Neuropsychological and neuroimaging underpinnings of schizoaffective disorder: a systematic review.

OBJECTIVES: The neurobiological basis and nosological status of schizoaffective disorder remains elusive and controversial. This study provides a systematic review of neurocognitive and neuroimaging findings in the disorder. METHODS: A comprehensive literature search was conducted via PubMed, ScienceDirect, Scopus and Web of Knowledge (from 1949 to 31st March 2015) using the keyword 'schizoaffective disorder' and any of the following terms: 'neuropsychology', 'cognition', 'structural neuroimaging', 'functional neuroimaging', 'multimodal', 'DTI' and 'VBM'. Only studies that explicitly examined a well defined sample, or subsample, of patients with schizoaffective disorder were included. RESULTS: Twenty-two of 43 neuropsychological and 19 of 51 neuroimaging articles fulfilled inclusion criteria. We found a general trend towards schizophrenia and schizoaffective disorder being related to worse cognitive performance than bipolar disorder. Grey matter volume loss in schizoaffective disorder is also more comparable to schizophrenia than to bipolar disorder which seems consistent across further neuroimaging techniques. CONCLUSIONS: Neurocognitive and neuroimaging abnormalities in schizoaffective disorder resemble more schizophrenia than bipolar disorder. This is suggestive for schizoaffective disorder being a subtype of schizophrenia or being part of the continuum spectrum model of psychosis, with schizoaffective disorder being more skewed towards schizophrenia than bipolar disorder.

Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder.

OBJECTIVE: Brain structural changes in schizoaffective disorder, and how far they resemble those seen in schizophrenia and bipolar disorder, have only been studied to a limited extent. METHOD: Forty-five patients meeting DSM-IV and RDC criteria for schizoaffective disorder, groups of patients with 45 matched schizophrenia and bipolar disorder, and 45 matched healthy controls were examined using voxel-based morphometry (VBM). RESULTS: Analyses comparing each patient group with the healthy control subjects found that the patients with schizoaffective disorder and the patients with schizophrenia showed widespread and overlapping areas of significant volume reduction, but the patients with bipolar disorder did not. A subsequent analysis compared the combined group of patients with the controls followed by extraction of clusters. In regions where the patients differed significantly from the controls, no significant differences in mean volume between patients with schizoaffective disorder and patients with schizophrenia in any of five regions of volume reduction were found, but mean volumes in the patients with bipolar disorder were significantly smaller in three of five. CONCLUSION: The findings provide evidence that, in terms of structural gray matter brain abnormality, schizoaffective disorder resembles schizophrenia more than bipolar disorder.

Association of formal thought disorder in schizophrenia with structural brain abnormalities in language-related cortical regions.

BACKGROUND: Formal thought disorder (FTD) in schizophrenia has been found to be associated with volume reductions in the left superior temporal cortex. However, there have been negative findings and some studies have also found associations in other cortical regions. METHOD: Fifty-one schizophrenic patients were evaluated for presence of FTD with the Thought, Language and Communication (TLC) scale and underwent whole-brain structural MRI using optimized voxel-based morphometry (VBM). Fifty-nine matched healthy controls were also scanned. RESULTS: Compared to 31 patients without FTD (global TLC rating 0 or 1), 20 patients with FTD (global TLC rating 2-5) showed clusters of volume reduction in the medial frontal and orbitofrontal cortex bilaterally, and in two left-sided areas approximating to Broca's and Wernicke's areas. The pattern of FTD-associated volume reductions was largely different from that found in a comparison between the healthy controls and the patients without FTD. Analysis of correlations within regions-of-interest based on the above clusters indicated that the 'fluent disorganization' component of FTD was correlated with volume reductions in both Broca's and Wernicke's areas, whereas poverty of content of speech was correlated with reductions in the medial frontal/orbitofrontal cortex. CONCLUSIONS: The findings point to a relationship between FTD in schizophrenia and structural brain pathology in brain areas involved in language and executive function.

Medial prefrontal cortex pathology in schizophrenia as revealed by convergent findings from multimodal imaging.

Neuroimaging studies have found evidence of altered brain structure and function in schizophrenia, but have had complex findings regarding the localization of abnormality. We applied multimodal imaging (voxel-based morphometry (VBM), functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) combined with tractography) to 32 chronic schizophrenic patients and matched healthy controls. At a conservative threshold of P=0.01 corrected, structural and functional imaging revealed overlapping regions of abnormality in the medial frontal cortex. DTI found that white matter abnormality predominated in the anterior corpus callosum, and analysis of the anatomical connectivity of representative seed regions again implicated fibres projecting to the medial frontal cortex. There was also evidence of convergent abnormality in the dorsolateral prefrontal cortex, although here the laterality was less consistent across techniques. The medial frontal region identified by these three imaging techniques corresponds to the anterior midline node of the default mode network, a brain system which is believed to support internally directed thought, a state of watchfulness, and/or the maintenance of one's sense of self, and which is of considerable current interest in neuropsychiatric disorders.

Characterizing brain anatomical connections using diffusion weighted MRI and graph theory.

A new methodology based on Diffusion Weighted Magnetic Resonance Imaging (DW-MRI) and Graph Theory is presented for characterizing the anatomical connections between brain gray matter areas. In a first step, brain voxels are modeled as nodes of a non-directed graph in which the weight of an arc linking two neighbor nodes is assumed to be proportional to the probability of being connected by nervous fibers. This probability is estimated by means of probabilistic tissue segmentation and intravoxel white matter orientational distribution function, obtained from anatomical MRI and DW-MRI, respectively. A new tractography algorithm for finding white matter routes is also introduced. This algorithm solves the most probable path problem between any two nodes, leading to the assessment of probabilistic brain anatomical connection maps. In a second step, for assessing anatomical connectivity between K gray matter structures, the previous graph is redefined as a K+1 partite graph by partitioning the initial nodes set in K non-overlapped gray matter subsets and one subset clustering the remaining nodes. Three different measures are proposed for quantifying anatomical connections between any pair of gray matter subsets: Anatomical Connection Strength (ACS), Anatomical Connection Density (ACD) and Anatomical Connection Probability (ACP). This methodology was applied to both artificial and actual human data. Results show that nervous fiber pathways between some regions of interest were reconstructed correctly. Additionally, mean connectivity maps of ACS, ACD and ACP between 71 gray matter structures for five healthy subjects are presented.