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      A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

      research-article
      International Multiple Sclerosis Genetics Consortium
      Sergio.Baranzini@ucsf.edu
      1
      Nature Communications
      Nature Publishing Group UK
      Cellular signalling networks, Genome informatics, Genome-wide association studies, Multiple sclerosis

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          Abstract

          Genome-wide association studies (GWAS) have identified more than 50,000 unique associations with common human traits. While this represents a substantial step forward, establishing the biology underlying these associations has proven extremely difficult. Even determining which cell types and which particular gene(s) are relevant continues to be a challenge. Here, we conduct a cell-specific pathway analysis of the latest GWAS in multiple sclerosis (MS), which had analyzed a total of 47,351 cases and 68,284 healthy controls and found more than 200 non-MHC genome-wide associations. Our analysis identifies pan immune cell as well as cell-specific susceptibility genes in T cells, B cells and monocytes. Finally, genotype-level data from 2,370 patients and 412 controls is used to compute intra-individual and cell-specific susceptibility pathways that offer a biological interpretation of the individual genetic risk to MS. This approach could be adopted in any other complex trait for which genome-wide data is available.

          Abstract

          Genome-wide association studies (GWAS) have so far uncovered more than 200 loci for multiple sclerosis (MS). Here, the authors integrate data from various sources for a cell type-specific pathway analysis of MS GWAS results that specifically highlights the involvement of the immune system in disease pathogenesis.

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          Most cited references30

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          CD28/B7 system of T cell costimulation.

          T cells play a central role in the initiation and regulation of the immune response to antigen. Both the engagement of the TCR with MHC/Ag and a second signal are needed for the complete activation of the T cell. The CD28/B7 receptor/ligand system is one of the dominant costimulatory pathways. Interruption of this signaling pathway with CD28 antagonists not only results in the suppression of the immune response, but in some cases induces antigen-specific tolerance. However, the CD28/B7 system is increasingly complex due to the identification of multiple receptors and ligands with positive and negative signaling activities. This review summarizes the state of CD28/B7 immunobiology both in vitro and in vivo; summarizes the many experiments that have led to our current understanding of the participants in this complex receptor/ligand system; and illustrates the current models for CD28/B7-mediated T cell and B cell regulation. It is our hope and expectation that this review will provoke additional research that will unravel this important, yet complex, signaling pathway.
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            Prioritizing candidate disease genes by network-based boosting of genome-wide association data.

            Network "guilt by association" (GBA) is a proven approach for identifying novel disease genes based on the observation that similar mutational phenotypes arise from functionally related genes. In principle, this approach could account even for nonadditive genetic interactions, which underlie the synergistic combinations of mutations often linked to complex diseases. Here, we analyze a large-scale, human gene functional interaction network (dubbed HumanNet). We show that candidate disease genes can be effectively identified by GBA in cross-validated tests using label propagation algorithms related to Google's PageRank. However, GBA has been shown to work poorly in genome-wide association studies (GWAS), where many genes are somewhat implicated, but few are known with very high certainty. Here, we resolve this by explicitly modeling the uncertainty of the associations and incorporating the uncertainty for the seed set into the GBA framework. We observe a significant boost in the power to detect validated candidate genes for Crohn's disease and type 2 diabetes by comparing our predictions to results from follow-up meta-analyses, with incorporation of the network serving to highlight the JAK-STAT pathway and associated adaptors GRB2/SHC1 in Crohn's disease and BACH2 in type 2 diabetes. Consideration of the network during GWAS thus conveys some of the benefits of enrolling more participants in the GWAS study. More generally, we demonstrate that a functional network of human genes provides a valuable statistical framework for prioritizing candidate disease genes, both for candidate gene-based and GWAS-based studies.
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              • Article: not found

              CD40 and CD154 in cell-mediated immunity.

              CD40-CD154-mediated contact-dependent signals between B and T cells are required for the generation of thymus dependent (TD) humoral immune responses. CD40-CD154 interactions are however also important in many other cell systems. CD40 is expressed by a large variety of cell types other than B cells, and these include dendritic cells, follicular dendritic cells, monocytes, macrophages, mast cells, fibroblasts, and endothelial cells. CD40- and CD154-knockout mice and antibodies to CD40 and CD154 have helped to elucidate the role of the CD40-CD154 system in immune responses. Recently published studies indicate that CD40-CD154 interactions can influence T cell priming and T cell-mediated effector functions; they can also upregulate costimulatory molecules and activate macrophages, NK cells, and endothelia as well as participate in organ-specific autoimmune disease, graft rejection, and even atherosclerosis. This review focuses on the role of the CD40-CD154 system in the regulation of many newly discovered functions important in inflammation and cell-mediated immunity.
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                Author and article information

                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                20 May 2019
                20 May 2019
                2019
                : 10
                : 2236
                Affiliations
                [1 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Weill Institute for Neurosciences, Department of Neurology, , University of California San Francisco, ; San Francisco, CA 94158 USA
                [2 ]ISNI 000000041936754X, GRID grid.38142.3c, Systems Biology and Computer Science Program, Ann Romney Center for Neurological Diseases, Department of Neurology, and Division of Genetics, Department of Medicine, Brigham & Women’s Hospital, , Harvard Medical School, ; Boston, MA 02115 USA
                [3 ]ISNI 0000 0001 2341 2786, GRID grid.116068.8, Broad Institute of Harvard University and Massachusetts Institute of Technology, ; Cambridge, MA 02142 USA
                [4 ]ISNI 0000000419368710, GRID grid.47100.32, Departments of Neurology, , Yale School of Medicine, ; 300 George St, New Haven, CT 06511 USA
                [5 ]ISNI 0000000419368710, GRID grid.47100.32, Department of Genetics, , Yale School of Medicine, ; 300 George St, New Haven, CT 06511 USA
                [6 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Institute of Clinical Medicine, University of Oslo, ; Oslo, 0318 Norway
                [7 ]ISNI 0000 0004 0389 8485, GRID grid.55325.34, Department of Neurology, , Oslo University Hospital, ; Oslo, 0424 Norway
                [8 ]ISNI 0000 0004 1936 8606, GRID grid.26790.3a, John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, ; Miami, FL 33136 USA
                [9 ]ISNI 0000 0004 1936 8606, GRID grid.26790.3a, Dr. John T. Macdonald Foundation Department of Human Genetics, , University of Miami, Miller School of Medicine, ; Miami, FL 33136 USA
                [10 ]ISNI 0000000123222966, GRID grid.6936.a, Department of Neurology, Klinikum rechts der Isar, School of Medicine, , Technical University of Munich, ; 81675 Munich, Germany
                [11 ]GRID grid.452617.3, Munich Cluster for Systems Neurology (SyNergy), ; 81377 Munich, Germany
                [12 ]Division of Epidemiology, School of Public HealthUniversity of California, 324 Stanley Hall, MC#3220, Berkeley, CA 94720 USA
                [13 ]Department of Mechanical, Electronics and Chemical Engineering, Oslo Metropolitan University, Oslo, 0167 Norway
                [14 ]ISNI 0000 0004 1762 5736, GRID grid.8982.b, Section of Biostatistics, Neurophyisiology and Psychiatry, Unit of medical and genomic statistics, , Universita of Pavia, ; Pavia, 27100 Italy
                [15 ]ISNI 0000 0004 1757 2822, GRID grid.4708.b, Department of Biomedical Sciences for Health, , University of Milan, ; Milan, 20133 Italy
                [16 ]ISNI 0000 0004 1766 7370, GRID grid.419557.b, MS Research Unit and Department of Neurology, , IRCCS Policlinico San Donato, San Donato Milanese, ; Milan, 20097 Italy
                [17 ]ISNI 0000 0001 0436 7430, GRID grid.452919.2, Faculty of Medicine, Westmead Clinical School, , The Westmead Institute for Medical Research, ; Sydney, NSW 2145 Australia
                [18 ]ISNI 0000 0001 2164 3847, GRID grid.67105.35, Department of Quantitative and Population Health Sciences, , School of Medicine, Case Western Reserve University, ; Cleveland, OH 44106 USA
                [19 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, Institute of Health and Society, University of Oslo, ; Oslo, 0318 Norway
                [20 ]Servei de Neurologia-Neuroimmunologia. Centre d’Esclerosi Múltiple de Catalunya (Cemcat), Institut de Recerca Vall d’Hebron (VHIR), Hospital Universitari Vall d’Hebron, Universitat Autònoma de Barcelona, Barcelona, 08035 Spain
                [21 ]ISNI 0000000417581884, GRID grid.18887.3e, Department of Neurology, , San Raffaele Scientific Institute, ; Milan, 20132 Italy
                [22 ]Department of Health Sciences, UPO University, Novara, 28100 Italy
                [23 ]ISNI 0000000121885934, GRID grid.5335.0, Department of Clinical Neurosciences. Neurology Unit, , University of Cambridge, ; Cambridge, CB2 1QW UK
                [24 ]ISNI 0000 0001 2292 3357, GRID grid.14848.31, Faculté de médecine, MS Clinic Centre Hospitalier de l’, , Université de Montréal. Université de Montréal Montreal, ; Montreal, QC H3A 1G1 Canada
                [25 ]GRID grid.411299.6, Department of Neurology, Laboratory of Neurogenetics, , University of Thessaly, University Hospital of Larissa, ; Larissa, 41223 Greece
                [26 ]ISNI 0000 0001 2150 9058, GRID grid.411439.a, Department of Neurology, , University Hopital Pitié-Salpêtrière, ; Paris, 75013 France
                [27 ]UMR 1127, Sorbonne-Université, INSERM, University Hopital Pitié-Salpêtrière, Paris, 75013 France
                [28 ]ISNI 0000 0001 0668 7884, GRID grid.5596.f, KU Leuven Department of Neurosciences, Laboratory for Neuroimmunology, ; Leuven, 3000 Belgium
                [29 ]GRID grid.4817.a, Université de Nantes, INSERM, Centre de Recherche en Transplantation et Immunologie, UMR 1064, ATIP-Avenir, Equipe 5, ; Nantes, F-44093 France
                [30 ]ISNI 0000 0004 0472 0371, GRID grid.277151.7, CHU de Nantes, INSERM, CIC 1413, Pôle Hospitalo-Universitaire 11: Santé Publique, Clinique des données, ; Nantes, F-44093 France
                [31 ]ISNI 0000000121167908, GRID grid.6603.3, Department of Neurology, , Medical School, University of Cyprus, ; Nicosia, 587G+X2 Cyprus
                [32 ]ISNI 0000 0004 0415 6205, GRID grid.9757.c, Institute for Science & Technology in Medicine, Keele University, ; Keele, ST5 5GB UK
                [33 ]ISNI 000000040459992X, GRID grid.5645.2, Department of Neurology, , Erasmus MC Dr Molewaterplein 40, ; Rotterdam, 3015 GD The Netherlands
                [34 ]ISNI 000000040459992X, GRID grid.5645.2, Department of Immunology, , Erasmus MC, ; Rotterdam, 3015 GD The Netherlands
                [35 ]ISNI 0000 0000 9100 9940, GRID grid.411798.2, First Faculty of Medicine, Department of Neurology and Center of Clinical Neuroscience, , Charles University and General University Hospital, ; Prague, 3CFG+RJ Czech Republic
                [36 ]ISNI 0000 0001 2242 4849, GRID grid.177174.3, Department of Neurology, , Kyushu University, ; Kyushu, 812-0053 Japan
                [37 ]GRID grid.439752.e, Royal Stoke MS Centre of Excellence, University Hospital North Midlands, ; Stoke-on-Trent, ST4 6QG UK
                [38 ]ISNI 0000 0000 8988 2476, GRID grid.11598.34, Department of Neurology, , Medical University of Graz, ; Graz, A-8036 Austria
                [39 ]ISNI 0000 0004 1937 0626, GRID grid.4714.6, Department of Clinical Neuroscience and Center for Molecular Medicine, , Karolinska Institutet, ; Stockholm, 17176 Sweden
                [40 ]GRID grid.410607.4, Department of Neurology, , University Medical Center of the Johannes Gutenberg University Mainz, ; Mainz, 55131 Germany
                [41 ]ISNI 0000 0001 0057 2672, GRID grid.4562.5, Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, , University of Lübeck, ; Lübeck, 23562 Germany
                [42 ]ISNI 0000 0004 1937 0650, GRID grid.7400.3, Neuroimmunology and MS Research (nims), Department of Neurology, University Zurich, ; Zürich, 8006 Switzerland
                [43 ]ISNI 0000 0001 0674 042X, GRID grid.5254.6, Department of Neurology, section 2082, Rigshospitalet, Danish Multiple Sclerosis Center, , University of Copenhagen, ; Copenhagen, 2100 Denmark
                [44 ]ISNI 0000 0004 0410 2071, GRID grid.7737.4, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, ; Helsinki, FIN-00014 Finland
                [45 ]ISNI 000000041936754X, GRID grid.38142.3c, Harvard University, Center for Human Genetic Research, ; Boston, MA 02115 USA
                [46 ]ISNI 0000000121901201, GRID grid.83440.3b, UK Dementia Research Institute at University College London, ; London, WC1E6BT UK
                [47 ]ISNI 0000 0004 1936 826X, GRID grid.1009.8, Menzies Institute for Medical Research, University of Tasmania, ; Hobart, TAS 7000 Australia
                [48 ]ISNI 0000000121885934, GRID grid.5335.0, Department of Clinical Neurosciences, Cambridge Biomedical Campus, , University of Cambridge, ; Cambridge, CB2 0QQ UK
                [49 ]ISNI 0000 0001 2285 2675, GRID grid.239585.0, Department of Neurology, Center for Translational and Computational Neuroimmunology and Multiple Sclerosis Center, , Columbia University Medical Center, ; New York, NY 10032 USA
                [50 ]ISNI 0000 0001 2297 6811, GRID grid.266102.1, Bakar Institute for Computational Health Science. University of California San Francisco, ; San Francisco, CA 94158 USA
                Article
                9773
                10.1038/s41467-019-09773-y
                6527683
                31110181
                3b1a8ffd-b916-43af-8030-c0edd907bc55
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 August 2018
                : 26 March 2019
                Categories
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                Custom metadata
                © The Author(s) 2019

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                cellular signalling networks,genome informatics,genome-wide association studies,multiple sclerosis

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