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Disturbed sleep and activity are prominent features of bipolar disorder type I (BP-I). However, the relationship of sleep and activity characteristics to brain structure and behavior in euthymic BP-I patients and their non-BP-I relatives is unknown. Additionally, underlying genetic relationships between these traits have not been investigated.
Relationships between sleep and activity phenotypes, assessed using actigraphy, with structural neuroimaging (brain) and cognitive and temperament (behavior) phenotypes were investigated in 558 euthymic individuals from multi-generational pedigrees including at least one member with BP-I. Genetic correlations between actigraphy-brain and actigraphy-behavior associations were assessed, and bivariate linkage analysis was conducted for trait pairs with evidence of shared genetic influences.
More physical activity and longer awake time were significantly associated with increased brain volumes and cortical thickness, better performance on neurocognitive measures of long-term memory and executive function, and less extreme scores on measures of temperament (impulsivity, cyclothymia). These associations did not differ between BP-I patients and their non-BP-I relatives. For nine activity-brain or activity-behavior pairs there was evidence for shared genetic influence (genetic correlations); of these pairs, a suggestive bivariate quantitative trait locus on chromosome 7 for wake duration and verbal working memory was identified.
Our findings indicate that increased physical activity and more adequate sleep are associated with increased brain size, better cognitive function and more stable temperament in BP-I patients and their non-BP-I relatives. Additionally, we found evidence for pleiotropy of several actigraphy-behavior and actigraphy-brain phenotypes, suggesting a shared genetic basis for these traits.
Bipolar disorder (BD) is a highly heritable mood disorder with complex genetic architecture and poorly understood etiology. Previous transcriptomic BD studies have had inconsistent findings due to issues such as small sample sizes and difficulty in adequately accounting for confounders like medication use.
We performed a differential expression analysis in a well-characterized BD case-control sample (Nsubjects = 480) by RNA sequencing of whole blood. We further performed co-expression network analysis, functional enrichment, and cell type decomposition, and integrated differentially expressed genes with genetic risk.
While we observed widespread differential gene expression patterns between affected and unaffected individuals, these effects were largely linked to lithium treatment at the time of blood draw (FDR < 0.05, Ngenes = 976) rather than BD diagnosis itself (FDR < 0.05, Ngenes = 6). These lithium-associated genes were enriched for cell signaling and immune response functional annotations, among others, and were associated with neutrophil cell-type proportions, which were elevated in lithium users. Neither genes with altered expression in cases nor in lithium users were enriched for BD, schizophrenia, and depression genetic risk based on information from genome-wide association studies, nor was gene expression associated with polygenic risk scores for BD.
These findings suggest that BD is associated with minimal changes in whole blood gene expression independent of medication use but emphasize the importance of accounting for medication use and cell type heterogeneity in psychiatric transcriptomic studies. The results of this study add to mounting evidence of lithium's cell signaling and immune-related mechanisms.
In a large and comprehensively assessed sample of patients with bipolar disorder type I (BDI), we investigated the prevalence of psychotic features and their relationship with life course, demographic, clinical, and cognitive characteristics. We hypothesized that groups of psychotic symptoms (Schneiderian, mood incongruent, thought disorder, delusions, and hallucinations) have distinct relations to risk factors.
In a cross-sectional study of 1342 BDI patients, comprehensive demographical and clinical characteristics were assessed using the Structured Clinical Interview for DSM-IV (SCID-I) interview. In addition, levels of childhood maltreatment and intelligence quotient (IQ) were assessed. The relationships between these characteristics and psychotic symptoms were analyzed using multiple general linear models.
A lifetime history of psychotic symptoms was present in 73.8% of BDI patients and included delusions in 68.9% of patients and hallucinations in 42.6%. Patients with psychotic symptoms showed a significant younger age of disease onset (β = −0.09, t = −3.38, p = 0.001) and a higher number of hospitalizations for manic episodes (F11 338 = 56.53, p < 0.001). Total IQ was comparable between groups. Patients with hallucinations had significant higher levels of childhood maltreatment (β = 0.09, t = 3.04, p = 0.002).
In this large cohort of BDI patients, the vast majority of patients had experienced psychotic symptoms. Psychotic symptoms in BDI were associated with an earlier disease onset and more frequent hospitalizations particularly for manic episodes. The study emphasizes the strength of the relation between childhood maltreatment and hallucinations but did not identify distinct subgroups based on psychotic features and instead reported of a large heterogeneity of psychotic symptoms in BD.
Schizophrenia is associated with lower intelligence and poor educational performance relative to the general population. This is, to a lesser degree, also found in first-degree relatives of schizophrenia patients. It is unclear whether bipolar disorder I (BD-I) patients and their relatives have similar lower intellectual and educational performance as that observed in schizophrenia.
This cross-sectional study investigated intelligence and educational performance in two outpatient samples [494 BD-I patients, 952 schizophrenia spectrum (SCZ) patients], 2231 relatives of BD-I and SCZ patients, 1104 healthy controls and 100 control siblings. Mixed-effects and regression models were used to compare groups on intelligence and educational performance.
BD-I patients were more likely to have completed the highest level of education (odds ratio 1.88, 95% confidence interval 1.66–2.70) despite having a lower IQ compared to controls (β = −9.09, s.e. = 1.27, p < 0.001). In contrast, SCZ patients showed both a lower IQ (β = −15.31, s.e. = 0.86, p < 0.001) and lower educational levels compared to controls. Siblings of both patient groups had significantly lower IQ than control siblings, but did not differ on educational performance. IQ scores did not differ between BD-I parents and SCZ parents, but BD-I parents had completed higher educational levels.
Although BD-I patients had a lower IQ than controls, they were more likely to have completed the highest level of education. This contrasts with SCZ patients, who showed both intellectual and educational deficits compared to healthy controls. Since relatives of BD-I patients did not demonstrate superior educational performance, our data suggest that high educational performance may be a distinctive feature of bipolar disorder patients.
Cannabis use is associated with increased risk for psychotic-like experiences (PLEs) and psychotic disorders. It remains unclear whether this relationship is causal or due to confounding.
A total of 1929 young adults aged 18–30 years participated in a nationwide internet-based survey in The Netherlands and gave information on demographics, substance use and parental psychiatric illness and completed the Community Assessment of Psychic Experiences (CAPE).
Cigarette smoking and cannabis use were equally strongly associated with the frequency of PLEs in a fully adjusted model (β = 0.098 and 0.079 respectively, p < 0.05). Cannabis use was associated with distress from PLEs in a model adjusted for an elaborate set of confounders excluding smoking (β = 0.082, p < 0.05). However, when cigarette smoking was included in the model, cannabis use was not a significant predictor of distress from PLEs. Cigarette smoking remained associated with distress from PLEs in a fully adjusted model (β = 0.107, p < 0.001).
Smoking is an equally strong independent predictor of frequency of PLEs as monthly cannabis use. Our results suggest that the association between moderate cannabis use and PLEs is confounded by cigarette smoking.
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