Neural Responses to Reward and Psychosis Dimensions.

Many studies have examined either electroencephalogram (EEG) frequency activity or gray matter volumes (GMV) in various psychoses [including schizophrenia (SZ), schizoaffective (SZA), and psychotic bipolar disorder (PBP)]. Prior work demonstrated similar EEG and gray matter abnormalities in both SZ and PBP. Integrating EEG and GMV and jointly analyzing the combined data fully elucidates the linkage between the two and may provide better biomarker- or endophenotype-specificity for a particular illness. Joint exploratory investigations of EEG and GMV are scarce in the literature and the relationship between the two in psychosis is even less explored. We investigated a joint multivariate model to test whether the linear relationship or linkage between awake EEG (AEEG) frequency activity and GMV is abnormal across the psychosis dimension and if such effects are also present in first-degree relatives. We assessed 607 subjects comprising 264 probands [105 SZ, 72 SZA, and 87 PBP], 233 of their first degree relatives [82 SZ relatives (SZR), 71 SZA relatives (SZAR), and 80 PBP relatives (PBPR)], and 110 healthy comparison subjects (HC). All subjects underwent structural MRI (sMRI) and EEG scans. Frequency activity and voxel-based morphometric GMV were derived from EEG and sMRI data, respectively. Seven AEEG frequency and gray matter components were extracted using Joint independent component analysis (jICA). The loading coefficients (LC) were examined for group differences using analysis of covariance. Further, the LCs were correlated with psychopathology scores to identify relationship with clinical symptoms. Joint ICA revealed a single component differentiating SZ from HC (p < 0.006), comprising increased posterior alpha activity associated with decreased volume in inferior parietal lobe, supramarginal, parahippocampal gyrus, middle frontal, inferior temporal gyri, and increased volume of uncus and culmen. No components were aberrant in either PBP or SZA or any relative group. No significant association was identified with clinical symptom measures. Our data suggest that a joint EEG and GMV model yielded a biomarker specific to SZ, not abnormal in PBP or SZA. Alpha activity was related to both increased and decreased volume in different cortical structures. Additionally, the joint model failed to identify endophenotypes across psychotic disorders.

Back to table of contents Previous article Next article Book ReviewsFull AccessThe Overlap of Affective and Schizophrenic SpectraVictoria Shea M.D.Victoria Shea M.D.Search for more papers by this authorPublished Online:1 Jan 2008https://doi.org/10.1176/ps.2008.59.1.118aAboutSectionsPDF/EPUB ToolsAdd to favoritesDownload CitationsTrack Citations ShareShare onFacebookTwitterLinked InEmail Two leading scholars and researchers in the field of mood and psychotic disorders edited this textbook, The Overlap of Affective and Schizophrenic Spectra . The book explores one of the most basic but complex issues facing 21st century psychiatry and is highly recommended for those who treat patients who have mood and psychotic disorders. In practice today in the United States, clinicians have become complacent in terms of thinking seriously about the phenomenology of mood and psychotic disorders. We may need to ask ourselves if we know much more than Kraepelin did at the end of the 19th century. The editions of the DSM have become more than the guides they were intended to be. In clinical practice we view diagnostic categories as distinct entities. Both the editors and other contributors of this densely packed but readable text continue to question our understanding of the Kraepelinian dichotomy. In the preface, Akiskal points out that Kraepelin himself had doubts: "The symptoms we have used so far are not sufficient to always reliably distinguish between manic-depressive insanity and schizophrenia, but there are overlaps based on the origin of these symptoms from given preconditions." Kraepelin tended to look at symptoms from a longitudinal approach; later attempts were meant to distill symptoms into being pathognomonic of a particular condition. Akiskal is a professor of psychiatry at the University of San Diego, and Marneros is affiliated with the Department of Psychiatry and Psychotherapy at the Martin Luther University in Halle-Wittenberg, Germany. Marneros has looked specifically at the "in-between" psychotic disorders—such as schizoaffective disorder, late-onset schizophrenia, and brief psychotic disorders—in some detail to tease out possible differences in phenomenology and clinical outcomes in these less classically defined disorders. The in-between conditions at the interface of the psychotic and mood disorders have continued to be characterized and formulated in different ways. The trend in the United States has been to expand the diagnostic criteria of the schizoaffective disorders, first characterized as a diagnosis by Kasanin in 1933, from the DSM-III in evolution to the DSM-IV-TR . Further complicating the picture is the lack of consistent evidence from family studies to indicate that the psychotic and affective disorders "breed true." Both psychotic and mood disorders can be found in family members of probands in either diagnostic category. Preliminary gene linkages also show that there are overlapping linkage peaks in bipolar disorder and schizophrenia. The psychopharmacologic treatments of both overlap, especially with the advent of the second-generation antipsychotics.Finally, no matter how the diagnoses are viewed, the predominant themes appear to become part of the "spectrum"—with schizophrenia being the most affected by biology, temperament, and psychosocial factors and unipolar depression the least, with schizoaffective and bipolar disorders in between in terms of severity. The interface of this spectrum of disorders is not yet understood and needs to be studied further. As Akiskal says in the final chapter, "Lines of evidence have revealed both continuities and discontinuities between the affective and schizophrenic spectra. Perhaps what is 'in-between' represents a cross of the underlying dimensions of the two 'voluminous' spectra, or superposition of some of the contributory factors of one on the other." One only has to wonder whether efforts could be made to unify the concepts of the ICD-10 with a future edition of the DSM —that is, DSM-V —could be a step in the right direction toward guiding future research in terms of the diagnostic characterization of mood and psychotic disorders. Dr. Shea is in private practice in Quincy, Massachusetts. FiguresReferencesCited byDetailsCited byNone Volume 59Issue 1 January, 2008Pages 118-119PSYCHIATRIC SERVICES January 2008 Volume 59 Number 1 Metrics PDF download History Published online 1 January 2008 Published in print 1 January 2008

Callosal Abnormalities Across the Psychosis Dimension: Bipolar Schizophrenia Network on Intermediate Phenotypes

Conceptualizing psychotic disorders: don't throw the baby out with the bathwater

Cognitive impairment occurs across the psychosis spectrum and is associated with functional outcome. However, it is unknown whether these shared manifestations of cognitive dysfunction across diagnostic categories also reflect shared neurobiological mechanisms or whether the source of impairment differs. To examine whether the general cognitive deficit observed across psychotic disorders is similarly associated with functional integrity of 2 brain networks widely implicated in supporting many cognitive domains. A total of 201 healthy control participants and 375 patients with psychotic disorders from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium were studied from September 29, 2007, to May 31, 2011. The B-SNIP recruited healthy controls and stable outpatients from 6 sites: Baltimore, Maryland; Boston, Massachusetts; Chicago, Illinois; Dallas, Texas; Detroit, Michigan; and Hartford, Connecticut. All participants underwent cognitive testing and resting-state functional magnetic resonance imaging. Data analysis was performed from April 28, 2015, to February 21, 2017. The Brief Assessment of Cognition in Schizophrenia was used to measure cognitive ability. A principal axis factor analysis on the Brief Assessment of Cognition in Schizophrenia battery yielded a single factor (54% variance explained) that served as the measure of general cognitive ability. Functional network integrity measures included global and local efficiency of the whole brain, cingulo-opercular network (CON), frontoparietal network, and auditory network and exploratory analyses of all networks from the Power atlas. Group differences in network measures, associations between cognition and network measures, and mediation models were tested. The final sample for the current study included 201 healthy controls, 143 patients with schizophrenia, 103 patients with schizoaffective disorder, and 129 patients with psychotic bipolar disorder (mean [SD] age, 35.1 [12.0] years; 281 male [48.8%] and 295 female [51.2%]; 181 white [31.4%], 348 black [60.4%], and 47 other [8.2%]). Patients with schizophrenia (Cohen d = 0.36, P < .001) and psychotic bipolar disorder (Cohen d = 0.33, P = .002) had significantly reduced CON global efficiency compared with healthy controls. All patients with psychotic disorders had significantly reduced CON local efficiency, but the clinical groups did not differ from one another. The CON global efficiency was significantly associated with general cognitive ability across all groups (β = 0.099, P = .009) and significantly mediated the association between psychotic disorder status and general cognition (β = -0.037; 95% CI, -0.076 to -0.014). Subcortical network global efficiency was also significantly reduced in psychotic disorders (F3,587 = 4.01, P = .008) and positively predicted cognitive ability (β = 0.094, P = .009). These findings provide evidence that reduced CON and subcortical network efficiency play a role in the general cognitive deficit observed across the psychosis spectrum. They provide new support for the dimensional hypothesis that a shared neurobiological mechanism underlies cognitive impairment in psychotic disorders.

Cognitive endophenotypes of psychosis within dimension and diagnosis

The criteria for schizotypal personality disorder were developed on the basis of traits observed in biologic relatives of schizophrenic and borderline schizophrenic probands from the Danish adoption studies. In this review, the relationship between schizotypal personality disorder and the schizophrenic spectrum, affective disorders, and psychotic disorders is explored. A dimension of psychosis may overlap with the schizophrenia spectrum to yield chronic schizophrenia, with the affective disorders spectrum to yield psychotic affective disorder, or by itself lead to other psychotic disorders. Schizotypal personality disorder in this model is posited to represent schizophrenia spectrum disorder that does not overlap with psychosis, whereas nonpsychotic affective disorders represent the affective disorders that do not overlap with psychosis. Delusional disorder represents another psychotic disorder that is not specifically related to either schizophrenia or the affective disorders. Evidence suggests that the schizotypal personality disorder criteria, particularly those emphasizing the negative symptoms or deficit-like symptoms of this disorder, specifically identify a unique relationship to the schizophrenia spectrum.

Factors associated with overweight and obesity in schizophrenia, schizoaffective and bipolar disorders

Overall : Evidence continues to accumulate on heterogeneity in phenomenology, course and outcome of non-affective and affective psychotic disorders. Both DSM and ICD classification systems have evolved to include a large number of categories of psychosis. However, doubt remains about this categorical approach because of high comorbidity, common etiological factors and the absence of zones of relative rarity between categorical diagnoses. Some authors have nevertheless argued that categorical representations of psychosis may still be of clinical utility if used in combination with dimensional indicators.It is now widely accepted that psychotic symptoms partition into several symptom dimensions that would support the heterogeneity of psychotic disorders. However, there is no consensus on the exact number of these dimensions, with previous factor-analytic work pointing towards models with two to twelve specific symptom dimensions. However, recently, there has been evidence for a transdiagnostic dimension underlying affective and non-affective psychotic symptoms in schizophrenia, schizoaffective and bipolar disorder that challenges their classification as distinct diagnostic constructs. There is also considerable heterogeneity in clinical course and outcome of psychotic disorders, but how to best map and model this over time remains to be established. Taken together, this presents significant challenges for the classification of psychotic disorders as separate diagnostic entities.This symposium brings together international researchers at the forefront of research into the phenomenology, course and outcome of psychotic disorders. Roman Kotov will present novel data on symptom dimensions and examines the course of these dimensions in an epidemiologic cohort of 628 first-admission inpatients with psychosis interviewed 6 times over two decades in the Suffolk County Mental Health Project. Craig Morgan will report new findings from the 10-year follow-up of the Aetiology and Ethnicity in Schizophrenia and Other Psychoses (AESOP-10) study, an epidemiological cohort of 552 patients with a first episode psychosis, using a data driven approach to identify latent trajectory classes to account for heterogeneity in patterns of change in psychotic symptoms over time and characterize these trajectories with the WHO classification, baseline demographic characteristics and diagnoses. Ulrich Reininghaus will present novel data from the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP) consortium to investigate whether there is a transdiagnostic dimension cutting across symptoms of schizophrenia, schizoaffective disorder and psychotic bipolar I disorder. Diego Quattrone will report recent findings from EU-GEI Functional Enviromics Study on genetic and socio-environmental factors associated with transdiagnostic and specific symptom dimensions of non-affective and affective psychosis. Robin Murray will discuss these findings in the context of new challenges in the field and directions for future research.

Alterations in hippocampal connectivity across the psychosis dimension

Cognitive burden of anticholinergic medications in psychotic disorders

Brain gray matter phenotypes across the psychosis dimension

P-1298 - Bilirubin and brief psychotic disorder

Mounting evidence suggests that compromised neurocognitive function is a central feature of schizophrenia. There are, however, schizophrenia patients with a normal neuropsychological (NP) performance, but estimates of the proportion of NP normal patients vary considerably between studies. Neurocognitive dysfunction is also a characteristic of other psychotic disorders, yet there are inconsistencies in the literature regarding the similarity to impairments in schizophrenia. NP normality in psychotic affective disorders has not been systematically studied. Data came from the Suffolk County Mental Health Project, an epidemiological study of first-admission patients with psychotic disorders. Respondents with a diagnosis of schizophrenia (N = 94) or schizoaffective disorder (N = 15), bipolar disorder (N = 78), and major depressive disorder (N = 48) were administered a battery of NP tests assessing 8 cognitive domains 2 years after index admission. Patients' performance profile was compared, and their NP status was classified based on 3 previously published criteria that vary in their stringency. The 4 diagnostic groups had comparable NP performance profile patterns. All groups demonstrated impairments in memory, executive functions, and attention and processing speed. However, schizophrenia patients were more impaired than the other groups on all cognitive domains. Results were not attenuated when IQ was controlled. Prevalence of NP normality ranged between 16% and 45% in schizophrenia, 20% and 33% in schizoaffective disorder, 42% and 64% in bipolar disorder, and 42% and 77% in depression, depending on the criterion employed. Evidence suggests that differences in NP performance between schizophrenia and psychotic affective disorders are largely quantitative. NP impairment is also common in psychotic affective disorders. A significant minority of schizophrenia patients are NP normal.

Patients with concurrent schizophrenic and mood symptoms are often treated with antipsychotics plus antidepressant or thymoleptic drugs. The authors review the literature on treatment of two overlapping groups of patients: those with schizoaffective disorder and those with schizophrenia and concurrent mood symptoms. MEDLINE searches (from 1976 onward) were undertaken to identify treatment studies of both groups, and references in these reports were checked. Selection of studies for review was based on the use of specified diagnostic criteria and of parallel-group, double-blind design (or, where few such studies addressed a particular issue, large open studies). A total of 18 treatment studies of schizoaffective disorder and 15 of schizophrenia with mood symptoms were selected for review. For acute exacerbations of schizoaffective disorder or of schizophrenia with mood symptoms, antipsychotics appeared to be as effective as combination treatments, and there was some evidence for superior efficacy of atypical antipsychotics. There was evidence supporting adjunctive antidepressant treatment for schizophrenic and schizoaffective patients who develop a major depressive syndrome after remission of acute psychosis, but there were mixed results for treatment of subsyndromal depression. There was little evidence to support adjunctive lithium for depressive symptoms and no evidence concerning its use for manic symptoms in patients with schizophrenia. Empirical data suggest that both groups of patients are best treated by optimizing antipsychotic treatment and that atypical antipsychotics may prove to be most effective. Adjunctive antidepressants may be useful for patients with major depression who are not acutely ill. Careful longitudinal assessment is required to ensure identification of primary mood disorders.