For Publishers
DiscoveryMetadataPeer reviewHostingPublishing
For Researchers
JoinPublishReviewCollect
Register
Blog
About
Search
Advanced search
My ScienceOpen
Search
For Publishers
For Researchers
Blog
About
83
views
37
references
 Top references
cited by
173
    
0 reviews
 Review
0
comments
 Comment
0
recommends
+1 Recommend
0 collections
    0
    shares
      647
      similar
       All similar
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Complex host genetics influence the microbiome in inflammatory bowel disease.

      Read this article at

      ScienceOpenPublisherPMC
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          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.

          Related collections

          Most cited references37

          • Record: found
          • Abstract: not found
          • Article: not found

          QIIME allows analysis of high-throughput community sequencing data.

          J. Gregory Caporaso, Justin Kuczynski, Jesse Stombaugh … (2010)
          Article 0 comments Cited 6072 times – based on 0 reviews     Review now
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

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

            Shaun Purcell, Benjamin M. Neale, Kathe Todd-Brown … (2007)
            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.
            Article 0 comments Cited 5676 times – based on 0 reviews     Review now
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Diet rapidly and reproducibly alters the human gut microbiome

              Lawrence A David, Corinne F. Maurice, Rachel Carmody … (2013)
              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.
              Article 0 comments Cited 2227 times – based on 0 reviews     Review now
                Bookmark
                All references

                Author and article information

                Journal
                Journal ID (iso-abbrev): Genome Med
                Title: Genome medicine
                Publisher: Springer Science and Business Media LLC
                ISSN: 1756-994X
                ISSN (Print): 1756-994X
                Publication date (Electronic): 2014
                Volume: 6
                Issue: 12
                Affiliations
                [1 ] 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.
                [2 ] Zane Cohen Centre for Digestive Diseases, Mount Sinai Hospital IBD Group, University of Toronto, Toronto, Ontario M5G 1X5 Canada.
                [3 ] Department of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, 9700RB The Netherlands.
                [4 ] Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142 USA.
                [5 ] Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114 USA.
                [6 ] Department of Gastroenterology and Hepatology, University Medical Center Groningen, Groningen, 9700RB The Netherlands ; Department of Genetics, University Medical Center Groningen, Groningen, 9700RB The Netherlands.
                [7 ] Biomedical Informatics and Computational Biology, University of Minnesota, Minneapolis, Minnesota 55455 USA.
                [8 ] Center for Computational and Integrative Biology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA ; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA.
                [9 ] Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA.
                [10 ] Department of Psychiatry, University of Toronto, Toronto, Ontario M5T 1R8 Canada.
                [11 ] Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142 USA ; 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.
                [12 ] Broad Institute of Harvard and MIT, Cambridge, Massachusetts 02142 USA ; Biostatistics Department, Harvard School of Public Health, Boston, Massachusetts 02115 USA.
                [13 ] 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 ; Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts 02114 USA.
                Article
                Publisher Item ID: 107
                DOI: 10.1186/s13073-014-0107-1
                PMC ID: 4292994
                PubMed ID: 25587358
                SO-VID: e8a06a34-98d6-4270-acad-ffe213f51d84
                History

                Data availability:

                Comments

                Comment on this article

                scite_

                Similar content647

                See all similar

                Cited by169

                See all cited by

                Most referenced authors1,609

                See all reference authors