene polymorphisms

OBJECTIVE

The aim of our work is to study the possible role of clinical variables, neuropsychological performance, and the 5HTTLPR, rs25531, and val108/58Met COMT polymorphisms on the prediction of depression remission after 12 weeks' treatment with fluoxetine. These variables have been studied as potential predictors of depression remission, but they present poor prognostic sensitivity and specificity by themselves.

METHODS

Seventy-two depressed patients were genotyped according to the aforementioned polymorphisms and were clinically and neuropsychologically assessed before a 12-week fluxetine treatment.

RESULTS

Only the La allele of rs25531 polymorphism and the GG and AA forms of the val 108/158 Met polymorphism predict major depressive disorder remission after 12 weeks' treatment with fluoxetine. None of the clinical and neuropsychological variables studied predicted remission.

CONCLUSIONS

Our results suggest that clinical and neuropsychological variables can initially predict early response to fluoxetine and mask the predictive role of genetic variables; but in remission, where clinical and neuropsychological symptoms associated with depression tend to disappear thanks to the treatment administered, the polymorphisms studied are the only variables in our model capable of predicting remission. However, placebo effects that are difficult to control require cautious interpretation of the results.

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.

The genetics of selective serotonin reuptake inhibitors

Selective serotonin reuptake inhibitors (SSRIs) are among the most widely prescribed drugs in psychiatry. Based on the fact that SSRIs increase extracellular monoamine levels in the brain, the monoamine hypothesis of depression was introduced, postulating that depression is associated with too low serotonin, dopamine and noradrenaline levels. However, several lines of evidence indicate that this hypothesis is too simplistic and that depression and the efficacy of SSRIs are dependent on neuroplastic changes mediated by changes in gene expression. Because a coherent view on global gene expression is lacking, we aim to provide an overview of the effects of SSRI treatment on the final targets of 5-HT receptor signal transduction pathways, namely the transcriptional regulation of genes. We address gene polymorphisms in humans that affect SSRI efficacy, as well as in vitro studies employing human-derived cells. We also discuss the molecular targets affected by SSRIs in animal models, both in vivo and in vitro. We conclude that serotonin transporter gene variation in humans affects the efficacy and side-effects of SSRIs, whereas SSRIs generally do not affect serotonin transporter gene expression in animals. Instead, SSRIs alter mRNA levels of genes encoding serotonin receptors, components of non-serotonergic neurotransmitter systems, neurotrophic factors, hypothalamic hormones and inflammatory factors. So far little is known about the epigenetic and age-dependent molecular effects of SSRIs, which might give more insights in the working mechanism(s) of SSRIs.

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.

Genome-wide association analysis of gender differences in major depressive disorder in the Netherlands NESDA and NTR population-based samples

BACKGROUND

Major depressive disorder (MDD) is a universally prevalent, genetic, and environment dependent mental condition that disables people of every culture, race, gender, and age. While the gender differences for MDD have been widely reported in literature, few genome-wide analyses of gender differences have been reported to date.

METHODS

We conducted a genome-wide association analysis of gender differences for MDD using the Netherlands NESDA and NTR population-based samples (1726 cases and 1630 controls). PLINK software was used to analyze the genome-wide association data of Perlegen 600 K SNP Chips.

RESULTS

We identified 40 male-specific and 56 female-specific MDD associated SNPs with P-values less than 10(-4). The best male-specific SNP was rs9352774 (P=2.26 × 10(-6)) within LGSN gene while the best female-specific SNP was rs2715148 (P=5.64 × 10(-7)) within PCLO gene. We also found 38 SNPs showing gene × gender interactions in influencing MDD (P<10(-4)). The best SNP was rs12692709 (P=5.75 × 10(-6)) near FIGN gene at 2q24.3 while the next best SNP was rs11039588 (P=1.16 × 10(-5)) within OR4B1 gene.

LIMITATIONS

The findings from this study need be replicated in other populations.

CONCLUSIONS

These results provide genetic basis for gender differences in MDD and will serve as a resource for replication in other populations to elucidate the potential role of these genetic variants in MDD.

Influence and interaction of genetic polymorphisms in catecholamine neurotransmitter systems and early life stress on antidepressant drug response

BACKGROUND

Catecholamine neurotransmission plays an important role in major depression. Variation in genes implicated in the synthesis and signal transduction of catecholamines (norepinephrine and dopamine) may interact with environmental factors to affect the outcome of antidepressant treatment. We aimed to determine how a range of polymorphisms in noradrenergic and dopaminergic genes influence this response to treatment and how they interact with childhood trauma and recent life stress in a Chinese sample.

METHODS

In a sample of 308 Chinese Han patients with major depressive disorder, 13 single nucleotide polymorphisms (SNPs) in coding regions of six genes (MAOA, SLC6A2, TH, COMT, DRD2, DRD3) with minor allele frequencies >5% were successfully genotyped from an initial series of 35 SNPs in 11 candidate genes associated with catecholamine neurotransmission. The responses to 6 weeks' treatment with antidepressant drugs was determined by changes in the 17-item Hamilton Depression Rating Scale (HAMD-17) score, and previous stressful events were evaluated by the Life Events Scale (LES) and Childhood Trauma Questionnaire-Short Form (CTQ-SF). Single SNP and haplotype associations with treatment response were analysed by UNPHASED 3.0.13, gene-gene interactions were analysed by generalized multifactor dimensionality reduction (GMDR) and gene-environment interactions by logistic regression.

RESULTS

A haplotype in MAOA (rs1137070 and rs6323) was significantly associated with antidepressant response in the total group, the nonSSRI subgroup and the female subgroup. Two haplotypes in COMT (involving rs4633, rs4818 and rs769224) were significantly associated with antidepressant response in the nonSSRI subgroup. The SLC6A2 SNPs interacted with childhood trauma to influence antidepressant response.

CONCLUSIONS

A haplotype in MAOA and two haplotypes in COMT are found to be associated with antidepressant treatment response in this sample. Stressors in early life may interact with polymorphisms in SLC6A2 to influence response to antidepressant treatment.

Interaction of early environment, gender and genes of monoamine neurotransmission in the aetiology of depression in a large population-based Finnish birth cohort

Objectives Depression is a worldwide leading cause of morbidity and disability. Genetic studies have recently begun to elucidate its molecular aetiology. The authors investigated candidate genes of monoamine neurotransmission and early environmental risk factors for depressiveness in the genetically isolated population-based Northern Finland Birth Cohort 1966 (12 058 live births). Design The authors ascertained and subdivided the study sample (n=5225) based on measures of early development and of social environment, and examined candidate genes of monoamine neurotransmission, many of which have shown prior evidence of a gene-environment interaction for affective disorders, namely SLC6A4, TPH2, COMT, MAOA and the dopamine receptor genes DRD1-DRD5. Results and conclusion The authors observed no major genetic effects of the analysed variants on depressiveness. However, when measures of early development and of social environment were considered, some evidence of interaction was observed. Allelic variants of COMT interacted with high early developmental risk (p=0.005 for rs2239393 and p=0.02 for rs4680) so that the association with depression was detected only in individuals at high developmental risk group (p=0.0046 and β=0.056 for rs5993883-rs2239393-rs4680 risk haplotype CGG including Val158), particularly in males (p=0.0053 and β=0.083 for the haplotype CGG). Rs4274224 from DRD2 interacted with gender (p=0.017) showing a significant association with depressiveness in males (p=0.0006 and β=0.0023; p=0.00005 and β=0.069 for rs4648318-rs4274224 haplotype GG). The results support the role of genes of monoamine neurotransmission in the aetiology of depression conditional on environmental risk and sex, but not direct major effects of monoaminergic genes in this unselected population.

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.

Gene expression and association analysis of the epithelial membrane protein 1 gene in major depressive disorder in the Japanese population

The epithelial membrane protein 1 (EMP1) plays a role in neuronal differentiation and neurite outgrowth, which are involved in the pathogenesis of major depressive disorder (MDD). We sought to determine whether the EMP1 gene is implicated in MDD. We determined the mRNA expression levels of the EMP1 gene in peripheral-blood leukocytes of patients and control subjects (n=27 each). Next, we performed case-control association analyses (MDD, n=182; controls, n=350) in the Japanese population. The level of expression of the EMP1 mRNA was significantly lower in medication-free patients compared with control subjects (P<0.001). The association analysis revealed an absence of association between the polymorphisms studied and MDD, whereas a gender-specific association was observed between male controls and male patients for marker rs7315725 (permutation P=0.039). Our results suggest that the EMP1 gene may be implicated in the pathophysiology of MDD in the Japanese population.

The role of clinical variables, neuropsychological performance and SLC6A4 and COMT gene polymorphisms on the prediction of early response to fluoxetine in major depressive disorder

INTRODUCTION

Major depressive disorder (MDD) is treated with antidepressants, but only between 50% and 70% of the patients respond to the initial treatment. Several authors suggested different factors that could predict antidepressant response, including clinical, psychophysiological, neuropsychological, neuroimaging, and genetic variables. However, these different predictors present poor prognostic sensitivity and specificity by themselves. The aim of our work is to study the possible role of clinical variables, neuropsychological performance, and the 5HTTLPR, rs25531, and val108/58Met COMT polymorphisms in the prediction of the response to fluoxetine after 4weeks of treatment in a sample of patient with MDD.

METHODS

64 patients with MDD were genotyped according to the above-mentioned polymorphisms, and were clinically and neuropsychologically assessed before a 4-week fluoxetine treatment. Fluoxetine response was assessed by using the Hamilton Depression Rating Scale. We carried out a binary logistic regression model for the potential predictive variables.

RESULTS

Out of the clinical variables studied, only the number of anxiety disorders comorbid with MDD have predicted a poor response to the treatment. A combination of a good performance in variables of attention and low performance in planning could predict a good response to fluoxetine in patients with MDD. None of the genetic variables studied had predictive value in our model.

LIMITATIONS

The possible placebo effect has not been controlled. Our study is focused on response prediction but not in remission prediction.

CONCLUSIONS

Our work suggests that the combination of the number of comorbid anxiety disorders, an attentional variable, and two planning variables makes it possible to correctly classify 82% of the depressed patients who responded to the treatment with fluoxetine, and 74% of the patients who did not respond to that treatment.

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.

The impact of catechol-O-methyltransferase SNPs and haplotypes on treatment response phenotypes in major depressive disorder: a case-control association study

Catechol-O-methyltransferase (COMT) has been suggested to be involved in the pathogenesis and pharmacological treatment of affective disorders. The nonsynonymous single nucleotide polymorphism (SNP) in exon 4 (Val108/158Met; rs4680) influences the COMT enzyme activity. Inconsistent results were found between Val158Met polymorphism (rs4680) and treatment response phenotypes in genetic association studies. However, the haplotype combinations of alleles at the Val108/158Met SNP with the other synonymous SNPs in the COMT gene region have shown association between enzyme activity/amount and COMT-dependent phenotypes. We carried out this study to define the functional impact of COMT genotypes/haplotypes on susceptibility and on treatment response phenotypes of major depressive disorder (MDD). Three hundred and ninety-six patients with MDD diagnosed according to the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition [(DSM)-IV] and 295 healthy controls were recruited for this study and genotyped for the seven COMT SNPs (rs2075507, rs737865, rs6269, rs4633, rs4818, rs4680, and rs165599). This is the first study with all these SNPs to investigate for MDD and treatment response phenotypes. Our results show that none of the seven SNPs, including the rs4680, was significantly associated with MDD after permutation correction in single SNP analyses. Although several haplotype combinations showed significance, the combinations of G-T-G-G haplotype for rs6269, rs4633, rs4818 and rs4680 were only present in the MDD group (G-T 4.5%, corrected sim P=0.0001; G-T-G 3.87%, corrected sim P=0.001; G-T-G-G 3.3% corrected sim P=0.0025). In the treatment response phenotypes, the GG genotype of the rs2075507 SNP (located in the promoter region of MB-COMT) was less common in resistant patients in a single SNP analysis with low corrected sim P=0.052 and power=0.086. However, in the haplotype analysis, the haplotypes of exonic SNPs, rs4633, rs4818, and rs4680, were related to the treatment response phenotypes investigated, especially the phenotype of the response to antidepressant treatment. The C-C-A haplotype of these SNPs was overrepresented (almost four-and eight-fold) in the responders compared with the nonresponders and controls, respectively, after Bonferroni correction (corrected sim P=0.048, 0.0001, respectively). Both nonsynonymous and synonymous SNPs within haplotypes may be more relevant than the single SNP in conferring MDD susceptibility and treatment response phenotypes. Despite the limited power of our analysis, this finding suggests that the polymorphic COMT gene that influences catecholaminergic neurotransmission may play a role in the individual response to antidepressants.

Sex differences in the pharmacokinetics and pharmacodynamics of antidepressants: an updated review

BACKGROUND

An increasing number of studies have reported differences in the pharmacokinetics and/or pharmacodynamics of antidepressants between women and men.

OBJECTIVES

This article updates previously published literature describing sex differences in the pharmacokinetics and pharmacodynamics of antidepressants, and examines specific issues that face women with psychiatric illness.

METHODS

An English-language literature search was performed with the PubMed database (March 2003-December 2008) using combinations of the search terms sex, gender, and antidepressants. In addition, each antidepressant was identified in the 63rd edition of the Physicians' Desk Reference.

RESULTS

The current data suggest that the pharmacokinetics of antidepressants can be substantially different between women and men. Likewise, the response to antidepressants can be quite variable, including sex differences in adverse effects and time to response.

CONCLUSIONS

Despite the many sex differences reported, there is still little published work systematically evaluating potential sex differences in antidepressant pharmacokinetics and pharmacodynamics. More research is needed to guide the treatment of depression and other 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).