Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels

Draisma, H.H.M., Pool, R., Kobl, M., Jansen, R., Petersen, A.-K., Vaarhorst, A.A.M., Yet, I., Haller, T., Demirkan, A., Esko, T., Zhu, G., Böhringer, S., Beekman, M., Van Klinken, J.B., Römisch-Margl, W., Prehn, C., Adamski, J., De Craen, A.J.M., Van Leeuwen, E.M., Amin, N., Dharuri, H., Westra, H.-J., Franke, L., De Geus, E.J.C., Hottenga, J.J., Willemsen, G., Henders, A.K., Montgomery, G.W., Nyholt, D.R., Whitfield, J.B., Penninx, B.W., Spector, T.D., Metspalu, A., Eline Slagboom, P., Van Dijk, K.W., 'T Hoen, P.A.C., Strauch, K., Martin, N.G., Van Ommen, G.-J.B., Illig, T., Bell, J.T., Mangino, M., Suhre, K., McCarthy, M.I., Gieger, C., Isaacs, A., Van Duijn, C.M., & Boomsma, D.I. (2015) Genome-wide association study identifies novel genetic variants contributing to variation in blood metabolite levels. Nature Communications, 6(7208).

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Abstract

Metabolites are small molecules involved in cellular metabolism, which can be detected in biological samples using metabolomic techniques. Here we present the results of genome-wide association and meta-analyses for variation in the blood serum levels of 129 metabolites as measured by the Biocrates metabolomic platform. In a discovery sample of 7,478 individuals of European descent, we find 4,068 genome- and metabolome-wide significant (Z-test, P<1.09 × 10−9) associations between single-nucleotide polymorphisms (SNPs) and metabolites, involving 59 independent SNPs and 85 metabolites. Five of the fifty-nine independent SNPs are new for serum metabolite levels, and were followed-up for replication in an independent sample (N=1,182). The novel SNPs are located in or near genes encoding metabolite transporter proteins or enzymes (SLC22A16, ARG1, AGPS and ACSL1) that have demonstrated biomedical or pharmaceutical importance. The further characterization of genetic influences on metabolic phenotypes is important for progress in biological and medical research.

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16 citations in Scopus
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16 citations in Web of Science®

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ID Code: 91742
Item Type: Journal Article
Refereed: Yes
Keywords: amino acid, biomarker, concentration (composition), drug, enzyme, gene expression, genetic analysis, genetic variation, genome, identification method, metabolism, metabolite, mutation, phenotype, serum, ACSL1 gene, AGPS gene, ARG1 gene, Article, blood level, European, gene, genetic association, genetic variability, human, metabolite, metabolome, metabolomics, phenotype, single nucleotide polymorphism, SLC22A16 gene
DOI: 10.1038/ncomms8208
ISSN: 2041-1723
Divisions: Current > Schools > School of Biomedical Sciences
Current > QUT Faculties and Divisions > Faculty of Health
Current > Institutes > Institute of Health and Biomedical Innovation
Copyright Owner: Copyright 2015 Macmillan Publishers Limited
Deposited On: 11 Jan 2016 22:43
Last Modified: 10 Apr 2017 18:14

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