Clinical and genetic differences between bipolar disorder type 1 and 2 in multiplex families

White and gray matter alterations in bipolar I and bipolar II disorder subtypes compared with healthy controls - exploring associations with disease course and polygenic risk

Patients with bipolar disorder (BD) show alterations in both gray matter volume (GMV) and white matter (WM) integrity compared with healthy controls (HC). However, it remains unclear whether the phenotypically distinct BD subtypes (BD-I and BD-II) also exhibit brain structural differences. This study investigated GMV and WM differences between HC, BD-I, and BD-II, along with clinical and genetic associations. N = 73 BD-I, n = 63 BD-II patients and n = 136 matched HC were included. Using voxel-based morphometry and tract-based spatial statistics, main effects of group in GMV and fractional anisotropy (FA) were analyzed. Associations between clinical and genetic features and GMV or FA were calculated using regression models. For FA but not GMV, we found significant differences between groups. BD-I patients showed lower FA compared with BD-II patients (ptfce-FWE = 0.006), primarily in the anterior corpus callosum. Compared with HC, BD-I patients exhibited lower FA in widespread clusters (ptfce-FWE < 0.001), including almost all major projection, association, and commissural fiber tracts. BD-II patients also demonstrated lower FA compared with HC, although less pronounced (ptfce-FWE = 0.049). The results remained unchanged after controlling for clinical and genetic features, for which no independent associations with FA or GMV emerged. Our findings suggest that, at a neurobiological level, BD subtypes may reflect distinct degrees of disease expression, with increasing WM microstructure disruption from BD-II to BD-I. This differential magnitude of microstructural alterations was not clearly linked to clinical and genetic variables. These findings should be considered when discussing the classification of BD subtypes within the spectrum of affective disorders.

Network dysfunction of sadness facial expression processing and morphometry in euthymic bipolar disorder

Facial emotion recognition (FER), including sadness, is altered in bipolar disorder (BD). However, the relationship between this impairment and the brain structure in BD is relatively unexplored. Furthermore, its association with clinical variables and with the subtypes of BD remains to be clarified. Twenty euthymic patients with BD type I (BD-I), 28 BD type II (BD-II), and 45 healthy controls completed a FER test and a 3D-T1-weighted magnetic resonance imaging. Gray matter volume (GMV) of the cortico-limbic regions implicated in emotional processing was estimated and their relationship with FER performance was investigated using network analysis. Patients with BD-I had worse total and sadness-related FER performance relative to the other groups. Total FER performance was significantly negatively associated with illness duration and positively associated with global functioning in patients with BD-I. Sadness-related FER performance was also significantly negatively associated with the number of previous manic episodes. Network analysis showed a reduced association of the GMV of the frontal-insular-occipital areas in patients with BD-I, with a greater edge strength between sadness-related FER performance and amygdala GMV relative to controls. Our results suggest that FER performance, particularly for facial sadness, may be distinctively impaired in patients with BD-I. The pattern of reduced interrelationship in the frontal-insular-occipital regions and a stronger positive relationship between facial sadness recognition and the amygdala GMV in BD may reflect altered cortical modulation of limbic structures that ultimately predisposes to emotional dysregulation. Future longitudinal studies investigating the effect of mood state on FER performance in BD are warranted.

A characteristic cerebellar biosignature for bipolar disorder, identified with fully automatic machine learning

Background

Transcriptomic profile differences between patients with bipolar disorder and healthy controls can be identified using machine learning and can provide information about the potential role of the cerebellum in the pathogenesis of bipolar disorder.With this aim, user-friendly, fully automated machine learning algorithms can achieve extremely high classification scores and disease-related predictive biosignature identification, in short time frames and scaled down to small datasets.

Method

A fully automated machine learning platform, based on the most suitable algorithm selection and relevant set of hyper-parameter values, was applied on a preprocessed transcriptomics dataset, in order to produce a model for biosignature selection and to classify subjects into groups of patients and controls. The parent GEO datasets were originally produced from the cerebellar and parietal lobe tissue of deceased bipolar patients and healthy controls, using Affymetrix Human Gene 1.0 ST Array.

Results

Patients and controls were classified into two separate groups, with no close-to-the-boundary cases, and this classification was based on the cerebellar transcriptomic biosignature of 25 features (genes), with Area Under Curve 0.929 and Average Precision 0.955. The biosignature includes both genes connected before to bipolar disorder, depression, psychosis or epilepsy, as well as genes not linked before with any psychiatric disease. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed participation of 4 identified features in 6 pathways which have also been associated with bipolar disorder.

Conclusion

Automated machine learning (AutoML) managed to identify accurately 25 genes that can jointly - in a multivariate-fashion - separate bipolar patients from healthy controls with high predictive power. The discovered features lead to new biological insights. Machine Learning (ML) analysis considers the features in combination (in contrast to standard differential expression analysis), removing both irrelevant as well as redundant markers, and thus, focusing to biological interpretation.

Polygenic Risk Scores for Bipolar Disorder: Progress and Perspectives

Bipolar disorder (BD) is a common and highly heritable psychiatric disorder, the study of BD genetic characteristics can help with early prevention and individualized treatment. At the same time, BD is a highly heterogeneous polygenic genetic disorder with significant genetic overlap with other psychiatric disorders. In recent years, polygenic risk scores (PRS) derived from genome-wide association studies (GWAS) data have been widely used in genetic studies of various complex diseases and can be used to explore the genetic susceptibility of diseases. This review discusses phenotypic associations and genetic correlations with other conditions of BD based on PRS, and provides ideas for genetic studies and prevention of BD.

Multiple psychiatric polygenic risk scores predict associations between childhood adversity and bipolar disorder

BACKGROUND

It remains unclear how adverse childhood experiences (ACE) and increased genetic risk for bipolar disorder (BD) interact to influence BD symptom outcomes. Here we calculated multiple psychiatric polygenic risk scores (PRS) and used the measures of ACE to understand these gene-environment interactions.

METHOD

885 BD subjects were included for analyses. BD, ADHD, MDD and SCZ PRSs were calculated using the PRS-CS-auto method. ACEs were evaluated using the Children Life Event Questionnaire (CLEQ). Participants were divided into groups based on the presence of ACE and the total number of ACEs. The associations between total ACE number, PRSs and their interactions were evaluated using multiple linear and logistic regressions. Secondary analyses were performed to evaluate the influence of ACE and PRS on sub-phenotypes of BD.

RESULTS

The number of ACEs increased with the ADHD PRS. BD participants who had ACEs showed an earlier age of BD onset and higher odds of having rapid cycling. Increased BD PRS was associated with increased odds of developing psychotic symptoms. Higher ADHD PRS was associated with increased odds of having rapid cycling. No prediction effect was observed from MDD and SCZ PRS. And, we found no significant interaction between ACE numbers and any of the PRSs in predicting any selected BD sub-phenotypes.

LIMITATIONS

The study was limited by sample size, ACE definition, and cross-sectional data collection method.

CONCLUSIONS

The findings consolidate the importance of considering multiple psychiatric PRSs in predicting symptom outcomes among BD patients.

Differential characteristics of bipolar I and II disorders: a retrospective, cross-sectional evaluation of clinical features, illness course, and response to treatment

BACKGROUND

The distinction between bipolar I and bipolar II disorder and its treatment implications have been a matter of ongoing debate. The aim of this study was to examine differences between patients with bipolar I and II disorders with particular emphasis on the early phases of the disorders.

METHODS

808 subjects diagnosed with bipolar I (N = 587) or bipolar II disorder (N = 221) according to DSM-IV criteria were recruited between April 1994 and March 2022 from tertiary-level mood disorder clinics. Sociodemographic and clinical variables concerning psychiatric and medical comorbidities, family history, illness course, suicidal behavior, and response to treatment were compared between the bipolar disorder types.

RESULTS

Bipolar II disorder patients were more frequently women, older, married or widowed. Bipolar II disorder was associated with later "bipolar" presentation, higher age at first (hypo)mania and treatment, less frequent referral after a single episode, and more episodes before lithium treatment. A higher proportion of first-degree relatives of bipolar II patients were affected by major depression and anxiety disorders. The course of bipolar II disorder was typically characterized by depressive onset, early depressive episodes, multiple depressive recurrences, and depressive predominant polarity; less often by (hypo)mania or (hypo)mania-depression cycles at onset or during the early course. The lifetime clinical course was more frequently rated as chronic fluctuating than episodic. More patients with bipolar II disorder had a history of rapid cycling and/or high number of episodes. Mood stabilizers and antipsychotics were prescribed less frequently during the early course of bipolar II disorder, while antidepressants were more common. We found no differences in global functioning, lifetime suicide attempts, family history of suicide, age at onset of mood disorders and depressive episodes, and lithium response.

CONCLUSIONS

Differences between bipolar I and II disorders are not limited to the severity of (hypo)manic syndromes but include patterns of clinical course and family history. Caution in the use of potentially mood-destabilizing agents is warranted during the early course of bipolar II disorder.

Microbiota-gut-brain axis mechanisms in the complex network of bipolar disorders: potential clinical implications and translational opportunities

Bipolar disorders (BD) represent a severe leading disabling mental condition worldwide characterized by episodic and often progressive mood fluctuations with manic and depressive stages. The biological mechanisms underlying the pathophysiology of BD remain incompletely understood, but it seems that there is a complex picture of genetic and environmental factors implicated. Nowadays, gut microbiota is in the spotlight of new research related to this kind of psychiatric disorder, as it can be consistently related to several pathophysiological events observed in BD. In the context of the so-called microbiota-gut-brain (MGB) axis, it is shown to have a strong influence on host neuromodulation and endocrine functions (i.e., controlling the synthesis of neurotransmitters like serotonin or mediating the activation of the hypothalamic-pituitary-adrenal axis), as well as in modulation of host immune responses, critically regulating intestinal, systemic and brain inflammation (neuroinflammation). The present review aims to elucidate pathophysiological mechanisms derived from the MGB axis disruption and possible therapeutic approaches mainly focusing on gut microbiota in the complex network of BD. Understanding the mechanisms of gut microbiota and its bidirectional communication with the immune and other systems can shed light on the discovery of new therapies for improving the clinical management of these patients. Besides, the effect of psychiatric drugs on gut microbiota currently used in BD patients, together with new therapeutical approaches targeting this ecosystem (dietary patterns, probiotics, prebiotics, and other novelties) will also be contemplated.

Clinicodemographic correlates of psychotic features in bipolar disorder - a multicenter study in China

BACKGROUND

Psychotic symptoms are prevalent in patients with bipolar disorder (BD). However, nearly all previous studies on differences in sociodemographic and clinical factors between patients with (BD P +) and without (BD P-) psychotic symptoms were conducted in Western populations, and limited information is known in China.

METHOD

A total of 555 patients with BD from seven centers across China were recruited. A standardized procedure was used to collect patients' sociodemographic and clinical characteristics. The patients were divided into BD P + or BD P- groups based on the presence of lifetime psychotic symptoms. Mann-Whitney U test or chi-square test was used to analyze differences in sociodemographic and clinical factors between patients with BD P + and BD P-. Multiple logistic regression analysis was conducted to explore factors that were independently correlated with psychotic symptoms in BD. All the above analyses were re-conducted after the patients were divided into BD I and BD II group according to their types of diagnosis.

RESULTS

A total of 35 patients refused to participate, and the remaining 520 patients were included in the analyses. Compared with patients with BD P-, those with BD P + were more likely to be diagnosed with BD I and mania/hypomania/mixed polarity in the first mood episode. Moreover, they were more likely to be misdiagnosed as schizophrenia than major depressive disorder, were hospitalized more often, used antidepressants less frequently, and used more antipsychotics and mood stabilizers. Multivariate analyses revealed that diagnosis of BD I, more frequent misdiagnosis as schizophrenia and other mental disorders, less frequent misdiagnosis as major depressive disorder, more frequent lifetime suicidal behavior, more frequent hospitalizations, less frequent use of antidepressants, more frequent use of antipsychotics and mood stabilizers were independently correlated with psychotic symptoms in BD. After dividing the patients into BD I and BD II groups, we observed notable differences in sociodemographic and clinical factors, as well as clinicodemographic correlates of psychotic features between the two groups.

CONCLUSIONS

Differences in clinical factors between patients with BD P + and BD P- showed cross-cultural consistency, but results on the clinicodemographic correlates of psychotic features were not. Notable differences between patients with BD I and BD II were found. Future work exploring the psychotic features of BD needs to take types of diagnosis and cultural differences into consideration.

TRIAL REGISTRATION

This study was first registered on the website of the ClinicalTrials.gov ( https://clinicaltrials.gov/ ) on 18/01/2013. Its registration number is NCT01770704.

Thalamic nuclei volumes in schizophrenia and bipolar spectrum disorders - Associations with diagnosis and clinical characteristics

BACKGROUND

The thalamus is central to brain functions ranging from primary sensory processing to higher-order cognition. Structural deficits in thalamic association nuclei such as the pulvinar and mediodorsal nuclei have previously been reported in schizophrenia. However, the specificity with regards to clinical presentation, and whether or not bipolar disorder (BD) is associated with similar alterations is unclear.

METHODS

We investigated thalamic nuclei volumes in 334 patients with schizophrenia spectrum disorders (SSD) (median age 29 years, 59 % male), 322 patients with BD (30 years, 40 % male), and 826 healthy controls (HC) (34 years, 54 % male). Volumes of 25 thalamic nuclei were extracted from T1-weighted magnetic resonance imaging using an automated Bayesian segmentation method and compared between groups. Furthermore, we explored associations with clinical characteristics across diagnostic groups, including psychotic and mood symptoms and medication use, as well as diagnostic subtype in BD.

RESULTS

Significantly smaller volumes were found in the mediodorsal, pulvinar, and lateral and medial geniculate thalamic nuclei in SSD. Similarly, smaller volumes were found in BD in the same four regions, but mediodorsal nucleus volume alterations were limited to its lateral part and pulvinar alterations to its anterior region. Smaller volumes in BD compared to HC were seen only in BD type I, not BD type II. Across diagnoses, having more negative symptoms was associated with smaller pulvinar volumes.

CONCLUSIONS

Structural alterations were found in both SSD and BD, mainly in the thalamic association nuclei. Structural deficits in the pulvinar may be of relevance for negative symptoms.

Bipolar I and bipolar II subtypes in older age: Results from the Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) project

OBJECTIVES

The distinction between bipolar I disorder (BD-I) and bipolar II disorder (BD-II) has been a topic of long-lasting debate. This study examined differences between BD-I and BD-II in a large, global sample of OABD, focusing on general functioning, cognition and somatic burden as these domains are often affected in OABD.

METHODS

Cross-sectional analyses were conducted with data from the Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) database. The sample included 963 participants aged ≥50 years (714 BD-I, 249 BD-II). Sociodemographic and clinical factors were compared between BD subtypes including adjustment for study cohort. Multivariable analyses were conducted with generalized linear mixed models (GLMMs) and estimated associations between BD subtype and (1) general functioning (GAF), (2) cognitive performance (g-score) and (3) somatic burden, with study cohort as random intercept.

RESULTS

After adjustment for study cohort, BD-II patients more often had a late onset ≥50 years (p = 0.008) and more current severe depression (p = 0.041). BD-I patients were more likely to have a history of psychiatric hospitalization (p < 0.001) and current use of anti-psychotics (p = 0.003). Multivariable analyses showed that BD subtype was not related to GAF, cognitive g-score or somatic burden.

CONCLUSION

BD-I and BD-II patients did not differ in terms of general functioning, cognitive impairment or somatic burden. Some clinical differences were observed between the groups, which could be the consequence of diagnostic definitions. The distinction between BD-I and BD-II is not the best way to subtype OABD patients. Future research should investigate other disease specifiers in this population.

Genetic contributions to transdiagnostic symptom dimensions in patients with major depressive disorder, bipolar disorder, and schizophrenia spectrum disorders

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorders (SZ) exhibit considerable phenotypic and genetic overlap. However, the contribution of genetic factors to their shared psychopathological symptom dimensions remains unclear. The present exploratory study investigated genetic contributions to the symptom dimensions "Depression", "Negative syndrome", "Positive formal thought disorder", "Paranoid-hallucinatory syndrome", and "Increased appetite" in a transdiagnostic subset of the German FOR2107 cohort (n = 1042 patients with MDD, BD, or SZ). As replication cohort, a subset of the German/Austrian PsyCourse study (n = 816 patients with MDD, BD, or SZ) was employed. First, the relationship between symptom dimensions and common variants associated with MDD, BD, and SZ was investigated via polygenic risk score (PRS) association analyses, with disorder-specific PRS as predictors and symptom dimensions as outcomes. In the FOR2107 study sample, PRS for BD and SZ were positively associated with "Positive formal thought disorder", the PRS for SZ was positively associated with "Paranoid-hallucinatory syndrome", and the PRS for BD was negatively associated with "Depression". The effects of PRS for SZ were replicated in PsyCourse. No significant associations were observed for the MDD PRS. Second, genome-wide association studies (GWAS) were performed for the five symptom dimensions. No genome-wide significant associations and no replicable suggestive associations (p < 1e-6 in the GWAS) were identified. In summary, our results suggest that, similar to diagnostic categories, transdiagnostic psychiatric symptom dimensions are attributable to polygenic contributions with small effect sizes. Further studies in larger thoroughly phenotyped psychiatric cohorts are required to elucidate the genetic factors that shape psychopathological symptom dimensions.

Bipolar disorder in the International Classification of Diseases-Eleventh version: A review of the changes, their basis, and usefulness

The World Health Organization’s 11^th revision of the International Classification of Diseases (ICD-11) including the chapter on mental disorders has come into effect this year. This review focuses on the “Bipolar or Related Disorders” section of the ICD-11 draft. It describes the benchmarks for the new version, particularly the foremost principle of clinical utility. The alterations made to the diagnosis of bipolar disorder (BD) are evaluated on their scientific basis and clinical utility. The change in the diagnostic requirements for manic and hypomanic episodes has been much debated. Whether the current criteria have achieved an optimum balance between sensitivity and specificity is still not clear. The ICD-11 definition of depressive episodes is substantially different, but the lack of empirical support for the changes has meant that the reliability and utility of bipolar depression are relatively low. Unlike the Diagnostic and Statistical Manual of Mental Disorders, 5^th edition (DSM-5), the ICD-11 has retained the category of mixed episodes. Although the concept of mixed episodes in the ICD-11 is not perfect, it appears to be more inclusive than the DSM-5 approach. Additionally, there are some uncertainties about the guidelines for the subtypes of BD and cyclothymic disorder. The initial results on the reliability and clinical utility of BD are promising, but the newly created diagnostic categories also appear to have some limitations. Although further improvement and research are needed, the focus should now be on facing the challenges of implementation, dissemination, and education and training in the use of these guidelines.

Social and environmental variables as predictors of mania: a review of longitudinal research findings

Considerable evidence suggests that psychosocial variables can shape the course of bipolar disorder. Here, though, we focus on the more specific idea that the social environment can predict the course of mania. We systematically review evidence from longitudinal studies concerning how social support, family interactions, traumatic life events, and recent life events relate to the age of onset, the frequency of episode recurrence, and the severity of manic symptoms. Although we find some evidence that the course of mania can be worsened by social environmental factors, the links are specific. Among social variables, some studies indicate that conflict and hostility are predictive, but more general social relationship qualities have not been found to predict mania. Some research indicates that childhood trauma, and recent life events involving goal attainment or sleep disruption can predict mania. Taken together, the profile of variables involving recent exposure that are most predictive include those that are activating, reward-related, or sleep-disrupting, which fits with general psychological hypotheses of behavioral activation and sleep disruption as important for mania. We discuss gaps in the literature, and we note future directions for research, including the need for more integrative, longitudinal research on a fuller range of social and biological risk variables.

Differences between bipolar disorder types 1 and 2 support the DSM two-syndrome concept

Objective

To compare characteristics of bipolar disorder patients diagnosed as DSM-5 types I (BD-1) vs. II (BD-2).

Methods

We compared descriptive, psychopathological, and treatment characteristics in a sample of 1377 consenting, closely and repeatedly evaluated adult BD patient-subjects from a specialty clinic, using bivariate methods and logistic multivariable modeling.

Results

Factors found more among BD-2 > BD-1 cases included: [a] descriptors (more familial affective disorder, older at onset, diagnosis and first-treatment, more education, employment and higher socioeconomic status, more marriage and children, and less obesity); [b] morbidity (more general medical diagnoses, less drug abuse and smoking, more initial depression and less [hypo]mania or psychosis, longer episodes, higher intake depression and anxiety ratings, less mood-switching with antidepressants, less seasonal mood-change, greater %-time depressed and less [hypo]manic, fewer hospitalizations, more depression-predominant polarity, DMI > MDI course-pattern, and less violent suicidal behavior); [c] specific item-scores with initial HDRS₂₁ (higher scores for depression, guilt, suicidality, insomnia, anxiety, agitation, gastrointestinal symptoms, hypochondriasis and weight-loss, with less psychomotor retardation, depersonalization, or paranoia); and [d] treatment (less use of lithium or antipsychotics, more antidepressant and benzodiazepine treatment).

Conclusions

BD-2 was characterized by more prominent and longer depressions with some hypomania and mixed-features but not mania and rarely psychosis. BD-2 subjects had higher socioeconomic and functional status but also high levels of long-term morbidity and suicidal risk. Accordingly, BD-2 is dissimilar to, but not necessarily less severe than BD-1, consistent with being distinct syndromes.

Characterizing the polygenic overlaps of bipolar disorder subtypes with schizophrenia and major depressive disorder

BACKGROUND

Large-scale studies have shown that bipolar I disorder (BD-I) and bipolar II disorder (BD-II) have differences in genetic association with schizophrenia (SCZ) and major depressive disorder (MDD). However, the underlying shared genetic architectures between BD subtypes and both SCZ and MDD remain largely unknown.

METHODS

We applied univariate and bivariate causal mixture models (MiXeR) to estimate the polygenicity and polygenic overlaps on large GWASs summary statistics of BD-I (n = 25,060), BD-II (n = 6781), SCZ (n = 69,369) and MDD (n = 170,756). Then, conjunctional false discovery rate approach was used to identify specific shared genetic loci between BD subtypes and both SCZ and MDD.

RESULTS

Univariate MiXeR revealed that BD-II was substantially more polygenic (22.37 K causal variants) as compared to BD-I, SCZ and MDD (7.87-12.43 K causal variants). Bivariate MiXeR revealed substantial polygenic overlaps between BD-I and SCZ (Dice-coefficient = 0.83) and between BD-I and MDD (Dice-coefficient = 0.76), which are beyond the genetic correlation (rg = 0.71 and 0.36). Conjunctional FDR analysis identified 236 distinct shared loci between BD-I and BD-II (2 loci), BD-I and SCZ (227 loci), BD-I and MDD (19 loci), BD-II and SCZ (1 locus), and BD-II and MDD (3 loci). Most of these shared loci have concordant effect directions among BD subtypes, SCZ and MDD.

LIMITATIONS

The bivariate MiXeR model was not applied for the BD-II because of insufficient power and inadequate model fit.

CONCLUSIONS

These findings provide evidence for extensive polygenic effects across BD subtypes, SCZ and MDD, which further our understanding of the potential genetic basis for the comorbid symptoms across these disorders.

Outcomes of Hospitalized Acute Alcoholic Hepatitis (AH) in Patients With Bipolar 1 Disorder (B1D)

Introduction: Alcoholic hepatitis (AH) is a common cause of hospital admissions and is associated with a high mortality rate. AH occurs frequently in patients with heavy alcohol use. Alcohol use disorder (AUD) commonly presents with comorbid psychiatric disorders such as bipolar disorder. Bipolar disorder patients are also known to be at an increased risk for chronic liver diseases. Bipolar 1 disorder (B1D) is often considered the most severe presentation among different types of bipolar disorder. This study assesses the clinical outcomes of patients admitted for AH with concomitant B1D.

Methods: Adult patients with AH were identified within the 2014 National Inpatient Sample (NIS) database. International Classification of Diseases, Ninth Edition Revision, Clinical Modification (ICD-9 CM) codes were used to select for all of the diagnoses for this study. AH patients were subdivided into those with and without B1D. The outcomes of interest were sepsis, hepatic encephalopathy, acute respiratory failure, acute kidney injury, ischemic stroke, hepatic failure, coagulopathy, and inpatient mortality. A multivariate logistic regression analysis was performed to explore whether B1D is an independent predictor for the outcomes.

Results: Among 4,453 patients with AH identified, 166 patients also had B1D. AH patients with comorbid B1D were seen to be younger (42.9 years old vs. 46.2 years old, p < 0.05) and more commonly female (55.4% vs. 36.5%, p < 0.05). The B1D subgroup of AH patients were found to less likely develop acute hepatic failure (adjusted odds ratio (aOR) 0.13, 95% confidence interval (CI): 0.02-0.97, p < 0.05). The adjusted odds ratios for the remaining outcomes were not statistically significant.

Conclusions: Our study indicates that B1D may be an independent protective factor against acute hepatic failure in patients hospitalized with AH. This finding can be explained by frequent laboratory monitoring and psychiatric assessments performed by psychiatrists treating B1D patients, as well as the impact B1D has on cortisol release induced by hyperactivity of the hypothalamic-pituitary-adrenal (HPA) axis.

Prevalence of type 2 diabetes mellitus, impaired fasting glucose, general obesity, and abdominal obesity in patients with bipolar disorder: A systematic review and meta-analysis

OBJECTIVES

The study herein aimed to assess the prevalence of type 2 diabetes mellitus (T2DM), impaired fasting glucose (IFG), as well as general and abdominal obesity in patients with bipolar disorder (BD). We also compared the prevalence of T2DM and general obesity in patients with BD with age- and gender-matched healthy controls.

METHODS

A systematic search of Embase, Medline, PubMed, and APA PsycArticles was conducted from inception to June 2021 without language restrictions. Methodological quality was assessed using the Newcastle-Ottawa Scale (NOS) modified for case-control studies.

RESULTS

A total of forty-nine studies were included in this analysis. The pooled prevalence of T2DM was 9.6% (95% CI, 7.3-12.2%). Patients with BD had a nearly 1.6 times greater risk of developing T2DM compared to their age- and gender-matched controls (RR=1.57, 95% CI 1.36-1.81, p<0.001). In the present analysis, IFG is defined as a fasting plasma glucose (FPG) ≥ 100 mg/dL (FPG≥100) with a prevalence of 22.4% (95% CI, 16.7-28.7%), or as an FPG equal to or greater than 110 mg/d (FPG≥110) with a prevalence of 14.8% (95% CI, 10.8-19.3%). The prevalence of general obesity (BMI≥30 kg/m²) was 29.0% (95% CI, 22.8-35.6%); the risk of obesity was almost twice the rate reported in patients with BD compared to controls (RR=1.67, 95% CI 1.32-2.12, p<0.001). We also observed that more than half of the BD participants had abdominal obesity (i.e., prevalence of 51.1%; 95% CI, 45.0-57.3%).

LIMITATIONS

A significant degree of heterogeneity was detected. Sources of heterogeneity included differences in study designs, inclusion criteria, measurement tools, and data analysis methods.

CONCLUSION

Bipolar disorder is associated with a higher prevalence of T2DM, IFG, general obesity, and abdominal obesity. Type 2 diabetes mellitus and obesity are significantly more prevalent in patients with BD than in their age- and gender-matched controls.

STUDY REGISTRATION

CRD42021258431.

Genomic and neuroimaging approaches to bipolar disorder

BACKGROUND

To date, besides genome-wide association studies, a variety of other genetic analyses (e.g. polygenic risk scores, whole-exome sequencing and whole-genome sequencing) have been conducted, and a large amount of data has been gathered for investigating the involvement of common, rare and very rare types of DNA sequence variants in bipolar disorder. Also, non-invasive neuroimaging methods can be used to quantify changes in brain structure and function in patients with bipolar disorder.

AIMS

To provide a comprehensive assessment of genetic findings associated with bipolar disorder, based on the evaluation of different genomic approaches and neuroimaging studies.

METHOD

We conducted a PubMed search of all relevant literatures from the beginning to the present, by querying related search strings.

RESULTS

ANK3, CACNA1C, SYNE1, ODZ4 and TRANK1 are five genes that have been replicated as key gene candidates in bipolar disorder pathophysiology, through the investigated studies. The percentage of phenotypic variance explained by the identified variants is small (approximately 4.7%). Bipolar disorder polygenic risk scores are associated with other psychiatric phenotypes. The ENIGMA-BD studies show a replicable pattern of lower cortical thickness, altered white matter integrity and smaller subcortical volumes in bipolar disorder.

CONCLUSIONS

The low amount of explained phenotypic variance highlights the need for further large-scale investigations, especially among non-European populations, to achieve a more complete understanding of the genetic architecture of bipolar disorder and the missing heritability. Combining neuroimaging data with genetic data in large-scale studies might help researchers acquire a better knowledge of the engaged brain regions in bipolar disorder.

Genetic risk for psychiatric illness is associated with the number of hospitalizations of bipolar disorder patients

OBJECTIVES

Bipolar disorder (BD) has a highly heterogeneous clinical course that is characterized by relapses and increased health care utilization in a significant fraction of patients. A thorough understanding of factors influencing illness course is essential for predicting disorder severity and developing targeted therapies.

METHODS

We performed polygenic score analyses in four cohorts (N = 954) to test whether the genetic risk for BD, schizophrenia, or major depression is associated with a severe course of BD. We analyzed BD patients with a minimum illness duration of five years. The severity of the disease course was assessed by using the number of hospitalizations in a mental health facility and a composite measure of longitudinal illness severity (OPCRIT item 90).

RESULTS

Our analyses showed that higher polygenic scores for BD (β = 0.11, SE = 0.03, p = 1.17 × 10-3) and schizophrenia (β = 0.09, SE = 0.03, p = 4.24 × 10-3), but not for major depression, were associated with more hospitalizations. None of the investigated polygenic scores was associated with the composite measure of longitudinal illness severity (OPCRIT item 90).

LIMITATIONS

We could not account for non-genetic influences on disease course. Our clinical sample contained more severe cases.

CONCLUSIONS

This study demonstrates that the genetic risk burden for psychiatric illness is associated with increased health care utilization, a proxy for disease severity, in BD patients. The findings are in line with previous observations made for patients diagnosed with schizophrenia or major depression. Therefore, in the future psychiatric disorder polygenic scores might become helpful for stratifying patients with high risk of a chronic manifestation and predicting disease course.

Impulsivity as a Risk Factor for Suicide in Bipolar Disorder

The accurate assessment of suicide risk in psychiatric, especially affective disorder diagnosed patients, remains a crucial clinical need. In this study, we applied temperament and character inventory (TCI), Barratt impulsiveness scale 11 (BIS-11), PEBL simple reaction time (SRT) test, continuous performance task (CPT), and Iowa gambling task (IGT) to seek for variables linked with attempted suicide in bipolar affective disorder group (n = 60; attempters n = 17). The main findings were: strong correlations between self-report tool scores and objective parameters in CPT; the difference between attempters and non-attempters was found in the number of correctly responded trials in IGT; only one parameter differed between attempters and non-attempters in BPI diagnosis; and no significant differences between suicide attempters and non-attempters in TCI, BIS-11, and SRT were found. These justify the conclusion that impulsivity itself is not a strong predictor, and used as a single variable might not be sufficient to indicate the high suicide risk group among bipolar patients.