Compositional and genetic alterations in Graves’ disease gut microbiome reveal specific diagnostic biomarkers View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2021-06-02

AUTHORS

Qiyun Zhu, Qiangchuan Hou, Shi Huang, Qianying Ou, Dongxue Huo, Yoshiki Vázquez-Baeza, Chaoping Cen, Victor Cantu, Mehrbod Estaki, Haibo Chang, Pedro Belda-Ferre, Ho-Cheol Kim, Kaining Chen, Rob Knight, Jiachao Zhang

ABSTRACT

Graves’ Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves’ disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson’s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases. More... »

PAGES

3399-3411

References to SciGraph publications

  • 2012-09-26. A metagenome-wide association study of gut microbiota in type 2 diabetes in NATURE
  • 2016-02-08. Intestinal Microbiota Distinguish Gout Patients from Healthy Humans in SCIENTIFIC REPORTS
  • 2020-03-11. Microbiome analyses of blood and tissues suggest cancer diagnostic approach in NATURE
  • 2018-11-26. Tongue coating microbiome as a potential biomarker for gastritis including precancerous cascade in PROTEIN & CELL
  • 2018-10-30. Species-level functional profiling of metagenomes and metatranscriptomes in NATURE METHODS
  • 2012-12-05. Genomic variation landscape of the human gut microbiome in NATURE
  • 2019-06-20. Establishing microbial composition measurement standards with reference frames in NATURE COMMUNICATIONS
  • 2018-02-28. Environment dominates over host genetics in shaping human gut microbiota in NATURE
  • 2020-05-19. Precise phylogenetic analysis of microbial isolates and genomes from metagenomes using PhyloPhlAn 3.0 in NATURE COMMUNICATIONS
  • 2015-08-11. Short-chain fatty acids in control of body weight and insulin sensitivity in NATURE REVIEWS ENDOCRINOLOGY
  • 2014-03-03. Kraken: ultrafast metagenomic sequence classification using exact alignments in GENOME BIOLOGY
  • 2020-07-03. Development of AI-based pathology biomarkers in gastrointestinal and liver cancer in NATURE REVIEWS GASTROENTEROLOGY & HEPATOLOGY
  • 2017-01-03. Faecalibacterium prausnitzii: from microbiology to diagnostics and prognostics in THE ISME JOURNAL: MULTIDISCIPLINARY JOURNAL OF MICROBIAL ECOLOGY
  • 2014-06-27. Gut Microbe Analysis Between Hyperthyroid and Healthy Individuals in CURRENT MICROBIOLOGY
  • 2019-03-27. Structural variation in the gut microbiome associates with host health in NATURE
  • 2019-05-22. Antibiotics, gut microbiota, and Alzheimer’s disease in JOURNAL OF NEUROINFLAMMATION
  • 2020-03-23. Dissection of the mutation accumulation process during bacterial range expansions in BMC GENOMICS
  • 2019-07-17. Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences in NATURE COMMUNICATIONS
  • 2014-07-23. Alterations of the human gut microbiome in liver cirrhosis in NATURE
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/s41396-021-01016-7

    DOI

    http://dx.doi.org/10.1038/s41396-021-01016-7

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1138518234

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/34079079


    Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
    Incoming Citations Browse incoming citations for this publication using opencitations.net

    JSON-LD is the canonical representation for SciGraph data.

    TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

    [
      {
        "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
        "about": [
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/06", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Biological Sciences", 
            "type": "DefinedTerm"
          }, 
          {
            "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0604", 
            "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
            "name": "Genetics", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Biomarkers", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Feces", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Gastrointestinal Microbiome", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Graves Disease", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Humans", 
            "type": "DefinedTerm"
          }, 
          {
            "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
            "name": "Metagenome", 
            "type": "DefinedTerm"
          }
        ], 
        "author": [
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhu", 
            "givenName": "Qiyun", 
            "id": "sg:person.011522220701.89", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011522220701.89"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Hubei Provincial Engineering and Technology Research Center for Food Ingredients, Hubei University of Arts and Science, Xiangyang, Hubei province, China", 
              "id": "http://www.grid.ac/institutes/grid.412979.0", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China", 
                "Hubei Provincial Engineering and Technology Research Center for Food Ingredients, Hubei University of Arts and Science, Xiangyang, Hubei province, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Hou", 
            "givenName": "Qiangchuan", 
            "id": "sg:person.01265705310.30", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265705310.30"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Huang", 
            "givenName": "Shi", 
            "id": "sg:person.01074626724.22", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074626724.22"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.459560.b", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Ou", 
            "givenName": "Qianying", 
            "id": "sg:person.016106134747.41", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016106134747.41"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, Haikou, China", 
              "id": "http://www.grid.ac/institutes/None", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Huo", 
            "givenName": "Dongxue", 
            "id": "sg:person.0620460120.04", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0620460120.04"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "V\u00e1zquez-Baeza", 
            "givenName": "Yoshiki", 
            "id": "sg:person.01113460501.49", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113460501.49"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.459560.b", 
              "name": [
                "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cen", 
            "givenName": "Chaoping", 
            "id": "sg:person.015722260216.20", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015722260216.20"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Bioengineering, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Bioengineering, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Cantu", 
            "givenName": "Victor", 
            "id": "sg:person.016507333101.73", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016507333101.73"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Estaki", 
            "givenName": "Mehrbod", 
            "id": "sg:person.0715356340.58", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715356340.58"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "School of Food Science and Engineering, Hainan University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.428986.9", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chang", 
            "givenName": "Haibo", 
            "id": "sg:person.016227240545.39", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016227240545.39"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Belda-Ferre", 
            "givenName": "Pedro", 
            "id": "sg:person.01255245123.96", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01255245123.96"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Scalable Knowledge Intelligence, IBM Research-Almaden, San Jose, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.481551.c", 
              "name": [
                "Scalable Knowledge Intelligence, IBM Research-Almaden, San Jose, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Kim", 
            "givenName": "Ho-Cheol", 
            "id": "sg:person.01260166777.63", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260166777.63"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China", 
              "id": "http://www.grid.ac/institutes/grid.459560.b", 
              "name": [
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Chen", 
            "givenName": "Kaining", 
            "id": "sg:person.07532351303.03", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07532351303.03"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA", 
              "id": "http://www.grid.ac/institutes/grid.266100.3", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
                "Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA", 
                "Department of Bioengineering, University of California San Diego, La Jolla, CA, USA", 
                "Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Knight", 
            "givenName": "Rob", 
            "id": "sg:person.016311745377.96", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96"
            ], 
            "type": "Person"
          }, 
          {
            "affiliation": {
              "alternateName": "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, Haikou, China", 
              "id": "http://www.grid.ac/institutes/None", 
              "name": [
                "Department of Pediatrics, University of California San Diego, La Jolla, CA, USA", 
                "School of Food Science and Engineering, Hainan University, Haikou, China", 
                "Key Laboratory of Food Nutrition and Functional Food of Hainan Province, Haikou, China"
              ], 
              "type": "Organization"
            }, 
            "familyName": "Zhang", 
            "givenName": "Jiachao", 
            "id": "sg:person.011346604554.69", 
            "sameAs": [
              "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011346604554.69"
            ], 
            "type": "Person"
          }
        ], 
        "citation": [
          {
            "id": "sg:pub.10.1186/s12864-020-6676-z", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1125836516", 
              "https://doi.org/10.1186/s12864-020-6676-z"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11711", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004024856", 
              "https://doi.org/10.1038/nature11711"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature25973", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1101264718", 
              "https://doi.org/10.1038/nature25973"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-019-10927-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1118037821", 
              "https://doi.org/10.1038/s41467-019-10927-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s13238-018-0596-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1110203631", 
              "https://doi.org/10.1007/s13238-018-0596-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1007/s00284-014-0640-6", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1050797470", 
              "https://doi.org/10.1007/s00284-014-0640-6"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature13568", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1042881212", 
              "https://doi.org/10.1038/nature13568"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nrendo.2015.128", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030773583", 
              "https://doi.org/10.1038/nrendo.2015.128"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/s12974-019-1494-4", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1115170428", 
              "https://doi.org/10.1186/s12974-019-1494-4"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/nature11450", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1004546178", 
              "https://doi.org/10.1038/nature11450"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-019-10656-5", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1117296456", 
              "https://doi.org/10.1038/s41467-019-10656-5"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41586-019-1065-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1113011488", 
              "https://doi.org/10.1038/s41586-019-1065-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41467-020-16366-7", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1127705453", 
              "https://doi.org/10.1038/s41467-020-16366-7"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/ismej.2016.176", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1019153013", 
              "https://doi.org/10.1038/ismej.2016.176"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41592-018-0176-y", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1107804224", 
              "https://doi.org/10.1038/s41592-018-0176-y"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41575-020-0343-3", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1128938746", 
              "https://doi.org/10.1038/s41575-020-0343-3"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/s41586-020-2095-1", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1125548941", 
              "https://doi.org/10.1038/s41586-020-2095-1"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1186/gb-2014-15-3-r46", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1030203790", 
              "https://doi.org/10.1186/gb-2014-15-3-r46"
            ], 
            "type": "CreativeWork"
          }, 
          {
            "id": "sg:pub.10.1038/srep20602", 
            "sameAs": [
              "https://app.dimensions.ai/details/publication/pub.1001228643", 
              "https://doi.org/10.1038/srep20602"
            ], 
            "type": "CreativeWork"
          }
        ], 
        "datePublished": "2021-06-02", 
        "datePublishedReg": "2021-06-02", 
        "description": "Graves\u2019 Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves\u2019 disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC\u2009=\u20090.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson\u2019s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.", 
        "genre": "article", 
        "id": "sg:pub.10.1038/s41396-021-01016-7", 
        "inLanguage": "en", 
        "isAccessibleForFree": true, 
        "isFundedItemOf": [
          {
            "id": "sg:grant.9313367", 
            "type": "MonetaryGrant"
          }, 
          {
            "id": "sg:grant.9382699", 
            "type": "MonetaryGrant"
          }
        ], 
        "isPartOf": [
          {
            "id": "sg:journal.1038436", 
            "issn": [
              "1751-7362", 
              "1751-7370"
            ], 
            "name": "The ISME Journal: Multidisciplinary Journal of Microbial Ecology", 
            "publisher": "Springer Nature", 
            "type": "Periodical"
          }, 
          {
            "issueNumber": "11", 
            "type": "PublicationIssue"
          }, 
          {
            "type": "PublicationVolume", 
            "volumeNumber": "15"
          }
        ], 
        "keywords": [
          "metagenome-assembled genomes", 
          "taxonomic markers", 
          "gut microbiome", 
          "microbial species", 
          "functional analysis", 
          "metabolic functions", 
          "genes", 
          "genetic alterations", 
          "microbiome", 
          "metabolite profiles", 
          "common organ-specific autoimmune disease", 
          "organ-specific autoimmune diseases", 
          "combination of biomarkers", 
          "specific diagnostic biomarkers", 
          "multi-cohort analysis", 
          "small pilot study", 
          "genome", 
          "severe Graves", 
          "diagnostic biomarkers", 
          "autoimmune diseases", 
          "disease patients", 
          "clinical indices", 
          "healthy controls", 
          "GD subjects", 
          "Parkinson's disease", 
          "species", 
          "SNPs", 
          "GD biomarkers", 
          "biomarker types", 
          "disease", 
          "high specificity", 
          "markers", 
          "pilot study", 
          "small sample size", 
          "biomarkers", 
          "sample size", 
          "alterations", 
          "Graves", 
          "specificity", 
          "patients", 
          "function", 
          "analysis", 
          "important limitations", 
          "subjects", 
          "predictive power", 
          "supervised classification model", 
          "profile", 
          "index", 
          "types", 
          "size", 
          "control", 
          "study", 
          "combination", 
          "diagnostics", 
          "limitations", 
          "model", 
          "network", 
          "work", 
          "classification model", 
          "power"
        ], 
        "name": "Compositional and genetic alterations in Graves\u2019 disease gut microbiome reveal specific diagnostic biomarkers", 
        "pagination": "3399-3411", 
        "productId": [
          {
            "name": "dimensions_id", 
            "type": "PropertyValue", 
            "value": [
              "pub.1138518234"
            ]
          }, 
          {
            "name": "doi", 
            "type": "PropertyValue", 
            "value": [
              "10.1038/s41396-021-01016-7"
            ]
          }, 
          {
            "name": "pubmed_id", 
            "type": "PropertyValue", 
            "value": [
              "34079079"
            ]
          }
        ], 
        "sameAs": [
          "https://doi.org/10.1038/s41396-021-01016-7", 
          "https://app.dimensions.ai/details/publication/pub.1138518234"
        ], 
        "sdDataset": "articles", 
        "sdDatePublished": "2022-06-01T22:24", 
        "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
        "sdPublisher": {
          "name": "Springer Nature - SN SciGraph project", 
          "type": "Organization"
        }, 
        "sdSource": "s3://com-springernature-scigraph/baseset/20220601/entities/gbq_results/article/article_889.jsonl", 
        "type": "ScholarlyArticle", 
        "url": "https://doi.org/10.1038/s41396-021-01016-7"
      }
    ]
     

    Download the RDF metadata as:  json-ld nt turtle xml License info

    HOW TO GET THIS DATA PROGRAMMATICALLY:

    JSON-LD is a popular format for linked data which is fully compatible with JSON.

    curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1038/s41396-021-01016-7'

    N-Triples is a line-based linked data format ideal for batch operations.

    curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1038/s41396-021-01016-7'

    Turtle is a human-readable linked data format.

    curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1038/s41396-021-01016-7'

    RDF/XML is a standard XML format for linked data.

    curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1038/s41396-021-01016-7'


     

    This table displays all metadata directly associated to this object as RDF triples.

    350 TRIPLES      22 PREDICATES      111 URIs      84 LITERALS      13 BLANK NODES

    Subject Predicate Object
    1 sg:pub.10.1038/s41396-021-01016-7 schema:about N2ac0709e012e47269d3f3717684e9973
    2 Nb052605fd7eb4838b685212163fd38f8
    3 Nb58bdd86ee524526b036c9bd27106b4d
    4 Nbd769f728f8d4c0aa8044f31210bd4e7
    5 Nbf3422fbe86843c88dc64008add71d5f
    6 Nd90c785987154f9ab2fd4accf051b6f3
    7 anzsrc-for:06
    8 anzsrc-for:0604
    9 schema:author Nd522284eb9f3470baef1af5872a0df3e
    10 schema:citation sg:pub.10.1007/s00284-014-0640-6
    11 sg:pub.10.1007/s13238-018-0596-6
    12 sg:pub.10.1038/ismej.2016.176
    13 sg:pub.10.1038/nature11450
    14 sg:pub.10.1038/nature11711
    15 sg:pub.10.1038/nature13568
    16 sg:pub.10.1038/nature25973
    17 sg:pub.10.1038/nrendo.2015.128
    18 sg:pub.10.1038/s41467-019-10656-5
    19 sg:pub.10.1038/s41467-019-10927-1
    20 sg:pub.10.1038/s41467-020-16366-7
    21 sg:pub.10.1038/s41575-020-0343-3
    22 sg:pub.10.1038/s41586-019-1065-y
    23 sg:pub.10.1038/s41586-020-2095-1
    24 sg:pub.10.1038/s41592-018-0176-y
    25 sg:pub.10.1038/srep20602
    26 sg:pub.10.1186/gb-2014-15-3-r46
    27 sg:pub.10.1186/s12864-020-6676-z
    28 sg:pub.10.1186/s12974-019-1494-4
    29 schema:datePublished 2021-06-02
    30 schema:datePublishedReg 2021-06-02
    31 schema:description Graves’ Disease is the most common organ-specific autoimmune disease and has been linked in small pilot studies to taxonomic markers within the gut microbiome. Important limitations of this work include small sample sizes and low-resolution taxonomic markers. Accordingly, we studied 162 gut microbiomes of mild and severe Graves’ disease (GD) patients and healthy controls. Taxonomic and functional analyses based on metagenome-assembled genomes (MAGs) and MAG-annotated genes, together with predicted metabolic functions and metabolite profiles, revealed a well-defined network of MAGs, genes and clinical indexes separating healthy from GD subjects. A supervised classification model identified a combination of biomarkers including microbial species, MAGs, genes and SNPs, with predictive power superior to models from any single biomarker type (AUC = 0.98). Global, cross-disease multi-cohort analysis of gut microbiomes revealed high specificity of these GD biomarkers, notably discriminating against Parkinson’s Disease, and suggesting that non-invasive stool-based diagnostics will be useful for these diseases.
    32 schema:genre article
    33 schema:inLanguage en
    34 schema:isAccessibleForFree true
    35 schema:isPartOf N088ba9d589fb4a8099a81a0cd6f7f3da
    36 N6c4685afbc3744fd84ff8f5bbac4cf8f
    37 sg:journal.1038436
    38 schema:keywords GD biomarkers
    39 GD subjects
    40 Graves
    41 Parkinson's disease
    42 SNPs
    43 alterations
    44 analysis
    45 autoimmune diseases
    46 biomarker types
    47 biomarkers
    48 classification model
    49 clinical indices
    50 combination
    51 combination of biomarkers
    52 common organ-specific autoimmune disease
    53 control
    54 diagnostic biomarkers
    55 diagnostics
    56 disease
    57 disease patients
    58 function
    59 functional analysis
    60 genes
    61 genetic alterations
    62 genome
    63 gut microbiome
    64 healthy controls
    65 high specificity
    66 important limitations
    67 index
    68 limitations
    69 markers
    70 metabolic functions
    71 metabolite profiles
    72 metagenome-assembled genomes
    73 microbial species
    74 microbiome
    75 model
    76 multi-cohort analysis
    77 network
    78 organ-specific autoimmune diseases
    79 patients
    80 pilot study
    81 power
    82 predictive power
    83 profile
    84 sample size
    85 severe Graves
    86 size
    87 small pilot study
    88 small sample size
    89 species
    90 specific diagnostic biomarkers
    91 specificity
    92 study
    93 subjects
    94 supervised classification model
    95 taxonomic markers
    96 types
    97 work
    98 schema:name Compositional and genetic alterations in Graves’ disease gut microbiome reveal specific diagnostic biomarkers
    99 schema:pagination 3399-3411
    100 schema:productId N34e68664a8f34fd3ba4cdde1def6a153
    101 Nd435b3082e704f01979443219aa1cebf
    102 Nfef9fca7a8da495d932cd8c205a9a2af
    103 schema:sameAs https://app.dimensions.ai/details/publication/pub.1138518234
    104 https://doi.org/10.1038/s41396-021-01016-7
    105 schema:sdDatePublished 2022-06-01T22:24
    106 schema:sdLicense https://scigraph.springernature.com/explorer/license/
    107 schema:sdPublisher N05f948db45564c75ae985b4e24f20e80
    108 schema:url https://doi.org/10.1038/s41396-021-01016-7
    109 sgo:license sg:explorer/license/
    110 sgo:sdDataset articles
    111 rdf:type schema:ScholarlyArticle
    112 N05f948db45564c75ae985b4e24f20e80 schema:name Springer Nature - SN SciGraph project
    113 rdf:type schema:Organization
    114 N088ba9d589fb4a8099a81a0cd6f7f3da schema:issueNumber 11
    115 rdf:type schema:PublicationIssue
    116 N0aacefd8513a4c37a818375d88f810fb rdf:first sg:person.016227240545.39
    117 rdf:rest N761d0365e04945f09b1cd1250bf9035c
    118 N1e53f3875f604bea96261c16663f8fc8 rdf:first sg:person.016106134747.41
    119 rdf:rest N23f4aa0039104e03b134035ef29e0013
    120 N23f4aa0039104e03b134035ef29e0013 rdf:first sg:person.0620460120.04
    121 rdf:rest Nf1e787c38c0941eeb4533a26dbb6d15a
    122 N2ac0709e012e47269d3f3717684e9973 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    123 schema:name Gastrointestinal Microbiome
    124 rdf:type schema:DefinedTerm
    125 N2e6499198c47450494d286e3ddb19fe0 rdf:first sg:person.0715356340.58
    126 rdf:rest N0aacefd8513a4c37a818375d88f810fb
    127 N34e68664a8f34fd3ba4cdde1def6a153 schema:name dimensions_id
    128 schema:value pub.1138518234
    129 rdf:type schema:PropertyValue
    130 N6c4685afbc3744fd84ff8f5bbac4cf8f schema:volumeNumber 15
    131 rdf:type schema:PublicationVolume
    132 N732b9147c102457599cce47849da09de rdf:first sg:person.011346604554.69
    133 rdf:rest rdf:nil
    134 N761d0365e04945f09b1cd1250bf9035c rdf:first sg:person.01255245123.96
    135 rdf:rest Na982757084494adeb0ad39683143cf1e
    136 N7a0c1a3d3c8a4033b2565f507ca3e11f rdf:first sg:person.07532351303.03
    137 rdf:rest Nc1c3e836e73e4281884e3f08cbc25f7e
    138 N7d26151eeebf419e85dc6e6d1eae3da5 rdf:first sg:person.01265705310.30
    139 rdf:rest Nf7e6e8a558394d54bc805eee0fc78ce2
    140 N89ec076780c046f8aa8172b1a7368484 rdf:first sg:person.016507333101.73
    141 rdf:rest N2e6499198c47450494d286e3ddb19fe0
    142 Na982757084494adeb0ad39683143cf1e rdf:first sg:person.01260166777.63
    143 rdf:rest N7a0c1a3d3c8a4033b2565f507ca3e11f
    144 Nb052605fd7eb4838b685212163fd38f8 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    145 schema:name Feces
    146 rdf:type schema:DefinedTerm
    147 Nb58bdd86ee524526b036c9bd27106b4d schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    148 schema:name Graves Disease
    149 rdf:type schema:DefinedTerm
    150 Nbd769f728f8d4c0aa8044f31210bd4e7 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    151 schema:name Biomarkers
    152 rdf:type schema:DefinedTerm
    153 Nbf3422fbe86843c88dc64008add71d5f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    154 schema:name Humans
    155 rdf:type schema:DefinedTerm
    156 Nc1c3e836e73e4281884e3f08cbc25f7e rdf:first sg:person.016311745377.96
    157 rdf:rest N732b9147c102457599cce47849da09de
    158 Nd435b3082e704f01979443219aa1cebf schema:name doi
    159 schema:value 10.1038/s41396-021-01016-7
    160 rdf:type schema:PropertyValue
    161 Nd522284eb9f3470baef1af5872a0df3e rdf:first sg:person.011522220701.89
    162 rdf:rest N7d26151eeebf419e85dc6e6d1eae3da5
    163 Nd90c785987154f9ab2fd4accf051b6f3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
    164 schema:name Metagenome
    165 rdf:type schema:DefinedTerm
    166 Ndf3a697dde334ee38ebb95a77a592b25 rdf:first sg:person.015722260216.20
    167 rdf:rest N89ec076780c046f8aa8172b1a7368484
    168 Nf1e787c38c0941eeb4533a26dbb6d15a rdf:first sg:person.01113460501.49
    169 rdf:rest Ndf3a697dde334ee38ebb95a77a592b25
    170 Nf7e6e8a558394d54bc805eee0fc78ce2 rdf:first sg:person.01074626724.22
    171 rdf:rest N1e53f3875f604bea96261c16663f8fc8
    172 Nfef9fca7a8da495d932cd8c205a9a2af schema:name pubmed_id
    173 schema:value 34079079
    174 rdf:type schema:PropertyValue
    175 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
    176 schema:name Biological Sciences
    177 rdf:type schema:DefinedTerm
    178 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
    179 schema:name Genetics
    180 rdf:type schema:DefinedTerm
    181 sg:grant.9313367 http://pending.schema.org/fundedItem sg:pub.10.1038/s41396-021-01016-7
    182 rdf:type schema:MonetaryGrant
    183 sg:grant.9382699 http://pending.schema.org/fundedItem sg:pub.10.1038/s41396-021-01016-7
    184 rdf:type schema:MonetaryGrant
    185 sg:journal.1038436 schema:issn 1751-7362
    186 1751-7370
    187 schema:name The ISME Journal: Multidisciplinary Journal of Microbial Ecology
    188 schema:publisher Springer Nature
    189 rdf:type schema:Periodical
    190 sg:person.01074626724.22 schema:affiliation grid-institutes:grid.266100.3
    191 schema:familyName Huang
    192 schema:givenName Shi
    193 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01074626724.22
    194 rdf:type schema:Person
    195 sg:person.01113460501.49 schema:affiliation grid-institutes:grid.266100.3
    196 schema:familyName Vázquez-Baeza
    197 schema:givenName Yoshiki
    198 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01113460501.49
    199 rdf:type schema:Person
    200 sg:person.011346604554.69 schema:affiliation grid-institutes:None
    201 schema:familyName Zhang
    202 schema:givenName Jiachao
    203 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011346604554.69
    204 rdf:type schema:Person
    205 sg:person.011522220701.89 schema:affiliation grid-institutes:grid.266100.3
    206 schema:familyName Zhu
    207 schema:givenName Qiyun
    208 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.011522220701.89
    209 rdf:type schema:Person
    210 sg:person.01255245123.96 schema:affiliation grid-institutes:grid.266100.3
    211 schema:familyName Belda-Ferre
    212 schema:givenName Pedro
    213 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01255245123.96
    214 rdf:type schema:Person
    215 sg:person.01260166777.63 schema:affiliation grid-institutes:grid.481551.c
    216 schema:familyName Kim
    217 schema:givenName Ho-Cheol
    218 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01260166777.63
    219 rdf:type schema:Person
    220 sg:person.01265705310.30 schema:affiliation grid-institutes:grid.412979.0
    221 schema:familyName Hou
    222 schema:givenName Qiangchuan
    223 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01265705310.30
    224 rdf:type schema:Person
    225 sg:person.015722260216.20 schema:affiliation grid-institutes:grid.459560.b
    226 schema:familyName Cen
    227 schema:givenName Chaoping
    228 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.015722260216.20
    229 rdf:type schema:Person
    230 sg:person.016106134747.41 schema:affiliation grid-institutes:grid.459560.b
    231 schema:familyName Ou
    232 schema:givenName Qianying
    233 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016106134747.41
    234 rdf:type schema:Person
    235 sg:person.016227240545.39 schema:affiliation grid-institutes:grid.428986.9
    236 schema:familyName Chang
    237 schema:givenName Haibo
    238 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016227240545.39
    239 rdf:type schema:Person
    240 sg:person.016311745377.96 schema:affiliation grid-institutes:grid.266100.3
    241 schema:familyName Knight
    242 schema:givenName Rob
    243 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016311745377.96
    244 rdf:type schema:Person
    245 sg:person.016507333101.73 schema:affiliation grid-institutes:grid.266100.3
    246 schema:familyName Cantu
    247 schema:givenName Victor
    248 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.016507333101.73
    249 rdf:type schema:Person
    250 sg:person.0620460120.04 schema:affiliation grid-institutes:None
    251 schema:familyName Huo
    252 schema:givenName Dongxue
    253 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0620460120.04
    254 rdf:type schema:Person
    255 sg:person.0715356340.58 schema:affiliation grid-institutes:grid.266100.3
    256 schema:familyName Estaki
    257 schema:givenName Mehrbod
    258 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0715356340.58
    259 rdf:type schema:Person
    260 sg:person.07532351303.03 schema:affiliation grid-institutes:grid.459560.b
    261 schema:familyName Chen
    262 schema:givenName Kaining
    263 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07532351303.03
    264 rdf:type schema:Person
    265 sg:pub.10.1007/s00284-014-0640-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050797470
    266 https://doi.org/10.1007/s00284-014-0640-6
    267 rdf:type schema:CreativeWork
    268 sg:pub.10.1007/s13238-018-0596-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1110203631
    269 https://doi.org/10.1007/s13238-018-0596-6
    270 rdf:type schema:CreativeWork
    271 sg:pub.10.1038/ismej.2016.176 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019153013
    272 https://doi.org/10.1038/ismej.2016.176
    273 rdf:type schema:CreativeWork
    274 sg:pub.10.1038/nature11450 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004546178
    275 https://doi.org/10.1038/nature11450
    276 rdf:type schema:CreativeWork
    277 sg:pub.10.1038/nature11711 schema:sameAs https://app.dimensions.ai/details/publication/pub.1004024856
    278 https://doi.org/10.1038/nature11711
    279 rdf:type schema:CreativeWork
    280 sg:pub.10.1038/nature13568 schema:sameAs https://app.dimensions.ai/details/publication/pub.1042881212
    281 https://doi.org/10.1038/nature13568
    282 rdf:type schema:CreativeWork
    283 sg:pub.10.1038/nature25973 schema:sameAs https://app.dimensions.ai/details/publication/pub.1101264718
    284 https://doi.org/10.1038/nature25973
    285 rdf:type schema:CreativeWork
    286 sg:pub.10.1038/nrendo.2015.128 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030773583
    287 https://doi.org/10.1038/nrendo.2015.128
    288 rdf:type schema:CreativeWork
    289 sg:pub.10.1038/s41467-019-10656-5 schema:sameAs https://app.dimensions.ai/details/publication/pub.1117296456
    290 https://doi.org/10.1038/s41467-019-10656-5
    291 rdf:type schema:CreativeWork
    292 sg:pub.10.1038/s41467-019-10927-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1118037821
    293 https://doi.org/10.1038/s41467-019-10927-1
    294 rdf:type schema:CreativeWork
    295 sg:pub.10.1038/s41467-020-16366-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1127705453
    296 https://doi.org/10.1038/s41467-020-16366-7
    297 rdf:type schema:CreativeWork
    298 sg:pub.10.1038/s41575-020-0343-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1128938746
    299 https://doi.org/10.1038/s41575-020-0343-3
    300 rdf:type schema:CreativeWork
    301 sg:pub.10.1038/s41586-019-1065-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1113011488
    302 https://doi.org/10.1038/s41586-019-1065-y
    303 rdf:type schema:CreativeWork
    304 sg:pub.10.1038/s41586-020-2095-1 schema:sameAs https://app.dimensions.ai/details/publication/pub.1125548941
    305 https://doi.org/10.1038/s41586-020-2095-1
    306 rdf:type schema:CreativeWork
    307 sg:pub.10.1038/s41592-018-0176-y schema:sameAs https://app.dimensions.ai/details/publication/pub.1107804224
    308 https://doi.org/10.1038/s41592-018-0176-y
    309 rdf:type schema:CreativeWork
    310 sg:pub.10.1038/srep20602 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001228643
    311 https://doi.org/10.1038/srep20602
    312 rdf:type schema:CreativeWork
    313 sg:pub.10.1186/gb-2014-15-3-r46 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030203790
    314 https://doi.org/10.1186/gb-2014-15-3-r46
    315 rdf:type schema:CreativeWork
    316 sg:pub.10.1186/s12864-020-6676-z schema:sameAs https://app.dimensions.ai/details/publication/pub.1125836516
    317 https://doi.org/10.1186/s12864-020-6676-z
    318 rdf:type schema:CreativeWork
    319 sg:pub.10.1186/s12974-019-1494-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1115170428
    320 https://doi.org/10.1186/s12974-019-1494-4
    321 rdf:type schema:CreativeWork
    322 grid-institutes:None schema:alternateName Key Laboratory of Food Nutrition and Functional Food of Hainan Province, Haikou, China
    323 schema:name Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
    324 Key Laboratory of Food Nutrition and Functional Food of Hainan Province, Haikou, China
    325 School of Food Science and Engineering, Hainan University, Haikou, China
    326 rdf:type schema:Organization
    327 grid-institutes:grid.266100.3 schema:alternateName Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
    328 Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
    329 Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
    330 Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
    331 schema:name Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
    332 Department of Bioengineering, University of California San Diego, La Jolla, CA, USA
    333 Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
    334 Department of Pediatrics, University of California San Diego, La Jolla, CA, USA
    335 rdf:type schema:Organization
    336 grid-institutes:grid.412979.0 schema:alternateName Hubei Provincial Engineering and Technology Research Center for Food Ingredients, Hubei University of Arts and Science, Xiangyang, Hubei province, China
    337 schema:name Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
    338 Hubei Provincial Engineering and Technology Research Center for Food Ingredients, Hubei University of Arts and Science, Xiangyang, Hubei province, China
    339 School of Food Science and Engineering, Hainan University, Haikou, China
    340 rdf:type schema:Organization
    341 grid-institutes:grid.428986.9 schema:alternateName School of Food Science and Engineering, Hainan University, Haikou, China
    342 schema:name School of Food Science and Engineering, Hainan University, Haikou, China
    343 rdf:type schema:Organization
    344 grid-institutes:grid.459560.b schema:alternateName Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
    345 schema:name Department of Endocrinology, Hainan General Hospital, Hainan Affiliated Hospital of Hainan Medical University, Haikou, China
    346 School of Food Science and Engineering, Hainan University, Haikou, China
    347 rdf:type schema:Organization
    348 grid-institutes:grid.481551.c schema:alternateName Scalable Knowledge Intelligence, IBM Research-Almaden, San Jose, CA, USA
    349 schema:name Scalable Knowledge Intelligence, IBM Research-Almaden, San Jose, CA, USA
    350 rdf:type schema:Organization
     




    Preview window. Press ESC to close (or click here)


    ...