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International audience; 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 is 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.

This narrative review summarizes and discusses the implications of the Diagnostic and Statistical Manual of Mental Disorders (DSM)-5 and the upcoming International Classification of Diseases (ICD)-11 classification systems on the prevalence of bipolar disorder and on the validity of the DSM-5 diagnosis of bipolar disorder according to the Robin and Guze criteria of diagnostic validity. Here we review and discuss current data on the prevalence of bipolar disorder diagnosed according to DSM-5 versus DSM-IV, and data on characteristics of bipolar disorder in the two diagnostic systems in relation to extended Robin and Guze criteria: 1) clinical presentation, 2) associations with para-clinical data such as brain imaging and blood-based biomarkers, 3) delimitation from other disorders, 4) associations with family history / genetics, 5) prognosis and long-term follow-up, and 6) treatment effects. The review highlights that few studies have investigated consequences for the prevalence of the diagnosis of bipolar disorder and for the validity of the diagnosis. Findings from these studies suggest a substantial decrease in the point prevalence of a diagnosis of bipolar with DSM-5 compared with DSM-IV, ranging from 30-50%, but a smaller decrease in the prevalence during lifetime, corresponding to a 6% reduction. It is concluded that it is likely that the use of DSM-5 and ICD-11 will result in diagnostic delay and delayed early intervention in bipolar disorder. Finally, we recommend areas for future research. (c) 2021 Elsevier B.V. and ECNP. All rights reserved.

BACKGROUND Cognitive impairments and negative symptoms in schizophrenia are associated with poor outcome, and may have common underlying mechanisms, such as psychomotor retardation. Vitamin D is a neuroactive component associated to both cognitive impairments and negative symptoms. The aim of the study is to evaluate the treatment effect of vitamin D supplementation compared to placebo on measures of psychomotor retardation. OBJECTIVE The primary objective is to investigate whether vitamin D supplementation is superior to placebo in improving processing speed. The secondary objectives are to investigate whether vitamin D supplementation is superior to placebo in improving negative symptoms, social and physical activity. METHODS Study design: Randomized placebo-controlled double blind trial. Study population: Men and women, aged 18-65 years, diagnosed with a schizophrenia spectrum disorder, in treatment for their disorder at the Division of Mental Health Services at Akershus University Hospital, and with baseline Vitamin D levels below 75 nmol/l. Intervention: Participants will be randomized 1:1 to either vitamin D3 (50µg capsules) or placebo daily for 12 weeks. The medical product or placebo will be given in addition to treatment as usual. Study measures: Cognitive tests for processing speed, symptom assessments for negative symptoms and blood sampling for vitamin D analyses will be performed at baseline and after 12 weeks intervention. During the 12 week intervention period the participants will use a smart phone application (MinDag) for daily self-report of occupational, social- and physical activity, and biweekly self-report of negative symptoms. Study participants will also wear an actigraph (MotionWatch 8 actigraph from CamNtech) for continuous registration of physical activity. RESULTS The study is currently recruiting. Primary outcome is change in cognitive performance on the symbol coding test from the Brief assessment of Cognition in Schizophrenia (BACS). Secondary outcomes are change in negative symptoms from the clinician rated Brief negative symptom scale (BNSS), and change in self-reported negative symptoms from the scale Self-assessment of Negative Symptoms (SNS). Secondary outcomes also include change in self-reported social activities from the MinDag app and change in actigraph registered physical activity. CONCLUSIONS The results from the study will indicate whether vitamin D supplementation could represent a beneficial treatment strategy for impaired processing speed and related symptoms in schizophrenia. CLINICALTRIAL ClinicalTrials.gov identifier NCT05211635.

International audience; 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=5,882 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 41-75%. 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, 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.

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. We aimed to characterize the sharedvs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD), a relevant transdiagnostic factor, using large genome-wide association studies (GWASs) data. We hypothesize that cross-analyzing these phenotypes would shed light on their unique and shared polygenicity, increase our knowledge regarding the genetic basis of the comorbidity between AUD and mood disorders, and boost discovery for jointly-associated loci. Summary statistics for MOOD, AC and AUD GWASs (Ns =363,705; 200,680 and 200,004; respectively) were analysed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD, respectively. To do so, we used a newly-established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify the cross-phenotype polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly-associated genomic loci. These loci were functionally characterized and mapped to genes and biological functions. We also performed validation in independent samples and phenotypic analyses. MOOD was highly polygenic (10,400 single nucleotide polymorphisms, SNPs) compared to AC and AUD (4,900 SNPs, SD =600 and 4,300 SNPs, SD =2,000; respectively). The polygenic overlap of MOOD and AC was much larger than that of MOOD and AUD (98%vs. 49%) and genetic correlation was opposite (−0.2vs. 0.23), which was confirmed in independent samples. MOOD&AUD causal SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 loci identified in the joint analysis, sixteen were novel for MOOD, AC and AUD. Similarly distinct patterns were evidenced for SNP localization, function and previous GWAS associations outside of the phenotypes that were currently studied. 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 shared biological underpinnings but clearly distinct functional patterns between MOOD&AC and MOOD&AUD. Using the MOOD endophenotype, the current study suggests new mechanisms for the comorbidity of AUD with mood disorders.

Background The concept of misperception of sleep refers to the estimated discrepancy between subjective and objective measures of sleep. This has been assessed only in a few prior studies in individuals with Bipolar Disorder (BD) as compared to Healthy Controls (HC) and with mixed results. Methods We assessed a sample of 133 euthymic individuals with BD and 63 HC for retrospective subjective (Pittsburgh Sleep Quality Index) and objective (21 days of actigraphy recording) measures of total sleep time, sleep latency and sleep efficiency. We first investigated the correlations between these subjective and objective measures in the two groups. We then compared individuals with BD and HC for the absolute values of the differences between subjective and objective sleep parameters, used as a proxy of the magnitude of misperception of sleep. Finally, we undertook regression analyses to assess associations between clinical groups, core demographics, clinical factors and misperception of sleep. Results The correlation coefficients between subjective and objective measures of sleep did not differ between groups (total sleep time: rho = .539 in BD and rho = .584 in HC; sleep latency: rho = .190 in BD and rho = .125 in HC; sleep efficiency: rho = .166 in BD and rho = .222 in HC). Individuals with BD did not differ from HC in the magnitude of misperception of total sleep time, sleep latency nor sleep efficiency. Individuals with BD type 1 misperceived their sleep efficiency significantly more than individuals with BD type 2, with no further difference between BD type 1 and BD type 2 regarding sleep latency and sleep duration misperceptions. Three factors (age, symptoms of obstructive sleep apnea, and mild depressive symptoms), were the main contributors to the magnitude of misperception of sleep. Conclusions Misperception of sleep was not associated with a diagnosis of BD. In this sample, mild depressive symptoms, older age, or symptoms of obstructive sleep apnea may be related to greater sleep misperception. In that case, the reliability of subjective measures may decrease as the misperception of sleep increases. This study may help guide clinicians in selecting the best approach for assessing sleep (objective versus subjective measures) in individuals with BD.

Background Childhood maltreatment is a well-known risk factor for developing a more severe and complex form of bipolar disorders (BD). However, knowledge is scarce about the interactions between childhood maltreatment and underlying genetic vulnerability on the clinical expression of BD. Method We assigned a BD-polygenic risk score (BD-PRS), calculated from the Psychiatric Genomics Consortium, to each individual in a sample of 402 cases with BD. The lifetime clinical expression of BD was characterized using structured interviews and patients completed the Childhood Trauma Questionnaire (CTQ) to assess the severity of childhood maltreatment. Results Cases who reported more severe childhood maltreatment had a lower BD-PRS (rho = -0.12, P = .01), especially when considering emotional abuse (rho = -0.16, P = .001). An interaction between BD-PRS and childhood maltreatment was observed for the risk of rapid cycling (P = .01). No further interactions between BD-PRS and childhood maltreatment were observed for other clinical characteristics (age at onset, suicide attempts, number of mood episodes, mixed features, substance use disorders and psychotic symptoms). Conclusion Our study is the first to show that less genetic risk may be needed to develop a more unstable form of BD when exposed to childhood maltreatment. Our study supports childhood trauma as an independent risk factor for BD.

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

Bipolar disorder (BD) might be associated with higher infection rates of coronavirus disease (COVID-19) which in turn could result in worsening the clinical course and outcome. This may be due to a high prevalence of somatic comorbidities and an increased risk of delays in and poorer treatment of somatic disease in patients with severe mental illness in general. Vaccination is the most important public health intervention to tackle the ongoing pandemic. We undertook a systematic review regarding the data on vaccinations in individuals with BD. Proportion of prevalence rates, efficacy and specific side effects of vaccinations and in individuals with BD were searched. Results show that only five studies have investigated vaccinations in individuals with BD, which substantially limits the interpretation of overall findings. Studies on antibody production after vaccinations in BD are very limited and results are inconsistent. Also, the evidence-based science on side effects of vaccinations in individuals with BD so far is poor. (c) 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license ( http://creativecommons.org/licenses/by/4.0/ )

A potential relationship between dysregulation of immune/inflammatory pathways and cognitive impairment has been suggested in severe mental illnesses (SMI), such as schizophrenia (SZ) and bipolar (BD) spectrum disorders. However, multivariate relationships between peripheral inflammatory/immune-related markers and cognitive domains are unclear, and many studies do not account for inter-individual variance in both cognitive functioning and inflammatory/immune status. This study aimed to investigate covariance patterns between inflammatory/immune-related markers and cognitive domains and further elucidate heterogeneity in a large SMI and healthy control (HC) cohort (SZ = 343, BD = 289, HC = 770). We applied canonical correlation analysis (CCA) to identify modes of maximum covariation between a comprehensive selection of cognitive domains and inflammatory/immune markers. We found that poor verbal learning and psychomotor processing speed was associated with higher levels of interleukin-18 system cytokines and beta defensin 2, reflecting enhanced activation of innate immunity, a pattern augmented in SMI compared to HC. Applying hierarchical clustering on covariance patterns identified by the CCA revealed a high cognition—low immune dysregulation subgroup with predominantly HC (24% SZ, 45% BD, 74% HC) and a low cognition—high immune dysregulation subgroup predominantly consisting of SMI patients (76% SZ, 55% BD, 26% HC). These subgroups differed in IQ, years of education, age, CRP, BMI (all groups), level of functioning, symptoms and defined daily dose (DDD) of antipsychotics (SMI cohort). Our findings suggest a link between cognitive impairment and innate immune dysregulation in a subset of individuals with severe mental illness.

Background Cell adhesion molecules (CAMs) orchestrate leukocyte trafficking and could link peripheral and neuroinflammation in patients with severe mental illness (SMI), by promoting inflammatory and immune-mediated responses and mediating signals across blood-brain barrier. We hypothesized that CAMs would be dysregulated in SMI and evaluated plasma levels of different vascular and neural CAMs. Dysregulated CAMs in plasma were further evaluated in vivo in leukocytes and brain tissue and in vitro in induced pluripotent stem cells. Methods We compared plasma soluble levels of different vascular (VCAM-1, ICAM-1, P-SEL) and neural (JAM-A, NCAD) CAMs in circulating leukocytes in a large SMI sample of schizophrenia (SCZ) spectrum disorder (n = 895) and affective disorder (n = 737) and healthy control participants (n = 1070) controlling for age, sex, body mass index, C-reactive protein, and freezer storage time. We also evaluated messenger RNA expression of ICAM1 and related genes encoding ICAM-1 receptors in leukocytes using microarray (n = 842) and in available RNA sequencing data from the CommonMind Consortium (CMC) in postmortem samples from the dorsolateral prefrontal cortex (n = 474). The regulation of soluble ICAM-1 in induced pluripotent stem cell–derived neurons and astrocytes was assessed in patients with SCZ and healthy control participants (n = 8 of each). Results Our major findings were 1) increased soluble ICAM-1 in patients with SMI compared with healthy control participants; 2) increased ITGB2 messenger RNA, encoding the beta chain of the ICAM-1 receptor, in circulating leukocytes from patients with SMI and increased prefrontal cortex messenger RNA expression of ICAM1 in SCZ; and 3) enhanced soluble ICAM-1 release in induced pluripotent stem cell–derived neurons from patients with SCZ. Conclusions Our results support a systemic and cerebral dysregulation of soluble ICAM-1 expression in SMI and especially in patients with SCZ.

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD., The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder.In the largest study of hippocampal subfields in bipolar disorder to date, from 23 sites worldwide, we report widespread reductions in nine of 12 subfields.The lack of differences between lithium users and healthy controls supports a possible protective role of lithium in bipolar disorder.

Schizophrenia (SCZ) spectrum and bipolar disorder (BD) are severe mental disorders with unknown pathophysiology. Altered visual evoked potential (VEP), an electroencephalogram signal reflecting function in the primary visual cortex (V1), abnormal visual processing and visual hallucinations reported in these patients, all point towards V1 dysfunction. While the mechanisms contributing to V1 dysfunction remain unknown, structural alterations are possible candidates. Lack of insight into neural substrates of structure and functional in V1 has limited our ability to determine implications of altered V1 function. While combining VEP and magnetic resonance imaging has increased our understanding of the structure-function relationship in V1 in healthy individuals, no previous study has examined the same structure-function relationship in patients with SCZ spectrum and BD. Here, we aimed to confirm previous findings of a selective positive correlation between the amplitude of the P100 component of the VEP and V1 surface area (SA) in 307 healthy individuals and to examine whether this relationship was altered in patients with SCZ spectrum (n=30) and BD (n=45). The correlation between the P100 amplitude and the total, (r=0.16, p=0.006), right (r=0.14, p=0.013) and left V1 surface area (r=0.13, p=0.02) was significant in healthy individuals, but not in patients. The current results support previous findings of a selective relationship between P100 amplitude and V1 surface area in healthy individuals and suggests that other factors than V1 surface area or thickness explain V1 dysfunction reported in these patients.

Mood instability (MOOD) is a transdiagnostic phenomenon with a prominent neurobiological basis. Recent genome-wide association studies found significant positive genetic correlation between MOOD and 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. 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 analysed using the bivariate causal mixture model and conjunctional false discovery rate methods to estimate the proportion of shared variants influencing MOOD and each disorder, and identify jointly associated genomic loci. MOOD correlated positively with all psychiatric disorders, but with wide variation in strength (rg=0.10-0.62). Of 10.4K genomic variants influencing MOOD, 4K-9.4K were estimated to influence psychiatric disorders. MOOD was jointly associated with DEP at 163 loci, SCZ at 110, BIP at 60 and ADHD at 25, with consistent genetic effects in independent samples. Fifty-three jointly associated loci were overlapping across two or more disorders (transdiagnostic), 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 of shared loci suggest divergent effects on corresponding neurobiological mechanisms which may relate to differences in the core clinical features of each disorder.

ObjectiveLow-level sensory disruption is hypothesized as a precursor to clinical and cognitive symptoms in severe mental disorders. We compared visual discrimination performance in patients with schizophrenia spectrum disorder or bipolar disorder with healthy controls, and investigated associations with clinical symptoms and IQ.MethodsPatients with schizophrenia spectrum disorder (n=32), bipolar disorder (n=55) and healthy controls (n=152) completed a computerized visual discrimination task. Participants responded whether the latter of two consecutive grids had higher or lower spatial frequency, and discrimination thresholds were estimated using an adaptive maximum likelihood procedure. Case-control differences in threshold were assessed using linear regression, F-test and post-hoc pair-wise comparisons. Linear models were used to test for associations between visual discrimination threshold and psychotic symptoms derived from the PANSS and IQ assessed using the Matrix Reasoning and Vocabulary subtests from the Wechsler Abbreviated Scale of Intelligence (WASI).ResultsRobust regression revealed a significant main effect of diagnosis on discrimination threshold (robust F=6.76, p=.001). Post-hoc comparisons revealed that patients with a schizophrenia spectrum disorder (mean=14%, SD=0.08) had higher thresholds compared to healthy controls (mean=10.8%, SD = 0.07, β = 0.35, t=3.4, p=0.002), as did patients with bipolar disorder (12.23%, SD=0.07, β= 0.21, t=2.42, p=0.04). There was no significant difference between bipolar disorder and schizophrenia (β=-0.14, t=-1.2, p=0.45). Linear models revealed negative associations between IQ and threshold across all participants when controlling for diagnostic group (β = -0.3, t=-3.43, p=0.0007). This association was found within healthy controls (t=-3.72, p=.0003) and patients with bipolar disorder (t=-2.53, p=.015), and no significant group by IQ interaction on threshold (F=0.044, p=.97). There were no significant associations between PANSS domain scores and discrimination threshold.ConclusionPatients with schizophrenia spectrum or bipolar disorders exhibited higher visual discrimination thresholds than healthy controls, supporting early visual deficits among patients with severe mental illness. Discrimination threshold was negatively associated with IQ among healthy controls and bipolar disorder patients. These findings elucidate perception-related disease mechanisms in severe mental illness, which warrants replication in independent samples.

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 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.

BackgroundSchizophrenia (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.MethodsWe 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.ResultsWe 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.ConclusionsBased 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.

BackgroundStudying the phenotypic and genetic characteristics of age and polarity at onset (AAO, PAO) in bipolar disorder (BD) can provide new insights into disease pathology and facilitate the development of screening tools.AimsTo examine the genetic architecture of AAO and PAO and their association with BD disease characteristics.MethodsGenome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (N=12977) and PAO (N=6773) were conducted in BD patients of 34 cohorts and a replication sample (N=2237). The association of onset with disease characteristics was investigated in two of these cohorts.ResultsEarlier AAO was associated with an increased risk of psychotic symptoms, suicidality, and fewer episodes. A depressive onset correlated with lifetime suicidality and a manic onset with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in SNV-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased polygenic scores for autism spectrum disorder (β=-0.34 years, SE=0.08), major depression (β=-0.34 years, SE=0.08), schizophrenia (β=-0.39 years, SE=0.08), and educational attainment (β=-0.31 years, SE=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.ConclusionsAAO and PAO are associated with indicators of BD 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.RELEVANCE STATEMENTIn the largest study to systematically characterize age at onset (N=12977) and polarity at onset (N=6773) in bipolar disorder, we describe an association between illness onset characteristics and indicators of severity, confirming their clinical relevance. Our study shows that that early illness onset is associated with genetic liability for a broad range of psychiatric disorders. However, we also highlight systematic differences in age at onset across cohorts, continents, and phenotype definitions. This heterogeneity results in reduced heritability and affects genetic analyses, underscoring the need for the development of standardized phenotype definitions.

The association between cannabis use and negative symptoms remains unclear because of inconsistent results in existing studies. In this study we aimed to investigate the association between different aspects of cannabis use and 1) diminished expression and 2) apathy as a two-dimensional model of negative symptoms in a sample of 460 participants with first-episode psychosis. Data were collected on relevant clinical and demographic factors including diagnostics and habits of drug use at baseline, with a follow-up assessment after 12-months. We found an association between the frequency of cannabis use two years prior to baseline and the severity of diminished expression and apathy at baseline, while only the association to diminished expression held after controlling for potential clinical and demographic confounders. Frequency of cannabis use at baseline also had a significant effect on the development of diminished expression over the 12-month follow-up period. In conclusion, this study suggests that the frequency of cannabis use contributes to the severity of diminished expression at baseline, and to the progression of diminished expression after 12-months follow-up. Our findings also imply a dose-response relationship between frequency of use and severity of symptoms and add evidence to an association between cannabis use and negative symptoms.

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Patients with bipolar disorder (BIP) have a high risk of cardiovascular disease (CVD), despite considerable individual variation. The mechanisms underlying comorbid CVD in BIP remain largely unknown. We investigated polygenic overlap between BIP and CVD phenotypes, including CVD risk factors and coronary artery disease (CAD). We analyzed large genome-wide association studies of BIP (n = 51,710) and CVD phenotypes (n = 159,208–795,640), using bivariate causal mixture model (MiXeR), which estimates the total amount of shared genetic variants, and conjunctional false discovery rate (FDR), which identifies specific overlapping loci. MiXeR revealed polygenic overlap between BIP and body mass index (BMI) (82%), diastolic and systolic blood pressure (20–22%) and CAD (11%) despite insignificant genetic correlations. Using conjunctional FDR n = 69), systolic (n = 53), and diastolic (n = 53) blood pressure, of which 22 are novel BIP loci. There was a pattern of mixed effect directions of the shared loci between BIP and CVD phenotypes. Functional analyses indicated that the shared loci are linked to brain-expressed genes and involved in neurodevelopment, lipid metabolism, chromatin assembly/disassembly and intracellular processes. Altogether, the study revealed extensive polygenic overlap between BIP and comorbid CVD, implicating shared molecular genetic mechanisms. The mixed effect directions of the shared loci suggest variation in genetic susceptibility to CVD across BIP subgroups, which may underlie the heterogeneity of CVD comorbidity in BIP patients. The findings suggest more focus on targeted lifestyle interventions and personalized pharmacological treatment to reduce CVD comorbidity in BIP.

Background Cardiometabolic risk is increased in severe mental disorders (SMDs), and there appears to be a relationship between childhood trauma and cardiometabolic risk, possibly related to adverse health behavior. The current study examined the association between childhood trauma and serum lipids and adiposity in SMDs and the potential mediating role of cognitive and personality characteristics. Methods Participants with schizophrenia and bipolar spectrum disorders (N = 819) were included, cardiometabolic risk factors (serum lipids, body mass index, and waist circumference) were measured, and history of childhood trauma was assessed by the Childhood Trauma Questionnaire. Cognitive and personality characteristics were available in subsamples, with assessments of cognitive control, impulsiveness, self-esteem, and affective lability. Linear regressions and mediation analyses with Hayes’ PROCESS were performed, adjusting for age, sex, antipsychotic agent propensity of metabolic side-effect, and diagnostic group. Results Experience of three or more subtypes of childhood trauma was positively associated with waist circumference in patients with SMDs (p = 0.014). There were no other significant associations between trauma variables and lipid or adiposity measures in the total sample. Cognitive control was a significant mediator between experience of one or two subtypes of childhood trauma and waist circumference. Conclusions The results indicate childhood trauma as a predisposing factor for increased waist circumference in individuals with SMDs. Poorer cognitive control, suggestive of adverse health behavior, might be a mediating factor of the association, and the findings indicate the potential importance of increased focus on these factors in prevention and treatment regimens targeting cardiometabolic health.

Clinical and epidemiological evidence suggest that loneliness is associated with severe mental disorders (SMDs) and increases the risk of cardiovascular disease (CVD). However, the mechanisms underlying the relationship between loneliness, SMDs, and CVD risk factors remain unknown. Here we explored overlapping genetic architecture and genetic loci shared between SMDs, loneliness, and CVD risk factors. We analyzed large independent genome-wide association study data on schizophrenia (SCZ), bipolar disorder (BD), major depression (MD), loneliness and CVD risk factors using bivariate causal mixture mode (MiXeR), which estimates the total amount of shared variants, and conditional false discovery rate to evaluate overlap in specific loci. We observed substantial genetic overlap between SMDs, loneliness and CVD risk factors, beyond genetic correlation. We identified 149 loci jointly associated with loneliness and SMDs (MD n = 67, SCZ n = 54, and BD n = 28), and 55 distinct loci jointly associated with loneliness and CVD risk factors. A total of 153 novel loneliness loci were found. Most of the shared loci possessed concordant effect directions, suggesting that genetic risk for loneliness may increase the risk of both SMDs and CVD. Functional analyses of the shared loci implicated biological processes related to the brain, metabolic processes, chromatin and immune system. Altogether, the study revealed polygenic overlap between loneliness, SMDs and CVD risk factors, providing new insights into their shared genetic architecture and common genetic mechanisms.

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.

Cognitive impairments are considered core features in schizophrenia and other psychotic disorders. Cognitive impairments are, to a lesser degree, also documented in healthy first-degree relatives. Although recent studies have shown (negative) genetic correlations between schizophrenia and general cognitive ability, the association between polygenic risk for schizophrenia and individual cognitive phenotypes remains unclear. We here investigated the association between a polygenic score for schizophrenia (SCZPGS) and six well-defined cognitive domains, in addition to a composite measure of cognitive ability and a measure of premorbid intellectual ability in 731 participants with a psychotic disorder and 851 healthy controls. We also investigated the association between a PGS for general cognitive ability (COGPGS) and the same cognitive domains in the same sample. We found no significant associations between the SCZPGS and any cognitive phenotypes, in either patients with a psychotic disorder or healthy controls. For COGPGS we observed stronger associations with cognitive phenotypes in healthy controls than in participants with psychotic disorders. In healthy controls, the association between COGPGS (at the p value threshold of ≥0.01) and working memory remained significant after Bonferroni correction (β = 0.12, p = 8.6 × 10−5). Altogether, the lack of associations between SCZPGS and COGPGS with cognitive performance in participants with psychotic disorders suggests that either environmental factors or unassessed genetic factors play a role in the development of cognitive impairments in psychotic disorders. Working memory should be further studied as an important cognitive phenotype.

Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders., The genetic architecture underlying brainstem regions and how this links to common brain disorders is not well understood. Here, the authors use MRI and GWAS data from 27,034 individuals to identify genetic and morphological brainstem features that influence common brain disorders.

Bipolar disorder (BD) is a severe manic-depressive illness. Patients with BD have been shown to have gray matter (GM) deficits in prefrontal, frontal, parietal, and temporal regions; however, the relationship between structural effects and clinical profiles has proved elusive when considered on a region by region or voxel by voxel basis. In this study, we applied parallel independent component analysis (pICA) to structural neuroimaging measures and the positive and negative syndrome scale (PANSS) in 110 patients (mean age 34.9 ± 11.65) with bipolar disorder, to examine networks of brain regions that relate to symptom profiles. The pICA revealed two distinct symptom profiles and associated GM concentration alteration circuits. The first PANSS pICA profile mainly involved anxiety, depression and guilty feelings, reflecting mood symptoms. Reduced GM concentration in right temporal regions predicted worse mood symptoms in this profile. The second PANSS pICA profile generally covered blunted affect, emotional withdrawal, passive/apathetic social withdrawal, depression and active social avoidance, exhibiting a withdrawal or apathy dominating component. Lower GM concentration in bilateral parietal and frontal regions showed worse symptom severity in this profile. In summary, a pICA decomposition suggested BD patients showed distinct mood and apathy profiles differing from the original PANSS subscales, relating to distinct brain structural networks., Highlights • Structural relationships with symptoms in bipolar disorder are complex. • A parallel ICA analysis of PANSS questions and structural images finds two correlated profiles. • The first pair links mood symptoms with right temporal regions. • The second pair highlights social withdrawal and apathy symptoms linked to bilateral frontal and parietal regions.