Differential change on depressive symptom factors with antidepressant medication and cognitive behavior therapy for major depressive disorder

Breakthroughs and challenges for generating brain network-based biomarkers of treatment response in depression

Treatment outcomes widely vary for individuals diagnosed with major depressive disorder, implicating a need for deeper understanding of the biological mechanisms conferring a greater likelihood of response to a particular treatment. Our improved understanding of intrinsic brain networks underlying depression psychopathology via magnetic resonance imaging and other neuroimaging modalities has helped reveal novel and potentially clinically meaningful biological markers of response. And while we have made considerable progress in identifying such biomarkers over the last decade, particularly with larger, multisite trials, there are significant methodological and practical obstacles that need to be overcome to translate these markers into the clinic. The aim of this review is to review current literature on brain network structural and functional biomarkers of treatment response or selection in depression, with a specific focus on recent large, multisite trials reporting predictive accuracy of candidate biomarkers. Regarding pharmaco- and psychotherapy, we discuss candidate biomarkers, reporting that while we have identified candidate biomarkers of response to a single intervention, we need more trials that distinguish biomarkers between first-line treatments. Further, we discuss the ways prognostic neuroimaging may help to improve treatment outcomes to neuromodulation-based therapies, such as transcranial magnetic stimulation and deep brain stimulation. Lastly, we highlight obstacles and technical developments that may help to address the knowledge gaps in this area of research. Ultimately, integrating neuroimaging-derived biomarkers into clinical practice holds promise for enhancing treatment outcomes and advancing precision psychiatry strategies for depression management. By elucidating the neural predictors of treatment response and selection, we can move towards more individualized and effective depression interventions, ultimately improving patient outcomes and quality of life.

Altered gamma oscillations and beta-gamma coupling in drug-naive first-episode major depressive disorder: Association with sleep and cognitive disturbance

OBJECTIVE

Gamma oscillations contribute to the pathogenesis mechanisms of major depressive disorder (MDD) have been proposed, but gamma activity is not well characterized. This study is the first attempt to investigate the altered gamma oscillations in first-episode MDD, particularly the beta-gamma coupling, and to determine the potential symptomatic relationship with the identified gamma dysregulation.

METHODS

Resting electroencephalography was recorded for 43 drug-naive first-episode MDD and 57 healthy control (HC) subjects. Integrated analysis of relative spectral power, weighted phase lag index, and phase-amplitude coupling (PAC) were utilized to reveal the alterations of gamma activities. Pearson's correlation was implemented to identify the relationship between altered gamma activities and the clinical depressive symptoms, which were categorized into four factors: anxiety somatization, retardation, cognitive disturbance, and sleep disturbance.

RESULTS

Compared with HC subjects, MDD patients showed not only significantly decreased gamma powers in the left temporal and the bilateral occipital regions but also weakened gamma connectivity between the left hemisphere and the right frontal region. Furthermore, attenuated beta-gamma PAC of MDD patients was observed in the left temporal regions. Importantly, the suppression of left occipital mid- and high gamma oscillations were negatively correlated with sleep disturbance, while the deficits in left temporal beta-mid-gamma PAC and beta-high gamma PAC showed negative correlations with cognitive disturbance.

LIMITATIONS

Important limitations are the small sample size and the possible inclusion of bipolar depression in the MDD group.

CONCLUSIONS

Our findings provide the first evidence that in first-episode MDD, aberrant gamma powers and beta-gamma coupling are associated with sleep and cognitive impairments, respectively, deepening our understanding of the physiological mechanisms underlying sleep and cognitive symptoms in first-episode MDD. Altered gamma oscillations emerge as promising biomarkers for diagnosing MDD.

Changes in depression domains as predictors of return to work in common mental disorders

BACKGROUND

Depression highly impairs function and reduces quality of life. Therefore, both symptomatic and functional recovery are important treatment goals. Depression consists of several cognitive, somatic, and affective symptom factors that differently affect function. However, it is unclear whether changes in these domains predict return to work (RTW) after treatment.

METHODS

Data were collected during treatment from patients on full or partial sick leave reporting depression symptoms (N = 300) at an out-patient clinic. Information on work status was assessed pre- and post-treatment and at 6 months follow-up. Multiple logistic regression was used to investigate if residualized changes in symptom factors predicted full RTW, controlling for gender, education level, and age.

RESULTS

Changes (as symptom improvement) in the cognitive, somatic, and affective factor scores each significantly predicted full RTW post-treatment and at follow-up for patients on full and partial sick leave, even after controlling for gender, education level, and age. The change in the somatic factor explained the largest proportion of variance for full work post-treatment in patients on full sick-leave, while change in the cognitive factor explained most unique variance for patients on graded sick leave.

LIMITATIONS

The sample consisted of a majority of women with a relatively high level of education. This study should be replicated in more heterogeneous samples.

CONCLUSION

Changes in depression symptom domains are significant predictors for RTW work post-treatment. The change in the somatic factor explained the largest proportion of variance in patients on full sick leave and thus may particularly influence RTW after treatment.

Depression and inflammation: Correlation between changes in inflammatory markers with antidepressant response and long-term prognosis

Inflammation may correlate with a specific subgroup of depression and differential antidepressant response, but no trial has studied changes of many inflammatory markers over several time points and evaluated symptom-specific antidepressant response and long-term prognosis. We performed secondary analyses among 90 outpatients with moderate-severe depression (71% female, mean age 38 years) treated for 26 weeks with escitalopram or nortriptyline. We measured 27 pro- and anti-inflammatory markers at week 0, 8, 12, and 26 and calculated composite inflammation scores. Three depression rating scales were applied and symptom dimensions of depression calculated. Via Danish nationwide registers, 10 years follow-up were included on psychiatric hospital contacts, indicating relapse. Pearson correlation analyses were performed between baseline inflammatory markers and depressive symptom severity, mixed effects models during the 26-week trial, and Cox regression analyses for the register-based outcomes, adjusted for age, sex, BMI, and smoking. Baseline inflammatory markers correlated with differential severity on specific symptom dimensions but not with overall depression severity. A total of 17 of 27 inflammatory markers decreased significantly during treatment. We found no correlation between baseline nor change in inflammatory markers nor composite inflammation scores with differential treatment response on the MADRS, but small correlations between changes in inflammatory markers and differential response on neurovegetative symptoms. Findings were similar among 59 treatment-naïve patients. Inflammatory markers were not associated with differential risks for 10-year relapse. These findings support the importance of studying specific depressive symptoms to further explore the correlation between inflammation with differential antidepressant response in a subgroup of depression. Clinical Trial Registration number: GENDEP is registered at EudraCT2004-001723-38 (http://eudract.emea.europa.eu) and ISRCTN03693000 (www.controlled-trials.com).

The bi-factor structure of the 17-item Hamilton Depression Rating Scale in persistent major depression; dimensional measurement of outcome

BACKGROUND

The 17-item Hamilton Depression Rating Scale (HDRS17) is used world-wide as an observer-rated measure of depression in randomised controlled trials (RCTs) despite continued uncertainty regarding its factor structure. This study investigated the dimensionality of HDRS17 for patients undergoing treatment in UK mental health settings with moderate to severe persistent major depressive disorder (PMDD).

METHODS

Exploratory Structural Equational Modelling (ESEM) was performed to examine the HDRS17 factor structure for adult PMDD patients with HDRS17 score ≥16. Participants (n = 187) were drawn from a multicentre RCT conducted in UK community mental health settings evaluating the outcomes of a depression service comprising CBT and psychopharmacology within a collaborative care model, against treatment as usual (TAU). The construct stability across a 12-month follow-up was examined through a measurement equivalence/invariance (ME/I) procedure via ESEM.

RESULTS

ESEM showed HDRS17 had a bi-factor structure for PMDD patients (baseline mean (sd) HDRS17 22.6 (5.2); 87% PMDD >1 year) with an overall depression factor and two group factors: vegetative-worry and retardation-agitation, further complicated by negative item loading. This bi-factor structure was stable over 12 months follow up. Analysis of the HDRS6 showed it had a unidimensional structure, with positive item loading also stable over 12 months.

CONCLUSIONS

In this cohort of moderate-severe PMDD the HDRS17 had a bi-factor structure stable across 12 months with negative item loading on domain specific factors, indicating that it may be more appropriate to multidimensional assessment of settled clinical states, with shorter unidimensional subscales such as the HDRS6 used as measures of change.

Concordance between clinician-rated and patient reported outcome measures of depressive symptoms in treatment resistant depression

BACKGROUND

Calls to implement measurement-based care (MBC) in psychiatry are increasing. A recent Cochrane meta-analysis concluded that there is insufficient evidence that routine application of patient reported outcomes (PROs) improves treatment outcomes for common psychiatric disorders. There is a particular paucity of this information in patients with treatment resistant depression (TRD).

METHODS

A TRD sample (n = 302) and a treatment-naïve sample with major depression (n = 344) were assessed for the level of agreement in depression severity between two PROs (the Beck Depression Inventory, BDI, and the Quick Inventory of Depressive Symptomatology Self-report, QIDS-SR) and two Clinician Rated (CRs) measures (Hamilton Depression Rating Scale, HDRS, and the Montgomery-Asberg Depression Rating Scale, MADRS).

RESULTS

Correlations between CR and PRO total scores in the TRD sample ranged from 0.57 (HDRS-QIDS-SR) to 0.68 (MADRS-BDI), reflecting a moderate-to-strong relationship between assessment tools. Correlations in the treatment naïve sample were non-significantly lower for most comparisons, ranging from 0.51 (HDRS-QIDS-SR) to 0.64 (MADRS-BDI). Few predictors of discordance between CRs and PROs were identified, though chronicity of the current episode in treatment-naïve patients was associated with greater agreement.

LIMITATIONS

Inter-rater reliability of the clinician interviews was conducted separately within the two studies so we could not determine the reliability between the two groups of raters used in the studies.

CONCLUSION

Findings generally supported acceptably high levels of agreement between patient and clinician ratings of baseline depression severity. More work is needed to determine the extent to which PROs can improve outcomes in MBC for depression and, more specifically, TRD.

Suicidal ideation and other persisting symptoms after CBT or antidepressant medication treatment for major depressive disorder

BACKGROUND

Persisting symptoms after treatment for major depressive disorder (MDD) contribute to ongoing impairment and relapse risk. Whether cognitive behavior therapy (CBT) or antidepressant medications result in different profiles of residual symptoms after treatment is largely unknown.

METHODS

Three hundred fifteen adults with MDD randomized to treatment with either CBT or antidepressant medication in the Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study were analyzed for the frequency of residual symptoms using the Montgomery Asberg Depression Rating Scale (MADRS) item scores at the end of the 12-week treatment period. Separate comparisons were made for treatment responders and non-responders.

RESULTS

Among treatment completers (n = 250) who responded to CBT or antidepressant medication, there were no significant differences in the persistence of residual MADRS symptoms. However, non-responders treated with medication were significantly less likely to endorse suicidal ideation (SI) at week 12 compared with those treated with CBT (non-responders to medication: 0/54, 0%, non-responders to CBT: 8/30, 26.7%; p = .001). Among patients who terminated the trial early (n = 65), residual MADRS item scores did not significantly differ between the CBT- and medication-treated groups.

CONCLUSIONS

Depressed adults who respond to CBT or antidepressant medication have similar residual symptom profiles. Antidepressant medications reduce SI, even among patients for whom the medication provides little overall benefit.

The symptom-specific efficacy of antidepressant medication vs. cognitive behavioral therapy in the treatment of depression: results from an individual patient data meta-analysis

A recent individual patient data meta-analysis showed that antidepressant medication is slightly more efficacious than cognitive behavioral therapy (CBT) in reducing overall depression severity in patients with a DSM-defined depressive disorder. We used an update of that dataset, based on seventeen randomized clinical trials, to examine the comparative efficacy of antidepressant medication vs. CBT in more detail by focusing on individual depressive symptoms as assessed with the 17-item Hamilton Rating Scale for Depression. Five symptoms (i.e., "depressed mood" , "feelings of guilt" , "suicidal thoughts" , "psychic anxiety" and "general somatic symptoms") showed larger improvements in the medication compared to the CBT condition (effect sizes ranging from .13 to .16), whereas no differences were found for the twelve other symptoms. In addition, network estimation techniques revealed that all effects, except that on "depressed mood" , were direct and could not be explained by any of the other direct or indirect treatment effects. Exploratory analyses showed that information about the symptom-specific efficacy could help in identifying those patients who, based on their pre-treatment symptomatology, are likely to benefit more from antidepressant medication than from CBT (effect size of .30) versus those for whom both treatments are likely to be equally efficacious. Overall, our symptom-oriented approach results in a more thorough evaluation of the efficacy of antidepressant medication over CBT and shows potential in "precision psychiatry" .