Working memory networks and activation patterns in schizophrenia and bipolar disorder: comparison with healthy controls

Shared white-matter dysconnectivity in schizophrenia and bipolar disorder with psychosis

BACKGROUND

There is an appreciable overlap in the clinical presentation, epidemiology and treatment response of the two major psychotic disorders - schizophrenia and bipolar disorder. Nevertheless, the shared neurobiological correlates of these two disorders are still elusive. Using diffusion tensor imaging (DTI), we sought to identify brain regions which share altered white-matter connectivity across a clinical spectrum of psychotic disorders.

METHOD

A sample of 41 healthy controls, 62 patients in a clinically stable state of an established psychotic disorder (40 with schizophrenia, 22 with bipolar disorder) were studied using DTI. Tract-based spatial statistics (TBSS) was used in order to study group differences between patients with psychosis and healthy controls using fractional anisotropy (FA). Probabilistic tractography was used in order to visualize the clusters that showed significant differences between these two groups.

RESULTS

The TBSS analysis revealed five clusters (callosal, posterior thalamic/optic, paralimbic, fronto-occipital) with reduced FA in psychosis. This reduction in FA was associated with an increase in radial diffusivity and a decrease in mode of anisotropy. Factor analysis revealed a single white-matter integrity factor that predicted social and occupational functioning scores in patients irrespective of the diagnostic categorization.

CONCLUSIONS

Our results show that a shared white-matter dysconnectivity links the two major psychotic disorders. These microstructural abnormalities predict functional outcome better than symptom-based diagnostic boundaries during a clinically stable phase of illness, highlighting the importance of seeking shared neurobiological factors that underlie the clinical spectrum of psychosis.

Association between Genetic Variation in the Oxytocin Receptor Gene and Emotional Withdrawal, but not between Oxytocin Pathway Genes and Diagnosis in Psychotic Disorders

Social dysfunction is common in patients with psychotic disorders. Oxytocin is a neuropeptide with a central role in social behavior. This study aims to explore the relationship between oxytocin pathway genes and symptoms related to social dysfunction in patients with psychotic disorders. We performed association analyses between four oxytocin pathway genes (OXT, OXTR, AVP, and CD38) and four areas of social behavior-related psychopathology as measured by Positive and Negative Syndrome Scale. For this purpose, we used both a polygenic risk score (PGRS) and single OXTR candidate single nucleotide polymorphism previously reported in the literature (rs53576, rs237902, and rs2254298). A total of 734 subjects with DSM-IV psychotic spectrum disorders and 420 healthy controls were included. Oxytocin pathway PGRSs were calculated based on the independent Psychiatric Genomics Consortium study sample. There was a significant association between symptom of Emotional Withdrawal and the previously reported OXTR risk allele A in rs53576. No significant associations between oxytocin pathway gene variants and a diagnosis of psychotic disorder were found. Our findings indicate that while oxytocin pathway genes do not appear to contribute to the susceptibility to psychotic disorders, variations in the OXTR gene might play a role in the development of impaired social behavior.

Cognitive impairments in psychotic disorders: common mechanisms and measurement

Decades of research have provided robust evidence of cognitive impairments in psychotic disorders. Individuals with schizophrenia appear to be impaired on the majority of neuropsychological tasks, leading some researchers to argue for a "generalized deficit", in which the multitude of cognitive impairments are the result of a common neurobiological source. One such common mechanism may be an inability to actively represent goal information in working memory as a means to guide behavior, with the associated neurobiological impairment being a disturbance in the function of the dorsolateral prefrontal cortex. Here, we provide a discussion of the evidence for such impairment in schizophrenia, and how it manifests in domains typically referred to as cognitive control, working memory and episodic memory. We also briefly discuss cognitive impairment in affective psychoses, reporting that the degree of impairment is worse in schizophrenia than in bipolar disorder and psychotic major depression, but the profile of impairment is similar, possibly reflecting common mechanisms at the neural level. Given the recent release of the DSM-5, we end with a brief discussion on assessing cognition in the context of diagnosis and treatment planning in psychotic disorders.

Polygenic risk score and the psychosis continuum model

OBJECTIVE

Schizophrenia (SZ) and bipolar disorder (BD) are heritable, polygenic disorders with shared clinical characteristics and genetic risk indicating a psychosis continuum. This is the first study using polygenic risk score (PGRS) to investigate the localization of diagnostic subcategories along the entire psychosis spectrum.

METHOD

Based on results from the Psychiatric Genomics Consortium (PGC), we assigned a SZ and BD PGRS to each individual in our independent sample [N=570 BD spectrum cases, 452 SZ spectrum cases and 415 healthy controls (CTR)]. Potential differences in mean SZ and BD PGRS across diagnostic spectrums and subcategories were explored.

RESULTS

SZ and BD PGRSs were significantly associated with both SZ and BD spectrums compared with CTR. For the subcategories, SZ PGRS was significantly associated with SZ, schizoaffective disorder, psychosis not otherwise specified, and BD1, while BD PGRS was significantly associated with BD1 and BD2. There were no significant differences between any of the diagnostic spectrums or subgroups for neither the SZ nor BD PGRS. Lifetime psychosis was significantly associated with SZ PGRS but not with BD PGRS.

CONCLUSION

These findings further support the psychosis continuum model and provide molecular polygenetic validation of the localization of diagnostic subcategories within this continuum.