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      Co-expression network of neural-differentiation genes shows specific pattern in schizophrenia

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          Schizophrenia is a neurodevelopmental disorder with genetic and environmental factors contributing to its pathogenesis, although the mechanism is unknown due to the difficulties in accessing diseased tissue during human neurodevelopment. The aim of this study was to find neuronal differentiation genes disrupted in schizophrenia and to evaluate those genes in post-mortem brain tissues from schizophrenia cases and controls.


          We analyzed differentially expressed genes (DEG), copy number variation (CNV) and differential methylation in human induced pluripotent stem cells (hiPSC) derived from fibroblasts from one control and one schizophrenia patient and further differentiated into neuron (NPC). Expression of the DEG were analyzed with microarrays of post-mortem brain tissue (frontal cortex) cohort of 29 schizophrenia cases and 30 controls. A Weighted Gene Co-expression Network Analysis (WGCNA) using the DEG was used to detect clusters of co-expressed genes that werenon-conserved between adult cases and controls brain samples.


          We identified methylation alterations potentially involved with neuronal differentiation in schizophrenia, which displayed an over-representation of genes related to chromatin remodeling complex (adjP = 0.04). We found 228 DEG associated with neuronal differentiation. These genes were involved with metabolic processes, signal transduction, nervous system development, regulation of neurogenesis and neuronal differentiation. Between adult brain samples from cases and controls there were 233 DEG, with only four genes overlapping with the 228 DEG, probably because we compared single cell to tissue bulks and more importantly, the cells were at different stages of development. The comparison of the co-expressed network of the 228 genes in adult brain samples between cases and controls revealed a less conserved module enriched for genes associated with oxidative stress and negative regulation of cell differentiation.


          This study supports the relevance of using cellular approaches to dissect molecular aspects of neurogenesis with impact in the schizophrenic brain. We showed that, although generated by different approaches, both sets of DEG associated to schizophrenia were involved with neocortical development. The results add to the hypothesis that critical metabolic changes may be occurring during early neurodevelopment influencing faulty development of the brain and potentially contributing to further vulnerability to the illness.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12920-015-0098-9) contains supplementary material, which is available to authorized users.

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          Most cited references 71

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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              Cancer metabolism has long been equated with aerobic glycolysis, seen by early biochemists as primitive and inefficient. Despite these early beliefs, the metabolic signatures of cancer cells are not passive responses to damaged mitochondria but result from oncogene-directed metabolic reprogramming required to support anabolic growth. Recent evidence suggests that metabolites themselves can be oncogenic by altering cell signaling and blocking cellular differentiation. No longer can cancer-associated alterations in metabolism be viewed as an indirect response to cell proliferation and survival signals. We contend that altered metabolism has attained the status of a core hallmark of cancer. Copyright © 2012 Elsevier Inc. All rights reserved.

                Author and article information

                BMC Med Genomics
                BMC Med Genomics
                BMC Medical Genomics
                BioMed Central (London )
                16 May 2015
                16 May 2015
                : 8
                [ ]LIM23 (Medical Investigation Laboratory 23), University of Sao Paulo Medical School (USP), São Paulo, SP Brazil
                [ ]Institute of Psychiatry-University of Sao Paulo, Medical School (FMUSP), São Paulo, SP Brazil
                [ ]Hospital Israelita Albert Einstein, São Paulo, Brazil
                [ ]Post-graduation Program Institute of Mathematics and Statistics, University of Sao Paulo, São Paulo, SP Brazil
                [ ]Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
                [ ]Department of Psychiatry, Federal University of Rio Grande do Sul, Porto Alegre, Brazil
                [ ]Institute of Biosciences, University of São Paulo, São Paulo, SP Brazil
                [ ]International Research Center-AC Camargo Cancer Center, São Paulo, Brazil
                [ ]Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal
                [ ]ICVS/3B’s-PT Government Associate Laboratory, Braga, Guimarães Portugal
                [ ]D’Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
                [ ]Department of Psychiatry, University of Sao Paulo, Medical School (FMUSP), Rua Dr Ovídio Pires de Campos,785-CEP 05403-010, São Paulo, SP Caixa Postal n 3671 Brazil
                [ ]National Institute of Developmental Psychiatry for Children and Adolescents, CNPq, São Paulo, SP Brazil
                © Maschietto et al.; licensee BioMed Central. 2015

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

                Research Article
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                oxidative stress, module analyses, neuronal differentiation, gene network, schizophrenia


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