Antidepressant Treatment Response Research Articles

Dispositional optimism predicts antidepressant treatment response in major depressive disorder: potential relevance for positive psychology interventions

ABSTRACT Positive psychology interventions have demonstrated efficacy in treating Major Depressive Disorder (MDD), but the relationship between dispositional optimism and antidepressant treatment response remains unclear. In this study, optimism (Revised Life Orientation Test, LOT-R) and depression severity (Hamilton Depression Rating Scale, HDRS) were assessed in healthy unmedicated MDD participants (N = 86) and healthy controls (N = 65). Treatment response (≥50% reduction in HDRS) was measured in 46 of these MDD participants after 8 weeks of open-label selective serotonin reuptake inhibitor (SSRI) treatment. MDD participants reported significantly lower pre-treatment optimism than healthy controls. Higher pre-treatment optimism, as well as greater increase in optimism (pre-treatment to 8 weeks), were associated with greater likelihood of being an SSRI responder versus non-responder (β = 0.21, p = 0.013; β = 0.32, p = 0.01, respectively), even when ratings of optimism/pessimism were excluded from depression severity/response ratings. The findings are consistent with the importance of aspects of positive psychology in treatment response. Possible mechanisms are discussed.

ABC Family Gene Polymorphisms and Cognitive Functions Interact to Influence Antidepressant Efficacy.

The importance of identifying relevant indicators of antidepressant efficacy is highlighted by the low response rates to antidepressant treatment for depression. The ABC gene family, encoding ATP-dependent transport proteins facilitating the transport of psychotropic drugs, has drawn attention. This study delved into the relationship between antidepressant efficacy and seven single nucleotide polymorphisms of ABCB1 and ABCB6 genes. A total of 549 depressed patients participated in the study, and all completed a 6-week course of antidepressant treatment. Cognitive function was assessed at baseline and post-treatment. Patients were categorized based on post-treatment HAMD-17 scores (with HAMD≤7 indicating remission), and comparisons were made between different groups in terms of allelic gene frequencies and genotypes. Logistic regression was used to explore the interaction between cognitive function and genotype on efficacy. Dual-luciferase reporter assays were performed to compare the regulatory effects of rs1109866 allele variants on the ABCB6 promoter. There were no notable differences in allelic gene frequencies and genotypes between the remission and non-remission groups. Nonetheless, a significant interaction was identified between the rs1109866 genotype and language fluency-related indicators concerning efficacy (p=0.029) before correction. The dual-luciferase reporter assays demonstrated markedly higher fluorescence intensity of rs1109866-C compared to that of rs1109866-T (p<0.001). Relying solely on genetic polymorphisms of ABC family genes as predictors of antidepressant treatment response may not be sufficient. However, the interaction between the rs1109866 and cognition plays a pivotal role. The potentially enhanced transcriptional activity of rs1109866-C might offer insight into its impact on antidepressant efficacy.

Liquid Biopsy-Based Detection and Response Prediction for Depression.

Proactively predicting antidepressant treatment response before medication failures is crucial, as it reduces unsuccessful attempts and facilitates the development of personalized therapeutic strategies, ultimately enhancing treatment efficacy. The current decision-making process, which heavily depends on subjective indicators, underscores the need for an objective, indicator-based approach. This study developed a method for detecting depression and predicting treatment response through deep learning-based spectroscopic analysis of extracellular vesicles (EVs) from plasma. EVs were isolated from the plasma of both nondepressed and depressed groups, followed by Raman signal acquisition, which was used for AI algorithm development. The algorithm successfully distinguished depression patients from healthy individuals and those with panic disorder, achieving an AUC accuracy of 0.95. This demonstrates the model's capability to selectively diagnose depression within a nondepressed group, including those with other mental health disorders. Furthermore, the algorithm identified depression-diagnosed patients likely to respond to antidepressants, classifying responders and nonresponders with an AUC accuracy of 0.91. To establish a diagnostic foundation, the algorithm applied explainable AI (XAI), enabling personalized medicine for companion diagnostics and highlighting its potential for the development of liquid biopsy-based mental disorder diagnosis.

Changes in P300 amplitude to negative emotional stimuli correlate with treatment responsiveness to sertraline in adolescents with depression

ObjectiveAdolescents with depression is characterized by high rates of recurrence and functional impairment, with a significant association with suicide risk. Antidepressants are commonly prescribed to treat depression, yet few reproducible neurobiological markers for depression and antidepressant treatment response have been identified. Therefore, discovering a stable and reliable neurobiological marker holds significant value for both the clinical diagnosis and treatment of depression in adolescents. MethodsOne hundred and seven patients with major depressive disorder (MDD group, 30 males, 77 females, mean age: 14.80 years), and 25 healthy subjects (HC group, 13 males, 12 females, mean age: 15.72 years) were recruited to perform a two-choice oddball task related to negative emotional cues. All participants completed a self-administered questionnaire to gather demographic information. A trained psychiatrist administered the Hamilton Depression Scale (HAMD-17) to assess depression severity. Of the 107 adolescents with depression, 61 received antidepressant medication for 8 weeks, and 61 of these patients were followed up. Multichannel EEG was recorded continuously from 64 scalp electrodes using the Curry 8 system. EEG signal preprocessing and analysis was performed offline using the EEGLAB toolbox in MATLAB. The ERP component characteristics associated with emotional processing were extracted from the difference waves and statistically analyzed. ResultsAdolescents with depression exhibited significantly larger P300 amplitudes than healthy controls in response to both neutral and negative emotional cues. Following sertraline treatment, both depression scores and P300 amplitudes decreased significantly in adolescents with depression. Moreover, a strong positive correlation was observed between changes in depression scores and changes in P300 amplitude in response to negative emotional cues before and after treatment. ConclusionsChanges in neural reactivity to negative emotional stimuli among adolescents with depression can be selectively modulated by sertraline and are significantly associated with improvements in depressive symptoms. SignificanceChanges in P300 amplitude to negative emotional stimuli significantly correlate with treatment responsiveness to sertraline in adolescents with depression.

Epigenome-Wide DNA Methylation in Unipolar Depression: Predictive Biomarker of Antidepressant Treatment Response?

Despite the well-documented efficacy of antidepressant agents for the treatment of major depressive disorder (MDD), initial treatment nonresponse rates are high. Recent years have seen an increase in research into predictive biomarkers toward improving diagnosis and individualized treatment. Among those, epigenetic mechanisms such as DNA methylation constitute promising candidate markers in predicting antidepressant treatment response in MDD. The present study sought to address epigenome-wide DNA methylation as a predictor of antidepressant treatment response in the largest sample to date of patients with MDD. Epigenome-wide DNA methylation was analyzed using the Infinium MethylationEPIC BeadChip in peripheral blood of n = 230 Caucasian patients with MDD receiving 6-week antidepressant treatment in a naturalistic in-patient setting as well as in a subsample of n = 107 patients primarily receiving continuous treatment with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors. Treatment response was assessed by means of the Hamilton Depression Scale. No genome-wide significant hits were observed. Suggestive (P < 1E-5) epigenome-wide evidence was discerned for altered DNA methylation at 6 CpG sites (LOC102724467, LOC100506023, RSPO2, SAG, IL16, PRKCI) to predict response to naturalistic antidepressant treatment. In patients treated with serotonin reuptake inhibitors or serotonin and norepinephrine reuptake inhibitors, differential DNA methylation at 11 CpGs, for example, mapping to the TIMP2, VDAC1, or SORL1 genes, was suggestively associated with treatment response. The present results provide preliminary evidence for altered DNA methylation patterns to be associated with antidepressant treatment response in MDD. Provided significant replication in independent and larger samples, the present findings might in the future aid in clinical decision-making toward more individualized and thus more efficacious treatments of MDD.

DNA methylation of serotonin genes as predictive biomarkers of antidepressant treatment response

Selective serotonin reuptake inhibitors (SSRI) are frequently ineffective in treating depressive episodes and biomarkers are needed to optimize antidepressant treatment outcomes. DNA methylation levels of serotonin transporter (SLC6A4) and tryptophan hydroxylase 2 genes (TPH2) have been suggested to predict antidepressant clinical outcomes but their applicability remains uncertain. In this study, we: 1) evaluated SLC6A4/TPH2 methylation biomarker potential for predicting clinical outcomes after escitalopram treatment; 2) evaluated whether changes in SLC6A4/TPH2 methylation are informative of treatment mechanisms. We used a cohort of 90 unmedicated patients with major depressive disorder that were part of a 12-week open-label longitudinal trial and compared our observations with previous findings. Depressive symptoms were measured at baseline and after 8 and 12 weeks of treatment using the Hamilton Depression Rating Scale (HAMD6/17). We found an association between baseline TPH2 methylation and both clinical response (β:3.43; p = 0.01; 95 % CI:[0.80; 6.06]) and change in depressive symptoms after 8 weeks (β:−45.44; p = 0.01; 95 %CI:[− −78.58; −12.30]). However, we found no evidence for predictive value of any gene (TPH2 AUC: 0.74 95 % CI:[0.42;0.79]; SLC6A4: AUC: 0.61; 95 % CI: [0.48–0.78]). Methylation levels changed at the trend level for CpG sites of SLC6A4 and TPH2 over the course of 12 weeks of treatment. In addition, similar to previous observations, we found a trend for an association between methylation of SLC6A4 CpG2 (chr17:30,236,083) and HAMD17 change after 12 weeks. Our findings suggest that although TPH2 and SLC6A4 methylation may be informative of antidepressant treatment outcome, they are unlikely to prove useful as clinical predictor tools.

Assessing antidepressant exposure and response using UK electronic health record data

Objective and ApproachMany people do not respond to antidepressants and our poor mechanistic understanding of antidepressant response has hampered efforts to personalise treatment. Understanding how and when antidepressants work at an individual level requires real-world antidepressant exposure and response data, at scale. To date, studies have rarely had access to sufficiently detailed clinical data at the scales needed to derive such phenotypes and track them longitudinally. Indeed, many studies use research-based measures and phenotypes that are not commonly used in clinical settings, making translation to clinically-applicable tools difficult. This study aims to develop novel measures of antidepressant treatment exposure and response by capitalising on the variety and volume of UK clinical records. We identify cases of depression from national primary and secondary care records, and derive longitudinal antidepressant treatment episodes from national community dispensing data. ResultsFocusing on the Generation Scotland cohort (N = 21,000), we describe common antidepressant treatment trajectories and identify changes in medication, dose and strength. We examine the frequency of drug switching, augmentation, and drug stability, contrasting these to other UK linked cohorts. We also describe the demographic characteristics of those defined as treatment resistant and those identified as in drug maintenance. ConclusionsLinked electronic records provide the opportunity to track antidepressant exposure and response longitudinally. Changes in treatment can provide new measures that help to better understand treatment resistance and maintenance. ImplicationsBy better tracking antidepressant response, the present study helps inform mechanistic research to understand treatment effectiveness and ultimately to develop personalised treatments.

Interaction Effect of Childhood Abuse History and Suicidality on 12-Month Antidepressant Response in Patients With Depressive Disorder.

We aimed to identify the individual and interactive effects of childhood abuse and suicidal ideation on antidepressant treatment response in 12 months. In this prospective research, 1,262 depressive patients were asked about their childhood abuse history, suicidal ideation, and other clinical characteristics and socio-demographic features at baseline, and 1,015 of them were followed during 1 year of stepwise pharmacotherapy. The individual and interactive relationships of the childhood abuse history and suicidal ideation on 12-month antidepressant non-remission were explored by logistic regression with relevant covariates. Having a childhood abuse history and higher suicidal ideation significantly predicted a non-remission state in 12 months respectively. The interaction term of childhood abuse and suicidal ideation was also significantly related to a non-remission state at 12 months. To be specific, in the low suicidal ideation group, depressive patients with a childhood abuse history were more likely to be in a non-remission state after 12 months of medication. In the high suicidal ideation group, however, childhood abuse history was not significantly associated with the non-remission state at 12 months. The childhood abuse history and the level of suicidal ideation are informative factors predicting the long-term results of antidepressant treatment, especially when they are combined. Clinicians may consider antidepressants with a higher affinity for patients with childhood abuse history even if they don't have suicidal ideation. The cognitive intervention for suicidal ideation might be helpful in addition to pharmacological treatment.

An Updated Review on Possible Therapeutic Role of Vincamine Via 5-HT Receptors in the Treatment of Depression

Background: Serotonin is a neurotransmitter that regulates neuronal activity and a variety of cognitive functions, and medicines that target serotonin receptors are frequently utilized in psychiatry and neurology. Clinical and preclinical research on the role of serotonin in major depressive disorder is growing. These findings demonstrate the intricacy of serotonin transmission across multiple receptors, in a variety of brain areas, and across the lifespan. The serotonin transporter's significance in major depressive disorder has been highlighted in geneenvironment association studies, as well as its participation in the mechanism of the most successful antidepressant medications, selective serotonin reuptake inhibitors. While most of the 15 known serotonin receptors have been linked to depression or depressive-like behaviour, the serotonin 1A (5-HT) and 1B (5-HT) receptors have received the most attention. Objectives: The primary goal of this study is to review the antidepressant effect of herbal medications by modifying serotonin receptors in the future. Result: Human brain imaging and genetic studies suggest that 5-HT and 5-HT receptors play a role in major depressive disorder and antidepressant treatment response. The availability of tissue-specific and inducible knockout mice lines in rodents has allowed for the detection of 5- HT and 5-HT receptor involvement throughout development and in cell-type specific ways. It may be found that herbal drugs will be effective as the serotonin reuptake inhibitors. Conclusion: This and other future preclinical pharmacology studies show that these receptors' autoreceptor and heteroreceptor populations play different roles in modulating depressionrelated behaviour and antidepressant responses, as well as having different functions during early postnatal development versus adulthood. According to analysis of our research findings, alkaloids may have some therapeutic promise as natural antidepressants. Given their widespread distribution in nature, alkaloids might be a cheap way to treat depression.

Common polygenic variation in the early medication change (EMC) cohort affects disorder risk, but not the antidepressant treatment response

BackgroundGiven the great interest in identifying reliable predictors of the response to antidepressant drugs, the present study investigated whether polygenic scores (PGS) for Major Depressive Disorder (MDD) and antidepressant treatment response (ADR) were related to the complex trait of antidepressant response in the Early Medication Change (EMC) cohort. MethodsIn this secondary analysis of the EMC trial (N = 889), 481 MDD patients were included and compared to controls from a population-based cohort. Patients were treated over eight weeks within a pre-defined treatment-algorithm. We investigated patients' genetic variation associated with MDD and ADR, using PGS and examined the association of PGS with treatment outcomes (early improvement, response, remission). Additionally, the influence of two cytochrome P450 drug-metabolizing enzymes (CYP2C19, CYP2D6) was determined. ResultsPGS for MDD was significantly associated with disorder status (NkR2 = 2.48 %, p < 1*10−12), with higher genetic burden in EMC patients compared to controls. The PGS for ADR did not explain remission status. The PGS for MDD and ADR were also not associated with treatment outcomes. In addition, there were no effects of common CYP450 gene variants on ADR. LimitationsThe study was limited by variability in the outcome parameters due to differences in treatment and insufficient sample size in the used ADR genome-wide association study (GWAS). ConclusionsThe present study confirms a polygenic contribution to MDD burden in the EMC patients. Larger GWAS with homogeneity in antidepressant treatments are needed to explore the genetic variation associated with ADR and realize the potential of PGS to contribute to specific response subtypes.

Genome-wide meta-analyses of non-response to antidepressants identify novel loci and potential drugs.

Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants. We performed genome-wide association meta-analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified two novel loci associated with non-response to antidepressants and showed significant polygenic prediction in independent samples. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.

Integrative Genetic Variation, DNA Methylation, and Gene Expression Analysis of Escitalopram and Aripiprazole Treatment Outcomes in Depression: A CAN-BIND-1 Study.

Little is known about the interplay between genetics and epigenetics on antidepressant treatment (1) response and remission, (2) side effects, and (3) serum levels. This study explored the relationship among single nucleotide polymorphisms (SNPs), DNA methylation (DNAm), and mRNA levels of four pharmacokinetic genes, CYP2C19, CYP2D6, CYP3A4, and ABCB1, and its effect on these outcomes. The Canadian Biomarker Integration Network for Depression-1 dataset consisted of 177 individuals with major depressive disorder treated for 8 weeks with escitalopram (ESC) followed by 8 weeks with ESC monotherapy or augmentation with aripiprazole. DNAm quantitative trait loci (mQTL), identified by SNP-CpG associations between 20 SNPs and 60 CpG sites in whole blood, were tested for associations with our outcomes, followed by causal inference tests (CITs) to identify methylation-mediated genetic effects. Eleven cis-SNP-CpG pairs (q<0.05) constituting four unique SNPs were identified. Although no significant associations were observed between mQTLs and response/remission, CYP2C19 rs4244285 was associated with treatment-related weight gain (q=0.027) and serum concentrations of ESCadj (q<0.001). Between weeks 2-4, 6.7% and 14.9% of those with *1/*1 (normal metabolizers) and *1/*2 (intermediate metabolizers) genotypes, respectively, reported ≥2 lbs of weight gain. In contrast, the *2/*2 genotype (poor metabolizers) did not report weight gain during this period and demonstrated the highest ESCadj concentrations. CITs did not indicate that these effects were epigenetically mediated. These results elucidate functional mechanisms underlying the established associations between CYP2C19 rs4244285 and ESC pharmacokinetics. This mQTL SNP as a marker for antidepressant-related weight gain needs to be further explored.

Early-treatment cerebral blood flow change as a predictive biomarker of antidepressant treatment response: evidence from the EMBARC clinical trial.

Major depressive disorder (MDD) is one of the most prevalent and disabling illnesses worldwide. Treatment of MDD typically relies on trial-and-error to find an effective approach. Identifying early response-related biomarkers that predict response to antidepressants would help clinicians to decide, as early as possible, whether a particular treatment might be suitable for a given patient. Data were from the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial. A whole-brain, voxel-wise, mixed-effects model was applied to identify early-treatment cerebral blood flow (CBF) changes as biomarkers of treatment response. We examined changes in CBF measured with arterial spin labeling 1-week after initiating double-masked sertraline/placebo. We tested whether these early 1-week scans could be used to predict response observed after 8-weeks of treatment. Response to 8-week placebo treatment was associated with increased cerebral perfusion in temporal cortex and reduced cerebral perfusion in postcentral region captured at 1-week of treatment. Additionally, CBF response in these brain regions was significantly correlated with improvement in Hamilton Depression Rating Scale score in the placebo group. No significant associations were found for selective serotonin reuptake inhibitor treatment. We conclude that early CBF responses to placebo administration in multiple brain regions represent candidate neural biomarkers of longer-term antidepressant effects.

Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

BackgroundPatients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories. MethodsA total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response. ResultsBrain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles. ConclusionsConsistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function.

Serum brain-derived neurotrophic factor, Val66Met polymorphism and open-label SSRI treatment response in Major Depressive Disorder

BackgroundBrain-derived neurotrophic factor (BDNF) has been implicated in the therapeutic action of antidepressants and possibly in the pathophysiology of Major Depressive Disorder (MDD). Clinical studies of peripheral blood levels of BDNF in MDD have provided conflicting results, and there are also conflicting reports regarding the predictive value of peripheral BDNF levels for antidepressant treatment response. The present study investigated the association between serum BDNF levels, the BDNF Val66Met polymorphism (rs6265), clinical characteristics and SSRI treatment response. MethodsThis open-label clinical trial included 99 physically healthy, unmedicated MDD participants and 70 healthy controls. Following a baseline assessment, 53 of the MDD participants completed an eight-week, open-label course of SSRI antidepressant treatment. Serum BDNF levels and Hamilton Rating Scale for Depression (HDRS) ratings were examined at baseline and after eight weeks of treatment. Antidepressant response was defined as a decrease in HDRS ratings of > 50% from baseline to the end-of-treatment. Finally, serum BDNF levels and SSRI treatment response were compared between MDD participants who were heterozygous or homozygous for the Met allele (“Met-carriers”) and individuals homozygous for the Val allele. ResultsSerum BDNF levels at baseline were significantly higher in the unmedicated MDD participants compared to healthy controls (15.90 ng/ml vs 13.75 ng/ml, t (167) = −2.041, p = 0.043). In a post-hoc analysis, this difference was seen in the female but not male participants (16.85 ng/ml vs 14.06 ng/ml, t (91) = −2.067, p = 0.042; 14.86 ng/ml vs 13.31 ng/ml, t (74) = −0.923, p = 0.359). Baseline serum BDNF levels were not associated with treatment responder status or with absolute change in depression ratings over the course of 8-week SSRI treatment (p = 0.599). In both Responders and Non-responders, no significant changes in serum BDNF levels were found over the 8-week period of SSRI-treatment (16.32 ng/ml vs 16.23 ng/ml, t (18) = 0.060, p = 0.953; 16.04 ng/ml vs 15.61 ng/ml, t (29) = 0.438, p = 0.665, respectively). Further, no differences were found in serum BDNF levels prior to treatment between MDD Met-carriers and MDD Val/Val homozygotes (15.32 ng/ml vs 16.36 ng/ml, t (85) = 0.747, p = 0.457), and no differences were found in post-treatment serum BDNF (F1,42= 0.031, p = 0.862). However, MDD Val/Val homozygotes showed significantly greater antidepressant responses at week 8 than did MDD Met-carriers (F1,46 = 4.366, p = 0.043). ConclusionOur results do not support sufficient reliability of using peripheral BDNF to characterize depression or to predict antidepressant response in clinical use. The role of sex in moderating BDNF differences in depression, and the role of BDNF gene polymorphisms in predicting antidepressant response, remain to be further investigated. We conclude that, while central nervous system BDNF is likely involved in antidepressant efficacy and in aspects of MDD pathophysiology, its reflection in serum BDNF levels is of limited diagnostic or prognostic utility.

One size does not fit all: notable individual variation in brain activity correlates of antidepressant treatment response.

To date, no robust electroencephalography (EEG) markers of antidepressant treatment response have been identified. Variable findings may arise from the use of group analyses, which neglect individual variation. Using a combination of group and single-participant analyses, we explored individual variability in EEG characteristics of treatment response. Resting-state EEG data and Montgomery-Åsberg Depression Rating Scale (MADRS) symptom scores were collected from 43 patients with depression before, at 1 and 12 weeks of pharmacotherapy. Partial least squares (PLS) was used to: 1) identify group differences in EEG connectivity (weighted phase lag index) and complexity (multiscale entropy) between eventual medication responders and non-responders, and 2) determine whether group patterns could be identified in individual patients. Responders showed decreased alpha and increased beta connectivity, and early, widespread decreases in complexity over treatment. Non-responders showed an opposite connectivity pattern, and later, spatially confined decreases in complexity. Thus, as in previous studies, our group analyses identified significant differences between groups of patients with different treatment outcomes. These group-level EEG characteristics were only identified in ~40-60% of individual patients, as assessed quantitatively by correlating the spatiotemporal brain patterns between groups and individual results, and by independent raters through visualization. Our single-participant analyses suggest that substantial individual variation exists, and needs to be considered when investigating characteristics of antidepressant treatment response for potential clinical applicability. https://clinicaltrials.gov, identifier NCT00519428.

Omega-3 fatty acids for inflamed depression – A match/mismatch study

Despite decades of research on the pathophysiology of depression, the development of new therapeutic interventions has been slow, and no biomarkers of treatment response have been clinically implemented. Several lines of evidence suggest that the clinical and biological heterogeneity among patients with major depressive disorder (MDD) has hampered progress in this field. MDD with low-grade inflammation – “inflamed depression” – is a subtype of depression that may be associated with a superior antidepressant treatment response to anti-inflammatory compounds. Omega-3 fatty acid eicosapentaenoic acid (EPA) has anti-inflammatory properties, and preliminary data suggest that it may be particularly efficacious in inflamed depression. In this study we tested the hypothesis that add-on EPA has greater antidepressant efficacy in MDD patients with high baseline high-sensitivity C-reactive protein (hs-CRP) compared to MDD patients with low hs-CRP. All subjects received 2.2 g EPA, 400 mg docosahexaenoic acid and 800 mg of other fatty acids daily for 8 weeks, added to stable ongoing antidepressant treatment. The primary outcome was change in the 17-item Hamilton Depression Rating Scale (HAMD-17). Patients and raters were blind to baseline hs-CRP status. In an intention-to-treat analysis including all subjects with at least one post baseline visit (n = 101), ahs-CRPcut-off of ≥1 mg/L, but not ≥3 mg/L, was associated with a greater improvement in HAMD-17 total score. In addition to a general antidepressant effect among patients with hs-CRP ≥ 1 mg/L, adjuvant EPA treatment improved symptoms putatively related to inflamed depression such as fatigue and sleep difficulties. This adds to the mounting evidence that delineation of MDD subgroups based on inflammation may be clinically relevant to predict treatment response to anti-inflammatory interventions.

Pharmacogenomic overlap between antidepressant treatment response in major depression & antidepressant associated treatment emergent mania in bipolar disorder

There is increasing interest in individualizing treatment selection for more than 25 regulatory approved treatments for major depressive disorder (MDD). Despite an inconclusive efficacy evidence base, antidepressants (ADs) are prescribed for the depressive phase of bipolar disorder (BD) with oftentimes, an inadequate treatment response and or clinical concern for mood destabilization. This study explored the relationship between antidepressant response in MDD and antidepressant-associated treatment emergent mania (TEM) in BD. We conducted a genome-wide association study (GWAS) and polygenic score analysis of TEM and tested its association in a subset of BD-type I patients treated with SSRIs or SNRIs. Our results did not identify any genome-wide significant variants although, we found that a higher polygenic score (PGS) for antidepressant response in MDD was associated with higher odds of TEM in BD. Future studies with larger transdiagnostic depressed cohorts treated with antidepressants are encouraged to identify a neurobiological mechanism associated with a spectrum of depression improvement from response to emergent mania.

Gustavo Turecki: Three fundamental questions – How does the brain respond to social and emotional experiences? Why does psychological trauma trigger depressive states? What are the mechanisms of antidepressant responses?

Gustavo Turecki MD PhD FRSC is a clinician scientist whose work focuses on understanding brain molecular changes that occur in major depressive disorder and suicide, as well as molecular processes that explain antidepressant treatment response. Dr. Turecki is Full Professor and Chair of the Department of Psychiatry at McGill University, the Scientific Director and Psychiatrist-in-Chief of the Douglas Institute in Montreal, Canada, where he also heads the Depressive Disorders Program. He has authored over 600 publications, including research articles in leading peer-reviewed journals such as Nature Neuroscience, Nature Medicine, and The Lancet and is among the world's most highly cited scientists according to Clarivate, Web of Science. He has received several national and international awards and sits on several advisory boards. Dr. Turecki graciously offers our audience a glimpse into his personal and professional journey.

Personality traits predict treatment outcome of an antidepressant in untreated adolescents with depression: An 8-week, open-label, flexible-dose study

BackgroundAntidepressant response in adults with major depressive disorder (MDD) is probably influenced by personality dimensions. However, personality dimensions in depression and their association with antidepressant treatment in adolescents are relatively unknown. We sought to investigate whether personality traits (PTs) can influence antidepressant treatment response in adolescents with depression. MethodsEighty-two adolescents with MDD who had completed the 8 weeks of treatment with selective serotonin reuptake inhibitors (SSRI) were enrolled. The Revised NEO Five-Factor Inventory (NEO-FFI-R) was used to measure their personality at baseline, and the 17-item Hamilton Depression Rating Scale (HAMD-17) and Children's Depression Rating Scale-Revised (CDRS-R) were used to evaluate depressive symptoms at baseline and 8 weeks. Moreover, logistic regression was performed to investigate the relationship between personality dimensions and antidepressant response. Receiver operating characteristic analyses were employed to determine the accuracy of a PT-based model in predicting the antidepressant response rate. ResultsAdolescents with MDD had significantly different PTs at baseline. Multivariable logistic regression analysis showed that extroversion scores were associated with response to antidepressant treatment, the lower the extroversion score, the better the response to antidepressant treatment, after correcting for variables with significant differences and trends or all potential confounding variables. It was also found that the combination of disease duration, extraversion-gregariousness, and agreeableness-trust effectively predicted antidepressant response in adolescents with MDD, with a sensitivity of 79.4 % and specificity of 68.7 %. ConclusionPersonality dysfunction in adolescents is associated with MDD. The antidepressant treatment response is influenced by the degree of extroversion in adolescents with MDD.