Biological predictors of pharmacological therapy in anxiety disorders

Association between resting-state connectivity patterns in the defensive system network and treatment response in spider phobia-a replication approach

Although highly effective on average, exposure-based treatments do not work equally well for all patients with anxiety disorders. The identification of pre-treatment response-predicting patient characteristics may enable patient stratification. Preliminary research highlights the relevance of inhibitory fronto-limbic networks as such. We aimed to identify pre-treatment neural signatures differing between exposure treatment responders and non-responders in spider phobia and to validate results through rigorous replication. Data of a bi-centric intervention study comprised clinical phenotyping and pre-treatment resting-state functional connectivity (rsFC) data of n = 79 patients with spider phobia (discovery sample) and n = 69 patients (replication sample). RsFC data analyses were accomplished using the Matlab-based CONN-toolbox with harmonized analyses protocols at both sites. Treatment response was defined by a reduction of >30% symptom severity from pre- to post-treatment (Spider Phobia Questionnaire Score, primary outcome). Secondary outcome was defined by a reduction of >50% in a Behavioral Avoidance Test (BAT). Mean within-session fear reduction functioned as a process measure for exposure. Compared to non-responders and pre-treatment, results in the discovery sample seemed to indicate that responders exhibited stronger negative connectivity between frontal and limbic structures and were characterized by heightened connectivity between the amygdala and ventral visual pathway regions. Patients exhibiting high within-session fear reduction showed stronger excitatory connectivity within the prefrontal cortex than patients with low within-session fear reduction. Whereas these results could be replicated by another team using the same data (cross-team replication), cross-site replication of the discovery sample findings in the independent replication sample was unsuccessful. Results seem to support negative fronto-limbic connectivity as promising ingredient to enhance response rates in specific phobia but lack sufficient replication. Further research is needed to obtain a valid basis for clinical decision-making and the development of individually tailored treatment options. Notably, future studies should regularly include replication approaches in their protocols.

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.

Peripheral Biomarkers in DSM-5 Anxiety Disorders: An Updated Overview

Anxiety disorders are prevalent and highly disabling mental disorders. In recent years, intensive efforts focused on the search for potential neuroimaging, genetic, and peripheral biomarkers in order to better understand the pathophysiology of these disorders, support their diagnosis, and characterize the treatment response. Of note, peripheral blood biomarkers, as surrogates for the central nervous system, represent a promising instrument to characterize psychiatric disorders, although their role has not been extensively applied to clinical practice. In this report, the state of the art on peripheral biomarkers of DSM-5 (Diagnostic and Statistical Manual of Mental Disorders, 5th edition) Anxiety Disorders is presented, in order to examine their role in the pathogenesis of these conditions and their potential application for diagnosis and treatment. Available data on the cerebrospinal fluid and blood-based biomarkers related to neurotransmitters, neuropeptides, the hypothalamic-pituitary-adrenal axis, neurotrophic factors, and the inflammation and immune system are reviewed. Despite the wide scientific literature and the promising results in the field, only a few of the proposed peripheral biomarkers have been defined as a specific diagnostic instrument or have been identified as a guide in the treatment response to DSM-5 Anxiety Disorders. Therefore, further investigations are needed to provide new biological insights into the pathogenesis of anxiety disorders, to help in their diagnosis, and to tailor a treatment.

Efficacy and safety of acupuncture combined with western medicine for anxiety: A systematic review protocol

BACKGROUND

As a common clinical mental disorder, the prevalence rate of anxiety disorder increased yearly, devastating both physical health and social-economic prospect. The most common treatment relied on the use of western medications which is yet to fulfill ideal performance. While acupuncture is adopted as a treatment for anxiety disorders, the combination treatment of acupuncture and western medicines becomes more acknowledged. Albeit a spike in related literatures, the curative effect and safety of the treatment are still in lack of evidence. Therefore, this systematic review and meta-analysis protocol is planned to evaluate the efficacy and safety of the combination treatment of acupuncture and western medications.

METHODS

Six English databases (PubMed, Web of science, Medline, EBASE, Springer Cochrane Library and WHO International Clinical Trials Registry Platform) and four Chinese databases (Wan fang Database, Chinese Scientific Journal Database, China National Knowledge Infrastructure Database (CNKI) and Chinese Biomedical Literature Database) will be searched normatively according to the rule of each database from the inception to June 1, 2020. Two reviewers will independently conduct article selection, data collection, and risk of bias evaluation. Any disagreement will be resolved by discussion with the third reviewer. Either the fixed-effects or random-effects model will be used for data synthesis based on the heterogeneity test. The change in the scores on the Hamilton Anxiety Scale (HANA) and the self-rating anxiety scale (SAS) will be used as the main outcome measure, quality of life scale (SF-36), changes of symptoms in TCM, hormone levels and clinical global impression (CGI) as the secondary outcome. treatment emergent symptom scale (TESS), general physical examination(temperature, pulse, respiration, blood pressure), Routine examination of blood, urine and stool, Electrocardiogram, Liver and kidney function examination as the security indexes. RevMan 5.3.5 will be used for meta-analysis.

RESULTS

This study will provide high-quality evidence to assess the effectiveness and safety of acupuncture combined with western medicine for anxiety.

CONCLUSION

This systematic review will explore whether acupuncture combined with western medicine is an effective and safe intervention for anxiety.

ETHICS AND DISSEMINATION

Ethical approval is not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and will be shared on social media platforms. This review will be disseminated in a peer-reviewed journal or conference presentation.

PROSPERO REGISTRATION NUMBER

PROSPERO CRD42020149746.

Prediction of treatment resistance in obsessive compulsive disorder patients based on EEG complexity as a biomarker

OBJECTIVE

This study aimed to identify an Electroencephalography (EEG) complexity biomarker that could predict treatment resistance in Obsessive compulsive disorder (OCD) patients. Additionally, the statistical differences between EEG complexity values in treatment-resistant and treatment-responsive patients were determined. Moreover, the existence of correlations between EEG complexity and Yale-Brown Obsessive Compulsive Scale (YBOCS) score were evaluated.

METHODS

EEG data for 29 treatment-resistant and 28 treatment-responsive OCD patients were retrospectively evaluated. Approximate entropy (ApEn) method was used to extract the EEG complexity from both whole EEG data and filtered EEG data, according to 4 common frequency bands, namely delta, theta, alpha, and beta. The random forests method was used to classify ApEn complexity.

RESULTS

ApEn complexity extracted from beta band EEG segments discriminated treatment-responsive and treatment-resistant OCD patients with an accuracy of 89.66% (sensitivity: 89.44%; specificity: 90.64%). Beta band EEG complexity was lower in the treatment-resistant patients and the severity of OCD, as measured by YBOCS score, was inversely correlated with complexity values.

CONCLUSIONS

The results indicate that, EEG complexity could be considered a biomarker for predicting treatment response in OCD patients.

SIGNIFICANCE

The prediction of treatment response in OCD patients might help clinicians devise and administer individualized treatment plans.

Role of MicroRNAs in Anxiety and Anxiety-Related Disorders

MicroRNAs as critical regulators of gene expression important for functions including neuronal development, synapse formation, and synaptic plasticity have been linked with the regulation of neurobiological systems that underlie anxiety processing in the brain. In this chapter, we give an update on associative evidence linking regulation of microRNAs with anxiety- and trauma-related disorders. Moving beyond correlative research, functional studies have emerged recently that explore causal relationships between microRNA expression and anxiety-like behavior. It has been demonstrated that experimental up- or downregulation of the candidate microRNAs in important nodes of the anxiety neurocircuitry can indeed modulate anxiety-related behavior in animal models. Improved methodologies for assessing microRNA-mediated modulation have aided such functional studies, revealing a number of anxiety-regulating microRNAs including miR-15a, miR-17-92, miR-34, miR-101, miR-124, miR-135, and miR-155. Important functional target genes of these identified microRNAs are associated with specific neurotransmitter/neuromodulator signaling, neurotrophin (e.g., BDNF) expression and other aspects of synaptic plasticity, as well as with stress-regulatory/hypothalamic-pituitary-axis function. Furthermore, microRNAs have been revealed that are regulated in distinct brain regions following various anxiety-attenuating strategies. These include pharmacological treatments such as antidepressants and other drugs, as well as non-pharmacological interventions such as fear extinction/exposure therapy or positive stimuli such as exposure to environmental enrichment. These are first indications for a role for microRNAs in the mechanism of action of anxiolytic treatments. As research continues, there is much hope that a deeper understanding of the microRNA-mediated mechanisms underlying anxiety-related disorders could open up possibilities for future novel biomarker and treatment strategies.

Neuroimaging, genetic, clinical, and demographic predictors of treatment response in patients with social anxiety disorder

BACKGROUND

Correct prediction of treatment response is a central goal of precision psychiatry. Here, we tested the predictive accuracy of a variety of pre-treatment patient characteristics, including clinical, demographic, molecular genetic, and neuroimaging markers, for treatment response in patients with social anxiety disorder (SAD).

METHODS

Forty-seven SAD patients (mean±SD age 33.9 ± 9.4 years, 24 women) were randomized and commenced 9 weeks' Internet-delivered cognitive behavior therapy (CBT) combined either with the selective serotonin reuptake inhibitor (SSRI) escitalopram (20 mg daily [10 mg first week], SSRI+CBT, n = 24) or placebo (placebo+CBT, n = 23). Treatment responders were defined from the Clinical Global Impression-Improvement scale (CGI-I ≤ 2). Before treatment, patients underwent functional magnetic resonance imaging and the Multi-Source Interference Task taxing cognitive interference. Support vector machines (SVMs) were trained to separate responders from nonresponders based on pre-treatment neural reactivity in the dorsal anterior cingulate cortex (dACC), amygdala, and occipital cortex, as well as molecular genetic, demographic, and clinical data. SVM models were tested using leave-one-subject-out cross-validation.

RESULTS

The best model separated treatment responders (n = 24) from nonresponders based on pre-treatment dACC reactivity (83% accuracy, P = 0.001). Responders had greater pre-treatment dACC reactivity than nonresponders especially in the SSRI+CBT group. No other variable was associated with clinical response or added predictive accuracy to the dACC SVM model.

LIMITATIONS

Small sample size, especially for genetic analyses. No replication or validation samples were available.

CONCLUSIONS

The findings demonstrate that treatment outcome predictions based on neural cingulate activity, at the individual level, outperform genetic, demographic, and clinical variables for medication-assisted Internet-delivered CBT, supporting the use of neuroimaging in precision psychiatry.

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.

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

PURPOSE OF REVIEW

The present review complements previous reviews on prediction research in anxiety disorders with a focus on clinical, imaging and genetic as well as epigenetic factors and aims to provide recommendations for the design of future integrative studies in adults as well as children.

RECENT FINDINGS

Clinical factors predicting worse outcome such as a diagnosis of social anxiety disorder, comorbid depression and certain cognitive, behavioral and personality traits as well as low socioeconomic status were confirmed in large clinical studies. Imaging factors focusing on the fear and anxiety network were repeatedly described as predicting therapy response in small exploratory studies. The plethora of candidate gene studies has now been complemented by large genome-wide association studies and small epigenetic investigations with the need for replication in larger samples.

SUMMARY

The present status of research on predictors for therapy response in anxiety disorders, in particular on imaging and genetic factors, is still fragmentary. Some clinical factors for poorer outcome, though, have been consistently replicated and should be considered in the revision of therapy guidelines. There is a definite need for large integrative studies at the national and international level integrating multiple levels of biomarkers at different stages of development.

Predictors of Pharmacotherapy Response in Generalized Anxiety Disorder: A Systematic Review

BACKGROUND

Pharmacotherapy for generalized anxiety disorder (GAD) may be effective in reducing symptoms in the majority of patients. The study of moderators and predictors of treatment response may help clinicians both to select appropriate interventions to maximize the probability of response and to inform the general prognosis.

METHODS

A systematic literature search of electronic databases, selected authors, and reference lists was used to identify articles that reported trials of drug monotherapy in GAD. Data on predictors and moderators were extracted. Quality of evidence was determined by the presence of a priori hypotheses, number of variables investigated, adequate quality of the measurement, and use of interaction-effects testing.

RESULTS

From the 98 articles meeting inclusion criteria, 24 reported a total of 22 factors associated with treatment response. The reported results were heterogeneous, ranging over sociodemographic, clinical, comorbidity, genetic, and functional-imaging studies. Major depressive symptoms were found to moderate treatment outcome in favor of antidepressants versus benzodiazepines. Neuroticism, previous treatment, genetic polymorphisms (including serotonin receptor gene 2A), and functional activation of the anterior cingulate cortex and amygdala were identified as potential predictors of treatment response.

CONCLUSIONS

Correlates of poor emotion regulation predicted poor treatment response, but subclinical depression was the only variable capable of informing treatment selection in this review. Future research should focus on further exploring the value of depression as a moderator and on a narrower list of potential genetic, brain-imaging, and temperament predictors of response to pharmacotherapy in GAD.

Is There Room for Second-Generation Antipsychotics in the Pharmacotherapy of Panic Disorder? A Systematic Review Based on PRISMA Guidelines

A role for second-generation antipsychotics (SGAs) in the treatment of panic disorders (PD) has been proposed, but the actual usefulness of SGAs in this disorder is unclear. According to the PRISMA guidelines, we undertook an updated systematic review of all of the studies that have examined, in randomized controlled trials, the efficacy and tolerability of SGAs (as either monotherapy or augmentation) in the treatment of PD, with or without other comorbid psychiatric disorders. Studies until 31 December 2015 were identified through PubMed, PsycINFO, Embase, Cochrane Library and Clinical trials.gov. Among 210 studies, five were included (two involving patients with a principal diagnosis of PD and three involving patients with bipolar disorder with comorbid PD or generalized anxiety disorder). All were eight-week trials and involved treatments with quetiapine extended release, risperidone and ziprasidone. Overall, a general lack of efficacy of SGAs on panic symptoms was observed. Some preliminary indications of the antipanic effectiveness of risperidone are insufficient to support its use in PD, primarily due to major limitations of the study. However, several methodological limitations may have negatively affected all of these studies, decreasing the validity of the results and making it difficult to draw reliable conclusions. Except for ziprasidone, SGAs were well tolerated in these short-term trials.

Long-Term Pharmacological Treatments of Anxiety Disorders: An Updated Systematic Review

Many aspects of long-term pharmacological treatments for anxiety disorders (AnxDs) are still debated. We undertook an updated systematic review of long-term pharmacological studies on panic disorder (PD), generalized anxiety disorder (GAD), and social anxiety disorder (SAD). Relevant studies dating from January 1, 2012 to August 31, 2015 were identified using the PubMed database and a review of bibliographies. Of 372 records identified in the search, five studies on PD and 15 on GAD were included in the review. No studies on SAD were found. Our review confirms the usefulness of long-term pharmacological treatments for PD and GAD and suggests that they can provide further improvement over that obtained during short-term therapy. Paroxetine, escitalopram, and clonazepam can be effective for long-term treatment of PD. However, further studies are needed to draw conclusions about the long-term benzodiazepine use in PD, particularly for the possible cognitive side-effects over time. Pregabalin and quetiapine can be effective for long-term treatment of GAD, while preliminary suggestions emerged for agomelatine and vortioxetine. We did not find any evidence for determining the optimal length and/or dosage of medications to minimize the relapse risk. Few investigations have attempted to identify potential predictors of long-term treatment response. Personalized treatments for AnxDs can be implemented using predictive tools to explore those factors affecting treatment response/tolerability heterogeneity, including neurobiological functions/clinical profiles, comorbidity, biomarkers, and genetic features, and to tailor medications according to each patient's unique features.