Specificity profile of venlafaxine and sertraline in major depression: metaregression of double-blind, randomized clinical trials

Critically appraising for antiracism

Racial bias in research impacts a study’s relevancy, validity and reliability, though presently this aspect is not addressed in critical appraisal tools, and consequently appraisers may not take racial bias into account when assessing a paper’s quality. Drawing on Critical Race Theory (CRT) tenets that racism is ubiquitous and race a social construct, this paper discusses concerns regarding racism in research which have been broadly divided into two categories for critical appraisers to consider: the underrepresentation of minoritised ethnic groups in health studies, especially where minoritised populations see higher rates of disease occurrence and; the utilisation of racial/ethnicity data to interpret disparities in outcomes, including speculation of biological race, the misinterpretation of genetic ancestry as race, and the lack of investigation into social determinants of health, including systemic, institutional and interpersonal forms of racism. The injustices exposed in this paper impact the health of minoritised ethnic groups and are therefore a Black Lives Matter issue. They risk resurrecting dangerous theories regarding biological inferiority among minoritised ethnic populations, as well as hindering study findings. The application of CRT frameworks in health science research quality appraisal are discussed in relation to the above themes – using largely UK-based contexts with supporting examples from the US – followed by recommendations for critically appraising for antiracism. Further information to support critically appraising for antiracism can be found via https://www.criticallyappraisingantiracism.org/.

The molecular pathophysiology of depression and the new therapeutics

Major depressive disorder (MDD) is a highly prevalent and disabling disorder. Despite the many hypotheses proposed to understand the molecular pathophysiology of depression, it is still unclear. Current treatments for depression are inadequate for many individuals, because of limited effectiveness, delayed efficacy (usually two weeks), and side effects. Consequently, novel drugs with increased speed of action and effectiveness are required. Ketamine has shown to have rapid, reliable, and long-lasting antidepressant effects in treatment-resistant MDD patients and represent a breakthrough therapy for patients with MDD; however, concerns regarding its efficacy, potential misuse, and side effects remain. In this review, we aimed to summarize molecular mechanisms and pharmacological treatments for depression. We focused on the fast antidepressant treatment and clarified the safety, tolerability, and efficacy of ketamine and its metabolites for the MDD treatment, along with a review of the potential pharmacological mechanisms, research challenges, and future clinical prospects.

Predicting treatment effects in unipolar depression: A meta-review

There is increasing interest in clinical prediction models in psychiatry, which focus on developing multivariate algorithms to guide personalized diagnostic or management decisions. The main target of these models is the prediction of treatment response to different antidepressant therapies. This is because the ability to predict response based on patients' personal data may allow clinicians to make improved treatment decisions, and to provide more efficacious or more tolerable medications to the right patient. We searched the literature for systematic reviews about treatment prediction in the context of existing treatment modalities for adult unipolar depression, until July 2019. Treatment effect is defined broadly to include efficacy, safety, tolerability and acceptability outcomes. We first focused on the identification of individual predictor variables that might predict treatment response, and second, we considered multivariate clinical prediction models. Our meta-review included a total of 10 systematic reviews; seven (from 2014 to 2018) focusing on individual predictor variables and three focusing on clinical prediction models. These identified a number of sociodemographic, phenomenological, clinical, neuroimaging, remote monitoring, genetic and serum marker variables as possible predictor variables for treatment response, alongside statistical and machine-learning approaches to clinical prediction model development. Effect sizes for individual predictor variables were generally small and clinical prediction models had generally not been validated in external populations. There is a need for rigorous model validation in large external data-sets to prove the clinical utility of models. We also discuss potential future avenues in the field of personalized psychiatry, particularly the combination of multiple sources of data and the emerging field of artificial intelligence and digital mental health to identify new individual predictor variables.

Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Despite several pharmacological options, the clinical outcomes of major depressive disorder (MDD) are often unsatisfactory. Personalized psychiatry attempts to tailor therapeutic interventions according to each patient's unique profile and characteristics. This approach can be a crucial strategy in improving pharmacological outcomes in MDD and overcoming trial-and-error treatment choices. In this narrative review, we evaluate whether sociodemographic (i.e., gender, age, race/ethnicity, and socioeconomic status) and clinical [i.e., body mass index (BMI), severity of depressive symptoms, and symptom profiles] variables that are easily assessable in clinical practice may help clinicians to optimize the selection of antidepressant treatment for each patient with MDD at the early stages of the disorder. We found that several variables were associated with poorer outcomes for all antidepressants. However, only preliminary associations were found between some clinical variables (i.e., BMI, anhedonia, and MDD with melancholic/atypical features) and possible benefits with some specific antidepressants. Finally, in clinical practice, the assessment of sociodemographic and clinical variables considered in our review can be valuable for early identification of depressed individuals at high risk for poor responses to antidepressants, but there are not enough data on which to ground any reliable selection of specific antidepressant class or compounds. Recent advances in computational resources, such as machine learning techniques, which are able to integrate multiple potential predictors, such as individual/ clinical variables, biomarkers, and genetic factors, may offer future reliable tools to guide personalized antidepressant choice for each patient with MDD.

A systematic meta-review of predictors of antidepressant treatment outcome in major depressive disorder

INTRODUCTION

The heterogeneity of symptoms and complex etiology of depression pose a significant challenge to the personalization of treatment. Meanwhile, the current application of generic treatment approaches to patients with vastly differing biological and clinical profiles is far from optimal. Here, we conduct a meta-review to identify predictors of response to antidepressant therapy in order to select robust input features for machine learning models of treatment response. These machine learning models will allow us to learn associations between patient features and treatment response which have predictive value at the individual patient level; this learning can be optimized by selecting high-quality input features for the model. While current research is difficult to directly apply to the clinic, machine learning models built using knowledge gleaned from current research may become useful clinical tools.

METHODS

The EMBASE and MEDLINE/PubMed online databases were searched from January 1996 to August 2017, using a combination of MeSH terms and keywords to identify relevant literature reviews. We identified a total of 1909 articles, wherein 199 articles met our inclusion criteria.

RESULTS

An array of genetic, immune, endocrine, neuroimaging, sociodemographic, and symptom-based predictors of treatment response were extracted, varying widely in clinical utility.

LIMITATIONS

Due to heterogeneous sample sizes, effect sizes, publication biases, and methodological disparities across reviews, we could not accurately assess the strength and directionality of every predictor.

CONCLUSION

Notwithstanding our cautious interpretation of the results, we have identified a multitude of predictors that can be used to formulate a priori hypotheses regarding the input features for a computational model. We highlight the importance of large-scale research initiatives and clinically accessible biomarkers, as well as the need for replication studies of current findings. In addition, we provide recommendations for future improvement and standardization of research efforts in this field.

Cariprazine specificity profile in the treatment of acute schizophrenia: a meta-analysis and meta-regression of randomized-controlled trials

Cariprazine is a new dopamine D2 and D3 receptor partial agonist antipsychotic. Meta-analytic evidence of efficacy in acute schizophrenia and specific groups of patients is lacking. We carried out a meta-analysis in patients with acute schizophrenia to evaluate the efficacy of cariprazine over placebo and active comparators in overall symptoms, positive and negative symptoms and quality of life. Low and high (≥6 mg/day) doses were tested separately. The possible effect of clinical-demographic modulators was also tested. Four studies (2144 patients) were included. Both high and low cariprazine doses proved superior to placebo in all symptom domains. The standardized mean difference (SMD) to placebo showed a modest impact on overall symptoms compared with meta-analytic results for other antipsychotics (SMD was similar to lurasidone, asenapine, ziprasidone and aripiprazole, but lower than risperidone, quetiapine and olanzapine). The SMD to placebo on negative symptoms was superior to many antipsychotics including aripiprazole, with a slightly more relevant effect of cariprazine low doses. This effect was probably on secondary negative symptoms since the short-term follow-up of the studies included. Meta-regression data further refined the compound clinical profile, suggesting that cariprazine may be particularly useful in young patients with a relatively short duration of disease.

Reporting of Sex Effects by Systematic Reviews on Interventions for Depression, Diabetes, and Chronic Pain

Systematic reviews (SRs) have the potential to contribute uniquely to the evaluation of sex and gender differences (termed "sex effects"). This article describes the reporting of sex effects by SRs on interventions for depression, type 2 diabetes mellitus, and chronic pain conditions (chronic low back pain, knee osteoarthritis, and fibromyalgia). It includes SRs published since 1 October 2009 that evaluate medications, behavioral interventions, exercise, quality improvement, and some condition-specific treatments. The reporting of sex effects by primary randomized, controlled trials is also examined. Of 313 eligible SRs (86 for depression, 159 for type 2 diabetes mellitus, and 68 for chronic pain), few (n = 29) reported sex effects. Most SRs reporting sex effects used metaregression, whereas 9 SRs used subgroup analysis or individual-patient data meta-analysis. The proportion of SRs reporting the sex distribution of primary studies varied from a low of 31% (n = 8) for low back pain to a high of 68% (n = 23) for fibromyalgia. Primary randomized, controlled trials also infrequently reported sex effects, and most lacked an adequate sample size to examine them. Therefore, all SRs should report the proportion of women enrolled in primary studies and evaluate sex effects using appropriate methods whenever power is adequate.

Double-Blind Randomized Clinical Trial of the Efficacy of Venlafaxine Versus Citalopram in the Treatment of the Acute Phase of Major Depressive Disorder

Background:

There are many antidepressant medications with different side-effects and efficacy profiles.

Objectives:

In this study, we compared the efficacy of citalopram and venlafaxine in major depression, which has not yet been studied in Iran.

Patients and Methods:

In this double-blind, randomized controlled trial study, 39 patients aged 18-54 year old with major depressive disorder were randomly allocated into two groups in Yazd City, Iran, between March 2011 and December 2012. A total of 16 patients were treated with velafaxine and 23 patients were treated with citalopram for 8 weeks. Hamilton Depression Rating Scale (HDRS) questionnaire was used for monitoring depression severity. Data were analyzed by SPSS version 20.0 software using Mann Whitney U test and chi-square statistical tests.

Results:

The HDRS scores were decreased significantly in each group after 8 weeks of treatment (P = 0.001). However, there was no significant difference considering the score of HDRS (P = 0.110). Ten patients in the venlafaxine group and two patients in the citalopram group stopped using medication, all due to nausea or vomiting, or both, and the rate of these two side-effects was significantly higher in the venlafaxine group (P = 0.010).

Conclusions:

The efficacy of venlafaxine and citalopram are almost the same, but compliance for the use of medication, such as nausea and vomiting, in patients using venlafaxine is much higher than the citalopram group. Therefore, this implies that citalopram could be a safer antidepressant for patients suffering from major depression.

[Epigenetics and drug addiction: a focus on MeCP2 and on histone acetylation]

Chronic drug exposure alters gene expression in the brain, which is believed to underlie compulsive drug seeking and drug taking behavior. Recent evidence shows that drug-induced long-term neuroadaptations in the brain are mediated in part by epigenetic mechanisms. By remodeling chromatin, this type of regulation contributes to drug-induced synaptic plasticity that translates into behavioral modifications. How drug-induced alterations in DNA methylation regulate gene expression is reviewed here, with a focus on MeCP2, a protein binding methylated DNA. The importance of histone modifications, especially acetylation is also discussed, with an emphasis on the effects of inhibitors of histone deacetylases on drug-induced behavioral changes. The precise identification of the epigenetic mechanisms that are under the control of drugs of abuse may help to uncover novel targets for the treatment of drug seeking and relapse.

Effect of the fragrance inhalation of essential oil from Asarum heterotropoides on depression-like behaviors in mice

Background

Psychological stressors may cause affective disorders, such as depression and anxiety, by altering expressions of corticotropin releasing factor (CRF), serotonin (5-HT), and tyrosine hydroxylase (TH) in the brain. This study investigated the effects of essential oil from Asarum heterotropoides (EOAH) on depression-like behaviors and brain expressions of CRF, 5-HT, and TH in mice challenged with stress.

Methods

Male ICR mice received fragrance inhalation of EOAH (0.25, 0.5, 1.0, and 2.0 g) for 3 h in the special cage capped with a filter paper before start of the forced swimming test (FST) and tail suspension test (TST). The duration of immobility was measured for the determination of depression-like behavior in the FST and TST. The selective serotonin reuptake inhibitor fluoxetine as positive control was administered at a dose of 15 mg/kg (i.p.) 30 min before start of behavioral testing. Immunoreactivities of CRF, 5-HT, and TH in the brain were also measured using separate groups of mice subjected to the FST.

Results

EOAH at higher doses (1.0 and 2.0 g) reduced immobility time in the FST and TST. In addition, EOAH at a dose of 1.0 g significantly reduced the expected increases in the expression of CRF positive neurons in the paraventricular nucleus and the expression of TH positive neurons in the locus coeruleus, and the expected decreases of the 5-HT positive neurons in the dorsal raphe nucleus.

Conclusion

These results provide strong evidence that EOAH effectively inhibits depression-like behavioral responses, brain CRF and TH expression increases, and brain 5-HT expression decreases in mice challenged with stress.

Ligustrazine attenuates the platelet-derived growth factor-BB-induced proliferation and migration of vascular smooth muscle cells by interrupting extracellular signal-regulated kinase and P38 mitogen-activated protein kinase pathways

The abnormal proliferation and migration of vascular smooth muscle cells (VSMCs) leads to intimal thickening of the aorta and is, therefore, important in the development of arteriosclerosis. As a result, the use of antiproliferative and antimigratory agents for VSMCs offers promise for the treatment of vascular disorders. Although several studies have demonstrated that ligustrazine may be used to treat heart and blood vessel diseases, the detailed mechanism underlying its actions remain to be elucidated. In the present study, the inhibitory effect of ligustrazine on platelet-derived growth factor (PDGF)-BB-stimulated VSMC proliferation and migration, and the underlying mechanisms were investigated. The findings demonstrated that ligustrazine significantly inhibited PDGF-BB-stimulated VSMC proliferation. VSMCs dedifferentiated into a proliferative phenotype under PDGF-BB stimulation, which was effectively reversed by the administration of ligustrazine. In addition, ligustrazine also downregulated the production of nitric oxide and cyclic guanine monophosphate, induced by PDGF-BB. Additionally, ligustrazine significantly inhibited PDGF-BB-stimulated VSMC migration. Mechanistic investigation indicated that the upregulation of cell cycle-associated proteins and the activation of the extracellular signal-regulated kinase (ERK) and P38 mitogen-activated protein kinase (MAPK) signaling induced by PDGF-BB was suppressed by the administration of ligustrazine. In conclusion, the present study, demonstrated for the first time, to the best of our knowledge, that ligustrazine downregulated PDGF-BB-induced VSMC proliferation and migration partly, at least, through inhibiting the activation of the ERK and P38 MAPK signaling.

Effects of acute ethanol exposure on anxiety measures and epigenetic modifiers in the extended amygdala of adolescent rats

Epigenetic mechanisms appear to play an important role in neurodevelopment. We investigated the effects of acute ethanol exposure on anxiety measures and function of histone deacetylases (HDAC) and DNA methyltransferases (DNMT) in the amygdala and bed nucleus of stria terminalis (BNST) of adolescent rats. One hour after ethanol exposure, rats were subjected to anxiety measures. A subset of adolescent rats was exposed to two doses (24 h apart) of ethanol (2 g/kg) to measure rapid ethanol tolerance to anxiolysis. The HDAC and DNMT activities and mRNA levels of DNMT isoforms were measured in the amygdala and BNST. The lower dose of ethanol (1 g/kg) produced neither anxiolysis, nor inhibited the HDAC and DNMT activities in the amygdala and BNST, except DNMT activity in BNST was attenuated. Anxiolysis by ethanol was observed at 2 and 2.25 g/kg, whereas higher doses (2.5 and 3 g/kg) were found to be sedative. DNMT activity in the amygdala and BNST, and nuclear HDAC activity in the amygdala, but not in the BNST were also inhibited by these doses of ethanol. A lack of tolerance was observed on ethanol-induced inhibition of DNMT activity in the amygdala and BNST, and nuclear HDAC activity in the amygdala, as well to anxiolysis produced by ethanol (2 g/kg). The DNMT1, DNMT3a, and DNMT3b mRNA expression in the amygdala was not affected by either 1or 2 doses of 2 g/kg. However, DNMT1 and DNMT3a expression in the BNST was increased, whereas DNMT3l mRNA was decreased in the amygdala, after 2 doses of 2 g/kg ethanol. These results suggest that reduced sensitivity to anxiolysis and the lack of rapid tolerance to the anxiolytic effects of ethanol and inhibition of HDAC and DNMT functions may play a role in engaging adolescents in binge drinking patterns.

Lipid peroxidation in psychiatric illness: overview of clinical evidence

The brain is known to be sensitive to oxidative stress and lipid peroxidation. While lipid peroxidation has been shown to contribute to many disease processes, its role in psychiatric illness has not been investigated until recently. In this paper, we provide an overview of lipid peroxidation in the central nervous system as well as clinical data supporting a link between lipid peroxidation and disorders such as schizophrenia, bipolar disorder, and major depressive disorder. These data support further investigation of lipid peroxidation in the effort to uncover therapeutic targets and biomarkers of psychiatric disease.