Specificity and Continuity of Schizophrenia and Bipolar Disorder: Relation to Biomarkers

Abstract

Schizophrenia and bipolar disorder overlap considerably in terms of symptoms, familial patterns, risk genes, outcome, and treatment response. This article provides an overview of the specificity and continuity of schizophrenia and mood disorders on the basis of biomarkers, such as genes, molecules, cells, circuits, physiology and clinical phenomenology. Overall, the discussions herein provided support for the view that schizophrenia, schizoaffective disorder and bipolar disorder are in the continuum of severity of impairment, with bipolar disorder closer to normality and schizophrenia at the most severe end. This approach is based on the concept that examining biomarkers in several modalities across these diseases from the dimensional perspective would be meaningful. These considerations are expected to help develop new treatments for unmet needs, such as cognitive dysfunction, in psychiatric conditions.

Keywords: RDoC; Schizophrenia; bipolar disorder; cognitive dysfunction; differential diagnosis; psychosis; spectrum..

Fig. (1)

Typical profile of each disease diagnosed with a combination of psychopathological categories and phenomenological features. Categorical diagnoses of schizophrenia (blue), bipolar disorder (green), and schizoaffective disorder (violet) are accompanied by a patient's quantitative scores (connected by red lines) on five main dimensions of psychopathology [4]. Copyright (2009), with permission from Elsevier. (A higher resolution / colour version of this figure is available in the electronic copy of the article).

Fig. (2)

Schematic diagram of the RDoC framework.

Fig. (3)

Circuitry of dopamine system regulation and its disruption in schizophrenia. Hyperactive, dysrhythmic limbic hippocampus potentially disrupts multiple interconnected circuits, and could contribute to all 3 symptom classes of schizophrenia [54]. Hipp: Hippocampus, PFC: Prefrontal cortex, BLA: Basolateral amygdala, VP: Ventral pallidum, DA: Dopamine. Copyright (2019), with permission from Oxford University Press.

Fig. (4)

The mean static functional connectivity matrix across subjects and its visualized pattern for health control (HC), bipolar disorder with psychosis (BPP), schizoaffective disorder (SAD) and schizophrenia (SZ) group, respectively [62]. The red and blue lines represent positive and negative connectivity strengths, respectively. Copyright (2017), with permission from John Wiley and Sons. (A higher resolution / colour version of this figure is available in the electronic copy of the article).

Fig. (5)

Neurocognitive profiles of bipolar disorder clusters and the schizophrenia sample. The X-axis indicates the MATRICS Consensus Cognitive Battery (MCCB) domains. The Y-axis depicts a Z-scale score with a mean of 0 and a standard deviation of 1. Z scores were computed based upon the healthy control sample. Patients are divided into lines based on scoring for each cognitive domain [72]. Copyright (2014), with permission from Cambridge University Press. (A higher resolution / colour version of this figure is available in the electronic copy of the article).