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      Microstructural white matter network-connectivity in individuals with psychotic disorder, unaffected siblings and controls

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          Abstract

          Background

          Altered structural network-connectivity has been reported in psychotic disorder but whether these alterations are associated with genetic vulnerability, and/or with phenotypic variation, has been less well examined. This study examined i) whether differences in network-connectivity exist between patients with psychotic disorder, siblings of patients with psychotic disorder and controls, and ii) whether network-connectivity alterations vary with (subclinical) symptomatology.

          Methods

          Network-connectivity measures (global efficiency (GE), density, local efficiency (LE), clustering coefficient (CC)) were derived from diffusion weighted imaging (DWI) and were compared between 85 patients with psychotic disorder, 93 siblings without psychotic disorder and 80 healthy comparison subjects using multilevel regression models. In patients, associations between Positive and Negative Syndrome Scale (PANSS) symptoms and topological measures were examined. In addition, interactions between subclinical psychopathology and sibling/healthy comparison subject status were examined in models of topological measures.

          Results

          While there was no main effect of group with respect to GE, density, LE and CC, siblings had a significantly higher CC compared to patients ( B=0.0039, p=.002). In patients, none of the PANSS symptom domains were significantly associated with any of the four network-connectivity measures. The two-way interaction between group and SIR-r positive score in the model of LE was significant ( χ 2 =6.24, p=.01, df=1). In the model of CC, the interactions between group and respectively SIS-r positive ( χ 2 =5.59, p=.02, df=1) and negative symptom scores ( χ 2 =4.71, p=.03, df=1) were significant. Stratified analysis showed that, in siblings, decreased LE and CC was significantly associated with increased SIS-r positive scores (LE: B=−0.0049, p=.003, CC: B=−0.0066, p=.01) and that decreased CC was significantly associated with increased SIS-r negative scores ( B=−0.012, p=.003). There were no significant interactions between group and SIS-r scores in the models of GE and density.

          Conclusion

          The findings indicate absence of structural network-connectivity alterations in individuals with psychotic disorder and in individuals at higher than average genetic risk for psychotic disorder, in comparison with healthy subjects. The differential subclinical symptom-network connectivity associations in siblings with respect to controls may be a sign of psychosis vulnerability in the siblings.

          Highlights

          • Patients with psychotic disorder had unchanged network efficiency and clustering.

          • Siblings of patients had higher clustering coefficient compared to patients.

          • Lower clustering/efficiency was associated with higher positive symptoms in siblings.

          • Decreased clustering was associated with increased negative symptoms in siblings.

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          Most cited references28

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          The positive and negative syndrome scale (PANSS) for schizophrenia.

          The variable results of positive-negative research with schizophrenics underscore the importance of well-characterized, standardized measurement techniques. We report on the development and initial standardization of the Positive and Negative Syndrome Scale (PANSS) for typological and dimensional assessment. Based on two established psychiatric rating systems, the 30-item PANSS was conceived as an operationalized, drug-sensitive instrument that provides balanced representation of positive and negative symptoms and gauges their relationship to one another and to global psychopathology. It thus constitutes four scales measuring positive and negative syndromes, their differential, and general severity of illness. Study of 101 schizophrenics found the four scales to be normally distributed and supported their reliability and stability. Positive and negative scores were inversely correlated once their common association with general psychopathology was extracted, suggesting that they represent mutually exclusive constructs. Review of five studies involving the PANSS provided evidence of its criterion-related validity with antecedent, genealogical, and concurrent measures, its predictive validity, its drug sensitivity, and its utility for both typological and dimensional assessment.
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            Rich-club organization of the human connectome.

            The human brain is a complex network of interlinked regions. Recent studies have demonstrated the existence of a number of highly connected and highly central neocortical hub regions, regions that play a key role in global information integration between different parts of the network. The potential functional importance of these "brain hubs" is underscored by recent studies showing that disturbances of their structural and functional connectivity profile are linked to neuropathology. This study aims to map out both the subcortical and neocortical hubs of the brain and examine their mutual relationship, particularly their structural linkages. Here, we demonstrate that brain hubs form a so-called "rich club," characterized by a tendency for high-degree nodes to be more densely connected among themselves than nodes of a lower degree, providing important information on the higher-level topology of the brain network. Whole-brain structural networks of 21 subjects were reconstructed using diffusion tensor imaging data. Examining the connectivity profile of these networks revealed a group of 12 strongly interconnected bihemispheric hub regions, comprising the precuneus, superior frontal and superior parietal cortex, as well as the subcortical hippocampus, putamen, and thalamus. Importantly, these hub regions were found to be more densely interconnected than would be expected based solely on their degree, together forming a rich club. We discuss the potential functional implications of the rich-club organization of the human connectome, particularly in light of its role in information integration and in conferring robustness to its structural core.
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              A classification of hand preference by association analysis.

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                Author and article information

                Contributors
                Journal
                Neuroimage Clin
                Neuroimage Clin
                NeuroImage : Clinical
                Elsevier
                2213-1582
                11 July 2019
                2019
                11 July 2019
                : 23
                : 101931
                Affiliations
                [a ]Department of Psychiatry & Neuropsychology, School for Mental Health and Neuroscience, EURON, Maastricht University Medical Centre, PO Box 616, Maastricht 6200, MD, the Netherlands
                [b ]Faculty of Psychology and Educational Sciences, Open University of the Netherlands, Heerlen, the Netherlands
                [c ]King's College London, King's Health Partners, Department of Psychosis Studies, Institute of Psychiatry, London, UK
                [d ]Department of Psychiatry, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
                [e ]Institute for Mental Health Care Eindhoven (GGzE), Eindhoven, the Netherlands
                Author notes
                Article
                S2213-1582(19)30281-5 101931
                10.1016/j.nicl.2019.101931
                6658824
                39ebf15d-a64e-452d-a211-4958948c49e3
                © 2019 The Authors

                This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

                History
                : 23 October 2018
                : 8 June 2019
                : 10 July 2019
                Categories
                Regular Article

                schizophrenia,white matter,connectivity,clustering,efficiency,siblings,ge, global efficiency,le, local efficiency,cc, clustering coefficient,dwi, diffusion weighted imaging,panss, positive and negative syndrome scale,sis-r, structured interview for schizotypy –revised,ap, antipsychotic medication,cidi, composite international diagnostic interview,roi, region of interest,aal, anatomical atlas labeling.

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