Effectiveness of Schema Therapy versus Cognitive Behavioral Therapy versus Supportive Therapy for Depression in Inpatient and Day Clinic Settings: A Randomized Clinical Trial.

INTRODUCTION: Schema therapy (ST) reduces depressive symptoms, but clinical trials have not investigated its effectiveness for patients suffering from severe forms of depression and high rates of comorbidities. There is high demand for exploring and improving treatments for this patient group. The objective of the current study was to evaluate whether ST is more effective than individual supportive therapy (IST) and noninferior compared with cognitive behavioral therapy (CBT) in treating depression. METHODS: For this clinical trial, medicated patients were recruited in inpatient and day clinic settings. The major inclusion criteria were age between 18 and 75 years and primary diagnosis of depression without psychotic symptoms. A total of 292 participants were randomized to ST, CBT, or IST and received 7 weeks of psychotherapy (up to 14 individual and 14 group sessions). The primary outcome was change in depression severity after treatment measured by Beck Depression Inventory-II. Primary test for efficacy was superiority of ST over IST. Secondary test was noninferiority of ST compared with CBT. Multilevel modeling was conducted. The results at 6-month follow-up were explored. RESULTS: Across treatment, ST was not superior to IST. Secondary outcome analyses and completer analyses showed similar results. However, ST showed clinically relevant noninferiority compared with CBT. CONCLUSION: ST for depression as part of a psychiatric care program showed clinical noninferiority compared to CBT, without being superior to IST. ST represents a potentially useful addition to the therapeutic repertoire for the treatment of depression but its efficacy, including long-term efficacy, should be evaluated further.

Free-viewing gaze patterns reveal a mood-congruency bias in MDD during an affective fMRI/eye-tracking task.

Major depressive disorder (MDD) has been related to abnormal amygdala activity during emotional face processing. However, a recent large-scale study (n = 28,638) found no such correlation, which is probably due to the low precision of fMRI measurements. To address this issue, we used simultaneous fMRI and eye-tracking measurements during a commonly employed emotional face recognition task. Eye-tracking provide high-precision data, which can be used to enrich and potentially stabilize fMRI readouts. With the behavioral response, we additionally divided the active task period into a task-related and a free-viewing phase to explore the gaze patterns of MDD patients and healthy controls (HC) and compare their respective neural correlates. Our analysis showed that a mood-congruency attentional bias could be detected in MDD compared to healthy controls during the free-viewing phase but without parallel amygdala disruption. Moreover, the neural correlates of gaze patterns reflected more prefrontal fMRI activity in the free-viewing than the task-related phase. Taken together, spontaneous emotional processing in free viewing might lead to a more pronounced mood-congruency bias in MDD, which indicates that combined fMRI with eye-tracking measurement could be beneficial for our understanding of the underlying psychopathology of MDD in different emotional processing phases.Trial Registration: The BeCOME study is registered on ClinicalTrials (gov: NCT03984084) by the Max Planck Institute of Psychiatry in Munich, Germany.

Epigenetic age acceleration as a biomarker for impaired cognitive abilities in adulthood following early life adversity and psychiatric disorders.

Background: Early life adversity and psychiatric disorders are associated with earlier declines in neurocognitive abilities during adulthood. These declines may be preceded by changes in biological aging, specifically epigenetic age acceleration, providing an opportunity to uncover genome-wide biomarkers that identify individuals most likely to benefit from early screening and prevention. Methods: Five unique epigenetic age acceleration clocks derived from peripheral blood were examined in relation to latent variables of general and speeded cognitive abilities across two independent cohorts: 1) the Female Growth and Development Study (FGDS; n = 86), a 30-year prospective cohort study of substantiated child sexual abuse and non-abused controls, and 2) the Biological Classification of Mental Disorders study (BeCOME; n = 313), an adult community cohort established based on psychiatric disorders. Results: A faster pace of biological aging (DunedinPoAm) was associated with lower general cognitive abilities in both cohorts and slower speeded abilities in the BeCOME cohort. Acceleration in the Horvath clock was significantly associated with slower speeded abilities in the BeCOME cohort but not the FGDS. Acceleration in the Hannum clock and the GrimAge clock were not significantly associated with either cognitive ability. Accelerated PhenoAge was associated with slower speeded abilities in the FGDS but not the BeCOME cohort. Conclusions: The present results suggest that epigenetic age acceleration has the potential to serve as a biomarker for neurocognitive decline in adults with a history of early life adversity or psychiatric disorders. Estimates of epigenetic aging may identify adults at risk of cognitive decline that could benefit from early neurocognitive screening.

Data-Driven Pupil Response Profiles as Transdiagnostic Readouts for the Detection of Neurocognitive Functioning in Affective and Anxiety Disorders.

BACKGROUND: Neurocognitive functioning is a relevant transdiagnostic dimension in psychiatry. As pupil size dynamics track cognitive load during a working memory task, we aimed to explore if this parameter allows identification of psychophysiological subtypes in healthy participants and patients with affective and anxiety disorders. METHODS: Our sample consisted of 226 participants who completed the n-back task during simultaneous functional magnetic resonance imaging and pupillometry measurements. We used latent class growth modeling to identify clusters based on pupil size in response to cognitive load. In a second step, these clusters were compared on affective and anxiety symptom levels, performance in neurocognitive tests, and functional magnetic resonance imaging activity. RESULTS: The clustering analysis resulted in two distinct pupil response profiles: one with a stepwise increasing pupil size with increasing cognitive load (reactive group) and one with a constant pupil size across conditions (nonreactive group). A larger increase in pupil size was significantly associated with better performance in neurocognitive tests in executive functioning and sustained attention. Statistical maps of parametric modulation of pupil size during the n-back task showed the frontoparietal network in the positive contrast and the default mode network in the negative contrast. The pupil response profile of the reactive group was associated with more thalamic activity, likely reflecting better arousal upregulation and less deactivation of the limbic system. CONCLUSIONS: Pupil measurements have the potential to serve as a highly sensitive psychophysiological readout for detection of neurocognitive deficits in the core domain of executive functioning, adding to the development of valid transdiagnostic constructs in psychiatry.

Startle Latency as a Potential Marker for Amygdala-Mediated Hyperarousal.

BACKGROUND: Fear-related disorders are characterized by hyperexcitability in reflexive circuits and maladaptive associative learning mechanisms. The startle reflex is suited to investigate both processes, either by probing it under baseline conditions or by deriving it in fear conditioning studies. In anxiety research, the amplitude of the fear-potentiated startle has been shown to be influenced by amygdalar circuits and has typically been the readout of interest. In schizophrenia research, prolonged startle peak latency under neutral conditions is an established readout, thought to reflect impaired processing speed. We therefore explored whether startle latency is an informative readout for human anxiety research. METHODS: We investigated potential similarities and differences of startle peak latency and amplitude derived from a classical fear conditioning task in a sample of 206 participants with varying severity levels of anxiety disorders and healthy control subjects. We first reduced startle response to stable components and regressed individual amygdala gray matter volumes onto the resulting startle measures. We then probed time, stimulus, and group effects of startle latency. RESULTS: We showed that startle latency and startle amplitude were 2 largely uncorrelated measures; startle latency, but not amplitude, showed a sex-specific association with gray matter volume of the amygdala; startle latencies showed a fear-dependent task modulation; and patients with fear-related disorders displayed shorter startle latencies throughout the fear learning task. CONCLUSIONS: These data provide support for the notion that probing startle latencies under threat may engage amygdala-modulated threat processing, making them a complementary marker for human anxiety research.

Psychometric Properties of the German Version of the Young Positive Schema Questionnaire (YPSQ) in the General Population and Psychiatric Patients.

Early adaptive schemas (EAS) are resilience-oriented counterparts to early maladaptive schemas (EMS), which are central in schema therapy. The Young Positive Schema Questionnaire (YPSQ) was developed as a measure of EAS but has been evaluated neither in relation to a clinical population nor in a German-speaking sample. Objectives of this study were therefore the psychometric validation of a German YPSQ in a community sample and the comparison of EAS to psychiatric patients. Participants were 1,418 individuals from a community sample and 182 psychiatric patients with a main diagnosis of major depressive disorder. A factor structure of 10 EAS, instead of the original 14, demonstrated satisfactory factorial validity and internal consistency in both samples. EAS exhibited divergent validity to EMS, childhood trauma, and psychopathology. Convergent validity was evident with resilience, self-efficacy, and satisfaction with life. Support for incremental validity beyond EMS was especially shown for resilience, self-efficacy, and satisfaction with life, and was also evident for several dimensions of psychopathology. Individuals in the community sample exhibited more pronounced EAS compared to psychiatric patients with the exception of empathic consideration. Especially for concepts associated with mental health, the YPSQ has the potential to be a highly valuable addition to current research and practice.

Separating EEG correlates of stress: Cognitive effort, time pressure, and social-evaluative threat.

The prefrontal cortex is a key player in stress response regulation. Electroencephalographic (EEG) responses, such as a decrease in frontal alpha and an increase in frontal beta power, have been proposed to reflect stress-related brain activity. However, the stress response is likely composed of different parts such as cognitive effort, time pressure, and social-evaluative threat, which have not been distinguished in previous studies. This distinction, however, is crucial if we aim to establish reliable tools for early detection of stress-related conditions and monitoring of stress responses throughout treatment. This randomized cross-over study (N = 38) aimed to disentangle EEG correlates of stress. With linear mixed models accounting for missing values in some conditions, we found a decrease in frontal alpha and increase in beta power when performing the Paced Auditory Serial Addition Test (PASAT; cognitive effort; n = 32) compared to resting state (n = 33). No change in EEG power was found when the PASAT was performed under time pressure (n = 29) or when adding social-evaluative threat (video camera; n = 29). These findings suggest that frontal EEG power can discriminate stress from resting state but not more fine-grained differences of the stress response.

Pupillometry tracks cognitive load and salience network activity in a working memory functional magnetic resonance imaging task.

The diameter of the human pupil tracks working memory processing and is associated with activity in the frontoparietal network. At the same time, recent neuroimaging research has linked human pupil fluctuations to activity in the salience network. In this combined functional magnetic resonance imaging (fMRI)/pupillometry study, we recorded the pupil size of healthy human participants while they performed a blockwise organized working memory task (N-back) inside an MRI scanner in order to monitor the pupil fluctuations associated neural activity during working memory processing. We first confirmed that mean pupil size closely followed working memory load. Combining this with fMRI data, we focused on blood oxygen level dependent (BOLD) correlates of mean pupil size modeled onto the task blocks as a parametric modulation. Interrogating this modulated task regressor, we were able to retrieve the frontoparietal network. Next, to fully exploit the within-block dynamics, we divided the blocks into 1 s time bins and filled these with corresponding pupil change values (first-order derivative of pupil size). We found that pupil change within N-back blocks was positively correlated with BOLD amplitudes in the areas of the salience network (namely bilateral insula, and anterior cingulate cortex). Taken together, fMRI with simultaneous measurement of pupil parameters constitutes a valuable tool to dissect working memory subprocesses related to both working memory load and salience of the presented stimuli.

Schema therapy versus cognitive behavioral therapy versus individual supportive therapy for depression in an inpatient and day clinic setting: study protocol of the OPTIMA-RCT.

BACKGROUND: Major depressive disorder represents (MDD) a major cause of disability and disease burden. Beside antidepressant medication, psychotherapy is a key approach of treatment. Schema therapy has been shown to be effective in the treatment of psychiatric disorders, especially personality disorders, in a variety of settings and patient groups. Nevertheless, there is no evidence on its effectiveness for MDD in an inpatient nor day clinic setting and little is known about the factors that drive treatment response in such a target group. METHODS: In the current protocol, we outline OPTIMA (OPtimized Treatment Identification at the MAx Planck Institute): a single-center randomized controlled trial of schema therapy as a treatment approach for MDD in an inpatient and day clinic setting. Over the course of 7 weeks, we compare schema therapy with cognitive behavioral therapy and individual supportive therapy, conducted in individual and group sessions and with no restrictions regarding concurrent antidepressant medication, thus approximating real-life treatment conditions. N = 300 depressed patients are included. All study therapists undergo a specific training and supervision and therapy adherence is assessed. Primary outcome is depressive symptom severity as self-assessment (Beck Depression Inventory-II) and secondary outcomes are clinical ratings of MDD (Montgomery-Asberg Depression Rating Scale), recovery rates after 7 weeks according to the Munich-Composite International Diagnostic Interview, general psychopathology (Brief Symptom Inventory), global functioning (World Health Organization Disability Assessment Schedule), and clinical parameters such as dropout rates. Further parameters on a behavioral, cognitive, psychophysiological, and biological level are measured before, during and after treatment and in 2 follow-up assessments after 6 and 24 months after end of treatment. DISCUSSION: To our knowledge, the OPTIMA-Trial is the first to investigate the effectiveness of schema therapy as a treatment approach of MDD, to investigate mechanisms of change, and explore predictors of treatment response in an inpatient and day clinic setting by using such a wide range of parameters. Insights from OPTIMA will allow more integrative approaches of psychotherapy of MDD. Especially, the identification of intervention-specific markers of treatment response can improve evidence-based clinical decision for individualizing treatment. TRIAL REGISTRATION: Identifier on clinicaltrials.gov : NCT03287362 ; September, 12, 2017.

Psychotherapy or medication for depression? Using individual symptom meta-analyses to derive a Symptom-Oriented Therapy (SOrT) metric for a personalised psychiatry.

BACKGROUND: Antidepressant medication (ADM) and psychotherapy are effective treatments for major depressive disorder (MDD). It is unclear, however, if treatments differ in their effectiveness at the symptom level and whether symptom information can be utilised to inform treatment allocation. The present study synthesises comparative effectiveness information from randomised controlled trials (RCTs) of ADM versus psychotherapy for MDD at the symptom level and develops and tests the Symptom-Oriented Therapy (SOrT) metric for precision treatment allocation. METHODS: First, we conducted systematic review and meta-analyses of RCTs comparing ADM and psychotherapy at the individual symptom level. We searched PubMed Medline, PsycINFO, and the Cochrane Central Register of Controlled Trials databases, a database specific for psychotherapy RCTs, and looked for unpublished RCTs. Random-effects meta-analyses were applied on sum-scores and for individual symptoms for the Hamilton Rating Scale for Depression (HAM-D) and Beck Depression Inventory (BDI) measures. Second, we computed the SOrT metric, which combines meta-analytic effect sizes with patients' symptom profiles. The SOrT metric was evaluated using data from the Munich Antidepressant Response Signature (MARS) study (n = 407) and the Emory Predictors of Remission in Depression to Individual and Combined Treatments (PReDICT) study (n = 234). RESULTS: The systematic review identified 38 RCTs for qualitative inclusion, 27 and 19 for quantitative inclusion at the sum-score level, and 9 and 4 for quantitative inclusion on individual symptom level for the HAM-D and BDI, respectively. Neither meta-analytic strategy revealed significant differences in the effectiveness of ADM and psychotherapy across the two depression measures. The SOrT metric did not show meaningful associations with other clinical variables in the MARS sample, and there was no indication of utility of the metric for better treatment allocation from PReDICT data. CONCLUSIONS: This registered report showed no differences of ADM and psychotherapy for the treatment of MDD at sum-score and symptom levels. Symptom-based metrics such as the proposed SOrT metric do not inform allocation to these treatments, but predictive value of symptom information requires further testing for other treatment comparisons.

Alexithymia and autistic traits as possible predictors for traits related to depression, anxiety, and stress: A multivariate statistical approach.

RATIONALE, AIMS, AND OBJECTIVES: Our study focused on the general population and explored the relationships between autistic traits and alexithymia, on the one hand, and traits related to depression, anxiety, and stress, on the other, using a multivariate statistical approach. In previous research, autistic traits and alexithymia have been linked to these traits both in clinical populations and in the general population. We also investigated a possible multiplicative effect of autistic traits and alexithymia and attempted to determine which of these two variables is the better predictor for health outcomes. METHODS: An online survey was conducted, and 302 participants were included in the statistical analysis. A structural equation modelling approach was chosen, and a model based on prior findings was designed and tested by using IBM SPSS AMOS 21. RESULTS: The results showed significant, medium-sized effects of alexithymia on depression, anxiety, and stress. Additionally, a medium-sized significant effect of autistic traits on depression, a small significant effect on stress, and a small nonsignificant effect on anxiety were found. The interaction term of alexithymia and autistic traits had no significant effects on any of the endogenous variables. CONCLUSIONS: Alexithymia can be considered the better predictor for anxiety in this sample, and it is unlikely that a multiplicative effect of alexithymia and autistic traits exists. The use of multivariate statistical methods provided additional information for understanding the investigated constructs and their interdependence.