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A Comparative Genomic Study in Schizophrenic and in Bipolar Disorder Patients, Based on Microarray Expression Profiling Meta-Analysis
Neuropsychiatric Research Laboratory, Department of Clinical Medicine, Örebro University, Örebro; Metabolic Engineering and Bioinformatics Program, Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece; Laboratory of Biotechnology, School of Chemical Engineering, National Technical University of Athens, Athens, Greece. (Experimentell neuropsykiatri)
Metabolic Engineering and Bioinformatics Program, Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
Neuropsychiatric Research Laboratory, Department of Clinical Medicine, Örebro University, Örebro. (Experimentell neuropsykiatri)ORCID iD: 0000-0001-8102-1804
Metabolic Engineering and Bioinformatics Program, Institute of Biology, Medicinal Chemistry and Biotechnology, National Hellenic Research Foundation, Athens, Greece.
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2013 (English)In: Scientific World Journal, ISSN 1537-744X, E-ISSN 1537-744X, Vol. 2013, no 685917, 1-14 p., 685917Article in journal (Refereed) Published
Abstract [en]

Schizophrenia affecting almost 1% and bipolar disorder affecting almost 3%-5% of the global population constitute two severe mental disorders. The catecholaminergic and the serotonergic pathways have been proved to play an important role in the development of schizophrenia, bipolar disorder, and other related psychiatric disorders. The aim of the study was to perform and interpret the results of a comparative genomic profiling study in schizophrenic patients as well as in healthy controls and in patients with bipolar disorder and try to relate and integrate our results with an aberrant amino acid transport through cell membranes. In particular we have focused on genes and mechanisms involved in amino acid transport through cell membranes from whole genome expression profiling data. We performed bioinformatic analysis on raw data derived from four different published studies. In two studies postmortem samples from prefrontal cortices, derived from patients with bipolar disorder, schizophrenia, and control subjects, have been used. In another study we used samples from postmortem orbitofrontal cortex of bipolar subjects while the final study was performed based on raw data from a gene expression profiling dataset in the postmortem superior temporal cortex of schizophrenics. The data were downloaded from NCBI's GEO datasets

Place, publisher, year, edition, pages
New York, USA: Hindawi Publishing Corporation, 2013. Vol. 2013, no 685917, 1-14 p., 685917
National Category
Medical and Health Sciences
Research subject
Biomedicine; Psychiatry
Identifiers
URN: urn:nbn:se:oru:diva-42590DOI: 10.1155/2013/685917ISI: 000316470600001PubMedID: 23554570Scopus ID: 2-s2.0-84876539074OAI: oai:DiVA.org:oru-42590DiVA: diva2:787819
Available from: 2015-02-11 Created: 2015-02-11 Last updated: 2017-12-04Bibliographically approved
In thesis
1. Integration of functional genomics and data mining methodologies in the study of bipolar disorder and schizophrenia
Open this publication in new window or tab >>Integration of functional genomics and data mining methodologies in the study of bipolar disorder and schizophrenia
2016 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Bipolar disorder and schizophrenia are two severe psychiatric disorders characterized by a complex genetic basis, coupled to the influence of environmental factors. In this thesis, functional genomic analysis tools were used for the study of the underlying pathophysiology of these disorders, focusing on gene expression and function on a global scale with the application of high-throughput methods. Datasets from public databases regarding transcriptomic data of postmortem brain and skin fibroblast cells of patients with either schizophrenia or bipolar disorder were analyzed in order to identify differentially expressed genes. In addition, fibroblast cells of bipolar disorder patients obtained from the Biobank of the Neuropsychiatric Research Laboratory of Örebro University were cultured, RNA was extracted and used for microarray analysis. In order to gain deeper insight into the biological mechanisms related to the studied psychiatric disorders, the differentially expressed gene lists were subjected to pathway and target prioritization analysis, using proprietary tools developed by the group of Metabolic Engineering and Bioinformatics, of the National Hellenic Research Foundation, thus indicating various cellular processes as significantly altered. Many of the molecular processes derived from the analysis of the postmortem brain data of schizophrenia and bipolar disorder were also identified in the skin fibroblast cells. Additionally, through the use of machine learning methods, gene expression data from patients with schizophrenia were exploited for the identification of a subset of genes with discriminative ability between schizophrenia and healthy control subjects. Interestingly, a set of genes with high separating efficiency was derived from fibroblast gene expression profiling. This thesis suggests the suitability of skin fibroblasts as a reliable model for the diagnostic evaluation of psychiatric disorders and schizophrenia in particular, through the construction of promising machine-learning based classification models, exploiting gene expression data from peripheral tissues.

Place, publisher, year, edition, pages
Örebro: Örebro university, 2016. 98 p.
Series
Örebro Studies in Medicine, ISSN 1652-4063 ; 153
Keyword
Bipolar Disorder, Schizophrenia, Fibroblasts, DNA Microarrays, Machine Learning, Functional Analysis, Gene Expression, Transcriptomics
National Category
Other Basic Medicine
Identifiers
urn:nbn:se:oru:diva-52644 (URN)978-91-7529-168-0 (ISBN)
Public defence
2016-12-09, Campus USÖ, hörsal C3, Södra Grev Rosengatan 32, Örebro, 09:00 (English)
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Supervisors
Available from: 2016-09-28 Created: 2016-09-28 Last updated: 2017-10-17Bibliographically approved

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