Genome-wide association study for serum metabolome reveals 57 associated loci for biomarkers of complex metabolic diseases. J. Kettunen1, T. Haller2, A. Demirkan3, R. Rawal4, T. Tukiainen5, T. Esko2,5, L. C. Karssen3, C. Gieger4, H. K. Dharuri6, J. B. van Klinken6, K. W. van Dijk6, M. Waldenberger7, M. Ala-Korpela8, P. Soininen8, A. J. Kangas8, T. Lehtimäki9, M. Perola10, C. van Duijn3, J. G. Eriksson11, T. Illig12, A. Metspalu2, A. Jula13, M.-R. Järvelin14, J. Kaprio15, O. Raitakari16, V. Salomaa17, A. Palotie1, S. Ripatti1 1) Institute for Molecular Medicine, Helsinki, Finland, FIMM; 2) Estonian Genome Center, University of Tartu, Tartu, Estonia; 3) Genetic Epidemiology Unit, Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands; 4) Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; 5) Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, USA; 6) Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands; 7) Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; 8) Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu, Finland; 9) Department of Clinical Chemistry, Fimlab Laboratories, Tampere University Hospital and University of Tampere, Finland; 10) Unit for Genetic Epidemiology, National Institute for Health and Welfare, Helsinki, Finland; 11) Department of General Practice and Primary Health Care, University of Helsinki and the Helsinki University Hospital, Helsinki, Finland; 12) Hannover Unified Biobank, Hannover Medical School, Hannover, Germany; 13) Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland; 14) Department of Epidemiology and Biostatistics, Imperial College, London, UK; 15) Department of Public Health, University of Helsinki, Helsinki, Finland; 16) Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; 17) Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
Our aim was to search for genetic determinants for circulating biomarkers of complex metabolic diseases to provide tools for causal inference between biomarker and disease. We performed a genome-wide association study (GWAS) for 123 metabolites measured using nuclear magnetic resonance spectroscopy (NMR). We had 10 European study populations with both metabolite data and genome-wide SNP data available, totaling up to 17 800 individuals. The SNP arrays were extended with imputation to 42 million markers by using April 2012 release of the 1000 Genomes project. We found 57 independent loci associated with one or more metabolic variables using multiple testing corrected genome-wide significance (p < 2.7*10-9). Out of these 57 significant loci, the lead associated measure was lipoprotein related in 24 cases, lipid related in 5 cases and small molecule or protein in 28 cases. In 7 cases the variant with strongest association was insertion or deletion. Out of the 57 significant loci, 12 loci were novel meaning that same locus had not been associated with same or similar metabolic measure before. Of the 12 novel loci, 1 was for lipoproteins, 10 were for small molecules and 1 for lipid measures. Further, we found novel loci for recently found type 2 diabetes biomarkers: One locus for phenylalanine and three for glycine. In addition, we found a new locus for creatinine, which is a biomarker for chronic kidney disease. The new loci for type 2 diabetes biomarkers harbored enzymes known to be involved in the metabolism of glycine or phenylalanine. The phenylalanine locus contained the phenylalanine hydroxylase gene (OMIM 612349), which harbors known variants cause phenylketonuria (PKU). The glycine loci contained the two genes of glycine cleavage system. Mutations in these genes have been shown to cause Mendelian disease Glycine encephalopathy (GE, OMIM 605899). PKU and GE both include patients with a spectrum of symptomatic severity. These three loci could potentially be associated with less severe forms or trait components of GE and PKU, however, screening in relevant patient samples is required. As a conclusion, this study provides new genetic determinants for several complex disease biomarkers and therefore provides better tools for evaluating causality between biomarkers and complex diseases such as type 2 diabetes and chronic kidney disease.
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