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Background: The brain-derived neurotrophic factor (BDNF) Val66Met polymorphism is associated with response to antidepressant drugs in depressed patients and with metabolic side effects after antipsychotic treatment. This study aims to assess the association between this polymorphism and insulin resistance after antidepressant treatment in depressed patients. Methods: One hundred forty-eight Caucasian patients with a current unipolar major depressive episode (DSM IV-TR) were genotyped for the BDNF Val66Met polymorphism and assessed at baseline and after 3 and 6 months of antidepressant treatment for the 'Homoeostasis model assessment of insulin resistance' (HOMA-IR) index, a valid measure of insulin resistance based on fasting plasma insulinaemia and glycaemia. Because validity assumptions were fulfilled, data were analysed using analysis of variance for repeated measures. Results: The 52 (35%) Met carriers and 96 (65%) Val/Val patients were not different at baseline for clinical characteristics and HOMA-IR. A significant Val66Met × time interaction (p = 0.02), a significant time effect (p = 0.03) and a significant Val66Met effect (p = 0.0497) were shown for HOMA-IR. A significant Val66Met × time interaction (p = 0.01) and a significant time effect (p = 0.003) were shown for fasting glycaemia. HOMA-IR and fasting glycaemia changes after antidepressant treatment were significantly higher in Met carrier than in Val/Val patients (HOMA-IR changes: Met: 0.71 ± 3.29 v. Val/Val: −0.16 ± 1.34, t = 2.3, df = 146, p = 0.02, glycaemia changes: Met: 0.09 ± 0.30 v. Val/Val: 0.02 ± 0.16, t = −2.0, df = 146, p = 0.045). Conclusions: The Met allele of the Val66Met BDNF polymorphism confers to depressed patients a higher risk of insulin-resistance after antidepressant treatment. These patients could benefit from specific monitoring of metabolism and preventive measures. [ABSTRACT FROM AUTHOR]

Objectives: Whether hippocampal volume predicts response and/or remission after antidepressant treatment of major depressive episodes (MDE) in major depressive disorder (MDD) remains unclear. We meta-analysed prospective studies comparing baseline hippocampal volume in patients with or without response/remission after antidepressant treatment. Methods: Pubmed, Embase and Google Scholar were searched for studies of patients with current MDE in MDD, with hippocampal volume assessments at baseline, initiation of antidepressant drug treatment, and prospective assessment of response/remission after treatment. Results: Six studies (374 patients), of which two were positive and four negative, were meta-analysed. Compared to responders/remitters, patients who failed to achieve response/remission had smaller total hippocampus volumes at baseline (mean volume difference¼260mm3, 95% CI [93; 427], P¼0.002). These results remained significant in patients under 60 years of age (P¼0.02), in those over 60 years old (P¼0.04), and for right (P¼0.006) and left (P¼0.02) hippocampi. The probability of non-response/non-remission was 68.6% for patients with a total hippocampal volume at least 10% lower than the average, and 47.1% for patients with a total hippocampal volume 10% higher than the average. Conclusions: In depressed patients treated with antidepressant drugs, smaller hippocampal volumes predict lower response/remission rates. [ABSTRACT FROM AUTHOR]

Background: Pioglitazone, a selective agonist of the nuclear transcription factor peroxisome proliferator-activated receptor-gamma (PPAR-γ), prescribed for the treatment of type 2 diabetes, could have antidepressant properties. However, its potential to induce remission of major depressive episodes, the optimal clinical target for an antidepressant drug, is a matter of concern. Indeed, only one out of four double-blind randomized controlled trials show higher remission rates with pioglitazone than with control treatments. Hence, the main aim of this study was to perform a meta-analysis of the efficacy of pioglitazone for the treatment of MDE, focusing on remission rates. Methods: Four double-blind randomized controlled trials, comprising 161 patients with an MDE, were included in this meta-analysis. Pioglitazone was studied either alone (one study) or as add-on therapy to conventional treatments (antidepressant drugs or lithium salts). It was compared either to placebo (three studies) or to metformin (one study). Remission was defined by a Hamilton Depression Rating Scale score <8 after treatment. Results: Pioglitazone could induce higher remission rates than control treatments (27% versus 10%, I2=17.3%, fixed-effect model: odds ratio [OR] =3.3, 95% confidence interval [95% CI; 1.4; 7.8], P=0.008). The OR was even higher in the subgroup of patients with major depressive disorder (n=80; 23% versus 8%, I2=0.0%; fixed-effect model: OR =5.9, 95% CI [1.6; 22.4], P=0.009) and in the subgroup of patients without metabolic comorbidities (n=84; 33% versus 10%, I2=0.0%; fixed-effect model: OR =5.1, 95% CI [1.5; 17.9], P=0.01). As compared to control treatments, results suggest six patients would need to be treated with pioglitazone in order to achieve the possibility of one more remission. Conclusion: Pioglitazone, either alone or as add-on therapy to conventional treatments, could induce remission of MDE, suggesting that drugs with PPAR-γ agonist properties may be true and clinically relevant antidepressants, even in patients without metabolic comorbidities. [ABSTRACT FROM AUTHOR]

In this preclinical pilot study, we used [ 11 C]UCB-J PET imaging to monitor the synaptic modulation in depression and after fluoxetine. PET imaging was performed in a validated mouse model of depression/anxiety (CORT model), and the effect of 5-week treatment with fluoxetine was tested. Depression/anxiety phenotype and antidepressant action of fluoxetine were confirmed using the novelty-suppressed feeding test, previously validated in the CORT model. PET data showed significant decreases of volume of distribution ( V T ) of [ 11 C]UCB-J in most brain regions of CORT mice compared with controls. After 5 weeks of fluoxetine, a trend toward restoration of V T values to control levels was observed, although it reached significance only in the olfactory bulb. These preliminary data support the use of [ 11 C]UCB-J PET imaging and the CORT model to study the synaptic modulation of antidepressants. It provides excellent translational opportunities to study the relationship between synaptic plasticity and the clinical efficacy of antidepressants., Competing Interests: The authors declare the following competing financial interest(s): D.J.D. serves as a consultant for Lundbeck Inc. D.J.D. receives compensation from Lundbeck and Janssen. R.H. receives compensation as a consultant for Roche, Lundbeck and Servier in relation to the generation of novel antidepressants. The other authors have no competing interest to disclose., (© 2025 The Authors. Published by American Chemical Society.)

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing 7,012 participants from 30 sites (N=2,772 MDD and N=4,240 HC), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible. Future studies are needed to determine whether more sophisticated integration of information from other MRI modalities such as fMRI and DWI will lead to a higher performance in this diagnostic task.

Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.5 ± 15.3 years; 154 (59%) female; mean response rate = 57%). Treatment response was defined as a ≥ 50% reduction in symptom severity score after 4-12 weeks post-initiation of antidepressant treatment. Structural MRI was acquired before, or < 14 days after, treatment initiation. The cortex was parcellated using FreeSurfer, from which cortical thickness and surface area were measured. We tested several machine learning pipeline configurations, which varied in (i) the way we presented the cortical data (i.e., average values per region of interest, as a vector containing voxel-wise cortical thickness and surface area measures, and as cortical thickness and surface area projections), (ii) whether we included clinical data, and the (iii) machine learning model (i.e., gradient boosting, support vector machine, and neural network classifiers) and (iv) cross-validation methods (i.e., k-fold and leave-one-site-out) we used. First, we tested if the overall predictive performance of the pipelines was better than chance, with a corrected 10-fold cross-validation permutation test. Second, we compared if some machine learning pipeline configurations outperformed others. In an exploratory analysis, we repeated our first analysis in three subpopulations, namely patients (i) from a single site, (ii) with comparable response rates, and (iii) showing the least (first quartile) and the most (fourth quartile) treatment response, which we call the extreme (non-)responders subpopulation. Finally, we explored the effect of including subcortical volumetric data on model performance. Overall, performance predicting antidepressant treatment response was not significantly better than chance (balanced accuracy = 50.5%; p = 0.66) and did not vary with alternative pipeline configurations. Exploratory analyses revealed that performance across models was only significantly better than chance in the extreme (non-)responders subpopulation (balanced accuracy = 63.9%, p = 0.001). Including subcortical data did not alter the observed model performance. Cortical structural MRI alone could not reliably predict individual pharmacotherapeutic treatment response in MDD. None of the used machine learning pipeline configurations outperformed the others. In exploratory analyses, we found that predicting response in the extreme (non-)responders subpopulation was feasible on both cortical data alone and combined with subcortical data, which suggests that specific MDD subpopulations may exhibit response-related patterns in structural data. Future work may use multimodal data to predict treatment response in MDD., (© 2025 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)

Objective: White matter hyperintensities (WMH) are associated with Major Depressive Episodes (MDE) in individuals aged 65 and over. WMH are prevalent in adults under 65, yet the association between their volume and MDE in this population remains uncertain. This study aimed to assess the association between WMH volume and MDE and its severity in patients < 65., Methods: This cross-sectional study included subjects under the age of 65, 69 patients with MDE and 32 healthy controls (HCs). Severity was assessed with the Hamilton Rating Scale and WMH were quantified by 2 experts. Post-hoc mediation analyses were conducted if associations were found between independent variables and WMH., Results: Mean was 34.5 (12.4) years old. There was no difference in WMH between patients and HCs. Higher WMH volume were observed in extremely severe MDE (2170.2 (3767.9) mm3 vs 416.6 (594.9) mm3 (r = 0.21; p < 0.05)), which completely mediated the effect of age on severity., Conclusions: In adults under 65, this study failed to identify higher WMH volume in MDE compared to HCs. However, WMH may act as a mediator of the association between age and MDE severity. This finding suggests that WMH could contribute to more severe depression in late-life., Competing Interests: The authors report no conflicts of interest.

Previous studies have suggested that alterations in white matter (WM) microstructure are implicated in suicidal thoughts and behaviours (STBs). However, findings of diffusion tensor imaging (DTI) studies have been inconsistent. In this large-scale mega-analysis conducted by the ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium, we examined WM alterations associated with STBs. Data processing was standardised across sites, and resulting WM microstructure measures (fractional anisotropy, axial diffusivity, mean diffusivity and radial diffusivity) for 25 WM tracts were pooled across 40 cohorts. We compared these measures among individuals with a psychiatric diagnosis and lifetime history of suicide attempt ( n =652; mean age=35.4±14.7; female=71.8%), individuals with a psychiatric diagnosis but no STB (i.e., clinical controls; n =1871; mean age=34±14.8; female=59.8%), and individuals with no mental disorder diagnosis and no STB (i.e., healthy controls; n =642; mean age=29.6±13.1; female=62.9%). We also compared these measures among individuals with recent suicidal ideation ( n =714; mean age=36.3±15.3; female=66.1%), clinical controls ( n =1184; mean age=36.8±15.6; female=63.1%), and healthy controls ( n =1240; mean age= 31.6±15.5; female=61.0%). We found subtle but statistically significant effects, such as lower fractional anisotropy associated with a history of suicide attempt, over and above the effect of psychiatric diagnoses. These effects were strongest in the corona radiata, thalamic radiation, fornix/stria terminalis, corpus callosum and superior longitudinal fasciculus. Effect sizes were small (Cohen's d < 0.25). Recent suicidal ideation was not associated with alterations in WM microstructure. This large-scale coordinated mega-analysis revealed subtle regional and global alterations in WM microstructure in individuals with a history of suicide attempt. Longitudinal studies are needed to confirm whether these alterations are a risk factor for suicidal behaviour., Competing Interests: Conflicts of interest ALvH receives consultancy fees from the Augeo foundation. CAZ is a full-time US government employee. He is listed as a co-inventor on a patent for the use of ketamine and its metabolites in major depression and suicidal ideation. Dr. Zarate has assigned his patent rights to the U.S. government but will share a percentage of any royalties that may be received by the government. HPB has consulted to the Milken Institute. MW is a member of the following advisory boards and gave presentations to the following companies: Bayer AG, Germany; Boehringer Ingelheim, Germany; and Biologische Heilmittel Heel GmbH, Germany. MW has further conducted studies with institutional research support from HEEL and Janssen Pharmaceutical Research for a clinical trial (IIT) on ketamine in patients with MDD, unrelated to this investigation. MW did not receive any financial compensation from the companies mentioned above. IA received speakers honorarium from Lundbeck. IBH is the Co-Director, Health and Policy at the Brain and Mind Centre (BMC) University of Sydney. The BMC operates an early-intervention youth services at Camperdown under contract to headspace. He is the Chief Scientific Advisor to, and a 3.2% equity shareholder in, InnoWell Pty Ltd which aims to transform mental health services through the use of innovative technologies. AC reports being currently an employee of the Regeneron Genetics Center, and may own Regeneron stock or stock options. JCS acknowledge to be related with the next companies ALKERMES (Advisory Board), BOEHRINGER Ingelheim (Consultant), COMPASS Pathways (Research Grant), JOHNSON & JOHNSON (Consultant), LIVANOVA (Consultant), RELMADA (Research Grant), SUNOVION (Research Grant),Mind Med (Research Grant). PMP received payment or honoraria for lectures and presentations in educational events for Sandoz, Daiichi Sankyo, Eurofarma, Abbot, Libbs, Instituto Israelita de Pesquisa e Ensino Albert Einstein, Instituto D’Or de Pesquisa e Ensino. All other authors report no biomedical financial interests, disclosures or potential conflicts of interest.

Background: Dyspnoea is a common persistent symptom after COVID-19. Whether it is associated with functional respiratory disorders remains unclear., Methods: We assessed the proportion and characteristics of patients with "functional respiratory complaints" (FRCs) (as defined by Nijmegen Questionnaire >22) among 177 post-COVID-19 individuals who benefited from outclinic evaluation in the COMEBAC study ( i.e. , symptomatic and/or intensive care unit (ICU) survivors at 4 months). In a distinct explanatory cohort of 21 consecutive individuals with unexplained post-COVID-19 dyspnoea after routine tests, we also analysed the physiological responses to incremental cardiopulmonary exercise testing (CPET)., Findings: In the COMEBAC cohort, 37 patients had significant FRCs (20.9%, IC95: 14.9-26.9). The prevalence of FRCs ranged from 7.2% (ICU patients) to 37.5% (non-ICU patients). The presence of FRCs was significantly associated with more severe dyspnoea, lower 6-min walk distance, more frequent psychological and neurological symptoms (cognitive complaint, anxiety, depression, insomnia and post-traumatic stress disorders) and poorer quality of life (all p<0.01). In the explanatory cohort, seven out of 21 patients had significant FRCs. Based on CPET, dysfunctional breathing was identified in 12 out of 21 patients, five out of 21 had normal CPET, three out of 21 had deconditioning and one out of 21 had evidence of uncontrolled cardiovascular disease., Interpretation: FRCs are common during post-COVID-19 follow-up, especially among patients with unexplained dyspnoea. Diagnosis of dysfunctional breathing should be considered in those cases., Competing Interests: Conflict of interest: A. Beurnier reports personal fees from Sanofi and AstraZeneca, outside the submitted work. Conflict of interest: L. Savale reports personal fees and nonfinancial support from Janssen and MSD, and grants, personal fees and nonfinancial support from GSK, outside the submitted work. Conflict of interest: X. Jaïs reports grants and personal fees from Janssen, grants and personal fees from MSD, and grants from Bayer and GSK, outside the submitted work. Conflict of interest: T. Gille reports personal fees from Roche SAS, and other support from Oxyvie (oxygen provider), Vivisol France (oxygen provider) and Menarini France, outside the submitted work. Conflict of interest: O. Sitbon reports grants from Acceleron, AOP Orphan, Janssen, GSK and MSD; consulting fees from Altavant, Gossamer Bio, Janssen and MSD; lecture honoraria from AOP Orphan, Janssen, Ferrer and MSD; and participation on advisory boards for Acceleron, Altavant, Gossamer Bio, Janssen, MSD and Ferrer, all outside the submitted work. Conflict of interest: Marc Humbert reports grants from Acceleron, AOP Orphan, Janssen, Merck and Shou Ti; consulting fees from Acceleron, Aerovate, Altavant, AOP Orphan, Bayer, Chiesi, Ferrer, Janssen, Merck, MorphogenIX, Shou Ti and United Therapeutics; lecture honoraria from Janssen and Merck; and advisory board participation for Acceleron, Altavant, Janssen, Merck and United Therapeutics, all outside the submitted work. Conflict of interest: D. Montani reports grants from Acceleron, Janssen and Merck; consulting fees from Acceleron; and lecture honoraria from Bayer, Janssen and Merck, all outside the submitted work. Conflict of interest: All other authors have nothing to disclose., (Copyright ©The authors 2023.)

Objective: Psychiatric symptoms and mental disorders are common after Coronavirus Disease-19 (COVID-19). Some drugs used to treat acute COVID-19 have psychiatric side effects. We assessed the psychiatric symptoms and mental disorders of patients treated for acute COVID-19 with hydroxychloroquine (HCQ), interleukin-6 receptor antagonists (anti-IL-6), and corticoids (CTC)., Methods: We evaluated 177 patients in a day hospital 4 months after acute infection., Results: In a multivariate analysis, HCQ was associated with significant anxiety symptoms (odds ratio [OR] = 5.9, 95% confidence interval [95% CI] = 1.8-20.0, p = 0.003) and mental disorders (OR = 4.1, 95% CI = 1.2-13.9, p = 0.02). In a bivariate analysis with propensity matched cohorts, HCQ was associated with significant anxiety symptoms (9 patients [50.0%] with significant symptoms in the HCQ group versus 15 [20.1%] in the control group, OR = 3.8, 95% CI = 1.3-11.3, p = 0.01). Anti-IL-6 and CTC were not associated with significant psychiatric symptoms or mental disorders., Conclusion: We recommend monitoring psychiatric symptoms, especially anxiety, in patients treated with HCQ during COVID-19 infection. Further studies with larger samples and prospective assessments are needed to confirm our results.

Background: Weight gain is a major side effect of antidepressant (AD) drugs. We assessed whether early weight gain is a predictor for long term weight gain in depressed patients treated with antidepressants., Methods: In the six month prospective METADAP cohort, 260 non-overweight patients with a major depressive disorder (MDD), who have recently experienced a Major Depressive Episode (MDE) were assessed for early weight gain (>3%,>5%, and >7%) after one month of treatment, and for long term weight gain (>15% and >20%) after three and six months of treatment. ROC analysis was used to determine the predictive power of early weight gain., Results: 12.4% (21/170) of patients became overweight after three months of treatment and 21.1% (26/123) were overweight after six months. Compared to non-early weight gainers, patients with early weight gain (>3%, >5% and >7%) were 11.3 (OR = 11.3, 95%CI: 4.6-27.6)], 9.9 (OR = 9.9, 95%CI: 3.6-26.9)] and 17.8 (OR = 17.8, 95%CI: 6.4-49.4)] times, respectively, more at risk of late weight gain (>15%). ROC analysis showed that early weight gain (>3%) after one month of treatment, was the best predictor of long term weight gain (≥15%) after three months [Area Under the Curve (AUC )= 87%] and six months of treatment (AUC = 88%) PERSPECTIVES: Given that our baseline sample consisted of strictly non-overweight patients, the 3% threshold for weight gain after one month should be used as an indicator to initiate early weight monitoring in depressed patients treated with antidepressants. High attrition rate remains a limitation in this cohort and other cohorts in psychiatric settings., Disclosures: Bruno Falissard consults for and received lecture fees from for E. Lilly, BMS, Servier, Sanofi-Aventis, GlaxoSmithKline, HRA, Roche, Boeringer Ingelheim, Bayer, Almirall, Allergan, Stallergene, Genzyme, Pierre Fabre, Astra Zeneca, Novartis, Janssen, Astellas, Biotronik, Daiichi-Sankyo, Gilead, MSD, Lundbeck. Florence Gressier received lecture fees from for Servier, Lundbeck and a grant from Servier. Mircea Polosan consults for and received lecture fees from Astra-Zeneca, Bristol Myers Squibb, Lundbeck, Otsuka and Servier. Emmanuel Haffen consults for and received lecture fees from Astra-Zeneca, Bristol Myers Squibb, Pfizer, Lilly, Lundbeck, Otsuka, Sanofi-Aventis, Servier. Philippe Chanson has received unrestricted research and educational grants from Ipsen, Novartis, Novo-Nordisk, and Pfizer for the Department of Endocrinology and Reproductive Diseases, Hôpitaux Universitaires Paris-Sud and for INSERM U 693. He has served as investigator (principal or coordinator) for clinical trials funded by Novartis, Pfizer, Ipsen, Italopharmaco, Antisense, Prolor Biotech. He is member of Advisory Boards from Ipsen, Novartis, Viropharma. He gave lectures for Ipsen, Novartis, Pfizer, NovoNordisk. All the fees and honoraria were paid to his Institution. Bruno Falissard consults for and received lecture fees from NovoNordisk, MSD and Sanofi-Aventis. Laurent Bequemont has close family member working at Sanofi-Aventis, consults for Sanofi-Aventis, Pfizer, Servier and received lecture fees from Genzyme, GlaxoSmithKline, Bristol-Myers Squibb and Merck Sharp and Dohme. Khalil El Asmar, Séverine Trabado, Albane Vievard, Céline Verstuyft, Romain Colle and Emmanuelle Corruble have nothing to declare., (Copyright © 2018. Published by Elsevier B.V.)

Background: Metabolic syndrome (MetS) is a major public health issue. We assessed whether early weight gain predicts later MetS in depressed patients treated with antidepressants., Methods: In the 6-month prospective METADAP cohort, 260 non-overweight patients with a Major Depressive Disorder (MDD) and a current Major Depressive Episode (MDE) were assessed for early weight gain (>5%) after one month of treatment, and for the later incidence of MetS after three and six months of treatment. Outcome variables were MetS, the number of MetS criteria, and each MetS criterion (high Waist Circumference (WC), high Blood Pressure (BP), high triglyceridemia (TG), low HDL-Cholesterolemia, and high Fasting Plasma Glucose (FPG). Multivariate models were adjusted for age, sex, previous MDD duration, severity of current MDE, and antidepressants., Results: 24.6% of patients had early weight gain. Compared to those without weight gain, patients with early weight gain had higher MetS incidence: 16.7% vs. 6.9% after 3 months (p = 0.07), and 23.8% vs. 7.1% after 6 months (p = 0.02). Among completers (n = 120), early weight gain was significantly associated with later MetS incidence (OR: 5.5) and a higher number of MetS criteria (IRR: 1.7). This effect was driven by the WC, TG, and HDL-C criteria., Conclusion: Compared to Non-early weight gainers, patients with early weight gain in the first month of antidepressant treatment have a significant higher risk of developing MetS during the 6 months of treatment. Early weight monitoring is recommended in order to set preventive measures to avoid new metabolic syndromes in depressed patients treated with antidepressants., (Copyright © 2018. Published by Elsevier Ltd.)

Background: 80-90% of patients with Major Depressive Episode (MDE) experience insomnia and up-to 50% severe insomnia. Glycogen Synthase Kinase-3β (GSK3B) is involved both in mood regulation and circadian rhythm. Since GSK3B polymorphisms could affect protein levels or functionality, we investigated the association of GSK3B polymorphisms with insomnia in a sample of depressed patients treated with antidepressants., Methods: In this 6-month prospective real-world treatment study in psychiatric settings (METADAP), 492 Caucasian patients requiring a new antidepressant treatment were included and genotyped for five GSK3B Single Nucleotide Polymorphisms (SNPs) (rs6808874, rs6782799, rs2319398, rs13321783, rs334558). Insomnia and MDE severity were rated using the Hamilton Depression Rating Scale (HDRS). Bi- and multivariate analyses were performed to assess the association between GSK3B SNPs and insomnia (main objective). We also assessed their association with MDE severity and HDRS response/remission after antidepressant treatment., Results: At baseline severe insomnia was associated with the GSK3B rs334558 minor allele (C+) [OR=1.81, CI95%(1.17-2.80), p=0.008]. GSK3B rs334558 C+ had greater insomnia improvement after 6 months of antidepressant treatment (p=0.007, β=0.17, t=2.736). No association was found between GSK3B SNPs and MDE baseline severity or 6-month response/remission., Conclusion: GSK3B rs334558 was associated with insomnia but not with MDE severity in depressed patients. Targeting GSK3B in patients with MDE and a severe insomnia could be a way to improve their symptoms with greater efficiency. And it should be further studied whether the GSK3B-insomnia association may fit into the larger picture of mood disorders., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Patients with mental disorders have a higher coronary morbidity and mortality as compared to the general population. However, it remains unclear whether their coronary risk scores are higher than those of the general population. We reviewed studies and meta-analyze case-control studies about coronary risk scores in individuals with symptoms or diagnoses of mental disorders. Search was performed in Pubmed and clinical trial registration databases. Four case-control studies were identified, comprising 963 individuals with symptoms or diagnoses of mental disorders and 1681 controls. They focused on the most validated coronary risk score, the Framingham Risk Score 1998 (FRS 1998). The mean FRS 1998 was significantly higher in individuals with symptoms or diagnoses of mental disorders than in the general population 7.9( ± 6.9) vs. 5.0( ± 4.8). FRS 1998 differs between individuals with symptoms or diagnoses of mental disorders and controls (Mean difference:1.84 [95% CI:0.57-3.11], p = 0.005]; high heterogeneity was observed (I 2 = 78%; p < 0.003). The difference was driven by three FRS 1998 criteria: smoking, diabetes and HDL cholesterolemia. The mean FRS 1998 was significantly higher in men, and to a trend in women. In conclusion, individuals with symptoms or diagnoses of mental disorders have a higher coronary risk score than controls. The FRS 1998 should be used as a simple and objective way of monitoring coronary risk in order to improve prevention of coronary events in psychiatric settings., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Tailoring antidepressant drug therapy to each individual patient is a complex process because these drugs have adverse effects leading to discontinuation. Pharmacogenetics may provide useful information in routine practice for optimizing antidepressant treatment by helping limit toxic effects while maintaining efficacy. This review presents the usefulness of pharmacogenetic tests for P450 cytochromes CYP2C19 and CYP2D6 in psychiatric patients taking antidepressants. Depending on the level of evidence, the French National Network of Pharmacogenetics (RNPGx) has issued recommendations stating that pharmacogenetic tests for CYP2D6 and CYP2C19 genes are potentially useful in psychiatric patients treated with antidepressant drugs., (Copyright © 2017 Société française de pharmacologie et de thérapeutique. Published by Elsevier Masson SAS. All rights reserved.)

Pharmacological studies have yielded valuable insights into the role of the serotonin 2A (5-HT2A) receptor in major depressive disorder (MDD) and antidepressant drugs (ADs) response. However, it is still unknown whether genetic variants in the HTR2A gene affect the therapeutic outcome of ADs and the mechanism underlying the regulation of such response remains poorly described. In this context, a translational human-mouse study offers a unique opportunity to address the possibility that variations in the HTR2A gene may represent a relevant marker to predict the efficacy of ADs. In a first part of this study, we investigated in depressed patients the effect of three HTR2A single nucleotide polymorphisms (SNPs), selected for their potential functional consequences on 5-HT2A receptor (rs6313, rs6314 and rs7333412), on response and remission rates after 3 months of antidepressant treatments. We also explored the consequences of the constitutive genetic inactivation of the 5-HT2A receptor (i.e. in 5-HT2A(-/-) mice) on the activity of acute and prolonged administration of SSRIs. Our clinical data indicate that GG patients for the rs7333412 SNP were less prone to respond to ADs than AA/AG patients. In the preclinical study, we demonstrated that the 5-HT2A receptor exerts an inhibitory influence on the neuronal activity of the serotonergic system after acute administration of SSRIs. However, while the chronic administration of the SSRIs escitalopram or fluoxetine elicited a progressive increased in the firing rate of 5-HT neurons in 5-HT2A(+/+) mice, it failed to do so in 5-HT2A(-/-) mutants. These electrophysiological impairments were associated with a decreased ability of the chronic administration of fluoxetine to stimulate hippocampal plasticity and to produce antidepressant-like activities. Genetic loss of the 5-HT2A receptor compromised the activity of chronic treatment with SSRIs, making this receptor a putative marker to predict ADs response., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Background: Incomplete hippocampal inversion (IHI), also called malrotation, is a frequent atypical anatomical pattern of the hippocampus. Because of the crucial implication of the hippocampus in Major Depressive Disorder (MDD) and the neurodevelopmental hypothesis of MDD, we aimed to assess the prevalence of IHI in patients with MDD, the link of IHI with hippocampal volume (HV) and the impact of IHI on the predictive value of HV for response and remission after antidepressant treatment., Methods: IHI (right and left, partial and total and IHI scores) and HV were assessed in 60 patients with a current Major Depressive Episode (MDE) in a context of MDD and 60 matched controls. Patients were prospectively assessed at baseline and after one, three and six months of antidepressant treatment for response and remission., Results: The prevalence of IHI did not significantly differ between MDD patients (right = 23.3%; left = 38.3%) and controls (right = 16.7%; left = 33.3%). IHI was not significantly associated with MDD clinical characteristics. IHI alone did not predict response and remission after antidepressant treatment. However, an interaction between left HV and left IHI predicted six-month response (p = 0.04), HDRS score decrease (p = 0.02) and both three-month (p = 0.04) and six-month (p = 0.03) remission. A case-control design in 30 matched patients with or without left IHI confirmed that interaction. In patients without left IHI, left HV at baseline were smaller in six-month non-remitters as compared to remitters (2.2(± 0.43) cm 3 vs 2.97(± 0.5) cm 3 p = 0.02), and in six-month non-responders as compared to responders (2.18(± 0.42) cm 3 vs 2.86(± 0.54) cm 3 , p = 0.03). In patients with left IHI, no association was found between left HV at baseline and antidepressant response and remission., Conclusion: IHI is not more frequent in MDD patients than in controls, is not associated with HV, but is a confounder that decreases the predictive value of hippocampal volume to predict response or remission after antidepressant treatment. IHI should be systematically assessed in future research studies assessing hippocampal volume in MDD.