The role of lithium treatment on comorbid anxiety symptoms in patients with bipolar depression.

BACKGROUND: Comorbid anxiety is pervasive and carries an immense psychosocial burden for patients with bipolar disorder. Despite this, trials reporting anxiety-related outcomes in this population are uncommon, particularly with regards to monotherapies. METHODS: Patients (n = 31) with both bipolar I or II disorder in current depressive episodes were enrolled in a six-week, open-label, single-center trial assessing the efficacy of lithium monotherapy in treating symptoms depression and comorbid anxiety. Patients were mostly medication-free and lithium-naïve at baseline. RESULTS: Significant improvements in depression (HAMD) and anxiety (HAM-A) were observed at the six-week endpoint, with remission and response rates greater than 50%. There was a positive correlation between endpoint HAM-A scores and HAM-D scores, r = 0.80, (p < 0.01). Improvements were realized at low serum lithium concentrations (0.49 ± 0.20 mEq/L). LIMITATIONS: Lack of placebo control and small sample size warrants validation in larger randomized studies. CONCLUSIONS: Taken in the context of prior evidence, lithium may have an important role in treating comorbid anxiety in bipolar disorder, both as adjunct and monotherapy. Lower doses of lithium may provide equivalent efficacy and enhance tolerability and compliance.

A Novel Refractory Mood Disorders and Electroconvulsive Therapy Elective for Medical Students: Fighting Stigma through Experience.

Treatment resistant mood disorders (TRMD) have a significant impact on patients and society. Electroconvulsive therapy (ECT) has been shown to be effective for treatment resistant depression (TRD). Despite the effectiveness and safety of ECT, there remains significant stigma surrounding its use. Studies worldwide have shown that many medical students receive their knowledge from the media, which often portrays ECT in a negative light, and very few have exposure to ECT prior to their psychiatric clinical rotations. In this article we highlight the importance of medical education and introduce a novel approach in helping to fight the stigma of ECT through educational intervention for medical trainees that combines active, longitudinal and theoretical learning. By ensuring that trainees have a robust education in this arena, we can help them educate patients about treatment options, improve confidence in prescribing and administering these therapies, and ultimately improve patient and societal outcomes.

Ecological momentary assessment of depressive symptoms using the mind.me application: Convergence with the Patient Health Questionnaire-9 (PHQ-9).

Ecological momentary assessment (EMA) for mental disorders, using application-based (app) technology capable of passive and ambient data collection, has been insufficiently evaluated and validated with rigorous, adequately-powered, high-quality studies. Herein, we sought to validate the mind.me application for the assessment of depressive symptoms in adults. Adults (ages 18-65) who self-identified as having clinically significant depressive symptoms [i.e. Patient Health Questionnaire 9 (PHQ-9) ≥ 5] utilized the mind.me app-a mobile phone technology that collects data passively and continuously, and is capable of integrating broad multimodal data [e.g., location variance (e.g. GPS), behavioural (e.g. social network activity), and communication data (e.g. SMS texting, phone calls)]. The primary outcome was predictive accuracy (i.e. convergent validity with depressive symptom measurement, as captured by the PHQ-9). 200 subjects were enrolled in the study (mean age 46 ± 12.71). The average PHQ-9 score was 12.8 ± 6.9. The predictive accuracy of the mind.me app was 0.91 ± 0.06. The sensitivity was 0.98 and the specificity was 0.93. The mind.me app was rated by 200 users as highly usable and informative to their illness. The mind.me app exhibits robust predictive accuracy in detecting depressive symptoms in adults with clinically relevant depressive symptoms. The mind.me app more specifically demonstrates convergence with the PHQ-9.

Intracellular Signaling Cascades in Bipolar Disorder.

Bipolar spectrum disorders carry a significant public health burden. Disproportionately high rates of suicide, incarceration, and comorbid medical conditions necessitate an extraordinary focus on understanding the intricacies of this disease. Elucidating granular, intracellular details seems to be a necessary preamble to advancing promising therapeutic opportunities. In this chapter, we review a wide range of intracellular mechanisms including mitochondrial energetics, calcium signaling, neuroinflammation, the microbiome, neurotransmitter metabolism, glycogen synthase kinase 3-beta (GSK3ß), protein kinase C (PKC) and diacylglycerol (DAG), and neurotrophins (especially BDNF), as well as the glutamatergic, dopaminergic, purinergic, and neurohormonal systems. Owing to the relative lack of understanding and effective therapeutic options compared to the rest of the spectrum, special attention is paid in the chapter to the latest developments in bipolar depression. Likewise, from a therapeutic standpoint, special attention should be paid to the pervasive mechanistic actions of lithium as a means of amalgamating numerous, disparate cascades into a digestible cognitive topology.

A case of mirror image agnosia and mirrored self-misidentification syndrome in schizophrenia without dementia or structural abnormalities.

Delusional misidentification syndrome (DMS) is an umbrella term encompassing a variety of disorders. One rare form of DMS is the delusional misidentification of one's own reflection, known as "mirrored self-misidentification syndrome". In "mirror image agnosia", the ability to identify the image of self and/or others in the mirror is lost, while the ability to identify the mirror itself is preserved. To our knowledge, mirror image agnosia has never been described in a patient with schizophrenia. Herein we present a case of a patient with schizophrenia with severe delusions of both mirrored self-misidentification and mirror image agnosia without any structural abnormalities or dementia.

Corrigendum to "Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review." J Affect Disord. 241 (2018) 519-532.

The authors regret an error in one of the extracted data points in the meta-analysis. The classification accuracy for Serretti et al. (2007) was corrected to 64% (Table 3b). The overall results before and after this correction remain directionally consistent and are summarized below (Figures 2 and 3; Table 2; results subsection 3.6). The authors apologise for any inconvenience caused.

The utility of smartphone-based, ecological momentary assessment for depressive symptoms.

BACKGROUND: Major Depressive Disorder (MDD) is a common and debilitating mood disorder. Individuals with MDD are often misdiagnosed or diagnosed in an untimely manner, exacerbating existing functional impairments. Ecological momentary assessment (EMA) involves the repeated sampling of an individual's symptoms within their natural environment and has been demonstrated to assist in illness assessment and characterization. Capturing data in this way would set the stage for improved treatment outcomes and serve as a complementary resource in the management and treatment of depressive symptoms. METHODS: Online databases PubMed/MedLine and PsycINFO were searched using PRISMA guidelines and combinations of the following keywords: EMA, depression, smartphone app, diagnosing, symptoms, phone, app, ecological momentary assessment, momentary assessment, data mining, unobtrusive, passive data, GPS, sensor. RESULTS: A total of nineteen original articles were identified using our search parameters and ten articles met the inclusion criteria for full-text review. Among the ten relevant studies, three studies evaluated feasibility, seven evaluated detection, and three evaluated treatment of MDD. LIMITATIONS: Limitations include that the design of all of the studies included in this review are non-randomized. It should be noted that most of the studies included were pilot studies and/or exploratory trials lacking a control group. CONCLUSIONS: Available evidence suggests that the use of passive smartphone-based applications may lead to improved management of depressive symptoms. This review aids the creation of new EMA applications, highlights the potential of EMA usage in clinical settings and drug development, emphasizes the importance for regulation of applications in the mental health field, and provides insight into future directions.

Expert Consensus on Screening and Assessment of Cognition in Psychiatry.

During the past two decades, it has been amply documented that neuropsychiatric disorders (NPDs) disproportionately account for burden of illness attributable to chronic non-communicable medical disorders globally. It is also likely that human capital costs attributable to NPDs will disproportionately increase as a consequence of population aging and beneficial risk factor modification of other common and chronic medical disorders (e.g., cardiovascular disease). Notwithstanding the availability of multiple modalities of antidepressant treatment, relatively few studies in psychiatry have primarily sought to determine whether improving cognitive function in MDD improves patient reported outcomes (PROs) and/or is cost effective. The mediational relevance of cognition in MDD potentially extrapolates to all NPDs, indicating that screening for, measuring, preventing, and treating cognitive deficits in psychiatry is not only a primary therapeutic target, but also should be conceptualized as a transdiagnostic domain to be considered regardless of patient age and/or differential diagnosis.

Serum metabolic profiling using small molecular water-soluble metabolites in individuals with schizophrenia: A longitudinal study using a pre-post-treatment design.

AIM: We sought to compare alterations in serum bioenergetic markers within a well-characterized sample of adults with schizophrenia at baseline and after 8 weeks of pharmacological treatment with the hypothesis that treatment would be associated with significant changes in bioenergetic markers given the role of bioenergetic dysfunction in schizophrenia. METHODS: We recruited adults with schizophrenia (n = 122) who had not received pharmacological treatment for at least 1 month prior to enrollment, including drug-naïve (i.e., first-episode) participants and treatment non-adherent participants. Pre- and post-treatment serum samples were analyzed using liquid chromatography-tandem mass spectrometry. RESULTS: Metabolites with the greatest change, when comparing pre- and post-treatment levels, were identified revealing 14 water-soluble metabolites of interest. The composition of these metabolites was: amino acids (n = 6), carnitines (n = 4), polar lipids (n = 3), and organic acid (n = 1). All amino acids and lysophosphatidylcholines (LysoPC) were increased, while the four carnitines - oleoylcarnitine, L-palmitoylcarnitine, linoleyl carnitine, and L-acetylcarnitine - were decreased post-treatment. Of these metabolite biomarkers, six - oleoylcarnitine, linoleyl carnitine, L-acetylcarnitine, LysoPC(15:0), D-glutamic acid, and L-arginine - were identified as having most consistently and predictably changed after 8 weeks of treatment. CONCLUSION: The current study identified several bioenergetic markers that consistently change with pharmacological treatment. These bioenergetic changes may provide further insights into the pathophysiology of schizophrenia along with furthering our understanding of the mechanisms subserving both the effects (e.g., antipsychotic effects) and side-effects (e.g., metabolic syndrome) of antipsychotics.

Cognitive impairment in major depressive disorder.

Cognitive dysfunction is a symptomatic domain identified across many mental disorders. Cognitive deficits in individuals with major depressive disorder (MDD) contribute significantly to occupational and functional disability. Notably, cognitive subdomains such as learning and memory, executive functioning, processing speed, and attention and concentration are significantly impaired during, and between, episodes in individuals with MDD. Most antidepressants have not been developed and/or evaluated for their ability to directly and independently ameliorate cognitive deficits. Multiple interacting neurobiological mechanisms (eg, neuroinflammation) are implicated as subserving cognitive deficits in MDD. A testable hypothesis, with preliminary support, posits that improving performance across cognitive domains in individuals with MDD may improve psychosocial function, workplace function, quality of life, and other patient-reported outcomes, independent of effects on core mood symptoms. Herein we aim to (1) provide a rationale for prioritizing cognitive deficits as a therapeutic target, (2) briefly discuss the neurobiological substrates subserving cognitive dysfunction, and (3) provide an update on current and future treatment avenues.

Evaluating the role of orexins in the pathophysiology and treatment of depression: A comprehensive review.

Orexins are neuropeptides that are postulated to play a central role in the regulation of the sleep-wake cycle, appetite, affect, and reward circuitry. The objectives of the current review are to comprehensively evaluate (1) the potential role of orexins in the pathophysiology of major depressive disorders (MDD) and (2) the orexin system as a novel target in the treatment of MDD. Dysfunction of the sleep-wake cycle is observed as a central feature of MDD pathophysiology. Orexin system disturbances produce sleep-wake dysfunction, as observed in MDD. Orexin antagonists have been shown to treat insomnia effectively without disrupting normal sleep architecture in both preclinical (e.g., animal models) and clinical studies. Orexin antagonists are generally safe, well-tolerated, and associated with an acceptable long-term adverse effect profile with relatively low propensity for tolerance or dependence. Orexin antagonists have also been shown to possess antidepressant-like properties in some animal models of MDD. Extant evidence indicates that orexin-modulating treatments exert pleiotropic effects on multiple neural systems implicated in the phenomenology of mood disorders and suggests orexins as a promising target for investigation and intervention in mood disorders. To date, no human clinical trials evaluating the antidepressant effects of orexin antagonists in MDD have been completed. Given the promising results from preclinical studies, clinical trials are merited to evaluate the antidepressant effects of orexin antagonists in MDD.

Perceived sleep quality predicts cognitive function in adults with major depressive disorder independent of depression severity.

BACKGROUND: The aim of this study was to examine the role of perceived sleep quality in predicting subjective as well as objective cognitive function in adults with major depressive disorder (MDD). METHODS: Adults with recurrent MDD (n = 100) experiencing a major depressive episode of at least moderate severity and age-, sex-, and education-matched healthy controls (HC) (n = 100) were recruited to participate in a clinical trial validating the THINC-integrated tool (THINC-it; NCT02508493) for cognitive function. The THINC-it includes subjective and objective measures of cognitive function. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI). RESULTS: Compared with HC, individuals with MDD reported significantly poorer sleep quality, as assessed by domain and global PSQI scores (all P values <.05). Both perceived sleep quality (P < .001) and depression severity (P = .002) were found to independently predict impairments in subjective cognitive performance. Only perceived sleep quality predicted objective cognitive impairments (P = .017). Exploratory mediation analysis revealed depression severity to be a partial mediator of the relationship between perceived sleep quality and subjective cognitive performance (95% confidence interval [CI]: -0.56, -0.33). CONCLUSIONS: The results indicate that the subjective and objective cognitive impairments are differentially related to perceived sleep quality and depression severity and emphasize the importance of treating sleep disturbances in MDD.

Rapastinel - an investigational NMDA-R modulator for major depressive disorder: evidence to date.

INTRODUCTION: Major depressive disorder (MDD) is a debilitating disorder with increasing prevalence globally. Despite the development of novel treatments for MDD, many patients present with treatment resistant depression (TRD), identified by treatment non-response following one or more adequate trials of an antidepressant. Rapastinel may prove to be a viable treatment for TRD; it has the potential to produce a rapid antidepressant response without serious adverse events and improve functional symptoms. Areas covered: We review the efficacy of rapastinel via completed and on-going clinical trials. The online databases Pubmed, clinicaltrials.gov and clinicaltrialsregister.eu were searched for rapastinel (GLYX-13) treatment in subjects with MDD. Nine clinical trials were identified. Expert opinion: Rapastinel is a novel and potentially transformative treatment for individuals with TRD. There is a limited number of clinical studies so far, but this compound has the potential to provide rapid, reliable and robust antidepressant effects without psychotomimetic and other unwanted side effects. Alternative formulations such as the oral formulation, provide the opportunity for rapastinel to be administered less frequently, i.e. once weekly. Furthermore, the beneficial effects on measures of cognition and suicidality so far, represent a tremendous advantage.

Recognition and Treatment of Cognitive Dysfunction in Major Depressive Disorder.

Major Depressive Disorder (MDD) is a prevalent, chronic, disabling, and multidimensional mental disorder. Cognitive dysfunction represents a core diagnostic and symptomatic criterion of MDD, and is a principal determinant of functional non-recovery. Cognitive impairment has been observed to persist despite remission of mood symptoms, suggesting dissociability of mood and cognitive symptoms in MDD. Recurrent impairments in several domains including, but not limited to, executive function, learning and memory, processing speed, and attention and concentration, are associated with poor psychosocial and occupational outcomes. Attempts to restore premorbid functioning in individuals with MDD requires regular screenings and assessment of objective and subjective measures of cognition by clinicians. Easily accessible and cost-effective tools such as the THINC-integrated tool (THINC-it) are suitable for use in a busy clinical environment and appear to be promising for routine usage in clinical settings. However, antidepressant treatments targeting specific cognitive domains in MDD have been insufficiently studied. While select antidepressants, e.g., vortioxetine, have been demonstrated to have direct and independent pro-cognitive effects in adults with MDD, research on additional agents remains nascent. A comprehensive clinical approach to cognitive impairments in MDD is required. The current narrative review aims to delineate the importance and relevance of cognitive dysfunction as a symptomatic target for prevention and treatment in the phenomenology of MDD.

Characterizing, Assessing, and Treating Cognitive Dysfunction in Major Depressive Disorder.

LEARNING OBJECTIVES: After participating in this activity, learners should be better able to:• Characterize cognitive dysfunction in patients with major depressive disorder.• Evaluate approaches to treating cognitive dysfunction in patients with major depressive disorder. ABSTRACT: Cognitive dysfunction is a core psychopathological domain in major depressive disorder (MDD) and is no longer considered to be a pseudo-specific phenomenon. Cognitive dysfunction in MDD is a principal determinant of patient-reported outcomes, which, hitherto, have been insufficiently targeted with existing multimodal treatments for MDD. The neural structures and substructures subserving cognitive function in MDD overlap with, yet are discrete from, those subserving emotion processing and affect regulation. Several modifiable factors influence the presence and extent of cognitive dysfunction in MDD, including clinical features (e.g., episode frequency and illness duration), comorbidity (e.g., obesity and diabetes), and iatrogenic artefact. Screening and measurement tools that comport with the clinical ecosystem are available to detect and measure cognitive function in MDD. Notwithstanding the availability of select antidepressants capable of exerting procognitive effects, most have not been sufficiently studied or rigorously evaluated. Promising pharmacological avenues, as well as psychosocial, behavioral, chronotherapeutic, and complementary alternative approaches, are currently being investigated.

Applications of machine learning algorithms to predict therapeutic outcomes in depression: A meta-analysis and systematic review.

BACKGROUND: No previous study has comprehensively reviewed the application of machine learning algorithms in mood disorders populations. Herein, we qualitatively and quantitatively evaluate previous studies of machine learning-devised models that predict therapeutic outcomes in mood disorders populations. METHODS: We searched Ovid MEDLINE/PubMed from inception to February 8, 2018 for relevant studies that included adults with bipolar or unipolar depression; assessed therapeutic outcomes with a pharmacological, neuromodulatory, or manual-based psychotherapeutic intervention for depression; applied a machine learning algorithm; and reported predictors of therapeutic response. A random-effects meta-analysis of proportions and meta-regression analyses were conducted. RESULTS: We identified 639 records: 75 full-text publications were assessed for eligibility; 26 studies (n=17,499) and 20 studies (n=6325) were included in qualitative and quantitative review, respectively. Classification algorithms were able to predict therapeutic outcomes with an overall accuracy of 0.82 (95% confidence interval [CI] of [0.77, 0.87]). Pooled estimates of classification accuracy were significantly greater (p < 0.01) in models informed by multiple data types (e.g., composite of phenomenological patient features and neuroimaging or peripheral gene expression data; pooled proportion [95% CI] = 0.93[0.86, 0.97]) when compared to models with lower-dimension data types (pooledproportion=0.68[0.62,0.74]to0.85[0.81,0.88]). LIMITATIONS: Most studies were retrospective; differences in machine learning algorithms and their implementation (e.g., cross-validation, hyperparameter tuning); cannot infer importance of individual variables fed into learning algorithm. CONCLUSIONS: Machine learning algorithms provide a powerful conceptual and analytic framework capable of integrating multiple data types and sources. An integrative approach may more effectively model neurobiological components as functional modules of pathophysiology embedded within the complex, social dynamics that influence the phenomenology of mental disorders.

Probiotics for the treatment of depressive symptoms: An anti-inflammatory mechanism?

During the past decade, there has been renewed interest in the relationship between brain-based disorders, the gut microbiota, and the possible beneficial effects of probiotics. Emerging evidence suggests that modifying the composition of the gut microbiota via probiotic supplementation may be a viable adjuvant treatment option for individuals with major depressive disorder (MDD). Convergent evidence indicates that persistent low-grade inflammatory activation is associated with the diagnosis of MDD as well as the severity of depressive symptoms and probability of treatment response. The objectives of this review are to (1) evaluate the evidence supporting an anti-inflammatory effect of probiotics and (2) describe immune system modulation as a potential mechanism for the therapeutic effects of probiotics in populations with MDD. A narrative review of studies investigating the effects of probiotics on systemic inflammation was conducted. Studies were identified using PubMed/Medline, Google Scholar, and clinicaltrials.gov (from inception to November 2017) using the following search terms (and/or variants): probiotic, inflammation, gut microbiota, and depression. The available evidence suggests that probiotics should be considered a promising adjuvant treatment to reduce the inflammatory activation commonly found in MDD. Several controversial points remain to be addressed including the role of leaky gut, the role of stress exposure, and the role of blood-brain-barrier permeability. Taken together, the results of this review suggest that probiotics may be a potentially beneficial, but insufficiently studied, antidepressant treatment intervention.

Cognitive impairment as measured by the THINC-integrated tool (THINC-it): The association with self-reported anxiety in Major Depressive Disorder.

BACKGROUND AND OBJECTIVES: This study evaluated the association between self-reported anxiety and objective/subjective measures of cognitive performance in adults with Major Depressive Disorder (MDD). METHODS: Acutely depressed subjects with recurrent MDD (n = 100) and age-, sex-, and education-matched healthy controls (HC; n = 100) between the ages of 18 and 65 completed the cross-sectional validation study of the THINC-integrated tool (THINC-it; ClinicalTrials.gov: NCT02508493). Objective cognitive performance was assessed using the THINC-it, and subjective cognitive impairment with the Perceived Deficits Questionnaire for Depression-5-item. Subjects also completed the Generalized Anxiety Disorder-7-item (GAD-7) questionnaire. RESULTS: Subjects with MDD reported significantly more anxiety symptoms, as assessed by the GAD-7, compared to HC (p < 0.001). Linear regression analysis determined that anxiety symptoms significantly accounted for 70.4% of the variability in subjective cognitive impairment, adjusting for depression severity. Moreover, subjects' ratings of the difficulties caused by their anxiety were reported as significantly more severe among subjects with MDD when compared to HC (p < 0.001). Likewise, greater self-reported difficulties with anxiety significantly predicted 57.8% of the variability in subjective cognitive impairment, adjusting for depression severity. Neither anxiety symptoms nor impairment due to anxiety symptoms predicted objective cognitive performance. LIMITATIONS: Subjects were not prospectively verified to have a clinical diagnosis of GAD. Rather, this study examined the relationships between symptoms of generalized anxiety, assessed using a brief screening tool, and subjective and objective cognitive function. CONCLUSIONS: Results from the current study indicate that adults with MDD and high levels of self-reported anxiety are significantly more likely to report experiencing subjective cognitive dysfunction.