A dimensional approach to the psychosis spectrum between bipolar disorder and schizophrenia: The Schizo-Bipolar Scale
ABSTRACT There is increasing evidence for phenomenological, biological and genetic overlap between schizophrenia and bipolar disorder, bringing into question the traditional dichotomy between them. Neurobiological models linked to dimensional clinical data may provide a better foundation to represent diagnostic variation in neuropsychiatric disorders.
To capture the interaction between psychosis and affective symptoms dimensionally, we devised a brief descriptive scale based on the type and relative proportions of psychotic and affective symptoms over the illness course. The scale was administered to a series of 762 patients with psychotic disorders, including schizophrenia, schizoaffective and psychotic bipolar disorder assessed as part of the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) study.
The resulting Schizo-Bipolar Scale scores across these disorders showed neither a clear dichotomy nor a simple continuous distribution. While the majority of cases had ratings close to prototypic schizophrenia or bipolar disorder, a large group (45% of cases) fell on the continuum between these two prototypes.
Our data suggest a hybrid conceptualization model with a representation of cases with prototypic schizophrenia or bipolar disorder at the extremes, but a large group of patients on the continuum between them that traditionally would be considered schizoaffective. A dimensional approach, using the Schizo-Bipolar Scale, characterized patients across a spectrum of psychopathology. This scale may provide a valuable means to examine the relationships between schizophrenia and psychotic bipolar disorder.
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ABSTRACT: The tremendous heterogeneity in the clinical symptoms and cognitive/emotional deficits seen in patients with schizophrenia has made it challenging to determine the underlying pathogenesis of the illness. One leading hypothesis that has come to the forefront over the past several decades is that schizophrenia is caused by aberrant connectivity between brain regions. In fact, a new field of connectomics has emerged to study the effects of brain connectivity in health and illness. It is known that schizophrenia is highly heritable, although in the search for the underlying genetic factors we have only scratched the tips of the omics icebergs. One technique to help identify underlying genetic factors is the use of heritable intermediate phenotypes, or endophenotypes. Endophenotypes provide mechanisms to study the genetic underpinnings of the disorder by focusing on measureable traits that are more proximal to gene regulation and expression than are symptoms. Thus, the goal of this paper is to conduct a critical review of the evidence linking both structural and functional connectivity as an endophenotype for schizophrenia.Current Topics in Medicinal Chemistry 11/2012; 12(21):2393-2403. DOI:10.2174/156802612805289953 · 3.45 Impact Factor
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ABSTRACT: Childhood-onset schizophrenia (COS) is a rare, chronic mental illness that is diagnosed in children prior to the age of 13. COS is a controversial diagnosis among clinicians and can be very difficult to diagnose for a number of reasons. Schizophrenia is a psychotic disorder characterized by hallucinations, delusions, flat affect, limited motivation and anhedonia. The psychotic nature of this disorder is quite disruptive to the child's emotional regulation, behavioural control and can reduce the child's ability to perform daily tasks that are crucial to adaptive functioning. Prior to the onset of schizophrenia, children often develop premorbid abnormalities, which are disturbances to a child's functioning that may serve as warning signs. These disturbances can manifest in a variety of behavioural ways and may include introversion, depression, aggression, suicidal ideation and manic-like behaviours. This article will review the clinical presentation of schizophrenia in children and examine the existing knowledge around aetiology, treatment approaches, assessment techniques and differential diagnostic considerations. Gaps in the literature are identified and directions for future research are discussed.01/2014; 2(1):735-747. DOI:10.1080/21642850.2014.927738
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ABSTRACT: There is increasing evidence that schizophrenia (SZ) and bipolar disorder (BD) share a number of cognitive, neurobiological, and genetic markers. Shared features may be most prevalent among SZ and BD with a history of psychosis. This study extended this literature by examining reinforcement learning (RL) performance in individuals with SZ (n = 29), BD with a history of psychosis (BD+; n = 24), BD without a history of psychosis (BD−; n = 23), and healthy controls (HC; n = 24). RL was assessed through a probabilistic stimulus selection task with acquisition and test phases. Computational modeling evaluated competing accounts of the data. Each participant’s trial-by-trial decision-making behavior was fit to 3 computational models of RL: (a) a standard actor–critic model simulating pure basal ganglia—dependent learning, (b) a pure Q-learning model simulating action selection as a function of learned expected reward value, and (c) a hybrid model where an actor–critic is “augmented” by a Q-learning component, meant to capture the top-down influence of orbitofrontal cortex value representations on the striatum. The SZ group demonstrated greater reinforcement learning impairments at acquisition and test phases than the BD+, BD−, and HC groups. The BD+ and BD− groups displayed comparable performance at acquisition and test phases. Collapsing across diagnostic categories, greater severity of current psychosis was associated with poorer acquisition of the most rewarding stimuli as well as poor go/no-go learning at test. Model fits revealed that reinforcement learning in SZ was best characterized by a pure actor–critic model where learning is driven by prediction error signaling alone. In contrast, BD−, BD+, and HC were best fit by a hybrid model where prediction errors are influenced by top-down expected value representations that guide decision making. These findings suggest that abnormalities in the reward system are more prominent in SZ than BD; however, current psychotic symptoms may be associated with reinforcement learning deficits regardless of a Diagnostic and Statistical Manual of Mental Disorders (5th Edition; American Psychiatric Association, 2013) diagnosis.Journal of Abnormal Psychology 01/2015; · 4.86 Impact Factor