Human metabolic individuality in biomedical and pharmaceutical research View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2011-09

AUTHORS

Karsten Suhre, So-Youn Shin, Ann-Kristin Petersen, Robert P. Mohney, David Meredith, Brigitte Wägele, Elisabeth Altmaier, CARDIoGRAM, Panos Deloukas, Jeanette Erdmann, Elin Grundberg, Christopher J. Hammond, Martin Hrabé de Angelis, Gabi Kastenmüller, Anna Köttgen, Florian Kronenberg, Massimo Mangino, Christa Meisinger, Thomas Meitinger, Hans-Werner Mewes, Michael V. Milburn, Cornelia Prehn, Johannes Raffler, Janina S. Ried, Werner Römisch-Margl, Nilesh J. Samani, Kerrin S. Small, H. -Erich Wichmann, Guangju Zhai, Thomas Illig, Tim D. Spector, Jerzy Adamski, Nicole Soranzo, Christian Gieger

ABSTRACT

Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research. More... »

PAGES

54

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  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1038/nature10354

    DOI

    http://dx.doi.org/10.1038/nature10354

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1040072135

    PUBMED

    https://www.ncbi.nlm.nih.gov/pubmed/21886157


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