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      Human genome-microbiome interaction: metagenomics frontiers for the aetiopathology of autoimmune diseases

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          Abstract

          A short while ago, the human genome and microbiome were analysed simultaneously for the first time as a multi-omic approach. The analyses of heterogeneous population cohorts showed that microbiome components were associated with human genome variations. In-depth analysis of these results reveals that the majority of those relationships are between immune pathways and autoimmune disease-associated microbiome components. Thus, it can be hypothesized that autoimmunity may be associated with homeostatic disequilibrium of the human-microbiome interactome. Further analysis of human genome–human microbiome relationships in disease contexts with tailored systems biology approaches may yield insights into disease pathogenesis and prognosis.

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          Gut-residing segmented filamentous bacteria drive autoimmune arthritis via T helper 17 cells.

          Commensal microbes can have a substantial impact on autoimmune disorders, but the underlying molecular and cellular mechanisms remain largely unexplored. We report that autoimmune arthritis was strongly attenuated in the K/BxN mouse model under germ-free (GF) conditions, accompanied by reductions in serum autoantibody titers, splenic autoantibody-secreting cells, germinal centers, and the splenic T helper 17 (Th17) cell population. Neutralization of interleukin-17 prevented arthritis development in specific-pathogen-free K/BxN mice resulting from a direct effect of this cytokine on B cells to inhibit germinal center formation. The systemic deficiencies of the GF animals reflected a loss of Th17 cells from the small intestinal lamina propria. Introduction of a single gut-residing species, segmented filamentous bacteria, into GF animals reinstated the lamina propria Th17 cell compartment and production of autoantibodies, and arthritis rapidly ensued. Thus, a single commensal microbe, via its ability to promote a specific Th cell subset, can drive an autoimmune disease. Copyright 2010 Elsevier Inc. All rights reserved.
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            Proinflammatory T-cell responses to gut microbiota promote experimental autoimmune encephalomyelitis.

            Although the effects of commensal bacteria on intestinal immune development seem to be profound, it remains speculative whether the gut microbiota influences extraintestinal biological functions. Multiple sclerosis (MS) is a devastating autoimmune disease leading to progressive deterioration of neurological function. Although the cause of MS is unknown, microorganisms seem to be important for the onset and/or progression of disease. However, it is unclear how microbial colonization, either symbiotic or infectious, affects autoimmunity. Herein, we investigate a role for the microbiota during the induction of experimental autoimmune encephalomyelitis (EAE), an animal model for MS. Mice maintained under germ-free conditions develop significantly attenuated EAE compared with conventionally colonized mice. Germ-free animals, induced for EAE, produce lower levels of the proinflammatory cytokines IFN-γ and IL-17A in both the intestine and spinal cord but display a reciprocal increase in CD4(+)CD25(+)Foxp3(+) regulatory T cells (Tregs). Mechanistically, we show that gut dendritic cells from germ-free animals are reduced in the ability to stimulate proinflammatory T cell responses. Intestinal colonization with segmented filamentous bacteria (SFB) is known to promote IL-17 production in the gut; here, we show that SFBs also induced IL-17A-producing CD4(+) T cells (Th17) in the CNS. Remarkably, germ-free animals harboring SFBs alone developed EAE, showing that gut bacteria can affect neurologic inflammation. These findings reveal that the intestinal microbiota profoundly impacts the balance between pro- and antiinflammatory immune responses during EAE and suggest that modulation of gut bacteria may provide therapeutic targets for extraintestinal inflammatory diseases such as MS.
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              Chapter 11: Genome-Wide Association Studies

              Genome-wide association studies (GWAS) have evolved over the last ten years into a powerful tool for investigating the genetic architecture of human disease. In this work, we review the key concepts underlying GWAS, including the architecture of common diseases, the structure of common human genetic variation, technologies for capturing genetic information, study designs, and the statistical methods used for data analysis. We also look forward to the future beyond GWAS.
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                Author and article information

                Journal
                Microb Genom
                Microb Genom
                MGen
                Microbial Genomics
                Microbiology Society
                2057-5858
                April 2017
                26 April 2017
                : 3
                : 4
                : e000112
                Affiliations
                [ 1] Erciyes University School of Medicine , Turkey
                [ 2] Genome and Stem Cell Center (GenKok), Erciyes University , Turkey
                [ 3] Department of Computer Engineering, Erciyes University , Turkey
                Author notes
                *Correspondence: Aycan Gundogdu, agundogdu@ 123456erciyes.edu.tr

                All supporting data, code and protocols have been provided within the article or through supplementary data files.

                Article
                mgen000112
                10.1099/mgen.0.000112
                5506383
                702f9e71-aa0e-47e6-8e36-a2f66ba8ffeb
                © 2017 The Authors

                This is an open access article under the terms of the Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution and reproduction in any medium, provided the original author and source are credited.

                History
                : 27 October 2016
                : 31 March 2017
                Categories
                Review
                Microbe-Niche Interactions
                Pathogenesis
                Custom metadata
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                genome-microbiome interaction,metagenomics,autoimmune disease

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