Although schizophrenia and schizoaffective disorder remain separable in diagnostic systems, the validity of the distinction is uncertain. This study asked whether schizophrenia and schizoaffective disorder are distinguishable on selected cognitive, social cognitive and structural social brain measures. Outpatients with a diagnosis of schizophrenia (n = 44) or schizoaffective disorder (n = 29) and non-psychiatric control participants (n = 62) were studied. Patients were assessed clinically (Positive and Negative Syndrome Scale) and all participants were administered a battery of cognitive (MATRICS Consensus Cognitive Battery; Wechsler Abbreviated Scale of Intelligence, Wide Range Achievement Reading) and social cognitive (Reading the Mind in the Eyes, Mayer-Salovey-Caruso Emotional Intelligence Test; MSCEIT) tasks. In addition, participants underwent structural magnetic resonance imaging (MRI) to yield cortical thickness data for 42 regions associated with the social brain network. Results showed no significant differences between patient groups on 17/18 cognitive/social cognitive and social brain cortical thickness measures. In contrast, schizophrenia and schizoaffective disorder patients differed from controls on 16/18 and 11/18 measures respectively. Schizoaffective disorder patients outperformed schizophrenia patients on an emotion regulation task (MSCEIT). Schizophrenia and schizoaffective disorder are largely indistinguishable on key cognitive, social cognitive and neural measures. The continuing separation of these syndromes in diagnostic systems and disease models requires is questionable and requires further attention.

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BackgroundResolving the definition, heterogeneity and validity of schizophrenia-spectrum disorders remains a challenge, including the distinctiveness of schizophrenia and schizoaffective disorder. Here we report clinical, cognitive and structural brain imaging data with special reference to social processing in corresponding patient groups and non-psychiatric control participants. The study question was: to what extent do these data support schizophrenia and schizoaffective disorder as separable biobehavioural syndromes of psychotic illness?MethodsDSM-V criteria were applied to an outpatient sample, yielding n=44 with schizophrenia and n=29 with schizoaffective disorder. In addition to demographic data, symptom severity was measured in both patient groups with the Positive and Negative Syndrome Scale (PANSS). Overall cognition was measured with the MATRICS Consensus Cognitive Battery (MCCB) composite and social cognition with Theory of Mind, emotion perception and attribution bias tasks. Cortical thickness in regions associated with the social brain network was measured with a 3T General Electric MRI short bore scanner, with parcellations obtained using methods described by Destrieux et al. (2010) in Freesurfer. Non-psychiatric control participants (n=63) were studied with cognitive, social cognitive and MRI measures for comparison.ResultsStudy groups did not differ in age, educational achievement, proportion of males or prevalence of English as the preferred language. Patient groups did not differ in symptom severity (PANSS) or anti-psychotic medication (1st versus 2nd generation), but did differ significantly in terms of independent living, with schizoaffective patients significantly more independent than schizophrenia patients. The composite MCCB index and theory of mind task revealed significant differences between controls and patient groups, but no differences between patient groups. Schizophrenia patients differed significantly from both schizoaffective and control participants on the emotion perception task. There were no group differences in attribution bias. Multivariate analysis of variance (MANOVA) revealed that cortical thickness values in the social network were significantly lower in patient groups relative to controls for 14 regions. There were no schizophrenia vs schizoaffective group differences following correction. However, 9 regions were significantly reduced in schizophrenia patients relative to controls and 5 regions in schizoaffective patients relative to controls. Cingulate gyrus and superior temporal sulcus regional differences remained significant following correction.DiscussionAlthough schizophrenia and schizoaffective disorder continue to be recognized as distinct syndromes in some diagnostic systems (e.g. DMS V), the validity of the distinction remains in question. Apart from functional independence, which may in part be an artifact of the diagnostic criteria, and aspects of emotion perception, we found no evidence to support longstanding conjectures that these syndromes are ...

Background: Genetics is known to influence both schizophrenia risk and brain structure. Thereby a question emerges as to whether the genetic underpinnings of these two traits overlap. Methods: We focused on 1402 common single nucleotide polymorphisms (SNPs) which were mapped from the psychiatric genomics consortium (PGC) 108 regions and showed relatively strong group differences (P < 1.00E-04 in PGC; Ripke et al., 2014). We used parallel independent component analysis (Liu et al., 2009) to study multivariate associations of these SNPs with whole-brain gray matter volume (GMV) variation (429655 voxels) in 1401 individuals. The discovery sample consisted of 355 schizophrenia (SZ) patients and 437 healthy controls not having been used in PGC. The components identified in the discovery sample were evaluated in an independent sample (272 SZ patients and 337 controls) for replication. Results: The component number was estimated to be 28 and 65 for the SNP and GMV modality respectively using minimal description length (Rissanen, 1978). One pair of SNP-GMV components were identified to show a significant association passing Bonferroni correction (r = −.16, P = 4.45E-06) which was further replicated when evaluated in the independent sample (r = −.08, P = 4.75E-02), both controlled for diagnosis. The GMV component presented a significant GMV reduction in the inferior parietal and superior temporal regions in the SZ group (P = 8.52E-11) and this reduction was also replicated (P = 2.04E-05). The SNP component included 39 dominant loci residing in chr6:28308034-28684183, echoing the most significant region of PGC 108 SZ relevant regions. Though in the discovery sample no significant group difference was noted in the SNP component loading, it indeed highly correlated (r = .97) with the cumulative polygenic risk score (PRS) for SZ (leveraging the PGC odds ratios) of the same 39 SNPs (Purcell et al., 2009; Ripke et al., 2014). Between the PRS for SZ and GMV component loading, a direct correlation of r = −.14 (P = 9.06E-05) was noted. The higher the PRS for SZ, the lower the GMV. Conclusion: Collectively, we provide evidence that a set of SNPs in 6p22.1, a region previously implicated for SZ susceptibility, likely influence both SZ and gray matter volume in temporal and parietal regions which are among the regions thought to be altered in this illness. The findings emphasize the need for dissecting SZ susceptibility loci to better understand their associations with focal brain measures. Background: Thinning of the cerebral cortex has been reported in schizophrenia, with reductions in frontotemporal regions a common finding. However, considerable heterogeneity across studies has also been reported with little consensus on a typical profile or signature of thinning in the disorder. In addition, reporting conventions tend to highlight regional findings meeting significance thresholds rather than effect sizes reflecting the magnitude of group difference and distribution overlap. Here we present Cohen's d and t test statistics for 14...