Antidepressant Response Research Articles

Anhedonia is associated with a specific depression profile and poor antidepressant response

Abstract Background Anhedonic features within major depressive disorder (MDD) have been associated with worse course and outcome and may predict non-response to treatment. However a detailed clinical profile of anhedonia in MDD is still lacking. Materials and Methods One thousand two hundred ninety-four patients with MDD were selected from the cross-sectional European multicenter Group for the Study of Resistant Depression (GSRD) study. Anhedonia was assessed through the Montgomery-Åsberg Depression Rating Scale anhedonia item “inability to feel”. Clinical and demographic features were then analyzed. Results The presence of anhedonia related to a distinct demographical (living alone) and clinical profile (thyroid diseases, diabetes, suicide risk, high number of previous depressive episodes, more severe MDD and more frequent inpatients status). Furthermore, anhedonia was associated with non-response to treatment and treatment resistance, even after adjusting for confounding variables. Conclusion Our findings support the role of anhedonia as a modulating feature of MDD, being associated with a more severe depression profile. Moreover, anhedonic features are independent predictors of poor treatment response.

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.

Efficacy and safety of low-frequency repetitive transcranial magnetic stimulation in adolescents with first-episode major depressive disorder: A randomized, double-blind, sham-controlled pilot trial

BackgroundA few sham-controlled studies have examined the efficacy, safety, and tolerability of low-frequency repetitive transcranial magnetic stimulation (LF-rTMS) in adolescents with first-episode major depressive disorder (FE-MDD). MethodsForty adolescents (aged 13–17 years) with FE-MDD were randomly assigned to receive active rTMS (n = 20) or sham rTMS (n = 20) for 10 sessions over two weeks. The severity of baseline depressive symptoms and their improvement on the day immediately after the second, fourth, sixth, eighth, and tenth sessions were assessed with the 17-item Hamilton Depression Rating Scale (HAMD-17). Results: After completing 10 rTMS treatment sessions, there was no significant difference in antidepressant response (70.0 % vs. 60.0 %, p > 0.05) and antidepressant remission (55.0 % vs. 35.0 %, p > 0.05) between rTMS groups. The linear mixed model analysis did not show a significant group-by-time interaction (F = 1.26; p > 0.05) in the HAMD-17 scores. There was a significant time main effect on the speed of processing (F = 13.61; p < 0.05), but this did not differ significantly between groups (p > 0.05). There were no other main effects and group-by-time interactions in the other MATRICS Consensus Cognitive Battery domains (all p > 0.05). All adverse event categories, such as fatigue and headache, were similar in the two groups (all p > 0.05). ConclusionsIn this study that compared a combination of LF-rTMS + medication with sham + medication, LF-rTMS had higher response and remission rates than a sham procedure in adolescents with FE-MDD, but the change was not statistically significant. LF-rTMS is generally safe, with mild adverse effects and no negative impact on neurocognitive performance for adolescents with FE-MDD. Registration numberChiCTR2000037878.

Meta-analysis on QEEG Changes to Antidepressant Treatment Among Patients with Depression

Introduction: Diagnostic and treatment accuracy of depression can lead to a better and possibly earlier response and remission in patients. The literature, though scanty, seems to suggest that quantitative electroencephalography (QEEG) can predict the outcome of antidepressant effects. Methodology: Articles published between January 1990 and July 2019, including those dealing with QEEG recordings before and after the initiation of antidepressant medication, were included. The pooled effect size and subgroup analysis of waveforms were calculated to predict response to antidepressants. Result: In all, 572 results were retrieved from the searches, of which 20 studies were included. Pooled data using a random-effects model (REM) calculated an effect size of 0.80 (95% CI [0.64–0.97]). Heterogeneity of the sample was low with Tau² = 0.02; df = 18 ( P = .30); I² = 12%. Moreover, subgroup analysis showed that theta band frequencies were better at predicting response than alpha band frequencies (the standard mean difference [SMD] for theta was 0.91 compared to 0.68 for alpha waves). Conclusions: QEEG is a valuable predictor of the antidepressant response. Among the EEG frequencies, the theta band showed the most significant change with treatment.

Molecular signature underlying (R)-ketamine rapid antidepressant response on anhedonic-like behavior induced by sustained exposure to stress

Anhedonia induced by sustained stress exposure is a hallmark symptom of major depressive disorder (MDD) and in rodents, it can be accessed through the sucrose preference test (SPT). (R)-ketamine is a fast-acting antidepressant with less detrimental side effects and abuse liability compared to racemic ketamine. The present study combined high-throughput proteomics and network analysis to identify molecular mechanisms involved in chronic variable stress (CVS)-induced anhedonia and promising targets underlying (R)-ketamine rapid antidepressant response. Male Wistar rats were subjected to CVS for five weeks. Based on the SPT, animals were clustered into resilient or anhedonic-like (ANH) groups. ANH rats received a single dose of saline or (R)-ketamine (20 mg/kg, i.p.), which was proceeded by treatment response evaluation. After prefrontal cortex collection, proteomic analysis was performed to uncover the differentially expressed proteins (DEPs) related to both anhedonic-like behavior and pharmacological response. The behavioral assessment showed that the ANH animals had a significant decrease in SPT, and that (R)-ketamine responders showed a reversal of anhedonic-like behavior. On a molecular level, anhedonia-like behavior was associated with the downregulation of Neuronal Pentraxin Receptor (Nptxr) and Galectin−1 (Gal-1). These data reinforce a disruption in the inflammatory response, neurotransmitter receptor activity, and glutamatergic synapses in chronic stress-induced anhedonia. (R)-ketamine response-associated DEPs included novel potential targets involved in the modulation of oxidative stress, energetic metabolism, synaptogenesis, dendritic arborization, neuroinflammation, gene expression, and telomere length, converging to biological themes extensively documented in MDD physiopathology. Our data provide valuable insights into the molecular mechanisms underlying the response to (R)-ketamine and highlight these pathways as potential therapeutic targets for anhedonia. By addressing proteins involved in oxidative stress, energy metabolism, synaptogenesis, dendritic arborization, neuroinflammation, gene expression, and telomere length, we can target multiple key factors involved in the pathophysiology of MDD. Modulating these proteins could open avenues for novel therapeutic strategies and deepen our understanding of anhedonia, offering hope for improved outcomes in individuals facing this challenging condition. However, additional studies will be essential to validate these findings and further explore their therapeutic implications.

Interplay between Stressful Life Events and Interleukin-1β on 12-week Antidepressant Response in Depressive Patients

Interplay between Stressful Life Events and Interleukin-1β on 12-week Antidepressant Response in Depressive Patients

The impact of voluntary wheel-running exercise on hippocampal neurogenesis and behaviours in response to nicotine cessation in rats.

The literature indicates that nicotine exposure or its discontinuation impair adult hippocampal neurogenesis in rats, though the impact of exercise on this process remains unclear. We have previously shown that disturbances in the number of doublecortin (DCX, a marker of immature neurons)-positive (DCX+) cells in the dentate gyrus (DG) of the hippocampus during nicotine deprivation may contribute to a depression-like state in rats. This study aimed to investigate the effect of running on hippocampal neurogenesis, depression-like symptoms, and drug-seeking behaviour during nicotine deprivation. The rats were subjected to nicotine (0.03mg/kg/inf) self-administration via an increasing schedule of reinforcement. After 21 sessions, the animals entered a 14-day abstinence phase during which they were housed in either standard home cages without wheels, cages equipped with running wheels, or cages with locked wheels. Wheel running increased the number of Ki-67+ and DCX+ cells in the DG of both nicotine-deprived and nicotine-naive rats. Wheel-running exercise evoked an antidepressant effect on abstinence Day 14 but had no effect on nicotine-seeking behaviour on abstinence Day 15 compared to rats with locked-wheel access. In summary, long-term wheel running positively affected the number of immature neurons in the hippocampus, which corresponded with an antidepressant response in nicotine-weaned rats. One possible mechanism underlying the positive effect of running on the affective state during nicotine cessation may be the reduction in deficits in DCX+ cells in the hippocampus.

Immediate effects of propofol on mood: a randomized comparison of two doses in a cohort with depression.

The intravenous anesthetic propofol is known to induce positive mood effects during routine clinical use, suggesting it might be repurposed as an antidepressant, but also raising concerns about abuse potential. How propofol's acute effects vary by dose and with repeated infusions is unknown. This exploratory analysis aimed to (1) compare the immediate mood effects of propofol administered at two different doses, (2) describe how those mood effects change with repeated infusions, and (3) evaluate whether acute mood improvement predicts later antidepressant response. Twenty-four adults with moderate-to-severe treatment-resistant depression were randomized into two dosing groups. Six low- or high-dose propofol infusions were administered under blinded conditions over a two-week period. Self-reported mood states were recorded before and after each infusion using the Positive and Negative Affect Schedule (PANAS-X). Abuse potential was evaluated with the Drug Effects Questionnaire (DEQ-5). At the first infusion, propofol induced acute improvements in PANAS-X Sadness, Fear, Joviality, and Serenity scales (p < 0.002), independent of dose. Over the series of six infusions, acute changes in Sadness, Fear, and Joviality, but not Serenity, diminished with infusion number (p < 0.002). The DEQ-5 "want more" rating decreased across infusions (p = 0.002). Changes in PANAS-X scales with the first infusion did not predict later improvement in depression severity (p > 0.05). Cumulative changes in mood states observed with repeated infusions suggest that propofolengages adaptive mechanisms in mood circuitry. Subjective responses with repeated infusions do not indicate increasing potential for abuse in this patient population.

Morphological correlates of anxiety-related experiences during a ketamine infusion

Objectives: Ketamine exerts rapid antidepressant effects by enhancing neuroplasticity, particularly in the amygdala and hippocampus—regions involved in fear processing and learning. While the role of ketamine’s dissociative effects in its antidepressant response is debated, anxiety experienced during infusion has been negatively correlated with treatment outcomes. Methods: In this single-blind, placebo-controlled study, a subset of 17 healthy volunteers (6 males, 23.12 ± 1.9 years) received intravenously a placebo in the first and 0.5 mg/kg racemic ketamine in the second session. Anxiety-related experiences were assessed by the 5D-ASC score obtained post-infusion, structural magnetic resonance imaging scans were acquired 4 h post-infusion. An anxiety-score was obtained from the 5D-ASC. Relation between post-placebo amygdala volume, hippocampal volume, and its subfields with the anxiety-score were assessed using linear regression models. Results: Results showed a statistically significant negative relation between hippocampal head volume and the anxiety score (β = −0.733, p = 0.006), with trending negative association for each subfield’s head and the score. Conclusion: These findings suggest that anxiety-related experiences during ketamine infusion may be mediated by the hippocampus, with smaller hippocampal volumes leading to more anxiety-related experiences. Thus, hippocampal subfield volumes may be used as a predictor for anxiety-related events during ketamine use and might predict treatment outcome in future approaches.

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.

Effects of ketamine on GABAergic and glutamatergic activity in the mPFC: biphasic recruitment of GABA function in antidepressant-like responses.

Major depressive disorder (MDD) is associated with disruptions in glutamatergic and GABAergic activity in the medial prefrontal cortex (mPFC), leading to altered synaptic formation and function. Low doses of ketamine rapidly rescue these deficits, inducing fast and sustained antidepressant effects. While it is suggested that ketamine produces a rapid glutamatergic enhancement in the mPFC, the temporal dynamics and the involvement of GABA interneurons in its sustained effects remain unclear. Using simultaneous photometry recordings of calcium activity in mPFC pyramidal and GABA neurons, as well as chemogenetic approaches in Gad1-Cre mice, we explored the hypothesis that initial effects of ketamine on glutamate signaling trigger subsequent enhancement of GABAergic responses, contributing to its sustained antidepressant responses. Calcium recordings revealed a biphasic effect of ketamine on activity of mPFC GABA neurons, characterized by an initial transient decrease (phase 1, <30 min) followed by an increase (phase 2, >60 min), in parallel with a transient increase in excitation/inhibition levels (10 min) and lasting enhancement of glutamatergic activity (30-120 min). Previous administration of ketamine enhanced GABA neuron activity during the sucrose splash test (SUST) and novelty suppressed feeding test (NSFT), 24 h and 72 h post-treatment, respectively. Chemogenetic inhibition of GABA interneurons during the surge of GABAergic activity (phase 2), or immediately before the SUST or NSFT, occluded ketamine's behavioral actions. These results indicate that time-dependent modulation of GABAergic activity is required for the sustained antidepressant-like responses induced by ketamine, suggesting that approaches to enhance GABAergic plasticity and function are promising therapeutic targets for antidepressant development.

Optimizing Antidepressant Efficacy: Generalizable Multimodal Neuroimaging Biomarkers for Prediction of Treatment Response.

Major depressive disorder (MDD) is a common and often severe condition that profoundly diminishes quality of life for individuals across ages and demographic groups. Unfortunately, current antidepressant and psychotherapeutic treatments exhibit limited efficacy and unsatisfactory response rates in a substantial number of patients. The development of effective therapies for MDD is hindered by the insufficiently understood heterogeneity within the disorder and its elusive underlying mechanisms. To address these challenges, we present a target-oriented multimodal fusion framework that robustly predicts antidepressant response by integrating structural and functional connectivity data (sertraline: R-squared = 0.31; placebo: R-squared = 0.22). Remarkably, the sertraline response biomarker is further tested on an independent escitalopram-medicated cohort of MDD patients, validating its generalizability (p = 0.01) and suggesting an overlap of psychopharmacological mechanisms across selective serotonin reuptake inhibitors. Through the model, we identify multimodal neuroimaging biomarkers of antidepressant response and observe that sertraline and placebo show distinct predictive patterns. We further decompose the overall predictive patterns into constitutive network constellations with generalizable structural-functional co-variation, which exhibit treatment-specific association with personality traits and behavioral/cognitive task performance. Our innovative and interpretable multimodal framework provides novel and reliable insights into the intricate neuropsychopharmacology of antidepressant treatment, paving the way for advances in precision medicine and development of more targeted antidepressant therapeutics.

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 non-response rates are high. Recent years have seen an increase in research into predictive biomarkers towards 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 so far largest sample 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 six-week antidepressant treatment in a naturalistic in-patient setting as well as in a subsample of N=107 patients primarily receiving continuous treatment with SSRIs or SNRIs. Treatment response was assessed by means of the Hamilton Depression Scale (HAM-D). No genome-wide significant hits were observed. Suggestive (p<1E-5) epigenome-wide evidence was discerned for altered DNA methylation at six CpG sites (LOC102724467, LOC100506023, RSPO2, SAG, IL16, PRKCI) to predict response to naturalistic antidepressant treatment. In patients treated with SSRIs or SNRIs, differential DNA methylation at 11 CpGs, e.g. 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 towards 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.

Impact of baseline body mass index on antidepressant response: A study in newly diagnosed patients at a tertiary care center in Kolkata

Background: Depression, affecting 350 million globally, poses significant morbidity and mortality. The correlation between major depressive disorder (MDD) and obesity is noted, with studies indicating poorer treatment outcomes among obese individuals. Measuring weight and body mass index (BMI) could aid in predicting depression treatment outcomes, influencing drug efficacy due to their ease of measurement, amid the shared public health burden of MDD and obesity. Aims and Objectives: The aims and objectives of the study are to evaluate baseline BMI’s impact on antidepressant response in newly diagnosed outpatient department (OPD) patients at a tertiary care center. Materials and Methods: This longitudinal observational study was conducted with OPD patients at a tertiary care center, aged 18–65 years with newly diagnosed MDD. Assessment tools included the Diagnostic Criteria for Research accompanying the ICD-10, the Hamilton Rating Scale for Depression, and physical measurement devices. Sample size determination considered BMI groups: Normal to underweight (N1=120), overweight (N2=120), and obese (N3=70). The methodology involved patient history, examination, and follow-up assessments after 6 weeks, analyzing antidepressant response statistically. Results: Obese patients exhibited reduced treatment response rates compared to normal and overweight counterparts. Responders had lower mean BMI. Gender disparities in obesity prevalence were noted. Limitations: The study’s limitations include a small sample size of 310 cases, single-center design, and potential selection bias in a tertiary care setting. Conclusion: The findings underscore the complex relationship between BMI, depression severity, and treatment response. Obese individuals demonstrated higher initial depression scores and poorer treatment response, echoing previous research. The study highlights the need for personalized treatment approaches that consider individual BMI levels to optimize depression management strategies effectively.

Contribution of resting-state functional connectivity of the subgenual anterior cingulate to prediction of antidepressant efficacy in patients with major depressive disorder

This study investigated how resting-state functional connectivity (rsFC) of the subgenual anterior cingulate cortex (sgACC) predicts antidepressant response in patients with major depressive disorder (MDD). Eighty-seven medication-free MDD patients underwent baseline resting-state functional MRI scans. After 12 weeks of escitalopram treatment, patients were classified into remission depression (RD, n = 42) and nonremission depression (NRD, n = 45) groups. We conducted two analyses: a voxel-wise rsFC analysis using sgACC as a seed to identify group differences, and a prediction model based on the sgACC rsFC map to predict treatment efficacy. Haufe transformation was used to interpret the predictive rsFC features. The RD group showed significantly higher rsFC between the sgACC and regions in the fronto-parietal network (FPN), including the bilateral dorsolateral prefrontal cortex (DLPFC) and bilateral inferior parietal lobule (IPL), compared to the NRD group. These sgACC rsFC measures correlated positively with symptom improvement. Baseline sgACC rsFC also significantly predicted treatment response after 12 weeks, with a mean accuracy of 72.64% (p < 0.001), mean area under the curve of 0.74 (p < 0.001), mean specificity of 0.82, and mean sensitivity of 0.70 in 10-fold cross-validation. The predictive voxels were mainly within the FPN. The rsFC between the sgACC and FPN is a valuable predictor of antidepressant response in MDD patients. These findings enhance our understanding of the neurobiological mechanisms underlying treatment response and could help inform personalized treatment strategies for MDD.

Mirtazapine blood levels and antidepressant response

Objective Therapeutic drug monitoring (TDM) is an important tool for treatment optimisation. Its usefulness has recently been demonstrated for some first-line antidepressants; however, few studies have been reported on the relationship between blood levels of mirtazapine and its antidepressant effects. The aim of this study was to investigate the association between blood concentration of mirtazapine and antidepressant response. Methods 59 outpatients treated with mirtazapine for depression were recruited and followed up for three months in a naturalistic setting. Hamilton Depression Rating Scale-21 (HAMD-21) was administered at baseline, month 1, and month 3 to assess antidepressant response. Mirtazapine serum concentration was measured at steady state. Linear regression analysis and nonlinear least-squares regression were used to estimate association between serum concentration of mirtazapine and antidepressant response. Results Our results showed no overall association between serum concentration of mirtazapine and symptom improvement at month 1 and month 3. A marginally significantly higher serum concentration of mirtazapine was found in responders vs non-responders at month 3. Conclusions The study suggests that serum concentration of mirtazapine is not strongly associated with the antidepressant efficacy of mirtazapine. This is probably attributed to its pharmacodynamic profile, even though higher blood levels seem to be marginally more effective.

Are BDNF and Stress Levels Related to Antidepressant Response?

A total of 40 depressed adults were included. We evaluated initial serum BDNF, anxiety through the State-Trait Anxiety Inventory (STAI), and the severity of depressive symptoms by the Hamilton Depression Rating Scale (HDRS). Participants received antidepressant treatment for 8 weeks, and response to treatment was evaluated according to the final HDRS scores. Basal BDNF was higher in responders compared to non-responder depressed patients, in addition to being inversely associated with the severity of anxiety and depression. Baseline BDNF serum is an adequate predictive factor for response to antidepressant treatment with SSRI, with lower pre-treatment levels of BDNF associated with higher anxiety symptoms after treatment. Stress levels could influence the response to treatment, but its association was not conclusive.

Opioids Diminish the Placebo Antidepressant Response: A Post Hoc Analysis of a Randomized Controlled Ketamine Trial.

The endogenous opioid system is thought to play a role in the placebo antidepressant response. A recent trial comparing the rapid antidepressant effects of ketamine versus placebo in surgical patients, some of whom were on chronic opioid therapy, revealed a substantial placebo effect. This finding provided an opportunity to test the hypothesis that opioid agonist exposure interacts with placebo antidepressant responses. This post hoc analysis utilized data from a previously reported randomized, anesthesia-blinded, placebo-controlled trial of intravenous ketamine in depressed patients undergoing routine surgery. Mixed-effects models were used to determine whether baseline opioid use influenced antidepressant responses to the trial interventions, as measured by the Montgomery-Åsberg Depression Rating Scale (MADRS) over 1 to 14 days post-treatment. The analysis showed that baseline opioid use significantly reduced post-treatment depression severity in patients who received placebo, but not in those who received ketamine. This reduction was independent of baseline depression severity, baseline pain intensity, and ethnicity. Additionally, there was negligible correlation between postoperative pain intensity and depression severity. This analysis was unregistered and conducted on a small sample; the findings need to be confirmed by prospective controlled studies. Opioid use at baseline attenuated the placebo antidepressant response independently of pain in depressed patients who received the study treatment under general anesthesia for routine surgery. The antidepressant response was preserved in opioid users who received intravenous ketamine.

Effect of sleep quality on repetitive transcranial magnetic stimulation outcomes in depression.

While repetitive transcranial magnetic stimulation (rTMS) is effective for 50-60% of those treatment-resistant depression, it is critical to identify predictors of response for optimal patient selection to improve therapy. Insomnia is a known symptom of depression that is both correlated with depression severity and associated with poor antidepressant response. Therefore, understanding this relationship may open new opportunities for the optimization of rTMS treatment. We aimed to explore whether baseline sleep quality, specifically insomnia, is associated with rTMS outcomes in a naturalistic sample of 975 patients (age 18-90; 63.9% F) receiving a standard course of rTMS treatment from two outpatient TMS clinics located within psychiatric hospitals in the United States. One site additionally collected information on concurrent medication use on 350 patients; among these, we examined whether pharmacological treatment of insomnia affected TMS treatment response. Depression was measured using the 30-item Inventory of Depressive Symptomology Self Report (IDS-SR) in site one and an abbreviated 16-item Quick Inventory of Depressive Symptomology (QIDS) derived from the IDS-SR in site two. Sleep disturbances were measured using three insomnia-related questions. Multilevel logistic regression was used to determine whether baseline insomnia scores were associated with TMS treatment outcome. Upon dichotomous categorization of the sample by insomnia and sleep-medication use, depression and sleep scores were analyzed across time using mixed repeated measures ANOVA. We found that sleep quality improves after TMS (p<.001) and correlates with improvement in non-insomnia related depression symptoms (r= .318, p<.001). We found that among those who had significant insomnia at baseline, those not using sleep medications had significantly worse post-treatment IDS-SR scores compared to those using sleep medications (p=. 021) despite no difference in final insomnia score. Together, our results suggest that while baseline insomnia is not associated with TMS effectiveness, treating insomnia may affect the trajectory of TMS therapy. Future prospective studies are needed to examine the effect of insomnia treatment alongside TMS for depression.