{
  "abstract": "Population-scale metabolomics studies have linked metabolic measures to diseases, quantitative traits, and genetic variation, but the results are scattered across assay platforms, phenotype definitions, and analytical formats. MetabDB integrates 16 public studies spanning nuclear magnetic resonance, mass spectrometry, and lipidomics. The current release contains 2663 metabolic measures, 3524 diseases and outcomes, 3382 other genome-wide association traits, and 2025 molecular quantitative trait locus (QTL) targets. MetabDB links genomic variants, genes and proteins, metabolic measures, and diseases or traits through variant/QTL associations, fine-mapping, rare-variant or burden analyses, colocalization, Mendelian randomization, and population associations. Metabolic measures areretained in their source-reported forms, including compounds, lipid species, lipoprotein measures, ratios, percentages, and derived traits. Gene- and protein-level evidence can be examined alongside genomic signals and related disease or trait evidence for the same metabolic measure. Source information and reported analytical details are retained, including the source study, original variable or phenotype definition, assay, unit, exposure scale, analytical model, and statistics where available. Search, browse, and colocalization pages, together with gene evidence breadth and disease-association profiles, provide access to these records. MetabDB is freely available at http://www.mulinlab.org/metabdb/.",
  "abstract_shown": true,
  "affiliations": [
    "Department of Pharmacology, State Key Laboratory of Experimental Hematology, The Province and Ministry Co-sponsored Collaborative Innovation Center for Medical Epigenetics, Tianjin Key Laboratory of Inflammation Biology, School of Basic Medical Sciences, Tianjin Medical University , Tianjin 300070 ,",
    "Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University , Tianjin 300070 ,"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 4,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Dandan Huang",
      "orcid": "0009-0002-3503-5855"
    },
    {
      "affs": [
        0
      ],
      "name": "Xinxin Shi"
    },
    {
      "affs": [
        0
      ],
      "name": "Sifan Cui"
    },
    {
      "affs": [
        1
      ],
      "name": "Qinyi Xu"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/38tp8h8xdz1p4.bib",
  "cited_by": 0,
  "doi": "10.1093/nar/gkag1086",
  "fulltext_url": null,
  "id": "38tp8h8xdz1p4",
  "issns": [
    "0305-1048",
    "1362-4962"
  ],
  "landing_url": "https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1086/9005760",
  "language": null,
  "licence": "CC-BY-NC-4.0",
  "licence_label": "CC BY-NC 4.0",
  "licence_source": "article",
  "licence_url": "https://creativecommons.org/licenses/by-nc/4.0/",
  "metadata_licence": null,
  "native_subjects": [],
  "openalex": null,
  "pdf_url": "https://academic.oup.com/nar/advance-article-pdf/doi/10.1093/nar/gkag1086/72639859/gkag1086.pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-31",
  "publisher": "Oxford University Press (OUP)",
  "ris": "https://research.draconitic.com/paper/38tp8h8xdz1p4.ris",
  "sources": [
    {
      "first_seen": "2026-10-31T12:21:18Z",
      "native_id": "10.1093/nar/gkag1086",
      "source": "crossref",
      "url": "https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1086/9005760"
    }
  ],
  "subjects": [
    {
      "field": "biochemistry",
      "origin": "issn:0305-1048",
      "subfield": "molecular-biology"
    }
  ],
  "title": "MetabDB: an integrated resource for human metabolic measures, disease associations, and genetic evidence",
  "title_text": "MetabDB: an integrated resource for human metabolic measures, disease associations, and genetic evidence",
  "type": "peer-reviewed",
  "updated_at": "2026-11-02T00:21:29Z",
  "url": "https://research.draconitic.com/paper/38tp8h8xdz1p4",
  "venue": "Nucleic Acids Research",
  "versions": []
}