Pretreatment Reward Sensitivity and Frontostriatal Resting-State Functional Connectivity Are Associated With Response to Bupropion After Sertraline Nonresponse

The computational structure of consummatory anhedonia

Anhedonia is a reduction in enjoyment, motivation, or interest. It is common across mental health disorders and a harbinger of poor treatment outcomes. The enjoyment aspect, termed 'consummatory anhedonia', in particular poses fundamental questions about how the brain constructs rewards: what processes determine how intensely a reward is experienced? Here, we outline limitations of existing computational conceptualisations of consummatory anhedonia. We then suggest a richer reinforcement learning (RL) account of consummatory anhedonia with a reconceptualisation of subjective hedonic experience in terms of goal progress. This accounts qualitatively for the impact of stress, dysfunctional cognitions, and maladaptive beliefs on hedonic experience. The model also offers new views on the treatments for anhedonia.

Translational In Vivo Assays in Behavioral Biology

The failure of preclinical research to advance successful candidate medications in psychiatry has created a paradigmatic crisis in psychiatry. The Research Domain Criteria (RDoC) initiative was designed to remedy this situation with a neuroscience-based approach that employs multimodal and cross-species in vivo methodology to increase the probability of translational findings and, consequently, drug discovery. The present review underscores the feasibility of this methodological approach by briefly reviewing, first, the use of multidimensional and cross-species methodologies in traditional behavioral pharmacology and, subsequently, the utility of this approach in contemporary neuroimaging and electrophysiology research-with a focus on the value of functionally homologous studies in nonhuman and human subjects. The final section provides a brief review of the RDoC, with a focus on the potential strengths and weaknesses of its domain-based underpinnings. Optimistically, this mechanistic and multidimensional approach in neuropsychiatric research will lead to novel therapeutics for the management of neuropsychiatric disorders.

Do We Need a Novel Framework for Classifying Psychopathology? A Discussion Paper

Introduction

The ICD-11 and DSM-5 are the leading systems for the classification of mental disorders, and their relevance for clinical work and research, as well as their impact for policy making and legal questions, has increased considerably. In recent years, other frameworks have been proposed to supplement or even replace the ICD and the DSM, raising many questions regarding clinical utility, scientific relevance, and, at the core, how best to conceptualize mental disorders.

Method

As examples of the new approaches that have emerged, here we introduce the Hierarchical Taxonomy of Psychopathology (HiTOP), the Research Domain Criteria (RDoC), systems and network approaches, process-based approaches, as well as a new approach to the classification of personality disorders.

Results and Discussion

We highlight main distinctions between these classification frameworks, largely related to different priorities and goals, and discuss areas of overlap and potential compatibility. Synergies among these systems may provide promising new avenues for research and clinical practice.

Brain connectivity in major depressive disorder: a precision component of treatment modalities?

Major depressive disorder (MDD) is a very prevalent mental disorder that imposes an enormous burden on individuals, society, and health care systems. Most patients benefit from commonly used treatment methods such as pharmacotherapy, psychotherapy, electroconvulsive therapy (ECT), and repetitive transcranial magnetic stimulation (rTMS). However, the clinical decision on which treatment method to use remains generally informed and the individual clinical response is difficult to predict. Most likely, a combination of neural variability and heterogeneity in MDD still impedes a full understanding of the disorder, as well as influences treatment success in many cases. With the help of neuroimaging methods like functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI), the brain can be understood as a modular set of functional and structural networks. In recent years, many studies have investigated baseline connectivity biomarkers of treatment response and the connectivity changes after successful treatment. Here, we systematically review the literature and summarize findings from longitudinal interventional studies investigating the functional and structural connectivity in MDD. By compiling and discussing these findings, we recommend the scientific and clinical community to deepen the systematization of findings to pave the way for future systems neuroscience roadmaps that include brain connectivity parameters as a possible precision component of the clinical evaluation and therapeutic decision.

A sex-specific genome-wide association study of depression phenotypes in UK Biobank

There are marked sex differences in the prevalence, phenotypic presentation and treatment response for major depression. While genome-wide association studies (GWAS) adjust for sex differences, to date, no studies seek to identify sex-specific markers and pathways. In this study, we performed a sex-stratified genome-wide association analysis for broad depression with the UK Biobank total participants (N = 274,141), including only non-related participants, as well as with males (N = 127,867) and females (N = 146,274) separately. Bioinformatics analyses were performed to characterize common and sex-specific markers and associated processes/pathways. We identified 11 loci passing genome-level significance (P < 5 × 10-8) in females and one in males. In both males and females, genetic correlations were significant between the broad depression GWA and other psychopathologies; however, correlations with educational attainment and metabolic features including body fat, waist circumference, waist-to-hip ratio and triglycerides were significant only in females. Gene-based analysis showed 147 genes significantly associated with broad depression in the total sample, 64 in the females and 53 in the males. Gene-based analysis revealed "Regulation of Gene Expression" as a common biological process, but suggested sex-specific molecular mechanisms. Finally, sex-specific polygenic risk scores (PRSs) for broad depression outperformed total and the opposite sex PRSs in the prediction of broad major depressive disorder. These findings provide evidence for sex-dependent genetic pathways for clinical depression as well as for health conditions comorbid with depression.

New and emerging approaches to treat psychiatric disorders

Psychiatric disorders are highly prevalent, often devastating diseases that negatively impact the lives of millions of people worldwide. Although their etiological and diagnostic heterogeneity has long challenged drug discovery, an emerging circuit-based understanding of psychiatric illness is offering an important alternative to the current reliance on trial and error, both in the development and in the clinical application of treatments. Here we review new and emerging treatment approaches, with a particular emphasis on the revolutionary potential of brain-circuit-based interventions for precision psychiatry. Limitations of circuit models, challenges of bringing precision therapeutics to market and the crucial advances needed to overcome these obstacles are presented.

Dynamic Resting-State Network Biomarkers of Antidepressant Treatment Response

BACKGROUND

Delivery of effective antidepressant treatment has been hampered by a lack of objective tools for predicting or monitoring treatment response. This study aimed to address this gap by testing novel dynamic resting-state functional network markers of antidepressant response.

METHODS

The Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study randomized adults with major depressive disorder to 8 weeks of either sertraline or placebo, and depression severity was evaluated longitudinally. Participants completed resting-state neuroimaging pretreatment and again after 1 week of treatment (n = 259 eligible for analyses). Coactivation pattern analyses identified recurrent whole-brain states of spatial coactivation, and computed time spent in each state for each participant was the main dynamic measure. Multilevel modeling estimated the associations between pretreatment network dynamics and sertraline response and between early (pretreatment to 1 week) changes in network dynamics and sertraline response.

RESULTS

Dynamic network markers of early sertraline response included increased time in network states consistent with canonical default and salience networks, together with decreased time in network states characterized by coactivation of cingulate and ventral limbic or temporal regions. The effect of sertraline on depression recovery was mediated by these dynamic network changes. In contrast, early changes in dynamic functioning of corticolimbic and frontoinsular-default networks were related to patterns of symptom recovery common across treatment groups.

CONCLUSIONS

Dynamic resting-state markers of early antidepressant response or general recovery may assist development of clinical tools for monitoring and predicting effective intervention.

Exploration of baseline and early changes in neurocognitive characteristics as predictors of treatment response to bupropion, sertraline, and placebo in the EMBARC clinical trial

BACKGROUND

Treatment for major depressive disorder (MDD) is imprecise and often involves trial-and-error to determine the most effective approach. To facilitate optimal treatment selection and inform timely adjustment, the current study investigated whether neurocognitive variables could predict an antidepressant response in a treatment-specific manner.

METHODS

In the two-stage Establishing Moderators and Biosignatures of Antidepressant Response for Clinical Care (EMBARC) trial, outpatients with non-psychotic recurrent MDD were first randomized to an 8-week course of sertraline selective serotonin reuptake inhibitor or placebo. Behavioral measures of reward responsiveness, cognitive control, verbal fluency, psychomotor, and cognitive processing speeds were collected at baseline and week 1. Treatment responders then continued on another 8-week course of the same medication, whereas non-responders to sertraline or placebo were crossed-over under double-blinded conditions to bupropion noradrenaline/dopamine reuptake inhibitor or sertraline, respectively. Hamilton Rating for Depression scores were also assessed at baseline, weeks 8, and 16.

RESULTS

Greater improvements in psychomotor and cognitive processing speeds within the first week, as well as better pretreatment performance in these domains, were specifically associated with higher likelihood of response to placebo. Moreover, better reward responsiveness, poorer cognitive control and greater verbal fluency were associated with greater likelihood of response to bupropion in patients who previously failed to respond to sertraline.

CONCLUSION

These exploratory results warrant further scrutiny, but demonstrate that quick and non-invasive behavioral tests may have substantial clinical value in predicting antidepressant treatment response.

Toward a Better Understanding of the Mechanisms and Pathophysiology of Anhedonia: Are We Ready for Translation?

Anhedonia-the loss of pleasure or lack of reactivity to pleasurable stimuli-remains a formidable treatment challenge across neuropsychiatric disorders. In major depressive disorder, anhedonia has been linked to poor disease course, worse response to psychological, pharmacological, and neurostimulation treatments, and increased suicide risk. Moreover, although some neural abnormalities linked to anhedonia normalize after successful treatment, several persist-for example, blunted activation of the ventral striatum to reward-related cues and reduced functional connectivity involving the ventral striatum. Critically, some of these abnormalities have also been identified in unaffected, never-depressed children of parents with major depressive disorder and have been found to prospectively predict the first onset of major depression. Thus, neural abnormalities linked to anhedonia may be promising targets for prevention. Despite increased appreciation of the clinical importance of anhedonia and its underlying neural mechanisms, important gaps remain. In this overview, the author first summarizes the extant knowledge about the pathophysiology of anhedonia, which may provide a road map toward novel treatment and prevention strategies, and then highlights several priorities to facilitate clinically meaningful breakthroughs. These include a need for 1) appropriately controlled clinical trials, especially those embracing an experimental therapeutics approach to probe target engagement; 2) novel preclinical models relevant to anhedonia, with stronger translational value; and 3) clinical scales that incorporate neuroscientific advances in our understanding of anhedonia. The author concludes by highlighting important future directions, emphasizing the need for an integrated, collaborative, cross-species, and multilevel approach to tackling anhedonic phenotypes.

Reduced nucleus accumbens functional connectivity in reward network and default mode network in patients with recurrent major depressive disorder

The nucleus accumbens (NAc) is considered a hub of reward processing and a growing body of evidence has suggested its crucial role in the pathophysiology of major depressive disorder (MDD). However, inconsistent results have been reported by studies on reward network-focused resting-state functional MRI (rs-fMRI). In this study, we examined functional alterations of the NAc-based reward circuits in patients with MDD via meta- and mega-analysis. First, we performed a coordinated-based meta-analysis with a new SDM-PSI method for all up-to-date rs-fMRI studies that focused on the reward circuits of patients with MDD. Then, we tested the meta-analysis results in the REST-meta-MDD database which provided anonymous rs-fMRI data from 186 recurrent MDDs and 465 healthy controls. Decreased functional connectivity (FC) within the reward system in patients with recurrent MDD was the most robust finding in this study. We also found disrupted NAc FCs in the DMN in patients with recurrent MDD compared with healthy controls. Specifically, the combination of disrupted NAc FCs within the reward network could discriminate patients with recurrent MDD from healthy controls with an optimal accuracy of 74.7%. This study confirmed the critical role of decreased FC in the reward network in the neuropathology of MDD. Disrupted inter-network connectivity between the reward network and DMN may also have contributed to the neural mechanisms of MDD. These abnormalities have potential to serve as brain-based biomarkers for individual diagnosis to differentiate patients with recurrent MDD from healthy controls.

Making Sense of the Matrix: A Qualitative Assessment and Commentary on Connecting Psychiatric Symptom Scale Items to the Research Domain Criteria (RDoC)

The Research Domain Criteria (RDoC) initiative aims to organize research according to domains of brain function. Dysfunction within these domains leads to psychopathology that is classically measured with rating scales. Examining the correspondence between the specific measures assessed within rating scales and RDoC domains is necessary to assess the needs for new RDoC-focused scales. Such RDoC-focused scales have the potential of allowing translation of this work into the clinical domain of measuring psychopathology and designing treatment. Here, we describe an initial qualitative assessment by a group of 10 clinician-scientists of the alignment between RDoC domains and the items within five commonly used rating scales. In this commentary, we report limited correspondence and make recommendations for future work needed to address these limitations.

Pharmacological Treatments for Anhedonia

Anhedonia - the reduced ability to experience or respond to pleasure - is an important symptom domain for many psychiatric disorders. It is particularly relevant to depression and other mood disorders and it is a diagnostic criterion of a major depressive episode. Developing safe and effective pharmacological interventions for anhedonia is a critical public health need. The current chapter will review the state of the field with respect to both the efficacy of currently available pharmacotherapies for anhedonia and the recent clinical research focusing on new brain targets, including the kappa-opioid receptor and the KCNQ2/3 receptors. The evidence for anti-anhedonic effects of ketamine and psychedelic agents will be reviewed, as well.

Anhedonia in Depression and Bipolar Disorder

Anhedonia is a hallmark feature of depression and is highly prevalent among individuals with mood disorders. The history and neurobiology of anhedonia has been most extensively studied in the context of unipolar Major Depressive Disorder (MDD), with converging lines of evidence indicating that marked anhedonia heralds a more chronic and treatment-refractory illness course. Furthermore, findings from neuroimaging studies suggest that anhedonia in MDD is associated with aberrant reward-related activation in key brain reward regions, particularly blunted reward anticipation-related activation in the ventral striatum. However, the ongoing clinical challenge of treating anhedonia in the context of Bipolar Disorder (BD) also highlights important gaps in our understanding of anhedonia's prevalence, severity, and pathophysiology along the entire mood disorder spectrum. In addition, although current theoretical models posit a key role for reward hyposensitivity in BD depression, unlike studies in MDD, studies in BD do not clearly show evidence for reduced reward-related activation in striatal or other brain regions. Although further research is needed, the evidence to date hints at a divergent pathophysiology for anhedonia in unipolar and bipolar mood disorders, which, if better understood, could lead to significant improvements in the diagnosis and treatment of MDD and BD.

Probabilistic Reinforcement Learning and Anhedonia

Despite the prominence of anhedonic symptoms associated with diverse neuropsychiatric conditions, there are currently no approved therapeutics designed to attenuate the loss of responsivity to previously rewarding stimuli. However, the search for improved treatment options for anhedonia has been reinvigorated by a recent reconceptualization of the very construct of anhedonia, including within the Research Domain Criteria (RDoC) initiative. This chapter will focus on the RDoC Positive Valence Systems construct of reward learning generally and sub-construct of probabilistic reinforcement learning specifically. The general framework emphasizes objective measurement of a subject's responsivity to reward via reinforcement learning under asymmetrical probabilistic contingencies as a means to quantify reward learning. Indeed, blunted reward responsiveness and reward learning are central features of anhedonia and have been repeatedly described in major depression. Moreover, these probabilistic reinforcement techniques can also reveal neurobiological mechanisms to aid development of innovative treatment approaches. In this chapter, we describe how investigating reward learning can improve our understanding of anhedonia via the four RDoC-recommended tasks that have been used to probe sensitivity to probabilistic reinforcement contingencies and how such task performance is disrupted in various neuropsychiatric conditions. We also illustrate how reverse translational approaches of probabilistic reinforcement assays in laboratory animals can inform understanding of pharmacological and physiological mechanisms. Next, we briefly summarize the neurobiology of probabilistic reinforcement learning, with a focus on the prefrontal cortex, anterior cingulate cortex, striatum, and amygdala. Finally, we discuss treatment implications and future directions in this burgeoning area.

Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review

Conventional monoamine-based pharmacotherapy, considered the first-line treatment for major depressive disorder (MDD), has several challenges, including high rates of non-response. To address these challenges, preclinical and clinical studies have sought to characterize antidepressant response through monoamine-independent mechanisms. One striking example is glutamate, the brain's foremost excitatory neurotransmitter: since the 1990s, studies have consistently reported altered levels of glutamate in MDD, as well as antidepressant effects following molecular targeting of glutamatergic receptors. Therapeutically, this has led to advances in the discovery, testing, and clinical application of a wide array of glutamatergic agents, particularly ketamine. Notably, ketamine has been demonstrated to rapidly improve mood symptoms, unlike monoamine-based interventions, and the neurobiological basis behind this rapid antidepressant response is under active investigation. Advances in brain imaging techniques, including functional magnetic resonance imaging, magnetic resonance spectroscopy, and positron emission tomography, enable the identification of the brain network-based characteristics distinguishing rapid glutamatergic modulation from the effect of slow-acting conventional monoamine-based pharmacology. Here, we review brain imaging studies that examine brain connectivity features associated with rapid antidepressant response in MDD patients treated with glutamatergic pharmacotherapies in contrast with patients treated with slow-acting monoamine-based treatments. Trends in recent brain imaging literature suggest that the activity of brain regions is organized into coherent functionally distinct networks, termed intrinsic connectivity networks (ICNs). We provide an overview of major ICNs implicated in depression and explore how treatment response following glutamatergic modulation alters functional connectivity of limbic, cognitive, and executive nodes within ICNs, with well-characterized anti-anhedonic effects and the enhancement of "top-down" executive control. Alterations within and between the core ICNs could potentially exert downstream effects on the nodes within other brain networks of relevance to MDD that are structurally and functionally interconnected through glutamatergic synapses. Understanding similarities and differences in brain ICNs features underlying treatment response will positively impact the trajectory and outcomes for adults suffering from MDD and will facilitate the development of biomarkers to enable glutamate-based precision therapeutics.

Extraversion but not depression predicts reward sensitivity: Revisiting the measurement of anhedonic phenotypes

Recently, increasing efforts have been made to define and measure dimensional phenotypes associated with psychiatric disorders. One example is a probabilistic reward task developed by Pizzagalli, Jahn, and O'Shea (2005) to assess anhedonia, by measuring response to a differential reinforcement schedule. This task has been used in many studies, which have connected blunted reward response in the task to depressive symptoms, across clinical groups and in the general population. The current study attempted to replicate these findings in a large community sample and also investigated possible associations with Extraversion, a personality trait linked to reward sensitivity. Participants (N = 299) completed the probabilistic reward task, as well as the Beck Depression Inventory, Personality Inventory for the DSM-5, Big Five Inventory, and Big Five Aspect Scales. Our direct replication attempts used bivariate correlations and analysis of variance models. Follow-up and extension analyses used structural equation models to assess relations among reward sensitivity, depression, Extraversion, and Neuroticism. No significant associations were found between reward sensitivity and depression, thus failing to replicate previous findings. Reward sensitivity (both modeled as response bias aggregated across blocks and as response bias controlling for baseline) showed positive associations with Extraversion, but not Neuroticism. Findings suggest reward sensitivity as measured by this task may be related primarily to Extraversion and its pathological manifestations, rather than to depression per se, consistent with existing models that conceptualize depressive symptoms as combining features of Neuroticism and low Extraversion. Findings are discussed in broader contexts of dimensional psychopathology frameworks, replicable science, and behavioral task reliability. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Perseverative Cognition in the Positive Valence Systems: An Experimental and Ecological Investigation

Perseverative cognition (PC) is a transdiagnostic risk factor that characterizes both hypo-motivational (e.g., depression) and hyper-motivational (e.g., addiction) disorders; however, it has been almost exclusively studied within the context of the negative valence systems. The present study aimed to fill this gap by combining laboratory-based, computational and ecological assessments. Healthy individuals performed the Probabilistic Reward Task (PRT) before and after the induction of PC or a waiting period. Computational modeling was applied to dissociate the effects of PC on reward sensitivity and learning rate. Afterwards, participants underwent a one-week ecological momentary assessment of daily PC occurrence, as well as anticipatory and consummatory reward-related behavior. Induction of PC led to increased response bias on the PRT compared to waiting, likely due to an increase in learning rate but not in reward sensitivity, as suggested by computational modeling. In daily-life, PC increased the discrepancy between expected and obtained rewards (i.e., prediction error). Current converging experimental and ecological evidence suggests that PC is associated with abnormalities in the functionality of positive valence systems. Given the role of PC in the prediction, maintenance, and recurrence of psychopathology, it would be clinically valuable to extend research on this topic beyond the negative valence systems.

Reward Functioning Abnormalities in Adolescents at High Familial Risk for Depressive Disorders

BACKGROUND

A parental history of major depressive disorder (MDD) is an established risk factor for MDD in youth, and clarifying the mechanisms related to familial risk transmission is critical. Aberrant reward processing is a promising biomarker of MDD risk; accordingly, the aim of this study was to test behavioral measures of reward responsiveness and underlying frontostriatal resting activity in healthy adolescents both with (high-risk) and without (low-risk) a maternal history of MDD.

METHODS

Low-risk and high-risk 12- to 14-year-old adolescents completed a probabilistic reward task (n = 74 low-risk, n = 27 high-risk) and a resting-state functional magnetic resonance imaging scan (n = 61 low-risk, n = 25 high-risk). Group differences in response bias toward reward and resting ventral striatal and medial prefrontal cortex (mPFC) fractional amplitude of low-frequency fluctuations (fALFFs) were examined. Computational modeling was applied to dissociate reward sensitivity from learning rate.

RESULTS

High-risk adolescents showed a blunted response bias compared with low-risk adolescents. Computational modeling analyses revealed that relative to low-risk adolescents, high-risk adolescents exhibited reduced reward sensitivity but similar learning rate. Although there were no group differences in ventral striatal and mPFC fALFFs, groups differed in their relationships between mPFC fALFFs and response bias. Specifically, among high-risk adolescents, higher mPFC fALFFs correlated with a blunted response bias, whereas there was no fALFFs-response bias relationship among low-risk youths.

CONCLUSIONS

High-risk adolescents exhibit reward functioning impairments, which are associated with mPFC fALFFs. The blunted response bias-mPFC fALFFs association may reflect an excessive mPFC-mediated suppression of reward-driven behavior, which may potentiate MDD risk.