Zihang Pan

Targeting cytokines in reduction of depressive symptoms: A comprehensive review

&NA; Heterogeneity in response to conventional antidepressants is a well‐recognized limitation of evidence‐based pharmacological treatments of major depressive disorder (MDD). Abnormal activation of inflammatory pathways is postulated as one likely mechanism contributing to treatment resistance in MDD. In a subset of depressed patients, the balance between pro‐ and anti‐inflammatory cytokines is thought to be altered, causing mood symptoms due to inflammation, as seen in co‐morbid depression associated with inflammatory conditions (e.g. psoriasis, hepatitis C, inflammatory bowel disease, rheumatoid arthritis, ankylosing spondylitis). The objectives of the current narrative review are to critically evaluate the literature about the effects of cytokine blockers on clinical outcomes in MDD and in the reduction of depressive symptom severity in individuals using these medications primarily to treat inflammatory conditions. A small number of clinical trials assessing the effects of cytokine blockers for depression and depressive symptoms have been completed. These trials suggest that in individuals with immune dysfunction (e.g. elevated pro‐inflammatory cytokine levels), cytokine blockers may allow for improved clinical outcomes in MDD that would not be achievable with current conventional antidepressants alone. Additional well‐designed clinical trials to assess the clinical utility of anti‐inflammatory medications for the treatment of depression and depressive symptoms are merited. Further, the use of anti‐inflammatories show promise for disease modifying effects that may alter illness trajectory, rather than solely ameliorating current mood symptoms.

Role of Proinflammatory Cytokines in Dopaminergic System Disturbances, Implications for Anhedonic Features of MDD

Anhedonia, characterized by a loss of interest and/or pleasure in previously enjoyable activities, is an important diagnostic criterion of Major Depressive Disorder (MDD). Converging evidence implicates a causal relationship between proinflammatory cytokines and behavioural disturbances that characterize anhedonia in the context of MDD. Additionally, anhedonia has been implicated in disturbances of key central dopaminergic modulatory pathways. Emerging research into the roles of tetrahydrobiopterin, a cytokine-targeted co-enzyme in the synthesis of dopamine, and kynurenine, a product of inflammation-sensitive breakdown of tryptophan via indoleamine 2, 3-dioxygenase, have shed new light into the role of inflammation in mediating anhedonic behaviours. The following narrative review is not meant to be comprehensive, but highlights the roles of both tetrahydrobiopterin and kynurenine pathways in anhedonia, and discusses a potential mechanism of action via oxidative stress and excitotoxicity. Treatment implications are discussed, with an emphasis on anti-inflammatories as complements to current treatments of anhedonia and MDD.

Predictors of Response to Ketamine in Treatment Resistant Major Depressive Disorder and Bipolar Disorder

Objectives: Extant evidence indicates that ketamine exerts rapid antidepressant effects in treatment-resistant depressive (TRD) symptoms as a part of major depressive disorder (MDD) and bipolar disorder (BD). The identification of depressed sub-populations that are more likely to benefit from ketamine treatment remains a priority. In keeping with this view, the present narrative review aims to identify the pretreatment predictors of response to ketamine in TRD as part of MDD and BD. Method: Electronic search engines PubMed/MEDLINE, ClinicalTrials.gov, and Scopus were searched for relevant articles from inception to January 2018. The search term ketamine was cross-referenced with the terms depression, major depressive disorder, bipolar disorder, predictors, and response and/or remission. Results: Multiple baseline pretreatment predictors of response were identified, including clinical (i.e., Body Mass Index (BMI), history of suicide, family history of alcohol use disorder), peripheral biochemistry (i.e., adiponectin levels, vitamin B12 levels), polysomnography (abnormalities in delta sleep ratio), neurochemistry (i.e., glutamine/glutamate ratio), neuroimaging (i.e., anterior cingulate cortex activity), genetic variation (i.e., Val66Met BDNF allele), and cognitive functioning (i.e., processing speed). High BMI and a positive family history of alcohol use disorder were the most replicated predictors. Conclusions: A pheno-biotype of depression more, or less likely, to benefit with ketamine treatment is far from complete. Notwithstanding, metabolic-inflammatory alterations are emerging as possible pretreatment response predictors of depressive symptom improvement, most notably being cognitive impairment. Sophisticated data-driven computational methods that are iterative and agnostic are more likely to provide actionable baseline pretreatment predictive information.

Pain and major depressive disorder: Associations with cognitive impairment as measured by the THINC-integrated tool (THINC-it)

Abstract Objectives To examine the role of pain on cognitive function in adults with major depressive disorder (MDD). Methods Adults (18–65) with a Diagnostic and Statistical Manual – Fifth Edition (DSM-5)-defined diagnosis of MDD experiencing a current major depressive episode (MDE) were enrolled (nMDD = 100). All subjects with MDD were matched in age, sex, and years of education to healthy controls (HC) (nHC = 100) for comparison. Cognitive function was assessed using the recently validated THINC-integrated tool (THINC-it), which comprises variants of the choice reaction time (i.e., THINC-it: Spotter), One-Back (i.e., THINC-it: Symbol Check), Digit Symbol Substitution Test (i.e., THINC-it: Codebreaker), Trail Making Test – Part B (i.e., THINC-it: Trails), as well as the Perceived Deficits Questionnaire for Depression – 5-item (i.e., THINC-it: PDQ-5-D). A global index of objective cognitive function was computed using objective measures from the THINC-it, while self-rated cognitive deficits were measured using the PDQ-5-D. Pain was measured using a Visual Analogue Scale (VAS). Regression analyses evaluated the role of pain in predicting objective and subjective cognitive function. Results A significant between-group differences on the VAS was observed (p < 0.001), with individuals with MDD reporting higher pain severity as evidenced by higher scores on the VAS than HC. Significant interaction effects were observed between self -rated cognitive deficits and pain ratings (p < 0.001) on objective cognitive performance (after adjusting for MADRS total score), suggesting that pain moderates the association between self-rated and objective cognitive function. Conclusions Results indicated that pain is associated with increased self-rated and objective cognitive deficits in adults with MDD. Implications The study herein provides preliminary evidence demonstrating that adults with MDD reporting pain symptomatology and poorer subjective cognitive function is predictive of poorer objective cognitive performance. THINC-it is capable of detecting cognitive dysfunction amongst adults with MDD and pain.

Comparison of serum essential trace metals between patients with schizophrenia and healthy controls

Preclinical and clinical studies have suggested that essential trace metals (ETMs) play an important role in the pathophysiology of brain-based disorders, including schizophrenia. This case-control study aimed to evaluate the association between ETMs and schizophrenia, and to further examine the association between ETMs and clinical characteristics in schizophrenia. One-hundred and five (nu2009=u2009105) subjects who meet DSM-IV criteria for schizophrenia between the ages of 18 and 40 were recruited for the study. One hundred and six (nu2009=u2009106) age- and sex-matched healthy controls (HCs) were recruited for comparison. Serum concentrations of seven ETMs [i.e. iron (Fe), zinc (Zn), copper (Cu), cobalt (Co), manganese (Mn), nickel (Ni) and molybdenum (Mo)] were evaluated using inductively coupled plasma mass spectrometry, which allows for the quantitative analysis of multiple ETMs at a single time point. Compared to HCs, serum concentrations of Mn and Mo were significantly lower in patients with schizophrenia. In contrast, serum concentrations of Fe and Ni were significantly higher in patients with schizophrenia. Additionally, correlations between specific ETMs and metabolic parameters (particularly those related to liver and renal function) were found in patients with schizophrenia, and the correlations between every two ETMs in HCs were widely interrupted. Differential levels of selected ETMs (i.e., Mn, Mo, and Ni) were identified between patients with schizophrenia and HCs following adjustment for potential confounders. The findings here should therefore be evaluated in future studies.

Therapeutic potential of JAK/STAT pathway modulation in mood disorders

Abstract Convergent evidence demonstrates that immune dysfunction (e.g. chronic low-grade inflammatory activation) plays an important role in the development and progression of mood disorders. The Janus kinase/signal transducers and activators of transcription (JAK/STAT) signaling pathway is a pleiotropic cellular cascade that transduces numerous signals, including signals from the release of cytokines and growth factors. The JAK/STAT signaling pathway is involved in mediating several functions of the central nervous system, including neurogenesis, synaptic plasticity, gliogenesis, and microglial activation, all of which have been implicated in the pathophysiology of mood disorders. In addition, the antidepressant actions of current treatments have been shown to be mediated by JAK/STAT-dependent mechanisms. To date, two JAK inhibitors (JAKinibs) have been approved by the U.S. Food and Drug Administration and are primarily indicated for the treatment of inflammatory conditions such as rheumatoid arthritis. Indirect evidence from studies in populations with inflammatory conditions indicates that JAKinibs significantly improve measures of mood and quality of life. There is also direct evidence from studies in populations with depressive disorders, suggesting that JAK/STAT pathways may be involved in the pathophysiology of depression and that the inhibition of specific JAK/STAT pathways (i.e. via JAKinibs) may be a promising novel treatment for depressive disorders.

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

BACKGROUNDnNo 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.nnnMETHODSnWe 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.nnnRESULTSnWe 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 (pu202f<u202f0.01) 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]).nnnLIMITATIONSnMost 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.nnnCONCLUSIONSnMachine 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.

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

BACKGROUND AND OBJECTIVESnThis study evaluated the association between self-reported anxiety and objective/subjective measures of cognitive performance in adults with Major Depressive Disorder (MDD).nnnMETHODSnAcutely depressed subjects with recurrent MDD (nu202f=u202f100) and age-, sex-, and education-matched healthy controls (HC; nu202f=u202f100) 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.nnnRESULTSnSubjects with MDD reported significantly more anxiety symptoms, as assessed by the GAD-7, compared to HC (pu202f<u202f0.001). 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 (pu202f<u202f0.001). 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.nnnLIMITATIONSnSubjects 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.nnnCONCLUSIONSnResults 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.

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.

Predicting antidepressant response using early changes in cognition: A systematic review

Background: Despite the widespread use of antidepressants in clinical practice, the current trial‐and‐error approach to medication selection contributes to treatment failure and underscores the need to identify reliable predictors of antidepressant response. Since changes in measures of cognition have been reported to occur early in treatment and prior to improvements in overall mood symptoms, the present review aims to determine whether early changes in measures of cognition can predict response in individuals with MDD. Methods: A systematic review of studies evaluating early cognitive change as a predictor of later treatment response in MDD was conducted using PubMed/Medline, Embase and PsychINFO. Results: A total of seven articles were identified. The available evidence suggests the early changes in cognition may predict treatment response in individuals with MDD. This was shown across antidepressant classes (i.e., SSRIs, SNRIs, NRIs, melatonergic antidepressants) and forms of therapy (i.e., pharmacotherapy, rTMS). The results depict an emerging trend towards early changes in facial emotion recognition (i.e., a hot cognitive process) as a predictor of treatment outcome. Limitations: Our qualitative analysis reflects a very limited number of studies. Moreover, there was significant heterogeneity in the evaluation of cognition across studies. Future research should aim to parse out this heterogeneity by evaluating the relative predictive value of different measures of cognition. Conclusion: The identification of reliable early treatment predictors of antidepressant response would be clinically significant, enabling clinicians to more accurately evaluate the efficacy of selected treatment avenues. HIGHLIGHTSCognitive dysfunction is a principal feature and determinant of health outcome in MDD.Cognitive changes have shown to occur prior to improvements in mood symptoms.Early changes in emotional processing may predict treatment response in MDD.