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      Gene-Disease Network Analysis Reveals Functional Modules in Mendelian, Complex and Environmental Diseases

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          Abstract

          Background

          Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.

          Principal Findings

          We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.

          Conclusions

          For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.

          Availability

          The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download.

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          Most cited references58

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          The Universal Protein Resource (UniProt) in 2010

          The primary mission of UniProt is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 3 weeks and can be accessed online for searches or download at http://www.uniprot.org.
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            The global burden of cancer: priorities for prevention

            Despite decreases in the cancer death rates in high-resource countries, such as the USA, the number of cancer cases and deaths is projected to more than double worldwide over the next 20–40 years. Cancer is now the third leading cause of death, with >12 million new cases and 7.6 million cancer deaths estimated to have occurred globally in 2007 (1). By 2030, it is projected that there will be ∼26 million new cancer cases and 17 million cancer deaths per year. The projected increase will be driven largely by growth and aging of populations and will be largest in low- and medium-resource countries. Under current trends, increased longevity in developing countries will nearly triple the number of people who survive to age 65 by 2050. This demographic shift is compounded by the entrenchment of modifiable risk factors such as smoking and obesity in many low-and medium-resource countries and by the slower decline in cancers related to chronic infections (especially stomach, liver and uterine cervix) in economically developing than in industrialized countries. This paper identifies several preventive measures that offer the most feasible approach to mitigate the anticipated global increase in cancer in countries that can least afford it. Foremost among these are the need to strengthen efforts in international tobacco control and to increase the availability of vaccines against hepatitis B and human papilloma virus in countries where they are most needed.
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              A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration.

              Many human inherited neurodegenerative disorders are characterized by loss of balance due to cerebellar Purkinje cell (PC) degeneration. Although the disease-causing mutations have been identified for a number of these disorders, the normal functions of the proteins involved remain, in many cases, unknown. To gain insight into the function of proteins involved in PC degeneration, we developed an interaction network for 54 proteins involved in 23 inherited ataxias and expanded the network by incorporating literature-curated and evolutionarily conserved interactions. We identified 770 mostly novel protein-protein interactions using a stringent yeast two-hybrid screen; of 75 pairs tested, 83% of the interactions were verified in mammalian cells. Many ataxia-causing proteins share interacting partners, a subset of which have been found to modify neurodegeneration in animal models. This interactome thus provides a tool for understanding pathogenic mechanisms common for this class of neurodegenerative disorders and for identifying candidate genes for inherited ataxias.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                14 June 2011
                : 6
                : 6
                : e20284
                Affiliations
                [1 ]Research Programme on Biomedical Informatics (GRIB), IMIM (Hospital del Mar Research Institute), Universitat Pompeu Fabra, Barcelona, Spain
                [2 ]Institute for Computer Science, Ludwig-Maximilians-University Munich, Munich, Germany
                Memorial Sloan Kettering Cancer Center, United States of America
                Author notes

                Conceived and designed the experiments: ABM LIF. Performed the experiments: ABM MB LIF. Analyzed the data: ABM MB LIF FS. Contributed reagents/materials/analysis tools: MB MAM MR. Wrote the paper: ABM MB MR MAM FS LIF.

                [¤]

                Current address: Roche Diagnostics GmbH, Penzberg, Germany

                Article
                PONE-D-11-01121
                10.1371/journal.pone.0020284
                3114846
                21695124
                bb82cc88-4350-489a-b475-46c95f6f1ca6
                Bauer-Mehren et al. 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 author and source are credited.
                History
                : 11 January 2011
                : 27 April 2011
                Page count
                Pages: 13
                Categories
                Research Article
                Biology
                Computational Biology
                Bio-Ontologies
                Biological Data Management
                Systems Biology
                Text Mining
                Genetics
                Genetics of Disease

                Uncategorized
                Uncategorized

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