Non-psychotic Bipolar Disorder Research Articles

A transdiagnostic prodrome for severe mental disorders: an electronic health record study.

Effective prevention of severe mental disorders (SMD), including non-psychotic unipolar mood disorders (UMD), non-psychotic bipolar mood disorders (BMD), and psychotic disorders (PSY), rely on accurate knowledge of the duration, first presentation, time course and transdiagnosticity of their prodromal stages. Here we present a retrospective, real-world, cohort study using electronic health records, adhering to RECORD guidelines. Natural language processing algorithms were used to extract monthly occurrences of 65 prodromal features (symptoms and substance use), grouped into eight prodromal clusters. The duration, first presentation, and transdiagnosticity of the prodrome were compared between SMD groups with one-way ANOVA, Cohen's f and d. The time course (mean occurrences) of prodromal clusters was compared between SMD groups with linear mixed-effects models. 26,975 individuals diagnosed with ICD-10 SMD were followed up for up to 12 years (UMD = 13,422; BMD = 2506; PSY = 11,047; median[IQR] age 39.8[23.7] years; 55% female; 52% white). The duration of the UMD prodrome (18[36] months) was shorter than BMD (26[35], d = 0.21) and PSY (24[38], d = 0.18). Most individuals presented with multiple first prodromal clusters, with the most common being non-specific ('other'; 88% UMD, 85% BMD, 78% PSY). The only first prodromal cluster that showed a medium-sized difference between the three SMD groups was positive symptoms (f = 0.30). Time course analysis showed an increase in prodromal cluster occurrences approaching SMD onset. Feature occurrence across the prodromal period showed small/negligible differences between SMD groups, suggesting that most features are transdiagnostic, except for positive symptoms (e.g. paranoia, f = 0.40). Taken together, our findings show minimal differences in the duration and first presentation of the SMD prodromes as recorded in secondary mental health care. All the prodromal clusters intensified as individuals approached SMD onset, and all the prodromal features other than positive symptoms are transdiagnostic. These results support proposals to develop transdiagnostic preventive services for affective and psychotic disorders detected in secondary mental healthcare.

Social Deprivation and Population Density Trajectories Before and After Psychotic Disorder Diagnosis

People with psychosis are more likely to be born and live in densely populated and socioeconomically deprived environments, but it is unclear whether these associations are a cause or consequence of disorder. To investigate whether trajectories of exposure to deprivation and population density before and after diagnosis are associated with psychotic disorders or nonpsychotic bipolar disorder. This nested case-control study included all individuals born in Sweden between January 1, 1982, and December 31, 2001, diagnosed for the first time with an International Statistical Classification of Diseases and Related Health Problems, Tenth Revision (ICD-10) psychotic disorder or nonpsychotic bipolar disorder between their 15th birthday and cohort exit (December 31, 2016). One sex- and birth year-matched control participant per case was selected. Data analysis was performed from July 2021 to June 2023. The main exposures were quintiles of neighborhood-level deprivation and population density each year from birth to age 14 years and from first diagnosis until cohort exit. The main outcomes were the odds of a serious mental illness outcome associated with trajectories of deprivation and population density, before and after diagnosis in cases. Group-based trajectory modeling was used to derive trajectories of each exposure in each period. Logistic regression was used to examine associations with outcomes. A total of 53 458 individuals (median [IQR] age at diagnosis in case patients, 23.2 [15.0-34.8] years; 30 746 [57.5%] female), including 26 729 case patients and 26 729 control participants, were studied. From birth to early adolescence, gradients were observed in exposure to deprivation and population density trajectories during upbringing and psychotic disorder, with those in the most vs least deprived (adjusted odds ratio [AOR], 1.17; 95% CI, 1.08-1.28) and most vs least densely populated (AOR, 1.49; 95% CI, 1.34-1.66) trajectories at greatest risk. A strong upward mobility trajectory to less deprived neighborhoods was associated with similar risk to living in the least deprived trajectory (AOR, 1.01; 95% CI, 0.91-1.12). Only 543 case patients (2.0%) drifted into more deprived areas after diagnosis; people with psychotic disorder were more likely to belong to this trajectory (AOR, 1.38; 95% CI, 1.16-1.65) or remain in the most deprived trajectory (AOR, 1.36; 95% CI, 1.24-1.48) relative to controls. Patterns were similar for nonpsychotic bipolar disorder and deprivation but weaker for population density. In this case-control study, greater exposure to deprivation during upbringing was associated with increased risk of serious mental illness, but upward mobility mitigated this association. People with serious mental illness disproportionately remained living in more deprived areas after diagnosis, highlighting issues of social immobility. Prevention and treatment should be proportionately located in deprived areas according to need.

Cannabis Use Disorder and Subsequent Risk of Psychotic and Nonpsychotic Unipolar Depression and Bipolar Disorder

Cannabis use is increasing worldwide and is suspected to be associated with increased risk of psychiatric disorders; however, the association with affective disorders has been insufficiently studied. To examine whether cannabis use disorder (CUD) is associated with an increased risk of psychotic and nonpsychotic unipolar depression and bipolar disorder and to compare associations of CUD with psychotic and nonpsychotic subtypes of these diagnoses. This prospective, population-based cohort study using Danish nationwide registers included all individuals born in Denmark before December 31, 2005, who were alive, aged at least 16 years, and living in Denmark between January 1, 1995, and December 31, 2021. Register-based diagnosis of CUD. The main outcome was register-based diagnosis of psychotic or nonpsychotic unipolar depression or bipolar disorder. Associations between CUD and subsequent affective disorders were estimated as hazard ratios (HRs) using Cox proportional hazards regression with time-varying information on CUD, adjusting for sex; alcohol use disorder; substance use disorder; having been born in Denmark; calendar year; parental educational level (highest attained); parental cannabis, alcohol, or substance use disorders; and parental affective disorders. A total of 6 651 765 individuals (50.3% female) were followed up for 119 526 786 person-years. Cannabis use disorder was associated with an increased risk of unipolar depression (HR, 1.84; 95% CI, 1.78-1.90), psychotic unipolar depression (HR, 1.97; 95% CI, 1.73-2.25), and nonpsychotic unipolar depression (HR, 1.83; 95% CI, 1.77-1.89). Cannabis use was associated with an increased risk of bipolar disorder in men (HR, 2.96; 95% CI, 2.73-3.21) and women (HR, 2.54; 95% CI, 2.31-2.80), psychotic bipolar disorder (HR, 4.05; 95% CI, 3.52-4.65), and nonpsychotic bipolar disorder in men (HR, 2.96; 95% CI, 2.73-3.21) and women (HR, 2.60; 95% CI, 2.36-2.85). Cannabis use disorder was associated with higher risk for psychotic than nonpsychotic subtypes of bipolar disorder (relative HR, 1.48; 95% CI, 1.21-1.81) but not unipolar depression (relative HR, 1.08; 95% CI, 0.92-1.27). This population-based cohort study found that CUD was associated with an increased risk of psychotic and nonpsychotic bipolar disorder and unipolar depression. These findings may inform policies regarding the legal status and control of cannabis use.

Risk for Mood, Anxiety, and Psychotic Disorders in Individuals at High and Low Genetic Liability for Bipolar Disorder and Major Depression

The nature of the genetic relationship between major depression and bipolar disorder remains unclear and might be clarified by considering disorders outside of the mood spectrum. To better understand the relationship between genetic liabilities for major depression (MD) and bipolar disorder (BD). A cohort study was conducted with data for individuals born in Sweden to Swedish parents from 1960 to 1990, with follow-up through December 31, 2018. The data included family genetic risk scores for MD and BD and International Classification of Diseases codes for a range of disorders as reported in primary care, specialist, and hospital registries. Data analysis was conducted from April 2022 to July 2022. High and low genetic liability were defined as being in the upper and lower 2 risk deciles. Risk was compared in individuals at high genetic liability to (1) MD only, (2) BD only, and (3) both MD and BD and those at (4) high genetic liability to BD and low genetic liability to MD and (5) high genetic liability to MD and low genetic liability to BD. Risk for nonpsychotic MD and BD, psychotic MD and BD, anxiety disorders, obsessive-compulsive disorder, schizoaffective disorder (SAD), schizophrenia, and other nonaffective psychosis. Data were included for 2 736 950 individuals with a mean (SD) age at follow-up of 43.9 (9.1) years. High genetic liability to only BD increased risk for nonpsychotic BD, psychotic BD, and SAD. High genetic liability to only MD augmented risk for nonpsychotic MD, anxiety disorders, and nonpsychotic BD. High genetic liability to both BD and MD had the strongest association with risk for nonpsychotic BD, anxiety disorders, and nonpsychotic MD. High genetic liability to BD and low genetic liability to MD increased risk for psychotic BD, nonpsychotic BD, and SAD with no increased risk for nonpsychotic MD or anxiety disorders. High genetic liability to MD and low genetic liability to BD increased risk for nonpsychotic MD, nonpsychotic BD, and anxiety disorders with no increased risk for psychotic BD. In this study, hypotheses that BD and MD are either genetically distinct or genetically closely interrelated were not supported. Both BD and MD were associated with a genetic vulnerability to mood disorders, but even that liability was partially selective. However, compared with individuals at high liability to MD, those at elevated genetic liability for BD had a substantially increased risk for psychosis. Compared with individuals at elevated genetic liability to BD, those at high genetic risk for MD had a considerably augmented risk for anxiety disorders. Clarifying genetic relationships between psychiatric syndromes can be substantially aided by the consideration of profiles of risk for a range of disorders.

Different patterns of white matter microstructural alterations between psychotic and non-psychotic bipolar disorder.

This study aimed to investigate alterations in white matter (WM) microstructure in patients with psychotic and non-psychotic bipolar disorder (PBD and NPBD, respectively). We used 3T-magnetic resonance imaging to examine 29 PBD, 23 NPBD, and 65 healthy control (HC) subjects. Using tract-based spatial statistics for diffusion tensor imaging data, we compared fractional anisotropy (FA) and mean diffusion (MD) pairwise among the PBD, NPBD, and HC groups. We found several WM areas of decreased FA or increased MD in the PBD and NPBD groups compared to HC. PBD showed widespread FA decreases in the corpus callosum as well as the bilateral internal capsule and fornix. However, NPBD showed local FA decreases in a part of the corpus callosum body as well as in limited regions within the left cerebral hemisphere, including the anterior and posterior corona radiata and the cingulum. In addition, both PBD and NPBD shared widespread MD increases across the posterior corona radiata, cingulum, and sagittal stratum. These findings suggest that widespread WM microstructural alterations might be a common neuroanatomical characteristic of bipolar disorder, regardless of being psychotic or non-psychotic. Particularly, PBD might involve extensive inter-and intra-hemispheric WM connectivity disruptions.

Auditory Oddball Responses Across the Schizophrenia-Bipolar Spectrum and Their Relationship to Cognitive and Clinical Features.

Neural activations during auditory oddball tasks may be endophenotypes for psychosis and bipolar disorder. The authors investigated oddball neural deviations that discriminate multiple diagnostic groups across the schizophrenia-bipolar spectrum (schizophrenia, schizoaffective disorder, psychotic bipolar disorder, and nonpsychotic bipolar disorder) and clarified their relationship to clinical and cognitive features. Auditory oddball responses to standard and target tones from 64 sensor EEG recordings were compared across patients with psychosis (total N=597; schizophrenia, N=225; schizoaffective disorder, N=201; bipolar disorder with psychosis, N=171), patients with bipolar disorder without psychosis (N=66), and healthy comparison subjects (N=415) from the second iteration of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP2) study. EEG activity was analyzed in voltage and in the time-frequency domain (low, beta, and gamma bands). Event-related potentials (ERPs) were compared with those from an independent sample collected during the first iteration of B-SNIP (B-SNIP1; healthy subjects, N=211; psychosis group, N=526) to establish the repeatability of complex oddball ERPs across multiple psychosis syndromes (r values >0.94 between B-SNIP1 and B-SNIP2). Twenty-six EEG features differentiated the groups; they were used in discriminant and correlational analyses. EEG variables from the N100, P300, and low-frequency ranges separated the groups along a diagnostic continuum from healthy to bipolar disorder with psychosis/bipolar disorder without psychosis to schizoaffective disorder/schizophrenia and were strongly related to general cognitive function (r=0.91). P50 responses to standard trials and early beta/gamma frequency responses separated the bipolar disorder without psychosis group from the bipolar disorder with psychosis group. P200, N200, and late beta/gamma frequency responses separated the two bipolar disorder groups from the other groups. Neural deviations during auditory processing are related to psychosis history and bipolar disorder. There is a powerful transdiagnostic relationship between severity of these neural deviations and general cognitive performance. These results have implications for understanding the neurobiology of clinical syndromes across the schizophrenia-bipolar spectrum that may have an impact on future biomarker research.

Distinguishing patterns of impairment on inhibitory control and general cognitive ability among bipolar with and without psychosis, schizophrenia, and schizoaffective disorder

BackgroundDeficits in inhibitory control on a Stop Signal Task (SST) were previously observed to be of similar magnitude across schizophrenia, schizoaffective, and bipolar disorder with psychosis, despite variation in general cognitive ability. Understanding different patterns of performance on the SST may elucidate different pathways to the impaired inhibitory control each group displayed. Comparing nonpsychotic bipolar disorder to the psychosis groups on SST may also expand our understanding of the shared neurobiology of this illness spectrum. MethodsWe tested schizophrenia (n = 220), schizoaffective (n = 216), bipolar disorder with (n = 192) and without psychosis (n = 67), and 280 healthy comparison participants with a SST and the Brief Assessment of Cognition in Schizophrenia (BACS), a measure of general cognitive ability. ResultsAll patient groups had a similar degree of impaired inhibitory control over prepotent responses. However, bipolar groups differed from schizophrenia and schizoaffective groups in showing speeded responses and inhibition errors that were not accounted for by general cognitive ability. Schizophrenia and schizoaffective groups had a broader set of deficits on inhibition and greater general cognitive deficit, which fully accounted for the inhibition deficits. No differences were found between the clinically well-matched bipolar with and without psychosis groups, including for inhibitory control or general cognitive ability. ConclusionsWe conclude that 1) while impaired inhibitory control on a SST is of similar magnitude across the schizo-bipolar spectrum, including nonpsychotic bipolar, different mechanisms may underlie the impairments, and 2) history of psychosis in bipolar disorder does not differentially impact inhibitory behavioral control or general cognitive abilities.

S169. THE IMPACT OF PSYCHOSIS IN ADOLESCENT-ONSET BIPOLAR DISORDER: A STRUCTURAL MRI STUDY

BackgroundBipolar Disorder (BD) is a major psychiatric illness defined by episodic mood changes, which in approximately 50% of cases is associated with psychotic features. Over the past decades, a large amount of research has identified brain structural and functional alterations in patients with this mental disorder. Some findings have been found to be specific to patients with psychotic symptoms, raising suggestions that this could represent a biological subtype of the disorder. Recent interest has been addressed to Early-Onset Bipolar Disorder (EOBD, onset prior to age 18). Latest reviews in EOBD samples have pointed to abnormalities in the frontal lobe and limbic structures, with some inconsistencies in the reported results possibly caused by differences in the methodology. In addition, no study so far has examined the neural structural correlates of psychotic symptoms in adolescent-onset bipolar disorder (AOBD).The aim of the present study is to examine the impact of psychosis on the neurobiological architecture in a sample of patients with AOBD. To our knowledge, this is the first study comparing gray matter structure between AOBD patients with or without psychotic features.MethodsWe conducted a cross-sectional study collecting T1-weighted structural magnetic resonance neuroimaging (3T-MRI) data in patients diagnosed with Bipolar Disorder type I or II between 12 and 19 years old (N=46, mean age (SD)=15.89 (1.94), gender=52.2% females). All patients were recruited from child and adolescent mental health services of the Hospital Clinic of Barcelona, Spain. Diagnoses were confirmed with a semi-structured clinical interview (Kiddie-Sads present and lifetime version) by child and adolescent psychiatrists.Images were pre-processed employing FreeSurfer 5.3.0, and data corresponding to Cortical Thickness (CTH) and Subcortical Volumes (SCV) was obtained. Groups were compared according to whether patients had experienced psychotic symptoms at any point during their illness: Non-Psychotic Bipolar Disorder (NPSBD, N=25) and Psychotic Bipolar Disorder (PSBD, N=21). No differences in age (t=0.498, p=0.621) or sex (χ2=0.001, p=0.979). Group effects in relation to both CT and SCV were examined with a general linear model. The main effect of group on CTH and SCV, was performed for the whole brain, performing a correction for multiple comparisons (Montecarlo correction, threshold = 0.05).ResultsBetween-group analyses showed smaller CTH in a cluster in the left medial orbitofrontal cortex (cluster size= 1142.58 mm2) in PSBD relative to NPSBD (x, y, z: 25.63, 89.61, -42.74; p=0.002). In addition, we observed a smaller right hippocampus volume (p=0.025) in PSBD relative to NPSBD. No other statistically significant differences were obtained.DiscussionPSBD showed smaller cortical thickness in the left medial orbitofrontal cortex, as well as a volumetric reduction in the right hippocampal volume. Similar results have been reported in a study comparing adolescent patients with psychotic BD and healthy controls. These results add evidence about the role of these two structures in the genesis of psychotic symptoms in a population diagnosed with AOBD. Interestingly, one study has reported a surface area decreased of the orbitofrontal cortex in adolescent patients with a non-bipolar psychotic disorder, which suggests that they may be a common substrate to psychotic symptoms during adolescence regardless of co-occurring affective symptoms.In summary, this study points to the existence of a distinct biological nature between bipolar patients according to psychotic symptoms, underpinned by a different neurobiological architecture. Future research should focus on replication and on examining the clinical value of this finding.

Effort-cost computation in a transdiagnostic psychiatric sample: Differences among patients with schizophrenia, bipolar disorder, and major depressive disorder.

Amotivational symptoms are observed in schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). Effort-cost computation may be a potential contributor to amotivation transdiagnostically. This study examined effort-cost computation in these three diagnostic groups. This study recruited 141 outpatients (49 SCZ, 52 non-psychotic BD, and 40 non-psychotic MDD) and 57 healthy controls (HCs). We administered the Effort-Expenditure for Reward Task (EEfRT), which manipulated different levels of reward magnitude and probability relating to a high and low physical effort task. There were significant interactions between group and reward magnitude, group and reward probability, and group and expected value on the percentage of high-effort choices. SCZ, BD, and MDD patients made comparably fewer high-effort choices than HCs in the high-reward magnitude, high-reward probability, and high-expected-value conditions. Self-reported amotivation did not correlate with decision-making on the EEfRT. Our findings suggest that reduced effort expenditure for reward is a transdiagnostic phenotype in SCZ, BD, and MDD.

Reward and punishment learning in schizophrenia and bipolar disorder

Prior studies on reward learning deficits in psychiatric disorders have used probabilistic learning tasks, making it unclear whether impairment is due to the probabilistic nature of the task rather than reward processing. In this study, we tested probabilistic vs. deterministic reward and punishment learning in healthy controls and three patient groups: schizophrenia (SZ), psychotic bipolar disorder (BD), and nonpsychotic BD. Experimental results show that reward learning was impaired in patients with SZ and patients with psychotic BD in the probabilistic learning task compared to patients with nonpsychotic BD and healthy controls. In contrast, punishment learning in the probabilistic task was impaired in patients with nonpsychotic BD compared to the other patient groups and healthy controls. There were no significant differences among all groups in the deterministic learning task scores. We also found that Hamilton Depression Scale scores negatively correlated with probabilistic learning performance. Our data may suggest that reward learning impairment may be due to the nature of the task as well as subtype of BD.

Psychotic versus non-psychotic bipolar disorder: Socio-demographic and clinical profiles in an Italian nationwide study

Psychotic versus non-psychotic patients with bipolar disorder have been traditionally associated with different unfavorable clinical features. In this study on bipolar Italian patients, we aimed to compare clinical and demographic differences between psychotic and non-psychotic individuals, exploring clinical factors that may favor early diagnosis and personalized treatment. A total of 1671 patients (males: n = 712 and females: n = 959; bipolar type 1: n = 1038 and bipolar type 2: n = 633) from different psychiatric departments were compared according to the lifetime presence of psychotic symptoms in terms of socio-demographic and clinical variables. Chi-square tests for qualitative variables and Student's t-tests for quantitative variables were performed for group comparison, and a multivariable logistic regression was performed, considering the lifetime psychotic symptoms as dependent variables and socio-demographic/clinical characteristics as independent variables. Psychotic versus non-psychotic bipolar subjects resulted to: be more frequently unemployed (p < 0.01) and never married/partnered (p < 0.01); have an earlier age at onset (p < 0.01); more frequently receive a first diagnosis different from a mood disorder (p < 0.01); have a shorter duration of untreated illness (p < 0.01); have a more frequently hypomanic/manic prevalent polarity (p < 0.01) and a prevalent manic-depressive type of cycling (p < 0.01); present a lower lifetime number of depressive episodes (p < 0.01), but have more manic episodes (p < 0.01); and less insight (p < 0.01) and more hospitalizations in the last year (p < 0.01). Multivariable regression analysis showed that psychotic versus non-psychotic bipolar patients received more frequently a first diagnosis different from bipolar disorder (odds ratio = 0.64, 95% confidence interval = [0.46, 0.90], p = 0.02) or major depressive disorder (odds ratio = 0.66, 95% confidence interval = [0.48, 0.91], p = 0.02), had more frequently a prevalent manic polarity (odds ratio = 1.84, 95% confidence interval = [1.14, 2.98], p < 0.01) and had a higher number of lifetime manic episodes (more than six) (odds ratio = 8.79, 95% confidence interval = [5.93, 13.05], p < 0.01). Lifetime psychotic symptoms in bipolar disorder are associated with unfavorable socio-demographic and clinical features as well as with a more frequent initial misdiagnosis.

Risk of schizophrenia, schizoaffective, and bipolar disorders by migrant status, region of origin, and age-at-migration: a national cohort study of 1.8 million people.

We assessed whether the risk of various psychotic disorders and non-psychotic bipolar disorder (including mania) varied by migrant status, a region of origin, or age-at-migration, hypothesizing that risk would only be elevated for psychotic disorders. We established a prospective cohort of 1 796 257 Swedish residents born between 1982 and 1996, followed from their 15th birthday, or immigration to Sweden after age 15, until diagnosis, emigration, death, or end of 2011. Cox proportional hazards models were used to model hazard ratios by migration-related factors, adjusted for covariates. All psychotic disorders were elevated among migrants and their children compared with Swedish-born individuals, including schizophrenia and schizoaffective disorder (adjusted hazard ratio [aHR]migrants: 2.20, 95% CI 1.96-2.47; aHRchildren : 2.00, 95% CI 1.79-2.25), affective psychotic disorders (aHRmigrant1.42, 95% CI 1.25-1.63; aHRchildren: 1.22 95% CI 1.07-1.40), and other non-affective psychotic disorders (aHRmigrant: 1.97, 95% CI 1.81-2.14; aHRchildren: 1.68, 95% CI 1.54-1.83). For all psychotic disorders, risks were generally highest in migrants from Africa (i.e. aHRschizophrenia: 5.24, 95% CI 4.26-6.45) and elevated at most ages-of-migration. By contrast, risk of non-psychotic bipolar disorders was lower for migrants (aHR: 0.58, 95% CI 0.52-0.64) overall, and across all ages-of-migration except infancy (aHR: 1.20; 95% CI 1.01-1.42), while risk for their children was similar to the Swedish-born population (aHR: 1.00, 95% CI 0.93-1.08). Increased risk of psychiatric disorders associated with migration and minority status may be specific to psychotic disorders, with exact risk dependent on the region of origin.

Aberrant transcriptomes and DNA methylomes define pathways that drive pathogenesis and loss of brain laterality/asymmetry in schizophrenia and bipolar disorder.

Although the loss of brain laterality is one of the most consistent modalities in schizophrenia (SCZ) and bipolar disorder (BD), its molecular basis remains elusive. Our limited previous studies indicated that epigenetic modifications are key to the asymmetric transcriptomes of brain hemispheres. We used whole-genome expression microarrays to profile postmortem brain samples from subjects with SCZ, psychotic BD [BD[+]] or non-psychotic BD [BD(-)], or matched controls (10/group) and performed whole-genome DNA methylation (DNAM) profiling of the same samples (3-4/group) to identify pathways associated with SCZ or BD[+] and genes/sites susceptible to epigenetic regulation. qRT-PCR and quantitative DNAM analysis were employed to validate findings in larger sample sets (35/group). Gene Set Enrichment Analysis (GSEA) demonstrated that BMP signaling and astrocyte and cerebral cortex development are significantly (FDR q < 0.25) coordinately upregulated in both SCZ and BD[+], and glutamate signaling and TGFβ signaling are significantly coordinately upregulated in SCZ. GSEA also indicated that collagens are downregulated in right versus left brain of controls, but not in SCZ or BD[+] patients. Ingenuity Pathway Analysis predicted that TGFB2 is an upstream regulator of these genes (p = .0012). While lateralized expression of TGFB2 in controls (p = .017) is associated with a corresponding change in DNAM (p ≤ .023), lateralized expression and DNAM of TGFB2 are absent in SCZ or BD. Loss of brain laterality in SCZ and BD corresponds to aberrant epigenetic regulation of TGFB2 and changes in TGFβ signaling, indicating potential avenues for disease prevention/treatment.

Gray matter bases of psychotic features in adult bipolar disorder: A systematic review and voxel-based meta-analysis of neuroimaging studies.

Psychotic bipolar disorder (P-BD) is a specific subset that presents greater risk of relapse and worse outcomes than nonpsychotic bipolar disorder (NP-BD). To explore the neuroanatomical bases of psychotic dimension in bipolar disorder (BD), a systematic review was carried out based on the gray matter volume (GMV) among P-BD and NP-BD patients and healthy controls (HC). Further, we conducted a meta-analysis of GMV differences between P-BD patients and HC using a whole-brain imaging approach. Our review revealed that P-BD patients exhibited smaller GMVs mainly in the prefronto-temporal and cingulate cortices, the precentral gyrus, and insula relative to HC both qualitatively and quantitatively. Qualitatively the comparison between P-BD and NP-BD patients suggested inconsistent GMV alterations mainly involving the prefrontal cortex, while NP-BD patients showed GMV deficits in local regions compared with HC. The higher proportions of female patients and patients taking psychotropic medication in P-BD and P-BD type I were associated with smaller GMV in the right precentral gyrus, and the right insula, respectively. In conclusions, psychosis in BD might be associated with specific cortical GMV deficits. Gender and psychotropic medication might have effects on the regional GMVs in P-BD patients. It is necessary to distinguish psychotic dimension in neuroimaging studies of BD.

Exploring the neuroanatomical bases of psychotic features in bipolar disorder.

Although bipolar disorder (BD) is traditionally conceptualised as one diagnostic entity, the heterogeneity of pathophysiological manifestations in BD suggests the need to classify the subtypes of the illness based on neural markers. Specifically, the presence of psychotic symptoms seems to be relevant for the clinical outcome and may have specific neuroanatomical bases. The main objective of the present review was to assess whether the distinction between psychotic BD (PBD) and non-psychotic BD (NPBD) can improve the identification of the neurobiological markers of this complex illness. To this end, we summarised the findings from the magnetic resonance imaging studies that explored the cerebral correlates of psychosis in BD in terms of grey matter volume (GMV). Overall, the results suggest the presence of peculiar GMV differences between PBD and NPBD. Specifically, psychosis in BD seems to be associated with cortical GMV deficits compared with both healthy controls and NPBD, mainly in the frontal region. Conversely, NPBD patients showed GMV deficits in selective regions of the basal ganglia when compared with the other groups. Taken together, this evidence confirms the importance to classify BD based on the psychotic dimension, which may have a specific neurobiological architecture that partially overlaps across multiple psychotic disorders.

16. Investigation of the Auditory Steady State Response in Schizophrenia, Schizoaffective, Psychotic and Nonpsychotic Bipolar Disorders

16. Investigation of the Auditory Steady State Response in Schizophrenia, Schizoaffective, Psychotic and Nonpsychotic Bipolar Disorders

SU5. Investigation of the Visual Steady-State Response in Schizophrenia, Schizoaffective, Psychotic, and Nonpsychotic Bipolar Disorders

Abstract Background: Electroencephalographic (EEG) studies of the auditory steady state response (aSSR) noninvasively probe oscillatory capacity and synchronization in the primary auditory cortex. Abnormalities in the aSSRs have been proposed as translational biomarkers for schizophrenia. However, few studies have examined the aSSRs across diagnostic categories and included the full spectrum of psychotic subgroups (Schizophrenia: SZ, Schizoaffective disorder: SAD, Bipolar disorder with psychosis: BDP, and Bipolar disorder without psychosis: BD-NP). This is a critical step to determine its utility as a potential biomarker and to provide insight into specific neural dysregulations related to psychotic etiology. In this study, auditory steady state stimuli were administered to a large sample of well-characterized participants diagnosed with SZ, SAD, BDP, or BD-NP. Methods: 501 individuals (HC = 184, SZ = 91, SAD = 97, BD-WP = 79, BD-NP = 50) completed aSSRs EEG task at the 5 BSNIP research sites. 1500ms broadband noise sequences modulated at 20, 40, or 80-Hz were presented to investigate neural responses related to distinct frequency bands. Intertrial phase coherence (ITC) was calculated for each subject and sensor resulting in time–frequency values ranging from 5 to 90-Hz and 500–2000 ms. An average aSSR was created using the average of the 7 peak sensors and the 0–1500ms period for each subject. 1-way ANOVAs were completed for each frequency of interest and follow up Welch’s t-tests were performed to compare group differences. Results: SZ and SAD had significantly reduced ITC for all three frequency conditions in comparison to HC and BD-NP. BDP was reduced in the 20 and 40-Hz conditions in comparison to HC, but not in the 80-Hz condition. BDP differed from BD-NP only in the 40-Hz condition. HC and BD-NP did not significantly differ in any of the frequency conditions. Conclusion: Three main conclusions can be drawn from this study. (1) All 3 psychotic subgroups (SZ, SAD, and BDP) had reduced ITC in comparison to HC and BD-NP at 40-Hz. This suggests that the 40-Hz aSSR indexes psychosis in general and is not a SZ specific response. (2) SZ and SAD both showed significant reductions in the 80-Hz aSSR. This suggests that these psychotic subgroups significantly differ in their high-gamma response, which could potentially be related to a difference in pathophysiology and the severity/noncyclical nature of their psychotic symptomology. (3) BD-NP did not significantly differ from HC in any of the aSSR conditions. This could explain the mixed findings in the literature of the aSSR response in bipolar disorder and suggests that future biological-based research should consider distinguishing these groups. Examining differences in the aSSR between proband groups offers unique insight into how neural synchronization relates to the etiology of major psychotic disorders and provides novel evidence about its use as a translational biomarker.

Tract-based analysis of white matter integrity in psychotic and nonpsychotic bipolar disorder

BackgroundAt least 50% of individuals with bipolar disorder (BD) present with psychosis during their lifetime. Psychotic symptoms have sometimes been linked to specific genetic and phenotypic markers. This study aims to explore potential differences between bipolar disorder subtypes by measuring white matter integrity of the brain and relationships with clinical measures. MethodsDiffusion tensor imaging and clinical measures were acquired from 102 participants, grouped as psychotic bipolar disorder (PBD) (n=48), non-psychotic bipolar disorder (NBD) (n=24), and healthy controls (n=30). We utilized a powerful, automated tool (TRACULA: Tracts Constrained by Underlying Anatomy) to analyze the fractional anisotropy (FA) and mean diffusivity (MD) of 18 white matter tracts. ResultsDecreased FA in numerous tracts was observed in bipolar disorder groups compared to healthy controls: bilateral cingulum-cingulate gyrus bundles, corticospinal tracts, and superior longitudinal fasciculi as well as the right hemisphere cingulum-angular bundle. Only left uncinate fasciculus FA differed between PBD and NPBD groups. We found no group differences in MD. Positive symptoms correlated with FA in the superior (inversely) and inferior (directly) longitudinal fasciculi. Negative symptoms directly correlated with mean FA of the corticospinal tract and cingulum-angular bundle. LimitationsNeurotropic, mood-stabilizing medication prescribed for individuals with BD may interact with measures of white matter integrity in our BD participants. ConclusionOur results indicate decreased white matter coherence in BD. Minimal differences in white matter FA between PBD and NPBD participants suggest related underlying neurobiology.

Biological aspects and candidate biomarkers for psychotic bipolar disorder: A systematic review.

We carried out a systematic review of the available literature about potential biomarkers of psychotic bipolar disorder (BD-P), a specific subset presenting worse outcome and greater risk of relapse than non-psychotic bipolar disorder (BD-NP). We searched the main psychiatric databases (PubMed, ISI Web of Knowledge, PsychInfo). Only original articles with the main topic of BD-P compared to schizophrenia/BD-NP/healthy controls (HC) written in English from 1994 to 2015 were included. BD-P patients presented higher kynurenic acid levels in the cerebrospinal fluid, elevated anti- S accharomyces cerevisiae antibodies levels, and lower serum levels of dehydroepiandrosterone sulfate and progesterone than BD-NP/HC. Event-related potentials abnormalities have been identified in BD-P with respect to BD-NP. BD-P patients also presented bigger ventricles but similar hippocampal volumes compared to BD-NP/HC. Although the results are contrasting, some cognitive deficits seemed to be related to the psychotic dimension of bipolar affective disorder, such as impairment in verbal/logical memory, working memory, verbal and semantic fluency and executive functioning. Finally, polymorphisms of genes, such as NRG1, 5HTTLPR (s), COMT, DAOA and some chromosome regions (16p12 and 13q), were positively associated with BD-P. Data about the identification of specific biomarkers for BD-P are promising, but most of them have not yet been replicated. They could lead the clinicians to an early diagnosis and proper treatment, thus ameliorating outcome of BD-P and reducing the biological changes associated with a long duration of illness. Further studies with bigger samples are needed to detect more specific biological markers of the psychotic dimension of bipolar affective disorder.

Subcortical neuromorphometry in schizophrenia spectrum and bipolar disorders.

BackgroundDisorders within the schizophrenia spectrum genetically overlap with bipolar disorder, yet questions remain about shared biological phenotypes. Investigation of brain structure in disease has been enhanced by developments in shape analysis methods that can identify subtle regional surface deformations. Our study aimed to identify brain structure surface deformations that were common across related psychiatric disorders, and characterize differences.MethodsUsing the automated FreeSurfer-initiated Large Deformation Diffeomorphic Metric Mapping, we examined volumes and shapes of seven brain structures: hippocampus, amygdala, caudate, nucleus accumbens, putamen, globus pallidus and thalamus. We compared findings in controls (CON; n = 40), and those with schizophrenia (SCZ; n = 52), schizotypal personality disorder (STP; n = 12), psychotic bipolar disorder (P-BP; n = 49) and nonpsychotic bipolar disorder (N-BP; n = 24), aged 15–35. Relationships between morphometric measures and positive, disorganized and negative symptoms were also investigated.ResultsInward deformation was present in the posterior thalamus in SCZ, P-BP and N-BP; and in the subiculum of the hippocampus in SCZ and STP. Most brain structures however showed unique shape deformations across groups. Correcting for intracranial size resulted in volumetric group differences for caudate (p < 0.001), putamen (p < 0.01) and globus pallidus (p < 0.001). Shape analysis showed dispersed patterns of expansion on the basal ganglia in SCZ. Significant clinical relationships with hippocampal, amygdalar and thalamic volumes were observed.ConclusionsFew similarities in surface deformation patterns were seen across groups, which may reflect differing neuropathologies. Posterior thalamic contraction in SCZ and BP suggest common genetic or environmental antecedents. Surface deformities in SCZ basal ganglia may have been due to antipsychotic drug effects.