Physical pain is a common issue in people with bipolar disorder (BD). It worsens mental health and quality of life, negatively impacts treatment response, and increases the risk of suicide. Lithium, which is prescribed in BD as a mood stabilizer, has shown promising effects on pain.

This naturalistic study included 760 subjects with BD ( FACE-BD cohort) divided in two groups: with and without self-reported pain (evaluated with the EQ-5D-5L questionnaire). In this sample, 176 subjects were treated with lithium salts. The objectives of the study were to determine whether patients receiving lithium reported less pain, and whether this effect was associated with the recommended mood-stabilizing blood concentration of lithium.

Subjects with lithium intake were less likely to report pain (odds ratio [OR] = 0.59, 95% confidence interval [CI], 0.35–0.95; p = 0.036) after controlling for sociodemographic variables, BD type, lifetime history of psychiatric disorders, suicide attempt, personality traits, current depression and anxiety levels, sleep quality, and psychomotor activity. Subjects taking lithium were even less likely to report pain when lithium concentration in blood was ≥0.5 mmol/l (OR = 0.45, 95% CI, 0.24–0.79; p = 0.008).

This is the first naturalistic study to show lithium’s promising effect on pain in subjects suffering from BD after controlling for many confounding variables. This analgesic effect seems independent of BD severity and comorbid conditions. Randomized controlled trials are needed to confirm the analgesic effect of lithium salts and to determine whether lithium decreases pain in other vulnerable populations.

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.

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.

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.

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.

Converging evidence suggests that a subgroup of bipolar disorder (BD) with an early age at onset (AAO) may develop from aberrant neurodevelopment. However, the definition of early AAO remains unprecise. We thus tested which age cut-off for early AAO best corresponds to distinguishable neurodevelopmental pathways.

We analyzed data from the FondaMental Advanced Center of Expertise-Bipolar Disorder cohort, a naturalistic sample of 4421 patients. First, a supervised learning framework was applied in binary classification experiments using neurodevelopmental history to predict early AAO, defined either with Gaussian mixture models (GMM) clustering or with each of the different cut-offs in the range 14 to 25 years. Second, an unsupervised learning approach was used to find clusters based on neurodevelopmental factors and to examine the overlap between such data-driven groups and definitions of early AAO used for supervised learning.

A young cut-off, i.e. 14 up to 16 years, induced higher separability [mean nested cross-validation test AUROC = 0.7327 (± 0.0169) for ⩽16 years]. Predictive performance deteriorated increasing the cut-off or setting early AAO with GMM. Similarly, defining early AAO below 17 years was associated with a higher degree of overlap with data-driven clusters (Normalized Mutual Information = 0.41 for ⩽17 years) relatively to other definitions.

Early AAO best captures distinctive neurodevelopmental patterns when defined as ⩽17 years. GMM-based definition of early AAO falls short of mapping to highly distinguishable neurodevelopmental pathways. These results should be used to improve patients' stratification in future studies of BD pathophysiology and biomarkers.

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.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

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.

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.

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.

Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

Despite its pivotal role in prophylaxis for bipolar-I-disorders (BD-I), variability in lithium (Li) response is poorly understood and only a third of patients show a good outcome. Converging research strands indicate that rest–activity rhythms can help characterize BD-I and might differentiate good responders (GR) and non-responders (NR).

Seventy outpatients with BD-I receiving Li prophylaxis were categorized as GR or NR according to the ratings on the retrospective assessment of response to lithium scale (Alda scale). Participants undertook 21 consecutive days of actigraphy monitoring of sleep quantity (SQ), sleep variability (SV) and circadian rhythmicity (CR).

Twenty-five individuals were categorized as GR (36%). After correcting statistical analysis to minimize false discoveries, four variables (intra-daily variability; median activity level; amplitude; and relative amplitude of activity) significantly differentiated GR from NR. The odds of being classified as a GR case were greatest for individuals showing more regular/stable CR (1.41; 95% confidence interval (CI) 1.08, 2.05; p < 0.04). Also, there was a trend for lower SV to be associated with GR (odds ratio: 0.56; 95% CI 0.31, 1.01; p < 0.06).

To our knowledge, this is the largest actigraphy study of rest–activity rhythms and Li response. Circadian markers associated with fragmentation, variability, amount and/or amplitude of day and night-time activity best-identified GR. However, associations were modest and future research must determine whether these objectively measured parameters, singly or together, represent robust treatment response biomarkers. Actigraphy may offer an adjunct to multi-platform approaches aimed at developing personalized treatments or stratification of individuals with BD-I into treatment-relevant subgroups.

Longitudinal studies of the relationship between cognition and functioning in bipolar disorder are scarce, although cognition is thought to be a key determinant of functioning. The causal structure between cognition and psychosocial functioning in bipolar disorder is unknown.

We sought to examine the direction of causality between cognitive performance and functional outcome over 2 years in a large cohort of euthymic patients with bipolar disorder.

The sample consisted of 272 adults diagnosed with bipolar disorder who were euthymic at baseline, 12 and 24 months. All participants were recruited via the FondaMental Advanced Centers of Expertise in Bipolar Disorders. We used a battery of tests, assessing six domains of cognition at baseline and 24 months. Residual depressive symptoms and psychosocial functioning were measured at baseline and 12 and 24 months. The possible causal structure between cognition and psychosocial functioning was investigated with cross-lagged panel models with residual depressive symptoms as a covariate.

The analyses support a causal model in which cognition moderately predicts and is causally primary to functional outcome 1 year later, whereas psychosocial functioning does not predict later cognitive performance. Subthreshold depressive symptoms concurrently affected functioning at each time of measure.

Our results are compatible with an upward causal effect of cognition on functional outcome in euthymic patients with bipolar disorder. Neuropsychological assessment may help specify individual prognoses. Further studies are warranted to confirm this causal link and evaluate cognitive remediation, before or simultaneously with functional remediation, as an intervention to improve functional outcome.

Cognitive deficits are a well-established feature of bipolar disorders (BD), even during periods of euthymia, but risk factors associated with cognitive deficits in euthymic BD are still poorly understood. We aimed to validate classification criteria for the identification of clinically significant cognitive impairment, based on psychometric properties, to estimate the prevalence of neuropsychological deficits in euthymic BD, and identify risk factors for cognitive deficits using a multivariate approach.

We investigated neuropsychological performance in 476 euthymic patients with BD recruited via the French network of BD expert centres. We used a battery of tests, assessing five domains of cognition. Five criteria for the identification of neuropsychological impairment were tested based on their convergent and concurrent validity. Uni- and multivariate logistic regressions between cognitive impairment and several clinical and demographic variables were performed to identify risk factors for neuropsychological impairment in BD.

One cut-off had satisfactory psychometric properties and yielded a prevalence of 12.4% for cognitive deficits in euthymic BD. Antipsychotics use were associated with the presence of a cognitive deficit.

This is the first study to validate a criterion for clinically significant cognitive impairment in BD. We report a lower prevalence of cognitive impairment than previous studies, which may have overestimated its prevalence. Patients with euthymic BD and cognitive impairment may benefit from cognitive remediation.

The relationship between residual depressive symptoms, cognition and functioning in patients with euthymic bipolar disorder is a subject of debate.

To assess whether cognition mediates the association between residual depressive symptoms and functioning in patients with bipolar disorder who were euthymic.

We included 241 adults with euthymic bipolar disorder in a multicentre cross-sectional study. We used a battery of tests to assess six cognition domains. A path analysis was then used to perform a mediation analysis of the relationship between residual depressive symptoms, cognitive components and functioning.

Only verbal and working memory were significantly associated with better functioning. Residual depressive symptoms were associated with poorer functioning. No significant relationship was found between residual depressive symptoms and any cognitive component.

Cognition and residual depressive symptoms appear to be two independent sources of variation in the functioning of people with euthymic bipolar disorder.

Bipolar disorder is a highly heritable polygenic disorder. Recent enrichment analyses suggest that there may be true risk variants for bipolar disorder in the expression quantitative trait loci (eQTL) in the brain.

We sought to assess the impact of eQTL variants on bipolar disorder risk by combining data from both bipolar disorder genome-wide association studies (GWAS) and brain eQTL.

To detect single nucleotide polymorphisms (SNPs) that influence expression levels of genes associated with bipolar disorder, we jointly analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls) and a genome-wide brain (cortical) eQTL (193 healthy controls) using a Bayesian statistical method, with independent follow-up replications. The identified risk SNP was then further tested for association with hippocampal volume (n = 5775) and cognitive performance (n = 342) among healthy individuals.

Integrative analysis revealed a significant association between a brain eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes factor = 5.48; bipolar disorder P = 5.85×10–5). Follow-up studies across multiple independent samples confirmed the association of the risk SNP (rs6088662) with gene expression and bipolar disorder susceptibility (P = 3.54×10–8). Further exploratory analysis revealed that rs6088662 is also associated with hippocampal volume and cognitive performance in healthy individuals.

Our findings suggest that 20q11.22 is likely a risk region for bipolar disorder; they also highlight the informative value of integrating functional annotation of genetic variants for gene expression in advancing our understanding of the biological basis underlying complex disorders, such as bipolar disorder.