Identification of baseline gene expression signatures predicting therapeutic responses to three biologic agents in rheumatoid arthritis: a retrospective observational study View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-12

AUTHORS

Seiji Nakamura, Katsuya Suzuki, Hiroshi Iijima, Yuko Hata, Chun Ren Lim, Yohei Ishizawa, Hideto Kameda, Koichi Amano, Kenichi Matsubara, Ryo Matoba, Tsutomu Takeuchi

ABSTRACT

BACKGROUND: According to EULAR recommendations, biologic DMARDs (bDMARDs) such as tumor necrosis factor inhibitor, tocilizumab (TCZ), and abatacept (ABT) are in parallel when prescribing to rheumatoid arthritis (RA) patients who have shown insufficient response to conventional synthetic DMARDs. However, most prediction studies of therapeutic response to bDMARDs using gene expression profiles were focused on a single bDMARD, and consideration of the results from the perspective of RA pathophysiology was insufficient. The aim of this study was to identify the specific molecular biological features predicting the therapeutic outcomes of three bDMARDs (infliximab [IFX], TCZ, and ABT) by studying blood gene expression signatures of patients before biologic treatment in a unified test platform. METHODS: RA patients who responded inadequately to methotrexate and were later commenced on any one of IFX (n = 140), TCZ (n = 38), or ABT (n = 31) as their first biologic between May 2007 and November 2011 were enrolled. Whole-blood gene expression data were obtained before biologic administration. Patients were categorized into remission (REM) and nonremission (NON-REM) groups according to CDAI at 6 months of biologic therapy. We employed Gene Set Enrichment Analysis (GSEA) to identify functional gene sets differentially expressed between these two groups for each biologic. Then, we compiled "signature scores" for these gene sets, and the prediction performances were assessed. RESULTS: GSEA showed that inflammasome genes were significantly upregulated with IFX in the NON-REM group compared with the REM group. With TCZ in the REM group, B-cell-specifically expressed genes were upregulated. RNA elongation, apoptosis-related, and NK-cell-specifically expressed genes were upregulated with ABT in the NON-REM group. Logistic regression analyses showed that "signature scores" of inflammasomes, B-cell-specifically expressed, and NK-cell-specifically expressed genes were significant, independently predictive factors for treatment outcome with IFX, TCZ, and ABT, respectively. The AUCs of ROC curves of these signature scores were 0.637, 0.796, and 0.768 for IFX, TCZ, and ABT, respectively. CONCLUSIONS: We have identified original gene expression predictive signatures uniquely underlying the therapeutic effects of IFX, TCZ, and ABT. This is, to our knowledge, the first attempt to predict therapeutic effects of three drugs concomitantly using a unified gene expression test platform. More... »

PAGES

159

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s13075-016-1052-8

DOI

http://dx.doi.org/10.1186/s13075-016-1052-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1021504450

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/27435242


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/2008/0604", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Genetics", 
        "type": "DefinedTerm"
      }, 
      {
        "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"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Abatacept", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Adult", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Antibodies, Monoclonal, Humanized", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Antirheumatic Agents", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Area Under Curve", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Arthritis, Rheumatoid", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Biomarkers", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Female", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Gene Expression Profiling", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Humans", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Infliximab", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Male", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Middle Aged", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Oligonucleotide Array Sequence Analysis", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Polymerase Chain Reaction", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "ROC Curve", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Retrospective Studies", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Sensitivity and Specificity", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Transcriptome", 
        "type": "DefinedTerm"
      }, 
      {
        "inDefinedTermSet": "https://www.nlm.nih.gov/mesh/", 
        "name": "Treatment Outcome", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Nakamura", 
        "givenName": "Seiji", 
        "id": "sg:person.0645721213.62", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645721213.62"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Keio University", 
          "id": "https://www.grid.ac/institutes/grid.26091.3c", 
          "name": [
            "Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, 160-8582, Shinjuku-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Suzuki", 
        "givenName": "Katsuya", 
        "id": "sg:person.01355246370.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01355246370.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Iijima", 
        "givenName": "Hiroshi", 
        "id": "sg:person.01073270601.56", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01073270601.56"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hata", 
        "givenName": "Yuko", 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Lim", 
        "givenName": "Chun Ren", 
        "id": "sg:person.0614663522.75", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614663522.75"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Ishizawa", 
        "givenName": "Yohei", 
        "id": "sg:person.01040322632.32", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01040322632.32"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Toho University Ohashi Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.470115.6", 
          "name": [
            "Division of Rheumatology, Department of Internal Medicine, Toho University Ohashi Medical Center, 2-17-6 Ohashi, 153-8515, Muguro-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Kameda", 
        "givenName": "Hideto", 
        "id": "sg:person.0656055364.47", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656055364.47"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Jichi Medical University Saitama Medical Center", 
          "id": "https://www.grid.ac/institutes/grid.415020.2", 
          "name": [
            "Department of Rheumatology and Clinical Immunology, Saitama Medical Center, Saitama Medical University, 1981 Tsujido-machi Kamoda, 350-8550, Kawagoe-shi, Saitama, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Amano", 
        "givenName": "Koichi", 
        "id": "sg:person.01023355176.35", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01023355176.35"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matsubara", 
        "givenName": "Kenichi", 
        "id": "sg:person.07540607175.11", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07540607175.11"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "DNA Chip Research (Japan)", 
          "id": "https://www.grid.ac/institutes/grid.452377.0", 
          "name": [
            "DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Matoba", 
        "givenName": "Ryo", 
        "id": "sg:person.01124473704.53", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01124473704.53"
        ], 
        "type": "Person"
      }, 
      {
        "affiliation": {
          "alternateName": "Keio University", 
          "id": "https://www.grid.ac/institutes/grid.26091.3c", 
          "name": [
            "Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, 160-8582, Shinjuku-ku, Tokyo, Japan"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Takeuchi", 
        "givenName": "Tsutomu", 
        "id": "sg:person.01041661127.18", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01041661127.18"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1146/annurev.immunol.14.1.397", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1000299859"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/annrheumdis-2013-204573", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1001531171"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1100/2012/491974", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1003018669"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(89)90430-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006313221"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0140-6736(89)90430-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1006313221"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.38400", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1008694500"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1182/blood-2008-06-162958", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009317926"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2217/imt.11.102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1009739654"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/tpj.2013.48", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011457576", 
          "https://doi.org/10.1038/tpj.2013.48"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.27702", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011868222"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.bbrc.2009.06.149", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1012335960"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1038/clpt.2009.244", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1019665679", 
          "https://doi.org/10.1038/clpt.2009.244"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0007556", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1021736217"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.3109/s10165-010-0402-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022060096"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.27740", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1025817260"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/ard.2011.153023", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1026232434"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/ar3819", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1029361733", 
          "https://doi.org/10.1186/ar3819"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/(sici)1521-4141(199805)28:05<1681::aid-immu1681>3.0.co;2-t", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030130179"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.cell.2010.01.040", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1031371585"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/s10165-010-0402-7", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1032495805", 
          "https://doi.org/10.1007/s10165-010-0402-7"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0506580102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037705714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.0506580102", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1037705714"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13075-015-0526-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040168264", 
          "https://doi.org/10.1186/s13075-015-0526-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/s13075-015-0526-4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040168264", 
          "https://doi.org/10.1186/s13075-015-0526-4"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/j.molmed.2010.11.001", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1040228946"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1186/ar1990", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043805175", 
          "https://doi.org/10.1186/ar1990"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pgen.1003394", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1044720120"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.30242", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047082539"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0071477", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1047335007"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1073/pnas.86.19.7547", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1050007753"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1136/ard.2004.025577", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052250176"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1371/journal.pone.0029979", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1052961249"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.38947", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053141087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1002/art.38947", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1053141087"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1093/biomet/80.1.27", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1059420374"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1517/14712598.8.5.669", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1067590046"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1075182543", 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4049/jimmunol.174.8.4590", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1077034528"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1083324891", 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2016-12", 
    "datePublishedReg": "2016-12-01", 
    "description": "BACKGROUND: According to EULAR recommendations, biologic DMARDs (bDMARDs) such as tumor necrosis factor inhibitor, tocilizumab (TCZ), and abatacept (ABT) are in parallel when prescribing to rheumatoid arthritis (RA) patients who have shown insufficient response to conventional synthetic DMARDs. However, most prediction studies of therapeutic response to bDMARDs using gene expression profiles were focused on a single bDMARD, and consideration of the results from the perspective of RA pathophysiology was insufficient. The aim of this study was to identify the specific molecular biological features predicting the therapeutic outcomes of three bDMARDs (infliximab [IFX], TCZ, and ABT) by studying blood gene expression signatures of patients before biologic treatment in a unified test platform.\nMETHODS: RA patients who responded inadequately to methotrexate and were later commenced on any one of IFX (n\u2009=\u2009140), TCZ (n\u2009=\u200938), or ABT (n\u2009=\u200931) as their first biologic between May 2007 and November 2011 were enrolled. Whole-blood gene expression data were obtained before biologic administration. Patients were categorized into remission (REM) and nonremission (NON-REM) groups according to CDAI at 6\u00a0months of biologic therapy. We employed Gene Set Enrichment Analysis (GSEA) to identify functional gene sets differentially expressed between these two groups for each biologic. Then, we compiled \"signature scores\" for these gene sets, and the prediction performances were assessed.\nRESULTS: GSEA showed that inflammasome genes were significantly upregulated with IFX in the NON-REM group compared with the REM group. With TCZ in the REM group, B-cell-specifically expressed genes were upregulated. RNA elongation, apoptosis-related, and NK-cell-specifically expressed genes were upregulated with ABT in the NON-REM group. Logistic regression analyses showed that \"signature scores\" of inflammasomes, B-cell-specifically expressed, and NK-cell-specifically expressed genes were significant, independently predictive factors for treatment outcome with IFX, TCZ, and ABT, respectively. The AUCs of ROC curves of these signature scores were 0.637, 0.796, and 0.768 for IFX, TCZ, and ABT, respectively.\nCONCLUSIONS: We have identified original gene expression predictive signatures uniquely underlying the therapeutic effects of IFX, TCZ, and ABT. This is, to our knowledge, the first attempt to predict therapeutic effects of three drugs concomitantly using a unified gene expression test platform.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s13075-016-1052-8", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isFundedItemOf": [
      {
        "id": "sg:grant.5872493", 
        "type": "MonetaryGrant"
      }
    ], 
    "isPartOf": [
      {
        "id": "sg:journal.1297499", 
        "issn": [
          "1478-6354", 
          "1478-6362"
        ], 
        "name": "Arthritis Research & Therapy", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "18"
      }
    ], 
    "name": "Identification of baseline gene expression signatures predicting therapeutic responses to three biologic agents in rheumatoid arthritis: a retrospective observational study", 
    "pagination": "159", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "66753c83058a8e4ba303f3170e7d49f4a60f73d8a4a24f65173c046707f70f97"
        ]
      }, 
      {
        "name": "pubmed_id", 
        "type": "PropertyValue", 
        "value": [
          "27435242"
        ]
      }, 
      {
        "name": "nlm_unique_id", 
        "type": "PropertyValue", 
        "value": [
          "101154438"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s13075-016-1052-8"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1021504450"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s13075-016-1052-8", 
      "https://app.dimensions.ai/details/publication/pub.1021504450"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:25", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87104_00000000.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs13075-016-1052-8"
  }
]
 

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.10.1186/s13075-016-1052-8'

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

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s13075-016-1052-8'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s13075-016-1052-8'

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

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s13075-016-1052-8'


 

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

342 TRIPLES      21 PREDICATES      85 URIs      42 LITERALS      30 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s13075-016-1052-8 schema:about N08549b964b6d47ffa9506d77367244c3
2 N1cf4668627854ecd9f9237149ac08584
3 N251dc85e2e914110844f660ea7536c14
4 N304962e1f86e42f1a20151dcd2aa7a9a
5 N33403a4c7b85404faa29887f75e393f0
6 N34ed5f9650c94c38a37c10b2e33e6d92
7 N403e49b21878411c84a6ba32cf92f358
8 N65bf665ca083415281349a74c21be24a
9 N6aa7f6fc8dda4cb9b453325df35a075c
10 N6f649bd773cf4c8e8f21da837fede535
11 N7f9f70198f9a459fbaf90b44a1c7feeb
12 N88044fb83bf245e59909fbc8b731f2c2
13 N900a856db4ca46a595a5674563263b90
14 Na3bf7b6723d145ea8fb99f1aa2154a4f
15 Nb2901568a218433989017cb0abdf868e
16 Nb64d53e4ee2a41a18c0a3591fc963949
17 Nb89075928c6a4b07838577edb1599d40
18 Nc0a3043147a1478c89d800c88ab2ab36
19 Nca377ca67bbf4ab29a9211faf67d7eec
20 Ne25bf3b95a6d410abde2d5bf0e8ecd8a
21 Nfc7f6250b85f4ac7bdea0a2a1b674c94
22 anzsrc-for:06
23 anzsrc-for:0604
24 schema:author N98bf38b2907e4db58a56a23d2e2ecb13
25 schema:citation sg:pub.10.1007/s10165-010-0402-7
26 sg:pub.10.1038/clpt.2009.244
27 sg:pub.10.1038/tpj.2013.48
28 sg:pub.10.1186/ar1990
29 sg:pub.10.1186/ar3819
30 sg:pub.10.1186/s13075-015-0526-4
31 https://app.dimensions.ai/details/publication/pub.1075182543
32 https://app.dimensions.ai/details/publication/pub.1083324891
33 https://doi.org/10.1002/(sici)1521-4141(199805)28:05<1681::aid-immu1681>3.0.co;2-t
34 https://doi.org/10.1002/art.27702
35 https://doi.org/10.1002/art.27740
36 https://doi.org/10.1002/art.30242
37 https://doi.org/10.1002/art.38400
38 https://doi.org/10.1002/art.38947
39 https://doi.org/10.1016/j.bbrc.2009.06.149
40 https://doi.org/10.1016/j.cell.2010.01.040
41 https://doi.org/10.1016/j.molmed.2010.11.001
42 https://doi.org/10.1016/s0140-6736(89)90430-3
43 https://doi.org/10.1073/pnas.0506580102
44 https://doi.org/10.1073/pnas.86.19.7547
45 https://doi.org/10.1093/biomet/80.1.27
46 https://doi.org/10.1100/2012/491974
47 https://doi.org/10.1136/annrheumdis-2013-204573
48 https://doi.org/10.1136/ard.2004.025577
49 https://doi.org/10.1136/ard.2011.153023
50 https://doi.org/10.1146/annurev.immunol.14.1.397
51 https://doi.org/10.1182/blood-2008-06-162958
52 https://doi.org/10.1371/journal.pgen.1003394
53 https://doi.org/10.1371/journal.pone.0007556
54 https://doi.org/10.1371/journal.pone.0029979
55 https://doi.org/10.1371/journal.pone.0071477
56 https://doi.org/10.1517/14712598.8.5.669
57 https://doi.org/10.2217/imt.11.102
58 https://doi.org/10.3109/s10165-010-0402-7
59 https://doi.org/10.4049/jimmunol.174.8.4590
60 schema:datePublished 2016-12
61 schema:datePublishedReg 2016-12-01
62 schema:description BACKGROUND: According to EULAR recommendations, biologic DMARDs (bDMARDs) such as tumor necrosis factor inhibitor, tocilizumab (TCZ), and abatacept (ABT) are in parallel when prescribing to rheumatoid arthritis (RA) patients who have shown insufficient response to conventional synthetic DMARDs. However, most prediction studies of therapeutic response to bDMARDs using gene expression profiles were focused on a single bDMARD, and consideration of the results from the perspective of RA pathophysiology was insufficient. The aim of this study was to identify the specific molecular biological features predicting the therapeutic outcomes of three bDMARDs (infliximab [IFX], TCZ, and ABT) by studying blood gene expression signatures of patients before biologic treatment in a unified test platform. METHODS: RA patients who responded inadequately to methotrexate and were later commenced on any one of IFX (n = 140), TCZ (n = 38), or ABT (n = 31) as their first biologic between May 2007 and November 2011 were enrolled. Whole-blood gene expression data were obtained before biologic administration. Patients were categorized into remission (REM) and nonremission (NON-REM) groups according to CDAI at 6 months of biologic therapy. We employed Gene Set Enrichment Analysis (GSEA) to identify functional gene sets differentially expressed between these two groups for each biologic. Then, we compiled "signature scores" for these gene sets, and the prediction performances were assessed. RESULTS: GSEA showed that inflammasome genes were significantly upregulated with IFX in the NON-REM group compared with the REM group. With TCZ in the REM group, B-cell-specifically expressed genes were upregulated. RNA elongation, apoptosis-related, and NK-cell-specifically expressed genes were upregulated with ABT in the NON-REM group. Logistic regression analyses showed that "signature scores" of inflammasomes, B-cell-specifically expressed, and NK-cell-specifically expressed genes were significant, independently predictive factors for treatment outcome with IFX, TCZ, and ABT, respectively. The AUCs of ROC curves of these signature scores were 0.637, 0.796, and 0.768 for IFX, TCZ, and ABT, respectively. CONCLUSIONS: We have identified original gene expression predictive signatures uniquely underlying the therapeutic effects of IFX, TCZ, and ABT. This is, to our knowledge, the first attempt to predict therapeutic effects of three drugs concomitantly using a unified gene expression test platform.
63 schema:genre research_article
64 schema:inLanguage en
65 schema:isAccessibleForFree true
66 schema:isPartOf N65e8ba570beb4c64af57f9e5c86a8d28
67 Nec5458c8f333416d892dbc4e60c1ea3a
68 sg:journal.1297499
69 schema:name Identification of baseline gene expression signatures predicting therapeutic responses to three biologic agents in rheumatoid arthritis: a retrospective observational study
70 schema:pagination 159
71 schema:productId N159ad0bbc4cf41d9a15b85b72485a5b6
72 N186c983cdbd74052960d32433dc5162f
73 Ncb9b091f36474380a880735895d8d1ef
74 Nde93a91c5215429e95641e85b4c7c05e
75 Ne60599f672f247bf8692b7d22e525bdc
76 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021504450
77 https://doi.org/10.1186/s13075-016-1052-8
78 schema:sdDatePublished 2019-04-11T12:25
79 schema:sdLicense https://scigraph.springernature.com/explorer/license/
80 schema:sdPublisher Nb3b2435b611e4351940762390a0b6d0f
81 schema:url https://link.springer.com/10.1186%2Fs13075-016-1052-8
82 sgo:license sg:explorer/license/
83 sgo:sdDataset articles
84 rdf:type schema:ScholarlyArticle
85 N06e808c786f74ca39aaca743730e3ebd rdf:first sg:person.0656055364.47
86 rdf:rest N532a097e3b414fef97ba52ce2b264586
87 N08549b964b6d47ffa9506d77367244c3 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
88 schema:name Female
89 rdf:type schema:DefinedTerm
90 N159ad0bbc4cf41d9a15b85b72485a5b6 schema:name nlm_unique_id
91 schema:value 101154438
92 rdf:type schema:PropertyValue
93 N186c983cdbd74052960d32433dc5162f schema:name readcube_id
94 schema:value 66753c83058a8e4ba303f3170e7d49f4a60f73d8a4a24f65173c046707f70f97
95 rdf:type schema:PropertyValue
96 N1cf4668627854ecd9f9237149ac08584 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
97 schema:name Male
98 rdf:type schema:DefinedTerm
99 N251dc85e2e914110844f660ea7536c14 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
100 schema:name Sensitivity and Specificity
101 rdf:type schema:DefinedTerm
102 N2f550afba2bd47d3ace1f19d57c53b5a rdf:first sg:person.01124473704.53
103 rdf:rest N352fcc1817ac40c78bad48bc2b346edc
104 N304962e1f86e42f1a20151dcd2aa7a9a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
105 schema:name Middle Aged
106 rdf:type schema:DefinedTerm
107 N33403a4c7b85404faa29887f75e393f0 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
108 schema:name Treatment Outcome
109 rdf:type schema:DefinedTerm
110 N34ed5f9650c94c38a37c10b2e33e6d92 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
111 schema:name Aged
112 rdf:type schema:DefinedTerm
113 N352fcc1817ac40c78bad48bc2b346edc rdf:first sg:person.01041661127.18
114 rdf:rest rdf:nil
115 N403e49b21878411c84a6ba32cf92f358 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
116 schema:name Humans
117 rdf:type schema:DefinedTerm
118 N4b39d034511c45caa2c1863aa22a73a0 rdf:first N8a4177aa116f4d5eaf72de9ed4ed1c42
119 rdf:rest Ndccdfc37956f4a41a42c84f857f51732
120 N532a097e3b414fef97ba52ce2b264586 rdf:first sg:person.01023355176.35
121 rdf:rest N72943b6d271a446a9f03c5db28f5276c
122 N65bf665ca083415281349a74c21be24a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
123 schema:name Polymerase Chain Reaction
124 rdf:type schema:DefinedTerm
125 N65e8ba570beb4c64af57f9e5c86a8d28 schema:volumeNumber 18
126 rdf:type schema:PublicationVolume
127 N6aa7f6fc8dda4cb9b453325df35a075c schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
128 schema:name Infliximab
129 rdf:type schema:DefinedTerm
130 N6f649bd773cf4c8e8f21da837fede535 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
131 schema:name Biomarkers
132 rdf:type schema:DefinedTerm
133 N72943b6d271a446a9f03c5db28f5276c rdf:first sg:person.07540607175.11
134 rdf:rest N2f550afba2bd47d3ace1f19d57c53b5a
135 N73924463ba13419ebc3bd9be14492ea5 rdf:first sg:person.01073270601.56
136 rdf:rest N4b39d034511c45caa2c1863aa22a73a0
137 N77ce61fc9fb34d0886166a7e5139e636 rdf:first sg:person.01040322632.32
138 rdf:rest N06e808c786f74ca39aaca743730e3ebd
139 N7f9f70198f9a459fbaf90b44a1c7feeb schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
140 schema:name ROC Curve
141 rdf:type schema:DefinedTerm
142 N88044fb83bf245e59909fbc8b731f2c2 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
143 schema:name Retrospective Studies
144 rdf:type schema:DefinedTerm
145 N8a4177aa116f4d5eaf72de9ed4ed1c42 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
146 schema:familyName Hata
147 schema:givenName Yuko
148 rdf:type schema:Person
149 N900a856db4ca46a595a5674563263b90 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
150 schema:name Arthritis, Rheumatoid
151 rdf:type schema:DefinedTerm
152 N98bf38b2907e4db58a56a23d2e2ecb13 rdf:first sg:person.0645721213.62
153 rdf:rest Ne63e2fd6d2654170b20c74c36e63344f
154 Na3bf7b6723d145ea8fb99f1aa2154a4f schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
155 schema:name Adult
156 rdf:type schema:DefinedTerm
157 Nb2901568a218433989017cb0abdf868e schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
158 schema:name Gene Expression Profiling
159 rdf:type schema:DefinedTerm
160 Nb3b2435b611e4351940762390a0b6d0f schema:name Springer Nature - SN SciGraph project
161 rdf:type schema:Organization
162 Nb64d53e4ee2a41a18c0a3591fc963949 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
163 schema:name Abatacept
164 rdf:type schema:DefinedTerm
165 Nb89075928c6a4b07838577edb1599d40 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
166 schema:name Oligonucleotide Array Sequence Analysis
167 rdf:type schema:DefinedTerm
168 Nc0a3043147a1478c89d800c88ab2ab36 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
169 schema:name Antibodies, Monoclonal, Humanized
170 rdf:type schema:DefinedTerm
171 Nca377ca67bbf4ab29a9211faf67d7eec schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
172 schema:name Antirheumatic Agents
173 rdf:type schema:DefinedTerm
174 Ncb9b091f36474380a880735895d8d1ef schema:name pubmed_id
175 schema:value 27435242
176 rdf:type schema:PropertyValue
177 Ndccdfc37956f4a41a42c84f857f51732 rdf:first sg:person.0614663522.75
178 rdf:rest N77ce61fc9fb34d0886166a7e5139e636
179 Nde93a91c5215429e95641e85b4c7c05e schema:name dimensions_id
180 schema:value pub.1021504450
181 rdf:type schema:PropertyValue
182 Ne25bf3b95a6d410abde2d5bf0e8ecd8a schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
183 schema:name Area Under Curve
184 rdf:type schema:DefinedTerm
185 Ne60599f672f247bf8692b7d22e525bdc schema:name doi
186 schema:value 10.1186/s13075-016-1052-8
187 rdf:type schema:PropertyValue
188 Ne63e2fd6d2654170b20c74c36e63344f rdf:first sg:person.01355246370.53
189 rdf:rest N73924463ba13419ebc3bd9be14492ea5
190 Nec5458c8f333416d892dbc4e60c1ea3a schema:issueNumber 1
191 rdf:type schema:PublicationIssue
192 Nfc7f6250b85f4ac7bdea0a2a1b674c94 schema:inDefinedTermSet https://www.nlm.nih.gov/mesh/
193 schema:name Transcriptome
194 rdf:type schema:DefinedTerm
195 anzsrc-for:06 schema:inDefinedTermSet anzsrc-for:
196 schema:name Biological Sciences
197 rdf:type schema:DefinedTerm
198 anzsrc-for:0604 schema:inDefinedTermSet anzsrc-for:
199 schema:name Genetics
200 rdf:type schema:DefinedTerm
201 sg:grant.5872493 http://pending.schema.org/fundedItem sg:pub.10.1186/s13075-016-1052-8
202 rdf:type schema:MonetaryGrant
203 sg:journal.1297499 schema:issn 1478-6354
204 1478-6362
205 schema:name Arthritis Research & Therapy
206 rdf:type schema:Periodical
207 sg:person.01023355176.35 schema:affiliation https://www.grid.ac/institutes/grid.415020.2
208 schema:familyName Amano
209 schema:givenName Koichi
210 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01023355176.35
211 rdf:type schema:Person
212 sg:person.01040322632.32 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
213 schema:familyName Ishizawa
214 schema:givenName Yohei
215 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01040322632.32
216 rdf:type schema:Person
217 sg:person.01041661127.18 schema:affiliation https://www.grid.ac/institutes/grid.26091.3c
218 schema:familyName Takeuchi
219 schema:givenName Tsutomu
220 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01041661127.18
221 rdf:type schema:Person
222 sg:person.01073270601.56 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
223 schema:familyName Iijima
224 schema:givenName Hiroshi
225 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01073270601.56
226 rdf:type schema:Person
227 sg:person.01124473704.53 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
228 schema:familyName Matoba
229 schema:givenName Ryo
230 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01124473704.53
231 rdf:type schema:Person
232 sg:person.01355246370.53 schema:affiliation https://www.grid.ac/institutes/grid.26091.3c
233 schema:familyName Suzuki
234 schema:givenName Katsuya
235 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.01355246370.53
236 rdf:type schema:Person
237 sg:person.0614663522.75 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
238 schema:familyName Lim
239 schema:givenName Chun Ren
240 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0614663522.75
241 rdf:type schema:Person
242 sg:person.0645721213.62 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
243 schema:familyName Nakamura
244 schema:givenName Seiji
245 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0645721213.62
246 rdf:type schema:Person
247 sg:person.0656055364.47 schema:affiliation https://www.grid.ac/institutes/grid.470115.6
248 schema:familyName Kameda
249 schema:givenName Hideto
250 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.0656055364.47
251 rdf:type schema:Person
252 sg:person.07540607175.11 schema:affiliation https://www.grid.ac/institutes/grid.452377.0
253 schema:familyName Matsubara
254 schema:givenName Kenichi
255 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.07540607175.11
256 rdf:type schema:Person
257 sg:pub.10.1007/s10165-010-0402-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1032495805
258 https://doi.org/10.1007/s10165-010-0402-7
259 rdf:type schema:CreativeWork
260 sg:pub.10.1038/clpt.2009.244 schema:sameAs https://app.dimensions.ai/details/publication/pub.1019665679
261 https://doi.org/10.1038/clpt.2009.244
262 rdf:type schema:CreativeWork
263 sg:pub.10.1038/tpj.2013.48 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011457576
264 https://doi.org/10.1038/tpj.2013.48
265 rdf:type schema:CreativeWork
266 sg:pub.10.1186/ar1990 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043805175
267 https://doi.org/10.1186/ar1990
268 rdf:type schema:CreativeWork
269 sg:pub.10.1186/ar3819 schema:sameAs https://app.dimensions.ai/details/publication/pub.1029361733
270 https://doi.org/10.1186/ar3819
271 rdf:type schema:CreativeWork
272 sg:pub.10.1186/s13075-015-0526-4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040168264
273 https://doi.org/10.1186/s13075-015-0526-4
274 rdf:type schema:CreativeWork
275 https://app.dimensions.ai/details/publication/pub.1075182543 schema:CreativeWork
276 https://app.dimensions.ai/details/publication/pub.1083324891 schema:CreativeWork
277 https://doi.org/10.1002/(sici)1521-4141(199805)28:05<1681::aid-immu1681>3.0.co;2-t schema:sameAs https://app.dimensions.ai/details/publication/pub.1030130179
278 rdf:type schema:CreativeWork
279 https://doi.org/10.1002/art.27702 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011868222
280 rdf:type schema:CreativeWork
281 https://doi.org/10.1002/art.27740 schema:sameAs https://app.dimensions.ai/details/publication/pub.1025817260
282 rdf:type schema:CreativeWork
283 https://doi.org/10.1002/art.30242 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047082539
284 rdf:type schema:CreativeWork
285 https://doi.org/10.1002/art.38400 schema:sameAs https://app.dimensions.ai/details/publication/pub.1008694500
286 rdf:type schema:CreativeWork
287 https://doi.org/10.1002/art.38947 schema:sameAs https://app.dimensions.ai/details/publication/pub.1053141087
288 rdf:type schema:CreativeWork
289 https://doi.org/10.1016/j.bbrc.2009.06.149 schema:sameAs https://app.dimensions.ai/details/publication/pub.1012335960
290 rdf:type schema:CreativeWork
291 https://doi.org/10.1016/j.cell.2010.01.040 schema:sameAs https://app.dimensions.ai/details/publication/pub.1031371585
292 rdf:type schema:CreativeWork
293 https://doi.org/10.1016/j.molmed.2010.11.001 schema:sameAs https://app.dimensions.ai/details/publication/pub.1040228946
294 rdf:type schema:CreativeWork
295 https://doi.org/10.1016/s0140-6736(89)90430-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1006313221
296 rdf:type schema:CreativeWork
297 https://doi.org/10.1073/pnas.0506580102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1037705714
298 rdf:type schema:CreativeWork
299 https://doi.org/10.1073/pnas.86.19.7547 schema:sameAs https://app.dimensions.ai/details/publication/pub.1050007753
300 rdf:type schema:CreativeWork
301 https://doi.org/10.1093/biomet/80.1.27 schema:sameAs https://app.dimensions.ai/details/publication/pub.1059420374
302 rdf:type schema:CreativeWork
303 https://doi.org/10.1100/2012/491974 schema:sameAs https://app.dimensions.ai/details/publication/pub.1003018669
304 rdf:type schema:CreativeWork
305 https://doi.org/10.1136/annrheumdis-2013-204573 schema:sameAs https://app.dimensions.ai/details/publication/pub.1001531171
306 rdf:type schema:CreativeWork
307 https://doi.org/10.1136/ard.2004.025577 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052250176
308 rdf:type schema:CreativeWork
309 https://doi.org/10.1136/ard.2011.153023 schema:sameAs https://app.dimensions.ai/details/publication/pub.1026232434
310 rdf:type schema:CreativeWork
311 https://doi.org/10.1146/annurev.immunol.14.1.397 schema:sameAs https://app.dimensions.ai/details/publication/pub.1000299859
312 rdf:type schema:CreativeWork
313 https://doi.org/10.1182/blood-2008-06-162958 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009317926
314 rdf:type schema:CreativeWork
315 https://doi.org/10.1371/journal.pgen.1003394 schema:sameAs https://app.dimensions.ai/details/publication/pub.1044720120
316 rdf:type schema:CreativeWork
317 https://doi.org/10.1371/journal.pone.0007556 schema:sameAs https://app.dimensions.ai/details/publication/pub.1021736217
318 rdf:type schema:CreativeWork
319 https://doi.org/10.1371/journal.pone.0029979 schema:sameAs https://app.dimensions.ai/details/publication/pub.1052961249
320 rdf:type schema:CreativeWork
321 https://doi.org/10.1371/journal.pone.0071477 schema:sameAs https://app.dimensions.ai/details/publication/pub.1047335007
322 rdf:type schema:CreativeWork
323 https://doi.org/10.1517/14712598.8.5.669 schema:sameAs https://app.dimensions.ai/details/publication/pub.1067590046
324 rdf:type schema:CreativeWork
325 https://doi.org/10.2217/imt.11.102 schema:sameAs https://app.dimensions.ai/details/publication/pub.1009739654
326 rdf:type schema:CreativeWork
327 https://doi.org/10.3109/s10165-010-0402-7 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022060096
328 rdf:type schema:CreativeWork
329 https://doi.org/10.4049/jimmunol.174.8.4590 schema:sameAs https://app.dimensions.ai/details/publication/pub.1077034528
330 rdf:type schema:CreativeWork
331 https://www.grid.ac/institutes/grid.26091.3c schema:alternateName Keio University
332 schema:name Division of Rheumatology, Department of Internal Medicine, Keio University School of Medicine, 35 Shinanomachi, 160-8582, Shinjuku-ku, Tokyo, Japan
333 rdf:type schema:Organization
334 https://www.grid.ac/institutes/grid.415020.2 schema:alternateName Jichi Medical University Saitama Medical Center
335 schema:name Department of Rheumatology and Clinical Immunology, Saitama Medical Center, Saitama Medical University, 1981 Tsujido-machi Kamoda, 350-8550, Kawagoe-shi, Saitama, Japan
336 rdf:type schema:Organization
337 https://www.grid.ac/institutes/grid.452377.0 schema:alternateName DNA Chip Research (Japan)
338 schema:name DNA Chip Research Inc., 1-15-1 Kaigan, Suzuebaydium 5F, 105-0022, Minato-ku, Tokyo, Japan
339 rdf:type schema:Organization
340 https://www.grid.ac/institutes/grid.470115.6 schema:alternateName Toho University Ohashi Medical Center
341 schema:name Division of Rheumatology, Department of Internal Medicine, Toho University Ohashi Medical Center, 2-17-6 Ohashi, 153-8515, Muguro-ku, Tokyo, Japan
342 rdf:type schema:Organization
 




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


...