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      Complex host genetics influence the microbiome in inflammatory bowel disease

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          Abstract

          Background

          Human genetics and host-associated microbial communities have been associated independently with a wide range of chronic diseases. One of the strongest associations in each case is inflammatory bowel disease (IBD), but disease risk cannot be explained fully by either factor individually. Recent findings point to interactions between host genetics and microbial exposures as important contributors to disease risk in IBD. These include evidence of the partial heritability of the gut microbiota and the conferral of gut mucosal inflammation by microbiome transplant even when the dysbiosis was initially genetically derived. Although there have been several tests for association of individual genetic loci with bacterial taxa, there has been no direct comparison of complex genome-microbiome associations in large cohorts of patients with an immunity-related disease.

          Methods

          We obtained 16S ribosomal RNA (rRNA) gene sequences from intestinal biopsies as well as host genotype via Immunochip in three independent cohorts totaling 474 individuals. We tested for correlation between relative abundance of bacterial taxa and number of minor alleles at known IBD risk loci, including fine mapping of multiple risk alleles in the Nucleotide-binding oligomerization domain-containing protein 2 ( NOD2) gene exon. We identified host polymorphisms whose associations with bacterial taxa were conserved across two or more cohorts, and we tested related genes for enrichment of host functional pathways.

          Results

          We identified and confirmed in two cohorts a significant association between NOD2 risk allele count and increased relative abundance of Enterobacteriaceae, with directionality of the effect conserved in the third cohort. Forty-eight additional IBD-related SNPs have directionality of their associations with bacterial taxa significantly conserved across two or three cohorts, implicating genes enriched for regulation of innate immune response, the JAK-STAT cascade, and other immunity-related pathways.

          Conclusions

          These results suggest complex interactions between genetically altered host functional pathways and the structure of the microbiome. Our findings demonstrate the ability to uncover novel associations from paired genome-microbiome data, and they suggest a complex link between host genetics and microbial dysbiosis in subjects with IBD across independent cohorts.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13073-014-0107-1) contains supplementary material, which is available to authorized users.

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          Most cited references37

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          QIIME allows analysis of high-throughput community sequencing data.

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            PLINK: a tool set for whole-genome association and population-based linkage analyses.

            Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.
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              Diet rapidly and reproducibly alters the human gut microbiome

              Long-term diet influences the structure and activity of the trillions of microorganisms residing in the human gut 1–5 , but it remains unclear how rapidly and reproducibly the human gut microbiome responds to short-term macronutrient change. Here, we show that the short-term consumption of diets composed entirely of animal or plant products alters microbial community structure and overwhelms inter-individual differences in microbial gene expression. The animal-based diet increased the abundance of bile-tolerant microorganisms (Alistipes, Bilophila, and Bacteroides) and decreased the levels of Firmicutes that metabolize dietary plant polysaccharides (Roseburia, Eubacterium rectale, and Ruminococcus bromii). Microbial activity mirrored differences between herbivorous and carnivorous mammals 2 , reflecting trade-offs between carbohydrate and protein fermentation. Foodborne microbes from both diets transiently colonized the gut, including bacteria, fungi, and even viruses. Finally, increases in the abundance and activity of Bilophila wadsworthia on the animal-based diet support a link between dietary fat, bile acids, and the outgrowth of microorganisms capable of triggering inflammatory bowel disease 6 . In concert, these results demonstrate that the gut microbiome can rapidly respond to altered diet, potentially facilitating the diversity of human dietary lifestyles.
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                Author and article information

                Contributors
                dknights@umn.edu
                xavier@molbio.mgh.harvard.edu
                r.k.weersma@umcg.nl
                dgevers@broadinstitute.org
                gerard.dijkstra@umcg.nl
                hhuang@atgu.mgh.harvard.edu
                atyler@mtsinai.on.ca
                s.van.sommeren@umcg.nl
                imhann@broadinstitute.org
                JStempak@mtsinai.on.ca
                huan0764@umn.edu
                vanga015@umn.edu
                algh0022@umn.edu
                CNRUSSELL@partners.org
                JSAUK@partners.org
                Jo.Knight@camh.ca
                mjdaly@atgu.mgh.harvard.edu
                chuttenh@hsph.harvard.edu
                xavier@molbio.mgh.harvard.edu
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                2 December 2014
                2 December 2014
                2014
                : 6
                : 12
                : 107
                Affiliations
                [ ]Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota 55455 USA
                [ ]Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142 USA
                [ ]Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA
                [ ]Biotechnology Institute, University of Minnesota, St. Paul, Minnesota 55108 USA
                [ ]Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital IBD Group, University of Toronto, Toronto, Ontario M5G 1X5 Canada
                [ ]Department of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, 9700RB The Netherlands
                [ ]Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114 USA
                [ ]Department of Genetics, University Medical Center Groningen, Groningen, 9700RB The Netherlands
                [ ]Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 USA
                [ ]Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA
                [ ]Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8 Canada
                [ ]Department of Medicine, Analytic and Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA
                [ ]Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142 USA
                [ ]Biostatistics Department, Harvard School of Public Health, Boston, Massachusetts 02115 USA
                Article
                107
                10.1186/s13073-014-0107-1
                4292994
                25587358
                e8a06a34-98d6-4270-acad-ffe213f51d84
                © Knights et al.; licensee BioMed Central. 2014

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 2 September 2014
                : 13 November 2014
                Categories
                Research
                Custom metadata
                © The Author(s) 2014

                Molecular medicine
                Molecular medicine

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