Prise de décision en contexte d’apprentissage par renforcement dans les troubles bipolaires : étude de la sensibilité à la récompense et à la punition en fonction du sous-type de trouble bipolaire

Phenotypic expression of bipolar disorder (BD) is wide and two bipolar subtypes prevail, bipolar 1 subtype (BD-I) and bipolar 2 subtype (BD-II). Decision-making and reward processing, which are involved into goal-directed behaviors, are largely documented into BD, related to the relevance of these behaviors (increased or decreased) during thymic relapse. Most of these studies doesn’t taking account this widely phenotypic expression, and include BD patients of both groups, or only BD-I patients. Very few studies investigate reward and punishment learning according to BD subtype. To date, neurobiology of BD-II still largely unknown, and some authors think about distinct pattern activation between BD-I and BD-II. Our study examines decision making during appetitive and punitive reinforcement learning, relative to BD subtype and healthy subjects. Our results showed reward hyposensitivity in BD than healthy subjects, but subtype didn’t differ. Nonetheless, we didn’t show difference in punishment processing between BD patients and healthy subjects, with a difference in punishment learning relative to BD subtype, with lower performance in BD-II, compared with BD-I. To date, no studies examine punishment processing in neuroimaging in BD-II, which could constitute a trait-dependent-marker of BD-II.L’expression phénotypique des troubles bipolaires (TB) est variée et deux sous-types prédominent, à savoir le type 1 (TB1) et le type 2 (TB2). L’étude de la prise de décision et du traitement de la récompense sous-tendant les comportements orientés vers un but a été étudiée dans le TB, du fait de la place centrale de ces comportements (majorés ou minorés) lors des décompensations thymiques. La plupart de ces études ne prennent pas en compte cette variabilité phénotypique et incluent soit des patients des deux sous-types, soit uniquement des TB1. Très peu d’études se sont intéressées à observer l’apprentissage de la récompense et de la punition en fonction du sous-type. La neurobiologie du TB2 reste à ce jour très peu connue, de nombreux auteurs mettant en avant des corrélats neurobiologiques bien distincts dans le TB2 par rapport au TB1. Notre étude s’est donc intéressée à la prise de décision en contexte d’apprentissage par renforcement appétitif et punitif, selon le sous-type de trouble bipolaire par rapport à des sujets sains. Nos résultats ont montré une hyposensibilité à la récompense dans les TB par rapport aux sujets sains, les sous-types ne différant cependant pas entre eux. D’un autre côté, nous n’avons pas mis en évidence de différence de performance entre les patients et les sujets sains dans le traitement de la punition, mais une différence dans l’apprentissage de la punition en fonction du sous-type avec des performances moindres pour le TB2 par rapport au TB1. Aucune étude à ce jour n’a évalué en neuroimagerie fonctionnelle le traitement de la punition dans le TB2 par rapport au TB1, ce qui pourrait constituer un potentiel marqueur-trait du TB2

Management of schizophrenia in women during the perinatal period: a synthesis of international recommendations

International audienc

Reward and punishment learning deficits among bipolar disorder subtypes

Objectives: Bipolar disorder (BD) is defined by alternation of depressive and (hypo)manic states. An essential dimension related to mood fluctuations is reward sensitivity. The expression of mood disorders can be modulated by environmental factors and life events, as well as by their subsequent learning related to reward or punishment sensitivity. According to the dimensional focus of the Research Domain Criteria, BD subtypes may be conceptualized as a spectrum in which reward sensitivity is a key dimension of pathology. Here, we examine reward maximizations vs. punishment avoidance learning in patients with BD during intercritical phase to test this hypothesis. Methods: Patients with BD-I (n=45), BD-II (n=34) and age and gender matched (n=30) healthy controls (HC) participated to the study. They performed an instrumental learning task designed to dissociate reward-based from punishment-based reinforcement learning. Computational modeling was used to identify the mechanisms underlying reinforcement learning performance. Results: Behavioral results showed a significant reward learning deficit across BD subtypes compared to HC. Conversely, BD-I patients performed better during punishment avoidance learning than BD-II patients. Computational analysis indicated that the observed reward-based learning deficit was captured by a lower reinforcement magnitude in both BD subtypes, when compared to HC. The punishment-based learning deficit was captured by a higher choice randomness in the BD-II compared to BD-I patients’ group. Conclusions: Our results are consistent with the reward hyposensitivity theory in BD. Furthermore, our results also suggest that studying punishment avoidance learning across BD subtypes could be useful for classification and consequent treatment tailoring in BD

Pharmacological treatment profiles in the FACE-BD cohort: Treatment description and complete data for bipolar subtypes

International audienceIn the current study, we provide the list of pharmacological interventions applied during the one-year follow-up period of the Pharmacological treatment profiles in the FACE-BD cohort study. These data show the treatments used in the new clusters formed in this previous study and also in usual bipolarity subtypes. The proportion of each treatment used during the follow-up was calculated. Days on each treatment were also included in this dataset. The complete clinical and paraclinical data analyzed for clusters and bipolar subtypes were included in this dataset. Socio-demographic self-administered and clinician-administered scales, clinical evaluation during the follow-up, psychiatric and somatic comorbidities, and blood tests are shown in this material

Pharmacological treatment profiles in the FACE-BD cohort: An unsupervised machine learning study, applied to a nationwide bipolar cohort✰

International audienceBackground: Despite thorough and validated clinical guidelines based on bipolar disorders subtypes, large pharmacological treatment heterogeneity remains in these patients. There is limited knowledge about the different treatment combinations used and their influence on patient outcomes. We attempted to determine profiles of patients based on their treatments and to understand the clinical characteristics associated with these treatment profiles.Methods: This multicentre longitudinal study was performed on a French nationwide bipolar cohort database. We performed hierarchical agglomerative clustering to search for clusters of individuals based on their treatments during the first year following inclusion. We then compared patient clinical characteristics according to these clusters.Results: Four groups were identified among the 1795 included patients: group 1 ("heterogeneous" n = 1099), group 2 ("lithium" n = 265), group 3 ("valproate" n = 268), and group 4 ("lamotrigine" n = 163). Proportion of bipolar 1 disorder, in groups 1 to 4 were: 48.2%, 57.0%, 48.9% and 32.5%. Groups 1 and 4 had greater functional impact at baseline and a less favorable clinical and functioning evolution at one-year follow-up, especially on GAF and FAST scales.Limitations: The one-year period used for the analysis of mood stabilizing treatments remains short in the evolution of bipolar disorder.Conclusions: Treatment profiles are associated with functional evolution of patients and were not clearly determined by bipolar subtypes. These profiles seem to group together common patient phenotypes. These findings do not seem to be influenced by the duration of disease prior to inclusion and neither by the number of treatments used during the follow-up period

Factors associated with lamotrigine concentration/dose ratio in individuals with bipolar disorders

International audienceMonitoring of lamotrigine levels is recommended in epilepsy. However, in bipolar disorders (BD), no study has described the therapeutic range in daily practice and factors being associated to it. We used retrospective data of individuals with BD, treated with lamotrigine, and included in the FondaMental Advanced Centers of Expertise for Bipolar Disorders cohort. We extracted clinical and biological data and explored associations between these variables and lamotrigine concentration/dose (C/D) ratio. The database included 675 individuals who received lamotrigine at inclusion, whose main characteristics were female sex (68.3%) and BD type 2 (52.1%). Data about lamotrigine C/D ratio were available for 205 individuals. Lamotrigine C/D ratio was significantly associated with: Body Mass Index (BMI) (r=-0.159), estimated GFR (glomerular filtration rate) (r=-0.228), total bilirubin (r = 0.241) and at a trend level, antidepressant co-prescription (U = 3169). The model obtained was: lamotrigine C/D ratio = 1.736 - 0.013*BMI + 0.095*total bilirubin (UI/L) - 0.007*eGFR (ml/min) + 0.210*AST/ALT – 0.004*GGT (UI/L) + 0.014*age (year) + 0.303*currently smoking (yes or no) – 0.588*antidepressant co-prescription (yes or no) – 0.357*gender (F = 1.899, p = 0.057, adjusted R2 = 0.11) Information about plasma lamotrigine C/D ratio were available for only 205 out of the 675 individuals in the database and has been obtained from different laboratories. The representativeness of the included sample may be questionable. This is the first study providing information on a large sample of individuals with BD regarding factors associated with lamotrigine C/D ratio. This study allows to propose a model of lamotrigine C/D ratio that would deserve further replication

What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group.

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness