Excess body weight as a predictor of response to treatment with antidepressants in patients with depressive disorder

Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets

Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selection still proceeds via "trial and error". Given the varied presentation of MDD and heterogeneity of treatment response, the use of machine learning to understand complex, non-linear relationships in data may be key for treatment personalization. Well-organized, structured data from clinical trials with standardized outcome measures is useful for training machine learning models; however, combining data across trials poses numerous challenges. There is also persistent concern that machine learning models can propagate harmful biases. We have created a methodology for organizing and preprocessing depression clinical trial data such that transformed variables harmonized across disparate datasets can be used as input for feature selection. Using Bayesian optimization, we identified an optimal multi-layer dense neural network that used data from 21 clinical and sociodemographic features as input in order to perform differential treatment benefit prediction. With this combined dataset of 5032 individuals and 6 drugs, we created a differential treatment benefit prediction model. Our model generalized well to the held-out test set and produced similar accuracy metrics in the test and validation set with an AUC of 0.7 when predicting binary remission. To address the potential for bias propagation, we used a bias testing performance metric to evaluate the model for harmful biases related to ethnicity, age, or sex. We present a full pipeline from data preprocessing to model validation that was employed to create the first differential treatment benefit prediction model for MDD containing 6 treatment options.

Ketamine vs Electroconvulsive Therapy for Treatment-Resistant Depression: A Secondary Analysis of a Randomized Clinical Trial

Importance

The ELEKT-D: Electroconvulsive Therapy (ECT) vs Ketamine in Patients With Treatment Resistant Depression (TRD) (ELEKT-D) trial demonstrated noninferiority of intravenous ketamine vs ECT for nonpsychotic TRD. Clinical features that can guide selection of ketamine vs ECT may inform shared decision-making for patients with TRD.

Objective

To evaluate whether selected clinical features were associated with differential improvement with ketamine vs ECT.

Design, Setting, and Participants

This secondary analysis of an open-label noninferiority randomized clinical trial was a multicenter study conducted at 5 US academic medical centers from April 7, 2017, to November 11, 2022. Analyses for this study, which were not prespecified in the trial protocol, were conducted from May 10 to Oct 31, 2023. The study cohort included patients with TRD, aged 21 to 75 years, who were in a current nonpsychotic depressive episode of at least moderate severity and were referred for ECT by their clinicians.

Exposures

Eligible participants were randomized 1:1 to receive either 6 infusions of ketamine or 9 treatments with ECT over 3 weeks.

Main Outcomes and Measures

Association between baseline factors (including 16-item Quick Inventory of Depressive Symptomatology Self-Report [QIDS-SR16], Montgomery-Asberg Depression Rating Scale [MADRS], premorbid intelligence, cognitive function, history of attempted suicide, and inpatient vs outpatient status) and treatment response were assessed with repeated measures mixed-effects model analyses.

Results

Among the 365 participants included in this study (mean [SD] age, 46.0 [14.5] years; 191 [52.3%] female), 195 were randomized to the ketamine group and 170 to the ECT group. In repeated measures mixed-effects models using depression levels over 3 weeks and after false discovery rate adjustment, participants with a baseline QIDS-SR16 score of 20 or less (-7.7 vs -5.6 points) and those starting treatment as outpatients (-8.4 vs -6.2 points) reported greater reduction in the QIDS-SR16 with ketamine vs ECT. Conversely, those with a baseline QIDS-SR16 score of more than 20 (ie, very severe depression) and starting treatment as inpatients reported greater reduction in the QIDS-SR16 earlier in course of treatment (-8.4 vs -6.7 points) with ECT, but scores were similar in both groups at the end-of-treatment visit (-9.0 vs -9.9 points). In the ECT group only, participants with higher scores on measures of premorbid intelligence (-14.0 vs -11.2 points) and with a comorbid posttraumatic stress disorder diagnosis (-16.6 vs -12.0 points) reported greater reduction in the MADRS score. Those with impaired memory recall had greater reduction in MADRS during the second week of treatment (-13.4 vs -9.6 points), but the levels of MADRS were similar to those with unimpaired recall at the end-of-treatment visit (-14.3 vs -12.2 points). Other results were not significant after false discovery rate adjustment.

Conclusions and Relevance

In this secondary analysis of the ELEKT-D randomized clinical trial of ECT vs ketamine, greater improvement in depression was observed with intravenous ketamine among outpatients with nonpsychotic TRD who had moderately severe or severe depression, suggesting that these patients may consider ketamine over ECT for TRD.

Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials

BACKGROUND

Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment.

AIMS

To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants.

METHOD

Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses.

RESULTS

Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, βpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, βpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2= 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (βpooled = 0.16) and the IMD index (βpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission.

CONCLUSIONS

Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.

Divergent transcriptomic profiles in depressed individuals with hyper- and hypophagia implicating inflammatory status

Major Depressive Disorder (MDD) is a heterogenous and etiologically complex disease encompassing a broad spectrum of psychopathology, presumably arising from distinct pathophysiological mechanisms. Divergent appetitive phenotypes including Hyperphagic MDD (characterized by an increased appetite) and Hypophagic MDD (characterized by a decrease in appetite) are important clinical characteristics that are closely related to comorbidities, including cardiometabolic disorders. Prior evidence supports the notion that hyperphagia is associated with atypical depression, decreased stress-hormone signaling, a pro-inflammatory status, hypersomnia, and poorer clinical outcomes. Yet, our understanding of the underlying mechanisms of Hyperphagic and Hypophagic MDD is limited, and knowledge of associated biological correlates of these endophenotypes remain fragmented. We performed an exploratory study on peripheral blood RNA profiling using bulk RNAseq in unmedicated individuals with Hyperphagic and Hypophagic MDD (n=8 and n=13, respectively) and discovered individual genes and gene pathways associated with appetitive phenotypes. In addition, we used the Maastricht Acute Stress Task to uncover stress-related transcriptomic profiles in Hyper- and Hypophagic MDD.

Divergent transcriptomic profiles in depressed individuals with hyper- and hypophagia implicating inflammatory status

Major Depressive Disorder (MDD) is a heterogenous and etiologically complex disease encompassing a broad spectrum of psychopathology, presumably arising from distinct pathophysiological mechanisms. Divergent appetitive phenotypes including Hyperphagic MDD (characterized by an increased appetite) and Hypophagic MDD (characterized by a decrease in appetite) are important clinical characteristics that are closely related to comorbidities, including cardiometabolic disorders. Prior evidence supports the notion that hyperphagia is associated with atypical depression, decreased stress-hormone signaling, a pro-inflammatory status, hypersomnia, and poorer clinical outcomes. Yet, our understanding of the underlying mechanisms of Hyperphagic and Hypophagic MDD is limited, and knowledge of associated biological correlates of these endophenotypes remain fragmented. We performed an exploratory study on peripheral blood RNA profiling using bulk RNAseq in unmedicated individuals with Hyperphagic and Hypophagic MDD (n=8 and n=13, respectively) and discovered individual genes and gene pathways associated with appetitive phenotypes. In addition, we used the Maastricht Acute Stress Task to uncover stress-related transcriptomic profiles in Hyper- and Hypophagic MDD.

Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study

BACKGROUND

Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR).

METHODS

We used the European UK Biobank subcohort ([Formula: see text]), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on general practitioner (GP) records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used a range of univariable, multivariable and mediation MR models techniques to address our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy-robust multivariable MR to one sample data and employed a Bayesian bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms standard approaches in sparse binary outcomes. Given the flexibility of the one-sample design, we evaluated age and sex as moderators of the effects.

RESULTS

In univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD ([Formula: see text] ([Formula: see text] CI): 0.133(0.072, 0.205)) and TRD (0.347(0.002, 0.682)), with a larger magnitude in females and with age acting as a moderator of the effect of BMI on severity of depression (0.22(0.050, 0.389)). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP (0.395(0.004, 0.732)). Our mediation analyses suggested that the effect of CRP on severity of depression was partly mediated by BMI. Individuals with TRD ([Formula: see text]) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy controls.

DISCUSSION

Our work supports the assertion that BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in females and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD.

Body mass index and clinical outcomes in individuals with major depressive disorder: Findings from the GSRD European Multicenter Database

BACKGROUND

Individuals with major depressive disorder (MDD) are at higher risk for obesity. In turn, weight gain is a predisposing factor for depression. Although clinical data are sparse, suicide risk also appears to be elevated in obese patients. This study used data from the European Group for the Study of Resistant Depression (GSRD) to investigate clinical outcomes associated with body mass index (BMI) in MDD.

METHODS

Data were drawn from 892 participants with MDD over the age of 18 years (580 female, 50.5 ± 13.6 years). Response and resistance to antidepressant medication, depression rating scale scores, and further clinical and sociodemographic variables were compared using multiple logistic and linear regressions controlled for age, sex, and risk of weight gain due to psychopharmacotherapy.

RESULTS

Of the 892 participants, 323 were categorized as treatment-responsive and 569 as treatment-resistant. Within this cohort, 278 (31.1 %) were overweight (BMI = 25-29.9 kg/m2) and 151 (16.9 %) were obese (BMI > 30 kg/m2). Elevated BMI was significantly associated with higher suicidality, longer duration of psychiatric hospitalizations over their lifetimes, earlier age of onset of MDD, and comorbidities. There was a trend-wise association of BMI with treatment resistance.

LIMITATIONS

Data were analyzed in a retrospective, cross-sectional design. BMI was used as an exclusive measure of overweight and obesity.

CONCLUSIONS

Participants with comorbid MDD and overweight/obesity were at risk for worse clinical outcomes, suggesting that weight gain should be closely monitored in individuals with MDD in daily clinical practice. Further studies are needed to explore the neurobiological mechanisms linking elevated BMI to impaired brain health.

Efficacy and safety of selective serotonin reuptake inhibitors in COVID-19 management: a systematic review and meta-analysis

BACKGROUND

The efficacy of selective serotonin reuptake inhibitors (SSRIs) in the treatment of acute COVID-19 is still under investigation, with conflicting results reported from randomized controlled trials (RCTs). Different dosing regimens may have contributed to the contradictory findings.

OBJECTIVES

To evaluate the efficacy and safety of SSRIs and the effect of different dosing regimens on the treatment of acute COVID-19.

DATA SOURCES

Seven databases were searched from January 2020 to December 2022. Trial registries, previous reviews, and preprint servers were hand-searched.

STUDY ELIGIBILITY CRITERIA

RCTs and observational studies with no language restrictions.

PARTICIPANTS

COVID-19 inpatients/outpatients.

INTERVENTIONS

SSRIs prescribed after diagnosis were compared against a placebo or standard of care.

ASSESSMENT OF RISK OF BIAS

Risk of bias was rated using the revised Cochrane Risk of Bias Tool for Randomized Trials version 2.0 and Risk of Bias in Non-Randomized Studies of Interventions.

METHODS OF DATA SYNTHESIS

Outcomes were mortality, hospitalization, composite of hospitalization/emergency room visits, hypoxemia, requirement for supplemental oxygen, ventilator support, and serious adverse events. RCT data were pooled in random-effects meta-analyses. Observational findings were narratively described. Subgroup analyses were performed on the basis of SSRI dose, and sensitivity analyses were performed excluding studies with a high risk of bias. The Grading of Recommendations, Assessment, Development and Evaluations framework was used to assess the quality of evidence.

RESULTS

Six RCTs (N = 4197) and five observational studies (N = 1156) were included. Meta-analyses associated fluvoxamine with reduced mortality (risk ratio, 0.72; 95% CI, 0.63-0.82) and hospitalization (risk ratio, 0.79; 95% CI, 0.64-0.99) on the basis of moderate quality of evidence. Medium-dose fluvoxamine (100 mg twice a day) was associated with reduced mortality, hospitalization, and composite of hospitalization/emergency room visits, but low-dose fluvoxamine (50 mg twice a day) was not. Fluvoxamine was not associated with increased serious adverse events. Observational studies support the use of fluvoxamine and highlight fluoxetine as a possible alternative to SSRIs for the treatment of COVID-19.

DISCUSSION

Fluvoxamine remains a candidate pharmacotherapy for treating COVID-19 in outpatients. Medium-dose fluvoxamine may be preferable over low-dose fluvoxamine.

DFO treatment protects against depression-like behaviors and cognitive impairment in CUMS mice

Depression has several negative effects on emotion as well as learning and memory abilities. Previous studies showed that depression could exacerbate inflammation, which in turn further aggravated depression. Deferoxamine (DFO) is a chelating agent binding iron and aluminium, and is clinically applied to treat acute ion poisoning and hemochromatosis. Researches showed that it could reduce inflammation via increasing the expression of hypoxia-inducible factor-1alpha (HIF-1α). Here, we established a chronic unpredictable mild stress (CUMS) model to investigate whether DFO exerted a neuroprotective function in depression. The results demonstrated that CUMS (4 weeks) effectively induced depression-like behaviors in mice based on sucrose preference test (SPT), forced swim test (FST), tail suspension test (TST), open field test (OFT), and elevated plus-maze test (EPT). It also brought cognitive deficits based on Morris water maze (MWM) test and the impairment of synaptic plasticity based on in vivo electrophysiological recordings. Additionally, CUMS exposure significantly decreased the expression of hippocampal synapse related proteins and the spine density of neurons in the DG region, accompanied by increasing the expression of hippocampal inflammatory cytokines, and promoted the activation of microglia in the hippocampus. The expression of HIF-1α was down-regulated as expected. However, DFO distinctly reversed the CUMS-induced impairments. The mechanism is associated with the DFO inhibition of inflammation by upregulating HIF-1 expression, thereby alleviating a series of pathology changes. Together, these findings suggest that DFO likely plays a protective role in cognitive impairments and synaptic plasticity deficits resulting from depression.

Electroconvulsive therapy and adiposity-related parameters in treatment-resistant depressed patients

Obesity is often accompanied by major depressive disorder (MDD), and vice versa. Latest research findings suggest the body mass index (BMI) to play a role in antidepressant treatment response in general. Our study aims to examine whether adiposity-related parameters such as BMI, glucose homeostasis, or serum lipids are associated with remission to electroconvulsive therapy (ECT). A pilot study (PS, n = 9) and a glucose study (GS, n = 29) were conducted. Blood was withdrawn directly before and 15 min (GS) as well as 1 h (PS) after the first ECT and directly before the last one (usually an ECT series comprised up to twelve sessions). BMI was associated with remission in the PS (remitters: M = 28, SD = 2.5; non-remitters: M = 22, SD = 2.08; t(7) = 3.325, p < 0.001, d = 0.24) but not in the GS or when pooled together. Glucose and insulin levels increased significantly after a single ECT session (GS: glucose: F (2,25.66) = 39.04, p < 0.001; insulin: PS: F (2,83) = 25.8, p < 0.001; GS: F (2,25.87) = 3.97, p < 0.05) but no chronic effect was detectable. Serum lipids were neither significantly altered after a single ECT session nor during a whole course of ECT. There was no difference between remitters and non-remitters in insulin, glucose, or serum lipid levels. Our study is lacking the differentiation between abdominal and peripheral fat distribution, and the sample size is small. Unexpectedly, BMI, glucose homeostasis, and lipid serum levels did not differ in patients remitting during ECT. In contrast to recently published studies, we cannot confirm the hypothesis that BMI may have an impact on ECT response.

Overweight in mood disorders: Effects on morbidity and treatment response

OBJECTIVE

As it is not clear how body-mass index (BMI) may relate to diagnosis, symptom-severity, illness-course, and treatment-response among psychiatric patients, we related BMI to psychiatric diagnosis and to selected clinical and demographic factors in major affective disorder subjects.

METHODS

We analyzed mean BMI levels vs. diagnosis, and evaluated selected risk factors for association with overweight and obesity among subjects with DSM-5 major affective disorders.

RESULTS

In 1884 subjects, BMI ranged from 23.4 kg/m² with anxiety disorders to 27.6 with psychotic disorders, and averaged 24.1 among 1469 affective disorder subjects. Mood-disorder subjects with BMI ≥ 25 (overweight/obese) were more likely: men, older, married, with more children and siblings, less education, lower socioeconomic status, engaged less in physical exercise, smoked more, and lived in less densely populated areas. They also were more likely to have: BD than MDD, familial mood disorders, no co-occurring ADHD, higher serum triglyceride levels, more time depressed and less improvement in depression ratings with treatment.

CONCLUSIONS

Risk of being overweight or obese was greatest with psychoses, least with anxiety, personality, and minor depressive disorders, and intermediate with major mood disorders. Several plausible risk factors for high BMI were identified in mood disorder subjects, including male sex and with BD > MDD. Striking were selectively greater prospective morbidity and decreased treatment-response for depression vs. mania with BMI ≥ 25.

Effects of body weight, smoking status, and sex on plasma concentrations of once-monthly paliperidone palmitate

OBJECTIVES

Knowledge about the impact of body composition features on pharmacokinetics of newer long-acting injectable antipsychotics is limited.

METHODS

We analyzed steady-state plasma concentrations of paliperidone in different body mass index (BMI), age, sex, and smoking status patient subgroups treated with once-monthly paliperidone palmitate (PP1M). Paliperidone plasma concentrations and dose-adjusted-plasma concentrations (C/D) from a therapeutic drug monitoring (TDM) database of PP1M-treated patients were compared among normal BMI, overweight, and obese patients as well as between females vs. males, elderly vs. non-elderly, and smokers vs. non-smokers using non-parametric tests.

RESULTS

In a total of 183 PP1M-treated patients, we found highly variable paliperidone plasma concentrations between individuals but no significant effect of PP1M dose or dosing intervals (p> 0.05). C/D ratios were similar in 54 obese, 82 overweight, and 47 normal BMI patients (p> 0.05). Females had 13.7% higher C/D ratios compared to males, yet this difference was not significant (p> 0.05). No differences were found between elderly vs. non-elderly patients or for smokers vs. non-smokers (p> 0.05).

CONCLUSION

Our findings suggest that age, sex, smoking, or body weight may not substantially affect pharmacokinetic indices of PP1M. The high interindividual variation of plasma concentrations implies that TDM may be helpful to enhance PP1M efficacy and tolerability.

Difference in patterns of prescribing antidepressants known for their weight-modulating and cardiovascular side effects for patients with obesity compared to patients with normal weight

BACKGROUND

Patients with depression and comorbid obesity may be more prone to weight modulating and cardiovascular side effects of selected antidepressants (AD). It is important to ascertain whether these AD prescriptions differ by patient weight status.

METHODS

Canadian Primary Care Sentinel Surveillance Network (CPCSSN) electronic medical records were used. Participants were adults with depression prescribed an AD in 2000-2016, with weight categories established before the first prescription. Logistic regression and mixed effects models were applied to examine associations between obesity and AD prescribing, adjusted for sex, age, and comorbidities. Machine learning algorithm random forest (RF) was used to evaluate the importance of weight in predicting prescribing patterns.

RESULTS

Of 26,571 participants, 72.4% were women, mean age was 38.9 years (standard deviation (SD)=14.2) and mean BMI 27.0 kg/m² (SD = 6.5); 9.5% had ≥ 1 comorbidity. Patients with obesity, compared to normal weight patients, were more likely to receive bupropion (adjusted odds ratio (aOR) 1.24, 95%CI: 1.09,1.42), fluoxetine (aOR 1.14, 95%CI: 0.97,1.34), and amitriptyline (aOR 1.13, 95%CI: 0.93,1.36), and less likely to receive mirtazapine (aOR 0.55, 95%CI: 0.44,0.68) and escitalopram (aOR 0.88, 95%CI: 0.80, 0.97). RF analysis showed that weight was among the most important predictors of prescribing patterns, equivalent to age and more important than sex.

CONCLUSIONS

AD prescribing patterns for patients with obesity appear to be different for selected AD types, including AD known for their weight-modulating and cardiovascular side effects. Longitudinal studies are needed to examine whether these prescribing patterns are associated with significant health outcomes.

Legumain knockout improves repeated corticosterone injection-induced depression-like emotional and cognitive deficits

Emotional and cognitive impairment has been recognized as a central feature of depression, which is closely related to hyperfunction of the hypothalamic-pituitary-adrenal (HPA) axis caused by down-regulation of glucocorticoid receptor (GR) expression in patients. A decrease in GR expression can cause pathological changes and lead to the impairment of synaptic plasticity. Legumain, a lysosomal cysteine protease, plays an important role in neurological diseases. It is reported that legumain activates the MAPK signaling pathway, which modifies the GR. Therefore, we hypothesize that regulation of the GR by legumain plays a crucial role in the pathological process of depression. The relationships between legumain, GR, synaptic plasticity and emotional and cognitive deficits were explored in this study. The results demonstrated that repeated corticosterone (CORT) injections (3 weeks) induced emotional and cognitive deficits in mice, based on behavioral experiments and the detection of synaptic plasticity. Furthermore, CORT injections decreased the expression of hippocampal synapse-related proteins, cell density and dendritic spine density in the hippocampus, accompanied by increased protein expression in the MAPK signaling pathway and decreased expression of the GR. In conclusion, our results demonstrated that legumain knockout up-regulated expression of the GR by reducing protein expression in the MAPK signaling pathway, thereby improving hippocampal synaptic plasticity as well as the emotional and cognitive impairment of model mice. This suggests that legumain may be an effective therapeutic target for emotional and cognitive deficits.

The association of body mass index (BMI) with treatment outcomes in patients with major depressive disorder

BACKGROUND

In patients with major depressive disorder (MDD), poor antidepressant treatment response might be associated with an excessive body mass index (BMI). However, the impact of underweight on treatment response is unclear. Moreover, it has not been studied whether a continuous or categorical BMI measure should be used to predict of treatment response.

METHODS

Post-hoc analysis of data collected in a clinical trial including adults with MDD (n=202) reporting outcomes of antidepressant medication, i.e. paroxetine, mirtazapine or paroxetine+mirtazapine. Measures included baseline BMI (underweight=BMI <18.5, normal weight:=BMI:18.5-23.9, overweight=BMI≥24) and symptom severity (17-item-Hamilton Depression scale; HAMD-17) assessed at weeks 0, 2, 3, 4, 6 and 8. Univariate analyses were used to explore the effect of baseline BMI on HAMD-17 reduction, response (defined as ≥50% HAMD-17 reduction) and remission (defined as HAMD-17 ≤7) at endpoint. Pearson correlation were used to explore the relationship between body weight, BMI as continuous measure and HAMD-17 reduction. Logistic regression was used to determine the predictors for remission. Multiple linear regression was used to establish the correlation of BMI with change of HAMD-17.

RESULTS

111 (55.0%) patients were normal weight, 20 (9.9%) were underweight, 71 (35.1%) were overweight. Underweight patients showed the best improvement to antidepressant treatment. Non-remitters had greater body weight and BMI than remitters (P<0.05). The reduction of HAMD-17 was correlated with baseline body weight (r=-0.16, P=0.032) and BMI (r=-0.19, P=0.012). Logistic regression found patients with BMI<24 to be 2 times (OR=1.958, 95%CI: 1.015, 3.774) remitters (P=0.045) than overweight patients. The multiple linear regression showed that the change of HAMD-17 total score decreased with increasing BMI (β=-0.32, P = 0.016).

CONCLUSION

We confirmed that BMI can predict treatment outcomes in MDD. For the first time we found that underweight patients benefit most from antidepressant treatment. The findings may be useful to physicians in their decision regarding the choice of antidepressants according to BMI.

Simvastatin add-on to escitalopram in patients with comorbid obesity and major depression (SIMCODE): study protocol of a multicentre, randomised, double-blind, placebo-controlled trial

INTRODUCTION

Major depressive disorder (MDD) and obesity are both common disorders associated with significant burden of disease worldwide. Importantly, MDD and obesity often co-occur, with each disorder increasing the risk for developing the other by about 50%-60%. Statins are among the most prescribed medications with well-established safety and efficacy. Statins are recommended in primary prevention of cardiovascular disease, which has been linked to both MDD and obesity. Moreover, statins are promising candidates to treat MDD because a meta-analysis of pilot randomised controlled trials has found antidepressive effects of statins as adjunct therapy to antidepressants. However, no study so far has tested the antidepressive potential of statins in patients with MDD and comorbid obesity. Importantly, this is a difficult-to-treat population that often exhibits a chronic course of MDD and is more likely to be treatment resistant. Thus, in this confirmatory randomised controlled trial, we will determine whether add-on simvastatin to standard antidepressant medication with escitalopram is more efficacious than add-on placebo over 12 weeks in 160 patients with MDD and comorbid obesity.

METHODS AND ANALYSIS

This is a protocol for a randomised, placebo-controlled, double-blind multicentre trial with parallel-group design (phase II). One hundred and sixty patients with MDD and comorbid obesity will be randomised 1:1 to simvastatin or placebo as add-on to standard antidepressant medication with escitalopram. The primary outcome is change in the Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to week 12. Secondary outcomes include MADRS response (defined as 50% MADRS score reduction from baseline), MADRS remission (defined as MADRS score <10), mean change in patients' self-reported Beck Depression Inventory (BDI-II) and mean change in high-density lipoprotein, low-density lipoprotein and total cholesterol from baseline to week 12.

ETHICS AND DISSEMINATION

This protocol has been approved by the ethics committee of the federal state of Berlin (Ethik-Kommission des Landes Berlin, reference: 19/0226-EK 11) and by the relevant federal authority (Bundesinstitut für Arzneimittel und Medizinprodukte (BfArM), reference: 4043387). Study findings will be published in peer-reviewed journals and will be presented at (inter)national conferences.

TRIAL REGISTRATION NUMBERS

NCT04301271, DRKS00021119, EudraCT 2018-002947-27.

Evaluating Prevalence and Patterns of Prescribing Medications for Depression for Patients With Obesity Using Large Primary Care Data (Canadian Primary Care Sentinel Surveillance Network)

Introduction: Depression is a serious disorder that brings a tremendous health and economic burden. Many antidepressants (AD) have obesogenic effects, increasing the population of obese patients at increased risk for a more severe disease course and poor treatment response. In addition, obese patients with depression may not be receiving the recommended standard of care due to "obesity bias." It is important to evaluate prescribing pharmacological treatment of depression in patients with obesity. Objectives: To describe the prevalence and patterns of AD prescribing for patients with depression and comorbid obesity compared with normal weight patients, and to examine the association of prescribing prevalence with obesity class. Methods: Study sample of adult patients (>18 years old) with depression was extracted from the national Canadian Primary Care Sentinel Surveillance Network (CPCSSN) Electronic Medical Records database for 2011-2016. Measures were prescribing of at least one AD (outcome) and body mass index (BMI) to categorize patients into weight categories (exposure). Data were analyzed cross-sectionally using descriptive statistics and mixed effects logistic regression model with clustering on CPCSSN networks and adjusting for age, sex, and the comorbidities. Results: Of 120,381 patients with depression, 63,830 patients had complete data on studied variables (complete cases analysis). Compared with normal weight patients, obese patients were more likely to receive an AD prescription (adjusted Odds Ratio [aOR] = 1.17; 95% Confidence Interval [CI]: 1.12-1.22). Patients with obesity classes II and III were 8% (95% CI: 1.00, 1.16) and 6% (95% CI: 0.98, 1.16) more likely, respectively, to receive AD. After imputing missing data using Multiple Imputations by Chained Equations, the results remained unchanged. The prevalence of prescribing >3 AD types was higher in obese category (7.27%, [95% CI: 6.84, 7.73]) than in normal weight category (5.6%; [95% CI: 5.24, 5.99]). Conclusion: The association between obesity and high prevalence of AD prescribing and prescribing high number of different AD to obese patients, consistent across geographical regions, raises a public health concern. Study results warrant qualitative studies to explore reasons behind the difference in prescribing, and quantitative longitudinal studies evaluating the association of AD prescribing patterns for obese patients with health outcomes.