Bipolar Disorder With Psychosis Research Articles

Risk for alcohol use problems in severe mental illness: Interactions with sex and racial/ethnic minority status

BackgroundAlcohol use disorder (AUD) is exceedingly common among individuals with bipolar disorder and schizophrenia. However, studies on alcohol use in psychiatric illness rely largely on population surveys with limited representation of severe mental illness (SMI); schizophrenia and bipolar disorder. MethodsUsing data from the Genomic Psychiatry Cohort (GPC) (Pato MT, 2013), associations of bipolar disorder and schizophrenia with alcohol use problems were examined in a diverse US based sample, considering the influence of self-described race (African Ancestry (AA), European Ancestry (EA), or Latinx Ancestry (LA)), sex, and tobacco use. Participants answered alcohol use problem items derived from the CAGE instrument, yielding a summed “probable” alcohol use disorder (pAUD) risk score. ResultsThis study included 1952 individuals with bipolar disorder with psychosis (BDwP), 409 with bipolar disorder without psychosis (BD), 9218 with schizophrenia (SCZ), and 10,416 unaffected individuals. We found that SMI (BDwP, BD, SCZ) was associated with elevated AUD risk scores (B = 0.223, p < 0.001), an association which was strongest in females, particularly those of AA and LA, and in tobacco users. Schizophrenia was associated with the greatest increase in pAUD score (B = 0.141, p < 0.001). pAUD risk scores were increased among participants with bipolar disorder, with greater increases in BDwP (B = 0.125, p < 0.001) than in BD without psychosis (B = 0.027, p < 0.001). LimitationsLimitations include reliance on self-report data, screening items for AUD, voluntary recruitment bias, and differences in race/sex distribution between groups, which were statistically adjusted for in analytic models. ConclusionsSMI is associated with risk for AUD, particularly among females from racial minority groups, smokers, and those with psychotic disorders.

Reduced white matter microstructure in bipolar disorder with and without psychosis.

Affective and psychotic features overlap considerably in bipolar I disorder, complicating efforts to determine its etiology and develop targeted treatments. In order to clarify whether mechanisms are similar or divergent for bipolar disorder with psychosis (BDP) and bipolar disorder with no psychosis (BDNP), neurobiological profiles for both the groups must first be established. This study examines white matter structure in the BDP and BDNP groups, in an effort to identify portions of white matter that may differ between the bipolar and healthy groups or between the bipolar subgroups themselves. Diffusion-weighted imaging data were acquired from participants with BDP (n=45), BDNP (n=40), and healthy comparisons (HC) (n=66). Fractional anisotropy (FA), radial diffusivity (RD), and spin distribution function (SDF) values indexing white matter diffusivity or spin density were calculated and compared between the groups. In comparisons between both the bipolar groups and HC, FA (FDR<0.00001) and RD (FDR=0.0037) differed minimally, in localized portions of the left cingulum and corpus callosum, while reductions in SDF (FDR=0.0002) were more widespread. The bipolar subgroups did not differ from each other on FA, RD, or SDF metrics. Together, these results demonstrate a novel profile of white matter differences in bipolar disorder and suggest that this white matter pathology is associated with the affective disturbance common to those with bipolar disorder rather than the psychotic features unique to some. The white matter alterations identified in this study may provide substrates for future studies examining specific mechanisms that target affective domains of illness.

Specific white matter connectomic changes in schizophrenia compared with psychotic bipolar disorder.

Schizophrenia (SZ) and bipolar disorder with psychosis (BDP) can be clinically confusing. The specific connectomic changes in SZ compared with BDP may lead to a deeper comprehension of the pathophysiological core of SZ. Therefore, this study explored the common and distinct white matter (WM) structural connectomic alterations between these two diseases. Diffusion tensor imaging data were collected from 19 drug-naïve patients with first episode SZ, 19 drug-naïve patients with BDP, and 19 healthy controls (HC). A graph theoretical approach was used to assess the brain WM network properties. Except for the clustering coefficients, no significant differences in the global parameters was found between SZ and BDP. Five brain regions, the right precentral, right post-cingulum, right insula, left superior occipital, and left inferior temporal gyri, showed specific differences in the nodal parameters in SZ compared with BDP and HC. Nine brain regions, the left rectus, left lingual, right inferior parietal, left superior temporal, right precentral, right postcentral, bilateral middle frontal, and right post-cingulum gyri, showed specific differences in the nodal parameters in BDP. Significant correlations between clinical symptoms and connectomic changes were detected in the right insula and left superior occipital gyrus in patients with SZ but in the left lingual gyrus in patients with BDP. Identifying shared and distinct WM structural networks between SZ and BDP may improve the understanding of the neuroanatomy of mental diseases. Specifically, the insula, the inferior temporal, superior temporal, and the lingual gyri may help to distinguish between SZ and BDP.

Auditory paired-stimuli responses across the psychosis and bipolar spectrum and their relationship to clinical features.

EEG responses during auditory paired-stimuli paradigms are putative biomarkers of psychosis syndromes. The initial iteration of the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP1) showed unique and common patterns of abnormalities across schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BDP). This study replicates those findings in new and large samples of psychosis cases and extends them to an important comparison group, bipolar disorder without psychosis (BDNP). Paired stimuli responses from 64-sensor EEG recording were compared across psychosis (n = 597; SZ = 225, SAD = 201, BDP = 171), BDNP (n = 66), and healthy (n = 415) subjects from the second iteration of B-SNIP. EEG activity was analyzed in voltage and in the time-frequency domain. Principal component analysis (PCA) over sensors (sPCA) was used to efficiently capture EEG voltage responses to the paired stimuli. Evoked power was calculated via a Morlet wavelet procedure. A frequency PCA divided evoked power data into three frequency bands: Low (4-17 Hz), Beta (18-32 Hz), and Gamma (33-55 Hz). Each time-course (ERP Voltage, Low, Beta, and Gamma) were then segmented into 20 ms bins and analyzed for group differences. To efficiently summarize the multiple EEG components that best captured group differences we used multivariate discriminant and correlational analyses. This approach yields a reduced set of measures that may be useful in subsequent biomarker investigations. Group ANOVAs identified 17 time-ranges that showed significant group differences (p < .05 after FDR correction), constructively replicating B-SNIP1 findings. Multivariate linear discriminant analysis parsimoniously selected variables that best accounted for group differences: The P50 response to S1 and S2 uniquely separated BDNP from healthy and psychosis subjects (BDNP > all other groups); the S1 N100 response separated groups along an axis of psychopathology severity (HC > BDNP > BDP > SAD > SZ); the S1 P200 response indexed psychosis psychopathology (HC/BDNP > SAD/SZ/BDP); and the preparatory period to the S2 stimulus separated SZ from other groups (SZ > SAD/BDP>HC/BDNP).Canonical correlation identified an association between the neural responses during the S1 N100, S1 N200 and S2 preparatory period and PANSS positive symptoms and social functioning. The neural responses during the S1 P50 and S1 N100 were associated with PANSS Negative/General, MADRS and Young Mania symptoms. This study constructively replicated prior B-SNIP1 research on auditory deviations observed during the paired stimuli task in SZ, SAD and BDP. Inclusion of a group of BDNP allows for the identification of biomarkers more closely related to affective versus nonaffective clinical phenotypes and neural distinctions between BDP and BDNP. Findings have implications for nosology and future translational work given that some biomarkers are shared across all psychosis and some are unique to affective syndromes.

Identifying commonality and specificity across psychosis sub-groups via classification based on features from dynamic connectivity analysis

It is difficult to distinguish schizophrenia (SZ), schizoaffective disorder (SAD), and bipolar disorder with psychosis (BPP) as their clinical diagnoses rely on symptoms that overlap. In this paper, we investigate if there is biological evidence to support the symptom-based clinical categories by looking across the three disorders using dynamic connectivity measures, and provide meaningful characteristics on which brain functional connectivity measures are commonly or uniquely impaired. Large-sample functional magnetic resonance image (fMRI) datasets from 623 subjects including 238 healthy controls (HCs), 113 SZ patients, 132 SAD patients, and 140 BPP patients were analyzed. First, we computed whole-brain dynamic functional connectivity (DFC) using a sliding-window technique, and then extracted the individual connectivity states by applying our previously proposed decomposition-based DFC analysis method. Next, with the features from the dominant connectivity state, we assessed the clinical categories by performing both four-group (SZ, SAD, BPP and healthy control groups) and pair-wise classification using a support vector machine within cross-validation. Furthermore, we comprehensively summarized the shared and unique connectivity alterations among the disorders. In terms of the classification performance, our method achieved 69% in the four-group classification and >80% in the between-group classifications for the mean overall accuracy; and yielded 66% in the four-group classification and >80% in the between-group classifications for the mean balanced accuracy. Through summarizing the features that were automatically selected in the classifications, we found that among the three symptom-related disorders, their disorder-common impairments primarily included the decreased connectivity strength between thalamus and cerebellum and the increased strength between postcentral gyrus and thalamus. The disorder-unique changes included more various brain regions, mainly in the temporal and frontal gyrus. Our work demonstrates that dynamic functional connectivity provides biological evidence that both common and unique impairments exist in psychosis sub-groups.

Auditory steady-state EEG response across the schizo-bipolar spectrum

Deviant auditory steady-state responses (aSSRs) in the gamma range (30–90 Hz) may be translational biomarkers for schizophrenia (SZ). This study tests whether aSSR deviations are (i) specific to SZ across the psychosis dimension, (ii) specific to particular frequency bands, and (iii) present in bipolar I disorder without psychosis (BDNP). MethodsBeta (20-), low- (40-), and high-gamma (80-Hz) aSSRs were measured with EEG and compared across 113 SZ, 105 schizoaffective disorder (SAD), 99 bipolar disorder with psychosis (BDP), 68 BDNP, and 137 healthy comparison subjects (HC). Standard aSSR measures (single-trial power [STP] and inter-trial phase coherence [ITC]), as well as evoked responses to stimulus onsets/offsets and pre-stimulus power, were quantified. Multivariate canonical discriminant analysis was used to summarize variables that efficiently and maximally differentiated groups. Results(i) Psychosis groups showed reduced responses on ITC 20 Hz, STP/ITC 40 Hz, STP/ITC 80 Hz, indicating dimensional reductions in aSSR across the psychosis spectrum not specific to aSSR frequency. For the 40- and 80-Hz ITCs there was greater reduction in SZ compared to SAD, possibly indexing cortical disruptions linked to psychosis without mood symptoms. (ii) All probands had elevated pre-stimulus power, possibly compromising neural entrainment to the steady-state stimuli. (iii) Onset/Offset and 80 Hz ITC responses were most important for group discrimination and showed dimensional reduction across the schizo-bipolar spectrum. ConclusionsDeviant aSSRs were found across the schizo-bipolar spectrum at multiple frequencies with psychosis status and severity linked to greatest reductions at low and high gamma.

Identifying dynamic functional connectivity biomarkers using GIG-ICA: Application to schizophrenia, schizoaffective disorder, and psychotic bipolar disorder.

Functional magnetic resonance imaging (fMRI) studies have shown altered brain dynamic functional connectivity (DFC) in mental disorders. Here, we aim to explore DFC across a spectrum of symptomatically-related disorders including bipolar disorder with psychosis (BPP), schizoaffective disorder (SAD), and schizophrenia (SZ). We introduce a group information guided independent component analysis procedure to estimate both group-level and subject-specific connectivity states from DFC. Using resting-state fMRI data of 238 healthy controls (HCs), 140 BPP, 132 SAD, and 113 SZ patients, we identified measures differentiating groups from the whole-brain DFC and traditional static functional connectivity (SFC), separately. Results show that DFC provided more informative measures than SFC. Diagnosis-related connectivity states were evident using DFC analysis. For the dominant state consistent across groups, we found 22 instances of hypoconnectivity (with decreasing trends from HC to BPP to SAD to SZ) mainly involving post-central, frontal, and cerebellar cortices as well as 34 examples of hyperconnectivity (with increasing trends HC through SZ) primarily involving thalamus and temporal cortices. Hypoconnectivities/hyperconnectivities also showed negative/positive correlations, respectively, with clinical symptom scores. Specifically, hypoconnectivities linking postcentral and frontal gyri were significantly negatively correlated with the PANSS positive/negative scores. For frontal connectivities, BPP resembled HC while SAD and SZ were more similar. Three connectivities involving the left cerebellar crus differentiated SZ from other groups and one connection linking frontal and fusiform cortices showed a SAD-unique change. In summary, our method is promising for assessing DFC and may yield imaging biomarkers for quantifying the dimension of psychosis. Hum Brain Mapp 38:2683-2708, 2017. © 2017 Wiley Periodicals, Inc.

Disconnection Between Amygdala and Medial Prefrontal Cortex in Psychotic Disorders.

Distracting emotional information impairs attention more in schizophrenia (SCZ) than in never-psychotic individuals. However, it is unclear whether this impairment and its neural circuitry is indicative generally of psychosis, or specifically of SCZ, and whether it is even more specific to certain SCZ symptoms (eg, deficit syndrome). It is also unclear if this abnormality contributes to impaired behavioral performance and real-world functioning. Functional imaging data were recorded while individuals with SCZ, bipolar disorder with psychosis (BDP) and no history of psychotic disorders (CON) attended to identity of faces while ignoring their emotional expressions. We examined group differences in functional connectivity between amygdala, involved in emotional evaluation, and sub-regions of medial prefrontal cortex (MPFC), involved in emotion regulation and cognitive control. Additionally, we examined correlation of this connectivity with deficit syndrome and real-world functioning. Behaviorally, SCZ showed the worst accuracy when matching the identity of emotional vs neutral faces. Neurally, SCZ showed lower amygdala-MPFC connectivity than BDP and CON. BPD did not differ from CON, neurally or behaviorally. In patients, reduced amygdala-MPFC connectivity during emotional distractors was related to worse emotional vs neutral accuracy, greater deficit syndrome severity, and unemployment. Thus, reduced amygdala-MPFC functional connectivity during emotional distractors reflects a deficit that is specific to SCZ. This reduction in connectivity is associated with worse clinical and real-world functioning. Overall, these findings provide support for the specificity and clinical utility of amygdala-MPFC functional connectivity as a potential neural marker of SCZ.

Myelin vs Axon Abnormalities in White Matter in Bipolar Disorder

White matter (WM) abnormalities are among the most commonly reported neuroimaging findings in bipolar disorder. Nonetheless, the specific nature and pathophysiology of these abnormalities remain unclear. Use of a combination of magnetization transfer ratio (MTR) and diffusion tensor spectroscopy (DTS) permits examination of myelin and axon abnormalities separately. We aimed to examine myelination and axon geometry in euthymic patients with bipolar disorder with psychosis (BDP) by combining these two complementary noninvasive MRI techniques. We applied a combined MRI approach using MTR to study myelin content and DTS to study metabolite (N-acetylaspartate, NAA) diffusion within axons in patients with BDP (n=21) and healthy controls (n=24). Data were collected from a 1 × 3 × 3-cm voxel within the right prefrontal cortex WM at 4 Tesla. Clinical and cognitive data were examined in association with MTR and DTS data. MTR was significantly reduced in BDP, suggesting reduced myelin content. The apparent diffusion coefficient of NAA did not differ from healthy controls, suggesting no changes in axon geometry in patients with BDP. These findings suggest that patients with BDP exhibit reduced myelin content, but no changes in axon geometry compared with controls. These findings are in contrast with our recent findings, using the same techniques, in patients with schizophrenia (SZ), which suggest both myelination and axon abnormalities in SZ. This difference may indicate that alterations in WM in BDP may have unique causes and may be less extensive than WM abnormalities seen in SZ.

Disease and drug effects on internally-generated and externally-elicited responses in first episode schizophrenia and psychotic bipolar disorder

Neurocognitive deficits are associated with most psychotic disorders, but may differ across diagnosis and by treatment status. This ambiguity is partly addressed in longitudinal pre/post treatment studies with first episode patients. Antipsychotic-naïve first-episode schizophrenia patients have shown intact performance on a predictive saccade task that assesses simple motor learning, spatial abilities, and response planning. After antipsychotic treatment, however, schizophrenia patients performing this task show a selective impairment in the accuracy of anticipatory responses, generated from learned internal representations of the task stimulus. This finding is in line with other observations of antipsychotic medication effects on frontostriatal systems, particularly dorsolateral prefrontal cortex. We sought to replicate this provocative finding with an independent sample of antipsychotic-naïve first-episode schizophrenia patients and extend it by including a group of patients with first episode bipolar disorder with psychosis (BDP). Matched healthy controls were also studied in parallel. Schizophrenia patients demonstrated intact performance pretreatment followed by impairment post-treatment for accuracy of anticipatory responses, and worse accuracy was associated with higher antipsychotic dose. BDP patients displayed saccade accuracy deficits before and after treatment and had no correlation of performance and antipsychotic dose. The findings suggest different neural alterations early in the course of each psychotic disorder, and different vulnerabilities to antipsychotic treatment effects between schizophrenia and BDP.

Spatiotemporal and frequency domain analysis of auditory paired stimuli processing in schizophrenia and bipolar disorder with psychosis

Individuals with schizophrenia (SZ) or bipolar disorder with psychosis (BPP) may share neurophysiological abnormalities as measured in auditory paired-stimuli paradigms with electroencephalography (EEG). Such investigations have been limited, however, by quantifying only event-related potential peaks and/or broad frequency bands at limited scalp locations without considering possible mediating factors (e.g., baseline differences). Results from 64-sensor EEG collected in 180 age- and gender-matched participants reveal (i) accentuated prestimulus gamma oscillations and (ii) reduced P2 amplitudes and theta/alpha oscillations to S1 among participants with both SZ and BPP. Conversely, (iii) N1s in those with SZ to S1 were reduced compared to healthy volunteers and those with BPP, whereas (iv) beta range oscillations 200-300 ms following S2 were accentuated in those with BPP but not those with SZ. Results reveal a pattern of both unique and shared neurophysiological phenotypes occurring within major psychotic diagnoses.