Context Efficacy of antidepressant treatment in depression is unsatisfactory as one in three patients does not fully recover even after several treatment trials. Genetic factors and clinical characteristics contribute to the failure of a favorable treatment outcome. Objective To identify genetic and clinical determinants of antidepressant treatment outcome in depression. Design Genome-wide pharmacogenetic association study with two independent replication samples. Setting We performed a genome-wide association (GWA) study in patients from the Munich-Antidepressant-Response-Signature (MARS) project and in pooled DNA from an independent German replication sample. A set of 328 single nucleotide polymorphisms (SNPs) highly related to outcome in both GWA studies was genotyped in a sample of the Sequenced-Treatment-Alternatives-to-Relieve-Depression (STAR*D) study. Participants 339 inpatients suffering from a depressive episode (MARS sample), further 361 depressed inpatients (German replication sample), and 832 outpatients with major depression (STAR*D sample). Main Outcome Measures We generated a multi-locus genetic variable describing the individual number of alleles of the selected SNPs associated with beneficial treatment outcome in the MARS sample (“response” alleles) to evaluate additive genetic effects on antidepressant treatment outcome. Results Multi-locus analysis revealed a significant contribution of a binary variable categorizing patients as carriers of a high vs. low number of response alleles in predicting antidepressant treatment outcome in both samples, MARS and STAR*D. In addition, we observed that patients with a comorbid anxiety disorder in combination with a low number of response alleles showed the least favorable outcome. Conclusion Our results demonstrate the importance of multiple genetic factors in combination with clinical features to predict antidepressant treatment outcome underscoring the multifactorial nature of this trait.

Major depression (MD) is one of the most prevalent psychiatric disorders and a leading cause of loss in work productivity. A combination of genetic and environmental risk factors likely contributes to MD. We present data from a genome-wide association study revealing a neuron-specific neutral amino acid transporter (SLC6A15) as a novel susceptibility gene for MD. Risk allele carrier status in humans and chronic stress in mice were associated with a downregulation of the expression of this gene in the hippocampus, a brain region implicated in the pathophysiology of MD. The same polymorphisms also showed associations with alterations in hippocampal volume and neuronal integrity. Thus, decreased SLC6A15 expression, due to genetic or environmental factors might alter neuronal circuits related to the susceptibility for MD. Our convergent data from human genetics, expression studies, brain imaging and animal models suggest a novel pathophysiological mechanism for MD that may be accessible to drug targeting.

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Single-nucleotide polymorphisms (SNPs) in the FKBP5, GRIK4, and HTR2A genes have been shown to be associated with response to citalopram treatment in the STAR*D sample, but only associations with FKBP5 have so far been tested in the Munich Antidepressant Response Signature (MARS) project. Response and remission of depressive symptoms after 5 weeks of antidepressant treatment were tested against 82 GRIK4 and 37 HTR2A SNPs. Association analysis was conducted in about 300 depressed patients from the MARS project, 10% of whom had bipolar disorder. The most predictive SNPs from these two genes and rs1360780 in FKBP5 were then genotyped in a total of 387 German depressed in-patients to analyze potential additive and interactive effects of these variants. We could not replicate previous findings of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study in our sample. Although not statistically significant, the effect for the best GRIK4 SNP of STAR*D (rs1954787, p ¼ 0.076, p corrected ¼ 0.98) seemed to be in the same direction. On the other hand, the nominally significant association with the top HTR2A SNPs of STAR*D (rs7997012, allelic, p ¼ 0.043, p corrected ¼ 0.62) was with the opposite risk allele. The GRIK4 SNP (rs12800734, genotypic, p ¼ 0.0019, p corrected ¼ 0.12) and the HTR2A SNP (rs17288723, genotypic, p ¼ 0.0011, p corrected ¼ 0.02), which showed the strongest association with remission in our sample, had not been reported previously. Associations across all genetic markers within the GRIK4 (genotypic, p ¼ 0.022) or HTR2A (genotypic, p ¼ 0.012) locus using the Fisher's product method (FPM) were also significant. In all 374 patients, the best predictive model included a main effect for GRIK4 rs12800734 and two significant interactions between GRIK4 rs12800734 and FKBP5 rs1360780, and GRIK4 rs12800734 and HTR2A rs17288723. This three SNP model explained 13.1% of the variance for remission after 5 weeks (p ¼ 0.00051 for the model). Analyzing a sub-sample of 194 patients, plasma ACTH (p ¼ 0.002) and cortisol (p ¼ 0.021) responses of rs12800734 GG (GRIK4) carriers, who also showed favorable treatment response, were significantly lower in the second combined dexamethasone (dex)/corticotrophin-releasing hormone (CRH) test before discharge compared with the other two genotype groups. Despite large differences in ethnicity and design compared with the STAR*D study, our results from the MARS study further support both independent and interactive involvement of GRIK4, HTR2A and FKBP5 in antidepressant treatment response.

Context A consistent body of evidence supports a role of reduced neurotrophic signaling in the pathophysiology of major depressive disorder (MDD) and suicidal behavior. Especially in suicide victims, lower postmortem brain messenger RNA and protein levels of neurotrophins and their receptors have been reported. Objective To determine whether the brain-derived neurotrophic factor (BDNF) gene or its high-affinity receptor gene, receptor tyrosine kinase 2 (NTRK2), confer risk for suicide attempt (SA) and MDD by investigating common genetic variants in these loci. Design Eighty-three tagging single-nucleotide polymorphisms (SNPs) covering the genetic variability of these loci in European populations were assessed in a casecontrol association design. Setting Inpatients and screened control subjects. Participants The discovery sample consisted of 394 depressed patients, of whom 113 had SA, and 366 matched healthy control subjects. The replication studies comprised 744 German patients with MDD and 921 African American nonpsychiatric clinic patients, of whom 152 and 119 were positive for SA, respectively. Interventions Blood or saliva samples were collected from each participant for DNA extraction and genotyping. Main Outcome Measures Associations of SNPs in BDNF and NTRK2 with SA and MDD. Results Independent SNPs within NTRK2 were associated with SA among depressed patients of the discovery sample that could be confirmed in both the German and African American replication samples. Multilocus interaction analysis revealed that single SNP associations within this locus contribute to the risk of SA in a multiplicative and interactive fashion (P = 4.7× 10−7 for a 3-SNP model in the combined German sample). The effect size was 4.5 (95% confidence interval, 2.1–9.8) when patients carrying risk genotypes in all 3 markers were compared with those without any of the 3 risk genotypes. Conclusions Our results suggest that a combination of several independent risk alleles within the NTRK2 locus is associated with SA in depressed patients, further supporting a role of neurotrophins in the pathophysiology of suicide.

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Psychiatric disorders are ubiquitously characterized by debilitating social impairments. These difficulties are thought to emerge from aberrant social inference. In order to elucidate the underlying computational mechanisms, patients diagnosed with major depressive disorder (N = 29), schizophrenia (N = 31), and borderline personality disorder (N = 31) as well as healthy controls (N = 34) performed a probabilistic reward learning task in which participants could learn from social and non-social information. Patients with schizophrenia and borderline personality disorder performed more poorly on the task than healthy controls and patients with major depressive disorder. Broken down by domain, borderline personality disorder patients performed better in the social compared to the non-social domain. In contrast, controls and major depressive disorder patients showed the opposite pattern and schizophrenia patients showed no difference between domains. In effect, borderline personality disorder patients gave up a possible overall performance advantage by concentrating their learning in the social at the expense of the non-social domain. We used computational modeling to assess learning and decision-making parameters estimated for each participant from their behavior. This enabled additional insights into the underlying learning and decision-making mechanisms. Patients with borderline personality disorder showed slower learning from social and non-social information and an exaggerated sensitivity to changes in environmental volatility, both in the non-social and the social domain, but more so in the latter. Regarding decision-making the modeling revealed that compared to controls and major depression patients, patients with borderline personality disorder and schizophrenia showed a stronger reliance on social relative to non-social information when making choices. Depressed patients did not differ significantly from controls in this respect. Overall, our results are consistent with the notion of a general interpersonal hypersensitivity in borderline personality disorder and schizophrenia based on a shared computational mechanism characterized by an over-reliance on beliefs about others in making decisions and by an exaggerated need to make sense of others during learning specifically in borderline personality disorder.

Emergence of suicidal ideation (TESI) during treatment with antidepressants in major depression led to a black box warning. We performed a genome-wide association study to identify genetic markers, which increase the risk for this serious side effect. TESI was evaluated in depressed in-patients (N ¼ 397) and defined by an emergence of suicidal thoughts during hospitalization without suicidal thoughts at admission using the suicide item (3) of the Hamilton Depression Rating Scale. Genotype distribution of 405.383 singlenucleotide polymorphisms (SNPs) in patients with TESI (N ¼ 32/8.1%) was compared to patients without increase in suicidal ideation (N ¼ 329/82.9%) and to a subgroup never reported suicidal ideation (N ¼ 79/19.9%). Top results were analyzed in an independent sample (N ¼ 501). None variant reached genome-wide significance, the best associated SNP was rs1630535 (p-value ¼ 1.3 Â 10 À7 ). The top 79 SNPs could be analyzed in an independent sample, and 14 variants showed nominal significant association with the same risk allele in the replication sample. A discriminant analysis classifying patients using these 79 SNPs revealed a 91% probability to classify TESI vs non-TESI cases correctly in the replication sample. Although our data need to be interpreted carefully owing to the small numbers in both cohorts, they suggest that a combination of genetic markers might indeed be used to identify patients at risk for TESI.