Pharmacogenetics studies in STAR*D: strengths, limitations, and results

Pharmacogenetic Factors Influence Escitalopram Pharmacokinetics and Adverse Events in Youth with a Family History of Bipolar Disorder: A Preliminary Study

Introduction: Escitalopram is an effective and generally well-tolerated antidepressant, but children of parents with bipolar disorder (BD) may be at increased risk for adverse events associated with antidepressants, including increased irritability, restlessness, impulsivity, and manic symptoms. This risk may be influenced by polymorphisms in genes encoding cytochrome P450 enzymes (CYP2C19 or CYP2D6), the serotonin transporter (SLC6A4), and the serotonin receptor 2A subtype (HTR2A). We explored whether gene-drug interactions influence the emergence of adverse events in depressed and/or anxious youth with a family history of BD. Materials and Methods: Children and adolescents aged 12-17 years with a first-degree relative with bipolar I disorder were treated with escitalopram and monitored for adverse effects, underwent pharmacogenetic testing, and provided serum escitalopram levels. Emergence of adverse events was determined by study clinicians, and symptoms were tracked using the Treatment-Emergent Activation and Suicidality Assessment Profile (TEASAP) and Pediatric Adverse Events Rating Scale. Clinical Pharmacogenetics Implementation Consortium guidelines were used to determine CYP2C19 and CYP2D6 phenotypes. Results: Slower CYP2C19 metabolizers had greater dose-normalized 24-hour area under the curve (AUC0-24; p = 0.025), trough concentrations (Ctrough; p = 0.013), and elimination half-lives (t1/2; p < 0.001). CYP2D6 phenotype was not significantly associated with any pharmacokinetic parameter. Slower CYP2D6 metabolizers had increased TEASAP akathisia (p = 0.015) scores. HTR2A A/A and A/G genotypes were associated with increased TEASAP "self-injury, suicidality, and harm to others" subscale scores (p = 0.017). Escitalopram maximum concentration, AUC0-24, CYP2C19 phenotype, and SLC6A4 genotype were not associated with adverse events. Conclusions: CYP2C19 phenotype influences escitalopram pharmacokinetics whereas CYP2D6 phenotype does not. Slower CYP2D6 metabolism was associated with increased akathisia, and HTR2A A/A or A/G genotypes were associated with increased risk of self-harm or harm to others. Larger cohorts are needed to identify associations between genetic test results and antidepressant-associated adverse events. Trial Registration: ClinicalTrials.gov identifier: NCT02553161.

Glutamate and depression: Reflecting a deepening knowledge of the gut and brain effects of a ubiquitous molecule

The versatility of glutamate as the brain’s foremost excitatory neurotransmitter and modulator of neurotransmission and function is considered common knowledge. Years of research have continued to uncover glutamate’s effects and roles in several neurological and neuropsychiatric disorders, including depression. It had been considered that a deeper understanding of the roles of glutamate in depression might open a new door to understanding the pathological basis of the disorder, improve the approach to patient management, and lead to the development of newer drugs that may benefit more patients. This review examines our current understanding of the roles of endogenous and exogenous sources of glutamate and the glutamatergic system in the aetiology, progression and management of depression. It also examines the relationships that link the gut-brain axis, glutamate and depression; as it emphasizes how the gut-brain axis could impact depression pathogenesis and management via changes in glutamate homeostasis. Finally, we consider what the likely future of glutamate-based therapies and glutamate-based therapeutic manipulations in depression are, and if with them, we are now on the final chapter of understanding the neurochemical milieu of depressive disorders.

Predicting SSRI-Resistance: Clinical Features and tagSNPs Prediction Models Based on Support Vector Machine

BACKGROUND

A large proportion of major depressive patients will experience recurring episodes. Many patients still do not response to available antidepressants. In order to meaningfully predict who will not respond to which antidepressant, it may be necessary to combine multiple biomarkers and clinical variables.

METHODS

Eight hundred fifty-seven patients with recurrent major depressive disorder who were followed up 3-10 years involved 32 variables including socio-demographic, clinical features, and SSRIs treatment features when they received the first treatment. Also, 34 tagSNPs related to 5-HT signaling pathway, were detected by using mass spectrometry analysis. The training samples which had 12 clinical variables and four tagSNPs with statistical differences were learned repeatedly to establish prediction models based on support vector machine (SVM).

RESULTS

Twelve clinical features (psychomotor retardation, psychotic symptoms, suicidality, weight loss, SSRIs average dose, first-course treatment response, sleep disturbance, residual symptoms, personality, onset age, frequency of episode, and duration) were found significantly difference (P< 0.05) between 302 SSRI-resistance and 304 SSRI non-resistance group. Ten SSRI-resistance predicting models were finally selected by using support vector machine, and our study found that mutations in tagSNPs increased the accuracy of these models to a certain degree.

CONCLUSION

Using a data-driven machine learning method, we found 10 predictive models by mining existing clinical data, which might enable prospective identification of patients who are likely to resistance to SSRIs antidepressant.

Genetic endophenotypes for insomnia of major depressive disorder and treatment-induced insomnia

Major depressive disorder (MDD) is primarily hinged on the presence of either low mood and/or anhedonia to previously pleasurable events for a minimum of 2 weeks. Other clinical features that characterize MDD include disturbances in sleep, appetite, concentration and thoughts. The combination of any/both of the primary MDD symptoms as well as any four of the other clinical features has been referred to as MDD. The challenge for replicating gene association findings with phenotypes of MDD as well as its treatment outcome is putatively due to stratification of MDD patients. Likelihood for replication of gene association findings is hypothesized with specificity in symptoms profile (homogenous clusters of symptom/individual symptoms) evaluated. The current review elucidates the genetic factors that have been associated with insomnia symptom of MDD phenotype, insomnia symptom as a constellation of neuro-vegetative cluster of MDD symptom, insomnia symptom of MDD as an individual entity and insomnia feature of treatment outcome. Homozygous CC genotype of 3111T/C, GSK3B-AT/TT genotype of rs33458 and haplotype of TPH1 218A/C were associated with insomnia symptom of MDD. Insomnia symptom of MDD was not resolved in patients with the A/A genotype of HTR2A-rs6311 when treated with SSRI. Homozygous short (SS) genotype-HTTLPR, GG genotype of HTR2A-rs6311 and CC genotype of HTR2A-rs6313 were associated with AD treatment-induced insomnia, while val/met genotype of BDNF-rs6265 and the TT genotype of GSK-3beta-rs5443 reduced it. Dearth of association studies may remain the bane for the identification of robust genetic endophenotypes in line with findings for genotypes of HTR2A-rs6311.

Role of glucocorticoid negative feedback in the regulation of HPA axis pulsatility

The hypothalamic-pituitary-adrenal (HPA) axis is the major neuroendocrine axis regulating homeostasis in mammals. Glucocorticoid hormones are rapidly synthesized and secreted from the adrenal gland in response to stress. In addition, under basal conditions glucocorticoids are released rhythmically with both a circadian and an ultradian (pulsatile) pattern. These rhythms are important not only for normal function of glucocorticoid target organs, but also for the HPA axis responses to stress. Several studies have shown that disruption of glucocorticoid rhythms is associated with disease both in humans and in rodents. In this review, we will discuss our knowledge of the negative feedback mechanisms that regulate basal ultradian synthesis and secretion of glucocorticoids, including the role of glucocorticoid and mineralocorticoid receptors and their chaperone protein FKBP51. Moreover, in light of recent findings, we will also discuss the importance of intra-adrenal glucocorticoid receptor signaling in regulating glucocorticoid synthesis.

A Role for Phosphodiesterase 11A (PDE11A) in the Formation of Social Memories and the Stabilization of Mood

The most recently discovered 3',5'-cyclic nucleotide phosphodiesterase family is the Phosphodiesterase 11 (PDE11) family, which is encoded by a single gene PDE11A. PDE11A is a dual-specific PDE, breaking down both cAMP and cGMP. There are four PDE11A splice variants (PDE11A1-4) with distinct tissue expression profiles and unique N-terminal regulatory regions, suggesting that each isoform could be individually targeted with a small molecule or biologic. PDE11A4 is the PDE11A isoform expressed in brain and is found in the hippocampal formation of humans and rodents. Studies in rodents show that PDE11A4 mRNA expression in brain is, in fact, restricted to the hippocampal formation (CA1, possibly CA2, subiculum, and the adjacently connected amygdalohippocampal area). Within the hippocampal formation of rodents, PDE11A4 protein is expressed in neurons but not astrocytes, with a distribution across nuclear, cytoplasmic, and membrane compartments. This subcellular localization of PDE11A4 is altered in response to social experience in mouse, and in vitro studies show the compartmentalization of PDE11A4 is controlled, at least in part, by homodimerization and N-terminal phosphorylation. PDE11A4 expression dramatically increases in the hippocampus with age in the rodent hippocampus, from early postnatal life to late aging, suggesting PDE11A4 function may evolve across the lifespan. Interestingly, PDE11A4 protein shows a three to tenfold enrichment in the rodent ventral hippocampal formation (VHIPP; a.k.a. anterior in primates) versus dorsal hippocampal formation (DHIPP). Consistent with this enrichment in VHIPP, studies in knockout mice show that PDE11A regulates the formation of social memories and the stabilization of mood and is a critical mechanism by which social experience feeds back to modify the brain and subsequent social behaviors. PDE11A4 likely controls behavior by regulating hippocampal glutamatergic, oxytocin, and cytokine signaling, as well as protein translation. Given its unique tissue distribution and relatively selective effects on behavior, PDE11A may represent a novel therapeutic target for neuropsychiatric, neurodevelopmental, or age-related disorders. Therapeutically targeting PDE11A4 may be a way to selectively restore aberrant cyclic nucleotide signaling in the hippocampal formation while leaving the rest of the brain and periphery untouched, thus, relieving deficits while avoiding unwanted side effects.

PDE11A negatively regulates lithium responsivity

Lithium responsivity in patients with bipolar disorder has been genetically associated with Phosphodiesterase 11A (PDE11A), and lithium decreases PDE11A mRNA in induced pluripotent stem cell-derived hippocampal neurons originating from lithium-responsive patients. PDE11 is an enzyme uniquely enriched in the hippocampus that breaks down cyclic AMP and cyclic GMP. Here we determined whether decreasing PDE11A expression is sufficient to increase lithium responsivity in mice. In dorsal hippocampus and ventral hippocampus (VHIPP), lithium-responsive C57BL/6J and 129S6/SvEvTac mice show decreased PDE11A4 protein expression relative to lithium-unresponsive BALB/cJ mice. In VHIPP, C57BL/6J mice also show differences in PDE11A4 compartmentalization relative to BALB/cJ mice. In contrast, neither PDE2A nor PDE10A expression differ among the strains. The compartment-specific differences in PDE11A4 protein expression are explained by a coding single-nucleotide polymorphism (SNP) at amino acid 499, which falls within the GAF-B homodimerization domain. Relative to the BALB/cJ 499T, the C57BL/6J 499A decreases PDE11A4 homodimerization, which removes PDE11A4 from the membrane. Consistent with the observation that lower PDE11A4 expression correlates with better lithium responsiveness, we found that Pde11a knockout mice (KO) given 0.4% lithium chow for 3+ weeks exhibit greater lithium responsivity relative to wild-type (WT) littermates in tail suspension, an antidepressant-predictive assay, and amphetamine hyperlocomotion, an anti-manic predictive assay. Reduced PDE11A4 expression may represent a lithium-sensitive pathophysiology, because both C57BL/6J and Pde11a KO mice show increased expression of the pro-inflammatory cytokine interleukin-6 (IL-6) relative to BALB/cJ and PDE11A WT mice, respectively. Our finding that PDE11A4 negatively regulates lithium responsivity in mice suggests that the PDE11A SNPs identified in patients may be functionally relevant.

TSPAN5, ERICH3 and selective serotonin reuptake inhibitors in major depressive disorder: pharmacometabolomics-informed pharmacogenomics

Millions of patients suffer from major depressive disorder (MDD), but many do not respond to selective serotonin reuptake inhibitor (SSRI) therapy. We used a pharmacometabolomics-informed pharmacogenomics research strategy to identify genes associated with metabolites that were related to SSRI response. Specifically, 306 MDD patients were treated with citalopram or escitalopram and blood was drawn at baseline, 4 and 8 weeks for blood drug levels, genome-wide single nucleotide polymorphism (SNP) genotyping and metabolomic analyses. SSRI treatment decreased plasma serotonin concentrations (P<0.0001). Baseline and plasma serotonin concentration changes were associated with clinical outcomes (P<0.05). Therefore, baseline and serotonin concentration changes were used as phenotypes for genome-wide association studies (GWAS). GWAS for baseline plasma serotonin concentrations revealed a genome-wide significant (P=7.84E-09) SNP cluster on chromosome four 5' of TSPAN5 and a cluster across ERICH3 on chromosome one (P=9.28E-08) that were also observed during GWAS for change in serotonin at 4 (P=5.6E-08 and P=7.54E-07, respectively) and 8 weeks (P=1.25E-06 and P=3.99E-07, respectively). The SNPs on chromosome four were expression quantitative trait loci for TSPAN5. Knockdown (KD) and overexpression (OE) of TSPAN5 in a neuroblastoma cell line significantly altered the expression of serotonin pathway genes (TPH1, TPH2, DDC and MAOA). Chromosome one SNPs included two ERICH3 nonsynonymous SNPs that resulted in accelerated proteasome-mediated degradation. In addition, ERICH3 and TSPAN5 KD and OE altered media serotonin concentrations. Application of a pharmacometabolomics-informed pharmacogenomic research strategy, followed by functional validation, indicated that TSPAN5 and ERICH3 are associated with plasma serotonin concentrations and may have a role in SSRI treatment outcomes.

Seeking an objective diagnosis of depression

Major depressive disorder (MDD: unipolar depression) is widely distributed in the USA and world-wide populations and it is one of the leading causes of disability in both adolescents and adults. Traditional diagnostic approaches for MDD are based on patient interviews, which provide a subjective assessment of clinical symptoms which are frequently shared with other maladies. Reliance upon clinical assessments and patient interviews for diagnosing MDD is frequently associated with misdiagnosis and suboptimal treatment outcomes. As such, there is increasing interest in the identification of objective methods for the diagnosis of depression. Newer technologies from genomics, transcriptomics, proteomics, metabolomics and imaging are technically sophisticated and objective but their application to diagnostic tests in psychiatry is still emerging. This brief overview evaluates the technical basis for these technologies and discusses how the extension of their clinical performance can lead to an objective diagnosis of MDD.

A genome-wide association study of antidepressant response in Koreans

We conducted a three-stage genome-wide association study (GWAS) of response to antidepressant drugs in an ethnically homogeneous sample of Korean patients in untreated episodes of nonpsychotic unipolar depression, mostly of mature onset. Strict quality control was maintained in case selection, diagnosis, verification of adherence and outcome assessments. Analyzed cases completed 6 weeks of treatment with adequate plasma drug concentrations. The overall successful completion rate was 85.5%. Four candidate single-nucleotide polymorphisms (SNPs) on three chromosomes were identified by genome-wide search in the discovery sample of 481 patients who received one of four allowed selective serotonin reuptake inhibitor (SSRI) antidepressant drugs (Stage 1). In a focused replication study of 230 SSRI-treated patients, two of these four SNP candidates were confirmed (Stage 2). Analysis of the Stage 1 and Stage 2 samples combined (n = 711) revealed GWAS significance (P = 1.60 × 10(-8)) for these two SNP candidates, which were in perfect linkage disequilibrium. These two significant SNPs were confirmed also in a focused cross-replication study of 159 patients treated with the non-SSRI antidepressant drug mirtazapine (Stage 3). Analysis of the Stage 1, Stage 2 and Stage 3 samples combined (n = 870) also revealed GWAS significance for these two SNPs, which was sustained after controlling for gender, age, number of previous episodes, age at onset and baseline severity (P = 3.57 × 10(-8)). For each SNP, the response rate decreased (odds ratio=0.31, 95% confidence interval: 0.20-0.47) as a function of the number of minor alleles (non-response alleles). The two SNPs significantly associated with antidepressant response are rs7785360 and rs12698828 of the AUTS2 gene, located on chromosome 7 in 7q11.22. This gene has multiple known linkages to human psychological functions and neurobehavioral disorders. Rigorous replication efforts in other ethnic populations are recommended.

Association of FKBP51 with priming of autophagy pathways and mediation of antidepressant treatment response: evidence in cells, mice, and humans

BACKGROUND

FK506 binding protein 51 (FKBP51) is an Hsp90 co-chaperone and regulator of the glucocorticoid receptor, and consequently of stress physiology. Clinical studies suggest a genetic link between FKBP51 and antidepressant response in mood disorders; however, the underlying mechanisms remain elusive. The objective of this study was to elucidate the role of FKBP51 in the actions of antidepressants, with a particular focus on pathways of autophagy.

METHODS AND FINDINGS

Established cell lines, primary neural cells, human blood cells of healthy individuals and patients with depression, and mice were treated with antidepressants. Mice were tested for several neuroendocrine and behavioral parameters. Protein interactions and autophagic pathway activity were mainly evaluated by co-immunoprecipitation and Western blots. We first show that the effects of acute antidepressant treatment on behavior are abolished in FKBP51 knockout (51KO) mice. Autophagic markers, such as the autophagy initiator Beclin1, were increased following acute antidepressant treatment in brains from wild-type, but not 51KO, animals. FKBP51 binds to Beclin1, changes decisive protein interactions and phosphorylation of Beclin1, and triggers autophagic pathways. Antidepressants and FKBP51 exhibited synergistic effects on these pathways. Using chronic social defeat as a depression-relevant stress model in combination with chronic paroxetine (PAR) treatment revealed that the stress response, as well as the effects of antidepressants on behavior and autophagic markers, depends on FKBP51. In human blood cells of healthy individuals, FKBP51 levels correlated with the potential of antidepressants to induce autophagic pathways. Importantly, the clinical antidepressant response of patients with depression (n = 51) could be predicted by the antidepressant response of autophagic markers in patient-derived peripheral blood lymphocytes cultivated and treated ex vivo (Beclin1/amitriptyline: r = 0.572, p = 0.003; Beclin1/PAR: r = 0.569, p = 0.004; Beclin1/fluoxetine: r = 0.454, p = 0.026; pAkt/amitriptyline: r =  -0.416, p = 0.006; pAkt/PAR: r =  -0.355, p = 0.021; LC3B-II/PAR: r = 0.453, p = 0.02), as well as by the lymphocytic expression levels of FKBP51 (r = 0.631, p<0.0001), pAkt (r =  -0.515, p = 0.003), and Beclin1 (r = 0.521, p = 0.002) at admission. Limitations of the study include the use of male mice only and the relatively low number of patients for protein analyses.

CONCLUSIONS

To our knowledge, these findings provide the first evidence for the molecular mechanism of FKBP51 in priming autophagic pathways; this process is linked to the potency of at least some antidepressants. These newly discovered functions of FKBP51 also provide novel predictive markers for treatment outcome, consistent with physiological and potential clinical relevance. Please see later in the article for the Editors' Summary.

Genetic prediction of antidepressant drug response and nonresponse in Korean patients

Genetic polymorphism contributes to variation in response to drug treatment of depression. We conducted three independent 6-week treatment studies in outpatients with major depressive disorder (MDD) to develop a pharmacogenomic model predicting response and nonresponse. We screened candidate genomic markers for association with response to selective serotonin reuptake inhibitors (SSRIs). No patients had received any antidepressant drug treatment in the current episode of depression. Outcome evaluation was blinded to drug and genotype data. The prediction model derived from a development sample of 239 completer cases treated with SSRIs comprised haplotypes and polymorphisms related to serotonin synthesis, serotonin transport, glutamate receptors, and GABA synthesis. The model was evaluated prospectively for prediction of outcome in a validation sample of 176 new SSRI-treated completer cases. The model gave a prediction in 60% of these cases. Predictive values were 85% for predicted responders and 86% for predicted nonresponders, compared to prior probabilities of 66% for observed response and 34% for observed nonresponse in those cases (both P<0.001). Convergent cross-validation was obtained through failure of the model to predict outcomes in a third independent sample of 189 completer cases who received non-SSRI antidepressants. We suggest proof of principle for genetic guidance to use or avoid SSRIs in a majority of Korean depressed patients.

The influence of 5-HTTLPR genotype on the association between the plasma concentration and therapeutic effect of paroxetine in patients with major depressive disorder

INTRODUCTION

The efficacy of treatment with selective serotonin reuptake inhibitors in patients with major depressive disorder (MDD) can differ depending on the patient's serotonin transporter-linked polymorphic region (5-HTTLPR) genotype, and the effects of varying plasma concentrations of drugs can also vary. We investigated the association between the paroxetine plasma concentration and clinical response in patients with different 5-HTTLPR genotypes.

METHODS

Fifty-one patients were enrolled in this study. The Montgomery-Asberg Depression Rating Scale (MADRS) was used to evaluate patients at 0, 1, 2, 4, and 6 weeks. The patients' paroxetine plasma concentrations at week 6 were measured using high-performance liquid chromatography. Additionally, their 5-HTTLPR polymorphisms (alleles S and L) were analyzed using a polymerase chain reaction with specific primers. We divided the participants into two groups based on their L haplotype: the SS group and the SL and LL group. We performed single and multiple regression analyses to investigate the associations between MADRS improvement and paroxetine plasma concentrations or other covariates for each group.

RESULTS

There were no significant differences between the two groups with regard to demographic or clinical data. In the SS group, the paroxetine plasma concentration was significantly negatively correlated with improvement in MADRS at week 6. In the SL and LL group, the paroxetine plasma concentration was significantly positively correlated with improvement in MADRS at week 6 according to the results of the single regression analysis; however, it was not significantly correlated with improvement in MADRS at week 6 according to the results of the multiple regression analysis.

CONCLUSION

Among patients with MDD who do not respond to paroxetine, a lower plasma concentration or a lower oral dose of paroxetine might be more effective in those with the SS genotype, and a higher plasma concentration might be more effective in those with the SL or LL genotype.

Influence of RGS2 on sertraline treatment for social anxiety disorder

Only a minority of patients with social anxiety disorder (SAD) has a robust therapeutic response to evidence-based serotonin reuptake inhibitor (SSRI) treatment. To help improve the personalized medicine approach to psychiatric care, we evaluated several candidate genetic predictors of SSRI response in SAD. At the start of a randomized controlled trial (NCT00282828), 346 patients with SAD at three sites received protocol-driven, open-label treatment with sertraline, up to 200. mg/d over 10 weeks. Efficacy was determined using a continuous measure of outcome (Liebowitz Social Anxiety Scale (LSAS)) and dichotomous indicators of response (LSAS ≤ 50) and remission (LSAS ≤ 30). Predictors of efficacy were examined in multivariate regression models that included eight polymorphic variants in four candidate genes (four in RGS2, two in HTR2A, one in SLC6A2, and one in SLC6A4). Adjusting for genetic ancestral cluster and non-genetic predictors of response, all four single-nucleotide polymorphisms (SNPs) in RGS2 predicted change in LSAS over time, at study-wise significance (p=0.00833), with the minor allele associated with less improvement over time. After adjusting for genetic ancestral cluster and non-genetic predictors of remission, two of the four RGS2 SNPs predicted likelihood of remission at or just below study-wise significance (p=0.025): rs4606 (AOR=0.49 (95% CI=0.27-0.90), p=0.022) and rs1819741 (AOR=0.50 (95% CI=0.28-0.92), p=0.027). Variation in RGS2, a gene previously shown to be associated with social anxiety phenotypes and serotonergic neurotransmission, may be a biomarker of the likelihood of substantially benefiting from sertraline among patients with SAD.

Race, genetic ancestry and response to antidepressant treatment for major depression

The Sequenced Treatment Alternatives to Relieve Depression (STAR*D) Study revealed poorer antidepressant treatment response among black compared with white participants. This racial disparity persisted even after socioeconomic and baseline clinical factors were taken into account. Some studies have suggested genetic contributions to this disparity, but none have attempted to disentangle race and genetic ancestry. Here we used genome-wide single-nucleotide polymorphism (SNP) data to examine independent contributions of race and genetic ancestry to citalopram response. Secondary data analyses included 1877 STAR*D participants who completed an average of 10 weeks of citalopram treatment and provided DNA samples. Participants reported their race as White (n=1464), black (n=299) or other/mixed (n=114). Genetic ancestry was estimated by multidimensional scaling (MDS) analyses of about 500 000 SNPs. Ancestry proportions were estimated by STRUCTURE. Structural equation modeling was used to examine the direct and indirect effects of observed and latent predictors of response, defined as change in the Quick Inventory of Depressive Symptomatology (QIDS) score from baseline to exit. Socioeconomic and baseline clinical factors, race, and anxiety significantly predicted response, as previously reported. However, direct effects of race disappeared in all models that included genetic ancestry. Genetic African ancestry predicted lower treatment response in all models. Although socioeconomic and baseline clinical factors drive racial differences in antidepressant response, genetic ancestry, rather than self-reported race, explains a significant fraction of the residual differences. Larger samples would be needed to identify the specific genetic mechanisms that may be involved, but these findings underscore the importance of including more African-American patients in drug trials.

A genome-wide association study of a sustained pattern of antidepressant response

Genome-wide association studies (GWAS) have failed to replicate common genetic variants associated with antidepressant response, as defined using a single endpoint. Genetic influences may be discernible by examining individual variation between sustained versus unsustained patterns of response, which may distinguish medication effects from non-specific, or placebo responses to active medication. We conducted a GWAS among 1116 subjects with Major Depressive Disorder from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial who were characterized using Growth Mixture Modeling as showing a sustained versus unsustained pattern of clinical response over 12 weeks of treatment with citalopram. Replication analyses examined 585 subjects from the Genome-based Therapeutic Drugs for Depression (GENDEP) trial. The strongest association with sustained as opposed to unsustained response in STAR*D involved a single nucleotide polymorphism (SNP; rs10492002) within the acyl-CoA synthetase short-chain family member 3 gene (ACSS3, p-value=4.5×10(-6), odds ratio=0.61). No SNPs met our threshold for genome-wide significance. SNP data were available in GENDEP for 18 of the top 25 SNPs in STAR*D. The most replicable association was with SNP rs7816924 (p=0.008, OR=1.58); no SNP met the replication p-value threshold of 0.003. Joint analysis of these 18 SNPs resulted in the strongest signal coming from rs7816924 (p=2.11×10(-7)), which resides in chondroitin sulfate N-acetylgalactosaminyltransferase 1 gene (CSGALNACT1). An exploratory genetic pathway analysis revealed evidence for an involvement of the KEGG pathway of long-term potentiation (FDR=.02). Results suggest novel genetic associations to sustained response.

Pharmacogenetics of antidepressants, mood stabilizers, and antipsychotics in diverse human populations

An increasing focus on personalized medicine is driving a renewed effort to understand the impact of ethnic and genetic background on treatment outcomes. Since responses to psychopharmacological treatments continue to be sub-optimal, there is a pressing need to identify markers of tolerability and efficacy. Pharmacogenomic studies aim to find such markers within the human genome, and have made some progress in recent years. Progress has been slower in populations with diverse racial and ethnic backgrounds. Here we review 10 genome-wide association studies (GWAS) that assessed outcomes after antidepressant, antipsychotic, or mood stabilizer treatment. These studies used samples collected by the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE), Sequenced Treatment Alternatives to Relieve Depression (STAR*D), and Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD) studies. We highlight findings from African American and European American participants since they are the largest groups studied, but we also address issues related to Asian and Hispanic groups. None of the GWAS we reviewed identified individual genetic markers at genome-wide significance, probably due to limited sample sizes. However, all the studies found poorer outcomes among African American participants. Some of this disparity seems to be explained by psychosocial and economic disadvantages, but at least 2 studies found that widespread genetic differences between participants of European and African ancestry also play an important role. Non-European groups are underrepresented in these studies, but the differences that are evident so far suggest that poorer outcomes among African Americans are not inevitable and may be particularly suited to pharmacogenomic strategies. The vision of more personalized psychopharmacology may critically depend on larger studies in more diverse human populations.

Revisiting serotonin reuptake inhibitors and the therapeutic potential of "uptake-2" in psychiatric disorders

Depression is among the most common psychiatric disorders, and in many patients a disorder for which available medications provide suboptimal or no symptom relief. The most commonly prescribed class of antidepressants, the selective serotonin reuptake inhibitors (SSRIs), are thought to act by increasing extracellular serotonin in brain by blocking its uptake via the high-affinity serotonin transporter (SERT). However, the relative lack of therapeutic efficacy of SSRIs has brought into question the utility of increasing extracellular serotonin for the treatment of depression. In this Viewpoint, we discuss why increasing extracellular serotonin should not be written off as a therapeutic strategy. We describe how "uptake-2" transporters may explain the relative lack of therapeutic efficacy of SSRIs, as well as why "uptake-2" transporters might be useful therapeutic targets.

The prospect of FKBP51 as a drug target

The FK506 binding protein 51 (FKBP51) is best known as an Hsp90-associated co-chaperone that regulates the responsiveness of steroid hormone receptors. In human genetic association studies, FKBP51 has repeatedly been associated with emotion processing and numerous stress-related affective disorders. It has also been implicated in contributing to the glucocorticoid hyposensitivity observed in New World primates. More recently, several research groups have consistently shown a protective effect of FKBP51 knockout or knockdown on stress endocrinology and stress-coping behavior in animal models of depression and anxiety. The principal druggability of FKBP51 is exemplified by the prototypic FKBP ligands FK506 and rapamycin. Moreover, FKBP51 is highly suited for X-ray co-crystallography, which should facilitate the rational drug design of improved FKBP51 ligands. In summary, FKBP51 has emerged as a promising new drug target for stress-related disorders that should be amenable to drug discovery.

Effect of obstructive sleep apnea on response to cognitive behavior therapy for depression after an acute myocardial infarction

OBJECTIVE

To determine whether obstructive sleep apnea (OSA) interferes with cognitive behavior therapy (CBT) for depression in patients with coronary heart disease.

METHODS

Patients who were depressed within 28 days after an acute myocardial infarction (MI) were enrolled in the Enhancing Recovery in Coronary Heart Disease (ENRICHD) trial; 289 (12%) of the 2481 participants in ENRICHD met the criteria for inclusion in this ancillary study.

RESULTS

A validated ambulatory ECG algorithm was used to detect OSA. Of the 289 participants, 64 (22%) met the criteria for OSA. CBT was efficacious relative to usual care (UC) for depression (p=.004). OSA had no effect on 6-month Beck Depression Inventory (BDI) scores (p=.11), and there was no interaction between OSA and treatment (p=.42). However, the adjusted mean (s.e.) 6-month BDI scores among patients without OSA were 12.2 (0.8) vs. 9.0 (0.8) in the UC and CBT groups (Cohen's d=.40); among those with OSA, they were 9.5 (1.4) and 8.1 (1.5) in the UC and CBT groups (d=.17). There were no significant OSA×Treatment interactions in the major depression (n=131) or minor depression (n=158) subgroups, but in those with major depression, there was a larger treatment effect in those without (d=.44) than with (d=.09) OSA. In those with minor depression, the treatment effects were d=.37 and d=.25 for the non-OSA and OSA subgroups.

CONCLUSION

CBT is efficacious for depression after an acute myocardial infarction in patients without obstructive sleep apnea, but it may be less efficacious for post-MI patients with OSA.

Recovery from depression

Full recovery from depression, as contrasted with symptom improvement, is a relatively new concept and therapeutic goal. It is an important goal, because the failure to achieve this goal leaves many patients with less productive and fulfilling lives, it leaves some children with lasting deficits, and it deprives families and societies of loved ones’ and employees’ care and investment. As a new therapeutic concept, recovery from depression is not as easy to define as it might seem; many or most patients were not euthymic before an episode of depression or have had some level of depression throughout their lives. There is no measurable definition of euthymia. In addition to definitional difficulties, we need to study and address other barriers to the achievement of recovery from depression. All the barriers to the diagnosis and treatment of depression are barriers against recovery: negative social and professional attitudes, comorbidity, lack of access to demonstrably efficacious professional and social services, and inability to match patients with the antidepressants most likely to help them. Efforts to address many of these knowledge and attitude gaps are already underway. Long-term studies are needed, both observational and experimental. Most published studies encompass only weeks or at best months of follow-up, but recovery must be sustained to be meaningful. As noted previously, there has been little or no attention to the developmental impact of depression. The restoration of premorbid function is not sufficient when depression has hindered a patient’s ability to form satisfying relationships and choose and perform satisfying work. We need to learn how to remediate patients whose history of depression has stifled their talents and aspirations. Studying these issues will not be easy, but millions of individuals with depression, and their physicians, will profit by it; it will be well worth the effort.

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.

GRIK4/KA1 protein expression in human brain and correlation with bipolar disorder risk variant status

The kainate class of ionotropic glutamate receptors is involved in the regulation of neuronal transmission and synaptic plasticity. Previously we reported that a deletion variant within the gene GRIK4, which encodes the KA1 kainate receptor subunit, was associated with a reduced risk of bipolar disorder and increased GRIK4 mRNA abundance. Using a high resolution immunohistochemistry technique, we characterized KA1 protein localization in human brain and performed a genotype-protein expression correlation study. KA1 was expressed in specific populations of neuronal cells in the cerebellum and all layers of the frontal and parahippocampal cortices. In the hippocampus, strong KA1 expression was observed in the stratum pyramidale and stratum lucidum of CA3 and CA2, in cell processes in CA1, in the neuropil of the CA4 region, in polymorphic cells including mossy fiber neurons in the hilus, and dentate gyrus (DG) granule cells. Mean counts of KA1 positive DG granule cells, hippocampal CA3 pyramidal cells, and layer 1 of the frontal cortex were significantly increased in subjects with the deletion allele (P = 0.0005, 0.018, and 0.0058, respectively) compared to subjects homozygous for the insertion. Neuronal expression levels in all regions quantified were higher in the deletion group. These results support our hypothesis that the deletion allele affords protection against bipolar disorder through increased KA1 protein abundance in neuronal cells. Biological mechanisms which may contribute to this protective effect include KA1 involvement in adult hippocampal neurogenesis, HPA axis activation, or plasticity processes affecting neuronal circuitry.

FKBP51 and FKBP52 in signaling and disease

FKBP51 and FKBP52 are diverse regulators of steroid hormone receptor signaling, including receptor maturation, hormone binding and nuclear translocation. Although structurally similar, they are functionally divergent, which is largely attributed to differences in the FK1 domain and the proline-rich loop. FKBP51 and FKBP52 have emerged as likely contributors to a variety of hormone-dependent diseases, including stress-related diseases, immune function, reproductive functions and a variety of cancers. In addition, recent studies have implicated FKBP51 and FKBP52 in Alzheimer's disease and other protein aggregation disorders. This review summarizes our current understanding of FKBP51 and FKBP52 interactions within the receptor-chaperone complex, their contributions to health and disease, and their potential as therapeutic targets for the treatment of these diseases.

Trajectories of depression severity in clinical trials of duloxetine: insights into antidepressant and placebo responses

CONTEXT

The high percentage of failed clinical trials in depression may be due to high placebo response rates and the failure of standard statistical approaches to capture heterogeneity in treatment response.

OBJECTIVE

To assess whether growth mixture modeling can provide insights into antidepressant and placebo responses in clinical trials of patients with major depression.

DESIGN

We reanalyzed clinical trials of duloxetine to identify distinct trajectories of Hamilton Scale for Depression (HAM-D) scores during treatment. We analyzed the trajectories in the entire sample and then separately in all active arms and in all placebo arms. Effects of duloxetine hydrochloride, selective serotonin reuptake inhibitor (SSRI), and covariates on the probability of following a particular trajectory were assessed. Outcomes in different trajectories were compared using mixed-effects models.

SETTING

Seven randomized double-blind clinical trials of duloxetine vs placebo and comparator SSRI. Patients A total of 2515 patients with major depression.

INTERVENTIONS

Duloxetine and comparator SSRI. Main Outcome Measure Total score on the HAM-D.

RESULTS

In the entire sample and in the antidepressant-treated subsample, we identified trajectories of responders (76.3% of the sample) and nonresponders (23.7% of the sample). However, placebo-treated patients were characterized by a single response trajectory. Duloxetine and SSRI did not differ in efficacy, and compared with placebo they significantly decreased the odds of following the nonresponder trajectory. Antidepressant responders had significantly better HAM-D scores over time than placebo-treated patients, but antidepressant nonresponders had significantly worse HAM-D scores over time than the placebo-treated patients.

CONCLUSIONS

Most patients treated with serotonergic antidepressants showed a clinical trajectory over time that is superior to that of placebo-treated patients. However, some patients receiving these medications did more poorly than patients receiving placebo. These data highlight the importance of ongoing monitoring of medication risks and benefits during serotonergic antidepressant treatment. They should further stimulate the search for biomarkers or other predictors of responder status in guiding antidepressant treatment.

Functional biomarkers of depression: diagnosis, treatment, and pathophysiology

Major depressive disorder (MDD) is a heterogeneous illness for which there are currently no effective methods to objectively assess severity, endophenotypes, or response to treatment. Increasing evidence suggests that circulating levels of peripheral/serum growth factors and cytokines are altered in patients with MDD, and that antidepressant treatments reverse or normalize these effects. Furthermore, there is a large body of literature demonstrating that MDD is associated with changes in endocrine and metabolic factors. Here we provide a brief overview of the evidence that peripheral growth factors, pro-inflammatory cytokines, endocrine factors, and metabolic markers contribute to the pathophysiology of MDD and antidepressant response. Recent preclinical studies demonstrating that peripheral growth factors and cytokines influence brain function and behavior are also discussed along with their implications for diagnosing and treating patients with MDD. Together, these studies highlight the need to develop a biomarker panel for depression that aims to profile diverse peripheral factors that together provide a biological signature of MDD subtypes as well as treatment response.

Biomarkers in development of psychotropic drugs

Biomarkers have been receiving increasing attention, especially in the field of psychiatry. In contrast to the availability of potent therapeutic tools including pharmacotherapy, psychotherapy, and biological therapies, unmet needs remain in terms of onset of action, stability of response, and further improvement of the clinical course. Biomarkers are objectively measured characteristics which serve as indicators of the causes of illnesses, their clinical course, and modification by treatment. There exist a variety of markers: laboratory markers which comprise the determination of genetic and epigenetic markers, neurotransmitters, hormones, cytokines, neuropeptides, enzymes, and others as single measures; electrophysiological markers which usually comprise electroencephalography (EEG) measures, and in particular sleep EEG and evoked potentials, magnetic encephalography, electrocardiogram, facial electromyography, skin conductance, and others; brain imaging techniques such as cranial computed tomography, magnetic resonance imaging, functional MRl, magnetic resonance spectroscopy, positron emission tomography, and single photon emission computed tomography; and behavioral approaches such as cue exposure and challenge tests which can be used to induce especially emotional processes in anxiety and depression. Examples for each of these domains are provided in this review. With a view to developing more individually tailored therapeutic strategies, the characterization of patients and the courses of different types of treatment will become even more important in the future.

Genome-wide association studies of antidepressant outcome: a brief review

Genome-wide association studies (GWAS) of antidepressant treatment outcome have been at the forefront of psychiatric pharmacogenetics. Such studies may ultimately help match medications with patients, maximizing efficacy while minimizing adverse effects. The hypothesis-free approach of the GWAS has the advantage of interrogating genes that otherwise would have not been considered as candidates due to our limited understanding of their function, and may also uncover important regulatory variation within the large regions of the genome that do not contain protein-coding genes. Three independent samples have so far been studied using a genome-wide approach: The Sequenced Treatment Alternatives to Relieve Depression sample (STAR*D) (n=1953), the Munich Antidepressant Response Signature (MARS) sample (n=339) and the Genome-based Therapeutic Drugs for Depression (GENDEP) sample (n=706). None of the studies reported results that achieved genome-wide significance, suggesting that larger samples and better outcome measures will be needed. This review discusses the published GWAS studies, their strengths, limitations, and possible future directions.

Strategies to achieve clinical effectiveness: refining existing therapies and pursuing emerging targets

BACKGROUND

Clinical effectiveness reflects a balance between efficacy and tolerability as well as patient satisfaction and overall improvement in quality of life and function. This is of particular importance when considering the long term use of antidepressant therapies for relapse prevention.

METHODS

The purpose of this review is to explore methods to enhance the modest efficacy and effectiveness outcomes reported with current antidepressant strategies. Two strategies are addressed: a) Doing better with existing treatments and b) pursuing novel targets beyond the monoamine system for new antidepressant drug development.

RESULTS

In the first instance, it is important to consider the balance between antidepressant efficacy and tolerability for individual patients and also be aware of evidence supporting superiority of one agent over others. Both sequential and concurrent combination therapies with existing antidepressants are also reviewed. The second approach involves a review of emerging novel pharmacological treatments based on biomarker research. Unique targets where antidepressant treatments appear effective include the melatonergic, glutamatergic, neurotrophic, cytokine, and neuropeptide systems.

CONCLUSIONS

While agomelatine represents an example of a clinically available antidepressant that targets melatonin receptors, drugs that act on other candidate systems are still in the development phase.

Pharmacogenetics of antidepressant response

Personalized medicine - the adaptation of therapies based on an individual's genetic and molecular profile - is one of the most promising aspects of modern medicine. The identification of the relation between genotype and drug response, including both the therapeutic effect and side effect profile, is expected to deeply affect medical practice. In this paper, we review the current knowledge about the genes related to antidepressant treatment response and provide methodologic proposals for future studies. We have mainly focused on genes associated with pharmacodynamics, for which a list of promising genes has been identified despite some inconsistency across studies. We have also synthesized the main results for pharmacokinetic genes, although so far they seem less relevant than those for pharmaco dynamic genes. We discuss possible reasons for these inconsistent findings and propose new study designs.

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.

Pharmacogenomics of suicidal events

Pharmacogenomic studies of antidepressant treatment-emergent suicidal events in depressed patients report associations with polymorphisms in genes involved in transcription (CREB1), neuroprotection (BDNF and NTRK2), glutamatergic and noradrenergic neurotransmission (GRIA3, GRIK2 and ADRA2A), the stress and inflammatory responses (FKBP5 and IL28RA), and the synthesis of glycoproteins (PAPLN). Nearly all of the reported events in these studies were modest one-time increases in suicidal ideation. In 3231 unique subjects across six studies, 424 (13.1%) patients showed increases in suicidal ideation, eight (0.25%) attempted suicide and four (0.12%) completed suicide. Systems related to most of these genes have also been implicated in studies of suicidal behavior irrespective of treatment. Future pharmacogenomic studies should target events that are clinically significant, related clinical phenotypes of response and medication side effects, and biological pathways that are involved in these outcomes in order to improve treatment approaches.

Haplotype structure and divergence at human and chimpanzee serotonin transporter and receptor genes: implications for behavioral disorder association analyses

Genetic variation in the human serotonin system has long-been studied because of its functional consequences and links to various behavior-related disorders and it being routinely targeted in research and development for drug therapy. However, aside from clinical studies, little is known about this genetic diversity and how it differs within and between human populations with respect to haplotype structure, which can greatly impact phenotype association studies. In addition, no evolutionary approach among humans and other primates has examined how long- and short-term selective pressures explain existing serotonin variation. Here, we examine DNA sequence variation in natural population samples of 192 human and 40 chimpanzee chromosome sequences for the most commonly implicated approximately 38-kb serotonin transporter (SLC6A4) and approximately 63-kb serotonin 2A receptor (HTR2A) genes. Our comparative population genetic analyses find significant linkage disequilibrium associated with functionally relevant variants in humans, as well as geographic variation for these haplotypes, at both loci. In addition, although amino acid divergence is consistent with purifying selection, promoter and untranslated regions exhibit significantly high divergence in both species lineages. These evolutionary analyses imply that the serotonin system may have accumulated significant regulatory variation over both recent and ancient periods of time in both humans and chimpanzees. We discuss the implications of this variation for disease association studies and for the evolution of behavior-related phenotypes during the divergence of humans and our closest primate relatives.

Biomarkers to predict antidepressant response

During the past several years, we have achieved a deeper understanding of the etiology/pathophysiology of major depressive disorder (MDD). However, this improved understanding has not translated to improved treatment outcome. Treatment often results in symptomatic improvement, but not full recovery. Clinical approaches are largely trial-and-error, and when the first treatment does not result in recovery for the patient, there is little proven scientific basis for choosing the next. One approach to enhancing treatment outcomes in MDD has been the use of standardized sequential treatment algorithms and measurement-based care. Such treatment algorithms stand in contrast to the personalized medicine approach, in which biomarkers would guide decision making. Incorporation of biomarker measurements into treatment algorithms could speed recovery from MDD by shortening or eliminating lengthy and ineffective trials. Recent research results suggest several classes of physiologic biomarkers may be useful for predicting response. These include brain structural or functional findings, as well as genomic, proteomic, and metabolomic measures. Recent data indicate that such measures, at baseline or early in the course of treatment, may constitute useful predictors of treatment outcome. Once such biomarkers are validated, they could form the basis of new paradigms for antidepressant treatment selection.