Showing papers on "Escitalopram published in 2020"

Pharmacological Treatment of Anxiety Disorders: The Role of the HPA Axis.

Abstract: Stress in general, and early life stress in particular, has been associated with the development of anxiety and mood disorders. The molecular, biological and psychological links between stress exposure and the pathogenesis of anxiety and mood disorders have been extensively studied, resulting in the search of novel psychopharmacological strategies aimed at targets of the hypothalamic-pituitary-adrenal (HPA) axis. Hyperactivity of the HPA axis has been observed in certain subgroups of patients with anxiety and mood disorders. In addition, the effects of different anti-anxiety agents on various components of the HPA axis has been investigated, including benzodiazepines, tricyclic antidepressants (TCAs), and selective serotonin reuptake inhibitors (SSRIs). For example, benzodiazepines, including clonazepam and alprazolam, have been demonstrated to reduce the activity of corticotrophin releasing factor (CRF) neurons in the hypothalamus. TCAs and SSRIs are also effective anti-anxiety agents and these may act, in part, by modulating the HPA axis. In this regard, the SSRI escitalopram inhibits CRF release in the central nucleus of the amygdala, while increasing glucocorticoid receptor (GRs) density in the hippocampus and hypothalamus. The molecular effects of these anti-anxiety agents in the regulation of the HPA axis, taken together with their clinical efficacy, may provide further understanding about the role of the HPA axis in the pathophysiology of mood and anxiety disorders, paving the way for the development of novel therapeutic strategies.

Use of Machine Learning for Predicting Escitalopram Treatment Outcome From Electroencephalography Recordings in Adult Patients With Depression

Abstract: Importance Social and economic costs of depression are exacerbated by prolonged periods spent identifying treatments that would be effective for a particular patient. Thus, a tool that reliably predicts an individual patient’s response to treatment could significantly reduce the burden of depression. Objective To estimate how accurately an outcome of escitalopram treatment can be predicted from electroencephalographic (EEG) data on patients with depression. Design, Setting, and Participants This prognostic study used a support vector machine classifier to predict treatment outcome using data from the first Canadian Biomarker Integration Network in Depression (CAN-BIND-1) study. The CAN-BIND-1 study comprised 180 patients (aged 18-60 years) diagnosed with major depressive disorder who had completed 8 weeks of treatment. Of this group, 122 patients had EEG data recorded before the treatment; 115 also had EEG data recorded after the first 2 weeks of treatment. Interventions All participants completed 8 weeks of open-label escitalopram (10-20 mg) treatment. Main Outcomes and Measures The ability of EEG data to predict treatment outcome, measured as accuracy, specificity, and sensitivity of the classifier at baseline and after the first 2 weeks of treatment. The treatment outcome was defined in terms of change in symptom severity, measured by the Montgomery-Asberg Depression Rating Scale, before and after 8 weeks of treatment. A patient was designated as a responder if the Montgomery-Asberg Depression Rating Scale score decreased by at least 50% during the 8 weeks and as a nonresponder if the score decrease was less than 50%. Results Of the 122 participants who completed a baseline EEG recording (mean [SD] age, 36.3 [12.7] years; 76 [62.3%] female), the classifier was able to identify responders with an estimated accuracy of 79.2% (sensitivity, 67.3%; specificity, 91.0%) when using only the baseline EEG data. For a subset of 115 participants who had additional EEG data recorded after the first 2 weeks of treatment, use of these data increased the accuracy to 82.4% (sensitivity, 79.2%; specificity, 85.5%). Conclusions and Relevance These findings demonstrate the potential utility of EEG as a treatment planning tool for escitalopram therapy. Further development of the classification tools presented in this study holds the promise of expediting the search for optimal treatment for each patient.

Kynurenic acid is a potential overlapped biomarker between diagnosis and treatment response for depression from metabolome analysis

Abstract: Since optimal treatment at an early stage leads to remission of symptoms and recovery of function, putative biomarkers leading to early diagnosis and prediction of therapeutic responses are desired. The current study aimed to use a metabolomic approach to extract metabolites involved in both the diagnosis of major depressive disorder (MDD) and the prediction of therapeutic response for escitalopram. We compared plasma metabolites of MDD patients (n = 88) with those in healthy participants (n = 88) and found significant differences in the concentrations of 20 metabolites. We measured the Hamilton Rating Scale for Depression (HRSD) on 62 patients who completed approximately six-week treatment with escitalopram before and after treatment and found that kynurenic acid and kynurenine were significantly and negatively associated with HRSD reduction. Only one metabolite, kynurenic acid, was detected among 73 metabolites for overlapped biomarkers. Kynurenic acid was lower in MDD, and lower levels showed a better therapeutic response to escitalopram. Kynurenic acid is a metabolite in the kynurenine pathway that has been widely accepted as being a major mechanism in MDD. Overlapping biomarkers that facilitate diagnosis and prediction of the treatment response may help to improve disease classification and reduce the exposure of patients to less effective treatments in MDD.

New generation antidepressants for depression in children and adolescents: a network meta-analysis

Abstract: Background Major depressive disorders have a significant impact on children and adolescents, including on educational and vocational outcomes, interpersonal relationships, and physical and mental health and well-being. There is an association between major depressive disorder and suicidal ideation, suicide attempts, and suicide. Antidepressant medication is used in moderate to severe depression; there is now a range of newer generations of these medications. Objectives To investigate, via network meta-analysis (NMA), the comparative effectiveness and safety of different newer generation antidepressants in children and adolescents with a diagnosed major depressive disorder (MDD) in terms of depression, functioning, suicide-related outcomes and other adverse outcomes. The impact of age, treatment duration, baseline severity, and pharmaceutical industry funding was investigated on clinician-rated depression (CDRS-R) and suicide-related outcomes. Search methods We searched the Cochrane Common Mental Disorders Specialised Register, the Cochrane Library (Central Register of Controlled Trials (CENTRAL) and Cochrane Database of Systematic Reviews (CDSR)), together with Ovid Embase, MEDLINE and PsycINFO till March 2020. Selection criteria Randomised trials of six to 18 year olds of either sex and any ethnicity with clinically diagnosed major depressive disorder were included. Trials that compared the effectiveness of newer generation antidepressants with each other or with a placebo were included. Newer generation antidepressants included: selective serotonin reuptake inhibitors; selective norepinephrine reuptake inhibitors (SNRIs); norepinephrine reuptake inhibitors; norepinephrine dopamine reuptake inhibitors; norepinephrine dopamine disinhibitors (NDDIs); and tetracyclic antidepressants (TeCAs). Data collection and analysis Two reviewers independently screened titles/abstracts and full texts, extracted data, and assessed risk of bias. We analysed dichotomous data as Odds Ratios (ORs), and continuous data as Mean Difference (MD) for the following outcomes: depression symptom severity (clinician rated), response or remission of depression symptoms, depression symptom severity (self-rated), functioning, suicide related outcomes and overall adverse outcomes. Random-effects network meta-analyses were conducted in a frequentist framework using multivariate meta-analysis. Certainty of evidence was assessed using Confidence in Network Meta-analysis (CINeMA). We used "informative statements" to standardise the interpretation and description of the results. Main results Twenty-six studies were included. There were no data for the two primary outcomes (depressive disorder established via clinical diagnostic interview and suicide), therefore, the results comprise only secondary outcomes. Most antidepressants may be associated with a "small and unimportant" reduction in depression symptoms on the CDRS-R scale (range 17 to 113) compared with placebo (high certainty evidence: paroxetine: MD -1.43, 95% CI -3.90, 1.04; vilazodone: MD -0.84, 95% CI -3.03, 1.35; desvenlafaxine MD -0.07, 95% CI -3.51, 3.36; moderate certainty evidence: sertraline: MD -3.51, 95% CI -6.99, -0.04; fluoxetine: MD -2.84, 95% CI -4.12, -1.56; escitalopram: MD -2.62, 95% CI -5.29, 0.04; low certainty evidence: duloxetine: MD -2.70, 95% CI -5.03, -0.37; vortioxetine: MD 0.60, 95% CI -2.52, 3.72; very low certainty evidence for comparisons between other antidepressants and placebo). There were "small and unimportant" differences between most antidepressants in reduction of depression symptoms (high- or moderate-certainty evidence). Results were similar across other outcomes of benefit. In most studies risk of self-harm or suicide was an exclusion criterion for the study. Proportions of suicide-related outcomes were low for most included studies and 95% confidence intervals were wide for all comparisons. The evidence is very uncertain about the effects of mirtazapine (OR 0.50, 95% CI 0.03, 8.04), duloxetine (OR 1.15, 95% CI 0.72, 1.82), vilazodone (OR 1.01, 95% CI 0.68, 1.48), desvenlafaxine (OR 0.94, 95% CI 0.59, 1.52), citalopram (OR 1.72, 95% CI 0.76, 3.87) or vortioxetine (OR 1.58, 95% CI 0.29, 8.60) on suicide-related outcomes compared with placebo. There is low certainty evidence that escitalopram may "at least slightly" reduce odds of suicide-related outcomes compared with placebo (OR 0.89, 95% CI 0.43, 1.84). There is low certainty evidence that fluoxetine (OR 1.27, 95% CI 0.87, 1.86), paroxetine (OR 1.81, 95% CI 0.85, 3.86), sertraline (OR 3.03, 95% CI 0.60, 15.22), and venlafaxine (OR 13.84, 95% CI 1.79, 106.90) may "at least slightly" increase odds of suicide-related outcomes compared with placebo. There is moderate certainty evidence that venlafaxine probably results in an "at least slightly" increased odds of suicide-related outcomes compared with desvenlafaxine (OR 0.07, 95% CI 0.01, 0.56) and escitalopram (OR 0.06, 95% CI 0.01, 0.56). There was very low certainty evidence regarding other comparisons between antidepressants. Authors' conclusions Overall, methodological shortcomings of the randomised trials make it difficult to interpret the findings with regard to the efficacy and safety of newer antidepressant medications. Findings suggest that most newer antidepressants may reduce depression symptoms in a small and unimportant way compared with placebo. Furthermore, there are likely to be small and unimportant differences in the reduction of depression symptoms between the majority of antidepressants. However, our findings reflect the average effects of the antidepressants, and given depression is a heterogeneous condition, some individuals may experience a greater response. Guideline developers and others making recommendations might therefore consider whether a recommendation for the use of newer generation antidepressants is warranted for some individuals in some circumstances. Our findings suggest sertraline, escitalopram, duloxetine, as well as fluoxetine (which is currently the only treatment recommended for first-line prescribing) could be considered as a first option. Children and adolescents considered at risk of suicide were frequently excluded from trials, so that we cannot be confident about the effects of these medications for these individuals. If an antidepressant is being considered for an individual, this should be done in consultation with the child/adolescent and their family/caregivers and it remains critical to ensure close monitoring of treatment effects and suicide-related outcomes (combined suicidal ideation and suicide attempt) in those treated with newer generation antidepressants, given findings that some of these medications may be associated with greater odds of these events. Consideration of psychotherapy, particularly cognitive behavioural therapy, as per guideline recommendations, remains important.

Individual Differences in Response to Antidepressants: A Meta-analysis of Placebo-Controlled Randomized Clinical Trials

Abstract: Importance Antidepressants are commonly used worldwide to treat major depressive disorder. Symptomatic response to antidepressants can vary depending on differences between individuals; however, this variability may reflect nonspecific or random factors. Objectives To investigate the assumption of systematic variability in symptomatic response to antidepressants and to assess whether this variability is associated with severity of major depressive disorder, antidepressant class, or year of study publication. Data Sources Data used were from a recent network meta-analysis of acute treatment with licensed antidepressants in adults with major depressive disorder. The following databases were searched from inception to January 8, 2016: the Cochrane Central Register of Controlled Trials, CINAHL, Embase, LILACS database, MEDLINE, MEDLINE In-Process, and PsycINFO. Additional sources were international trial registries, drug approval agency websites, and key scientific journals. Study Selection Analysis was restricted to double-blind, randomized placebo-controlled trials with available data at the study’s end point. Data Extraction and Synthesis Baseline and end point means, SDs, number of participants in each group, antidepressant class, and publication year were extracted. The data were analyzed between August 14 and November 18, 2019. Main Outcomes and Measures With the use of validated methods, coefficients of variation were derived for antidepressants and placebo, and their ratios were calculated to compare outcome variability between antidepressant and placebo. Ratios were entered into a random-effects model, with the expectation that response to antidepressants would be more variable than response to placebo. Analysis was repeated after stratifying by baseline severity of depression, antidepressant class (selective serotonin reuptake inhibitors: citalopram, escitalopram, fluoxetine, fluvoxamine, paroxetine, sertraline, and vilazodone; serotonin and norepinephrine reuptake inhibitors: desvenlafaxine and venlafaxine; norepinephrine-dopamine reuptake inhibitor: bupropion; noradrenergic agents: amitriptyline and reboxetine; and other antidepressants: agomelatine, mirtazapine, and trazodone), and publication year. Results In the 87 eligible randomized placebo-controlled trials (17 540 unique participants), there was significantly more variability in response to antidepressants than to placebo (coefficients of variation ratio, 1.14; 95% CI, 1.11-1.17;P Conclusions and Relevance Individual differences may be systematically associated with responses to antidepressants in major depressive disorder beyond placebo effects or statistical factors. This study provides empirical support for identifying moderators and personalizing antidepressant treatment.

The Relationship between Plasma Serotonin and Kynurenine Pathway Metabolite Levels and the Treatment Response to Escitalopram and Desvenlafaxine

Abstract: Introduction The response of patients with major depressive disorders (MDD) to antidepressant treatments have been shown to be affected by multiple factors, including disease severity and inflammation. Increasing evidence indicates that the kynurenine metabolic pathway is activated by inflammation in MDD patients and plays a role in the pathophysiology of depression. Antidepressant treatments have been reported to affect kynurenine pathway metabolite levels as well. This study investigates differential associations between the antidepressant treatment outcome to escitalopram versus desvenlafaxine with the pre-treatment and post-treatment-changes in serotonin and kynurenine pathway metabolite levels. Methods The levels of serotonin and of kynurenine pathway metabolites were measured in plasma using liquid chromatography-mass spectrometry (LC-MS) in 161 currently depressed patients with MDD at baseline and after 8 weeks of treatment with either escitalopram or desvenlafaxine. Treatment response was defined conventionally by a reduction of at least 50% in the Hamilton Depression Rating Scale 21 item (HAMD-21) total score from baseline; remission was defined by reaching a post-treatment HAMD-21 score ≤7. Results Response to escitalopram treatment was associated with higher baseline serotonin levels (p = 0.022), lower baseline kynurenine (Kyn)/tryptophan (Trp) ratio (p = 0.008) and lower baseline quinolinic acid (QuinA)/tryptophan (Trp) ratio (p = 0.047), suggesting a lower inflammation state. Greater improvement in depression symptoms as measured by percent change of HAMD-21 score from baseline was also associated with higher baseline serotonin levels (p = 0.033) in escitalopram treatment arm. Furthermore, remitters to escitalopram treatment showed significant increases in the kynurenic acid (KynA)/3-hydroxykynurenine (3HK) ratio after treatment (p = 0.015). In contrast, response to desvenlafaxine treatment was not associated with any metabolite analyzed. We also confirmed a previous report that plasma serotonin levels are lower in MDD patients compared to healthy controls (p = 0.004) and that the kynurenine plasma level is negatively associated with depression symptom severity (p = 0.047). Conclusions In MDD patients the antidepressant response to escitalopram was positively associated with baseline serotonin levels and inversely associated with activation of the kynurenine pathway. These results appear consistent with previous literature showing that biomarker evidence of inflammation is associated with lower response to antidepressants from the selective serotonin reuptake inhibitor class. Moreover, increases in the kynurenic acid (KynA)/3-hydroxykynurenine (3HK) ratio, which previously has been characterized as a neuroprotective index, were associated with full remission under escitalopram treatment.

Escitalopram in Adolescents With Generalized Anxiety Disorder: A Double-Blind, Randomized, Placebo-Controlled Study

Abstract: BACKGROUND Selective serotonin reuptake inhibitors (SSRIs) are commonly used to treat pediatric anxiety disorders, including generalized anxiety disorder (GAD); however, their efficacy and tolerability are difficult to predict. This study evaluated the efficacy and tolerability of escitalopram in adolescents with GAD (DSM-IV-TR) and the impact of variants in HTR2A and serotonin transporter (SLC6A4) genes and cytochrome P450 2C19 (CYP2C19) phenotypes on response as well as CYP2C19 phenotype on escitalopram pharmacokinetics from February 2015 through November 2018. METHODS Patients were treated with escitalopram (forced titration to 15 mg/d, then flexible titration to 20 mg/d) (n = 26, mean ± SD age: 14.8 ± 1.7 years) or placebo (n = 25, mean ± SD age: 14.9 ± 1.6 years) for 8 weeks. Outcomes were the change in scores on the Pediatric Anxiety Rating Scale (PARS) and Clinical Global Impressions (CGI) scales as well as vital signs and adverse events. Plasma escitalopram and desmethylcitalopram area under the curve during 24 hours (AUC0-24) and maximum concentration (Cmax) were determined and compared across CYP2C19 phenotypes. RESULTS Escitalopram was superior to placebo for mean ± SD baseline-to-endpoint change in PARS (-8.65 ± 1.3 vs -3.52 ± 1.1, P = .005) and CGI scores, and increasing CYP2C19 metabolism was associated with decreases in escitalopram Cmax (P = .07) and AUC0-24 (P < .05). Vital signs, corrected QT interval, and adverse events were similar in patients who received escitalopram and placebo. CONCLUSIONS Escitalopram reduces anxiety symptoms, and pharmacogenetics variables influence the trajectory and magnitude of improvement. Variation in CYP2C19 metabolism accounts for significant differences in escitalopram pharmacokinetics, raising the possibility that CYP2C19 phenotype should be considered when prescribing escitalopram. TRIAL REGISTRATION ClinicalTrials.gov identifier: NCT02818751.

Treatment concerns for psychiatric symptoms in patients with COVID-19 with or without psychiatric disorders.

Abstract: Many psychiatric patients have been infected with COVID-19, and patients with COVID-19 may develop psychiatric symptoms after treatment with antiviral drugs. Given the tolerability and minimal P450 interactions, antidepressants (i.e., citalopram, escitalopram etc.), antipsychotics (i.e., olanzapine) and valproate can be considered to be safe in combination with antiviral drugs.

A Randomized Double-Blind Placebo-Controlled Trial of Combined Escitalopram and Memantine for Older Adults With Major Depression and Subjective Memory Complaints.

Abstract: Objective Geriatric depression is difficult to treat and frequently accompanied by cognitive complaints that increase risk for dementia. New treatment strategies targeting both depression and cognition are urgently needed. Methods We conducted a 6-month double-blind placebo-controlled trial to assess the efficacy and tolerability of escitalopram + memantine (ESC/MEM) compared to escitalopram + placebo (ESC/PBO) for improving mood and cognitive functioning in depressed older adults with subjective memory complaints (NCT01902004). Primary outcome was change in depression as assessed by the HAM-D post-treatment (at 6 months). Remission was defined as HAM-D ≤6; naturalistic follow-up continued until 12 months. Results Of the 95 randomized participants, 62 completed the 6-month assessment. Dropout and tolerability did not differ between groups. Mean daily escitalopram dose was 11.1 mg (SD = 3.7; range: 5–20 mg). Mean daily memantine dose was 19.3 mg (SD = 2.6; range 10–20 mg). Remission rate within ESC/MEM was 45.8% and 47.9%, compared to 38.3% and 31.9% in ESC/PBO, at 3 and 6 months, respectively (χ2(1) = 2.0, p = 0.15). Both groups improved significantly on the HAM-D at 3, 6, and 12 months, with no observed between-group differences. ESC/MEM demonstrated greater improvement in delayed recall (F(2,82) = 4.3, p = 0.02) and executive functioning (F(2,82) = 5.1, p = 0.01) at 12 months compared to ESC/PBO. Conclusions The combination of memantine with escitalopram was well tolerated and as effective as escitalopram and placebo in improving depression using HAM-D. Combination memantine and escitalopram was significantly more effective than escitalopram and placebo in improving cognitive outcomes at 12 months. Future reports will address the role of biomarkers of aging in treatment response.

Effect of escitalopram on Aβ levels and plaque load in an Alzheimer mouse model.

Abstract: Background Several neurotransmitter receptors activate signaling pathways that alter processing of the amyloid precursor protein (APP) into β-amyloid (Aβ). Serotonin signaling through a subset of serotonin receptors suppresses Aβ generation. We proposed that escitalopram, the most specific selective serotonin reuptake inhibitor (SSRI) that inhibits the serotonin transporter SERT, would suppress Aβ levels in mice. Objectives We hypothesized that acute treatment with escitalopram would reduce Aβ generation, which would be reflected chronically with a significant reduction in Aβ plaque load. Methods We performed in vivo microdialysis and in vivo 2-photon imaging to assess changes in brain interstitial fluid (ISF) Aβ and Aβ plaque size over time, respectively, in the APP/presenilin 1 mouse model of Alzheimer disease treated with vehicle or escitalopram. We also chronically treated mice with escitalopram to determine the effect on plaques histologically. Results Escitalopram acutely reduced ISF Aβ by 25% by increasing α-secretase cleavage of APP. Chronic administration of escitalopram significantly reduced plaque load by 28% and 34% at 2.5 and 5 mg/d, respectively. Escitalopram at 5 mg/kg did not remove existing plaques, but completely arrested individual plaque growth over time. Conclusions Escitalopram significantly reduced Aβ in mice, similar to previous findings in humans treated with acute dosing of an SSRI.

Association between SSRI Antidepressant Use and Reduced Risk of Intubation or Death in Hospitalized Patients with Coronavirus Disease 2019: a Multicenter Retrospective Observational Study

Abstract: Objective To examine the association between antidepressant use and the risk of intubation or death in hospitalized patients with COVID-19. Design Multicenter observational retrospective cohort study. Setting Greater Paris University hospitals, France. Participants 7,345 adults hospitalized with COVID-19 between 24 January and 1 April 2020, including 460 patients (6.3%) who received an antidepressant during the visit. Data source Assistance Publique-Hopitaux de Paris Health Data Warehouse. Main outcome measures The primary endpoint was a composite of intubation or death. We compared this endpoint between patients who received antidepressants and those who did not in time-to-event analyses adjusting for patient characteristics (such as age, sex, and comorbidities), disease severity and other psychotropic medications. The primary analyses were multivariable Cox models with inverse probability weighting. Results Over a mean follow-up of 18.5 days (SD=27.1), 1,331 patients (18.1%) had a primary end-point event. Unadjusted hazard ratio estimates of the association between antidepressant use and the primary outcome stratified by age (i.e., 18-50, 51-70, 71-80, and 81+) were non-significant (all p>0.072), except in the group of patients aged 71-80 years (HR, 0.66; 95% CI, 0.45 to 0.98; p=0.041). Following adjustments, the primary analyses showed a significant association between use of any antidepressant (HR, 0.64; 95% CI, 0.51 to 0.80; p Conclusions SSRI use could be associated with lower risk of death or intubation in hospitalized patients with COVID-19. Double-blind controlled randomized clinical trials of these medications for COVID-19 are needed. What is already known on this topic A prior meta-analysis, mainly including studies on selective serotonin reuptake inhibitors (SSRIs), showed that antidepressant use in major depressive disorder was associated with reduced levels of several pro-inflammatory cytokines, including IL-6, TNF-α, and CCL-2, which have been suggested to be associated with severe COVID-19. A recent in-vitro study supports antiviral effects of the SSRI fluoxetine on SARS-CoV-2. To our knowledge, no study has examined the efficacy of antidepressants in patients with COVID-19. What this study adds In a multicenter observational retrospective study, we examined the association between antidepressant use and the risk of intubation or death in hospitalized patients with COVID-19, adjusting for patient characteristics, disease severity and other psychotropic medications. Antidepressant use was significantly and substantially associated with reduced risk of intubation or death. At the level of antidepressant classes, SSRI use was significantly and substantially associated with reduced risk of intubation or death, but not other antidepressant classes. At the level of antidepressant medications, exposures to the SSRIs fluoxetine and escitalopram, and the SNRI venlafaxine were significantly associated with lower risk of intubation or death. Double-blind controlled randomized clinical trials of these medications for COVID-19 are needed.

Predicting escitalopram monotherapy response in depression: The role of anterior cingulate cortex

Abstract: Neuroimaging biomarkers of treatment efficacy can be used to guide personalized treatment in major depressive disorder (MDD). Escitalopram is recommended as first-line therapy for MDD and severe depression. An interesting hypothesis suggests that the reconfiguration of dynamic brain networks might provide important insights into antidepressant mechanisms. The present study assesses whether the spatiotemporal modulation across functional brain networks could serve as a predictor of effective antidepressant treatment with escitalopram. A total of 106 first-episode, drug-naive patients and 109 healthy controls from three different multicenters underwent resting-state functional magnetic resonance imaging. Patients were considered as responders if they had a reduction of at least 50% in Hamilton Rating Scale for Depression scores at endpoint (>2 weeks). Multilayer modularity framework was applied on the whole brain to construct features in relation to network dynamic characters that were used for multivariate pattern analysis. Linear soft-threshold support vector machine models were used to separate responders from nonresponders. The permutation tests demonstrated the robustness of discrimination performances. The discriminative regions formed a spatially distributed pattern with anterior cingulate cortex (ACC) as the hub in the default mode subnetwork. Interestingly, a significantly larger module allegiance of ACC was also found in treatment responders compared to nonresponders, suggesting high interactivities of ACC to other regions may be beneficial for the recovery after treatment. Consistent results across multicenters confirmed that ACC could serve as a predictor of escitalopram monotherapy treatment outcome, implying strong likelihood of replication in the future.

Alterations in Acylcarnitines, Amines, and Lipids Inform about Mechanism of Action of Citalopram/Escitalopram in Major Depression

Abstract: Selective serotonin reuptake inhibitors (SSRIs) are the first-line treatment for major depressive disorder (MDD), yet their mechanisms of action are not fully understood and their therapeutic benefit varies among individuals. We used a targeted metabolomics approach utilizing a panel of 180 metabolites to gain insights into mechanisms of action and response to citalopram/escitalopram. Plasma samples from 136 participants with MDD enrolled into the Mayo Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) were profiled at baseline and after 8 weeks of treatment. After treatment, we saw increased levels of short-chain acylcarnitines and decreased levels of medium- and long-chain acylcarnitines, suggesting an SSRI effect on β-oxidation and mitochondrial function. Amines – including arginine, proline, and methionine-sulfoxide – were upregulated while serotonin and sarcosine were downregulated, suggesting an SSRI effect on urea cycle, one-carbon metabolism and serotonin uptake. Eighteen lipids within the phosphatidylcholine (PC aa and ae) classes were upregulated. Changes in several lipid and amine levels correlated with changes in 17-item Hamilton Rating Scale for Depression scores (HRSD17). Differences in metabolic profiles at baseline and post-treatment were noted between participants who remitted (HRSD17≤7) and those who gained no meaningful benefits (

Predicting Treatment Outcome in Major Depressive Disorder Using Serotonin 4 Receptor PET Brain Imaging, Functional MRI, Cognitive-, EEG-Based, and Peripheral Biomarkers: A NeuroPharm Open Label Clinical Trial Protocol.

Abstract: Background Between 30 and 50% of patients with major depressive disorder (MDD) do not respond sufficiently to antidepressant regimens. The conventional pharmacological treatments predominantly target serotonergic brain signaling but better tools to predict treatment response and identify relevant subgroups of MDD are needed to support individualized and mechanistically targeted treatment strategies. The aim of this study is to investigate antidepressant-free patients with MDD using neuroimaging, electrophysiological, molecular, cognitive, and clinical examinations and evaluate their ability to predict clinical response to SSRI treatment as individual or combined predictors. Methods We will include 100 untreated patients with moderate to severe depression (>17 on the Hamilton Depression Rating Scale 17) in a non-randomized open clinical trial. We will collect data from serotonin 4 receptor positron emission tomography (PET) brain scans, functional magnetic resonance imaging (fMRI), electroencephalogram (EEG), cognitive tests, psychometry, and peripheral biomarkers, before (at baseline), during, and after 12 weeks of standard antidepressant treatment. Patients will be treated with escitalopram, and in case of non-response at week 4 or intolerable side effects, offered to switch to a second line treatment with duloxetine. Our primary outcome (treatment response) is assessed using the Hamilton depression rating subscale 6-item scores at week 8, compared to baseline. In a subset of the patients (n = ~40), we will re-assess the neurobiological response (using PET, fMRI, and EEG) 8 weeks after initiated pharmacological antidepressant treatment, to map neurobiological signatures of treatment responses. Data from matched controls will either be collected or is already available from other cohorts. Discussion The extensive investigational program with follow-up in this large cohort of participants provides a unique possibility to (a) uncover potential biomarkers for antidepressant treatment response, (b) apply the findings for future stratification of MDD, (c) advance the understanding of pathophysiological underpinnings of MDD, and (d) uncover how putative biomarkers change in response to 8 weeks of pharmacological antidepressant treatment. Our data can pave the way for a precision medicine approach for optimized treatment of MDD and also provides a resource for future research and data sharing. Clinical trial registration The study was registered at clinicaltrials.gov prior to initiation (NCT02869035; 08.16.2016, URL: https://clinicaltrials.gov/ct2/results?cond=&term=NCT02869035&cntry=&state=&city=&dist=).

S-Adenosylmethionine (SAMe) in major depressive disorder (MDD): a clinician-oriented systematic review.

Abstract: Major depressive disorder (MDD) is a recurrent illness with high rates of chronicity, treatment-resistance, and significant economic impact. S-Adenosylmethionine (SAMe), a molecule that is formed naturally in the human body, has shown antidepressant effects and may expand the available options for treating MDD. This systematic review examines the evidence concerning the efficacy of SAMe as monotherapy or in combination with antidepressants. A systematic search in Medline, Psychinfo, AMED, and Cochrane Controlled Trials Register was conducted for any reference recorded up to March 2020. Double-blind, randomised controlled trials, comparing the antidepressant efficacy of SAMe to placebo or/and to other antidepressants, were selected. Two authors evaluated each study independently and then, reconciled findings. Eight trials, with a total of 11 arms and 1011 subjects, evaluating the efficacy of SAMe used as monotherapy or as adjunctive therapy (512 individuals), were included in this review. The study duration ranged between 2 and 12 weeks and the daily dose of SAMe varied from 200 to 3200 mg. Five comparisons evaluated the differences between SAMe and placebo and SAMe resulted significantly better than placebo in three of these studies. Four comparisons evaluated the differences between SAMe and other antidepressants (imipramine or escitalopram) and showed no significant difference. One study showed that SAMe was significantly better than placebo in accelerating the response to imipramine from day 4 to day 12, but the mean scores were not statistically different at the day 14 endpoint. One study showed that SAMe combined with serotonin reuptake inhibitors (SSRI) was better than PBO combined with SSRI. The studies reported only mild, transient or non-clinically relevant side effects. The existing trials of SAMe, used as monotherapy or add on to another antidepressants, have shown encouraging and generally positive results. However, more evidence is necessary before definitive conclusions can be drawn. Larger, double-blind randomised controlled studies are warranted to confirm the antidepressant effectiveness of SAMe.

The impact of pregnancy on the pharmacokinetics of antidepressants: a systematic critical review and meta-analysis

Abstract: Introduction: Pregnancy-related physiological changes exert a crucial impact on the pharmacokinetics of antidepressants; however, the current evidence presents inconsistencies. A clearer understanding of pregnancy-related effects on antidepressant disposition may facilitate the development of guidelines for appropriate dose adjustments during the course of pregnancy based on therapeutic drug monitoring.Areas covered: We systematically reviewed studies comparing antidepressant levels in the same individuals during pregnant and non-pregnant states. Using dose-adjusted plasma concentration measurements, we estimated alteration ratios between the 3rd trimester and baseline (before or after pregnancy). Additionally, we performed a meta-analysis for changes in dose-adjusted concentrations to estimate mean differences.Expert opinion: Data for several antidepressants display clear alteration patterns during pregnancy. On the basis of the alteration ratios trimipramine, fluvoxamine, and nortriptyline show a prominent decrease in dose-adjusted levels, especially in the 3rd trimester. Clomipramine, imipramine, citalopram, and paroxetine show smaller decreases in dose-adjusted concentrations in the third trimester. For escitalopram, venlafaxine and fluoxetine, changes are considered negligible. For sertraline, there was a tendency toward increased dose-adjusted concentrations in pregnancy. Available evidence suffers from major limitations and factors affecting pharmacokinetics have been insufficiently addressed. Further research is required to promote knowledge on pregnancy effects on antidepressant pharmacokinetics.

Predicting treatment dropout after antidepressant initiation

Abstract: Antidepressants exhibit similar efficacy, but varying tolerability, in randomized controlled trials. Predicting tolerability in real-world clinical populations may facilitate personalization of treatment and maximize adherence. This retrospective longitudinal cohort study aimed to determine the extent to which incorporating patient history from electronic health records improved prediction of unplanned treatment discontinuation at index antidepressant prescription. Clinical data were analyzed from individuals from health networks affiliated with two large academic medical centers between March 1, 2008 and December 31, 2014. In total, the study cohorts included 51,683 patients with at least one International Classification of Diseases diagnostic code for major depressive disorder or depressive disorder not otherwise specified who initiated antidepressant treatment. Among 70,121 total medication changes, 16,665 (23.77%) of them were followed by failure to return; maximum risk was observed with paroxetine (27.71% discontinuation), and minimum with venlafaxine (20.78% discontinuation); Mantel–Haenzel χ2 (8 df) = 126.44, p = 1.54e–23 <1e–6. Models incorporating diagnostic and procedure codes and medication prescriptions improved per-medication Areas Under the Curve (AUCs) to a mean of 0.69 [0.64–0.73] (ranging from 0.62 for paroxetine to 0.80 for escitalopram), with similar performance in the second, replication health system. Machine learning applied to coded electronic health records facilitates identification of individuals at high-risk for treatment dropout following change in antidepressant medication. Such methods may assist primary care physicians and psychiatrists in the clinic to personalize antidepressant treatment on the basis not solely of efficacy, but of tolerability.

Effect of escitalopram dose and treatment duration on CSF Aβ levels in healthy older adults: A controlled clinical trial

Abstract: Objective To determine whether treatment with escitalopram compared with placebo would lower CSF β-amyloid 42 (Aβ42) levels. Rationale Serotonin signaling suppresses Aβ42 in animal models of Alzheimer disease (AD) and young healthy humans. In a prospective study in older adults, we examined dose and treatment duration effects of escitalopram. Methods Using lumbar punctures to sample CSF levels before and after a course of escitalopram treatment, cognitively normal older adults (n = 114) were assigned to placebo, 20 mg escitalopram × 2 weeks, 20 mg escitalopram × 8 weeks, or 30 mg escitalopram × 8 weeks; CSF sampled pretreatment and posttreatment and within-subject percent change in Aβ42 was used as the primary outcome in subsequent analyses. Results An overall 9.4% greater reduction in CSF Aβ42 was found in escitalopram-treated compared with placebo-treated groups (p 250 pg/mL). Conclusions Short-term longitudinal doses of escitalopram decreased CSF Aβ42 in cognitively normal older adults, the target group for AD prevention. Clinicaltrials.gov identifier NCT02161458. Classification of evidence This study provides Class II evidence that for cognitively normal older adults, escitalopram decreases CSF Aβ42.

Clinical implications of directly switching antidepressants in well-treated depressed patients with treatment-emergent sexual dysfunction: a comparison between vortioxetine and escitalopram

Abstract: Objective The objective of this work was to describe treatment-emergent sexual dysfunction (TESD) and tolerability following a switch from selective serotonin reuptake inhibitor (SSRI: citalopram, paroxetine, or sertraline) monotherapy to vortioxetine or escitalopram monotherapy in adults with well-treated major depressive disorder (MDD) and SSRI-induced sexual dysfunction. Methods Data were analyzed from the primary study, an 8-week, randomized, double-blind, head-to-head study in which participants with well-treated depressive symptoms but experiencing TESD with SSRIs were directly switched to flexible doses (10/20 mg) of vortioxetine or escitalopram. Sexual functioning was assessed by the Changes in Sexual Functioning Questionnaire-14 (CSFQ-14), efficacy by the Montgomery-Asberg Depression Rating Scale scores (MADRS) and Clinicians Global Impression of Severity/Improvement (CGI-S/CGI-I), and tolerability by adverse events. Efficacy and tolerability were assessed by pre-switch SSRI therapy where possible, and by participant characteristics. Results Greater improvements in TESD were seen in the vortioxetine compared with escitalopram groups based on: participant demographics (≤45 years, women; P = 0.045), prior SSRI treatment (P = 0.044), number of prior major depressive episodes (MDEs) (1-3; P = 0.001), and duration of prior SSRI therapy (>1 year; P = 0.001). Prior SSRI treatment did not appear to influence the incidence or severity of TEAEs, except for nausea. Regardless of prior SSRI, both treatments maintained antidepressant efficacy after 8 weeks. Conclusion Results suggest that vortioxetine is a safe and effective switch therapy for treating SSRI-induced sexual dysfunction in adults with well-treated MDD. Also, improvement in sexual dysfunction with vortioxetine or escitalopram may be influenced by prior SSRI usage, sex, age, and history of MDEs.

Drug-specific risk of severe QT prolongation following acute drug overdose

Abstract: Background: Severe QT prolongation (SQTP) has been identified as a strong predictor of adverse cardiovascular events in acute drug overdose, but drug-specific causes of SQTP in the setting of acute drug overdose remain unclear. We aimed to perform the most definitive study to date describing drug-specific risk of SQTP following acute drug overdose.Methods: This was a prospective multicenter cohort study at >50 hospital sites across the US using the ToxIC Registry between 2015 and 2018. Inclusion criteria were adults (≥18 years) receiving medical toxicology consultation for acute drug overdose. The primary outcome was SQTP, which was defined using the computer automated Bazett QT correction (QTc) on the ECG with the previously validated cut point of 500 milliseconds. Mean difference in QTc was also calculated for specific drugs. Drugs associated with SQTP were analyzed using multivariable logistic regression to control for known confounders of QT risk (age, sex, race, cardiac disease).Results: From 25,303 patients screened, 6473 met inclusion criteria with SQTP occurring in 825 (13%). Drugs associated with increased adjusted odds of SQTP included Class III antidysrhythmics (sotalol), sodium channel blockers (amitriptyline, diphenhydramine, doxepin, imipramine, nortriptyline), antidepressants (bupropion, citalopram, escitalopram, trazodone), antipsychotics (haloperidol, quetiapine), and the antiemetic serotonin antagonist ondansetron.Conclusions: This large US cohort describes drug-specific risk of SQTP following acute drug overdose. Healthcare providers caring for acute drug overdoses from any of these implicated drugs should pay close attention to cardiac monitoring for occurrence of SQTP.

Comparative Remission Rates and Tolerability of Drugs for Generalised Anxiety Disorder: A Systematic Review and Network Meta-analysis of Double-Blind Randomized Controlled Trials.

Abstract: Background: Generalized anxiety disorder (GAD) is one of the most common psychiatric disorders associated with substantial dysfunction and socioeconomic burden. Pharmacotherapy is the first choice for GAD. Remission [Hamilton Anxiety Scale (HAM-A) score ≤7] is regarded as a crucial treatment goal for patients with GAD. There is no up-to-date evidence to compare remission rate and tolerability of all available drugs by using network meta-analysis. Therefore, the goal of our study is to update evidence and determine the best advantageous drugs for GAD in remission rate and tolerability profiles. Method: We performed a systematic review and network meta-analysis of double-blind randomized controlled trials (RCTs). We searched PubMed, EMBASE, Cochrane Central Register of Controlled Trials, Chinese National Knowledge Infrastructure, wanfang data, China Biology Medicine and ClinicalTrials.gov from their inception to March 2020 to identify eligible double-blind, RCTs reporting the outcome of remission in adult patients who received any pharmacological treatment for GAD. Two reviewers independently assessed quality of included studies utilizing the Cochrane Collaboration's risk of bias tool as described in Cochrane Collaboration Handbook and extracted data from all manuscripts. Our outcomes were remission rate (proportion of participants with a final score of seven or less on HAM-A) and tolerability (treatments discontinuations due to adverse events). We calculated summary odds ratios (ORs) and 95% confidence intervals (CIs) of each outcome via pairwise and network meta-analysis with random effects. Results: Overall, 30 studies were included, comprising 32 double-blind RCTs, involving 13,338 participants diagnosed as GAD by DSM-IV criteria. Twenty-eight trials were rated as moderate risk of bias, four trials as low. For remission rate, agomelatine (OR 2.70, 95% CI 1.74-4.19), duloxetine (OR 1.88, 95% CI 1.47-2.40), escitalopram (OR 2.03, 95% CI 1.48-2.78), paroxetine (OR 1.74, 95% CI 1.25-2.42), quetiapine (OR 1.88, 95% CI 1.39-2.55), and venlafaxine (OR 2.28, 95% CI 1.69-3.07) were superior to placebo. For tolerability, sertraline, agomelatine, vortioxetine, and pregabalin were found to be comparable to placebo. However, the others were worse than placebo in terms of tolerability, with ORs ranging between 1.86 (95% CI 1.25-2.75) for tiagabine and 5.98 (95% CI 2.41-14.87) for lorazepam. In head-to-head comparisons, agomelatine, duloxetine, escitalopram, quetiapine, and venlafaxine were more efficacious than tiagabine in terms of remission rate, ORs from 1.66 (95% CI 1.04-2.65) for duloxetine to 2.38 (95% CI 1.32-4.31) for agomelatine. We also found that agomelatine (OR 2.08, 95% CI 1.15-3.75) and venlafaxine (OR 1.76, 95% CI 1.08-2.86) were superior to vortioxetine. Lorazepam and quetiapine were poorly tolerated when compared with other drugs. Conclusions: Of these interventions, only agomelatine manifested better remission with relatively good tolerability but these results were limited by small sample sizes. Duloxetine, escitalopram, venlafaxine, paroxetine, and quetiapine showed better remission but were poorly tolerated.

Indoxyl sulfate, a gut microbiome-derived uremic toxin, is associated with psychic anxiety and its functional magnetic resonance imaging-based neurologic signature

Abstract: Background It is unknown whether indoles, metabolites of tryptophan that are derived entirely from bacterial metabolism in the gut, are associated with symptoms of depression and anxiety. Methods Serum samples (baseline, 12 weeks) were drawn from participants (n=196) randomized to treatment with cognitive behavioral therapy (CBT), escitalopram, or duloxetine for major depressive disorder. Results Baseline indoxyl sulfate abundance was positively correlated with severity of psychic anxiety and total anxiety and with resting state functional connectivity to a network that processes aversive stimuli (which includes the subcallosal cingulate cortex (SCC-FC), bilateral anterior insula, right anterior midcingulate cortex, and the right premotor areas). The relation between indoxyl sulfate and psychic anxiety was mediated only through the metabolite’s effect on the SCC-FC with the premotor area. Baseline indole abundances were unrelated to post-treatment outcome measures, which suggests that CBT and antidepressant medications relieve anxiety via mechanisms unrelated to gut microbiota. Conclusions A peripheral gut microbiome-derived metabolite was associated with altered neural processing and with psychiatric symptom (anxiety) in humans, which provides further evidence that gut microbiome disruption can contribute to neuropsychiatric disorders that may require different therapeutic approaches.

A functional variant in the serotonin receptor 7 gene (HTR7), rs7905446, is associated with good response to SSRIs in bipolar and unipolar depression

Abstract: Predicting antidepressant response has been a clinical challenge for mood disorder. Although several genome-wide association studies have suggested a number of genetic variants to be associated with antidepressant response, the sample sizes are small and the results are difficult to replicate. Previous animal studies have shown that knockout of the serotonin receptor 7 gene (HTR7) resulted in an antidepressant-like phenotype, suggesting it was important to antidepressant action. In this report, in the first stage, we used a cost-effective pooled-sequencing strategy to sequence the entire HTR7 gene and its regulatory regions to investigate the association of common variants in HTR7 and clinical response to four selective serotonin reuptake inhibitors (SSRIs: citalopram, paroxetine, fluoxetine and sertraline) in a retrospective cohort mainly consisting of subjects with bipolar disorder (n = 359). We found 80 single-nucleotide polymorphisms (SNPs) with false discovery rate < 0.05 associated with response to paroxetine. Among the significant SNPs, rs7905446 (T/G), which is located at the promoter region, also showed nominal significance (P < 0.05) in fluoxetine group. GG/TG genotypes for rs7905446 and female gender were associated with better response to two SSRIs (paroxetine and fluoxetine). In the second stage, we replicated this association in two independent prospective samples of SSRI-treated patients with major depressive disorder: the MARS (n = 253, P = 0.0169) and GENDEP studies (n = 432, P = 0.008). The GG/TG genotypes were consistently associated with response in all three samples. Functional study of rs7905446 showed greater activity of the G allele in regulating expression of HTR7. The G allele displayed higher luciferase activity in two neuronal-related cell lines, and estrogen treatment decreased the activity of only the G allele. Electrophoretic mobility shift assay suggested that the G allele interacted with CCAAT/enhancer-binding protein beta transcription factor (TF), while the T allele did not show any interaction with any TFs. Our results provided novel pharmacogenomic evidence to support the role of HTR7 in association with antidepressant response.

Combinatorial Pharmacogenomic Algorithm is Predictive of Citalopram and Escitalopram Metabolism in Patients with Major Depressive Disorder

Abstract: Pharmacogenomic tests used to guide clinical treatment for major depressive disorder (MDD) must be thoroughly validated. One important assessment of validity is the ability to predict medication blood levels, which reflect altered metabolism. Historically, the metabolic impact of individual genes has been evaluated; however, we now know that multiple genes are often involved in medication metabolism. Here, we evaluated the ability of individual pharmacokinetic genes (CYP2C19, CYP2D6, CYP3A4) and a combinatorial pharmacogenomic test (GeneSight Psychotropic®; weighted assessment of all three genes) to predict citalopram/escitalopram blood levels in patients with MDD. Patients from the Genomics Used to Improve DEpression Decisions (GUIDED) trial who were taking citalopram/escitalopram at screening and had available blood level data were included (N=191). In multivariate analysis of the individual genes and combinatorial pharmacogenomic test separately (adjusted for age, smoking status), the F statistic for the combinatorial pharmacogenomic test was 1.7 to 2.9-times higher than the individual genes, showing that it explained more variance in citalopram/escitalopram blood levels. In multivariate analysis of the individual genes and combinatorial pharmacogenomic test together, only the combinatorial pharmacogenomic test remained significant. Overall, this demonstrates that the combinatorial pharmacogenomic test was a superior predictor of citalopram/escitalopram blood levels compared to individual genes.