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Background: Cohort and cost-effectiveness studies suggest that measuring variation in genes that influence metabolism of common drugs could improve antidepressant treatment outcomes. Prior randomized trials have yielded inconsistent results.Method: Multicenter randomized double-blind (subject and rater), controlled trial of pharmacogenomic testing among outpatients with nonpsychotic major depressive disorder. Study participants (n = 304) were randomized 1:1 to assay-guided treatment (AGT; N = 151) or treatment-as-usual (TAU; N = 153). Participants and raters were blinded to study arm; unblinded clinicians received results of a pharmacogenomic test and adjusted treatment in light of the test report. Primary outcome was change over 8 weeks in Hamilton Depression Rating Scale (SIGH-D-17).Results: For the primary comparison of interest, change in SIGH-D-17, no significant difference was detected between AGT and TAU at Week 8 (p = .53). Rates of study completion also did not differ between the arms (AGT 92.7%, TAU 92.2% (χ2  = 0.03, df = 1, p = .86). Exploratory analyses suggested significantly fewer individuals experienced worsening of depressive symptoms following AGT, and that treatment concordant with assay results was associated with greater likelihood of remission.Conclusion: Pharmacogenomic testing using a panel of pharmacokinetic and pharmacodynamic variants was not associated with significant improvement in the primary efficacy outcome when providers were unconstrained by the assay results. Further investigation is needed to understand the discordance with cost-effectiveness results and among randomized trials. [ABSTRACT FROM AUTHOR]

Background: Low rates of medication adherence remain a major challenge across psychiatry. In part, this likely reflects patient concerns about safety and adverse effects, accurate or otherwise. We therefore sought to characterize online information about common psychiatric medications in terms of positive and negative sentiment.Methods: We applied a natural language processing tool to score the sentiment expressed in web search results for 51 psychotropic medications across 3 drug classes (antidepressants, antipsychotics, and mood stabilizers), as a means of seeing if articles referencing these medications were generally positive or generally negative in tone. We compared between medications of the same class, and across medication classes.Results: Across 12,733 web search results, significant within-class differences in positive (antidepressants: F(24,2682) = 2.97, p < 0.001; antipsychotics: F(16,4029) = 3.25, p < 0.001; mood stabilizers: F(8,2371) = 6.88, p < 0.001) and negative sentiment (antidepressants: F(24,6282) = 11.17, p < 0.001; antipsychotics: F(16, 4029)  = 12.13, p < 0.001; mood stabilizers: F(8, 2371) = 13.28, p < 0.001) were identified. Among these were significantly greater negative sentiment for the antidepressants sertraline, duloxetine, venlafaxine, and paroxetine, and for the antipsychotics, quetiapine and risperidone. Conversely, lithium preparations and valproate exhibited less negative sentiment than other mood stabilizing medications.Limitations: While these results provide a novel means of comparing medications, the present analyses cannot be linked to individual patient consumption of this information, or to its influence on their future clinical interactions.Conclusions: Overall, a subset of psychotropic medications were associated with significantly more negative sentiment. Characterizing these differences may allow clinicians to anticipate patient willingness to initiate or continue medications. [ABSTRACT FROM AUTHOR]

This Viewpoint revisits the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study design 20 years after its initiation and assesses it in light of current strategies to treat major depression. [ABSTRACT FROM AUTHOR]

Clinical guidelines recommend adding a second drug for patients with major depressive disorder who have a partial response and switching antidepressants for those who show no response or intolerance. This guidelines-based strategy was compared with other strategies for the management of unresponsive depression. A total of 1436 individuals experiencing treatment failure with citalopram and still requiring antidepressant therapy were identified in the STAR∗D (Sequenced Treatment Alternatives to Relieve Depression) trial. A (hypothetical) target trial was then designed and emulated. The following strategies for decision making were compared: sequential monotherapy, sequential dual non–selective serotonin reuptake inhibitor therapy (SD), and a guidelines-based strategy. The primary outcome was symptomatic remission defined as a Hamilton Depression Rating Scale score ≤7 or 2 consecutive scores ≤5 on the 16-item Quick Inventory of Depressive Symptomatology–Clinician Rated. Secondary outcomes were serious events (hospitalizations, suicide, and mortality). Inverse probability weighting was used to control for possible confounding. A total of 971 patients were eligible for our emulation. Patients initiating SD had the lowest levels of depression at baseline. The estimated 9-month probability of remission was 43.5% for the sequential monotherapy group, 47.6% for the SD group, and 53.2% for the guidelines-based strategy group. Compared with the sequential monotherapy group, the difference in 9-month probability of remission was −4.2% (95% CI, −15.6 to 4.6) for the SD group and −9.7% (−19.3 to 1.9) for the guidelines-based strategy group. The 9-month relative risks of remission were 1.09 (0.90 to 1.38) and 1.22 (0.96 to 1.46), respectively. Results were consistent across sensitivity analyses. The 9-month relative risks of serious events were 0.77 (0.38 to 1.40) and 0.62 (0.33 to 1.00), respectively. Using the guidelines-based strategy was associated with an increased probability of remission and a lower risk of serious adverse events. The potential implications are substantial given the large number of patients experiencing treatment failure to antidepressants. [ABSTRACT FROM AUTHOR]

Background: Early identification of depressed individuals at high risk for treatment resistance could be helpful in selecting optimal setting and intensity of care. At present, validated tools to facilitate this risk stratification are rarely used in psychiatric practice. Methods: Data were drawn from the first two treatment levels of a multicenter antidepressant effectiveness study in major depressive disorder, the STAR⁎D (Sequenced Treatment Alternatives to Relieve Depression) cohort. This cohort was divided into training, testing, and validation subsets. Only clinical or sociodemographic variables available by or readily amenable to self-report were considered. Multivariate models were developed to discriminate individuals reaching remission with a first or second pharmacological treatment trial from those not reaching remission despite two trials. Results: A logistic regression model achieved an area under the receiver operating characteristic curve exceeding .71 in training, testing, and validation cohorts and maintained good calibration across cohorts. Performance of three alternative models with machine learning approaches—a naïve Bayes classifier and a support vector machine, and a random forest model—was less consistent. Similar performance was observed between more and less severe depression, men and women, and primary versus specialty care sites. A web-based calculator was developed that implements this tool and provides graphical estimates of risk. Conclusion: Risk for treatment resistance among outpatients with major depressive disorder can be estimated with a simple model incorporating baseline sociodemographic and clinical features. Future studies should examine the performance of this model in other clinical populations and its utility in treatment selection or clinical trial design. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The article discusses the study on the likelihood of experiencing recurrence or worsening of symptoms including thoughts of suicide or suicidal behavior during a second treatment trial with a different antidepressant for patients undergoing initial antidepressant treatment. The study found similar overall magnitude of risk among next-step pharmacologic augmentation against switching, suggesting the need for closer follow-up during the next-step treatment regardless of modality selected.

Objective: It has been suggested that there is a mechanism by which nonsteroidal anti-inflammatory drugs (NSAIDs) may interfere with antidepressant response, and poorer outcomes among NSAIDtreated patients were reported in the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study. To attempt to confirm this association in an independent population-based treatment cohort and explore potential confounding variables, the authors examined use of NSAIDs and related medications among 1,528 outpatients in a New England health care system. Method: Treatment outcomes were classified using a validated machine learning tool applied to electronic medical records. Logistic regression was used to examine the association between medication exposure and treatment outcomes, adjusted for potential confounding variables. To further elucidate confounding and treatment specificity of the observed effects, data from the STAR*D study were reanalyzed. Results: NSAID exposure was associated with a greater likelihood of depression classified as treatment resistant compared with depression classified as responsive to selective serotonin reuptake inhibitors (odds ratio=1.55, 95% Cl=1.21-2.00). This association was apparent in the NSAIDs only group but not in those using other agents with NSAID-like mechanisms (cyclooxygenase-2 inhibitors and saucylates). Inclusion of age, sex, ethnicity, and measures of comorbidity and health care utilization in regression models indicated confounding; association with outcome was no longer significant in fully adjusted models. Reanalysis of STAR*D results likewise identified an association in NSAIDs but not NSAID-like drugs, with more modest effects persisting after adjustment for potential confounding variables. Conclusions: These results support an association between NSAID use and poorer antidepressant outcomes in major depressive disorder but indicate that some of the observed effect may be a result of confounding. [ABSTRACT FROM AUTHOR]

The article discusses a research study which explored the association between bipolar spectrum features and antidepressant treatment outcome in U.S. outpatients with major depressive disorder (MDD). It reveals that irritability and psychotic-like symptoms at entry and some neurovegetative symptoms of depression were strongly linked with poorer outcomes. The data also failed to support the hypothesis that unrecognized bipolar spectrum illness is a key contributor to antidepressant treatment resistance.

Some individuals with bipolar disorder transition directly from major depressive episodes to manic, hypomanic, or mixed states during treatment, even in the absence of antidepressant treatment. Prevalence and risk factors associated with such transitions in clinical populations are not well established, and were examined in the Systematic Treatment Enhancement Program for Bipolar Disorder study, a longitudinal cohort study. Survival analysis was used to examine time to transition to mania, hypomania, or mixed state among 2166 bipolar I and II individuals in a major depressive episode. Cox regression was used to examine baseline clinical and sociodemographic features associated with hazard for such a direct transition. These features were also examined for interactive effects with antidepressant treatment. In total, 461/2166 subjects in a major depressive episode (21.3%) transitioned to a manic/hypomanic or mixed state before remission, including 289/1475 (19.6%) of those treated with antidepressants during the episode. Among the clinical features associated with greatest transition hazard were greater number of past depressive episodes, recent or lifetime rapid cycling, alcohol use disorder, previous suicide attempt, and history of switch while treated with antidepressants. Greater manic symptom severity was also associated with risk for manic transition among both antidepressant-treated and antidepressant-untreated individuals. Three features, history of suicide attempt, younger onset age, and bipolar subtype, exhibited differential effects between individuals treated with antidepressants and those who were not. These results indicate that certain clinical features may be associated with greater risk of transition from depression to manic or mixed states, but the majority of them are not specific to antidepressant-treated patients. [ABSTRACT FROM AUTHOR]

Background: Recent studies have identified associations of polymorphisms in several target genes with antidepressant treatment response of serotonin reuptake inhibitors and a tricyclic antidepressant. We sought to replicate these associations in a study of a serotonin-norepinephrine reuptake inhibitor. Methods: In 250 outpatients with nonpsychotic major depressive disorder, response to treatment with once-daily duloxetine (60 mg/day) over 6 weeks was examined for associations with polymorphisms in eight candidate genes previously associated with antidepressant response using mixed-effect model repeated-measures analysis. Treatment response was quantified on the basis of changes from baseline using 17-item Hamilton Depression Rating Scale total scores. Results: Polymorphisms in PDE1A, PDE1C, PDE6A, PDE11A, ABCB1, GRIK4, SLC6A4, and OPRM1 genes showed no statistically significant associations (uncorrected, two-tailed p > .05) with duloxetine treatment response. Conclusions: Previously, described associations between polymorphisms in candidate genes and antidepressant treatment response were not replicated in this study. This result may suggest that previous associations are specific to serotonin reuptake inhibitors. [Copyright &y& Elsevier]

The potential of personalized medicine to transform the treatment of mood disorders has been widely touted in psychiatry, but has not been quantified. We estimated the costs and benefits of a putative pharmacogenetic test for antidepressant response in the treatment of major depressive disorder (MDD) from the societal perspective. Specifically, we performed cost-effectiveness analyses using state-transition probability models incorporating probabilities from the multicenter STAR*D effectiveness study of MDD. Costs and quality-adjusted life years (QALYs) were compared for sequential antidepressant trials, with or without guidance from a pharmacogenetic test for differential response to selective serotonin reuptake inhibitors (SSRIs). Likely SSRI responders received an SSRI, whereas likely nonresponders received the norepinephrine/dopamine reuptake inhibitor bupropion. For a 40-year old with MDD, applying the pharmacogenetic test and using the non-SSRI bupropion for those at higher risk for nonresponse cost $93 520 per additional QALY compared with treating all patients with an SSRI first and switching sequentially in the case of nonremission. Cost per QALY dropped below $50 000 for tests with remission rate ratios as low as 1.5, corresponding to odds ratios ∼1.8–2.0. Tests for differential antidepressant response could thus become cost effective under certain circumstances. These circumstances, particularly availability of alternative treatment strategies and test effect sizes, can be estimated and should be considered before these tests are broadly applied in clinical settings.Neuropsychopharmacology (2009) 34, 2227–2236; doi:10.1038/npp.2009.50; published online 3 June 2009 [ABSTRACT FROM AUTHOR]

Background: The study objective was to evaluate variations in genes implicated in antidepressant mechanism of action for association with response to duloxetine treatment in major depressive disorder (MDD). Methods: We assessed response over 6 weeks in 250 duloxetine-treated Caucasian patients in a randomized, double-blind study of patients with MDD. Single nucleotide polymorphisms (SNPs) were genotyped in 19 candidate genes selected based on evidence for involvement in antidepressant mechanism of action. Primary analysis examined baseline to end point reduction in the 17-item Hamilton Depression Rating Scale (HAMD17) total score, using a set-based test for association for each gene. Follow-up analyses examined individual SNPs within any significant gene for association with reduction in HAMD17 and 30-item Inventory of Depressive Symptomatology-Clinician Rated (IDS-C-30). Results: After correction for multiple comparisons, only COMT was associated with change in HAMD17 (experimentwide p = .018). Peak association was detected with rs165599 (p = .006), which accounted for approximately 3% of variance in HAMD17 change and >4% of variance in IDS-C-30 change (p = .001). The least-squared mean change (SE) in HAMD17 score by rs165599 genotype was −10.8 (1.2), −8.7 (.6), and −6.5 (.7) for patients with GG, GA, and AA genotypes, respectively. For SNPs in serotonin 2A receptor (HTR2A) previously associated with citalopram response, including rs7997012, no significant evidence of association with duloxetine response was identified. Conclusions: Single nucleotide polymorphisms in COMT were associated with symptom change in duloxetine-treated patients with MDD. If replicated, the magnitude of the COMT genotype effect is of clinical relevance. [Copyright &y& Elsevier]

The article discusses a study on the prevalence of complex multi-drug prescriptions among participants in the U.S. National Institute of Mental Health (NIMH) Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Complex polypharmacy regimens are found to be prescribed to a substantial proportion of individuals with bipolar disorder. It states that antidepressant use is linked with multiple depressive episodes. Receiver operating characteristic (ROC) approach for creating clinical profiles are said to beneficial.

Recent rodent models of antidepressant response implicate a novel set of genes in mechanisms of antidepressant action. The authors examined variants in four such genes (KCNK2 (TREK1), SLC18A2 (VMAT2), S100A10, and HDAC5) for association with remission in a large effectiveness trial of antidepressant treatments. Subjects were drawn from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study, a multicenter, prospective, effectiveness trial in major depressive disorder (MDD). Outpatients with nonpsychotic MDD were initially treated with citalopram for up to 14 weeks; those who did not remit with citalopram were sequentially randomized to a series of next-step treatments, each for up to 12 weeks. Single-nucleotide polymorphisms in four genes were examined for association with remission, defined as a clinician-rated Quick Inventory of Depressive Symptomatology (QIDS-C16) score 5. Of 1554 participants for whom DNA was available, 565 (36%) reached remission with citalopram treatment. No association with any of the four genes was identified. However, among the 751 who entered next-step treatment, variants in KCNK2 were associated with treatment response (Bonferroni-corrected, gene-based empirical p<0.001). In follow-up analyses, KCNK2 was also associated with effects of similar magnitude for third-step treatment among those with unsatisfactory benefit to both citalopram and one next-step pharmacotherapy (n=225). These findings indicate that genetic variation in KCNK2 may identify individuals at risk for treatment resistance. More broadly, they indicate the utility of animal models in identifying genes for pharmacogenetic studies of antidepressant response.Neuropsychopharmacology (2008) 33, 2810–2819; doi:10.1038/npp.2008.6; published online 20 February 2008 [ABSTRACT FROM AUTHOR]

The article discusses the association of a polymorphism near CREB1 with differential aversion processing. It is said that functional neuroimaging studies have identified a network of brain regions that process aversive stimuli, including anger. It is cited that a polymorphism near the cyclic adenosine monophosphate response element binding protein gene has been associated with anger control and risk for antidepressant treatment. It is mentioned that coincident activation in the left insula is associated with behavioral avoidance of the stimuli.

Objective: Practice guidelines have advised against treating patients with antidepressants during bipolar mixed states or dysphoric manias. However, few studies have examined the outcomes of patients with co-occurring manic and depressive symptoms who are treated with antidepressants plus mood stabilizing drugs. Method: The authors compared outcomes in patients with bipolar disorder who received a mood stabilizing agent with versus without an antidepressant for a bipolar depressive episode accompanied by ≥2 concurrent manic symptoms. The 335 participants were drawn from the first 2,000 enrollees in the National Institute of Mental Health (NIMH) Systematic Treatment Enhancement Program for Bipolar Disorder (STEP-BD). Kaplan-Meier survival curves and Cox regression models were used to compare time to recovery. General linear models examined the relationship between antidepressant use or mania symptom load at the study entry and mania or depression symptom severity at the 3-month follow-up. Results: Adjunctive antidepressant use was associated with significantly higher mania symptom severity at the 3-month follow-up. The probability of recovery at 3 months was lower among patients with higher baseline depression severity. Antidepressant use neither hastened nor prolonged time to recovery once potential confounding factors were covaried in a Cox regression model. Conclusions: In bipolar depression accompanied by manic symptoms, antidepressants do not hasten time to recovery relative to treatment with mood stabilizers alone, and treatment with antidepressants may lead to greater manic symptom severity. These findings are consistent with those from the STEP-BD randomized trial for pure bipolar depression, in which adjunctive antidepressants did not yield higher recovery rates than did mood stabilizer monotherapy. [ABSTRACT FROM AUTHOR]

Background: An increased incidence of brain white-matter hyperintensities has been described in major depressive disorder, butthe impact of such hyperintensities on treatment outcome is still controversial.Aims: To investigate the relationship of brain white-matter hyperintensities with cardiovascular risk factors and with treatment outcome in younger people with major depressive disorder.Method: We assessed brain white-matter hyperintensities and cardiovascular risk factors in 84 people with major depressive disorder prior to initiating antidepressant treatment. We also assessed hyperintensities in 35 matched controls.Results: We found no significant difference in the prevalence of white-matter hyperintensities between the depression and the control groups. Left-hemisphere subcortical hyperintensities correlated with lower rates of treatment response. We found no correlation between global hyperintensity measures and clinical outcome. Brain white-matter hyperintensities correlated with hypertension and age and withtotal cardiovascular risk score.Conclusions: Subcortical white-matter hyperintensities in the left hemisphere (but notin other brain areas) maybe associated with poor response to antidepressant treatment in major depression. [ABSTRACT FROM AUTHOR]

: BackgroundThe short (S) allele of the serotonin transporter gene-linked polymorphic region (5HTTLPR) has been associated with poorer antidepressant response in major depressive disorder (MDD) and with antidepressant-induced mania. This study investigated a possible association with treatment-emergent insomnia or agitation.: MethodsThirty-six outpatients with MDD were genotyped at 5HTTLPR and treated with open-label fluoxetine up to 60 mg/day. Treatment-emergent adverse effects were assessed at each study visit.: ResultsOf nine subjects homozygous for the “S” allele, seven (78%) developed new or worsening insomnia, versus 6 of 27 (22%) non-“S”-homozygous subjects (Fisher’s exact p = .005). Similarly, six of nine subjects homozygous for the “S” allele (67%) developed agitation, versus 2 of 27 (7%) of non-“S”-homozygous subjects (Fisher’s exact p = .001).: ConclusionsThe “S” allele of the 5HTTLPR may identify patients at risk for developing insomnia or agitation with fluoxetine treatment. This preliminary result requires confirmation in larger samples. [Copyright &y& Elsevier]

Effective antidepressant pharmacotherapy began in the 1950s, with the introduction of tricyclic antidepressants (TCA) and monoamine oxidase inhibitors (MAOI). Unfortunately, these medications have properties that can limit their utility. TCA can produce a variety of side effects and they have a narrow therapeutic index with a high risk of death in overdose. MAOI require dietary restrictions and carry a risk of hyperadrenergic crisis. Moreover, the advent of selective serotonin reuptake inhibitors (SSRI) has significantly affected the treatment of depression. SSRI have become the first-line treatment for depression because they are effective, require minimal dose titration and have fewer side effects with less risk of death in overdose than the traditional agents. In addition, the sexual side effects of SSRI and the older antidepressants can reduce compliance and diminish patient's quality of life.

The author reflects on an article published in the "New York Times" which presents public health population-level data indicating that many people are taking antidepressant. He is critical on the potential of the article to readers to make fallacious conclusion that psychiatric disease and the suffering it brings are a failing of character. He also outlines the lack of information on the extent to which treatment of depression can truly change lives for the better.

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%). [ABSTRACT FROM AUTHOR]

Objective: Response to specific depression treatments varies widely among individuals. Understanding and predicting that variation could have great benefits for people living with depression. Method: The authors describe a conceptual model for identifying and evaluating evidence relevant to personalizing treatment for depression. They review evidence related to three specific treatment decisions: choice between antidepressant medication and psychotherapy, selection of a specific antidepressant medication, and selection of a specific psychotherapy. They then discuss potential explanations for negative findings as well as implications for research and clinical practice. Results: Many previous studies have examined general predictors of outcome, but few have examined true moderators (predictors of differential response to alternative treatments). The limited evidence indicates that some specific clinical characteristics may inform the choice between antidepressant medication and psychotherapy and the choice of specific antidepressant medication. Research to date does not identify any biologic or genetic predictors of sufficient clinical utility to inform the choice between medication and psychotherapy, the selection of specific medication, or the selection of a specific psychotherapy. Conclusions: While individuals vary widely in response to specific depression treatments, the variability remains largely unpredictable. Future research should focus on identifying true moderator effects and should consider how response to treatments varies across episodes. At this time, our inability to match patients with treatments implies that systematic follow-up assessment and adjustment of treatment are more important than initial treatment selection. [ABSTRACT FROM AUTHOR]

Background: While clinicians commonly learn heuristics to guide antidepressant treatment selection, surveys suggest real-world prescribing practices vary widely. We aimed to determine the extent to which antidepressant prescriptions were consistent with commonly-advocated heuristics for treatment selection.Methods: This retrospective longitudinal cohort study examined electronic health records from psychiatry and non-psychiatry practice networks affiliated with two large academic medical centers between March 2008 and December 2017. Patients included 45,955 individuals with a major depressive disorder or depressive disorder not otherwise specified diagnosis who were prescribed at least one of 11 common antidepressant medications. Specific clinical features that may impact prescribing choices were extracted from coded data, and analyzed for association with index prescription in logistic regression models adjusted for sociodemographic variables and provider type.Results: Multiple clinical features yielded 10% or greater change in odds of prescribing, including overweight and underweight status and sexual dysfunction. These heuristics were generally applied similarly across hospital systems and psychiatrist and non-psychiatrist providers.Limitations: These analyses rely on coded clinical data, which is likely to substantially underestimate prevalence of particular clinical features. Additionally, numerous other features that may impact prescribing choices are not able to be modeled.Conclusion: Our results confirm the hypothesis that clinicians apply heuristics on the basis of clinical features to guide antidepressant prescribing, although the magnitude of these effects is modest, suggesting other patient- or clinician-level factors have larger effects.Funding: This work was funded by NSF GRFP (grant no. DGE1745303), Harvard SEAS, the Center for Research on Computation and Society at Harvard, the Harvard Data Science Initiative, and a grant from the National Institute of Mental Health (grant no. 1R01MH106577). [ABSTRACT FROM AUTHOR]

Objective: To evaluate the association of antenatal depression symptoms with preterm birth and small for gestational age (SGA).Methods: This was an observational cohort study conducted among women who completed Edinburgh Postnatal Depression Scale screening and delivered at 20 weeks of gestation or greater. The primary outcomes were preterm birth and an SGA neonate at birth (less than 10th percentile for gestational age); the primary predictor was an Edinburgh Postnatal Depression Scale antepartum score of 10 or greater, indicating symptoms of depression. Logistic regression models were used with and without consideration of antidepressant exposure during pregnancy.Results: Among 7,267 women, 831 (11%) screened positive for depression. In multivariable analyses adjusting for maternal age, race, income, body mass index, tobacco use, lifetime diagnosis of major depression and anxiety, diabetes, hypertension, and preeclampsia, women who screened positive for depression experienced an increased risk of preterm birth (less than 37 weeks of gestation) (adjusted odds ratio [OR] 1.27, 95% confidence interval [CI] 1.04-1.55) and very preterm birth (less than 32 weeks of gestation) (adjusted OR 1.82, 95% CI 1.09-3.02) as well as of having an SGA neonate (adjusted OR 1.28, 95% CI 1.04-1.58). In secondary analyses, among women who were treated with an antidepressant during pregnancy (19% of those who screened positive and 5% of those who screened negative), depressive symptoms were not associated with a significantly increased risk of preterm and very preterm birth or an SGA neonate.Conclusions: In a large cohort of women screened for depression antepartum, those with depressive symptoms had an increased likelihood of preterm and very preterm delivery as well having an SGA neonate. Such risk was not apparent among women who were treated with an antidepressant medication. [ABSTRACT FROM AUTHOR]

Background While antidepressant treatment response appears to be partially heritable, no consistent genetic associations have been identified. Large, rare copy number variants (CNVs) play a role in other neuropsychiatric diseases, so we assessed their association with treatment-resistant depression (TRD). Methods We analyzed data from two genome-wide association studies comprising 1263 Caucasian patients with major depressive disorder. One was drawn from a large health system by applying natural language processing to electronic health records (i2b2 cohort). The second consisted of a multicenter study of sequential antidepressant treatments, Sequenced Treatment Alternatives to Relieve Depression. The Birdsuite package was used to identify rare deletions and duplications. Individuals without symptomatic remission, despite two antidepressant treatment trials, were contrasted with those who remitted with a first treatment trial. Results CNV data were derived for 778 subjects in the i2b2 cohort, including 300 subjects (37%) with TRD, and 485 subjects in Sequenced Treatment Alternatives to Relieve Depression cohort, including 152 (31%) with TRD. CNV burden analyses identified modest enrichment of duplications in cases (empirical p = .04 for duplications of 100–200 kilobase) and a particular deletion region spanning gene PABPC4L (empirical p = .02, 6 cases: 0 controls). Pathway analysis suggested enrichment of CNVs intersecting genes regulating actin cytoskeleton. However, none of these associations survived genome-wide correction. Conclusions Contribution of rare CNVs to TRD appears to be modest, individually or in aggregate. The electronic health record-based methodology demonstrated here should facilitate collection of larger TRD cohorts necessary to further characterize these effects. [ABSTRACT FROM AUTHOR]

Abstract: Leptin, a peptide hormone from adipose tissue and key player in weight regulation, has been suggested to be involved in sleep and cognition and to exert antidepressant-like effects, presumably via its action on the HPA-axis and hippocampal function. This led us to investigate whether genetic variants in the leptin gene, the level of leptin mRNA-expression and leptin serum concentrations are associated with response to antidepressant treatment. Our sample consisted of inpatients from the Munich Antidepressant Response Signature (MARS) project with weekly Hamilton Depression ratings, divided into two subsamples. In the exploratory sample (n=251) 17 single nucleotide polymorphisms (SNPs) covering the leptin gene region were genotyped. We found significant associations of several SNPs with impaired antidepressant treatment outcome and impaired cognitive performance after correction for multiple testing. The SNP (rs10487506) showing the highest association with treatment response (p=3.9×10−5) was analyzed in the replication sample (n=358) and the association could be verified (p=0.021) with response to tricyclic antidepressants. In an additional meta-analysis combining results from the MARS study with data from the Genome-based Therapeutic Drugs for Depression (GENDEP) and the Sequenced Treatment Alternatives to Relieve Depression (STAR⁎D) studies, nominal associations of several polymorphisms in the upstream vicinity of rs10487506 with treatment outcome were detected (p=0.001). In addition, we determined leptin mRNA expression in lymphocytes and leptin serum levels in subsamples of the MARS study. Unfavorable treatment outcome was accompanied with decreased leptin mRNA and leptin serum levels. Our results suggest an involvement of leptin in antidepressant action and cognitive function in depression with genetic polymorphisms in the leptin gene, decreased leptin gene expression and leptin deficiency in serum being risk factors for resistance to antidepressant therapy in depressed patients. [Copyright &y& Elsevier]