Predicting treatment outcome for anxiety disorders with or without comorbid depression using clinical, imaging and (epi)genetic data

Brain structural and functional abnormalities in affective network are associated with anxious depression

BACKGROUND

Anxious depression (AD) is a common subtype of major depressive disorder (MDD). Neuroimaging studies of AD have revealed inconsistent and heterogeneous brain alterations with the use of single-model methods. Therefore, it is necessary to explore the pathogenesis of AD using multi-model imaging analyses to obtain more homogeneous and robust results.

METHODS

One hundred and eighty-two patients with MDD and 64 matched healthy controls (HCs) were recruited. Voxel-based morphometry (VBM) was used to estimate the gray matter volume (GMV) of all subjects. The GMV differences between the AD and non-anxious depression (NAD) participants were used as regions of interest (ROIs) for subsequent resting state functional connectivity (rs-FC) analyses. Correlation analysis was used to evaluate the associations between clinical symptoms and abnormal function in specific brain areas.

RESULTS

Decreased GMV in the medial frontal gyrus (MFG) and the superior frontal gyrus (SFG) was observed in the AD group compared to the NAD group. Taking the MFG and SFG as ROIs, the rs-FC analysis revealed decreased FC between the left SFG and left temporal pole and between the left SFG and right MFG in the AD group compared to the NAD group. Finally, the FC between the left SFG and left temporal pole was negatively correlated with HAMD-17 scores in the AD group.

CONCLUSION

By combining the GMV and rs-FC models, this study revealed that structural and functional disruption of the affective network may be an important pathophysiology underlying AD. The structural impairment may serve as the foundation of the functional impairment.

Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

The genetic architecture of youth anxiety: a study protocol

BACKGROUND

Anxiety disorders are the most common psychiatric problems among Canadian youth and typically have an onset in childhood or adolescence. They are characterized by high rates of relapse and chronicity, often resulting in substantial impairment across the lifespan. Genetic factors play an important role in the vulnerability toward anxiety disorders. However, genetic contribution to anxiety in youth is not well understood and can change across developmental stages. Large-scale genetic studies of youth are needed with detailed assessments of symptoms of anxiety disorders and their major comorbidities to inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care.

METHODS

The Genetic Architecture of Youth Anxiety (GAYA) study is a Pan-Canadian effort of clinical and genetic experts with specific recruitment sites in Calgary, Halifax, Hamilton, Toronto, and Vancouver. Youth aged 10-19 (n = 13,000) will be recruited from both clinical and community settings and will provide saliva samples, complete online questionnaires on demographics, symptoms of mental health concerns, and behavioural inhibition, and complete neurocognitive tasks. A subset of youth will be offered access to a self-managed Internet-based cognitive behavioral therapy resource. Analyses will focus on the identification of novel genetic risk loci for anxiety disorders in youth and assess how much of the genetic risk for anxiety disorders is unique or shared across the life span.

DISCUSSION

Results will substantially inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care. Given that the GAYA study will be the biggest genomic study of anxiety disorders in youth in Canada, this project will further foster collaborations nationally and across the world.

Generalised anxiety and panic symptoms in the German National Cohort (NAKO)

OBJECTIVES

Anxiety disorders (AD) are common in the general population, leading to high emotional distress and disability. The German National Cohort (NAKO) is a population-based mega-cohort study, examining participants in 16 German regions. The present study includes data of the first 101,667 participants and investigates the frequency and severity of generalised anxiety symptoms and panic attacks (PA).

METHODS

The Generalised Anxiety Disorder Symptoms Scale (GAD-7) and the first part of the Patient Health Questionnaire Panic Disorder (PHQ-PD) were filled out by NAKO participants (93,002). We examined the correlation of GAD-7 and PHQ-PD with demographic variables, stress (PHQ-Stress), depression (PHQ-9) and childhood trauma (CTS).

RESULTS

The total proportion of prior lifetime diagnoses of AD in the NAKO cohort reached 7.8%. Panic attacks were reported by 6.0% and possible/probable current GAD symptoms in 5.2% of the examined participants. Higher anxiety severity was associated with female sex, lower education level, German as a foreign language and younger age as well as high perceived stress and depression.

CONCLUSIONS

Clinically relevant GAD symptoms as well as panic attacks are frequent in the NAKO and are associated with sociodemographic factors, and high anxiety symptoms are accompanied by pronounced stress and depression levels.

Program of algorithm for pharmacological treatment of major depressive disorder in China: Benefits or not?

Background

This research was designed to investigate Algorithm Guided Treatment (AGT) and clinical traits for the prediction of antidepressant treatment outcomes in Chinese patients with major depressive disorder (MDD).

Methods

This study included 581 patients who had reached treatment response and 406 patients remained non-responded observed after three months of treatment. Sociodemographic factors, clinical traits, and psychiatric rating scales for evaluating therapeutic responses between the two groups were compared. Logistic regression analysis was adopted to determine the risk factors of unresponsive to antidepressant (URA) in MDD. Kaplan-Meier survival analysis was utilized to compare the therapeutic response between AGT and treatment as usual (TAU).

Results

Compared to the MDD responsive to antidepressant (RA) group, the URA group had significantly lower rates of the following clinical traits: married status, anxious distress, moderate to severe depressive symptoms, and higher rates of comorbidity (p-value < 0.05). Logistic Regression Analysis showed that eight clinical traits from psychiatric rating scales, such as anxious characteristics, were correlated positively with URA, while the other eight symptoms, such as autonomic symptoms, were negatively correlated. Time to symptomatic remission was longer in TAU without statistically significant (p-value = 0.11) by log-rank testing.

Conclusions

The factors may affect the therapeutic responses and compliance of patients, increasing the non-response risk for antidepressants. Therapeutic responses might be improved by increasing the clarification and elucidation of different symptom clusters of patients. Benefits on treatment response to AGT were not found in our study, indicating a one-size-fits-all approach may not work.Trial Registration: We registered as a clinical trial at the International Clinical Trials Registry Platform (No. NCT01764867) and obtained ethical approval 2012-42 from SMHC.

A Precision Treatment Model for Internet-Delivered Cognitive Behavioral Therapy for Anxiety and Depression Among University Students: A Secondary Analysis of a Randomized Clinical Trial

Importance

Guided internet-delivered cognitive behavioral therapy (i-CBT) is a low-cost way to address high unmet need for anxiety and depression treatment. Scalability could be increased if some patients were helped as much by self-guided i-CBT as guided i-CBT.

Objective

To develop an individualized treatment rule using machine learning methods for guided i-CBT vs self-guided i-CBT based on a rich set of baseline predictors.

Design, Setting, and Participants

This prespecified secondary analysis of an assessor-blinded, multisite randomized clinical trial of guided i-CBT, self-guided i-CBT, and treatment as usual included students in Colombia and Mexico who were seeking treatment for anxiety (defined as a 7-item Generalized Anxiety Disorder [GAD-7] score of ≥10) and/or depression (defined as a 9-item Patient Health Questionnaire [PHQ-9] score of ≥10). Study recruitment was from March 1 to October 26, 2021. Initial data analysis was conducted from May 23 to October 26, 2022.

Interventions

Participants were randomized to a culturally adapted transdiagnostic i-CBT that was guided (n = 445), self-guided (n = 439), or treatment as usual (n = 435).

Main Outcomes and Measures

Remission of anxiety (GAD-7 scores of ≤4) and depression (PHQ-9 scores of ≤4) 3 months after baseline.

Results

The study included 1319 participants (mean [SD] age, 21.4 [3.2] years; 1038 women [78.7%]; 725 participants [55.0%] came from Mexico). A total of 1210 participants (91.7%) had significantly higher mean (SE) probabilities of joint remission of anxiety and depression with guided i-CBT (51.8% [3.0%]) than with self-guided i-CBT (37.8% [3.0%]; P = .003) or treatment as usual (40.0% [2.7%]; P = .001). The remaining 109 participants (8.3%) had low mean (SE) probabilities of joint remission of anxiety and depression across all groups (guided i-CBT: 24.5% [9.1%]; P = .007; self-guided i-CBT: 25.4% [8.8%]; P = .004; treatment as usual: 31.0% [9.4%]; P = .001). All participants with baseline anxiety had nonsignificantly higher mean (SE) probabilities of anxiety remission with guided i-CBT (62.7% [5.9%]) than the other 2 groups (self-guided i-CBT: 50.2% [6.2%]; P = .14; treatment as usual: 53.0% [6.0%]; P = .25). A total of 841 of 1177 participants (71.5%) with baseline depression had significantly higher mean (SE) probabilities of depression remission with guided i-CBT (61.5% [3.6%]) than the other 2 groups (self-guided i-CBT: 44.3% [3.7%]; P = .001; treatment as usual: 41.8% [3.2%]; P < .001). The other 336 participants (28.5%) with baseline depression had nonsignificantly higher mean (SE) probabilities of depression remission with self-guided i-CBT (54.4% [6.0%]) than guided i-CBT (39.8% [5.4%]; P = .07).

Conclusions and Relevance

Guided i-CBT yielded the highest probabilities of remission of anxiety and depression for most participants; however, these differences were nonsignificant for anxiety. Some participants had the highest probabilities of remission of depression with self-guided i-CBT. Information about this variation could be used to optimize allocation of guided and self-guided i-CBT in resource-constrained settings.

Trial Registration

ClinicalTrials.gov Identifier: NCT04780542.

The application of virtual reality exposure versus relaxation training in music performance anxiety: a randomized controlled study

BACKGROUND

Performance anxiety is the most frequently reported anxiety disorder among professional musicians. Typical symptoms are - on a physical level - the consequences of an increase in sympathetic tone with cardiac stress, such as acceleration of heartbeat, increase in blood pressure, increased respiratory rate and tremor up to nausea or flush reactions. These symptoms can cause emotional distress, a reduced musical and artistical performance up to an impaired functioning. While anxiety disorders are preferably treated using cognitive-behavioral therapy with exposure, this approach is rather difficult for treating music performance anxiety since the presence of a public or professional jury is required and not easily available. The use of virtual reality (VR) could therefore display an alternative. So far, no therapy studies on music performance anxiety applying virtual reality exposure therapy have investigated the therapy outcome including cardiovascular changes as outcome parameters.

METHODS

This mono-center, prospective, randomized and controlled clinical trial has a pre-post design with a follow-up period of 6 months. 46 professional and semi-professional musicians will be recruited and allocated randomly to an VR exposure group or a control group receiving progressive muscle relaxation training. Both groups will be treated over 4 single sessions. Music performance anxiety will be diagnosed based on a clinical interview using ICD-10 and DSM-5 criteria for specific phobia or social anxiety. A behavioral assessment test is conducted three times (pre, post, follow-up) in VR through an audition in a concert hall. Primary outcomes are the changes in music performance anxiety measured by the German Bühnenangstfragebogen and the cardiovascular reactivity reflected by heart rate variability (HRV). Secondary outcomes are changes in blood pressure, stress parameters such as cortisol in the blood and saliva, neuropeptides, and DNA-methylation.

DISCUSSION

The trial investigates the effect of VR exposure in musicians with performance anxiety compared to a relaxation technique on anxiety symptoms and corresponding cardiovascular parameters. We expect a reduction of anxiety but also a consecutive improvement of HRV with cardiovascular protective effects.

TRIAL REGISTRATION

This study was registered on clinicaltrials.gov. (ClinicalTrials.gov Number: NCT05735860).

Candidate biomarkers in psychiatric disorders: state of the field

The field of psychiatry is hampered by a lack of robust, reliable and valid biomarkers that can aid in objectively diagnosing patients and providing individualized treatment recommendations. Here we review and critically evaluate the evidence for the most promising biomarkers in the psychiatric neuroscience literature for autism spectrum disorder, schizophrenia, anxiety disorders and post-traumatic stress disorder, major depression and bipolar disorder, and substance use disorders. Candidate biomarkers reviewed include various neuroimaging, genetic, molecular and peripheral assays, for the purposes of determining susceptibility or presence of illness, and predicting treatment response or safety. This review highlights a critical gap in the biomarker validation process. An enormous societal investment over the past 50 years has identified numerous candidate biomarkers. However, to date, the overwhelming majority of these measures have not been proven sufficiently reliable, valid and useful to be adopted clinically. It is time to consider whether strategic investments might break this impasse, focusing on a limited number of promising candidates to advance through a process of definitive testing for a specific indication. Some promising candidates for definitive testing include the N170 signal, an event-related brain potential measured using electroencephalography, for subgroup identification within autism spectrum disorder; striatal resting-state functional magnetic resonance imaging (fMRI) measures, such as the striatal connectivity index (SCI) and the functional striatal abnormalities (FSA) index, for prediction of treatment response in schizophrenia; error-related negativity (ERN), an electrophysiological index, for prediction of first onset of generalized anxiety disorder, and resting-state and structural brain connectomic measures for prediction of treatment response in social anxiety disorder. Alternate forms of classification may be useful for conceptualizing and testing potential biomarkers. Collaborative efforts allowing the inclusion of biosystems beyond genetics and neuroimaging are needed, and online remote acquisition of selected measures in a naturalistic setting using mobile health tools may significantly advance the field. Setting specific benchmarks for well-defined target application, along with development of appropriate funding and partnership mechanisms, would also be crucial. Finally, it should never be forgotten that, for a biomarker to be actionable, it will need to be clinically predictive at the individual level and viable in clinical settings.

CO2 reactivity as a biomarker of exposure-based therapy non-response: study protocol

BACKGROUND

Exposure-based therapy is an effective first-line treatment for anxiety-, obsessive-compulsive, and trauma- and stressor-related disorders; however, many patients do not improve, resulting in prolonged suffering and poorly used resources. Basic research on fear extinction may inform the development of a biomarker for the selection of exposure-based therapy. Growing evidence links orexin system activity to deficits in fear extinction and we have demonstrated that reactivity to an inhaled carbon dioxide (CO₂) challenge-a safe, affordable, and easy-to-implement procedure-can serve as a proxy for orexin system activity and predicts fear extinction deficits in rodents. Building upon this basic research, the goal for the proposed study is to validate CO₂ reactivity as a biomarker of exposure-based therapy non-response.

METHODS

We will assess CO₂ reactivity in 600 adults meeting criteria for one or more fear- or anxiety-related disorders prior to providing open exposure-based therapy. By incorporating CO₂ reactivity into a multivariate model predicting treatment non-response that also includes reactivity to hyperventilation as well as a number of related predictor variables, we will establish the mechanistic specificity and the additive predictive utility of the potential CO₂ reactivity biomarker. By developing models independently within two study sites (University of Texas at Austin and Boston University) and predicting the other site's data, we will validate that the results are likely to generalize to future clinical samples.

DISCUSSION

Representing a necessary stage in translating basic research, this investigation addresses an important public health issue by testing an accessible clinical assessment strategy that may lead to a more effective treatment selection (personalized medicine) for patients with anxiety- and fear-related disorders, and enhanced understanding of the mechanisms governing exposure-based therapy.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT05467683 (20/07/2022).

DNA-methylation dynamics across short-term, exposure-containing CBT in patients with panic disorder

Interaction of genetic predispositions and environmental factors via epigenetic mechanisms have been hypothesized to play a central role in Panic Disorder (PD) aetiology and therapy. Cognitive Behavioral Therapy (CBT), including exposure interventions, belong to the most efficient treatments of PD although its biological mechanism of action remains unknown. For the first time, we explored the dynamics and magnitude of DNA-methylation and immune cell-type composition during CBT (n = 38) and the therapeutic exposure intervention (n = 21) to unravel their biological correlates and identify possible biomarkers of therapy success. We report transient regulation of the CD4 + T-Cells, Natural Killers cells, Granulocytes during exposure and a significant change in the proportions of CD4 + T cells, CD8 + T cells and B-Cells and Granulocytes during therapy. In an epigenome-wide association study we identified cg01586609 located in a CpG island and annotated to the serotonin receptor 3 A (HTR3A) to be differentially methylated during fear exposure and regulated at gene expression level with significant differences between remitters and non-remitters (p = 0.028). We moreover report cg01699630 annotated to ARG1 to undergo long lasting methylation changes during therapy (paired t test, genome-wide adj.p value = 0.02). This study reports the first data-driven biological candidates for epigenetically mediated effects of acute fear exposure and CBT in PD patients. Our results provide evidence of changes in the serotonin receptor 3 A methylation and expression during fear exposure associated with different long-term CBT trajectories and outcome, making it a possible candidate in the search of markers for therapy success. Finally, our results add to a growing body of evidence showing immune system changes associated with PD.

Contributions of diagnostic, cognitive, and somatovisceral information to the prediction of fear ratings in spider phobic and non-spider-fearful individuals

BACKGROUND

Physiological responding is a key characteristic of fear responses. Yet, it is unknown whether the time-consuming measurement of somatovisceral responses ameliorates the prediction of individual fear responses beyond the accuracy reached by the consideration of diagnostic (e.g., phobic vs. non phobic) and cognitive (e.g., risk estimation) factors, which can be more easily assessed.

METHOD

We applied a machine learning approach to data of an experiment, in which spider phobic and non-spider fearful participants (diagnostic factor) faced pictures of spiders. For each experimental trial, participants specified their personal risk of encountering the spider (cognitive factor), as well as their subjective fear (outcome variable) on quasi-continuous scales, while diverse somatovisceral responses were registered (heart rate, electrodermal activity, respiration, facial muscle activity).

RESULTS

The machine-learning analyses revealed that fear ratings were predominantly predictable by the diagnostic factor. Yet, when allowing for learning of individual patterns in the data, somatovisceral responses contributed additional information on the fear ratings, yielding a prediction accuracy of 81% explained variance. Moreover, heart rate prior to picture onset, but not heart rate reactivity increased predictive power.

LIMITATIONS

Fear was solely assessed by verbal reports, only 27 females were considered, and no generalization to other anxiety disorders is possible.

CONCLUSIONS

After training the algorithm to learn about individual-specific responding, somatovisceral patterns can be successfully exploited. Our findings further point to the possibility that the expectancy-related autonomic state throughout the experiment predisposes an individual to experience specific levels of fear, with less influence of the actual visual stimulations.

Genetic contributions to anxiety disorders: where we are and where we are heading

Anxiety disorders are among the most common psychiatric disorders worldwide. They often onset early in life, with symptoms and consequences that can persist for decades. This makes anxiety disorders some of the most debilitating and costly disorders of our time. Although much is known about the synaptic and circuit mechanisms of fear and anxiety, research on the underlying genetics has lagged behind that of other psychiatric disorders. However, alongside the formation of the Psychiatric Genomic Consortium Anxiety workgroup, progress is rapidly advancing, offering opportunities for future research.Here we review current knowledge about the genetics of anxiety across the lifespan from genetically informative designs (i.e. twin studies and molecular genetics). We include studies of specific anxiety disorders (e.g. panic disorder, generalised anxiety disorder) as well as those using dimensional measures of trait anxiety. We particularly address findings from large-scale genome-wide association studies and show how such discoveries may provide opportunities for translation into improved or new therapeutics for affected individuals. Finally, we describe how discoveries in anxiety genetics open the door to numerous new research possibilities, such as the investigation of specific gene-environment interactions and the disentangling of causal associations with related traits and disorders.We discuss how the field of anxiety genetics is expected to move forward. In addition to the obvious need for larger sample sizes in genome-wide studies, we highlight the need for studies among young people, focusing on specific underlying dimensional traits or components of anxiety.

A review of systems biology research of anxiety disorders

The development of "omic" technologies and deep phenotyping may facilitate a systems biology approach to understanding anxiety disorders. Systems biology approaches incorporate data from multiple modalities (e.g., genomic, neuroimaging) with functional analyses (e.g., animal and tissue culture models) and mathematical modeling (e.g., machine learning) to investigate pathological biophysical networks at various scales. Here we review: i) the neurobiology of anxiety disorders; ii) how systems biology approaches have advanced this work; and iii) the clinical implications and future directions of this research. Systems biology approaches have provided an improved functional understanding of candidate biomarkers and have suggested future potential for refining the diagnosis, prognosis, and treatment of anxiety disorders. The systems biology approach for anxiety disorders is, however, in its infancy and in some instances is characterized by insufficient power and replication. The studies reviewed here represent important steps to further untangling the pathophysiology of anxiety disorders.

A Web-Based Group Cognitive Behavioral Therapy Intervention for Symptoms of Anxiety and Depression Among University Students: Open-Label, Pragmatic Trial

BACKGROUND

Anxiety and depression are common among university students, and university counseling centers are under pressure to develop effective, novel, and sustainable interventions that engage and retain students. Group interventions delivered via the internet could be a novel and effective way to promote student mental health.

OBJECTIVE

We conducted a pragmatic open trial to investigate the uptake, retention, treatment response, and level of satisfaction with a remote group cognitive behavioral therapy intervention designed to reduce symptoms of anxiety and depression delivered on the web to university students during the COVID-19 pandemic.

METHODS

Preintervention and postintervention self-reported data on anxiety and depression were collected using the Generalized Anxiety Disorder-7 and Patient Health Questionnaire-9. Satisfaction was assessed postintervention using the Client Satisfaction with Treatment Questionnaire.

RESULTS

A total of 175 students were enrolled, 158 (90.3%) of whom initiated treatment. Among those initiating treatment, 86.1% (135/158) identified as female, and the mean age was 22.4 (SD 4.9) years. The mean number of sessions attended was 6.4 (SD 2.8) out of 10. Among participants with clinically significant symptoms at baseline, mean symptom scores decreased significantly for anxiety (t₅₆=11.6; P<.001), depression (t₆₁=7.8; P<.001), and composite anxiety and depression (t₆₀=10.7; P<.001), with large effect sizes (d=1-1.5). Remission rates among participants with clinically significant baseline symptoms were 67.7%-78.9% and were not associated with baseline symptom severity. High overall levels of satisfaction with treatment were reported.

CONCLUSIONS

The results of this study serve as a proof of concept for the use of web-based group cognitive behavioral therapy to promote the mental health of university students.

Clinical Efficacy and Cost-Effectiveness of Imagery Rescripting Only Compared to Imagery Rescripting and Schema Therapy in Adult Patients With PTSD and Comorbid Cluster C Personality Disorder: Study Design of a Randomized Controlled Trial

Background: Posttraumatic stress disorder (PTSD) is a serious and relatively common mental disorder causing a high burden of suffering. Whereas evidence-based treatments are available, dropout and non-response rates remain high. PTSD and Cluster C personality disorders (avoidant, dependent or obsessive-compulsive personality disorder; CPD) are highly comorbid and there is evidence for suboptimal treatment effects in this subgroup of patients. An integrated PTSD and CPD treatment may be needed to increase treatment efficacy. However, no studies directly comparing the efficacy of regular PTSD treatment and treatment tailored to PTSD and comorbid CPD are available. Whether integrated treatment is more effective than treatment focused on PTSD alone is important, since (1) no evidence-based guideline for PTSD and comorbid CPD treatment exists, and (2) treatment approaches to CPD are costly and time consuming. Present study design describes a randomized controlled trial (RCT) directly comparing trauma focused treatment with integrated trauma focused and personality focused treatment. Methods: An RCT with two parallel groups design will be used to compare the clinical efficacy and cost-effectiveness of "standalone" imagery rescripting (n = 63) with integrated imagery rescripting and schema therapy (n = 63). This trial is part of a larger research project on PTSD and personality disorders. Predictors, mediators and outcome variables are measured at regular intervals over the course of 18 months. The main outcome is PTSD severity at 12 months. Additionally, machine-learning techniques will be used to predict treatment outcome using biopsychosocial variables. Discussion: This study protocol outlines the first RCT aimed at directly comparing the clinical efficacy and cost-effectiveness of imagery rescripting and integrated imagery rescripting and schema therapy for treatment seeking adult patients with PTSD and comorbid cluster C personality pathology. Additionally, biopsychosocial variables will be used to predict treatment outcome. As such, the trial adds to the development of an empirically informed and individualized treatment indication process. Clinical Trial registration: ClinicalTrials.gov, NCT03833531.

Impact of Substance Use Disorder on Quality of Inpatient Mental Health Services for People With Anxiety and Depression

Objective: Substance use disorders are commonly comorbid with anxiety and depressive disorders and are associated with poor treatment outcomes. The mechanisms underlying this association remain unclear-one possibility is that patients with anxiety/depressive disorders and substance use disorders receive poorer treatment. Concerns have been raised about the quality of inpatient care received by patients with substance use disorders. The purspose of this research was to examine the quality of care received by inpatients with an anxiety or depressive disorder, comparing subgroups with or without a comorbid substance use disorder. Methods: This was a retrospective case-note review of 3,795 patients admitted to inpatient psychiatric wards in England. Data were gathered on all acute admissions with anxiety/depressive illness over a 6-month period, for a number of measures of quality of care derived from national standards. Association of coexisting substance use disorders with a variety of quality of care outcomes (relating to assessment, care planning, medication management, psychological therapies, discharge, crisis planning, and follow-up) was investigated using multivariable regression analyses. Results: In all, 543 (14.3%) patients in the study had a secondary diagnosis of a substance use disorder. Patients with substance use disorders were less likely to have had care plans that were developed jointly (i.e., with input from both patient and clinician; odds ratio [OR] = 0.76, 95% confidence interval [CI] [0.55, 0.93], p = .034) and less likely to have had their medication reviewed either during the admission (OR = 0.83, 95% CI [0.69, 0.94], p = .030) or at follow-up after discharge (OR = 0.58, 95% CI [0.39, 0.86], p = .007). Carers of patients with substance use disorders were less likely to have been provided with information about available support services (OR = 0.79, 95% CI [0.57, 0.98], p = .047). Patients with substance use disorders were less likely to have received adequate (at least 24 hours) notice in advance of their discharge (OR = 0.72, 95% CI [0.54, 0.96], p = .033), as were their carers (OR = 0.63, 95% CI [0.41, 0.85], p = .007). They were less likely to have a crisis plan in place at the point of discharge (OR = 0.85, 95% CI [0.74, 0.98], p = .044). There was also strong evidence that patients with substance use disorders were less likely to have been referred for psychological therapy (OR = 0.69, 95% CI [0.55, 0.87], p = .002). Conclusions: We found evidence of poorer quality of care for inpatients with anxiety and depressive disorders with comorbid substance use disorders, highlighting the need for more to be done to support these patients. Discrepancies in care quality may be contributed to the poor treatment outcomes experienced by patients with substance use disorders, and strategies to reduce this inequality are necessary to improve the well-being of this substantial patient group.

Impact of co-morbid personality disorder on quality of inpatient mental health services for people with anxiety and depression

INTRODUCTION

Concerns have been raised about the quality of inpatient care received by patients with a diagnosis of personality disorder.

OBJECTIVES

The aim of this study was to examine the quality of care received by inpatients with an anxiety or depressive disorder, comparing subgroups with or without a co-morbid personality disorder.

METHOD

We used a retrospective case-note review of 3 795 patients admitted to inpatient psychiatric wards in England, utilizing data from the National Clinical Audit of Anxiety and Depression. Data were gathered on all acute admissions with an anxiety or depressive disorder over a 6-month period, for a number of measures reflecting quality of care derived from national standards. Association of coexisting personality disorder with quality of care was investigated using multivariable regression analyses.

RESULTS

Four hundred sixteen (11.0%) of the patients had a co-co-morbid diagnosis of personality disorder. Patients with personality disorder were less likely to have been asked about prior responses to treatment in their initial assessment (odds ratio (OR) = 0.67, 95% confidence interval (CI) 0.50 to 0.89, p = 0.007). They were less likely to receive adequate notice in advance of their discharge (OR = 0.87, 95% CI 0.65 to 0.98, p = 0.046). They were more likely to be prescribed medication at the point of discharge (OR = 1.52, 95% CI 1.02 to 2.09, p = 0.012) and less likely to have been provided with information about the medicines they were taking (OR = 0.86, 95% CI 0.69 to 0.94, p = 0.048). In addition, the carers of patients with co-morbid personality disorder were less likely to have been provided with information about available support services (OR = 0.73, 95% CI 0.51 to 0.93, p = 0.045).

CONCLUSION

We found evidence of poorer quality of care for patients with co-morbid personality disorder who were admitted to psychiatric hospital for treatment of anxiety or depressive disorders, highlighting the need for improved clinical care in this patient group.

Cognitive functioning in posttraumatic stress disorder before and after cognitive-behavioral therapy

Although substantial evidence suggests altered executive functioning and autobiographical memory in posttraumatic stress disorder (PTSD), the clinical significance of these findings remains unclear. Here, we investigated the effects of cognitive-behavioral therapy (CBT) on different aspects of cognitive functioning (working memory, interference susceptibility, conflict adaptation, autobiographical memory) in PTSD patients in a pre-post control group design with a nested cross-sectional element. Cross-sectional analyses at baseline were conducted on 58 PTSD patients, 39 traumatized (TC), and 45 non-traumatized controls (NTC). Intervention effects were investigated before and after 25 CBT sessions in 25 PTSD and 34 untreated NTC individuals assessed in parallel. At baseline, PTSD patients showed higher conflict adaptation than the NTC group and less autobiographical memory specificity than both control groups, suggesting particularly the latter to be a correlate of PTSD. No consistent evidence for treatment-induced improvements in cognitive functioning emerged on the group level or from associations between intra-individual clinical and cognitive changes. Analyses on the role of cognitive functioning on subsequent treatment effects revealed a predictive effect of backward digit span on CBT-induced reductions of depressiveness, but no other significant effects. Our findings highlight the need for further research to identify more relevant predictors of differential treatment response.

Graph theoretical measures of the uncinate fasciculus subnetwork as predictors and correlates of treatment response in a transdiagnostic psychiatric cohort

The internalizing psychopathologies (IP) are a highly prevalent group of disorders for which little data exists to guide treatment selection. We examine whether graph theoretical metrics from white matter connectomes may serve as biomarkers of disease and predictors of treatment response. We focus on the uncinate fasciculus subnetwork, which has been previously implicated in these disorders. We compared baseline graph measures from a transdiagnostic IP cohort with controls. Patients were randomized to either SSRI or cognitive behavioral therapy and we determined if graph theory metrics change following treatment, and whether these changes correlated with treatment response. Lastly, we investigated whether baseline metrics correlated with treatment response. Several baseline nodal graph metrics differed at baseline. Of note, right amygdala betweenness centrality was increased in patients relative to controls. In addition, white matter integrity of the uncinate fasciculus was decreased at baseline in patients versus controls. The SSRI and CBT cohorts had increased left frontal superior orbital betweenness centrality and left frontal medial orbital clustering coefficient, respectively, suggesting the presence of treatment specific neural correlates of treatment response. This study provides insight on shared white matter network features of IPs and elucidates potential biomarkers of treatment response that may be modality-specific.

Alpha2-adrenergic dysregulation in congenic DxH recombinant inbred mice selectively bred for a high fear-sensitized (H-FSS) startle response

Patients with anxiety disorders and posttraumatic stress disorder (PTSD) exhibit exaggerated fear responses and noradrenergic dysregulation. Fear-related responses to α₂-adrenergic challenge were therefore studied in DxH C3H/HeJ-like recombinant inbred (C3HLRI) mice, which are a DBA/2J-congenic strain selectively bred for a high fear-sensitized startle (H-FSS). C3HLRI mice showed an enhanced acoustic startle response and immobility in the forced swim test compared to DBA/2J controls. The α₂-adrenoceptor antagonist yohimbine (Yoh; 5.0 mg/kg) induced an anxiogenic and the α₂-adrenoceptor agonist clonidine (Clon; 0.1 mg/kg) an anxiolytic effect in the open field (OF) in C3HLRI but not DBA/2J mice. In auditory fear-conditioning, Yoh (5.0 mg/kg)-treated C3HLRI mice showed higher freezing during fear recall and extinction learning than DBA/2J mice, and a higher ceiling for the Yoh-induced deficit in fear extinction. No strain differences were observed in exploration-related anxiety/spatial learning or the Clon-induced (0.1 mg/kg) corticosterone surge. A global analysis of the behavioral profile of the two mouse strains based on observed and expected numbers of significant behavioral outcomes indicated that C3HLRI mice showed significantly more often fear- and stress-related PTSD-like behaviors than DBA/2J controls. The analysis of the robustness of significant outcomes based on false discovery rate (FDR) thresholds confirmed significant differences for the strain-Yoh-interactions in the OF center and periphery, the Yoh-induced general extinction deficit, strain differences in conditioned fear levels, and at the dose of 5.0 mg/kg for the Yoh-induced ceiling in freezing levels among others. The current findings are consistent with previous observations showing alterations in the central noradrenergic system of C3HLRI mice (Browne et al., 2014, Stress 17:471-83). Based on their behavioral profile and response to α₂-adrenergic stimulation, C3HLRI mice are a valuable genetic model for studying adrenergic mechanisms of anxiety disorders and potentially also of PTSD.

Psychoradiological Biomarkers for Psychopharmaceutical Effects

The application of personalized medicine to psychiatry is challenging. Psychoradiology could provide biomarkers based on objective tests in support of the diagnostic classifications and treatment planning. We review potential psychoradiological biomarkers for psychopharmaceutical effects. Although none of the biomarkers reviewed are yet of sufficient clinical utility to inform the selection of a specific pharmacologic compound for an individual patient, there is strong consensus that advanced multimodal approaches will contribute to discovery of novel treatment predictors in psychiatric disorders. Progress has been sufficient to warrant enthusiasm, in which application of neuroimaging-based biomarkers would represent a paradigm shift and modernization of psychiatric practice.

Novel pharmacological targets in drug development for the treatment of anxiety and anxiety-related disorders

Current medication for anxiety disorders is suboptimal in terms of efficiency and tolerability, highlighting the need for improved drug treatments. In this review an overview of drugs being studied in different phases of clinical trials for their potential in the treatment of fear-, anxiety- and trauma-related disorders is presented. One strategy followed in drug development is refining and improving compounds interacting with existing anxiolytic drug targets, such as serotonergic and prototypical GABAergic benzodiazepines. A more innovative approach involves the search for compounds with novel mechanisms of anxiolytic action using the growing knowledge base concerning the relevant neurocircuitries and neurobiological mechanisms underlying pathological fear and anxiety. The target systems evaluated in clinical trials include glutamate, endocannabinoid and neuropeptide systems, as well as ion channels and targets derived from phytochemicals. Examples of promising novel candidates currently in clinical development for generalised anxiety disorder, social anxiety disorder, panic disorder, obsessive compulsive disorder or post-traumatic stress disorder include ketamine, riluzole, xenon with one common pharmacological action of modulation of glutamatergic neurotransmission, as well as the neurosteroid aloradine. Finally, compounds such as D-cycloserine, MDMA, L-DOPA and cannabinoids have shown efficacy in enhancing fear-extinction learning in humans. They are thus investigated in clinical trials as an augmentative strategy for speeding up and enhancing the long-term effectiveness of exposure-based psychotherapy, which could render chronic anxiolytic drug treatment dispensable for many patients. These efforts are indicative of a rekindled interest and renewed optimism in the anxiety drug discovery field, after decades of relative stagnation.