Treatment Response In Major Depressive Disorder Research Articles

Goal Attainment Scaling for Depression: Validation of the Japanese GAS-D Tool in Patients with Major Depressive Disorder.

Goal attainment scaling (GAS) has been proposed as a person-centric, semi-quantitative measure that assimilates achievement of individually set goals into a single standardized "goal attainment score" that can be compared at the population level. We aimed to examine the reliability and validity of the Japanese version of the GAS for depression (GAS-D) tool in assessing goal attainment in people living with major depressive disorder (MDD). This was a prespecified analysis of a prospective, 24-week, multicenter, observational cohort study of employed Japanese outpatients with MDD initiating treatment with vortioxetine according to the Japanese label (JRCT1031210200). Participants were assessed using the Japanese version of the GAS-D and other clinical rating scales at baseline and Weeks 8, 12 and 24. Goal attainment was significantly associated with symptom severity as assessed by the Montgomery-Åsberg Depression Rating Scale (MADRS) scale, confirming convergent validity. In particular, GAS-D scores were significantly related to MADRS total score at Weeks 12 and 24, indicating that improvements in overall symptom severity with vortioxetine treatment were likely to be reflected in the achievement of individualized treatment goals. With an intraclass correlation coefficient of 0.67 (95% CI 0.45-0.82), the GAS-D also showed moderate test-retest reliability between Weeks 8 and 12 while proving independent of demographic characteristics. The results of this open-label study support the use of the GAS-D as a valid and sensitive outcome measure in the assessment of treatment response in MDD.

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.

Investigating genetic variants for treatment response to selective serotonin reuptake inhibitors in syndromal factors and side effects among patients with depression in Taiwanese Han population.

Major depressive disorder (MDD) is associated with high heterogeneity in clinical presentation. In addition, response to treatment with selective serotonin reuptake inhibitors (SSRIs) varies considerably among patients. Therefore, identifying genetic variants that may contribute to SSRI treatment responses in MDD is essential. In this study, we analyzed the syndromal factor structures of the Hamilton Depression Rating Scale in 479 patients with MDD by using exploratory factor analysis. All patients were followed up biweekly for 8 weeks. Treatment response was defined for all syndromal factors and total scores. In addition, a genome-wide association study was performed to investigate the treatment outcomes at week 4 and repeatedly assess all visits during follow-up by using mixed models adjusted for age, gender, and population substructure. Moreover, the role of genetic variants in suicidal and sexual side effects was explored, and five syndromal factors for depression were derived: core, insomnia, somatic anxiety, psychomotor-insight, and anorexia. Subsequently, several known genes were mapped to suggestive signals for treatment outcomes, including single-nucleotide polymorphisms (SNPs) in PRF1, UTP20, MGAM, and ENSG00000286536 for psychomotor-insight and in C4orf51 for anorexia. In total, 33 independent SNPs for treatment responses were tested in a mixed model, 12 of which demonstrated a p value <0.05. The most significant SNP was rs2182717 in the ENSR00000803469 gene located on chromosome 6 for the core syndromal factor (β = -0.638, p = 1.8 × 10-4) in terms of symptom improvement over time. Patients with a GG or GA genotype with the rs2182717 SNP also exhibited a treatment response (β = 0.089, p = 2.0 × 10-6) at week 4. Moreover, rs1836075352 was associated with sexual side effects (p = 3.2 × 10-8). Pathway and network analyses using the identified SNPs revealed potential biological functions involved in treatment response, such as neurodevelopment-related functions and immune processes. In conclusion, we identified loci that may affect the clinical response to treatment with antidepressants in the context of empirically defined depressive syndromal factors and side effects among the Taiwanese Han population, thus providing novel biological targets for further investigation.

Sequence Modeling of Passive Sensing Data for Treatment Response Prediction in Major Depressive Disorder.

Major depressive disorder (MDD) is a prevalent mental health condition and has become a pressing societal challenge. Early prediction of treatment response may aid in the rehabilitation engineering of depression, which is of great practical significance for the relief of suffering and burden of MDD. In this paper, we present a sequence modeling approach that uses data collected by passive sensing techniques to predict patients with an outcome of treatment responded defined by the reduction in clinical administrated scales. Hundreds of patients with MDD have been recruited from outpatient clinics at 4 psychiatric sites. Each has been delivered with a self-developed app to passively record their daily phone usage and physical data with minimal human action. An unavoidable dilemma in passive sensing is missing values. To overcome that, the proposed approach combined feature extraction and sequence modeling methods to fully utilize the pattern of missing values from longitudinal data. With no treatment constraints, it enables us to predict the treatment response of MDD 8-10 weeks before the completion of the treatment course, leaving time for preventative measures. Our work explored the feasibility of treatment response prediction using longitudinal passive sensing data and sparse ground truth, and also has the potential for preventing depression by forecasting treatment outcomes weeks in advance.

Effect of pharmacogenomic testing on pediatric mental health outcome: a 6-month follow-up.

Aim: This retrospective, case-control study evaluated the effect of pharmacogenomic testing (PGT) on the management of pediatrics with anxiety, major depressive disorder (MDD) and attention-deficit/hyperactivity disorder (ADHD). Methods: The authors examined psychiatric diagnoses, medication histories, CYP450 profiles, SLC6A4, HTR2A, COMT and MTHFR. Results: The authors found no difference in clinical improvement between the two groups. However, the number of medication changes was significantly larger after PGT. The treatment response in MDD and anxiety was not different between the groups, while ADHD treatment response was substantially improved in PGT and correlated with COMT status. Conclusion: PGT had some value with ADHD with doubtful benefit for MDD or anxiety disorders. Accordingly, pediatric indications must be weighed against cost, utility and clinician experience. Limitations included sample size and selection bias.

Discovery and validation of acetyl-L-carnitine in serum for diagnosis of major depressive disorder and remission status through metabolomic approach.

Major depressive disorder (MDD) is one of the most common psychiatric disorders that accompany psychophysiological and mood changes. However, the pathophysiology-based disease mechanism of MDD is not yet fully understood, and diagnosis is also conducted through interviews with clinicians and patients. Diagnosis and treatment of MDD are limited due to the absence of biomarkers underlying the pathophysiological mechanisms of MDD. Although various attempts have been made to discover metabolite biomarkers for the diagnosis and treatment response of MDD, problems with sample size and consistency of results have limited clinical application. In addition, it was reported that future biomarker studies must consider exposure to antidepressants, which is the main cause of heterogeneity in depression subgroups. Therefore, the purpose of this study is to discover and validate biomarkers for the diagnosis of depression in consideration of exposure to drug treatment including antidepressants that contribute to the heterogeneity of the MDD subgroup. In the biomarker discovery and validation set, the disease group consisted of a mixture of patients exposed and unexposed to drug treatment including antidepressants for the treatment of MDD. The serum metabolites that differed between the MDD patients and the control group were profiled using mass spectrometry. The validation set including the remission group was used to verify the effectiveness as a biomarker for the diagnosis of depression and determination of remission status. The presence of different metabolites between the two groups was confirmed through serum metabolite profiling between the MDD patient group and the control group. Finally, Acetylcarnitine was selected as a biomarker. In validation, acetylcarnitine was significantly decreased in MDD and was distinguished from remission status. This study confirmed that the discovered acetylcarnitine has potential as a biomarker for diagnosing depression and determining remission status, regardless of exposure to drug treatment including antidepressants.

Cardiovascular biomarkers of response to accelerated low frequency repetitive transcranial magnetic stimulation in major depression

Background and objectiveRepetitive transcranial magnetic stimulation (rTMS) is an effective and safe treatment for major depressive disorder (MDD). rTMS is in need of a reliable biomarker of treatment response. High frequency (HF) dorsolateral prefrontal cortex (DLPFC) rTMS has been reported to induce significant changes in the cardiac activity of MDD patients. Low frequency DLPFC rTMS has many advantages over HF-DLPFC rTMS and thus this study aims to further investigate the effect of low frequency 1 Hz right hemisphere (R)-DLPFC rTMS on the cardiac activity of MDD patients, as well as the potential of using electrocardiogram (ECG) parameters as biomarkers of treatment outcome. MethodsBaseline ECG sessions were performed for 19 MDD patients. All patients then underwent 40 sessions of accelerated 1 Hz R-DLPFC rTMS one week after the baseline session. ResultsHeart rate (HR) significantly decreased from the resting period to the first and third minute of the 1 Hz R-DLPFC rTMS period. Resting HR was found to have a significant negative association with treatment outcome. Prior to Bonferroni correction, HR during stimulation and the degree of rTMS-induced HR reduction were significantly negatively associated with treatment outcome. No significant changes were observed for the heart rate variability (HRV) parameters. LimitationsSample size (n = 19); the use of electroencephalography equipment for ECG; lack of respiration monitoring; relatively short recording duration for HRV parameters. ConclusionThis novel study provides further preliminary evidence that ECG may be utilized as a biomarker of rTMS treatment response in MDD. Trial registrationClinicalTrials.gov Identifier: NCT04376697.

Creating sparser prediction models of treatment outcome in depression: a proof-of-concept study using simultaneous feature selection and hyperparameter tuning

BackgroundPredicting treatment outcome in major depressive disorder (MDD) remains an essential challenge for precision psychiatry. Clinical prediction models (CPMs) based on supervised machine learning have been a promising approach for this endeavor. However, only few CPMs have focused on model sparsity even though sparser models might facilitate the translation into clinical practice and lower the expenses of their application.MethodsIn this study, we developed a predictive modeling pipeline that combines hyperparameter tuning and recursive feature elimination in a nested cross-validation framework. We applied this pipeline to a real-world clinical data set on MDD treatment response and to a second simulated data set using three different classification algorithms. Performance was evaluated by permutation testing and comparison to a reference pipeline without nested feature selection.ResultsAcross all models, the proposed pipeline led to sparser CPMs compared to the reference pipeline. Except for one comparison, the proposed pipeline resulted in equally or more accurate predictions. For MDD treatment response, balanced accuracy scores ranged between 61 and 71% when models were applied to hold-out validation data.ConclusionsThe resulting models might be particularly interesting for clinical applications as they could reduce expenses for clinical institutions and stress for patients.

Effects of Antidepressant Treatment on Neurotrophic Factors (BDNF and IGF-1) in Patients with Major Depressive Disorder (MDD).

Major depressive disorder (MDD) remains the subject of ongoing research as a multifactorial disease and a serious public health problem. There is a growing body of literature focusing on the role of neurotrophic factors in pathophysiology of MDD. A neurotrophic hypothesis of depression proposes that abnormalities of neurotrophins serum levels lead to neuronal atrophy and decreased neurogenesis, resulting in mood disorders. Consequently, in accordance with recent findings, antidepressant treatment modifies the serum levels of neurotrophins and thus leads to a clinical improvement of MDD. The purpose of this review is to summarize the available data on the effects of various antidepressants on serum levels of neurotrophins such as brain-derived neurotrophic factor (BDNF) and insulin-like growth factor (IGF-1). In addition, the authors discuss their role as prognostic factors for treatment response in MDD. A literature search was performed using the PubMed database. Following the inclusion and exclusion criteria, nine original articles and three meta-analyses were selected. The vast majority of studies have confirmed the effect of antidepressants on BDNF levels. Research on IGF-1 is limited and insufficient to describe the correlation between different antidepressant drugs and factor serum levels; however, four studies indicated a decrease in IGF-1 after treatment. Preliminary data suggest BDNF as a promising predictor of treatment response in MDD patients. The role of IGF-1 needs further investigation.

Visual and Auditory Markers of Major Depressive Disorder Treatment Response to Serotonin Reuptake Inhibitors: Evidence for Changes in Motor Functioning as an Index of Antidepressant Response

Multiple machine learning-based visual and auditory digital markers have demonstrated associations between Major Depressive Disorder (MDD) status and severity. The current study examines if such measurements can quantify response to antidepressant treatment (ADT) with selective serotonin reuptake inhibitors (SSRIs) and serotonin-norepinephrine uptake inhibitors (SNRIs). Given the role of serotonin in movement/motor functioning via expression in the motor cortex, we hypothesized that measures reflecting motor activity would be responsive to SSRI-based ADT.

Effects of Antidepressant Treatment on Peripheral Biomarkers in Patients with Major Depressive Disorder (MDD).

Major depressive disorder (MDD) is one of the most prevalent mental illness and a leading cause of disability worldwide. Despite a range of effective treatments, more than 30% of patients do not achieve remission as a result of conventional therapy. In these circumstances the identification of novel drug targets and pathogenic factors becomes essential for selecting more efficacious and personalized treatment. Increasing evidence has implicated the role of inflammation in the pathophysiology of depression, revealing potential new pathways and treatment options. Moreover, convergent evidence indicates that MDD is related to disturbed neurogenesis and suggests a possible role of neurotrophic factors in recovery of function in patients. Although the influence of antidepressants on inflammatory cytokines balance was widely reported in various studies, the exact correlation between drugs used and specific cytokines and neurotrophins serum levels often remains inconsistent. Available data suggest anti-inflammatory properties of selective serotonin reuptake inhibitors (SSRIs), selective serotonin and noradrenaline inhibitors (SNRIs), and tricyclic antidepressants (TCAs) as a possible additional mechanism of reduction of depressive symptoms. In this review, we outline emerging data regarding the influence of different antidepressant drugs on a wide array of peripheral biomarkers such as interleukin (IL)-1ß, IL-2, IL-5, IL-6, IL-8, IL-10, C-reactive protein (CRP), or interferon (IFN)-γ. Presented results indicate anti-inflammatory effect for selected drugs or lack of such effect. Research in this field is insufficient to define the role of inflammatory markers as a predictor of treatment response in MDD.

Fronto-limbic neuroimaging biomarkers for diagnosis and prediction of treatment responses in major depressive disorder

The neuroimaging is an important tool for understanding the biomarkers and predicting treatment responses in major depressive disorder (MDD). The potential biomarkers and prediction of treatment response in MDD will be addressed in the review article. The brain regions of cognitive control and emotion regulation, such as the frontal and limbic regions, might represent the potential targets for MDD biomarkers. The potential targets of frontal lobes might include anterior cingulate cortex (ACC), dorsolateral prefrontal cortex (DLPFC) and orbitofrontal cortex (OFC). For the limbic system, hippocampus and amygdala might be the potentially promising targets for MDD. The potential targets of fronto-limbic regions have been found in the studies of several major neuroimaging modalities, such as the magnetic resonance imaging, near-infrared spectroscopy, electroencephalography, positron emission tomography, and single-photon emission computed tomography. Additional regions, such as brainstem and midbrain, might also play a part in the MDD biomarkers. For the prediction of treatment response, the gray matter volumes, white matter tracts, functional representations and receptor bindings of ACC, DLPFC, OFC, amygdala, and hippocampus might play a role in the prediction of antidepressant responses in MDD. For the response prediction of psychotherapies, the fronto-limbic, reward regions, and insula will be the potential targets. For the repetitive transcranial magnetic stimulation, the DLPFC, ACC, limbic, and visuospatial regions might represent the predictive targets for treatment. The neuroimaging targets of MDD might be focused in the fronto-limbic regions. However, the neuroimaging targets for the prediction of treatment responses might be inconclusive and beyond the fronto-limbic regions.

Higher polygenic risk scores for schizophrenia may be suggestive of treatment non-response in major depressive disorder

Up to 60% of patients with major depressive disorder (MDD) do not respond to the first treatment with antidepressants. Response to antidepressants is a polygenic trait, although its underpinning genetics has not been fully clarified.This study aimed to investigate if polygenic risk scores (PRSs) for major psychiatric disorders and trait neuroticism (NEU) were associated with non-response or resistance to antidepressants in MDD.PRSs for bipolar disorder, MDD, NEU, and schizophrenia (SCZ) were computed in 1,148 patients with MDD. Summary statistics from the largest meta-analyses of genome-wide association studies were used as base data. Patients were classified as responders, non-responders to one treatment, non-responders to two or more treatments (treatment-resistant depression or TRD). Regression analyses were adjusted for population stratification and recruitment sites.PRSs did not predict either non-response vs response or TRD vs response after Bonferroni correction. However, SCZ-PRS was nominally associated with non-response (p = 0.003). Patients in the highest SCZ-PRS quintile were more likely to be non-responders than those in the lowest quintile (OR = 2.23, 95% CI = 1.21–4.10, p = 0.02). Patients in the lowest SCZ-PRS quintile showed higher response rates when they did not receive augmentation with second-generation antipsychotics (SGAs), while those in the highest SCZ-PRS quintile had a poor response independently from the treatment strategy (p = 0.009).A higher genetic liability to SCZ may reduce treatment response in MDD, and patients with low SCZ-PRSs may show higher response rates without SGA augmentation. Multivariate approaches and methodological refinements will be necessary before clinical implementations of PRSs.

Value of peripheral neurotrophin levels for the diagnosis of depression and response to treatment: A systematic review and meta-analysis

The neurotrophin hypothesis indicates that neurotrophic factors are important for the pathophysiology of major depressive disorder (MDD), with alterations in peripheral neurotrophin levels having potential clinical application for MDD. The present meta-analysis aimed to investigate the diagnostic value for MDD of peripheral neurotrophin levels in cross-sectional studies and the association between peripheral neurotrophin levels and the response to antidepressant treatment in longitudinal studies. Published studies in the PubMed and Web of Science databases were systematically searched up to February 2020. The search terms included depressive disorder, neurotrophic factor, serum/plasma and their synonyms. Human studies reporting on BDNF, GDNF, IGF-2, VEGF, NGF, FGF-2, and S100B levels in MDD patients were included. Data comparing MDD patients and healthy controls, and/or between responders and non-responders before and after antidepressant treatment were extracted. A random effects model was used to calculate standardized mean differences. A total of 177 original studies were identified, including 139 cross-sectional and 38 longitudinal studies. Significantly reduced BDNF and NGF levels and significantly elevated IGF-1, VEGF, and S100B levels were reported in MDD patients compared with healthy controls, while GDNF and FGF-2 levels were not significantly different. Furthermore, compared with non-responders, S100B levels at baseline and BDNF levels following treatment were significantly elevated in responders. In addition, there was a significantly elevated level of VEGF after treatment in responders only. In conclusions, alterations in peripheral neurotrophins levels were strongly associated with the biology and the treatment response of MDD. Further investigations are required to examine potential sources of heterogeneity.

Influence of genetic polymorphisms in homocysteine and lipid metabolism systems on antidepressant drug response

BackgroundVariation in genes implicated in homocysteine and lipid metabolism systems may influence antidepressant response for patients with major depressive disorder (MDD). This study aimed to investigate whether association of polymorphisms on the MTHFR, ApoE and ApoA4 genes with the treatment response in MDD subjects.MethodsA total of 281 Han Chinese MDD patients received a single antidepressant drug (SSRI or SNRI) for at least 6 weeks, among whom 275 were followed up for 8 weeks. Their response to 6 weeks’ treatment and remission to 8 weeks’ treatment with antidepressant drugs was determined by changes in the 17-item Hamilton Depression Rating Scale (HARS-17) score. Single SNP and haplotype associations with treatment response were analyzed by UNPHASED 3.0.13. Logistic regression analysis was used to explore the interactions between genotypes and gender or drug type on treatment outcome, only those SNPs that had interactional association with gender or drug type were subjected to further stratified analysis.ResultsIn total group, the haplotype (C-A) in MTHFR (rsl801133 and rs1801131) and the ApoE rs405509 AA genotype were significantly associated with better efficacy of antidepressants; In gender subgroups, only haplotype (C-A) in MTHFR (rsl801133 and rs1801131) was significantly associated with better efficacy of antidepressants in male subgroup; In drug type subgroup, the haplotype (C-A) in MTHFR (rsl801133 and rs1801131) and haplotype (G-C) in ApoE (rs7412 and rs405509) were associated with better efficacy of antidepressants in SNRI treated subgroup; The ApoA4 rs5092 G allele and GG genotype were associated with worse efficacy of antidepressants in SNRI treated subgroup.ConclusionsGenetic polymorphisms in homocysteine and lipid metabolism systems are associated with antidepressant response, particularly for the interactions of the certain genetic with gender or drug type.

A randomized placebo-controlled PET study of ketamine\xb4s effect on serotonin1B receptor binding in patients with SSRI-resistant depression

The glutamate N-methyl-d-aspartate receptor antagonist ketamine has a rapid antidepressant effect. Despite large research efforts, ketamine’s mechanism of action in major depressive disorder (MDD) has still not been determined. In rodents, the antidepressant properties of ketamine were found to be dependent on both the α-amino-3-hydroxy-5-methylisoxazole-4-propionic acid (AMPA) and the serotonin (5-HT)1B receptor. Low 5-HT1B receptor binding in limbic brain regions is a replicated finding in MDD. In non-human primates, AMPA-dependent increase in 5-HT1B receptor binding in the ventral striatum (VST) has been demonstrated after ketamine infusion. Thirty selective serotonin reuptake inhibitor-resistant MDD patients were recruited via advertisement and randomized to double-blind monotherapy with 0.5 mg/kg ketamine or placebo infusion. The patients were examined with the 5-HT1B receptor selective radioligand [11C]AZ10419369 and positron emission tomography (PET) before and 24–72 h after treatment. 5-HT1B receptor binding did not significantly alter in patients treated with ketamine compared with placebo. An increase in 5-HT1B receptor binding with 16.7 % (p = 0.036) was found in the hippocampus after one ketamine treatment. 5-HT1B receptor binding in VST at baseline correlated with MDD symptom ratings (r = −0.426, p = 0.019) and with reduction of depressive symptoms with ketamine (r = −0.644, p = 0.002). In conclusion, reduction of depressive symptoms in MDD patients after ketamine treatment is correlated inversely with baseline 5-HT1B receptor binding in VST. Further studies examining the role of 5-HT1B receptors in the antidepressant mechanism of action of ketamine should be conducted, homing in on the 5-HT1B receptor as an MDD treatment response marker.

Ratio of plasma BDNF to leptin levels are associated with treatment response in major depressive disorder but not in panic disorder: A 12-week follow-up study

BackgroundA link between brain-derived neurotrophic factor (BDNF) expression and the mood regulatory effect of leptin has been suggested in the pathophysiology of major depressive disorder (MDD). We investigated treatment response and pre-treatment leptin and BDNF in patients with MDD and with panic disorder (PD). MethodsWe recruited 41 patients with MDD, 52 patients with PD, and 59 matched healthy controls. All subjects completed five visits (at baseline, 2, 4, 8, and 12 weeks), and both MDD and PD patients were treated with standard pharmacotherapy for 12 weeks. Plasma BDNF (pBDNF) and blood leptin levels were obtained along with a 17-item Hamilton Depression Scale rating (HDRS-17) score at every visit. ResultsThe ratio of pre-treatment pBDNF to leptin was significantly lower in patients with MDD and PD compared to healthy controls (p = 0.024), but was not associated with severity of depressive or anxiety symptoms. Pre-treatment pBDNF:leptin ratio was significantly higher in treatment responders than in non-responders (p = 0.012) in MDD but not in PD. This difference was larger in MDD patients with appetite loss (p = 0.034). In multivariate analysis, pre-treatment pBDNF:leptin ratio was significantly associated with treatment responsiveness (Adjusted Odds Ration [AOR] = 2.50, 95% CI 1.02–6.14) in MDD. Limitationsmall sample size; limited information on detailed pharmacological effects. ConclusionsA relatively higher ratio of pre-treatment pBDNF to leptin was associated with greater treatment response in MDD but not in PD. Further research should focus on exploration of a link between BDNF and leptin underlying neuronal plasticity in depression.

The association of obesity and coronary artery disease genes with response to SSRIs treatment in major depression.

Selective serotonin reuptake inhibitors (SSRIs) are first-line antidepressants for the treatment of major depressive disorder (MDD). However, treatment response during an initial therapeutic trial is often poor and is difficult to predict. Heterogeneity of response to SSRIs in depressed patients is partly driven by co-occurring somatic disorders such as coronary artery disease (CAD) and obesity. CAD and obesity may also be associated with metabolic side effects of SSRIs. In this study, we assessed the association of CAD and obesity with treatment response to SSRIs in patients with MDD using a polygenic score (PGS) approach. Additionally, we performed cross-trait meta-analyses to pinpoint genetic variants underpinnings the relationship of CAD and obesity with SSRIs treatment response. First, PGSs were calculated at different p value thresholds (PT) for obesity and CAD. Next, binary logistic regression was applied to evaluate the association of the PGSs to SSRIs treatment response in a discovery sample (ISPC, N = 865), and in a replication cohort (STAR*D, N = 1,878). Finally, a cross-trait GWAS meta-analysis was performed by combining summary statistics. We show that the PGSs for CAD and obesity were inversely associated with SSRIs treatment response. At the most significant thresholds, the PGS for CAD and body mass index accounted 1.3%, and 0.8% of the observed variability in treatment response to SSRIs, respectively. In the cross-trait meta-analyses, we identified (1) 14 genetic loci (including NEGR1, CADM2, PMAIP1, PARK2) that are associated with both obesity and SSRIs treatment response; (2) five genetic loci (LINC01412, PHACTR1, CDKN2B, ATXN2, KCNE2) with effects on CAD and SSRIs treatment response. Our findings implicate that the genetic variants of CAD and obesity are linked to SSRIs treatment response in MDD. A better SSRIs treatment response might be achieved through a stratified allocation of treatment for MDD patients with a genetic risk for obesity or CAD.

233. Indices of Cellular Health are Associated With Antidepressant Treatment Response

Accelerated cellular aging, evidenced by shortened leukocyte telomere length (LTL), has been reported in Major Depressive Disorder (MDD), and may convey an increased risk for somatic co-morbidity. Shortened LTL reflects a cell’s mitotic history, cellular “age” and cumulative exposure to inflammation and oxidation, as well as the availability of telomerase, a telomere-lengthening enzyme. Telomere shortening leads to replicative senescence and cellular malfunctions including oxidative stress, mitochondrial damage, and apoptosis. Here we present data linking indices of accelerated cellular aging to worse antidepressant treatment response in MDD.

Dissociative symptoms are associated with neurocognitive dysfunction in patients with MDD

IntroductionIt is widely reported that persons with major depressive disorder (MDD) show impaired performance on cognitive functioning, including frontotemporally mediated cognitive functions. The presence of cognitive dysfunction among patients with dissociative symptoms in trauma-related disorders may contribute to poorer treatment outcomes. Patients with major depressive disorder (MDD) frequently report dissociative symptoms. Here we investigate association of dissociative symptoms and neurocognitive dysfunction in patients with depression. We predicted that higher levels of dissociative symptoms among persons with MDD would be associated with lower scores on objective measures of frontotemporally mediated neurocognitive functions.MethodsPatients who met DSM-V diagnostic criteria for a primary diagnosis of recurrent MDD were recruited. The Hamilton Rating Scale for Depression (HAM-D) was administered to assess the severity of depressive symptoms. To assess dissociative symptoms participants completed the Multiscale Dissociation Inventory (MDI). Two groups of patients were selected and matched. One group consisted of 13 patients having MDD and dissociative symptoms and second group consisted of 12 patients having MDD only. To measure frontotemporally mediated cognitive functioning following tests were administered: Color Trails Test; Wisconsin Card Sorting Test; Conners’ Continuous Performance Test (CPT). To examine group differences on clinical and neuropsychological scores, two-tailed independent samples t-tests was performed.ResultsGroup comparisons of performance on neuropsychological tests showed that participants with depression and dissociative symptoms performed worse on Color Trails Test Part 2 completion time, a measure of mental flexibility and processing speed. MDI depersonalization scores were correlated with measures of processing speed, mental flexibility and sustained attention. Specifically, Color Trails Test Part 2 scores were negatively correlated with depersonalization symptoms, where lower scores indicate slower completion time. Depersonalization symptoms on the MDI were also related to the CPT Hit Reaction Time Interstimulus Interval Change (a measure of vigilance), such that higher levels of depersonalization were related to better performance in a less active environment.ConclusionsOur results suggest that dissociation is related to specific subtle impairments in neurocognitive functioning. Dissociative symptoms should ideally be assessed before treatment, as they may influence MDD treatment response. The findings point towards the need to further examine the impact of dissociation on functioning in patients with depression.Disclosure of interestThe authors have not supplied their declaration of competing interest.