Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Exploring the genetics of lithium response in bipolar disorders.

Background: Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N=2,064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results: We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions: Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Lithium Response in Bipolar Disorder is Associated with Focal Adhesion and PI3K-Akt Networks: A Multi-omics Replication Study.

Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2,039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Deep brain stimulation and digital monitoring for patients with treatment-resistant schizophrenia and bipolar disorder: A case series.

AIM: The use of deep brain stimulation (DBS) has been recently extended for treating resistant psychiatric disorders, but the experience in patients with schizophrenia-related disorders and bipolar disorder (BD) is scarce. METHOD: We conducted an observational, one-year longitudinal study to evaluate the effects of DBS in four treatment-resistant patients with schizophrenia, schizoaffective, and BD, included in a pilot, last-resource protocol. Patients were digitally monitored for objective assessment of behavioral changes. RESULTS: After one year of its initiation, DBS of the nucleus accumbens (in subjects N2, N3, and N4) and subgenual anterior cingulate cortex (in N1) produced a significant clinical improvement, associated with decreases in the Clinical Global Impression (from 5.25±0.5 to 3.5±1, p=0.035) and in the Hamilton Depression Rating Scale (HADRS scores, from 14.5±6.56 to 1.5±1.29, p=0.020). We observed a notable, durable therapeutic response in two patients from this cohort (N1 and N3), a clinically relevant relief in a third (N2), and a lack of a significant response in the last one (N4). Maintenance electroconvulsive therapy sessions could be discontinued in the three patients that responded to DBS (N1-3). There were no side effects or relevant changes in cognitive functioning. There were relevant differences between physical activity and sleep time among the four participants. CONCLUSIONS: These results suggest initial evidence that DBS may be an effective and safe alternative for treating complex and resistant forms of schizophrenia-related disorders and BD. Digital monitoring may help to capture objective measures of behavioral changes after the intervention.

Effects of malnutrition on length of stay in patients hospitalized in an acute psychiatric ward.

INTRODUCTION: Psychiatric patients are considered at risk for malnutrition due to pharmacological treatments, lifestyle habits and the mental illness by itself. Even though metabolic risk factors have been related to worse outcomes in certain conditions, the evidence regarding the nutritional status and its impact on the length of stay in psychiatric inpatients is scarce. This study aims to characterize the nutritional status in acute psychiatric patients, to correlate it with the length of stay, and to find specific potential indicators of malnutrition. METHODS: Adult patients admitted to the Hospital Clínic of Barcelona acute psychiatric ward throughout a 1-year period were included in this cross-sectional study. Sociodemographic and clinical variables were registered, including length of stay and the nutritional status measured with the CONUT score. RESULTS: Malnutrition was observed in 42.5% of patients. Plasmatic transferrin saturation, protein and iron levels were inversely correlated with length of stay, having low iron levels an association with longer hospitalizations. The length of stay was not influenced by diagnosis or treatment. Negative correlations with the nutritional status were found in: BMI, cholesterol, triglycerides, albumin, total proteins, prealbumin, iron, lymphocytes and zinc levels, and transferrin saturation. The multivariate analysis showed a significant association for cholesterol and zinc levels, lymphocyte count, and BMI. CONCLUSIONS: Our results suggest that nutritional status might influence the course of psychiatric admissions. Cholesterol and zinc levels, lymphocyte count, and BMI might be factors strongly associated with malnutrition. This consideration might allow the identification of profiles in which lifestyle interventions could be implemented.

Association of polygenic score and the involvement of cholinergic and glutamatergic pathways with lithium treatment response in patients with bipolar disorder.

Lithium is regarded as the first-line treatment for bipolar disorder (BD), a severe and disabling mental health disorder that affects about 1% of the population worldwide. Nevertheless, lithium is not consistently effective, with only 30% of patients showing a favorable response to treatment. To provide personalized treatment options for bipolar patients, it is essential to identify prediction biomarkers such as polygenic scores. In this study, we developed a polygenic score for lithium treatment response (Li+PGS) in patients with BD. To gain further insights into lithium's possible molecular mechanism of action, we performed a genome-wide gene-based analysis. Using polygenic score modeling, via methods incorporating Bayesian regression and continuous shrinkage priors, Li+PGS was developed in the International Consortium of Lithium Genetics cohort (ConLi+Gen: N = 2367) and replicated in the combined PsyCourse (N = 89) and BipoLife (N = 102) studies. The associations of Li+PGS and lithium treatment response - defined in a continuous ALDA scale and a categorical outcome (good response vs. poor response) were tested using regression models, each adjusted for the covariates: age, sex, and the first four genetic principal components. Statistical significance was determined at P < 0.05. Li+PGS was positively associated with lithium treatment response in the ConLi+Gen cohort, in both the categorical (P = 9.8 × 10-12, R2 = 1.9%) and continuous (P = 6.4 × 10-9, R2 = 2.6%) outcomes. Compared to bipolar patients in the 1st decile of the risk distribution, individuals in the 10th decile had 3.47-fold (95%CI: 2.22-5.47) higher odds of responding favorably to lithium. The results were replicated in the independent cohorts for the categorical treatment outcome (P = 3.9 × 10-4, R2 = 0.9%), but not for the continuous outcome (P = 0.13). Gene-based analyses revealed 36 candidate genes that are enriched in biological pathways controlled by glutamate and acetylcholine. Li+PGS may be useful in the development of pharmacogenomic testing strategies by enabling a classification of bipolar patients according to their response to treatment.

Immunogenetics of lithium response and psychiatric phenotypes in patients with bipolar disorder.

The link between bipolar disorder (BP) and immune dysfunction remains controversial. While epidemiological studies have long suggested an association, recent research has found only limited evidence of such a relationship. To clarify this, we investigated the contributions of immune-relevant genetic factors to the response to lithium (Li) treatment and the clinical presentation of BP. First, we assessed the association of a large collection of immune-related genes (4,925) with Li response, defined by the Retrospective Assessment of the Lithium Response Phenotype Scale (Alda scale), and clinical characteristics in patients with BP from the International Consortium on Lithium Genetics (ConLi+Gen, N = 2,374). Second, we calculated here previously published polygenic scores (PGSs) for immune-related traits and evaluated their associations with Li response and clinical features. We found several genes associated with Li response at p < 1×10- 4 values, including HAS3, CNTNAP5 and NFIB. Network and functional enrichment analyses uncovered an overrepresentation of pathways involved in cell adhesion and intercellular communication, which appear to converge on the well-known Li-induced inhibition of GSK-3ß. We also found various genes associated with BP's age-at-onset, number of mood episodes, and presence of psychosis, substance abuse and/or suicidal ideation at the exploratory threshold. These included RTN4, XKR4, NRXN1, NRG1/3 and GRK5. Additionally, PGS analyses suggested serum FAS, ECP, TRANCE and cytokine ligands, amongst others, might represent potential circulating biomarkers of Li response and clinical presentation. Taken together, our results support the notion of a relatively weak association between immunity and clinically relevant features of BP at the genetic level.

Using polygenic scores and clinical data for bipolar disorder patient stratification and lithium response prediction: machine learning approach.

BACKGROUND: Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment. AIMS: To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder. METHOD: This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework. RESULTS: The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data. CONCLUSIONS: Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Evaluating maintenance electroconvulsive therapy in Bipolar Disorders: 3-year mirror-image study.

BACKGORUND: Maintenance electroconvulsive therapy (mECT) is underused in the treatment of bipolar disorder (BD). We aimed to study the real-life effectiveness of mECT in BD. METHODS: Naturalistic 3-year mirror-image study in individuals diagnosed with BD who underwent mECT at a tertiary hospital. Intra-subject comparisons of psychiatric hospitalization were performed using McNemar test. Days and number of psychiatric hospitalizations before and during mECT were compared through wilcoxon signed-rank test. Mean annual days and mean annual number of psychiatric hospitalizations per patient were compared by means of the rate ratio (RR) estimation through a generalized estimating equation (GEE) model. RESULTS: A total of 43 patients were included and 37 required psychiatric hospitalization during the study. The use of mECT showed an effectiveness of 62.2% for preventing psychiatric hospitalizations (p<0.01). We found significant reduction in days and number of psychiatric hospitalizations during mECT compared to before mECT (p<0.01). Comparison of the 3-year period before/during mECT showed a reduction in mean annual days (RR=0.14; 95%CI: 0.07-0.29) and mean annual number (RR=0.24; 95%CI: 0.13-0.43) of psychiatric hospitalizations, without substantial changes for adjusted models for gender and age of onset of the illness. LIMITATIONS: The main limitations of this study consisted of the mirror-image retrospective naturalistic study design, the relatively small sample size, and possibly patient selection bias. CONCLUSIONS: mECT reduced the number of psychiatric hospitalizations and hospitalization days in BD. The use of mECT outlines a mood stabilizing effect in BD. This naturalistic study supports the effectiveness of mECT in BD across several mood states.

Identifying neurocognitive heterogeneity in Older Adults with Bipolar Disorder: a cluster analysis.

BACKGROUND: Cognitive profiles of BD patients show a demonstrated heterogeneity among young and middle-aged patients, but this issue has not yet deeply explored in Older Adults with bipolar disorder (OABD). The aim of the present study was to analyze cognitive variability in a sample of OABD. METHODS: A total of 138 OABD patients and 73 healthy controls were included in this study. A comprehensive neuropsychological assessment was administered. We performed a k-means cluster analysis method based on the neurocognitive performance to detect heterogeneous subgroups. Demographic, clinical, cognitive and functional variables were compared. Finally, univariate logistic regressions were conducted to detect variables associated with the severity of the cognitive impairment. RESULTS: We identified three distinct clusters based on the severity of cognitive impairment: (1) a preserved group (n = 58; 42%) with similar cognitive performance to HC, (2) a group showing mild cognitive deficits in all cognitive domains (n = 64; 46%) and, finally, (3) a group exhibiting severe cognitive impairment (n = 16; 12%). Older age, late onset, higher number of psychiatric admissions and lower psychosocial functioning were associated with the greatest cognitive impairment. Lower age, more years of education and higher estimated IQ were associated with a preserve cognitive functioning. LIMITATIONS: The small sample size of the severely impaired group. CONCLUSIONS: Cognitive heterogeneity remains at late-life bipolar disorder. Demographic and specific illness factors are related to cognitive dysfunction. Detecting distinct cognitive subgroups may have significant clinical implications for tailoring specific intervention strategies adapted to the level of the impairment and also to prevent cognitive decline.

Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients.

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders.

Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × 10-3; FDR < 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common inflammatory/autoimmune processes, our findings strongly suggest that HLA-mediated low inflammatory background may contribute to the efficient response to Li in BD patients, while an inflammatory status overriding Li anti-inflammatory properties would favor a weak response.

Association of polygenic score for major depression with response to lithium in patients with bipolar disorder.

Lithium is a first-line medication for bipolar disorder (BD), but only one in three patients respond optimally to the drug. Since evidence shows a strong clinical and genetic overlap between depression and bipolar disorder, we investigated whether a polygenic susceptibility to major depression is associated with response to lithium treatment in patients with BD. Weighted polygenic scores (PGSs) were computed for major depression (MD) at different GWAS p value thresholds using genetic data obtained from 2586 bipolar patients who received lithium treatment and took part in the Consortium on Lithium Genetics (ConLi+Gen) study. Summary statistics from genome-wide association studies in MD (135,458 cases and 344,901 controls) from the Psychiatric Genomics Consortium (PGC) were used for PGS weighting. Response to lithium treatment was defined by continuous scores and categorical outcome (responders versus non-responders) using measurements on the Alda scale. Associations between PGSs of MD and lithium treatment response were assessed using a linear and binary logistic regression modeling for the continuous and categorical outcomes, respectively. The analysis was performed for the entire cohort, and for European and Asian sub-samples. The PGSs for MD were significantly associated with lithium treatment response in multi-ethnic, European or Asian populations, at various p value thresholds. Bipolar patients with a low polygenic load for MD were more likely to respond well to lithium, compared to those patients with high polygenic load [lowest vs highest PGS quartiles, multi-ethnic sample: OR = 1.54 (95% CI: 1.18-2.01) and European sample: OR = 1.75 (95% CI: 1.30-2.36)]. While our analysis in the Asian sample found equivalent effect size in the same direction: OR = 1.71 (95% CI: 0.61-4.90), this was not statistically significant. Using PGS decile comparison, we found a similar trend of association between a high genetic loading for MD and lower response to lithium. Our findings underscore the genetic contribution to lithium response in BD and support the emerging concept of a lithium-responsive biotype in BD.

Genetic differences between bipolar disorder subtypes: A systematic review focused in bipolar disorder type II.

BACKGROUND: The identification of bipolar disorder (BD) type II patients has both treatment and prognostic implications. Better understanding of its underlying genetics may yield useful diagnostic tools. METHODS: A systematic review on BDII genetics was done using articles published in 2009-2019, following PRISMA recommendations. RESULTS: The most studied polymorphism was BDNF Val66Met with several gene-gene interactions within the dopaminergic system. Associations were reported within the monoaminergic systems (DRD3, ADH1B and SLC6A4), calcium (CACNB2 and CACNG2) and cAMP (PDE1DA, PDE4B and DISC1) signal transduction pathways and the immune system (TNFα, IFNδ and IL-10). Chromosomes 2, 3 and 10 were associated with BDII and polygenic risk scores distinguished between BD subtypes and with major depressive disorder. CONCLUSIONS: Research on BDII stems from BDI findings, however with a stronger contribution of gene-gene interactions and low-effect alleles on known neuroplasticity and monoaminergic system genes. Genome studies point to transdiagnostic backgrounds, with wider associations across bipolar spectrum disorders. Findings able to accurately differentiate BDII remain elusive, dependent on better phenotypic characterization and new research methods.

Uso de asenapina en la práctica clínica: recomendaciones de un panel de expertos / Management of asenapine treatment in clinical practice: Recommendations from a panel of experts

Introducción: La selección del antipsicótico adecuado para el tratamiento de pacientes con trastorno bipolar (TB) debe basarse en los síntomas presentes, así como en las necesidades terapéuticas de cada paciente y en los posibles efectos adversos asociados al tratamiento. Asenapina es un antipsicótico de segunda generación indicado para el tratamiento de pacientes con TB de tipoI, cuyo perfil farmacocinético y farmacodinámico presenta características diferenciales con respecto al resto de antipsicóticos. Material y métodos: Este documento de recomendaciones ha sido elaborado por un panel de expertos con experiencia en el uso de asenapina en los ámbitos de la atención psiquiátrica de urgencias, hospitalaria y ambulatoria. Las recomendaciones se debatieron en una única reunión y fueron elaboradas a partir de la práctica clínica de los expertos y la evidencia proporcionada por la literatura científica. Resultados: Se describe el perfil de pacientes que mejor se ajusta a las características farmacodinámicas de asenapina, así como las ventajas y limitaciones del perfil farmacocinético asociado a la administración sublingual. Se abordan también las principales características de seguridad de asenapina, así como las posibles medidas a tomar para mitigar los efectos adversos más frecuentes. Finalmente, el documento proporciona una orientación acerca de la dosificación y el manejo general del fármaco, incluyendo las combinaciones con otros fármacos y el cambio de otros antipsicóticos a asenapina. Conclusiones: Este artículo proporciona una orientación para el uso adecuado de asenapina, así como para la identificación de los pacientes en los que este antipsicótico puede resultar más adecuado

Introduction: The choice of an antipsychotic should be based on bipolar disorder (BD) symptoms and the particular needs of each patient, as well as the adverse events potentially associated with treatment. Asenapine is an atypical antipsychotic indicated for the management of type-I BD, with distinct pharmacokinetic and receptor affinity profiles. Material and methods: Recommendations document developed by a panel of experts with extensive experience in the use of asenapine in psychiatric care, including emergency department, hospital, and outpatient care. Recommendations were discussed in a single meeting and were based on both the clinical experience of the panel of experts and the empirical evidence provided in the scientific literature. Results: The present document describes the patient profile that best suits the pharmacodynamic characteristics of asenapine, as well as the advantages and limitations of the pharmacokinetics associated with the sublingual route. The document also addresses the main safety issues of asenapine and suggests interventions aimed at mitigating the most frequent adverse reactions associated with asenapine treatment. Finally, the article provides advice on dosing and overall management of asenapine treatment, including the combination with other treatments and the switch from other antipsychotics to asenapine. Conclusions: In this recommendations document, we provide clinicians with guidance on the use of asenapine in real-life practice, including the identification of patients who best suit the characteristics of this antipsychotic

Management of asenapine treatment in clinical practice: Recommendations from a panel of experts. / Uso de asenapina en la práctica clínica: recomendaciones de un panel de expertos.

INTRODUCTION: The choice of an antipsychotic should be based on bipolar disorder (BD) symptoms and the particular needs of each patient, as well as the adverse events potentially associated with treatment. Asenapine is an atypical antipsychotic indicated for the management of type-I BD, with distinct pharmacokinetic and receptor affinity profiles. MATERIAL AND METHODS: Recommendations document developed by a panel of experts with extensive experience in the use of asenapine in psychiatric care, including emergency department, hospital, and outpatient care. Recommendations were discussed in a single meeting and were based on both the clinical experience of the panel of experts and the empirical evidence provided in the scientific literature. RESULTS: The present document describes the patient profile that best suits the pharmacodynamic characteristics of asenapine, as well as the advantages and limitations of the pharmacokinetics associated with the sublingual route. The document also addresses the main safety issues of asenapine and suggests interventions aimed at mitigating the most frequent adverse reactions associated with asenapine treatment. Finally, the article provides advice on dosing and overall management of asenapine treatment, including the combination with other treatments and the switch from other antipsychotics to asenapine. CONCLUSIONS: In this recommendations document, we provide clinicians with guidance on the use of asenapine in real-life practice, including the identification of patients who best suit the characteristics of this antipsychotic.

Investigating polygenic burden in age at disease onset in bipolar disorder: Findings from an international multicentric study.

OBJECTIVES: Bipolar disorder (BD) with early disease onset is associated with an unfavorable clinical outcome and constitutes a clinically and biologically homogenous subgroup within the heterogeneous BD spectrum. Previous studies have found an accumulation of early age at onset (AAO) in BD families and have therefore hypothesized that there is a larger genetic contribution to the early-onset cases than to late onset BD. To investigate the genetic background of this subphenotype, we evaluated whether an increased polygenic burden of BD- and schizophrenia (SCZ)-associated risk variants is associated with an earlier AAO in BD patients. METHODS: A total of 1995 BD type 1 patients from the Consortium of Lithium Genetics (ConLiGen), PsyCourse and Bonn-Mannheim samples were genotyped and their BD and SCZ polygenic risk scores (PRSs) were calculated using the summary statistics of the Psychiatric Genomics Consortium as a training data set. AAO was either separated into onset groups of clinical interest (childhood and adolescence [≤18 years] vs adulthood [>18 years]) or considered as a continuous measure. The associations between BD- and SCZ-PRSs and AAO were evaluated with regression models. RESULTS: BD- and SCZ-PRSs were not significantly associated with age at disease onset. Results remained the same when analyses were stratified by site of recruitment. CONCLUSIONS: The current study is the largest conducted so far to investigate the association between the cumulative BD and SCZ polygenic risk and AAO in BD patients. The reported negative results suggest that such a polygenic influence, if there is any, is not large, and highlight the importance of conducting further, larger scale studies to obtain more information on the genetic architecture of this clinically relevant phenotype.

Analysis of the Influence of microRNAs in Lithium Response in Bipolar Disorder.

Bipolar disorder (BD) is a common, highly heritable neuropsychiatric disease characterized by recurrent episodes of mania and depression. Lithium is the best-established long-term treatment for BD, even though individual response is highly variable. Evidence suggests that some of this variability has a genetic basis. This is supported by the largest genome-wide association study (GWAS) of lithium response to date conducted by the International Consortium on Lithium Genetics (ConLiGen). Recently, we performed the first genome-wide analysis of the involvement of miRNAs in BD and identified nine BD-associated miRNAs. However, it is unknown whether these miRNAs are also associated with lithium response in BD. In the present study, we therefore tested whether common variants at these nine candidate miRNAs contribute to the variance in lithium response in BD. Furthermore, we systematically analyzed whether any other miRNA in the genome is implicated in the response to lithium. For this purpose, we performed gene-based tests for all known miRNA coding genes in the ConLiGen GWAS dataset (n = 2,563 patients) using a set-based testing approach adapted from the versatile gene-based test for GWAS (VEGAS2). In the candidate approach, miR-499a showed a nominally significant association with lithium response, providing some evidence for involvement in both development and treatment of BD. In the genome-wide miRNA analysis, 71 miRNAs showed nominally significant associations with the dichotomous phenotype and 106 with the continuous trait for treatment response. A total of 15 miRNAs revealed nominal significance in both phenotypes with miR-633 showing the strongest association with the continuous trait (p = 9.80E-04) and miR-607 with the dichotomous phenotype (p = 5.79E-04). No association between miRNAs and treatment response to lithium in BD in either of the tested conditions withstood multiple testing correction. Given the limited power of our study, the investigation of miRNAs in larger GWAS samples of BD and lithium response is warranted.