Cognitive neuropsychological theory of antidepressant action: a modern-day approach to depression and its treatment

Treatment-resistant depression: therapeutic options when first-line treatments fail

The Cochrane review by Davies et al aimed to address the lack of clarity on the risks and benefits of switching and augmentation strategies in the pharmacological treatment of treatment-resistant depression in adults who did not respond (or partially responded) to at least 4 weeks of antidepressant treatment at a recommended dose. This commentary assesses their review and their conclusion that augmenting the current antidepressant with mianserin or with an antipsychotic improves depressive symptoms over the short-term (8 to 12 weeks). Their results need to be treated with caution owing to the small body of evidence and individual comparisons supported by one, two or three studies, the limited evidence on long-term effects and the significant gaps in the literature (e.g. a lack of studies assessing dose increases).

Altered effective connectivity of the extended face processing system in depression and its association with treatment response: findings from the YoDA-C randomized controlled trial

BACKGROUND

Depression is commonly associated with fronto-amygdala dysfunction during the processing of emotional face expressions. Interactions between these regions are hypothesized to contribute to negative emotional processing biases and as such have been highlighted as potential biomarkers of treatment response. This study aimed to investigate depression associated alterations to directional connectivity and assess the utility of these parameters as predictors of treatment response.

METHODS

Ninety-two unmedicated adolescents and young adults (mean age 20.1; 56.5% female) with moderate-to-severe major depressive disorder and 88 healthy controls (mean age 19.8; 61.4% female) completed an implicit emotional face processing fMRI task. Patients were randomized to receive cognitive behavioral therapy for 12 weeks, plus either fluoxetine or placebo. Using dynamic causal modelling, we examined functional relationships between six brain regions implicated in emotional face processing, comparing both patients and controls and treatment responders and non-responders.

RESULTS

Depressed patients demonstrated reduced inhibition from the dlPFC to vmPFC and reduced excitation from the dlPFC to amygdala during sad expression processing. During fearful expression processing patients showed reduced inhibition from the vmPFC to amygdala and reduced excitation from the amygdala to dlPFC. Response was associated with connectivity from the amygdala to dlPFC during sad expression processing and amygdala to vmPFC connectivity during fearful expression processing.

CONCLUSIONS

Our study clarifies the nature of face processing network alterations in adolescents and young adults with depression, highlighting key interactions between the amygdala and prefrontal cortex. Moreover, these findings highlight the potential utility of these interactions in predicting treatment response.

The effects of atorvastatin on emotional processing, reward learning, verbal memory and inflammation in healthy volunteers: An experimental medicine study

BACKGROUND

Growing evidence from clinical trials and epidemiological studies suggests that statins can have clinically significant antidepressant effects, potentially related to anti-inflammatory action on several neurobiological structures. However, the underlying neuropsychological mechanisms of these effects remain unexplored.

AIMS

In this experimental medicine trial, we investigated the 7-day effects of the lipophilic statin, atorvastatin on a battery of neuropsychological tests and inflammation in healthy volunteers.

METHODS

Fifty healthy volunteers were randomised to either 7 days of atorvastatin 20 mg or placebo in a double-blind design. Participants were assessed with psychological questionnaires and a battery of well-validated behavioural tasks assessing emotional processing, which is sensitive to putative antidepressant effects, reward learning and verbal memory, as well as the inflammatory marker, C-reactive protein.

RESULTS

Compared to placebo, 7-day atorvastatin increased the recognition (p = 0.006), discriminability (p = 0.03) and misclassifications (p = 0.04) of fearful facial expression, independently from subjective states of mood and anxiety, and C-reactive protein levels. Otherwise, atorvastatin did not significantly affect any other psychological and behavioural measure, nor peripheral C-reactive protein.

CONCLUSIONS

Our results reveal for the first time the early influence of atorvastatin on emotional cognition by increasing the processing of anxiety-related stimuli (i.e. increased recognition, discriminability and misclassifications of fearful facial expression) in healthy volunteers, in the absence of more general effects on negative affective bias. Further studies exploring the effects of statins in depressed patients, especially with raised inflammatory markers, may clarify this finding and inform future clinical trials.

Neuromolecular Underpinnings of Negative Cognitive Bias in Depression

This selective review aims to summarize the recent advances in understanding the neuromolecular underpinnings of biased cognition in depressive disorder. We begin by considering the cognitive correlates of depressed mood and the key brain systems implicated in its development. We then review the core findings across two domains of biased cognitive function in depression: pessimistic judgment bias and abnormal response to negative feedback. In considering their underlying substrates, we focus on the neurochemical mechanisms identified by genetic, molecular and pharmacological challenge studies. We conclude by discussing experimental approaches to the treatment of depression, which are derived largely from an improved understanding of its cognitive substrates.

Systematic review of the effects of evidence-based psychotherapies on neurocognitive functioning in mood disorders

OBJECTIVE

Neurocognitive impairment is considered a core feature of mood disorders. Research has shown that neurocognitive impairment often persists beyond mood symptom resolution and can have significant deleterious effects on interpersonal relationships, academic achievement, occupational functioning and independent living. As such, neurocognitive impairment has become an important target for intervention. In this systematic review, we aimed to examine the extant literature to ascertain whether current standard evidence-based psychotherapies can improve neurocognitive functioning in mood disorders.

METHOD

Studies examining changes in neurocognitive functioning following evidence-based psychotherapy were identified using MEDLINE, PsycINFO and Web of Science databases. Given the heterogeneity of study procedures, treatment protocols and patient samples, a narrative rather than meta-analytic review technique was employed.

RESULTS

Nineteen studies (21 articles) met inclusion criteria. There was preliminary evidence of improved executive functioning following evidence-based psychotherapy for Major Depressive Disorder and Bipolar Disorder. There was also some signal of reduced negative biases in emotional information processing following psychotherapy in depression. Due to methodological variability across studies however, it was difficult to draw clear conclusions.

CONCLUSION

Findings from the current review suggest that evidence-based psychotherapies may influence some aspects of neurocognitive functioning in mood disorders. This continues to be an ongoing area of importance and warrants further research.

Acute Neurofunctional Effects of Escitalopram in Pediatric Anxiety: A Double-Blind, Placebo-Controlled Trial

OBJECTIVE

Amygdala-ventrolateral prefrontal cortex (VLPFC) circuitry is disrupted in pediatric anxiety disorders, yet how selective serotonin reuptake inhibitors (SSRIs) affect this circuitry is unknown. We examined the impact of the SSRI escitalopram on functional connectivity (FC) within this circuit, and whether early FC changes predicted treatment response in adolescents with generalized anxiety disorder (GAD).

METHOD

Resting-state functional magnetic resonance (MR) images were acquired before and after 2 weeks of treatment in 41 adolescents with GAD (12-17 years of age) who received double-blind escitalopram or placebo for 8 weeks. Change in amygdala-based whole-brain FC and anxiety severity were analyzed.

RESULTS

Controlling for age, sex, and pretreatment anxiety, escitalopram increased amygdala-VLPFC connectivity compared to placebo (F = 17.79, p = .002 FWE-corrected). This early FC change predicted 76.7% of the variability in improvement trajectory in patients who received escitalopram (p < .001) but not placebo (p = .169); the predictive power of early amygdala-VLPFC FC change significantly differed between placebo and escitalopram (p = .013). Furthermore, this FC change predicted improvement better than baseline FC or clinical/demographic characteristics. Exploratory analyses of amygdala subfields' FC revealed connectivity of left basolateral amygdala (BLA) -VLPFC (F = 19.64, p < .001 FWE-corrected) and superficial amygdala-posterior cingulate cortex (F = 22.92, p = .001 FWE-corrected) were also increased by escitalopram, but only BLA-VLPFC FC predicted improvement in anxiety over 8 weeks of treatment.

CONCLUSION

In adolescents with GAD, escitalopram increased amygdala-prefrontal connectivity within the first 2 weeks of treatment, and the magnitude of this change predicted subsequent clinical improvement. Early normalization of amygdala-VLPFC circuitry might represent a useful tool for identifying future treatment responders as well as a promising biomarker for drug development.

CLINICAL TRIAL REGISTRATION INFORMATION

Neurofunctional Predictors of Escitalopram Treatment Response in Adolescents With Anxiety; https://www.clinicaltrials.gov/; NCT02818751.

Editorial: The Cognitive Neuropsychological Hypothesis in Pediatric Anxiety and the Advantage of Revealing Early Changes in Brain Mechanisms Associated With Therapeutic Effects

There is a pressing need to improve treatment, and clinical trials should not only focus on efficacy, but also on identifying the underlying mechanisms through which treatments operate.¹ Treatment with a serotonergic antidepressant is commonly used to treat pediatric anxiety disorders, including generalized anxiety disorder (GAD). Serotonergic antidepressants require considerable time to induce clinically observed responses, and tolerability and efficacy are difficult to predict. Risk and precautions have been widely discussed and are weighed against urgent needs for interventions early in life that may prevent recurrent mental health complaints. Drug-induced molecular, cellular, and chemical effects result in neurocognitive changes, which are believed to occur before behavioral changes. Assessments of early neurocognitive changes may therefore be a powerful tool to reveal key mechanisms through which antidepressants work. When the neurofunctional mechanisms believed to cause the symptoms are restored, the clinical manifestation of symptom improvement is expected. The degree of symptom improvement should also follow the degree of positive changes in neurocognitive function. Many patients do not respond early enough in the course of symptom evolution,^2,3 and thus assessments of early neurocognitive mechanisms may guide treatment individualization during titration of doses and effects.

Brain-based mechanisms of late-life depression: Implications for novel interventions

Late-life depression (LLD) is a particularly debilitating illness. Older adults suffering from depression commonly experience poor outcomes in response to antidepressant treatments, medical comorbidities, and declines in daily functioning. This review aims to further our understanding of the brain network dysfunctions underlying LLD that contribute to disrupted cognitive and affective processes and corresponding clinical manifestations. We provide an overview of a network model of LLD that integrates the salience network, the default mode network (DMN) and the executive control network (ECN). We discuss the brain-based structural and functional mechanisms of LLD with an emphasis on their link to clinical subtypes that often fail to respond to available treatments. Understanding the brain networks that underlie these disrupted processes can inform the development of targeted interventions for LLD. We propose behavioral, cognitive, or computational approaches to identifying novel, personalized interventions that may more effectively target the key cognitive and affective symptoms of LLD.

Efficacy of ketamine for major depressive episodes at 2, 4, and 6-weeks post-treatment: A meta-analysis

RATIONALE

Major depressive episodes are severe mood episodes which occur both in major depressive disorder and bipolar I and II disorder. Major depressive episodes are characterized by debilitating symptoms that often persist and interfere with typical daily functioning. Various treatments exist for major depressive episodes; however, most primary pharmacologic treatments may take weeks to months to provide relief from depressive symptoms. Ketamine is a demonstrated treatment for major depressive episodes, as relief from depressive symptoms can occur rapidly following treatment.

OBJECTIVES

Prior meta-analyses have been conducted to analyze the effectiveness of ketamine for the treatment of major depressive episodes, but at the time of this writing, no meta-analysis had been conducted to observe ketamine treatment efficacy beyond 2 weeks.

METHODS

The present meta-analysis evaluated the efficacy of ketamine for the treatment of major depressive episodes; observations of depressive episode severity were analyzed at 2, 4, and 6-weeks post-treatment.

RESULTS

The present meta-analysis observed large effects at 2 weeks (g = -1.28), 4 weeks, (g = -1.28), and 6 weeks (g = -1.36) post-treatment.

CONCLUSIONS

The results from the present meta-analysis indicate that ketamine can be an effective pharmacologic intervention for major depressive episodes, with treatment effects lasting up to 6 weeks post-ketamine administration, which has many positive implications for treatment.

Translating the promise of 5HT4 receptor agonists for the treatment of depression

Animal experimental studies suggest that 5-HT4 receptor activation holds promise as a novel target for the treatment of depression and cognitive impairment. 5-HT4 receptors are post-synaptic receptors that are located in striatal and limbic areas known to be involved in cognition and mood. Consistent with this, 5-HT4 receptor agonists produce rapid antidepressant effects in a number of animal models of depression, and pro-cognitive effects in tasks of learning and memory. These effects are accompanied by molecular changes, such as the increased expression of neuroplasticity-related proteins that are typical of clinically useful antidepressant drugs. Intriguingly, these antidepressant-like effects have a fast onset of their action, raising the possibility that 5-HT4 receptor agonists may be a particularly useful augmentation strategy in the early stages of SSRI treatment. Until recently, the translation of these effects to humans has been challenging. Here, we review the evidence from animal studies that the 5-HT4 receptor is a promising target for the treatment of depression and cognitive disorders, and outline a potential pathway for the efficient and cost-effective translation of these effects into humans and, ultimately, to the clinic.

Early symptomatic improvements as a predictor of response to repeated-dose intravenous ketamine: Results from the Canadian Rapid Treatment Center of Excellence

BACKGROUND

Early symptomatic improvement with monoamine-based antidepressants is predictive of treatment response. The objective of this study was to determine if early symptomatic improvements with intravenous (IV) ketamine predicted treatment response to an acute course of four infusions.

METHOD

134 adults with treatment resistant depression (TRD) received four ketamine infusions over one to two weeks. Depressive symptoms were measured using the Quick Inventory for Depressive Symptomatology Self-Report₁₆ (QIDS-SR₁₆) at baseline and post-infusions 1, 2, 3, and 4. Early improvement was defined as ≥20% reduction in QIDS-SR₁₆ scores after the first or second infusion. Linear models were used to determine whether early improvement was associated with post-infusion 4 QIDS-SR₁₆ scores after controlling for baseline characteristics.

RESULTS

Early improvement post-infusion 1 (β = -3.52, 95% BCa CI [-5.40, -1.78]) and 2 (β = -3.16, 95% BCa CI [-5.75, -1.59]) both significantly predicted QIDS-SR₁₆ scores post-infusion 4. Early improvers had significantly lower QIDS-SR₁₆ scores at post-infusion 4 (post-infusion 1 improvers: M = 9.8, SD = 4.5; post-infusion 2 improvers: M = 10.6, SD = 5.7) compared to non-early improvers (post-infusion 1 non-improvers: M = 13.7, SD = 5.8; post-infusion 2 non-improvers: M = 14.1, SD = 5.3) when controlling for baseline characteristics. The majority (58%) of individuals who did not improve post-infusions 1 or 2 still experienced an antidepressant response or partial response (≥20% reduction in QIDS-SR₁₆) post-infusion 4.

LIMITATIONS

This is a post-hoc analysis of an open-label study.

CONCLUSION

Early improvement was associated with greater antidepressant effects following a course of four ketamine infusions. However, individuals who did not show early improvements still had a high likelihood of experiencing clinically significant symptom reduction after the fourth infusion, suggesting that completing four infusions, regardless of early symptom changes, is appropriate and merited.

Inclusion of genetic variants in an ensemble of gradient boosting decision trees does not improve the prediction of citalopram treatment response

Identifying in advance who is unlikely to respond to a specific antidepressant treatment is crucial to precision medicine efforts. The current work leverages genome-wide genetic variation and machine learning to predict response to the antidepressant citalopram using data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial (n = 1257 with both valid genomic and outcome data). A confirmatory approach selected 11 SNPs previously reported to predict response to escitalopram in a sample different from the current study. A novel exploratory approach selected SNPs from across the genome using nested cross-validation with elastic net logistic regression with a predominantly lasso penalty (alpha = 0.99). SNPs from each approach were combined with baseline clinical predictors and treatment response outcomes were predicted using a stacked ensemble of gradient boosting decision trees. Using pre-treatment clinical and symptom predictors only, out-of-fold prediction of a novel treatment response definition based on STAR*D treatment guidelines was acceptable, AUC = .659, 95% CI [0.629, 0.689]. The inclusion of SNPs using confirmatory or exploratory selection methods did not improve the out-of-fold prediction of treatment response (AUCs were .662, 95% CI [0.632, 0.692] and .655, 95% CI [0.625, 0.685], respectively). A similar pattern of results were observed for the secondary outcomes of the presence or absence of distressing side effects regardless of treatment response and achieving remission or satisfactory partial response, assuming medication tolerance. In the current study, incorporating SNP variation into prognostic models did not enhance the prediction of citalopram response in the STAR*D sample.

Cognition in mood disorders

Cognitive impairment plays a key role in determining the course of illness and functional outcomes in mood disorders. This article summarises and discusses important papers within this thematic series of BJPsych Open that contribute to a greater understanding of the complexity of 'Cognition in Mood Disorders'.

Effect of acute citalopram on self-referential emotional processing and social cognition in healthy volunteers

BACKGROUND

Depression is characterised by negative views of the self. Antidepressant treatment may remediate negative self-schema through increasing processing of positive information about the self. Changes in affective processing during social interactions may increase expression of prosocial behaviours, improving interpersonal communications.

AIMS

To examine whether acute administration of citalopram is associated with an increase in positive affective learning biases about the self and prosocial behaviour.

METHOD

Healthy volunteers (n = 41) were randomised to either an acute 20 mg dose of citalopram or matched placebo in a between-subjects double-blind design. Participants completed computer-based cognitive tasks designed to measure referential affective processing, social cognition and expression of prosocial behaviours.

RESULTS

Participants administered citalopram made more cooperative choices than those administered placebo in a prisoner's dilemma task (β = 20%, 95% CI: 2%, 37%). Exploratory analyses indicated that participants administered citalopram showed a positive bias when learning social evaluations about a friend (β = 4.06, 95% CI: 0.88, 7.24), but not about the self or a stranger. Similarly, exploratory analyses found evidence of increased recall of positive words and reduced recall of negative words about others (β = 2.41, 95% CI: 0.89, 3.93), but not the self, in the citalopram group.

CONCLUSIONS

Participants administered citalopram showed greater prosocial behaviours, increased positive recall and increased positive learning of social evaluations towards others. The increase in positive affective bias and prosocial behaviours towards others may, at least partially, be a mechanism of antidepressant effect. However, we found no evidence that citalopram influenced self-referential processing.