Effect of cytochrome CYP2C19 metabolizing activity on antidepressant response and side effects: Meta-analysis of data from genome-wide association studies.

Cytochrome (CYP) P450 enzymes have a primary role in antidepressant metabolism and variants in these polymorphic genes are targets for pharmacogenetic investigation. This is the first meta-analysis to investigate how CYP2C19 polymorphisms predict citalopram/escitalopram efficacy and side effects. CYP2C19 metabolic phenotypes comprise poor metabolizers (PM), intermediate and intermediate+ metabolizers (IM; IM+), extensive and extensive+ metabolizers (EM [wild type]; EM+) and ultra-rapid metabolizers (UM) defined by the two most common CYP2C19 functional polymorphisms (rs4244285 and rs12248560) in Caucasians. These polymorphisms were genotyped or imputed from genome-wide data in four samples treated with citalopram or escitalopram (GENDEP, STAR*D, GenPod, PGRN-AMPS). Treatment efficacy was assessed by standardized percentage symptom improvement and by remission. Side effect data were available at weeks 2-4, 6 and 9 in three samples. A fixed-effects meta-analysis was performed using EM as the reference group. Analysis of 2558 patients for efficacy and 2037 patients for side effects showed that PMs had higher symptom improvement (SMD = 0.43, CI = 0.19-0.66) and higher remission rates (OR = 1.55, CI = 1.23-1.96) compared to EMs. At weeks 2-4, PMs showed higher risk of gastro-intestinal (OR = 1.26, CI = 1.08-1.47), neurological (OR = 1.28, CI = 1.07-1.53) and sexual side effects (OR = 1.52, CI = 1.23-1.87; week 6 values were similar). No difference was seen at week 9 or in total side effect burden. PMs did not have higher risk of dropout at week 4 compared to EMs. Antidepressant dose was not different among CYP2C19 groups. CYP2C19 polymorphisms may provide helpful information for guiding citalopram/escitalopram treatment, despite PMs being relatively rare among Caucasians (∼2%).

Pharmacogenetics of antidepressant response: A polygenic approach.

BACKGROUND: Major depressive disorder (MDD) has a high personal and socio-economic burden and >60% of patients fail to achieve remission with the first antidepressant. The biological mechanisms behind antidepressant response are only partially known but genetic factors play a relevant role. A combined predictor across genetic variants may be useful to investigate this complex trait. METHODS: Polygenic risk scores (PRS) were used to estimate multi-allelic contribution to: 1) antidepressant efficacy; 2) its overlap with MDD and schizophrenia. We constructed PRS and tested whether these predicted symptom improvement or remission from the GENDEP study (n=736) to the STAR*D study (n=1409) and vice-versa, including the whole sample or only patients treated with escitalopram or citalopram. Using summary statistics from Psychiatric Genomics Consortium for MDD and schizophrenia, we tested whether PRS from these disorders predicted symptom improvement in GENDEP, STAR*D, and five further studies (n=3756). RESULTS: No significant prediction of antidepressant efficacy was obtained from PRS in GENDEP/STAR*D but this analysis might have been underpowered. There was no evidence of overlap in the genetics of antidepressant response with either MDD or schizophrenia, either in individual studies or a meta-analysis. Stratifying by antidepressant did not alter the results. DISCUSSION: We identified no significant predictive effect using PRS between pharmacogenetic studies. The genetic liability to MDD or schizophrenia did not predict response to antidepressants, suggesting differences between the genetic component of depression and treatment response. Larger or more homogeneous studies will be necessary to obtain a polygenic predictor of antidepressant response.

[Mental Health Recovery Star: features and validation study of the Italian version]. / La Mental Health Recovery Star: caratteristiche e studio di validazione della versione italiana.

AIM: Mental Health Recovery Star (MHRS) is an instrument that helps to assess recovery processes of mental health patients through a collaborative approach. The aim of the study is to describe the features of the instrument and to report the results of the Italian validation study. METHODS: The study involved 117 users which were evaluated in two phases. Besides MRHS, HoNOS, WHOQoL-brief, GAF were used. Acceptability for users and key-workers of the instruments and its main psychometric properties, as test-retes (ICC) and concurrent validity (Pearson's correlation coefficient), were evaluated. RESULTS: MHRS showed to have temporal stability in all its areas. Significant correlations were found between the MHRS and the most closely related areas of the scales used. Inter-rater reliability were studied in an unsatisfactory way. MHRS was appreciated and easy to use. Collaborative evaluations were completed mostly in less than 45 minutes. CONCLUSIONS: MHRS is an acceptable tool for users and staff-members, distinguishing itself from the use of useful visual aids; helps to identify the patient's recovery path and supports a collaborative approach between user and operator. The results of the psychometric properties of the instrument appeared promising but not exhaustive. Although further efforts should be addressed to the implementation of such aspects of the instrument and reflections should be raised with respect to the traditional methods to detect the complex meaning of recovery (subjective-objective aspects), the valuable collaborative contribution of MHRS can not be denied in favoring the user's responsibility and supporting the professional worker in his role of case manager.

Transcriptomics and the mechanisms of antidepressant efficacy.

The mechanisms by which antidepressants have their effects are not clear and the reasons for variability in treatment outcomes are also unknown. However, there is evidence from candidate gene research that indicates gene expression changes may be involved in antidepressant action. In this study, we examined antidepressant-induced alterations in gene expression on a transcriptome-wide scale, exploring associations with treatment response. Blood samples were taken from a subset of depressed patients from the GENDEP study (n=136) before and after eight weeks of treatment with either escitalopram or nortriptyline. Transcriptomic data were obtained from these samples using Illumina HumanHT-12 v4 Expression BeadChip microarrays. When analysing individual genes, we observed that changes in the expression of two genes (MMP28 and KXD1) were associated with better response to nortriptyline. Considering connectivity between genes, we identified modules of genes that were highly coexpressed. In the whole sample, changes in one of the ten identified coexpression modules showed significant correlation with treatment response (cor=0.27, p=0.0029). Using transcriptomic approaches, we have identified gene expression correlates of the therapeutic effects of antidepressants, highlighting possible molecular pathways involved in efficacious antidepressant treatment.

Exploring the role of drug-metabolising enzymes in antidepressant side effects.

RATIONALE: Cytochrome P450 enzymes are important in the metabolism of antidepressants. The highly polymorphic nature of these enzymes has been linked to variability in antidepressant metabolism rates, leading to hope regarding the use of P450 genotyping to guide treatment. However, evidence that P450 genotypic differences underlie the variation in treatment outcomes is inconclusive. OBJECTIVES: We explored the links between both P450 genotype and serum concentrations of antidepressant with antidepressant side effects, using data from the Genome-Based Therapeutic Drugs for Depression Project (GENDEP), which is a large (n = 868), pharmacogenetic study of depressed individuals treated with escitalopram or nortriptyline. METHODS: Patients were genotyped for the enzymes CYP2C19 and CYP2D6, and serum concentrations of both antidepressant and primary metabolite were measured after 8 weeks of treatment. Side effects were assessed weekly. We investigated associations between P450 genotypes, serum concentrations of antidepressants and side effects, as well as the relationship between P450 genotype and study discontinuation. RESULTS: P450 genotype did not predict total side effect burden (nortriptyline: n = 251, p = 0.5638, ß = -0.133, standard error (SE) = 0.229; escitalopram: n = 340, p = 0.9627, ß = -0.004, SE = 0.085), study discontinuation (nortriptyline n = 284, hazard ratio (HR) = 1.300, p = 0.174; escitalopram n = 376, HR = 0.870, p = 0.118) or specific side effects. Serum concentrations of antidepressant were only related to a minority of the specific side effects measured: dry mouth, dizziness and diarrhoea. CONCLUSIONS: In this sample where antidepressant dosage is titrated using clinical judgement, P450 genotypes do not explain differences between patients in side effects with antidepressants. Serum drug concentrations appear to only explain variability in the occurrence of a minority of specific side effects.

Genetic predictors of antidepressant side effects: a grouped candidate gene approach in the Genome-Based Therapeutic Drugs for Depression (GENDEP) study.

BACKGROUND: The unwanted side effects associated with antidepressants are key determinants of treatment adherence in depression; propensity to experience these adverse drug reactions (ADRs) may be influenced by genetic variation. However, previous work attempting to ascertain the genetic variants involved has had limited success, in part due to the range of ADRs reported with antidepressants. METHOD: ADRs reported with antidepressant treatment were categorised using their likely pharmacological basis; adrenergic, cholinergic, serotonergic and histaminergic. To identify genetic predictors of susceptibility to each group of ADRs, a candidate gene analysis was performed with data from 431 depressed patients (from a total sample size of 811 patients) enrolled in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, who were randomly allocated to receive treatment with escitalopram or nortriptyline. Data from 474 patients treated with citalopram or reboxetine in the GenPod project (total sample of 601 patients) were used for replication of significant findings. RESULTS: We found no significant predictors of presumed adrenergic, cholinergic and histaminergic ADRs. Putative serotonergic ADRs were significantly associated with variation in the gene encoding the serotonin 2C receptor (HTR2C, rs6644093, odds ratio (OR)=1.72, 95% confidence interval (CI)=1.31-2.25, p=7.43×10(-5)) in GENDEP. However, this finding was not replicated in GenPod. CONCLUSIONS: The association between serotonergic side effects and variation in the HTR2C gene in the GENDEP sample supports the hypothesis that serotonin receptor-mediated mechanisms underlie these adverse reactions, however this finding was not replicated in GenPod.

Genetic differences in cytochrome P450 enzymes and antidepressant treatment response.

AIMS: Antidepressant response varies between patients, possibly due to differences in the rate cytochrome P450 enzymes metabolise antidepressants into inactive compounds. Drug metabolism rates are influenced by common variants in the genes encoding these enzymes. However, it remains unclear whether treatment outcomes can be predicted by either CYP450 genotype or antidepressant serum concentration. METHODS: In GENDEP (a pharmacogenetic study of depressed individuals treated with either escitalopram or nortriptyline), serum concentrations of antidepressants and their primary metabolite were measured after eight weeks treatment and variants in CYP2D6 and CYP2C19 were genotyped. RESULTS: Amongst patients taking escitalopram (n=223), the genotype CYP2C19 was significantly associated with escitalopram serum concentrations and desmethylescitalopram:escitalopram ratio. For those taking nortriptyline (n=161), the CYP2D6 genotype was significantly associated with nortriptyline and 10-hydroxynortriptyline serum concentrations and 10-hydroxynortriptyline:nortrip-tyline ratio. CYP450 genotypes conferring greater enzyme activity were linked to lower drug serum concentrations and higher metabolite:drug ratios. Nonetheless, no significant association was found between either CYP450 genotype or antidepressant serum concentration and treatment response. CONCLUSIONS: While there is a significant relationship between the CYP450 genotype and serum concentrations of escitalopram and nortriptyline, the genotypes are not predictive of differences in treatment response for either drug. Furthermore, differences in antidepressant serum concentrations are not associated with variability in treatment response.

Genome-wide association study of co-occurring anxiety in major depression.

OBJECTIVES: Co-morbidity between depression and anxiety disorders is common. In this study we define a quantitative measure of anxiety by summating four anxiety items from the SCAN interview in a large collection of major depression (MDD) cases to identify genes contributing to this complex phenotype. METHODS: A total of 1522 MDD cases dichotomised according to those with at least one anxiety item scored (n = 1080) and those without anxiety (n = 442) were analysed, and also compared to 1588 healthy controls at a genome-wide level, to identify genes that may contribute to anxiety in MDD. RESULTS: For the quantitative trait, suggestive evidence of association was detected for two SNPs, and for the dichotomous anxiety present/absent ratings for three SNPs at genome-wide level. In the genome-wide analysis of MDD cases with co-morbid anxiety and healthy controls, two SNPs attained P values of < 5 × 10⁻6. Analysing candidate genes, P values ≤ 0.0005 were found with three SNPs for the quantitative trait and three SNPs for the dichotomous trait. CONCLUSIONS: This study provides an initial genome-wide assessment of possible genetic contribution to anxiety in MDD. Although suggestive evidence of association was found for several SNPs, our findings suggest that there are no common variants strongly associated with anxious depression.

Genome-wide association analysis accounting for environmental factors through propensity-score matching: application to stressful live events in major depressive disorder.

Stressful life events are an established trigger for depression and may contribute to the heterogeneity within genome-wide association analyses. With depression cases showing an excess of exposure to stressful events compared to controls, there is difficulty in distinguishing between "true" cases and a "normal" response to a stressful environment. This potential contamination of cases, and that from genetically at risk controls that have not yet experienced environmental triggers for onset, may reduce the power of studies to detect causal variants. In the RADIANT sample of 3,690 European individuals, we used propensity score matching to pair cases and controls on exposure to stressful life events. In 805 case-control pairs matched on stressful life event, we tested the influence of 457,670 common genetic variants on the propensity to depression under comparable level of adversity with a sign test. While this analysis produced no significant findings after genome-wide correction for multiple testing, we outline a novel methodology and perspective for providing environmental context in genetic studies. We recommend contextualizing depression by incorporating environmental exposure into genome-wide analyses as a complementary approach to testing gene-environment interactions. Possible explanations for negative findings include a lack of statistical power due to small sample size and conditional effects, resulting from the low rate of adequate matching. Our findings underscore the importance of collecting information on environmental risk factors in studies of depression and other complex phenotypes, so that sufficient sample sizes are available to investigate their effect in genome-wide association analysis.

Genetic predictors of response to serotonergic and noradrenergic antidepressants in major depressive disorder: a genome-wide analysis of individual-level data and a meta-analysis.

BACKGROUND: It has been suggested that outcomes of antidepressant treatment for major depressive disorder could be significantly improved if treatment choice is informed by genetic data. This study aims to test the hypothesis that common genetic variants can predict response to antidepressants in a clinically meaningful way. METHODS AND FINDINGS: The NEWMEDS consortium, an academia-industry partnership, assembled a database of over 2,000 European-ancestry individuals with major depressive disorder, prospectively measured treatment outcomes with serotonin reuptake inhibiting or noradrenaline reuptake inhibiting antidepressants and available genetic samples from five studies (three randomized controlled trials, one part-randomized controlled trial, and one treatment cohort study). After quality control, a dataset of 1,790 individuals with high-quality genome-wide genotyping provided adequate power to test the hypotheses that antidepressant response or a clinically significant differential response to the two classes of antidepressants could be predicted from a single common genetic polymorphism. None of the more than half million genetic markers significantly predicted response to antidepressants overall, serotonin reuptake inhibitors, or noradrenaline reuptake inhibitors, or differential response to the two types of antidepressants (genome-wide significance p<5×10(-8)). No biological pathways were significantly overrepresented in the results. No significant associations (genome-wide significance p<5×10(-8)) were detected in a meta-analysis of NEWMEDS and another large sample (STAR*D), with 2,897 individuals in total. Polygenic scoring found no convergence among multiple associations in NEWMEDS and STAR*D. CONCLUSIONS: No single common genetic variant was associated with antidepressant response at a clinically relevant level in a European-ancestry cohort. Effects specific to particular antidepressant drugs could not be investigated in the current study. Please see later in the article for the Editors' Summary.

Self-report and clinician-rated measures of depression severity: can one replace the other?

BACKGROUND: It has been suggested that clinician-rated scales and self-report questionnaires may be interchangeable in the measurement of depression severity, but it has not been tested whether clinically significant information is lost when assessment is restricted to either clinician-rated or self-report instruments. The aim of this study is to test whether self-report provides information relevant to short-term treatment outcomes that is not captured by clinician-rating and vice versa. METHODS: In genome-based drugs for depression (GENDEP), 811 patients with major depressive disorder treated with escitalopram or nortriptyline were assessed with the clinician-rated Montgomery-Åsberg Depression Rating Scale (MADRS), Hamilton Rating Scale for Depression (HRSD), and the self-report Beck Depression Inventory (BDI). In sequenced treatment alternatives to relieve depression (STAR*D), 4,041 patients treated with citalopram were assessed with the clinician-rated and self-report versions of the Quick Inventory of Depressive Symptomatology (QIDS-C and QIDS-SR) in addition to HRSD. RESULTS: In GENDEP, baseline BDI significantly predicted outcome on MADRS/HRSD after adjusting for baseline MADRS/HRSD, explaining additional 3 to 4% of variation in the clinician-rated outcomes (both P < .001). Likewise, each clinician-rated scale significantly predicted outcome on BDI after adjusting for baseline BDI and explained additional 1% of variance in the self-reported outcome (both P < .001). The results were confirmed in STAR*D, where self-report and clinician-rated versions of the same instrument each uniquely contributed to the prediction of treatment outcome. CONCLUSIONS: Complete assessment of depression should include both clinician-rated scales and self-reported measures.

Dissecting the genetic heterogeneity of depression through age at onset.

Genome-wide studies in major depression have identified few replicated associations, potentially due to heterogeneity within the disorder. Several studies have suggested that age at onset (AAO) can distinguish sub-types of depression with specific heritable components. This paper investigates the role of AAO in the genetic susceptibility for depression using genome-wide association data on 2,746 cases and 1,594 screened controls from the RADIANT studies, with replication performed in 1,471 cases and 1,403 controls from two Munich studies. Three methods were used to analyze AAO: First a time-to-event analysis with controls censored, secondly comparing controls to case-subsets defined using AAO cut-offs, and lastly analyzing AAO as a quantitative trait. In the time-to-event analysis three SNPs reached suggestive significance (P < 5E-06), overlapping with the original case-control analysis of this study. In a case-control analysis using AAO thresholds, SNPs in 10 genomic regions showed suggestive association though again none reached genome-wide significance. Lastly, case-only analysis of AAO as a quantitative trait resulted in 5 SNPs reaching suggestive significance. Sex specific analysis was performed as a secondary analysis, yielding one SNP reaching genome-wide significance in early-onset males. No SNPs achieved significance in the replication study after correction for multiple testing. Analysis of AAO as a quantitative trait did suggest that, across all SNPs, common genetic variants explained a large proportion of the variance (51%, P = 0.04). This study provides the first focussed analysis of the genetic contribution to AAO in depression, and establishes a statistical framework that can be applied to a quantitative trait underlying any disorder.

Non-random dropout and the relative efficacy of escitalopram and nortriptyline in treating major depressive disorder.

Most comparisons of the efficacy of antidepressants have relied on the assumption that missing data are randomly distributed. Dropout rates differ between drugs, suggesting this assumption may not hold true. This paper examines the effect of non-random dropout on a comparison of two antidepressant drugs, escitalopram and nortriptyline, in the treatment of major depressive disorder. The GENDEP study followed adult patients with major depressive disorder over 12 weeks of treatment, and the primary analysis found no difference in efficacy of the two antidepressants under missing at random assumption. By applying the recently developed Muthén-Roy model, we compared the relative efficacy of these two antidepressants taking into account non-random distribution of missing outcomes (NMAR). Individuals who dropped out of the study were those who were not responding to treatment. Based on the best fitting NMAR model, it was found that escitalopram reduced symptom scores by an additional 1.4 points on the Montgomery-Åsberg Depression Rating Scale (p = 0.02), equivalent to 5% of baseline depression severity, compared to nortriptyline. We conclude that association between dropout and worsening symptoms led to an overestimate of the effectiveness of treatment, especially with nortriptyline, in the primary analysis. These findings review the primary analysis of GENDEP and suggest that, when non-random dropout is accounted for, escitalopram is more effective than nortriptyline in reducing symptoms of major depression.

Sexual dysfunction during treatment with serotonergic and noradrenergic antidepressants: clinical description and the role of the 5-HTTLPR.

OBJECTIVES: Sexual dysfunction (SD) is a frequently reported side-effect of antidepressant treatment, particularly of selective serotonin reuptake inhibitors (SSRIs). In the multicentre clinical and pharmacogenetic GENDEP study (Genome-based Therapeutic Drugs for Depression), the effect of the serotonin transporter gene promoter polymorphism 5-HTTLPR on sexual function was investigated during treatment with escitalopram (SSRI) and nortriptyline (tricyclic antidepressant). METHODS: A total of 494 subjects with an episode of DSM-IV major depression were randomly assigned to treatment with escitalopram or nortriptyline. Over 12 weeks, depressive symptoms and SD were measured weekly with the Montgomery-Asberg Depression Rating Scale, the Antidepressant Side-Effect Checklist, the UKU Side Effect Rating Scale, and the Sexual Functioning Questionnaire. RESULTS: The incidence of reported SD after 12 weeks of treatment was relatively low, and did not differ significantly between antidepressants (14.9% escitalopram, 19.7% nortriptyline). There was no significant interaction between the 5-HTTLPR and antidepressant on SD. Improvement in depressive symptoms and younger age were both associated with lower SD. The effect of age on SD may have been moderated by the 5-HTTLPR. CONCLUSIONS: In GENDEP, rates of reported SD during treatment were lower than those described in previous reports. There was no apparent effect of the 5-HTTLPR on the observed decline in SD.

Melancholic, atypical and anxious depression subtypes and outcome of treatment with escitalopram and nortriptyline.

OBJECTIVE: To investigate whether subtypes of depression predict differential outcomes of treatment with selective serotonin-reuptake inhibitor (SSRI) and a tricyclic antidepressant in major depression. METHOD: Among 811 adults with moderate-to-severe depression, melancholic, atypical, anxious and anxious-somatizing depression subtypes established at baseline were evaluated as predictors of outcome of treatment with flexible dosage of the SSRI escitalopram or the tricyclic antidepressant nortriptyline. The primary outcome measure was the Montgomery-Åsberg Depression Rating Scale (MADRS). Secondary outcome measures were the 17-item Hamilton Rating Scale for Depression (HRSD-17) and the Beck Depression Inventory (BDI). RESULTS: Melancholic depression was associated with slightly worse outcomes among individuals treated with escitalopram, but did not affect outcome of treatment with nortriptyline. The interaction between melancholic depression and drug did not reach statistical significance for the primary outcome measure and significant results for secondary outcome measures were not robust in sensitivity analyses. Atypical depression was unrelated to outcome of treatment with either antidepressant. Anxious and anxious-somatizing depression did not predict outcome on the primary measure, but inconsistently predicted worse outcome in some secondary analyses. LIMITATIONS: Some participants were non-randomly allocated to drug. Therefore, drug-by-predictor interactions had to be validated in sensitivity analyses restricted to the 468 randomly allocated individuals. CONCLUSIONS: Melancholic, atypical or anxious depression, are not sufficiently robust differential predictors of outcome to help clinician choose between SSRI and tricyclic antidepressants. There is a need to investigate other predictors of outcome.

Changes in body weight during pharmacological treatment of depression.

The risk of weight gain is an important determinant of the acceptability and tolerability of antidepressant medication. To compare changes in body weight during treatment with different antidepressants, body weight and height were measured at baseline and after 6, 8, 12 and 26 wk treatment with escitalopram or nortriptyline in 630 adults with moderate-to-severe unipolar depression participating in GENDEP, a part-randomized open-label study. Weight increased significantly more during treatment with nortriptyline compared to escitalopram. The weight gain commenced during the first 6 wk of nortriptyline treatment, reached on average 1.2 kg at 12 wk (0.44-point BMI increase), and continued throughout the 6-month follow-up period. Participants who were underweight at baseline gained most weight. Participants who were obese at baseline did not gain more weight during treatment. Weight gain occurred irrespective of whether weight loss was a symptom of current depressive episode and was identified as an undesired effect of the antidepressant by most participants who gained weight. There was little weight change during treatment with escitalopram, with an average increase of 0.14 kg (0.05-point BMI increase) over 12 wk of treatment. In conclusion, treatment with the tricyclic antidepressant nortriptyline was associated with moderate weight gain, which cannot be explained as a reversal of symptomatic weight loss and is usually perceived as an undesired adverse effect. While treatment with nortriptyline may be recommended in underweight subjects with typical neurovegetative symptoms, escitalopram is a suitable alternative for subjects at risk of weight gain.

Variation in GNB3 predicts response and adverse reactions to antidepressants.

There is substantial inter-individual variation in response and adverse reactions to antidepressants, and genetic variation may, in part, explain these differences. GNB3 encodes the ß3 subunit of the G protein complex, which is involved in the downstream signalling cascade following monoamine receptor activation. A functional polymorphism in this gene (C825T) has been associated with response to antidepressants. Several lines of evidence suggest that GNB3 moderates improvement in the neurovegetative symptoms of depression (such as sleep and appetite) and related adverse reactions independently of change in core mood symptoms. We here report analysis of data from GENDEP, a part-randomized pharmacogenomic trial, on the outcome of 811 subjects with major depression undergoing treatment with either escitalopram or nortriptyline in which the C825T SNP and three further SNPs in GNB3 were genotyped. The TT genotype was significantly associated with a superior response to nortriptyline and these effects were specific to improvements in neurovegetative symptoms. In addition, the same genotype predicted fewer incidents of treatment-emergent insomnia and greater weight gain on the same drug. Our results are consistent with previous associations with GNB3 and emphasize the importance of signalling genes in antidepressant response.

Convergent animal and human evidence suggests a role of PPM1A gene in response to antidepressants.

BACKGROUND: Antidepressant drugs are used as first-line treatment in depression, but response has been shown to be highly heterogeneous, with drugs often failing to have the desired therapeutic effect. We report on an integrative analysis from the Genome-Based Therapeutic Drugs for Depression (GENDEP) study using gene expression from mice to inform prioritization in a human pharmacogenetic study. METHODS: The same two antidepressants were used in mice and humans: escitalopram (a serotonin reuptake inhibitor) and nortriptyline (a norepinephrine reuptake inhibitor). The animal study used four inbred strains of mice (129S1/SvlmJ, C57LB/6J, DBA/2J, and FVB/NJ). Hippocampus mRNA levels were measured in 144 animals using the Affymetrix MOE 430 v2 chip. RESULTS: Based on gene-expression analysis of strain-by-drug interactions, 17 genes differentially expressed with nortriptyline or escitalopram versus saline were prioritized in the human pharmacogenetic analysis. Single nucleotide polymorphisms tagging common sequence variation in human orthologs of these genes were tested for association with response to antidepressants in 706 participants of the GENDEP human pharmacogenetic study, treated with escitalopram or nortriptyline for 12 weeks, with available high-quality Illumina 610 quad array genotyping. Several polymorphisms in the protein phosphatase 1A gene (PPM1A) remained significantly associated with response to nortriptyline in humans after correction for multiple comparisons within the gene. PPM1A encodes a phosphatase involved in mitogen-activated protein kinase signaling and cell stress response. CONCLUSIONS: Convergent evidence from mice and humans suggests a role of the PPM1A in response to noradrenergic but not serotonergic antidepressants.

Genome-wide pharmacogenetics of antidepressant response in the GENDEP project.

OBJECTIVE: The purpose of this study was to identify genetic variants underlying the considerable individual differences in response to antidepressant treatment. The authors performed a genome-wide association analysis of improvement of depression severity with two antidepressant drugs. METHOD: High-quality Illumina Human610-quad chip genotyping data were available for 706 unrelated participants of European ancestry treated for major depression with escitalopram (N=394) or nortriptyline (N=312) over a 12-week period in the Genome-Based Therapeutic Drugs for Depression (GENDEP) project, a partially randomized open-label pharmacogenetic trial. RESULTS: Single nucleotide polymorphisms in two intergenic regions containing copy number variants on chromosomes 1 and 10 were associated with the outcome of treatment with escitalopram or nortriptyline at suggestive levels of significance and with a high posterior likelihood of true association. Drug-specific analyses revealed a genome-wide significant association between marker rs2500535 in the uronyl 2-sulphotransferase gene and response to nortriptyline. Response to escitalopram was best predicted by a marker in the interleukin-11 (IL11) gene. A set of 72 a priori-selected candidate genes did not show pharmacogenetic associations above a chance level, but an association with response to escitalopram was detected in the interleukin-6 gene, which is a close homologue of IL11. CONCLUSIONS: While limited statistical power means that a number of true associations may have been missed, these results suggest that efficacy of antidepressants may be predicted by genetic markers other than traditional candidates. Genome-wide studies, if properly replicated, may thus be important steps in the elucidation of the genetic basis of pharmacological response.

Serum and plasma BDNF levels in major depression: a replication study and meta-analyses.

OBJECTIVES: Alterations of BDNF signalling in major depression (MD) are supported by studies demonstrating decreased levels of the neurotrophin serum and plasma content in MD patients. We conducted a replication study and we performed two meta-analyses on studies analysing serum and plasma BDNF levels in MD patients. METHODS: The samples were composed by 489 patients/483 controls for the meta-analysis on serum and by 161 patients/211 controls for that on plasma levels. We performed also subgroup analyses to examine whether the decrease in BDNF levels in MD was influenced by gender. RESULTS: In the replication study we found decreased serum BDNF levels in MD patients (P<0.01) and we demonstrated that is down-regulated the mature form of the neurotrophin (mBDNF). No significant difference was evidenced for plasma BDNF levels. The meta-analyses showed a reduction of both BDNF serum (P<0.0001) and plasma levels (P=0.02) in MD. No difference in the effect size on serum BDNF was observed between males and females (P=0.18). CONCLUSIONS: In conclusion, our results provide evidence of peripheral BDNF alteration in MD and support the rationale for further investigation aiming to the identification of biomarkers for differential diagnosis and personalization of therapies in this disorder.