BackgroundIndividuals with bipolar disorder (BD) often experience unstable mood beyond mood episodes, which appears to be more prominent in BD II than in BD I. It is unclear whether the mood instability and associated sleep- and substance use patterns are different between BD subtypes and also present in the first treatment phase of the disorder. In this study, we compared the degree of instability of mood, sleep characteristics, and use of nicotine and alcohol across BD I and II.MethodsWe recruited 40 patients with BD in their first treatment phase (BD I n = 15, BD II n = 22 and BD Not Otherwise Specified n = 3) at Oslo University Hospital in Norway. The “MinDag” (MyDay) app was used to collect daily self-reports of mood (sadness, irritability, mood elevation and anxiety), sleep (length and quality) and weekly reports of alcohol and nicotine use for up to six months (mean no. of weeks = 18.5, a total of up to 740 weeks). To compare the degree of instability in the time-series across the two BD subtypes we used Root Mean Squared Successive Differences (rMSSD), representing the time domain, and power spectral density (PSD), representing the frequency domain. Cumulative difference periodogram (CDP) was used for group comparison.ResultsSignificant differences were found between BD I and BD II in the mean levels of irritability and mean hours of sleep throughout the follow-up period. The trends for higher instability in anxiety (.029) and irritability (.058) in BD II compared to BD I did not survive Bonferroni correction. Similarly, the variability of sleep length and quality and the use of nicotine and alcohol was comparable across the two groups.ConclusionApplying longitudinal app-based self-monitoring and time-series analyses, our study did not replicate previous findings of more mood instability in BD II versus BD I. The pattern of similar instability across the groups also applied to sleep characteristics and nicotine and alcohol use. Larger samples are needed to investigate how BD subtypes can explain the instability of mood and other illness-related features, which could support the development of more personalized treatment.

Alcohol use disorder (AUD) is highly heritable and burdensome worldwide. Genome-wide association studies can provide new evidence regarding the etiology of AUD. We report a multi-ancestry genome-wide association study focusing on a narrow AUD phenotype, using novel statistical tools in a total sample of 1,041,450 individuals (102,079 cases; European, 75,583; African, 20,689 (mostly African American); Hispanic American, 3,449; East Asian, 2,254; South Asian, 104; descent). Cross-ancestry functional analyses were performed with European and African samples. Thirty-seven genome-wide significant loci (105 variants) were identified, of which seven were novel for AUD and six for other alcohol phenotypes. Loci were mapped to genes, which show altered expression in brain regions relevant for AUD (striatum, hypothalamus and prefrontal cortex) and encode potential drug targets (GABAergic, dopaminergic and serotonergic neurons). African-specific analysis yielded a unique pattern of immune-related gene sets. Polygenic overlap and positive genetic correlations showed extensive shared genetic architecture between AUD and both mental and general medical phenotypes, suggesting that they are not only complications of alcohol use but also share genetic liability with AUD. Leveraging a cross-ancestry approach allowed identification of novel genetic loci for AUD and underscores the value of multi-ancestry genetic studies. These findings advance our understanding of AUD risk and clinically relevant comorbidities. This multi-ancestral meta-analysis of alcohol use disorder in over one million individuals identifies genome-wide significant risk variants from independent genomic loci and shared genetic architecture between alcohol use disorder and other mental and general medical conditions.

BACKGROUND:The prevalence of substance use disorders in bipolar disorder (BD) is high. Exploring potential interactions between mood and the use of common substances such as alcohol and nicotine may contribute to a better understanding of the mechanisms underlying such comorbidities. Digital tools now allow for continuous monitoring and data collection of both symptoms and behavior. This enables time-series analyses to explore such associations with greater precision. METHODS:Thirty-two individuals in the early phases of BD registered their mood daily and their use of substances weekly in the MinDag (MyDay) app for up to 6 months. We explored temporal relationships between the use of alcohol and nicotine and the levels of depressed, elevated, irritable, and anxious mood using Vector Autoregressive Models and Granger causality tests. RESULTS:We found indications that mood influenced alcohol- and nicotine use, and vice versa. Significant temporal relationships (Granger causality) were found in 55% (11 out of 20) of the participants for alcohol and 70% (7 out of 10) for nicotine use, and with high proportions of the variance explained by the one time-series on the other. The associations were consistent with causal effects in one or both directions, but with no adjustment for confounding. CONCLUSION:Our findings indicate that mood influences alcohol- and nicotine use and vice versa in individuals with BD, although caution should be taken due to the exploratory approach. Larger samples are needed to further disentangle these relationships to provide insight for better prevention and treatment of BD and comorbid substance use disorders.

The app “MinDag” (MyDay) was developed as a tool for monitoring mood, symptoms and illness-relevant behaviour in the initial treatment of bipolar disorder. Digital self-monitoring may provide patients and clinicians with valuable data for tailoring treatment interventions. This study aims to evaluate the practical use and clinical implications of integrating MinDag in the early treatment of bipolar disorder from the perspectives of both patients and clinicians. The MinDag app includes six content modules covering mood, sleep, functioning/activities, substance use, emotional reactivity, and psychotic symptoms. Patients were asked to use the app for six months, and automated feedback based on the app registrations was delivered to the patients’ clinicians biweekly. The study involved quantitative evaluations completed by patients (n = 20), as well as interviews with patients (n = 7) and clinicians (n = 2). Overall, the patients reported that they felt that MinDag was safe, relevant and easy to use, although technical difficulties such as too many automated reminders and need for reinstallations were reported. The patients appreciated the potential for increased awareness of their mental health, but expressed a desire for direct access to their data. Clinicians found the visual reports and feedback useful for tailoring treatment, even though the alert system for high-risk variables needed refinement. The quantitative evaluations indicated a positive general reception, with suggestions for improvement in usability and accessibility. The MinDag app shows promise as a tool for enhancing the treatment of bipolar disorder by facilitating self-monitoring and providing actionable data to clinicians. However, technical issues and the need for direct patient access to data must be addressed. Development of digital tools to support the treatment of bipolar disorder and other mental health conditions is resource demanding, and there is a need to clarify criteria to establish proof of concept to guide the selection of tools for upscaling and implementation.

In this pilot study we explored the feasibility and acceptability of “The Unified Protocol for Transdiagnostic Treatment of Emotional Disorders” (UP) in a group format for individuals with early bipolar disorder (BD). Using a mixed methods design we integrated quantitative assessments and qualitative interviews to examine the practical application of UP in a clinical setting with a focus on how participants experienced the treatment. Nine participants with BD diagnoses completed the 12-session group intervention with modules focusing on emotion regulation through skills in non-judgmental awareness, cognitive flexibility, and exposure strategies. Quantitative findings indicated significant improvements in affective lability, overall functioning, and well-being. Qualitative findings highlighted participants’ appreciation for the structured format and peer support from the group, which facilitated exploration of emotional experiences and skills practice. Participants reported particular benefit from non-judgmental awareness exercises, notably the “three-point check,” and valued the group’s role in reducing isolation and promoting shared learning. The study underscores UP’s potential adaptability for individuals with BD in a group format. Possible adjustments are discussed, such as strengthening the focus on affective symptoms as well as increasing session duration and customizing exposure exercises for BD-specific challenges. Overall, the UP group format shows promise as a feasible, acceptable, and potentially effective adjunct treatment for BD, with room for targeted refinements to optimize outcomes.

Background: People with severe mental disorders (SMDs) show an increased prevalence of tobacco smoking compared to the general population. Tobacco smoking and other adult adverse health behaviors have been associated with traumatic experiences in childhood. In the present study we investigated the relationship between childhood trauma and tobacco smoking in people with SMDs, including the possible mediating role of cognitive- and personality characteristics, i.e. cognitive control, impulsiveness, affective lability and self-esteem. Methods: Enrolled in the study were 871 participants with schizophrenia (SCZ, N = 484) and bipolar (BD, N = 387) spectrum disorders. We assessed tobacco smoking behavior (yes/no and amount), and history of childhood trauma with the Childhood Trauma Questionnaire. Data on cognitive control, impulsiveness, affective lability, and self-esteem were available in subsamples. We performed linear and logistic regressions, and conducted mediation analyses in PROCESS. All analyses were as standard adjusted for age, sex, and diagnostic group. Results: Experience of one or more subtypes of childhood trauma was significantly associated with smoking tobacco in SMDs (p = 0.002). There were no significant associations between childhood trauma and amount of tobacco smoking. Cognitive control and impulsiveness were significant mediators between childhood trauma and tobacco smoking. Conclusions: These findings indicate the experience of childhood trauma as a predisposing factor for tobacco smoking in SMDs. Cognitive control and impulsiveness were suggested as mediating mechanisms, indicating the importance of considering inhibition related self-regulatory aspects in efforts to improve health behavior in individuals with SMDs and childhood trauma.

BACKGROUND:The use of alcohol and nicotine can negatively impact the course of bipolar disorder (BD), but there is limited knowledge about how symptoms and sleep disturbances are related to concurrent nicotine use and non-pathological use of alcohol.METHODS:We investigated how nicotine use and non-pathological use of alcohol relates to affective symptoms and sleep disturbances in 453 participants with BD without substance use disorders. Manic symptoms were assessed with the Young Mania Rating Scale, and depressive symptoms with The Inventory of Depressive Symptomatology, Clinician-Rated (IDS-C). Sleep-related questions from IDS-C were used to create proxy variables for sleep disturbances, including Insomnia and Hypersomnia. Multinomial regression analysis was conducted to investigate the associations between nicotine use and sleep disturbances, controlling for possible confounders such as current use of illicit drugs and psychopharmacological treatment.RESULTS:Depressive and manic symptoms were not associated with the concurrent level of alcohol or nicotine use. Individuals with medium and high levels of daily nicotine use had higher risk of insomnia than those without. Non-pathological alcohol use was not associated with sleep disturbances.LIMITATIONS:Sleep disturbances were based on items from the IDS-C questionnaire.CONCLUSION:We found an elevated risk for insomnia in individuals with BD and medium or high levels of daily nicotine use. We found no association between the level of affective symptoms and the level of use of alcohol or nicotine. The direction of the relationship between nicotine use and insomnia needs clarification, as it is highly relevant for treatment planning.

Converging evidence suggests that childhood trauma is a causal factor in schizophrenia (SZ) and in bipolar disorders (BD). Here, we investigated whether retrospective reports are associated with severity of illness, independent of current symptom state in a large sample of participants with SZ or BD. We included 1260 individuals (SZ [n = 461], BD [n = 352]), and healthy controls; HC [n = 447]) recruited from the same catchment area. A history of childhood trauma was obtained with the Childhood Trauma Questionnaire (CTQ). Diagnosis and episodes were obtained with the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I). Clinical symptoms (state) were assessed with the Positive and Negative Syndrome scale (PANSS), the Calgary Depression Scale (CDSS). Trait related illness characteristics were assessed with age at illness onset, number of episodes, and lifetime suicide attempts. Patients who reported multiple types of childhood trauma experiences had significantly more severe illness course including an earlier illness onset, more mood episodes, and increased risk of at least one suicide attempt, also after adjusting for current symptom state. Retrospective assessed childhood trauma experiences are associated with illness severity in mental disorders adjusted for symptom state. Our results strengthen the role of childhood trauma in development of psychopathology.

Introduction: The illness course of bipolar disorder (BD) is highly heterogeneous with substantial variation between individuals with the same BD subtype and within individuals over time. This heterogeneity is not well-delineated and hampers the development of more targeted treatment. Furthermore, although lifestyle-related behaviors are believed to play a role in the illness course, such mechanisms are poorly understood. To address some of these knowledge gaps, we aimed to develop an app for collection of multi-dimensional longitudinal data on BD-relevant symptoms and lifestyle-related behaviors. Methods: An app named MinDag was developed at the Norwegian Center for Mental Disorders Research in Oslo, Norway. The app was designed to tap into selected areas: mood, sleep, functioning/activities (social, occupational, physical exercise, leisure), substance use, emotional reactivity, and psychotic experiences. Ethical, security and usability issues were highly prioritized throughout the development and for the final app solution. We conducted beta- and pilot testing to eliminate technical problems and enhance usability and acceptability. Results: The final version of MinDag comprises six modules; three which are presented for the user once daily (the Sleep module in the morning and the Mood and Functoning/Activities modules in the evening) and three which are presented once weekly (Substance Use, Emotional Reactivity, and Psychotic Experiences modules). In general, MinDag was well received in both in the beta-testing and the pilot study, and the participants provided valuable feedback that was taken into account in the final development. MinDag is now in use as part of the research protocol at the NORMENT center and in a specialized treatment unit for BD at Oslo University Hospital in Norway. Discussion: We believe that MinDag will generate unique longitudinal data well suited for capturing the heterogeneity of BD and clarifying important unresolved issues such as how life-style related behavior may influence BD symptoms. Also, the experiences and knowledge derived from the development of MinDag may contribute to improving the security, acceptability, and benefit of digital tools in mental health.

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. Understanding the genetic architecture of this comorbidity could be improved by focusing on intermediate traits that show positive genetic correlation with the disorders. Thus, we aimed to characterize the shared vs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD) –beyond genetic correlation, and boost discovery for jointly-associated loci. Summary statistics for MOOD (a binary measure of the tendency to report frequent mood swings), AC (number of standard drinks over a typical consumption week) and AUD GWASs (Ns > 200,000) were analyzed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD. To do so, we used a newly established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly associated genomic loci, which were mapped to genes and biological functions. MOOD was highly polygenic (10.4k single nucleotide polymorphisms, SNPs, SD = 2k) compared to AC (4.9k SNPs, SD = 0.6k) and AUD (4.3k SNPs, SD = 2k). The polygenic overlap of MOOD and AC was twice that of MOOD and AUD (98% vs. 49%), with opposite genetic correlation (−0.2 vs. 0.23), as confirmed in independent samples. MOOD&AUD associated SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 jointly associated loci, fifteen were novel for MOOD, AC and AUD. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated partly shared biological underpinnings, yet, clearly distinct functional patterns between MOOD&AC and MOOD&AUD, suggesting new mechanisms for the comorbidity of AUD with mood disorders.

BACKGROUND:Immune dysfunction has been implicated in the pathogenesis of schizophrenia and other nonaffective psychosis (SCZ), bipolar spectrum disorder (BIP) and major depressive disorder (MDD). The cytokines B cell-activating factor (BAFF) and A proliferation-inducing ligand (APRIL) belong to the tumor necrosis factor (TNF) super family and are essential in orchestrating immune responses. Abnormal levels of BAFF and APRIL have been found in autoimmune diseases with CNS affection.METHODS:We investigated if plasma levels of BAFF and APRIL differed between patients with SCZ, BIP, and MDD with psychotic symptoms (n = 2009) and healthy control subjects (HC, n = 1212), and tested for associations with psychotic symptom load, controlling for sociodemographic status, antipsychotic and other psychotropic medication, smoking, body-mass-index, and high sensitivity CRP.RESULTS:Plasma APRIL level was significantly lower across all patient groups compared to HC (P < .001; Cohen's d = 0.33), and in SCZ compared to HC (P < .001; d = 0.28) and in BIP compared to HC (P < .001; d = 0.37). Lower plasma APRIL was associated with higher psychotic symptom load with nominal significance (P = .017), but not with any other clinical characteristics. Plasma BAFF was not significantly different across patient groups vs HC, but significantly higher in BIP compared to HC (P = .040; d = 0.12) and SCZ (P = .027; d = 0.10).CONCLUSIONS:These results show aberrant levels of BAFF and APRIL and association with psychotic symptoms in patients with SCZ and BIP. This suggest that dysregulation of the TNF system, mediated by BAFF and APRIL, is involved in the pathophysiology of psychotic disorders.

ObjectiveThe 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.MethodsSeven 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.ResultsComorbid 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).ConclusionSUD 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.

Social functioning is impaired in severe mental disorders despite clinical remission, illustrating the need to identify other mechanisms that hinder psychosocial recovery. Affective lability is elevated and associated with an increased clinical burden in psychosis spectrum disorders. We aimed to investigate putative associations between affective lability and social functioning in 293 participants with severe mental disorders (schizophrenia- and bipolar spectrum), and if such an association was independent of well-established predictors of social impairments. The Affective Lability Scale (ALS-SF) was used to measure affective lability covering the dimensions of anxiety-depression, depression-elation and anger. The interpersonal domain of the Social Functioning Scale (SFS) was used to measure social functioning. Correlation analyses were conducted to investigate associations between affective lability and social functioning, followed by a hierarchical multiple regression and follow-up analyses in diagnostic subgroups. Features related to premorbid and clinical characteristics were entered as independent variables together with the ALS-SF scores. We found that higher scores on all ALS-SF subdimensions were significantly associated with lower social functioning (p < 0.005) in the total sample. For the anxiety-depression dimension of the ALS-SF, this association persisted after controlling for potential confounders such as premorbid social functioning, duration of untreated illness and current symptoms (p = 0.019). Our results indicate that elevated affective lability may have a negative impact on social functioning in severe mental disorders, which warrants further investigation. Clinically, it might be fruitful to target affective lability in severe mental disorders to improve psychosocial outcomes.

Recent genome-wide association studies of mood instability (MOOD) have found significant positive genetic correlation with major depression (DEP) and weak correlations with other psychiatric disorders. We investigated the polygenic overlap between MOOD and psychiatric disorders beyond genetic correlation to better characterize putative shared genetic determinants. GWAS summary statistics for schizophrenia (SCZ, n = 105,318), bipolar disorder (BIP, n = 413,466), DEP (n = 450,619), attention-deficit hyperactivity disorder (ADHD, n = 53,293), and MOOD (n = 363,705) were analyzed using the bivariate causal mixture model and conjunctional false discovery rate methods. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg  = 0.10-0.62). Of 10.4 K genomic variants influencing MOOD, 4 K-9.4 K influenced psychiatric disorders. Furthermore, MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25. Fifty-three jointly associated loci were overlapping across two or more disorders, seven of which had discordant effect directions on psychiatric disorders. Genes mapped to loci associated with MOOD and all four disorders were enriched in a single gene-set, "synapse organization." The extensive polygenic overlap indicates shared molecular underpinnings across MOOD and psychiatric disorders. However, distinct patterns of genetic correlation and effect directions may relate to differences in the core clinical features of each disorder.

Background Affective lability is elevated and associated with increased clinical burden in psychosis spectrum disorders. The extent to which the level, structure and dispersion of affective lability varies between the specific disorders included in the psychosis spectrum is however unclear. To have potential value as a treatment target, further characterization of affective lability in these populations is necessary. The main aim of our study was to investigate differences in the architecture of affective lability in different psychosis spectrum disorders, and if putative differences remained when we controlled for current symptom status. Methods Affective lability was measured with The Affective Lability Scale Short Form (ALS-SF) in participants with schizophrenia (SZ, n = 76), bipolar I disorder (BD-I, n = 105), bipolar II disorder (BD-II, n = 68) and a mixed psychosis-affective group (MP, n = 48). Multiple analyses of covariance were conducted to compare the ALS-SF total and subdimension scores of the diagnostic groups, correcting for current psychotic, affective and anxiety symptoms, substance use and sex. Double generalized linear models were performed to compare the dispersion of affective lability in the different groups. Results Overall group differences in affective lability remained significant after adjusting for covariates (p = .001). BD-II had higher affective lability compared to SZ and BD-I (p = .004), with no significant differences between SZ and BD-I. There were no significant differences in the contributions of ALS-SF dimensions to the total affective lability or in dispersion of affective lability between the groups. Conclusions This study provides the construct of affective lability in psychosis spectrum disorders with more granular details that may have implications for research and clinical care. It demonstrates that despite overlap in core symptom profiles, BD-I is more similar to SZ than it is to BD-II concerning affective lability and the BD groups should consequently be studied apart. Further, affective lability appears to be characterized by fluctuations between depressive- and other affective states across different psychosis spectrum disorders, indicating that affective lability may be related to internalizing problems in these disorders. Finally, although the level varies between groups, affective lability is evenly spread and not driven by extremes across psychosis spectrum disorders and should be assessed irrespective of diagnosis.

ABSTRACT Background Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental illnesses (SMI) that are part of a psychosis continuum, and dysregulated innate immune responses have been suggested to be involved in their pathophysiology. However, disease-specific immune mechanisms in SMI are not known yet. Recently, dyslipidemia has been linked to systemic inflammasome activation, and elevated atherogenic lipid ratios have been shown to correlate with circulating levels of inflammatory biomarkers in SMI. It is, however, not yet known if increased systemic cholesterol load leads to inflammasome activation in these patients. Methods We tested the hypothesis that patients with SCZ and BD display higher circulating levels compared to healthy individuals of key members of the IL-18 system using a large patient cohort (n=1632; including 737 SCZ and 895 BD), and healthy controls (CTRL; n=1070). In addition, we assessed associations with coronary artery disease risk factors in SMI, focusing on relevant inflammasome-related, neuroendocrine, and lipid markers. Results We report higher baseline levels of circulating IL-18 system components (IL-18, IL-18BPA) as well as increased expression of inflammasome-related genes ( NLRP3 and NLRC4 ) in the blood of patients relative to CTRL. We demonstrate a cholesterol dyslipidemia pattern in psychotic disorders, and report correlations between levels of blood cholesterol species and the expression of inflammasome system elements in SMI. Conclusions Based on these results, we suggest a link between systemic inflammasome activation/dysregulation and cholesterol load in SMI. Our findings further the understanding of possible underlying inflammatory and metabolic mechanisms and may expose important therapeutic targets in SMI.