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

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.

Christian Gieger | Toomas Haller | Andres Metspalu | Jerzy Adamski | Karsten Suhre | Mark I McCarthy | Peter A C 't Hoen | Lude Franke | Nicholas G Martin | Harish Dharuri | Konstantin Strauch | Tõnu Esko | Cornelia M van Duijn | Harm-Jan Westra | Cornelia Prehn | Thomas Illig | Massimo Mangino | Dorret I Boomsma | Gonneke Willemsen | Eco J C de Geus | René Pool | Aaron Isaacs | Marian Beekman | Stefan Böhringer | Tim D Spector | Dale R Nyholt | Idil Yet | Jordana T Bell | Najaf Amin | Ann-Kristin Petersen | C. Gieger | T. Spector | J. Bell | M. McCarthy | K. Strauch | M. Mangino | N. Martin | J. Whitfield | B. Penninx | G. Willemsen | A. Metspalu | T. Esko | G. Montgomery | T. Haller | T. Illig | D. Boomsma | E. D. de Geus | D. Nyholt | J. Hottenga | A. Isaacs | M. Beekman | H. Westra | A. D. de Craen | E. V. van Leeuwen | C. V. van Duijn | L. Franke | K. Suhre | N. Amin | A. Demirkan | A. Petersen | A. Henders | G. Zhu | S. Böhringer | J. Adamski | R. Jansen | K. V. van Dijk | R. Pool | C. Prehn | W. Römisch-Margl | G. V. van Ommen | H. Draisma | I. Yet | Michael Kobl | Gu Zhu | Werner Römisch-Margl | P Eline Slagboom | Brenda W Penninx | John B Whitfield | Grant W Montgomery | Gert-Jan B van Ommen | Jouke Jan Hottenga | Rick Jansen | Harmen H M Draisma | Anton J M de Craen | J. V. van Klinken | Anjali K Henders | Ayşe Demirkan | Elisabeth M van Leeuwen | Anika A M Vaarhorst | Ko Willems van Dijk | Michael Kobl | Jan Bert van Klinken | Harish Dharuri | P. Eline Slagboom | A. Vaarhorst | P. ’. ’t Hoen

[1]  L. Cupples,et al.  Gene-nutrient interactions with dietary fat modulate the association between genetic variation of the ACSL1 gene and metabolic syndrome , 2010, Journal of Lipid Research.

[2]  J. J. Wang,et al.  Genome-wide meta-analysis identifies six novel loci associated with habitual coffee consumption , 2014, Molecular Psychiatry.

[3]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[4]  G. Willemsen,et al.  Familial Resemblance for Serum Metabolite Concentrations , 2013, Twin Research and Human Genetics.

[5]  John F. Peden,et al.  Thirty-five common variants for coronary artery disease: the fruits of much collaborative labour , 2011, Human molecular genetics.

[6]  F. Collins,et al.  Potential etiologic and functional implications of genome-wide association loci for human diseases and traits , 2009, Proceedings of the National Academy of Sciences.

[7]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[8]  Peter Donnelly,et al.  A Genome-Wide Metabolic QTL Analysis in Europeans Implicates Two Loci Shaped by Recent Positive Selection , 2011, PLoS genetics.

[9]  Kimmo Kaski,et al.  Detailed metabolic and genetic characterization reveals new associations for 30 known lipid loci. , 2012, Human molecular genetics.

[10]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[11]  M. Daly,et al.  Estimation of the multiple testing burden for genomewide association studies of nearly all common variants , 2008, Genetic epidemiology.

[12]  J. Naylor,et al.  Mendelian inheritance in man: A catalog of human genes and genetic disorders , 1996 .

[13]  C. Gieger,et al.  Serum metabolite concentrations and decreased GFR in the general population. , 2012, American journal of kidney diseases : the official journal of the National Kidney Foundation.

[14]  A. Hamsten,et al.  Fatty acid handling protein expression in adipose tissue, fatty acid composition of adipose tissue and serum, and markers of insulin resistance , 2006, European Journal of Clinical Nutrition.

[15]  Zhaohui S. Qin,et al.  A second generation human haplotype map of over 3.1 million SNPs , 2007, Nature.

[16]  C. Gieger,et al.  Human metabolic individuality in biomedical and pharmaceutical research , 2011, Nature.

[17]  S. Hazen,et al.  Diminished global arginine bioavailability and increased arginine catabolism as metabolic profile of increased cardiovascular risk. , 2009, Journal of the American College of Cardiology.

[18]  Ralf Herwig,et al.  ConsensusPathDB: toward a more complete picture of cell biology , 2010, Nucleic Acids Res..

[19]  Markus Perola,et al.  Genome-wide association study identifies multiple loci influencing human serum metabolite levels , 2012, Nature Genetics.

[20]  Jerzy Adamski,et al.  Procedure for tissue sample preparation and metabolite extraction for high-throughput targeted metabolomics , 2011, Metabolomics.

[21]  Christian Gieger,et al.  Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture , 2013, Nature Genetics.

[22]  Christian Gieger,et al.  Genetic variation in metabolic phenotypes: study designs and applications , 2012, Nature Reviews Genetics.

[23]  Michael Boehnke,et al.  LocusZoom: regional visualization of genome-wide association scan results , 2010, Bioinform..

[24]  Christian Gieger,et al.  Genetics Meets Metabolomics: A Genome-Wide Association Study of Metabolite Profiles in Human Serum , 2008, PLoS genetics.

[25]  A. Park,et al.  CENTER FOR DRUG EVALUATION AND RESEARCH , 2009 .

[26]  Milton H. Saier,et al.  TCDB: the Transporter Classification Database for membrane transport protein analyses and information , 2005, Nucleic Acids Res..

[27]  Cwi Cwi Overview research activities 1996 / Centrum voor Wiskunde en Informatica (CWI) , 1995 .

[28]  N. Mehta Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. , 2011, Circulation. Cardiovascular genetics.

[29]  C. V. van Duijn,et al.  Genetics of the human metabolome, what is next? , 2014, Biochimica et biophysica acta.

[30]  Ming-Huei Chen,et al.  A genome-wide association study of the human metabolome in a community-based cohort. , 2013, Cell metabolism.

[31]  Thomas Meitinger,et al.  Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations , 2009, PLoS genetics.

[32]  P. Visscher,et al.  Beyond the Single SNP: Emerging Developments in Mendelian Randomization in the “Omics” Era , 2014, Current Epidemiology Reports.

[33]  Reedik Mägi,et al.  GWAMA: software for genome-wide association meta-analysis , 2010, BMC Bioinformatics.

[34]  Yurii S. Aulchenko,et al.  Genome-Wide Association Study Identifies Novel Loci Associated with Circulating Phospho- and Sphingolipid Concentrations , 2012, PLoS genetics.

[35]  Eric Boerwinkle,et al.  Genetic Determinants Influencing Human Serum Metabolome among African Americans , 2014, PLoS genetics.

[36]  John P. Overington,et al.  An atlas of genetic influences on human blood metabolites , 2014, Nature Genetics.

[37]  Fabian J Theis,et al.  Discovery of Sexual Dimorphisms in Metabolic and Genetic Biomarkers , 2011, PLoS genetics.

[38]  D. Ramotar,et al.  The Human Carnitine Transporter SLC22A16 Mediates High Affinity Uptake of the Anticancer Polyamine Analogue Bleomycin-A5* , 2009, The Journal of Biological Chemistry.

[39]  Michele Magrane,et al.  UniProt Knowledgebase: a hub of integrated protein data , 2011, Database J. Biol. Databases Curation.

[40]  D Jamieson,et al.  Influence of pharmacogenetics on response and toxicity in breast cancer patients treated with doxorubicin and cyclophosphamide , 2010, British Journal of Cancer.

[41]  J. Li,et al.  Adjusting multiple testing in multilocus analyses using the eigenvalues of a correlation matrix , 2005, Heredity.

[42]  P. Visscher,et al.  Common polygenic variation contributes to risk of schizophrenia and bipolar disorder , 2009, Nature.

[43]  Yun Li,et al.  METAL: fast and efficient meta-analysis of genomewide association scans , 2010, Bioinform..

[44]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[45]  Christian Gieger,et al.  A genome-wide perspective of genetic variation in human metabolism , 2010, Nature Genetics.

[46]  P. Visscher,et al.  GCTA: a tool for genome-wide complex trait analysis. , 2011, American journal of human genetics.

[47]  A. Moser,et al.  Functional characterization of novel mutations in GNPAT and AGPS, causing rhizomelic chondrodysplasia punctata (RCDP) types 2 and 3 , 2012, Human mutation.

[48]  Cwi Cwi Vakantiecursus 2005 Centrum voor Wiskunde en Informatica : De schijf van vijf, Amsterdam en Eindhoven, 2005 , 2005 .

[49]  M. Ashburner,et al.  Gene Ontology: tool for the unification of biology , 2000, Nature Genetics.

[50]  Ron D. Appel,et al.  ExPASy: the proteomics server for in-depth protein knowledge and analysis , 2003, Nucleic Acids Res..

[51]  T. Pieber,et al.  Multifactorial risk factor intervention in patients with Type 2 diabetes improves arginine bioavailability ratios , 2012, Diabetic medicine : a journal of the British Diabetic Association.

[52]  N. Wray,et al.  Genetic risk profiles for depression and anxiety in adult and elderly cohorts , 2010, Molecular Psychiatry.

[53]  J. Danesh,et al.  Large-scale association analysis identifies new risk loci for coronary artery disease , 2013 .