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Human metabolic individuality in biomedical and pharmaceutical research
Open accessAbstract
Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10-60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research.
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“Comparing to most GWAS findings, these associations showed much larger effect sizes than those for disease traits (Suhre et al., 2011)”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Suhre et al., 2011
In the citing paper
“A non-targeted genome-metabolome-wide study analyzed more than 250 metabolites from 60 known pathways in human serum samples. Combined with genome-wide SNP data from the same 2,820 individuals with metabolomic data, 37 mQTLs were significant at a stringent genome-wide threshold.”
From Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases (2016) · cites this paper as Suhre et al., 2011
In the citing paper
“A number of loci associated with variations in the concentration of endogenous metabolites could be identified in genome-wide analysis studies, and many of these genes were coding for metabolic enzymes (180-182).”
From The food metabolome: a window over dietary exposure (2014) · cites this paper as [180]
In the citing paper
“Other polymorphisms had previously been shown to associate with cardiovascular disorders, gout and type-2 diabetes, all of which are known to involve changes in core metabolic pathways (Suhre et al., 2011).”
From Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us? (2012) · cites this paper as Suhre et al., 2011
In the citing paper
“However, there were also associations with drug toxicity, Crohn’s disease and other conditions not conventionally thought to be related to intermediary metabolism (Suhre et al., 2011).”
From Cellular Metabolism and Disease: What Do Metabolic Outliers Teach Us? (2012) · cites this paper as Suhre et al., 2011
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PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Hindorff, L. A., Sethupathy, P., Junkins, H. A., Ramos, E. M., Mehta, J. P., Collins, F. S., & Manolio, T. A. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0903103106 · Cited by 4,013
Howie, B. N., Donnelly, P., & Marchini, J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000529 · Cited by 3,928
Biological, clinical and population relevance of 95 loci for blood lipids
Teslovich, T. M., Musunuru, K., Smith, A. V., Edmondson, A. C., Stylianou, I. M., Koseki, M., Pirruccello, J. P., Ripatti, S., Chasman, D. I., Willer, C. J., et al. (2010) · Nature · doi:10.1038/nature09270 · Cited by 3,487
Self-citationMerlin—rapid analysis of dense genetic maps using sparse gene flow trees
Abecasis, G. R., Cherny, S. S., Cookson, W., & Cardon, L. R. (2001) · Nature Genetics · doi:10.1038/ng786 · Cited by 3,323
Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression
Sreekumar, A., Poisson, L., Rajendiran, T. M., Khan, A. P., Cao, Q., Yu, J., Laxman, B., Mehra, R., Lonigro, R. J., Li, Y., et al. (2009) · Nature · doi:10.1038/nature07762 · Cited by 2,269
New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk
DIAGRAM Consortium, Dupuis, J., GIANT Consortium, Global BPgen Consortium, Anders Hamsten on behalf of Procardis Consortium, the MAGIC investigators, Langenberg, C., Prokopenko, I., Saxena, R., Soranzo, N., et al. (2010) · Nature Genetics · doi:10.1038/ng.520 · Cited by 2,166
Self-citationSLCO1B1 Variants and Statin-Induced Myopathy — A Genomewide Study
(2008) · New England Journal of Medicine · doi:10.1056/nejmoa0801936 · Cited by 2,043
Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease
Cardiogenics, Schunkert, H., the CARDIoGRAM Consortium, König, I. R., Kathiresan, S., Reilly, M. P., Assimes, T. L., Holm, H., Preuss, M., Stewart, A. F. R., et al. (2011) · Nature Genetics · doi:10.1038/ng.784 · Cited by 1,866
Self-citationEvans, A. M., DeHaven, C. D., Barrett, T., Mitchell, M. W., & Milgram, K. E. (2009) · Analytical Chemistry · doi:10.1021/ac901536h · Cited by 1,317
Loci influencing lipid levels and coronary heart disease risk in 16 European population cohorts
Aulchenko, Y. S., Janssens, A. C. J. W., Albert Hofman, D., Isaacs, A. J., Sijbrands, E. J. G., Witteman, J. C. M., van Duijn, C. M., Ripatti, S., Lindqvist, I., Perola, M., et al. (2008) · Nature Genetics · doi:10.1038/ng.269 · Cited by 860
Self-citationNew loci associated with kidney function and chronic kidney disease
Köttgen, A., Pattaro, C., Böger, C. A., Fuchsberger, C., Olden, M., Glazer, N. L., Parsa, A., Gao, X., Yang, Q., Smith, A. V., et al. (2010) · Nature Genetics · doi:10.1038/ng.568 · Cited by 807
Self-citationGenetics meets metabolomics: a genome-wide association study of metabolite profiles in human serum
Gieger, C., Geistlinger, L., Altmaier, E., Hrabé de Angelis, M., Kronenberg, F., Meitinger, T., Mewes, H.-W., Wichmann, H.-E., Weinberger, K. M., Adamski, J., et al. (2008) · PLoS Genetics · doi:10.1371/journal.pgen.1000282 · Cited by 737
Self-citationBone mineral density, osteoporosis, and osteoporotic fractures: a genome-wide association study
Richards, J. B., Rivadeneira, F., Inouye, M., Pastinen, T., Soranzo, N., Wilson, S. G., Andrew, T., Falchi, M., Gwilliam, R., Ahmadi, K. R., et al. (2008) · The Lancet · doi:10.1016/s0140-6736(08)60599-1 · Cited by 685
Self-citationKolz, M., Johnson, T., Sanna, S., Teumer, A., Vitart, V., Perola, M., Mangino, M., Albrecht, E., Wallace, C., Farrall, M., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000504 · Cited by 666
Self-citationA genome-wide perspective of genetic variation in human metabolism
Illig, T., Gieger, C., Zhai, G., Römisch-Margl, W., Wang-Sattler, R., Prehn, C., Altmaier, E., Kastenmüller, G., Kato, B. S., Mewes, H.-W., et al. (2010) · Nature Genetics · doi:10.1038/ng.507 · Cited by 653
Self-citationMetabolic Footprint of Diabetes: A Multiplatform Metabolomics Study in an Epidemiological Setting
Suhre, K., Meisinger, C., Döring, A., Altmaier, E., Belcredi, P., Gieger, C., Chang, D., Milburn, M. V., Gall, W. E., Weinberger, K. M., et al. (2010) · PLoS ONE · doi:10.1371/journal.pone.0013953 · Cited by 567
Self-citationSoranzo, N., Spector, T. D., Mangino, M., Kuehnel, B., Rendon, A., Teumer, A., Willenborg, C., Wright, B. J., Chen, L., Li, M., et al. (2009) · Nature Genetics · doi:10.1038/ng.467 · Cited by 527
Self-citationThe SLC22 drug transporter family
Koepsell, H., & Endou, H. (2004) · Pflügers Archiv - European Journal of Physiology · doi:10.1007/s00424-003-1089-9 · Cited by 521
Analysis of the Adult Human Plasma Metabolome
Lawton, K. A., Berger, A., Mitchell, M., Milgram, K. E., Evans, A. M., Guo, L., Hanson, R. W., Kalhan, S. C., Ryals, J. A., & Milburn, M. V. (2008) · Pharmacogenomics · doi:10.2217/14622416.9.4.383 · Cited by 490
Self-citationEffect of Genetic Variation in the Organic Cation Transporter 1, OCT1, on Metformin Pharmacokinetics
Shu, Y., Brown, C., Castro, R. A., Shi, R., Lin, E., Owen, R., Sheardown, S., Yue, L., Burchard, E. G., Brett, C., et al. (2007) · Clinical Pharmacology & Therapeutics · doi:10.1038/sj.clpt.6100275 · Cited by 480
Yuan, X., Waterworth, D. M., Perry, J. R. B., Lim, N., Song, K. S., Chambers, J. C., Zhang, W., Vollenweider, P., Stirnadel-Farrant, H. A., Johnson, T., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.09.012 · Cited by 457
SLC2A9 influences uric acid concentrations with pronounced sex-specific effects
Döring, A., Gieger, C., Mehta, D., Gohlke, H., Prokisch, H., Coassin, S., Fischer, G., Henke, K., Klopp, N., Kronenberg, F., et al. (2008) · Nature Genetics · doi:10.1038/ng.107 · Cited by 444
Self-citationAndrew, T., Hart, D. J., Snieder, H., de Lange, M., Spector, T. D., & MacGregor, A. J. (2001) · Twin Research · doi:10.1375/1369052012803 · Cited by 440
Self-citationRaychaudhuri, S., Plenge, R. M., Rossin, E. J., Ng, A., Purcell, S., Sklar, P. B., Scolnick, E. M., Xavier, R. J., Altshuler, D., & Daly, M. J. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000534 · Cited by 427
KORA-gen - Resource for Population Genetics, Controls and a Broad Spectrum of Disease Phenotypes
Wichmann, H. ‐., Gieger, C., & Illig, T. (2005) · Das Gesundheitswesen · doi:10.1055/s-2005-858226 · Cited by 417
Self-citationSLC2A9 Is a High-Capacity Urate Transporter in Humans
Caulfield, M. J., Munroe, P. B., O’Neill, D., Witkowska, K., Charchar, F. J., Doblado, M., Evans, S., Eyheramendy, S., Onipinla, A. K., Howard, P., et al. (2008) · PLoS Medicine · doi:10.1371/journal.pmed.0050197 · Cited by 375
Self-citationIntegrating genotype and phenotype information: an overview of the PharmGKB project
Klein, T. E., Chang, J. T., Cho, M. K., Easton, K. L., Fergerson, R. W., Hewett, M., Lin, Z., Liu, Y. I., Liu, S., Oliver, D. E., et al. (2001) · The Pharmacogenomics Journal · doi:10.1038/sj.tpj.6500035 · Cited by 359
Trégouët, D., Heath, S. C., Saut, N., Biron‐Andréani, C., Schved, J., Pernod, G., Galan, P., Drouet, L. O., Zélénika, D., Juhan-Vague, I., et al. (2009) · Blood · doi:10.1182/blood-2008-11-190389 · Cited by 323
Andrew, T., Hart, D. J., Snieder, H., de Lange, M., Spector, T. D., & MacGregor, A. J. (2001) · Twin Research · doi:10.1375/twin.4.6.464 · Cited by 289
Self-citationSoranzo, N., Rivadeneira, F., Chinappen-Horsley, U., Malkina, I., Richards, J. B., Hammond, N., Stolk, L., Nica, A., Inouye, M., Albert Hofman, D., et al. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000445 · Cited by 276
Self-citationGenetic loci influencing kidney function and chronic kidney disease
Chambers, J. C., Zhang, W., Lord, G. M., van der Harst, P., Lawlor, D. A., Sehmi, J., Gale, D. P., Wass, M. N., Ahmadi, K. R., Bakker, S. J. L., et al. (2010) · Nature Genetics · doi:10.1038/ng.566 · Cited by 275
Self-citationChen, Y., Li, S., Brown, C., Cheatham, S. C., Castro, R. A., Leabman, M. K., Urban, T. J., Chen, L., Yee, S. W., Choi, J. H., et al. (2009) · Pharmacogenetics and Genomics · doi:10.1097/fpc.0b013e32832cc7e9 · Cited by 249
Genome-wide association meta-analysis for total serum bilirubin levels
Johnson, A. D., Kavousi, M., Smith, A. V., Chen, M., Dehghan, A., Aspelund, T., Lin, J.-P., van Duijn, C. M., Harris, T. B., Cupples, L. A., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp202 · Cited by 235
A genotype calling algorithm for the Illumina BeadArray platform
Teo, Y. Y., Inouye, M., Small, K. S., Gwilliam, R., Deloukas, P., Kwiatkowski, D. P., & Clark, T. G. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm443 · Cited by 216
Self-citationOhta, T., Masutomi, N., Tsutsui, N., Sakairi, T., Mitchell, M., Milburn, M. V., Ryals, J. A., Beebe, K. D., & Guo, L. (2009) · Toxicologic Pathology · doi:10.1177/0192623309336152 · Cited by 213
Self-citationHuang, R. S., Duan, S., Bleibel, W. K., Kistner, E. O., Zhang, W., Clark, T. A., Chen, T. X., Schweitzer, A. C., Blume, J. E., Cox, N. J., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0703736104 · Cited by 197
Sanna, S., Busonero, F., Maschio, A., McArdle, P. F., Usala, G., Dei, M., Lai, S., Mulas, A., Piras, M. G., Perseu, L., et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp203 · Cited by 128
Altmaier, E., Ramsay, S. L., Graber, A., Mewes, H., Weinberger, K. M., & Suhre, K. (2008) · Endocrinology · doi:10.1210/en.2007-1747 · Cited by 124
Self-citationZhai, G., Teumer, A., Stolk, L., Perry, J. R. B., Vandenput, L., Coviello, A. D., Koster, A., Bell, J. T., Bhasin, S., Eriksson, J., et al. (2011) · PLoS Genetics · doi:10.1371/journal.pgen.1002025 · Cited by 107
Self-citationThe SLC16 monocaboxylate transporter family
Meredith, D., & Christian, H. (2008) · Xenobiotica · doi:10.1080/00498250802010868 · Cited by 103
Self-citationLankisch, T. O., Schulz, C. U., Zwingers, T., Erichsen, T. J., Manns, M. P., Heinemann, V., & Strassburg, C. P. (2008) · Cancer Epidemiology Biomarkers & Prevention · doi:10.1158/1055-9965.epi-07-2517 · Cited by 93
Mannose Enters Mammalian Cells Using a Specific Transporter That Is Insensitive to Glucose
Panneerselvam, K., & Freeze, H. H. (1996) · Journal of Biological Chemistry · doi:10.1074/jbc.271.16.9417 · Cited by 90
Deeken, J. F., Cormier, T., Price, D. K., Sissung, T. M., Steinberg, S. M., Tran, K., Liewehr, D. J., Dahut, W. L., Miao, X., & Figg, W. D. (2009) · The Pharmacogenomics Journal · doi:10.1038/tpj.2009.57 · Cited by 79
Amino-Acid Sequence and the Occurrence of Phosphorus in Human Fibrinopeptides
Blombäck, B., Blombäck, M., Edman, P., & HESSEL, B. (1962) · Nature · doi:10.1038/193883a0 · Cited by 73
Davies, N., Hayden, R. E., Simpson, P. J., Birtwistle, J., Mayer, K., Ride, J. P., & Bunce, C. M. (2009) · Cancer Research · doi:10.1158/0008-5472.can-08-4533 · Cited by 66
Meredith, D. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m313922200 · Cited by 36
Self-citationGetting biological about the genetics of diabetes
Newgard, C. B., & Attie, A. (2010) · Nature Medicine · doi:10.1038/nm0410-388 · Cited by 35
Hepatic glycogen breakdown is implicated in the maintenance of plasma mannose concentration
Taguchi, T., YAMASHITA, E., Mizutani, T., Nakajima, H., Yabuuchi, M., Asano, N., & Miwa, I. (2004) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.00451.2004 · Cited by 33
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Mootha, V. K., & Hirschhorn, J. N. (2010) · Nature Genetics · doi:10.1038/ng0210-97 · Cited by 24
Increased phosphate content of fibrinogen in vivo correlates with alteration in fibrinogen behaviour
Martin, S. C., Ekman, P., Forsberg, P.-O., & Ersmark, H. (1992) · Thrombosis Research · doi:10.1016/0049-3848(92)90059-j · Cited by 18
Management and Scientific Manpower
(1962) · Nature · doi:10.1038/193833a0 · Cited by 5
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Metadata
- Authors
- CARDIoGRAM, Suhre, K., Shin, S.-Y., Petersen, A.-K., Mohney, R. P., Meredith, D., Wägele, B., Altmaier, E., Deloukas, P., Erdmann, J., Grundberg, E., Hammond, C. J., de Angelis, M. H., Kastenmüller, G., Köttgen, A., Kronenberg, F., Mangino, M., Meisinger, C., Meitinger, T., Mewes, H.-W., Milburn, M. V., Prehn, C., Raffler, J., Ried, J. S., Römisch-Margl, W., Samani, N. J., Small, K. S., -Erich Wichmann, H., Zhai, G., Illig, T., Spector, T. D., Adamski, J., Soranzo, N., & Gieger, C.
- Affiliations
- Helmholtz Munich (DE)
- Wellcome Sanger Institute (GB)
- Oxford Brookes University (GB)
- St Thomas' Hospital (GB)
- King's College London (GB)
- University Medical Center Freiburg (DE)
- Innsbruck Medical University (AT)
- TUM Klinikum (DE)
- Corresponding author
- Suhre, Karsten
- Soranzo, Nicole
- ORCID
- Suhre, Karsten
- Shin, So-Youn
- Mohney, Robert P.
- Meredith, David
- Deloukas, Panos
- Erdmann, Jeanette
- Grundberg, Elin
- Hammond, Christopher J.
- Kastenmüller, Gabi
- Köttgen, Anna
- Kronenberg, Florian
- Mangino, Massimo
- Meisinger, Christa
- Meitinger, Thomas
- Mewes, Hans-Werner
- Prehn, Cornelia
- Raffler, Johannes
- Samani, Nilesh J.
- Small, Kerrin S.
- Zhai, Guangju
- Spector, Tim D.
- Adamski, Jerzy
- Soranzo, Nicole
- Gieger, Christian
- Venue
- Nature
- Published
- 2011-08-31
- Volume
- 477
- Issue
- 7362
- Pages
- 54-60
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC3832838
- OpenAlex
- W2166711199
- Cited by
- 1,017
- References
- 52
- Citations by year
- 2026: 31 · 2025: 34 · 2024: 53 · 2023: 55 · 2022: 69 · 2021: 63 · 2020: 73 · 2019: 48 · 2018: 69 · 2017: 68 · 2016: 84 · 2015: 82 · 2014: 89 · 2013: 88 · 2012: 95
- FWCI
- 57.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- IRIS (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Leicester Research Archive (University of Leicester) (submittedVersion)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- mediaTUM (Technical University of Munich) (submittedVersion, other-oa)
- Site cant be reached (submittedVersion)
- Explore Bristol Research (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- OPUS (Augsburg University) (submittedVersion)
- Funders
- Wellcome Trust (091746/Z/10/Z, 091746)
- Cancer Research UK
- British Heart Foundation
- National Institutes of Health (n01ag12100-57-0-2, n01hc55021-47-0-1, n01hc55020-39-0-0, n01hc55016-37-0-0, n01hc055022-024, n01hc55019-35-0-1, n01hc55018-38-0-1, n01hc55015-48-0-1)
- Canadian Institutes of Health Research (MOP--82810, #MOP77682, MOP172605)
- Biotechnology and Biological Sciences Research Council
- National Institute on Aging (N01-AG12100)
- National Heart, Lung, and Blood Institute (N01-HC55022, N01-HC-55018, N01 HC 55020, N01 HC 55019, R01HL087676, R01HL103931, R01HL087647, HL087647, N01-HC55016, P01HL076491, P01HL098055, P01HL087018, N01‐HC‐55015, N01-HC55021, R01HL089650)
- National Institute of Diabetes and Digestive and Kidney Diseases (R01DK080732)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Metabolomics and Mass Spectrometry Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Keywords
- blood metabolites, genetic loci, untargeted metabolomics, endophenotypes, type 2 diabetes, cardiovascular disease, kidney disease, cancer, gout, venous thromboembolism, Crohn's disease, gene-environment interaction, TwinsUK
- MeSH terms
- Adolescent, Adult, Aged, Aged, 80 and over, Blood, Child, Chronic Disease, Coronary Artery Disease, Diabetes Mellitus, Drug Industry, Female, Genotype, Humans, Male, Metabolism, Middle Aged, Pharmacogenetics, Risk Factors, Genetic Variation, Biomedical Research, Renal Insufficiency, Venous Thromboembolism, Genome-Wide Association Study, Metabolomics, Young Adult, Genetic Loci
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