Characterizing personal recovery in severe mental illness: French psychometric validation of the Questionnaire about the Process of Recovery (QPR-Fr).

OBJECTIVE: The support of the personal recovery of people with lived experience of mental illness is a major issue in clinical practice. Thus, a valid instrument to assess personal recovery is needed. The present study aimed to validate the French translation of the 22-item Questionnaire about the Process of Recovery (QPR-Fr). METHOD: A convenience sample of 222 participants reporting a severe mental illness diagnosis was recruited online. Psychometric properties of the QPR-Fr were evaluated. A confirmatory factor analysis was conducted for structural validity. Internal consistency and test-retest reliability were assessed. To test for convergent validity, we conducted multiple linear regression analysis to explore the QPR-Fr associations with psychological distress and the CHIME framework (with Connectedness, Hope and optimism about the future, Identity, Meaning in life, and Empowerment) proxy measures (perceived social support, hope, self-esteem, quality of life, and empowerment). RESULTS: An adequate fit was found for a 19-item unidimensional factor structure. Internal consistency was excellent. Test reliability was good. The QPR-Fr total score was significantly positively associated with quality of life, hope, self-esteem, and social support satisfaction and negatively associated with psychological distress. No significant association was found with social support availability nor with empowerment. CONCLUSIONS AND IMPLICATIONS FOR PRACTICE: This study provides additional data to support the cross-cultural validity of the Questionnaire about the Process of Recovery. The QPR-Fr is a valid and reliable tool to assess personal recovery. Practitioners could use the QPR-Fr to assess personal recovery in collaboration with people with lived experience. Convergent validity with CHIME proxy measures supports the validity of the CHIME framework in a French cultural context. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

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.

Accelerated aging in bipolar disorders: An exploratory study of six epigenetic clocks.

Bipolar disorder (BD) is a chronic and severe psychiatric disorder associated with significant medical morbidity and reduced life expectancy. In this study, we assessed accelerated epigenetic aging in individuals with BD using various DNA methylation (DNAm)-based markers. For this purpose, we used five epigenetic clocks (Horvath, Hannum, EN, PhenoAge, and GrimAge) and a DNAm-based telomere length clock (DNAmTL). DNAm profiles were obtained using Infinium MethylationEPIC Arrays from whole-blood samples of 184 individuals with BD. We also estimated blood cell counts based on DNAm levels for adjustment. Significant correlations between chronological age and each epigenetic age estimated using the six different clocks were observed. Following adjustment for blood cell counts, we found that the six epigenetic AgeAccels (age accelerations) were significantly associated with the body mass index. GrimAge AgeAccel was significantly associated with male sex, smoking status and childhood maltreatment. DNAmTL AgeAccel was significantly associated with smoking status. Overall, this study showed that distinct epigenetic clocks are sensitive to different aspects of aging process in BD. Further investigations with comprehensive epigenetic clock analyses and large samples are required to confirm our findings of potential determinants of an accelerated epigenetic aging in BD.

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.

Childhood maltreatment contributes to the medical morbidity of individuals with bipolar disorders.

BACKGROUND: Individuals with bipolar disorders (BD) are at risk of premature death, mainly due to medical comorbidities. Childhood maltreatment might contribute to this medical morbidity, which remains underexplored in the literature. METHODS: We assessed 2891 outpatients with BD (according to DSM-IV criteria). Childhood maltreatment was assessed using the Childhood Trauma Questionnaire. Lifetime diagnoses for medical disorders were retrospectively assessed using a systematic interview and checked against medical notes. Medical morbidity was defined by the sum of medical disorders. We investigated associations between childhood maltreatment (neglect and abuse) and medical morbidity while adjusting for potential confounders. RESULTS: One quarter of individuals had no medical comorbidities, while almost half of them had at least two. Multivariable regression showed that childhood maltreatment (mainly abuse, but also sexual abuse) was associated with a higher medical morbidity. Medical morbidity was also associated with sex, age, body mass index, sleep disturbances, lifetime anxiety disorders and lifetime density of mood episodes. Childhood maltreatment was associated with an increased prevalence of four (i.e. migraine/headache, drug eruption, duodenal ulcer, and thyroid diseases) of the fifteen most frequent medical disorders, however with no difference in terms of age at onset. CONCLUSIONS: This large cross-sectional study confirmed a high medical morbidity in BD and its association with childhood maltreatment. The assessment of childhood maltreatment in individuals with BD should be systematically included in routine care and the potential impact on physical health of psycho-social interventions targeting childhood maltreatment and its consequences should be evaluated.

Crossed clinical features between eating disorders and types of bipolar disorder: Results from the FondaMental Advanced Centers of Expertise - Bipolar Disorder cohort.

BACKGROUND: Eating disorders (EDs) are liable to alter the disease course of bipolar disorder (BD). We explored the crossed clinical features between EDs and BD, particularly as a function of BD type (BD1 vs. BD2). METHODS: 2929 outpatients attending FondaMental Advanced Centers of Expertise were assessed for BD and lifetime EDs with a semi-structured interview, and their sociodemographic, dimensional and clinical data were collected according to a standardized procedure. For each ED type, bivariate analyses were used to investigate associations between these variables and the type of BD type followed by multinomial regressions with the variables associated with EDs and BDs after Bonferroni correction. RESULTS: Comorbid EDs were diagnosed in 478 (16.4 %) cases, and were more prevalent in patients with BD2 than in those with BD1 (20.6 % vs. 12.4 %, p < 0.001). Regression models showed no difference according to the subtype of bipolar disorder on the characteristics of patients with anorexia nervosa (AN), bulimia nervosa (BN) or binge eating disorder (BED). After multiple adjustments, the factors differentiating BD patients with versus without ED were primarily age, gender, body mass index, more affective lability and comorbidity with anxiety disorders. BD patients with BED also scored higher regarding childhood trauma. BD patients with AN also showed higher risk of past suicide attempts than those with BED. CONCLUSIONS: In a large sample of patients with BD, we found a high prevalence of lifetime EDs, especially for the BD2 type. EDs were associated with several severity indicators, but not with BD type-specific characteristics. This should prompt clinicians to carefully screen patients with BD for EDs, regardless of BD and ED types.

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 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=2,367) 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<����������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������������.

Physical and mental health status of former smokers and non-smokers patients with bipolar disorder.

OBJECTIVES: Up to 70% individuals with bipolar disorder (BD) are lifetime tobacco smokers, a major modifiable risk factor for morbidity. However, quitting smoking is rarely proposed to individuals with BD, mainly because of fear of unfavorable metabolic or psychiatric changes. Evaluating the physical and mental impact of tobacco cessation is primordial. The aim of this study was to characterize the psychiatric and nonpsychiatric correlates of tobacco smoking status (never- vs. current vs. former smokers) in individuals with BD. METHODS: 3860 individuals with ascertained BD recruited in the network of Fondamental expert centers for BD between 2009 and 2020 were categorized into current, former, and never tobacco smokers. We compared the sociodemographic and clinical characteristics assessed by standard instruments (e.g., BD type, current symptoms load, and non-psychiatric morbidity-including anthropometric and biological data) of the three groups using multinomial regression logistic models. Corrections for multiple testing were applied. RESULTS: Current smokers had higher depression, anxiety, and impulsivity levels than former and never-smokers, and also higher risk of comorbid substance use disorders with a gradient from never to former to current smokers-suggesting shared liability. Current smokers were at higher risk to have a metabolic syndrome than never-smokers, although this was only evidenced in cases, who were not using antipsychotics. CONCLUSIONS: Tobacco smoking was associated with high morbidity level. Strikingly, as in the general population, quitting smoking seemed associated with their return to the never-smokers' levels. Our findings strongly highlight the need to spread strategies to treat tobacco addiction in the BD population.

Telomere length and mitochondrial DNA copy number in bipolar disorder: A sibling study.

OBJECTIVES: An accelerated cellular ageing has been observed in bipolar disorder (BD) using biomarkers such as telomere length (TL) and mitochondrial DNA copy number (mtDNAcn). Several risk factors might drive premature ageing in individuals with BD, including a familial predisposition. This study compared TL and mtDNAcn between individuals with BD and their (un)-affected siblings, and explored factors that may explain proband-sibling differences. METHODS: Sixty individuals with BD and seventy-four siblings (34 affected with BD or mood disorders and 40 unaffected) were included. Quantitative polymerase chain reaction (qPCR) was used to measure TL and mtDNAcn from peripheral blood genomic DNA. RESULTS: TL and mtDNAcn did not significantly differ between probands and their siblings, whatever these latter were affected or not with mood disorders. However, the correlation plots of TL or mtDNAcn in proband-sibling pairs suggested that some pairs were discordant. The within proband-sibling pairs differences for TL and mtDNAcn were not explained by differences in all tested factors. CONCLUSIONS: This study shows that probands with BD and their siblings are concordant for TL and mtDNAcn suggesting that they may share some environmental or genetic determinants of these two biomarkers of cellular ageing.

Predictors of Functional Impairment in Bipolar Disorder: Results From 13 Cohorts From Seven Countries by the Global Bipolar Cohort Collaborative.

Objectives: Persistent functional impairment is common in bipolar disorder (BD) and is influenced by a number of demographic, clinical, and cognitive features. The goal of this project was to estimate and compare the influence of key factors on community function in multiple cohorts of well-characterized samples of individuals with BD. Methods: Thirteen cohorts from 7 countries included n = 5882 individuals with BD across multiple sites. The statistical approach consisted of a systematic uniform application of analyses across sites. Each site performed a logistic regression analysis with empirically derived "higher versus lower function" as the dependent variable and selected clinical and demographic variables as predictors. Results: We found high rates of functional impairment, ranging from 41 to 75%. Lower community functioning was associated with depressive symptoms in 10 of 12 of the cohorts that included this variable in the analysis. Lower levels of education, a greater number of prior mood episodes, the presence of a comorbid substance use disorder, and a greater total number of psychotropic medications were also associated with low functioning. Conclusions: The bipolar clinical research community is poised to work together to characterize the multi-dimensional contributors to impairment and address the barriers that impede patients' complete recovery. We must also identify the core features which enable many to thrive and live successfully with BD. A large-scale, worldwide, prospective longitudinal study focused squarely on BD and its heterogeneous presentations will serve as a platform for discovery and promote major advances toward optimizing outcomes for every individual with this illness.Reprinted from Bipolar Disord 2022; 24:709-719, with permission from John Wiley and Sons. Copyright © 2022.

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

Monitoring 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.

Preventive Medication Patterns in Bipolar Disorder and Their Relationship With Comorbid Substance Use Disorders in a Cross-National Observational Study.

Objective: The potential role of sub-optimal pharmacological treatment in the poorer outcomes observed in bipolar disorder (BD) with vs. without comorbid substance use disorders (SUDs) is not known. Thus, we investigated whether patients with BD and comorbid SUD had different medication regimens than those with BD alone, in samples from France and Norway, focusing on compliance to international guidelines. Methods: Seven hundred and seventy patients from France and Norway with reliably ascertained BD I or II (68% BD-I) were included. Medication information was obtained from patients and hospital records, and preventive treatment was categorized according to compliance to guidelines. We used Bayesian and regression analyses to investigate associations between SUD comorbidity and medication. In the Norwegian subsample, we also investigated association with lack of medication. Results: Comorbid SUDs were as follows: current tobacco smoking, 26%, alcohol use disorder (AUD), 16%; cannabis use disorder (CUD), 10%; other SUDs, 5%. Compliance to guidelines for preventive medication was lacking in 8%, partial in 44%, and complete in 48% of the sample. Compliance to guidelines was not different in BD with and without SUD comorbidity, as was supported by Bayesian analyses (highest Bayes Factor = 0.16). Cross national differences in treatment regimens led us to conduct country-specific adjusted regression analyses, showing that (1) CUD was associated with increased antipsychotics use in France (OR = 2.4, 95% CI = 1.4-3.9, p = 0.001), (2) current tobacco smoking was associated with increased anti-epileptics use in Norway (OR = 4.4, 95% CI = 1.9-11, p < 0.001), and (3) AUD was associated with decreased likelihood of being medicated in Norway (OR = 1.2, 95% CI = 1.04-1.3, p = 0.038). Conclusion: SUD comorbidity in BD was overall not associated with different pharmacological treatment in our sample, and not related to the level of compliance to guidelines. We found country-specific associations between comorbid SUDs and specific medications that warrant further studies.

Predictors of functional impairment in bipolar disorder: Results from 13 cohorts from seven countries by the global bipolar cohort collaborative.

OBJECTIVES: Persistent functional impairment is common in bipolar disorder (BD) and is influenced by a number of demographic, clinical, and cognitive features. The goal of this project was to estimate and compare the influence of key factors on community function in multiple cohorts of well-characterized samples of individuals with BD. METHODS: Thirteen cohorts from 7 countries included n = 5882 individuals with BD across multiple sites. The statistical approach consisted of a systematic uniform application of analyses across sites. Each site performed a logistic regression analysis with empirically derived "higher versus lower function" as the dependent variable and selected clinical and demographic variables as predictors. RESULTS: We found high rates of functional impairment, ranging from 41 to 75%. Lower community functioning was associated with depressive symptoms in 10 of 12 of the cohorts that included this variable in the analysis. Lower levels of education, a greater number of prior mood episodes, the presence of a comorbid substance use disorder, and a greater total number of psychotropic medications were also associated with low functioning. CONCLUSIONS: The bipolar clinical research community is poised to work together to characterize the multi-dimensional contributors to impairment and address the barriers that impede patients' complete recovery. We must also identify the core features which enable many to thrive and live successfully with BD. A large-scale, worldwide, prospective longitudinal study focused squarely on BD and its heterogeneous presentations will serve as a platform for discovery and promote major advances toward optimizing outcomes for every individual with this illness.

Direct medical cost of bipolar disorder: Insights from the FACE-BD longitudinal cohort.

BACKGROUND: Bipolar disorder (BD) is a severe chronic psychiatric disorder affecting 0.5 to 1% of the population worldwide. To date, most studies have estimated the cost of BD via information sourced from insurance claims with limited information on clinical characteristics and course of BD. The aims of this study are (i) to estimate the direct healthcare cost associated with BD and to identify contributing factors and (ii) to study the evolution of cost during a two-year follow-up period. METHOD: We analyzed a sample of 1116 individuals with BD included in the Advanced Centers of Expertise in Bipolar Disorder cohort. We estimated the direct healthcare cost per year and per patient, and we identified the clinical features of patients with BD associated with higher direct healthcare costs. In a subsample of patients followed up for two years centers of expertise for BD, we studied the evolution of direct healthcare cost. RESULTS: The average cost of bipolar disorder was € 6910 per year and per patient. Clinical features of BD, sociodemographic characteristics, and associated addiction were associated with higher direct healthcare costs. In the subsample of patients followed-up for two years, direct healthcare cost dropped by more than 50%, strongly suggesting the beneficial effect of specialized care organization. LIMITATION: We did not estimate indirect healthcare and intangible costs. CONCLUSION: Our study investigates the cost of BD and its evolution in a deeply phenotyped longitudinal sample. Cost-utility and cost-effectiveness analyses are required to inform resource allocation decisions and to promote innovative healthcare organizations.

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.