Genome-wide association study identifies multiple loci influencing human serum metabolite levels

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    Author
    Kettunen, J; Tukiainen, T; Sarin, A-P; Ortega-Alonso, A; Tikkanen, E; Lyytikainen, L-P; Kangas, AJ; Soininen, P; Wuertz, P; Silander, K; ...
    Date
    2012-03-01
    Source Title
    NATURE GENETICS
    Publisher
    NATURE PUBLISHING GROUP
    University of Melbourne Author/s
    Inouye, Michael
    Affiliation
    Medical Biology (W.E.H.I.)
    Metadata
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    Document Type
    Journal Article
    Citations
    Kettunen, J., Tukiainen, T., Sarin, A. -P., Ortega-Alonso, A., Tikkanen, E., Lyytikainen, L. -P., Kangas, A. J., Soininen, P., Wuertz, P., Silander, K., Dick, D. M., Rose, R. J., Savolainen, M. J., Viikari, J., Kahonen, M., Lehtimaki, T., Pietilainen, K. H., Inouye, M., McCarthy, M. I. ,... Ripatti, S. (2012). Genome-wide association study identifies multiple loci influencing human serum metabolite levels. NATURE GENETICS, 44 (3), pp.269-U65. https://doi.org/10.1038/ng.1073.
    Access Status
    Access this item via the Open Access location
    URI
    http://hdl.handle.net/11343/33059
    DOI
    10.1038/ng.1073
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3605033
    Description

    C1 - Journal Articles Refereed
    Abstract
    Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10(-10)) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.
    Keywords
    Medical Biochemistry: Amino Acids and Metabolites; Genomics; Expanding Knowledge in the Biological Sciences

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