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A genome-wide association study of metabolic traits in human urine


We present a genome-wide association study of metabolic traits in human urine, designed to investigate the detoxification capacity of the human body. Using NMR spectroscopy, we tested for associations between 59 metabolites in urine from 862 male participants in the population-based SHIP study. We replicated the results using 1,039 additional samples of the same study, including a 5-year follow-up, and 992 samples from the independent KORA study. We report five loci with joint P values of association from 3.2 × 10−19 to 2.1 × 10−182. Variants at three of these loci have previously been linked with important clinical outcomes: SLC7A9 is a risk locus for chronic kidney disease, NAT2 for coronary artery disease and genotype-dependent response to drug toxicity, and SLC6A20 for iminoglycinuria. Moreover, we identify rs37369 in AGXT2 as the genetic basis of hyper-β-aminoisobutyric aciduria.

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Figure 1: Manhattan plots for metabolic traits.
Figure 2: Association between 3-aminoisobutyrate concentrations and coding SNP rs37369 (V140I) in the AGXT2 gene.

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SHIP is part of the Community Medicine Research net of the University of Greifswald, Germany, which is funded by the German Federal Ministry of Education and Research (BMBF; grants 01ZZ9603, 01ZZ0103 and 01ZZ0403), the German Ministry of Cultural Affairs and the Social Ministry of the Federal State of Mecklenburg–West Pomerania. Genome-wide studies were supported by BMBF (grant 03ZIK012) and a joint grant from Siemens Healthcare and the Federal State of Mecklenburg–West Pomerania. The University of Greifswald is a member of the Siemens 'Center of Knowledge Interchange' program. NMR studies were supported by Bruker BioSpin. This study was also supported in part by a grant from BMBF to the German Center for Diabetes Research (DZD e.V.), and by the Genomics of Lipid-associated Disorders project of the Austrian Genome Research Programme. This work is also part of the research project Greifswald Approach to Individualized Medicine (GANI_MED). The GANI_MED consortium is funded by the BMBF and the Ministry of Cultural Affairs of the Federal State of Mecklenburg–West Pomerania (03IS2061A). The KORA research platform and the 'Monitoring trends and determinants on cardiovascular diseases' (MONICA) Augsburg studies were initiated and financed by the Helmholtz Zentrum München–National Research Center for Environmental Health, which is funded by the German Federal Ministry of Education, Science, Research and Technology and by the State of Bavaria. Part of this work was financed by the German National Genome Research Network (NGFNPlus 01GS0823). Part of this research was supported within the Munich Center of Health Sciences (MC Health) as part of LMUinnovativ. J.R. is supported by Deutsche Forschungsgemeinschaft Graduiertenkolleg 'GRK 1563, Regulation and Evolution of Cellular Systems' (RECESS). Computing resources have been provided by the Leibniz Supercomputing Centre of the Bavarian Academy of Sciences and Humanities (HLRB project h1231) and the DEISA Extreme Computing Initiative (project PHAGEDA). We thank P. Lichtner, G. Eckstein, G. Fischer, T. Strom and all other members of the Helmholtz Zentrum München genotyping staff for generating the KORA SNP data set, as well as all field staff members involved in the MONICA and KORA Augsburg studies. The KORA group consists of H.E. Wichmann (speaker), A. Peters, C. Meisinger, T. Illig, R. Holle, J. John and their co-workers, who are responsible for the design and conduct of the KORA studies. We thank all participants in the SHIP and KORA studies for donating their blood, urine and time.

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Authors and Affiliations



K.S., H.W. and M.N. conceived and designed the experiments. H.W., N.F., R.H., K.M., C.W., A.K. and U.V. performed the experiments. K.S. and J.R. performed statistical analysis. K.S., H.W., J.R., F.K., N.F., D.C., A.T., C.G. and W.R.-M. analyzed the data. W.H., T.K., S.B.F., H.V. and R.B. designed and conducted the SHIP study. C.M, H.-E.W. and T.I. designed and conducted the KORA study. C.M., H.-E.W., T.I., H.K.K. and M.N. contributed reagents, materials and analysis tools. K.S., H.W., F.K., C.G. and M.N. wrote the paper.

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Correspondence to Karsten Suhre.

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Competing interests

D.C. is an employee of Chenomx Inc., which sells the software suite used for the NMR analysis in this study.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–3 and Supplementary Note. (PDF 1196 kb)

Supplementary Table 1

MS-Excel data file, providing 15,475 associations that are significant at the 5% level after correcting for testing 1,720 metabolic traits at a single locus (p < 2.9×10−5) and that have a p-gain > 59 in the case of ratios (XLS 8487 kb)

Supplementary Table 2

MS-Excel data file providing associations based on 1000-Genomes data imputed genotypes at the five loci reported in Table 1 (XLS 11483 kb)

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Suhre, K., Wallaschofski, H., Raffler, J. et al. A genome-wide association study of metabolic traits in human urine. Nat Genet 43, 565–569 (2011).

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