Antidepressant Response In Patients Research Articles

A genome-wide association study of escitalopram treatment outcomes in patients with major depressive disorder

Major depressive disorder (MDD) is a common psychological condition, the consequences of which, such as suicide, can be severe. Escitalopram, a selective serotonin reuptake inhibitor, is a commonly used antidepressant in clinics. However, more than one-third of patients with MDD do not respond to this drug. Gene polymorphism may affect the efficacy of escitalopram, but the genetic architecture of the antidepressant response in patients with MDD remains unclear. We perform a genome-wide association study (GWAS) of the genetic effect on the outcome of escitalopram in patients with MDD. A total of 203 patients with MDD and 176 healthy control (HC) adults were recruited from Beijing Anding Hospital. Patients received 12 weeks of antidepressant treatment with escitalopram. The Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) or Hamilton depression scale (HAMD) were used to evaluate the severity of depression symptoms at the baseline and the end of 2 and 12 weeks of treatment. A total of 140 variants in MDD patients were identified by GWAS to have genome-wide significance (p < 5e − 8) compared with HCs. Similarly, 189 and 18 variants were identified to be associated with QIDS-SR and HAMD score changes in patients after antidepressant treatment (p < 1e − 5), including rs12602361, rs72799048, rs16842235, and rs2518256. In the two weeks QIDS-SR score study, the gene-level association for these variants and gene set enrichment analyses implicate the enrichment of genes involved in the synaptic plasticity process and nervous system development. Our results implicate the predictive capacity of the effect of escitalopram treatment, supporting a link between genetic basis and remission of depression.

Hippocampal and parahippocampal volume and function predict antidepressant response in patients with major depression: A multimodal neuroimaging study.

For many patients with major depressive disorder (MDD) adequate treatment remains elusive. Neuroimaging techniques received attention for their potential use in guiding and predicting response, but were rarely investigated in real-world psychiatric settings. To identify structural and functional Magnetic Resonance Imaging (MRI) biomarkers associated with antidepressant response in a real-world clinical sample. We studied 100 MDD inpatients admitted to our psychiatric ward, treated with various antidepressants upon clinical need. Hamilton Depression Rating Scale percentage decrease from admission to discharge was used as a measure of response. All patients underwent 3.0 T MRI scanning. Grey matter (GM) volumes were investigated both in a voxel-based morphometry (VBM), and in a regions of interest (ROI) analysis. In a subsample of patients, functional resting-state connectivity patterns were also explored. In the VBM analysis, worse response was associated to lower GM volumes in two clusters, encompassing the left hippocampus and parahippocampal gyrus, and the right superior and middle temporal gyrus. Investigating ROIs, lower bilateral hippocampi and amygdalae volumes predicted worse treatment outcomes. Functional connectivity in the right temporal and parahippocampal gyrus was also associated to response. Our results expand existing literature on the relationship between the structure and function of several brain regions and treatment response in MDD. While we are still far from routine use of MRI biomarkers in clinical practice, we confirm a possible role of these techniques in guiding treatment choices and predicting their efficacy.

The impact of age on antidepressant response: A mega-analysis of individuals with major depressive disorder

IntroductionUnderstanding how age affects antidepressant response in patients with major depressive disorder has been complicated by small and heterogeneous studies. Yet, understanding how age—across the lifespan—contributes to variation in response could inform treatment selection across the lifespan. This study sought to identify how age impacts antidepressant response using participant-level data from large, NIH-sponsored trials in individuals with MDD aged 12–74 years. Materials and methodsParticipant-level data were abstracted from three NIH-sponsored trials of pharmacotherapy (Treatment of SSRI-Resistant Depression in Adolescents (TORDIA) Study, Treatment of Adolescent Depression Study (TADS), and the Combining Medications to Enhance Depression Outcomes Study (COMED)) in patients with MDD. Bayesian Hierarchical Models (BHMs) of individual treatment trajectories were developed using Hamiltonian Monte Carlo No U-Turn Sampling. The individual trajectory of improvement in depressive symptoms (Clinical Global Impression-Severity [CGI-S] and CGI-S equivalent from COMED) was modeled across studies and across individuals with logarithmic trend “random effects” coefficients BHMs. Age and sex (and their interaction) were examined categorically across patients. ResultsStudy participants (N = 907) were 29.7 ± 17 years of age, 66.3% women, and had a mean baseline CGI-S score of 4.6 ± 0.9. Patients ≤21 years and those >55 years had slower and less response to pharmacotherapy compared to those aged 21–35. Additionally, women improved more than men, and this effect did not differ across ages. DiscussionThe patient's age should be considered in predicting antidepressant response, particularly in older and younger individuals who may benefit from other interventions to enhance treatment response.

Influence of antidepressant treatment on SLC6A4 methylation in Korean patients with major depression.

Genetic variation of the serotonin transporter gene (SLC6A4) has been suggested as potential mediator for antidepressant response in patients with depression. This study aimed to determine whether DNA methylation in SLC6A4 changes after antidepressant treatment and whether it affects treatment response in patients with depression. Overall, 221 Korean patients with depression completed 6 weeks of selective serotonin reuptake inhibitor (SSRI) monotherapy. DNA was extracted from venous blood pre- and post-treatment, and DNA methylation was analyzed using polymerase chain reaction. We used Wilcoxon's signed-rank test to verify the difference in methylation after treatment. Treatment response was assessed using the 17-item Hamilton Depression Rating Scale, and mRNA levels were quantified. After adjusting for relevant covariates, DNA methylation was significantly altered in specific CpG sites in SLC6A4 (p < .001 in CpG3, CpG4, and CpG5) following 6 weeks of treatment. Methylation change's magnitude (ΔDNA methylation) after drug treatment was not associated with treatment response or mRNA level change. SSRI antidepressants can influence SLC6A4 methylation in patients with depression. However, ΔDNA methylation at CpG3, CpG4, and CpG5 in SLC6A4 was not associated with treatment response. Future studies should investigate the integrative effect of other genetic variants and CpG methylation on gene transcription and antidepressant treatment response.

Machine learning, pharmacogenomics, and clinical psychiatry: predicting antidepressant response in patients with major depressive disorder

ABSTRACT Introduction The efficacy of antidepressants for patients with major depressive disorder (MDD) varies from individual to individual, making the prediction of therapeutic outcomes difficult. Better methods for predicting antidepressant outcomes are needed. However, complex interactions between biological, psychological, and environmental factors affect outcomes, presenting immense computational challenges for prediction. Using machine learning (ML) techniques with pharmacogenomics data provides one pathway toward individualized prediction of therapeutic outcomes of antidepressants. Areas covered This report systematically reviews the methods, results, and limitations of individual studies of ML and pharmacogenomics for predicting response and/or remission with antidepressants in patients with MDD. Future directions for research and pragmatic considerations for the clinical implementation of ML-based pharmacogenomic algorithms are also discussed. Expert opinion ML methods utilizing pharmacogenomic and clinical data demonstrate promising results for predicting short-term antidepressant response. However, predictions of antidepressant treatment outcomes depend on contextual factors that ML algorithms may not be able to capture. As such, ML-driven prediction is best viewed as a companion to clinical judgment, not its replacement. Successful implementation and adoption of methods predicting antidepressant response warrants provider education about ML and close collaborations between computing scientists, pharmacogenomic experts, health system engineers, laboratory medicine experts, and clinicians.

The interaction of P11 methylation and early-life stress impacts the antidepressant response in patients with major depressive disorder

PurposeThe present research investigates the influence of P11 gene DNA methylation combined with life stress on the response to antidepressants in the first two weeks. MethodsA total of 291 Han Chinese patients with major depressive disorder and 100 healthy controls were included. The Life Events Scale and the Childhood Trauma Questionnaire were used to assess stress. The primary endpoint was the Hamilton Depression Rating Scale-17 reduction rate after two weeks of treatment. The Illumina HiSeq Platform was used to detect the methylation of 74 CpG sites of the P11 gene in peripheral blood samples. ResultsThe mean methylation of all P11 CpG sites, as well as the methylation at 4 CpG sites (P11-2-169, P11-2-192, P11-2-202, P11-2-204), were significantly higher in patients with MDD than in healthy controls (FDR-corrected P < 0.05). The response to antidepressants was associated with the following interactions: the CTQ score and P11-3-185 site methylation (OR = 0.297, FDR-corrected P = 0.023), the CTQ physical neglect score and P11-2-117 site methylation (OR = 0.005, FDR-corrected P = 0.033), and the CTQ emotional abuse score and P11-3-185 site methylation (OR = 0.001, FDR-corrected P = 0.023). ConclusionsThe methylation of the P11 gene was significantly higher in patients with major depressive disorder. The interaction of P11 DNA methylation and early-life stress may influence the short-term antidepressant treatment response.

Less basal thyrotropin levels predict antidepressant response in patients with major depression

IntroductionThe close association among thyroid metabolism, mood disorders and behavior has long been known. The role of basal thyroid axis in antidepressant treatment response is less known.ObjectivesThe aim of the present study was to study the association of basal serum thyrotropin (TSH) levels, with antidepressant treatment response in major depressive disorder.MethodsThirty-one depressed adult outpatients were included. Major depressive episode was diagnosed through the MINI (DSM-IV-TR) interview. Clinical symptomatology and blood samples were assessed at baseline, and at 4- and 8-weeks of either escitalopram or sertraline. Treatment response was defined by an improvement ≥50% in MADRS scores at 4-, and 8-weeks. Basal TSH levels were included in a linear regression model as predictor of treatment response.ResultsTwenty-seven patients finished 8-weeks of treatment. Response to treatment was of 74% at 4-weeks, and 63% at 8-weeks of antidepressant treatment. Basal median TSH levels were between normal ranges (M+SD=1.85+1,02 mlU/L). Basal TSH levels not correlated with basal MADRS scores, but with higher MADRS scores at week-4 (r=0,415, p=0,031) and at week-8 (r=0,392, p=0,043). Moreover, less baseline TSH levels trend to be a significant good predictor for treatment response at 4-weeks (R2=.116, p=.083); and a good predictor at 8-weeks treatment (R2=.147, p=.049).ConclusionsBaseline TSH levels even within the normal range may play a role in predicting antidepressant response.DisclosureNo significant relationships.

P354. Brain Hippocampal volume, Cortisol and C-Reactive Protein Levels Relationship With Antidepressant Response in Patients With Major Depressive Disorder

Major depression disorder limits psychosocial functioning and quality of life. The pathophysiological theories associate that higher glucocorticoids levels and inflammatory responses in with changes in the hippocampus volume observed in depressive patients.

High S100B Levels Predict Antidepressant Response in Patients With Major Depression Even When Considering Inflammatory and Metabolic Markers.

BackgroundThe relationship between antidepressant response and glial, inflammatory, and metabolic markers is poorly understood in depression. This study assessed the ability of biological markers to predict antidepressant response in major depressive disorder (MDD).MethodsWe included 31 MDD outpatients treated with escitalopram or sertraline for 8 consecutive weeks. The Montgomery-Åsberg Depression Rating Scale (MADRS) was administered at baseline and at week 4 and 8 of treatment. Concomitantly, blood samples were collected for the determination of serum S100B, C-reactive protein (CRP), and high-density lipoprotein cholesterol (HDL)-C levels. Treatment response was defined as ≥50% improvement in the MADRS score from baseline to either week 4 or 8. Variables associated with treatment response were included in a linear regression model as predictors of treatment response.ResultsTwenty-seven patients (87%) completed 8 weeks of treatment; 74% and 63% were responders at week 4 and 8, respectively. High S100B and low HDL-C levels at baseline were associated with better treatment response at both time points. Low CRP levels were correlated with better response at week 4. Multivariate analysis showed that high baseline S100B levels and low baseline HDL-C levels were good predictors of treatment response at week 4 (R2 = 0.457, P = .001), while S100B was at week 8 (R2 = 0.239, P = .011). Importantly, baseline S100B and HDL-C levels were not associated with depression severity and did not change over time with clinical improvement.ConclusionsSerum S100B levels appear to be a useful biomarker of antidepressant response in MDD even when considering inflammatory and metabolic markers.

A randomized, multicenter trial assessing the effects of rapastinel compared to ketamine, alprazolam, and placebo on simulated driving performance.

N‐methyl‐D‐aspartate ionotropic glutamatergic receptor (NMDAR) modulators, including rapastinel and ketamine, elicit rapid and sustained antidepressant responses in patients with treatment‐resistant major depressive disorder. This phase I, randomized, multicenter, placebo‐controlled, five‐period, crossover, single‐dose study evaluated simulated driving performance of healthy participants (N = 107) after single doses of rapastinel slow intravenous (i.v.) bolus 900 and 1800 mg, alprazolam oral 0.75 mg (positive control), ketamine i.v. infusion 0.5 mg/kg (clinical comparator), and placebo ~ 45 min before driving. The primary end point was SD of lateral position (SDLP) during the 60‐min 100‐km simulated driving scenario. Additional measures of driving performance, sleepiness, and cognition were also evaluated. To assess effects over time, mean SDLP was calculated for each 10‐min interval of driving. Sensitivity of the assays was confirmed with alprazolam (all placebo comparisons p < 0.02). Rapastinel 900 and 1800 mg did not significantly affect simulated driving performance compared to placebo (both p > 0.5). Both rapastinel doses resulted in significantly less impaired driving compared to alprazolam or ketamine (all p < 0.002); ketamine significantly impaired driving compared to placebo (p = 0.0001). Results for the additional measures were similar to the primary end point. No new safety signals were observed for any study interventions. This first study of rapastinel effects on simulated driving found that rapastinel 900 and 1800 mg did not impair driving performance, but ketamine 0.5 mg/kg resulted in significantly impaired driving performance. Ketamine’s effects on driving were maintained for at least 105 min, indicating that clinicians should be vigilant to prevent or postpone driving in patients after ketamine treatment.

Ketamine decreases neuronally released glutamate via retrograde stimulation of presynaptic adenosine A1 receptors

Ketamine produces a rapid antidepressant response in patients with major depressive disorder (MDD), but the underlying mechanisms appear multifaceted. One hypothesis, proposes that by antagonizing NMDA receptors on GABAergic interneurons, ketamine disinhibits afferens to glutamatergic principal neurons and increases extracellular glutamate levels. However, ketamine seems also to reduce rapid glutamate release at some synapses. Therefore, clinical studies in MDD patients have stressed the need to identify mechanisms whereby ketamine decreases presynaptic activity and glutamate release. In the present study, the effect of ketamine and its antidepressant metabolite, (2R,6R)-HNK, on neuronally derived glutamate release was examined in rodents. We used FAST methodology to measure depolarization-evoked extracellular glutamate levels in vivo in freely moving or anesthetized animals, synaptosomes to detect synaptic recycling ex vivo and primary cortical neurons to perform functional imaging and to examine intracellular signaling in vitro. In all these versatile approaches, ketamine and (2R,6R)-HNK reduced glutamate release in a manner which could be blocked by AMPA receptor antagonism. Antagonism of adenosine A1 receptors, which are almost exclusively expressed at nerve terminals, also counteracted ketamine’s effect on glutamate release and presynaptic activity. Signal transduction studies in primary neuronal cultures demonstrated that ketamine reduced P-T286-CamKII and P-S9-Synapsin, which correlated with decreased synaptic vesicle recycling. Moreover, systemic administration of A1R antagonist counteracted the antidepressant-like actions of ketamine and (2R,6R)-HNK in the forced swim test. To conclude, by studying neuronally released glutamate, we identified a novel retrograde adenosinergic feedback mechanism that mediate inhibitory actions of ketamine on glutamate release that may contribute to its rapid antidepressant action.

The relationship between plasma cytokine levels and antidepressant response in patients with first-episode major depressive disorder

BackgroundCytokines are involved in the pathophysiology of major depressive disorder (MDD) and treatment response. Efforts have been made to identify inflammatory markers but results are often contradictory. The present study explored the plasma levels of multiple cytokines in first-episode MDD using a longitudinal design, with the aim to determine the involvement of cytokines in depression and identify the inflammatory markers. MethodFifty-four first-episode drug naïve MDD patients and 60 healthy controls (HCs) were enrolled in this study. The 17-item Hamilton Depression Rating Scale (HAMD-17) was administered and blood samples were collected at baseline and four-week posttreatment in MDD group, while blood samples were only collected once in HC group. Plasma levels of nineteen cytokines were examined by a multiplexed flow cytometric assay. ResultsSixteen out of 19 cytokines levels in MDD group were significantly higher than those in HC group (all P < 0.05). After 4-week of antidepressant treatment, levels of the 14 cytokines elevated at baseline decreased to normal levels (all P < 0.05). Partial correlation showed that baseline level of interferon-inducible T cell alpha chemoattractant (ITAC) was negatively correlated with reduction in HAMD-17 score (r=−0.319, p=0.020), and multiple regression showed lower baseline ITAC level was associated with better treatment response (p = 0.020). LimitationThe sample size was relatively small. ConclusionA range of cytokines were abnormal in patients with first-episode drug naïve MDD and most of the cytokines could be normalized after antidepressant treatment. Furthermore, baseline ITAC level could be a predictive factor of antidepressant response.

Development of Neuroimaging-Based Biomarkers in Major Depression.

A leading goal in the field of biological psychiatry for depression is to find a promising diagnostic biomarker and selection of specific psychiatric treatment mode that is most likely to benefit patients with depression. Recent neuroimaging studies have characterized the pathophysiology of major depressive disorder (MDD) with functional and structural alterations in the neural circuitry involved in emotion or reward processing. Particularly, structural and functional magnetic resonance imaging (MRI) studies have reported that the brain structures deeply involved in emotion regulation or reward processing including the amygdala, prefrontal cortex (PFC), anterior cingulate cortex (ACC), ventral striatum, and hippocampus are key regions that provide useful information about diagnosis and treatment outcome prediction in MDD. For example, it has been consistently reported that elevated activity of the ACC is associated with better antidepressant response in patients with MDD. This chapter will discuss a growing body of evidence that suggests that diagnosis or prediction of outcome for specific treatment can be assisted by a neuroimaging-based biomarker in MDD.

Assessment of Relationship of Ketamine Dose With Magnetic Resonance Spectroscopy of Glx and GABA Responses in Adults With Major Depression

A single subanesthetic dose of ketamine produces an antidepressant response in patients with major depressive disorder (MDD) within hours, but the mechanism of antidepressant effect is uncertain. To evaluate whether ketamine dose and brain glutamate and glutamine (Glx) and γ-aminobutyric acid (GABA) level responses to ketamine are related to antidepressant benefit and adverse effects. This randomized, parallel-group, triple-masked clinical trial included 38 physically healthy, psychotropic medication-free adult outpatients who were in a major depressive episode of MDD but not actively suicidal. The trial was conducted at Columbia University Medical Center. Data were collected from February 2012 to May 2015. Data analysis was conducted from January to March 2020. Participants received 1 dose of placebo or ketamine (0.1, 0.2, 0.3, 0.4, or 0.5 mg/kg) intravenously during 40 minutes of a proton magnetic resonance spectroscopy scan that measured ventro-medial prefrontal cortex Glx and GABA levels in 13-minute data frames. Clinical improvement was measured using a 22-item version of the Hamilton Depression Rating Scale (HDRS-22) 24 hours after ketamine was administered. Ketamine and metabolite blood levels were measured after the scan. A total of 38 individuals participated in the study, with a mean (SD) age of 38.6 (11.2) years, 23 (60.5%) women, and 25 (65.8%) White patients. Improvement in HDRS-22 score at 24 hours correlated positively with ketamine dose (t36 = 2.81; P = .008; slope estimate, 19.80 [95% CI, 5.49 to 34.11]) and blood level (t36 = 2.25; P = .03; slope estimate, 0.070 [95% CI, 0.007 to 0.133]). The lower the Glx response, the better the antidepressant response (t33 = -2.400; P = .02; slope estimate, -9.85 [95% CI, -18.2 to -1.50]). Although GABA levels correlated with Glx (t33 = 8.117; P < .001; slope estimate, 0.510 [95% CI, 0.382 to 0.638]), GABA response did not correlate with antidepressant effect. When both ketamine dose and Glx response were included in a mediation analysis model, ketamine dose was no longer associated with antidepressant effect, indicating that Glx response mediated the relationship. Adverse effects were related to blood levels in men only (t5 = 2.606; P = .048; estimated slope, 0.093 [95% CI, 0.001 to 0.186]), but Glx and GABA response were not related to adverse effects. In this study, intravenous ketamine dose and blood levels correlated positively with antidepressant response. The Glx response correlated inversely with ketamine dose and with antidepressant effect. Future studies are needed to determine whether the relationship between Glx level and antidepressant effect is due to glutamate or glutamine. ClinicalTrials.gov Identifier: NCT01558063.

Targeted exome sequencing identifies five novel loci at genome-wide significance for modulating antidepressant response in patients with major depressive disorder

In order to determine the role of single nucleotide variants (SNVs) in modulating antidepressant response, we conducted a study, consisting of 929 major depressive disorder (MDD) patients, who were treated with antidepressant drugs (drug-only) or in combination with a repetitive transcranial magnetic stimulation (plus-rTMS), followed by targeted exome sequencing analysis. We found that the “plus-rTMS” patients presented a more effective response to the treatment when compared to the ‘drug-only’ group. Our data firstly demonstrated that the SNV burden had a significant impact on the antidepressant response presented in the “drug-only” group, but was limited in the “plus-rTMS” group. Further, after controlling for overall SNV burden, seven single nucleotide polymorphisms (SNPs) at five loci, IL1A, GNA15, PPP2CB, PLA2G4C, and GBA, were identified as affecting the antidepressant response at genome-wide significance (P < 5 × 10−08). Additional multiple variants achieved a level of correction for multiple testing, including GNA11, also shown as a strong signal for MDD risk. Our study showed some promising evidence on genetic variants that could be used as individualized therapeutic guides for MDD patients.

The role of eEF2 kinase in the rapid antidepressant actions of ketamine.

Major depressive disorder is a prevalent and serious form of mental illness. While traditional antidepressants ameliorate some of the symptoms associated with depression, the onset of action typically takes several weeks leaving severely depressed individuals vulnerable to self-injurious behavior and possibly suicide. There has been a major unmet need for the development of pharmacological therapies that can quickly alleviate symptoms associated with depression. Clinical data shows that a single sub-psychomimetic dose of ketamine, a noncompetitive glutamatergic N-methyl-d-aspartate (NMDA) receptor antagonist, has rapid antidepressant responses in patients with treatment-resistant major depressive disorder. We have studied key signaling pathways and synaptic mechanisms underlying the rapid antidepressant action of ketamine. Our studies show ketamine blocks synaptic NMDA receptors involved in spontaneous synaptic transmission, which deactivates calcium/calmodulin-dependent kinase eukaryotic elongation factor 2 kinase (eEF2K), resulting in dephosphorylation of eukaryotic elongation factor 2 (eEF2), and the subsequent desuppression of brain-derived neurotrophic factor (BDNF) protein synthesis in the hippocampus. This signaling pathway then potentiates synaptic α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA) receptor responses that results in a novel form of synaptic potentiation which corresponds with antidepressant efficacy. In this chapter, we focus on our studies examining ketamine's action and the instructive role of eEF2K in rapid antidepressant action. Our recent studies highlight eEF2K as a major molecular substrate mediating synaptic plasticity and the rapid antidepressant effects of ketamine.

Involvement of muscarinic receptor mechanisms in antidepressant drug action.

Conventional antidepressants typically require weeks of daily dosing to achieve full antidepressant response in antidepressant responders. A newly evolving group of compounds can engender more rapid response times in depressed patients. These drugs include the newly approved antidepressant (S)-ketamine (esketamine, Spravato). A seminal study by Furey and Drevets in 2006 showed antidepressant response in patients after only a few doses with the antimuscarinic drug scopolamine. Several clinical reports have generally confirmed scopolamine as a rapid-acting antidepressant. The data with scopolamine are consistent with the adrenergic/cholinergic hypothesis of mania/depression derived from clinical reports originating in the 1970s from Janowsky and colleagues. Additional support for a role for muscarinic receptors in mood disorders comes from the greater efficacy of conventional antidepressants that have relatively high levels of muscarinic receptor blocking actions (e.g., the tricyclic antidepressant amitriptyline vs the selective serotonin reuptake inhibitor fluoxetine). There appears to be appreciable overlap in the mechanisms of action of scopolamine and other rapid-acting antidepressants (ketamine) or putative rapid-acting agents (mGlu2/3 receptor antagonists) although gaps exist in the experimental literature. Current hypotheses regarding the mechanisms underlying the rapid antidepressant response to scopolamine posit an M1 receptor subtype-initiated cascade of biological events that involve the amplification of AMPA receptors. Consequent impact on brain-derived neurotrophic factor and mTor signaling pathways result in the induction of dendritic spines that enable augmented functional connectivity in brain areas regulating mood. Two major goals for research in this area focus on finding ways in which scopolamine might best be utilized for depressed patients and the discovery of alternative compounds that improve upon the efficacy and safety of scopolamine.

Childhood trauma, HPA axis activity and antidepressant response in patients with depression

Childhood trauma is among the most potent contributing risk factors for depression and is associated with poor treatment response. Hypothalamic-pituitary-adrenal (HPA) axis abnormalities have been linked to both childhood trauma and depression, but the underlying mechanisms are poorly understood. The present study aimed to investigate the link between childhood trauma, HPA axis activity and antidepressant response in patients with depression. As part of the Wellcome Trust NIMA consortium, 163 depressed patients and 55 healthy volunteers were included in this study. Adult patients meeting Structured Clinical Interview for Diagnostic and Statistical Manual Version-5 criteria for major depression were categorised into subgroups of treatment responder (n = 42), treatment non-responder (n = 80) and untreated depressed (n = 41) based on current depressive symptom severity measured by the 17-item Hamilton Rating Scale for Depression and exposure to antidepressant medications established by Antidepressant Treatment Response Questionnaire. Childhood Trauma Questionnaire was obtained. Baseline serum C-reactive protein was measured using turbidimetric detection. Salivary cortisol was analyzed at multiple time points during the day using the ELISA technique. Glucocorticoid resistance was defined as the coexistence of hypercortisolemia and inflammation. Our results show that treatment non-responder patients had higher exposure to childhood trauma than responders. No specific HPA axis abnormalities were found in treatment non-responder depressed patients. Untreated depressed showed increased diurnal cortisol levels compared with patients on antidepressant medication, and higher prevalence of glucocorticoid resistance than medicated patients and controls. The severity of childhood trauma was associated with increased diurnal cortisol levels only in individuals with glucocorticoid resistance. Therefore, our findings suggest that the severity of childhood trauma experience contributes to a lack of response to antidepressant treatment. The effects of childhood trauma on increased cortisol levels are specifically evident in patients with glucocorticoid resistance and suggest glucocorticoid resistance as a target for the development of personalized treatment for a subgroup of depressed patients with a history of childhood trauma rather than for all patients with resistance to antidepressant treatment.

Modulation of the inflammatory response benefits treatment-resistant bipolar depression: A randomized clinical trial

ObjectiveThe goal of this study was to reduce treatment resistance and enhance antidepressant response in patients with treatment-resistant bipolar depression (TRBDD) by modulating inflammatory activation. MethodsForty-seven TRBDD patients completed a randomized, double-blind, placebo (PBO)-controlled two-arm study using celecoxib (CBX), a cyclooxygenase 2 (COX-2) inhibitor, in combination with escitalopram (ESC). The Hamilton Depression (17-Item) and the Hamilton Anxiety Rating Scales were used to quantify symptom severity. Self-rating instruments included BDI, BAI and QLES-Q questioner. An adverse events inventory was used, and the possibility of bleeding diathesis was monitored. Complete blood count (CBC), prothrombin time (PT), and activated partial thromboplastin time (APTT) were determined. Comparison of mood scores between the CBX and PBO groups were conducted using a mixed ANOVA and an Independent Sample Student t-test. ResultsThe CBX adjunctive treatment produced significantly more responders and remitters than the PBO arm. Compared to the PBO group (n = 20), the CBX group (n = 27) experienced lower depression severity through the entire course of the study, showing significant decrease in depression and anxiety scores as early as week 1. Except for initial mild nausea, no adverse events were reported and study medications were well tolerated. ConclusionsModulation of the inflammatory response through targeted inhibition of the enzyme COX-2 by means of CBX reduces TRBDD and augments and accelerates treatment response in an efficacious and safe manner. Future studies should replicate these findings and additionally investigate whether prolonged administration of CBX is required to maintain remission by adding a discontinuation phase to the study design. Trial RegistrationClinicaltrials.gov ID: NCT01479829.

Abstract # 4264 Glucocorticoid resistance, childhood trauma and antidepressant response in patients with depression: Results from BIODEP study UK

Abstract # 4264 Glucocorticoid resistance, childhood trauma and antidepressant response in patients with depression: Results from BIODEP study UK