New insights into the pharmacogenomics of antidepressant response from the GENDEP and STAR*D studies: rare variant analysis and high-density imputation.

Genome-wide association studies have generally failed to identify polymorphisms associated with antidepressant response. Possible reasons include limited coverage of genetic variants that this study tried to address by exome genotyping and dense imputation. A meta-analysis of Genome-Based Therapeutic Drugs for Depression (GENDEP) and Sequenced Treatment Alternatives to Relieve Depression (STAR*D) studies was performed at the single-nucleotide polymorphism (SNP), gene and pathway levels. Coverage of genetic variants was increased compared with previous studies by adding exome genotypes to previously available genome-wide data and using the Haplotype Reference Consortium panel for imputation. Standard quality control was applied. Phenotypes were symptom improvement and remission after 12 weeks of antidepressant treatment. Significant findings were investigated in NEWMEDS consortium samples and Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) for replication. A total of 7062 950 SNPs were analyzed in GENDEP (n=738) and STAR*D (n=1409). rs116692768 (P=1.80e-08, ITGA9 (integrin α9)) and rs76191705 (P=2.59e-08, NRXN3 (neurexin 3)) were significantly associated with symptom improvement during citalopram/escitalopram treatment. At the gene level, no consistent effect was found. At the pathway level, the Gene Ontology (GO) terms GO: 0005694 (chromosome) and GO: 0044427 (chromosomal part) were associated with improvement (corrected P=0.007 and 0.045, respectively). The association between rs116692768 and symptom improvement was replicated in PGRN-AMPS (P=0.047), whereas rs76191705 was not. The two SNPs did not replicate in NEWMEDS. ITGA9 codes for a membrane receptor for neurotrophins and NRXN3 is a transmembrane neuronal adhesion receptor involved in synaptic differentiation. Despite their meaningful biological rationale for being involved in antidepressant effect, replication was partial. Further studies may help in clarifying their role.

Copy number variants and therapeutic response to antidepressant medication in major depressive disorder.

It would be beneficial to find genetic predictors of antidepressant response to help personalise treatment of major depressive disorder (MDD). Rare copy number variants (CNVs) have been implicated in several psychiatric disorders, including MDD, but their role in antidepressant response has yet to be investigated. CNV data were available for 1565 individuals with MDD from the NEWMEDS (Novel Methods leading to New Medications in Depression and Schizophrenia) consortium with prospective data on treatment outcome with either a serotonergic or noradrenergic antidepressant. No association was seen between the presence of CNV (rare or common), the overall number of CNVs or genomic CNV 'burden' and antidepressant response. Specific CNVs were nominally associated with antidepressant response, including 15q13.3 duplications and exonic NRXN1 deletions. These were associated with poor response to antidepressants. Overall burden of CNVs is unlikely to contribute to personalising antidepressant treatment. Specific CNVs associated with antidepressant treatment require replication and further study to confirm their role in the therapeutic action of antidepressant.

Estimating the heritability of reporting stressful life events captured by common genetic variants.

BACKGROUND: Although usually thought of as external environmental stressors, a significant heritable component has been reported for measures of stressful life events (SLEs) in twin studies. Method We examined the variance in SLEs captured by common genetic variants from a genome-wide association study (GWAS) of 2578 individuals. Genome-wide complex trait analysis (GCTA) was used to estimate the phenotypic variance tagged by single nucleotide polymorphisms (SNPs). We also performed a GWAS on the number of SLEs, and looked at correlations between siblings. RESULTS: A significant proportion of variance in SLEs was captured by SNPs (30%, p = 0.04). When events were divided into those considered to be dependent or independent, an equal amount of variance was explained for both. This 'heritability' was in part confounded by personality measures of neuroticism and psychoticism. A GWAS for the total number of SLEs revealed one SNP that reached genome-wide significance (p = 4 × 10-8), although this association was not replicated in separate samples. Using available sibling data for 744 individuals, we also found a significant positive correlation of R 2 = 0.08 in SLEs (p = 0.03). CONCLUSIONS: These results provide independent validation from molecular data for the heritability of reporting environmental measures, and show that this heritability is in part due to both common variants and the confounding effect of personality.

Non-steroidal anti-inflammatory drugs and efficacy of antidepressants in major depressive disorder.

BACKGROUND: It has been proposed that non-steroidal anti-inflammatory drugs (NSAIDs) may interfere with the efficacy of antidepressants and contribute to treatment resistance in major depressive disorder (MDD). This effect requires replication and a test of whether it is specific to serotonin-reuptake inhibiting (SRI) antidepressants. METHOD: We tested the effect of concomitant medication with NSAIDs on the efficacy of escitalopram, a SRI antidepressant, and nortriptyline, a tricyclic antidepressant, among 811 subjects with MDD treated for up to 12 weeks in the GENDEP study. Effects of NSAIDs on improvement of depressive symptoms were tested in mixed-effect linear models. Effects on remission were tested in logistic regression. Age, sex, baseline severity and centre of recruitment were considered as potential confounding factors. RESULTS: Ten percent (n=78) of subjects were taking NSAIDs during the antidepressant treatment. Older subjects were significantly more likely to take NSAIDs. After controlling for age, sex, centre of recruitment and baseline severity, concomitant medication with NSAIDs did not significantly influence the efficacy of escitalopram [ß=0.035, 95% confidence interval (CI) -0.145 to 0.215, p=0.704] or nortriptyline (ß=0.075, 95% CI -0.131 to 0.281, p=0.476). Although slightly fewer subjects who took NSAIDs reached remission [odds ratio (OR) 0.80, 95% CI 0.49-1.31, p=0.383], this non-significant effect was reversed after controlling for age, sex, baseline severity and recruitment centre effects (OR 1.04, 95% CI 0.61-1.77, p=0.882). CONCLUSIONS: NSAIDs are unlikely to affect the efficacy of SRI or other antidepressants. Concurrent use of NSAIDs and antidepressants does not need to be avoided.

Interaction between serotonin transporter gene variants and life events predicts response to antidepressants in the GENDEP project.

There is substantial inter-individual variation in response to antidepressants, and genetic variation may, in part, explain these differences. For example, there is evidence to suggest that variation in the serotonin transporter gene (SLC6A4) predicts response to selective serotonin reuptake inhibitors (SSRIs). Environmental factors such as the occurrence of stressful life events before treatment may also be important. One prior report suggests that both factors interact in predicting response to antidepressants. GENDEP, a prospective part-randomized pharmacogenomics trial, collected longitudinal data on the outcome of 811 patients with major depression undergoing treatment with either an SSRI (escitalopram) or a tricyclic antidepressant (nortriptyline). Life events experienced over 6 months preceding treatment were measured using a List of Threatening Experiences Questionnaire, and several polymorphisms in the serotonin transporter gene (SLC6A4) have been genotyped including the serotonin transporter-linked polymorphic region (5-HTTLPR). Stressful life events were shown to predict a significantly better response to escitalopram but had no effect on response to nortriptyline. Variation in the 5-HTTLPR and another polymorphism in the gene, STin4, significantly modified these effects. Gene-environment interactions including life events may therefore be important not only in the aetiology of depression, but also in predicting response to antidepressant medication.

Trajectories of change in depression severity during treatment with antidepressants.

BACKGROUND: Response and remission defined by cut-off values on the last observed depression severity score are commonly used as outcome criteria in clinical trials, but ignore the time course of symptomatic change and may lead to inefficient analyses. We explore alternative categorization of outcome by naturally occurring trajectories of symptom change. METHOD: Growth mixture models were applied to repeated measurements of depression severity in 807 participants with major depression treated for 12 weeks with escitalopram or nortriptyline in the part-randomized Genome-based Therapeutic Drugs for Depression study. Latent trajectory classes were validated as outcomes in drug efficacy comparison and pharmacogenetic analyses. RESULTS: The final two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants and showed an antidepressant-specific pattern of pharmacogenetic associations. In contrast, conventional response and remission favoured escitalopram and produced chance results in pharmacogenetic analyses. Controlling for drop-out reduced drug differences on response and remission but did not affect latent trajectory results. CONCLUSIONS: Latent trajectory mixture models capture heterogeneity in the development of clinical response after the initiation of antidepressants and provide an outcome that is distinct from traditional endpoint measures. It differentiates between antidepressants with different modes of action and is robust against bias due to differential discontinuation.

Laterality effect on emotional faces processing: ALE meta-analysis of evidence.

Recognizing emotion from facial expressions draws on diverse psychological processes implemented in a large array of neural structures. Two major theories of cerebral lateralization of emotional perception have been proposed: (i) the Right-Hemisphere Hypothesis (RHH) and (ii) the Valence-Specific Hypothesis (VSH). To test these lateralization models we conducted a large voxel-based meta-analysis of current functional magnetic resonance imaging (fMRI) studies employing emotional faces paradigms in healthy volunteers. Two independent researchers conducted separate comprehensive PUBMED (1990-May 2008) searches to find all functional magnetic resonance imaging studies using a variant of the emotional faces paradigm in healthy subjects. Out of the 551 originally identified studies, 105 studies met inclusion criteria. The overall database consisted of 1785 brain coordinates which yield an overall sample of 1600 healthy subjects. We found no support for the hypothesis of overall right-lateralization of emotional processing. Conversely, across all emotional conditions the parahippocampal gyrus and amygdala, fusiform gyrus, lingual gyrus, precuneus, inferior and middle occipital gyrus, posterior cingulated, middle temporal gyrus, inferior frontal and superior frontal gyri were activated bilaterally (p=0.001). There was a valence-specific lateralization of brain response during negative emotions processing in the left amygdala (p=0.001). Significant interactions between the approach and avoidance dimensions and prefrontal response were observed (p=0.001).

Measuring depression: comparison and integration of three scales in the GENDEP study.

BACKGROUND: A number of scales are used to estimate the severity of depression. However, differences between self-report and clinician rating, multi-dimensionality and different weighting of individual symptoms in summed scores may affect the validity of measurement. In this study we examined and integrated the psychometric properties of three commonly used rating scales. METHOD: The 17-item Hamilton Depression Rating Scale (HAMD-17), the Montgomery-Asberg Depression Rating Scale (MADRS) and the Beck Depression Inventory (BDI) were administered to 660 adult patients with unipolar depression in a multi-centre pharmacogenetic study. Item response theory (IRT) and factor analysis were used to evaluate their psychometric properties and estimate true depression severity, as well as to group items and derive factor scores. RESULTS: The MADRS and the BDI provide internally consistent but mutually distinct estimates of depression severity. The HAMD-17 is not internally consistent and contains several items less suitable for out-patients. Factor analyses indicated a dominant depression factor. A model comprising three dimensions, namely 'observed mood and anxiety', 'cognitive' and 'neurovegetative', provided a more detailed description of depression severity. CONCLUSIONS: The MADRS and the BDI can be recommended as complementary measures of depression severity. The three factor scores are proposed for external validation.