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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.
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.
Migration has been reported to be associated with higher prevalence of mental disorders and suicidal behaviour.
To examine the prevalence of emotional and behavioural difficulties, suicidal ideation and suicide attempts among migrant adolescents and their non-migrant peers.
A school-based survey was completed by 11 057 European adolescents as part of the Saving and Empowering Young Lives in Europe (SEYLE) study.
A previous suicide attempt was reported by 386 (3.6%) adolescents. Compared with non-migrants, first-generation migrants had an elevated prevalence of suicide attempts (odds ratio (OR) 2.08; 95% CI 1.32–3.26; P=0.001 for European migrants and OR 1.86; 95% CI 1.06–3.27; P=0.031 for non-European migrants) and significantly higher levels of peer difficulties. Highest levels of conduct and hyperactivity problems were found among migrants of non-European origin.
Appropriate mental health services and school-based supports are required to meet the complex needs of migrant adolescents.
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
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.
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