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Tin A, Schlosser P, Matias-Garcia PR, et al. Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus. Nat Commun. 2021;12(1):7173doi: 10.1038/s41467-021-27198-4.
Tin, A., Schlosser, P., Matias-Garcia, P. R., Thio, C. H. L., Joehanes, R., Liu, H., Yu, Z., Weihs, A., Hoppmann, A., Grundner-Culemann, F., Min, J. L., Kuhns, V. L. H., Adeyemo, A. A., Agyemang, C., Ärnlöv, J., Aziz, N. A., Baccarelli, A., Bochud, M., Brenner, H., Bressler, J., Breteler, M. M. B., Carmeli, C., Chaker, L., Coresh, J., Corre, T., Correa, A., Cox, S. R., Delgado, G. E., Eckardt, K. U., Ekici, A. B., Endlich, K., Floyd, J. S., Fraszczyk, E., Gao, X., Gào, X., Gelber, A. C., Ghanbari, M., Ghasemi, S., Gieger, C., Greenland, P., Grove, M. L., Harris, S. E., Hemani, G., Henneman, P., Herder, C., Horvath, S., Hou, L., Hurme, M. A., Hwang, S. J., Kardia, S. L. R., Kasela, S., Kleber, M. E., Koenig, W., Kooner, J. S., Kronenberg, F., Kühnel, B., Ladd-Acosta, C., Lehtimäki, T., Lind, L., Liu, D., Lloyd-Jones, D. M., Lorkowski, S., Lu, A. T., Marioni, R. E., März, W., McCartney, D. L., Meeks, K. A. C., Milani, L., Mishra, P. P., Nauck, M., Nowak, C., Peters, A., Prokisch, H., Psaty, B. M., Raitakari, O. T., Ratliff, S. M., Reiner, A. P., Schöttker, B., Schwartz, J., Sedaghat, S., Smith, J. A., Sotoodehnia, N., Stocker, H. R., Stringhini, S., Sundström, J., Swenson, B. R., van Meurs, J. B. J., van Vliet-Ostaptchouk, J. V., Venema, A., Völker, U., Winkelmann, J., Wolffenbuttel, B. H. R., Zhao, W., Zheng, Y., Loh, M., Snieder, H., Waldenberger, M., Levy, D., Akilesh, S., Woodward, O. M., Susztak, K., Teumer, A., & Köttgen, A. (2021). Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus. Nature communications, 12(1), 7173. https://doi.org/10.1038/s41467-021-27198-4
Tin, Adrienne, et al. "Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus." Nature communications vol. 12,1 (2021): 7173. doi: https://doi.org/10.1038/s41467-021-27198-4
Tin A, Schlosser P, Matias-Garcia PR, Thio CHL, Joehanes R, Liu H, Yu Z, Weihs A, Hoppmann A, Grundner-Culemann F, Min JL, Kuhns VLH, Adeyemo AA, Agyemang C, Ärnlöv J, Aziz NA, Baccarelli A, Bochud M, Brenner H, Bressler J, Breteler MMB, Carmeli C, Chaker L, Coresh J, Corre T, Correa A, Cox SR, Delgado GE, Eckardt KU, Ekici AB, Endlich K, Floyd JS, Fraszczyk E, Gao X, Gào X, Gelber AC, Ghanbari M, Ghasemi S, Gieger C, Greenland P, Grove ML, Harris SE, Hemani G, Henneman P, Herder C, Horvath S, Hou L, Hurme MA, Hwang SJ, Kardia SLR, Kasela S, Kleber ME, Koenig W, Kooner JS, Kronenberg F, Kühnel B, Ladd-Acosta C, Lehtimäki T, Lind L, Liu D, Lloyd-Jones DM, Lorkowski S, Lu AT, Marioni RE, März W, McCartney DL, Meeks KAC, Milani L, Mishra PP, Nauck M, Nowak C, Peters A, Prokisch H, Psaty BM, Raitakari OT, Ratliff SM, Reiner AP, Schöttker B, Schwartz J, Sedaghat S, Smith JA, Sotoodehnia N, Stocker HR, Stringhini S, Sundström J, Swenson BR, van Meurs JBJ, van Vliet-Ostaptchouk JV, Venema A, Völker U, Winkelmann J, Wolffenbuttel BHR, Zhao W, Zheng Y, Loh M, Snieder H, Waldenberger M, Levy D, Akilesh S, Woodward OM, Susztak K, Teumer A, Köttgen A. Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus. Nat Commun. 2021 Dec 09;12(1):7173. doi: 10.1038/s41467-021-27198-4. PMID: 34887389.
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Nat Commun. 2021 Dec 09;12(1):7173. doi: 10.1038/s41467-021-27198-4.

Epigenome-wide association study of serum urate reveals insights into urate co-regulation and the SLC2A9 locus.

Nature communications

Adrienne Tin, Pascal Schlosser, Pamela R Matias-Garcia, Chris H L Thio, Roby Joehanes, Hongbo Liu, Zhi Yu, Antoine Weihs, Anselm Hoppmann, Franziska Grundner-Culemann, Josine L Min, Victoria L Halperin Kuhns, Adebowale A Adeyemo, Charles Agyemang, Johan Ärnlöv, Nasir A Aziz, Andrea Baccarelli, Murielle Bochud, Hermann Brenner, Jan Bressler, Monique M B Breteler, Cristian Carmeli, Layal Chaker, Josef Coresh, Tanguy Corre, Adolfo Correa, Simon R Cox, Graciela E Delgado, Kai-Uwe Eckardt, Arif B Ekici, Karlhans Endlich, James S Floyd, Eliza Fraszczyk, Xu Gao, Xīn Gào, Allan C Gelber, Mohsen Ghanbari, Sahar Ghasemi, Christian Gieger, Philip Greenland, Megan L Grove, Sarah E Harris, Gibran Hemani, Peter Henneman, Christian Herder, Steve Horvath, Lifang Hou, Mikko A Hurme, Shih-Jen Hwang, Sharon L R Kardia, Silva Kasela, Marcus E Kleber, Wolfgang Koenig, Jaspal S Kooner, Florian Kronenberg, Brigitte Kühnel, Christine Ladd-Acosta, Terho Lehtimäki, Lars Lind, Dan Liu, Donald M Lloyd-Jones, Stefan Lorkowski, Ake T Lu, Riccardo E Marioni, Winfried März, Daniel L McCartney, Karlijn A C Meeks, Lili Milani, Pashupati P Mishra, Matthias Nauck, Christoph Nowak, Annette Peters, Holger Prokisch, Bruce M Psaty, Olli T Raitakari, Scott M Ratliff, Alex P Reiner, Ben Schöttker, Joel Schwartz, Sanaz Sedaghat, Jennifer A Smith, Nona Sotoodehnia, Hannah R Stocker, Silvia Stringhini, Johan Sundström, Brenton R Swenson, Joyce B J van Meurs, Jana V van Vliet-Ostaptchouk, Andrea Venema, Uwe Völker, Juliane Winkelmann, Bruce H R Wolffenbuttel, Wei Zhao, Yinan Zheng, Marie Loh, Harold Snieder, Melanie Waldenberger, Daniel Levy, Shreeram Akilesh, Owen M Woodward, Katalin Susztak, Alexander Teumer, Anna Köttgen

Affiliations

  1. Department of Medicine, University of Mississippi Medical Center, Jackson, 39216, MS, USA. [email protected].
  2. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. [email protected].
  3. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
  4. Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany.
  5. Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany.
  6. Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, D-85764, Bavaria, Germany.
  7. TUM School of Medicine, Technical University of Munich, Munich, Germany.
  8. Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  9. Framingham Heart Study, Framingham, MA, USA.
  10. Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  11. Department of Medicine and Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, 19104, PA, USA.
  12. Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
  13. Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
  14. Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA.
  15. Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany.
  16. MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
  17. Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  18. Department of Physiology, University of Maryland School of Medicine, Baltimore, MD, USA.
  19. Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
  20. Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, 1105 AZ, Amsterdam, the Netherlands.
  21. Department of Neurobiology, Care Sciences and Society (NVS), Family Medicine and Primary Care Unit, Karolinska Institutet, Huddinge, Sweden.
  22. School of Health and Social Studies, Dalarna University, Falun, Sweden.
  23. Population Health Sciences, German Centre for Neurodegenerative Diseases (DZNE), Bonn, Germany.
  24. Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany.
  25. Laboratory of Environmental Precision Health, Mailman School of Public Health, Columbia University, New York, NY, USA.
  26. Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
  27. German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, Heidelberg, Germany.
  28. Network Aging Research, Heidelberg University, Heidelberg, Germany.
  29. Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany.
  30. German Cancer Consortium, German Cancer Research Center (DKFZ), Heidelberg, Germany.
  31. Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, 77030, TX, USA.
  32. Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany.
  33. Population Health Laboratory, University of Fribourg, Fribourg, Switzerland.
  34. Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
  35. Department of Internal Medicine, Erasmus Medical Center, Rotterdam, the Netherlands.
  36. Department of Medicine, University of Mississippi Medical Center, Jackson, 39216, MS, USA.
  37. Lothian Birth Cohorts Group, Department of Psychology, The University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.
  38. Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany.
  39. Department of Nephrology and Hypertension, University of Erlangen-Nürnberg, Erlangen, Germany.
  40. Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  41. Institute of Human Genetics, Friedrich-Alexander-UniversitätErlangen-Nürnberg, 91054, Erlangen, Germany.
  42. Department of Anatomy and Cell Biology, University Medicine Greifswald, Greifswald, Germany.
  43. DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany.
  44. Department of Medicine, University of Washington, Seattle, 98101, WA, USA.
  45. Department of Epidemiology, University of Washington, Seattle, 98101, WA, USA.
  46. Cardiovascular Health Research Unit, University of Washington, Seattle, 98101, WA, USA.
  47. Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing, China.
  48. Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
  49. Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany.
  50. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA.
  51. Department of Clinical Genetics, Amsterdam Reproduction & Development Research Institute, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam, the Netherlands.
  52. Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
  53. German Center for Diabetes Research, Munich-Neuherberg, Germany.
  54. Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
  55. Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, 90095, CA, USA.
  56. Biostatistics, Fielding School of Public Health, UCLA, Los Angeles, CA, USA.
  57. Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland.
  58. Division of Intramural Research, Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA.
  59. Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, 48109, MI, USA.
  60. Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
  61. SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany.
  62. Deutsches Herzzentrum München, Technische Universität München, Munich, Germany.
  63. DZHK (German Centre for Cardiovascular Research), Partner site Munich Heart Alliance, Munich, Germany.
  64. Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany.
  65. National Heart and Lung Institute, Imperial College London, London, UK.
  66. Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK.
  67. Imperial College Healthcare NHS Trust, London, UK.
  68. Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.
  69. Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
  70. Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
  71. Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland.
  72. Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
  73. Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany.
  74. Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany.
  75. Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK.
  76. Synlab Academy, SYNLAB Holding Deutschland GmbH, Mannheim and Augsburg, Germany.
  77. Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria.
  78. Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany.
  79. Ludwig-Maximilians Universität München, Munich, Germany.
  80. Institute of Human Genetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
  81. Department of Computational Health, Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany.
  82. Department of Health Services, University of Washington, Seattle, 98101, WA, USA.
  83. Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
  84. Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.
  85. Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
  86. Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
  87. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA.
  88. Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA.
  89. The George Institute for Global Health, University of New South Wales, Sydney, NSW, Australia.
  90. Institute for Public Health Genetics, University of Washington, Seattle, WA, USA.
  91. Department of Endocrinology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
  92. Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany.
  93. Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany.
  94. Chair Neurogenetics, Klinikum rechts der Isar, Technische Universität München, Munich, Germany.
  95. Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
  96. Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  97. Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
  98. Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA, USA.
  99. Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland.
  100. Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA. [email protected].
  101. Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany. [email protected].

PMID: 34887389 DOI: 10.1038/s41467-021-27198-4

Abstract

Elevated serum urate levels, a complex trait and major risk factor for incident gout, are correlated with cardiometabolic traits via incompletely understood mechanisms. DNA methylation in whole blood captures genetic and environmental influences and is assessed in transethnic meta-analysis of epigenome-wide association studies (EWAS) of serum urate (discovery, n = 12,474, replication, n = 5522). The 100 replicated, epigenome-wide significant (p < 1.1E-7) CpGs explain 11.6% of the serum urate variance. At SLC2A9, the serum urate locus with the largest effect in genome-wide association studies (GWAS), five CpGs are associated with SLC2A9 gene expression. Four CpGs at SLC2A9 have significant causal effects on serum urate levels and/or gout, and two of these partly mediate the effects of urate-associated GWAS variants. In other genes, including SLC7A11 and PHGDH, 17 urate-associated CpGs are associated with conditions defining metabolic syndrome, suggesting that these CpGs may represent a blood DNA methylation signature of cardiometabolic risk factors. This study demonstrates that EWAS can provide new insights into GWAS loci and the correlation of serum urate with other complex traits.

© 2021. The Author(s).

References

  1. Kottgen, A. et al. Genome-wide association analyses identify 18 new loci associated with serum urate concentrations. Nat. Genet. 45, 145–154 (2013). - PubMed
  2. Kanai, M. et al. Genetic analysis of quantitative traits in the Japanese population links cell types to complex human diseases. Nat. Genet. 50, 390–400 (2018). - PubMed
  3. Tin, A. et al. Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels. Nat. Genet. 51, 1459–1474 (2019). - PubMed
  4. Roddy, E. & Choi, H. K. Epidemiology of gout. Rheum. Dis. Clin. North Am. 40, 155–175 (2014). - PubMed
  5. Choi, H. K., Atkinson, K., Karlson, E. W., Willett, W. & Curhan, G. Purine-rich foods, dairy and protein intake, and the risk of gout in men. N. Engl. J. Med. 350, 1093–1103 (2004). - PubMed
  6. Dalbeth, N. et al. Gout. Nat. Rev. Dis. Prim. 5, 69 (2019). - PubMed
  7. Feig, D. I., Kang, D. H. & Johnson, R. J. Uric acid and cardiovascular risk. N. Engl. J. Med. 359, 1811–1821 (2008). - PubMed
  8. Sundström, J. et al. Relations of serum uric acid to longitudinal blood pressure tracking and hypertension incidence. Hypertension 45, 28–33 (2005). - PubMed
  9. Juraschek, S. P., Miller, E. R. III & Gelber, A. C. Body mass index, obesity, and prevalent gout in the United States in 1988-1994 and 2007-2010. Arthritis Care Res. (Hoboken) 65, 127–132 (2013). - PubMed
  10. Emmerson, B. T., Nagel, S. L., Duffy, D. L. & Martin, N. G. Genetic control of the renal clearance of urate: a study of twins. Ann. Rheum. Dis. 51, 375–377 (1992). - PubMed
  11. Rice, T. et al. Heterogeneity in the familial aggregation of fasting serum uric acid level in five North American populations: the Lipid Research Clinics Family Study. Am. J. Med. Genet. 36, 219–225 (1990). - PubMed
  12. Major, T. J., Dalbeth, N., Stahl, E. A. & Merriman, T. R. An update on the genetics of hyperuricaemia and gout. Nat. Rev. Rheumatol. 14, 341–353 (2018). - PubMed
  13. Mandal, A. K. & Mount, D. B. The molecular physiology of uric acid homeostasis. Annu. Rev. Physiol. 77, 323–345 (2015). - PubMed
  14. Futagi, Y., Narumi, K., Furugen, A., Kobayashi, M. & Iseki, K. Molecular characterization of the orphan transporter SLC16A9, an extracellular pH- and Na+-sensitive creatine transporter. Biochem. Biophys. Res. Commun. 522, 539–544 (2020). - PubMed
  15. Woodward, O. M. et al. Identification of a urate transporter, ABCG2, with a common functional polymorphism causing gout. Proc. Natl Acad. Sci. USA. 106, 10338–10342 (2009). - PubMed
  16. Vitart, V. et al. SLC2A9 is a newly identified urate transporter influencing serum urate concentration, urate excretion and gout. Nat. Genet. 40, 437–442 (2008). - PubMed
  17. Kooner, J. S. et al. Genome-wide association study in individuals of South Asian ancestry identifies six new type 2 diabetes susceptibility loci. Nat. Genet. 43, 984–989 (2011). - PubMed
  18. Voight, B. F. et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010). - PubMed
  19. Teslovich, T. M. et al. Biological, clinical and population relevance of 95 loci for blood lipids. Nature 466, 707–713 (2010). - PubMed
  20. Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434–443 (2020). - PubMed
  21. Kilpinen, H. & Dermitzakis, E. T. Genetic and epigenetic contribution to complex traits. Hum. Mol. Genet. 21, R24–R28 (2012). - PubMed
  22. Hannon, E. et al. Characterizing genetic and environmental influences on variable DNA methylation using monozygotic and dizygotic twins. PLoS Genet. 14, e1007544–e1007544 (2018). - PubMed
  23. van Dongen, J. et al. Genetic and environmental influences interact with age and sex in shaping the human methylome. Nat. Commun. 7, 11115 (2016). - PubMed
  24. McRae, A. F. et al. Contribution of genetic variation to transgenerational inheritance of DNA methylation. Genome Biol. 15, R73 (2014). - PubMed
  25. Suzuki, M. M. & Bird, A. DNA methylation landscapes: provocative insights from epigenomics. Nat. Rev. Genet 9, 465–476 (2008). - PubMed
  26. Uhlen, M. et al. Proteomics. Tissue-based map of the human proteome. Science 347, 1260419 (2015). - PubMed
  27. Kennedy, E. M. et al. An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells. BMC Genomics 19, 476 (2018). - PubMed
  28. Anastasiadi, D., Esteve-Codina, A. & Piferrer, F. Consistent inverse correlation between DNA methylation of the first intron and gene expression across tissues and species. Epigenetics Chromatin 11, 37 (2018). - PubMed
  29. Kimura, T., Takahashi, M., Yan, K. & Sakurai, H. Expression of SLC2A9 isoforms in the kidney and their localization in polarized epithelial cells. PLoS One 9, e84996 (2014). - PubMed
  30. Local, A. et al. Identification of H3K4me1-associated proteins at mammalian enhancers. Nat. Genet. 50, 73–82 (2018). - PubMed
  31. Sharifi-Zarchi, A. et al. DNA methylation regulates discrimination of enhancers from promoters through a H3K4me1-H3K4me3 seesaw mechanism. BMC Genomics 18, 964 (2017). - PubMed
  32. Young, M. D. et al. ChIP-seq analysis reveals distinct H3K27me3 profiles that correlate with transcriptional activity. Nucleic Acids Res. 39, 7415–7427 (2011). - PubMed
  33. Nicetto, D. et al. H3K9me3-heterochromatin loss at protein-coding genes enables developmental lineage specification. Science 363, 294–297 (2019). - PubMed
  34. Maiuolo, J., Oppedisano, F., Gratteri, S., Muscoli, C. & Mollace, V. Regulation of uric acid metabolism and excretion. Int J. Cardiol. 213, 8–14 (2016). - PubMed
  35. Kodama, S. et al. Association between serum uric acid and development of type 2 diabetes. Diabetes Care 32, 1737–1742 (2009). - PubMed
  36. Krishnan, E., Kwoh, C. K., Schumacher, H. R. & Kuller, L. Hyperuricemia and incidence of hypertension among men without metabolic syndrome. Hypertension 49, 298–303 (2007). - PubMed
  37. Choi, H. K. & Ford, E. S. Prevalence of the metabolic syndrome in individuals with hyperuricemia. Am. J. Med. 120, 442–447 (2007). - PubMed
  38. Grundy Scott, M., Brewer, H. B., Cleeman James, I., Smith Sidney, C. & Lenfant, C. Definition of metabolic syndrome. Circulation 109, 433–438 (2004). - PubMed
  39. Gomez-Alonso, M. D. C. et al. DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures. Clin. Epigenetics 13, 7 (2021). - PubMed
  40. Petersen, A.-K. et al. Epigenetics meets metabolomics: an epigenome-wide association study with blood serum metabolic traits. Hum. Mol. Genet. 23, 534–545 (2014). - PubMed
  41. Cabău, G., Crișan, T. O., Klück, V., Popp, R. A. & Joosten, L. A. B. Urate-induced immune programming: consequences for gouty arthritis and hyperuricemia. Immunol. Rev. 294, 92–105 (2020). - PubMed
  42. Crișan, T. O. et al. Soluble uric acid primes TLR-induced proinflammatory cytokine production by human primary cells via inhibition of IL-1Ra. Ann. Rheum. Dis. 75, 755–762 (2016). - PubMed
  43. Chu, A. Y. et al. Epigenome-wide association studies identify DNA methylation associated with kidney function. Nat. Commun. 8, 1286 (2017). - PubMed
  44. Gluck, C. et al. Kidney cytosine methylation changes improve renal function decline estimation in patients with diabetic kidney disease. Nat. Commun. 10, 2461 (2019). - PubMed
  45. Dekkers, K. F. et al. Blood lipids influence DNA methylation in circulating cells. Genome Biol. 17, 138 (2016). - PubMed
  46. Richard, M. A. et al. DNA methylation analysis identifies loci for blood pressure regulation. Am. J. Hum. Genet. 101, 888–902 (2017). - PubMed
  47. Wahl, S. et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541, 81–86 (2017). - PubMed
  48. Nano, J. et al. Epigenome-wide association study identifies methylation sites associated with liver enzymes and hepatic steatosis. Gastroenterology 153, 1096–1106.e2 (2017). - PubMed
  49. Ligthart, S. et al. DNA methylation signatures of chronic low-grade inflammation are associated with complex diseases. Genome Biol. 17, 255 (2016). - PubMed
  50. Cardona, A. et al. Epigenome-wide association study of incident type 2 diabetes in a british population: EPIC-Norfolk Study. Diabetes 68, 2315–2326 (2019). - PubMed
  51. Li, X. et al. MR-PheWAS: exploring the causal effect of SUA level on multiple disease outcomes by using genetic instruments in UK Biobank. Ann. Rheum. Dis. 77, 1039–1047 (2018). - PubMed
  52. Li, X. et al. Serum uric acid levels and multiple health outcomes: umbrella review of evidence from observational studies, randomised controlled trials, and Mendelian randomisation studies. BMJ 357, j2376 (2017). - PubMed
  53. Doring, A. et al. SLC2A9 influences uric acid concentrations with pronounced sex-specific effects. Nat. Genet. 40, 430–436 (2008). - PubMed
  54. Yang, Q. et al. Multiple genetic loci influence serum urate levels and their relationship with gout and cardiovascular disease risk factors. Circ. Cardiovasc. Genet. 3, 523–530 (2010). - PubMed
  55. Matsuo, H. et al. Genome-wide association study of clinically defined gout identifies multiple risk loci and its association with clinical subtypes. Ann. Rheum. Dis. 75, 652–659 (2016). - PubMed
  56. Li, S. et al. The GLUT9 gene is associated with serum uric acid levels in Sardinia and Chianti cohorts. PLoS Genet. 3, e194 (2007). - PubMed
  57. Tin, A. et al. Genome-wide association study for serum urate concentrations and gout among African Americans identifies genomic risk loci and a novel URAT1 loss-of-function allele. Hum. Mol. Genet. 20, 4056–4068 (2011). - PubMed
  58. Anzai, N. et al. Plasma urate level is directly regulated by a voltage-driven urate efflux transporter URATv1 (SLC2A9) in humans. J. Biol. Chem. 283, 26834–26838 (2008). - PubMed
  59. Phay, J. E., Hussain, H. B. & Moley, J. F. Cloning and expression analysis of a novel member of the facilitative glucose transporter family, SLC2A9 (GLUT9). Genomics 66, 217–220 (2000). - PubMed
  60. Keembiyehetty, C. et al. Mouse glucose transporter 9 splice variants are expressed in adult liver and kidney and are up-regulated in diabetes. Mol. Endocrinol. 20, 686–697 (2006). - PubMed
  61. Witkowska, K. et al. hGLUT9 as a novel urate transporter: its role in liver urate handling and functional study of SLC2A9 SNPs. FASEB J. 23, 797.4–797.4 (2009). - PubMed
  62. Preitner, F. et al. Glut9 is a major regulator of urate homeostasis and its genetic inactivation induces hyperuricosuria and urate nephropathy. Proc. Natl Acad. Sci. USA. 106, 15501–15506 (2009). - PubMed
  63. Bannasch, D. et al. Mutations in the SLC2A9 gene cause hyperuricosuria and hyperuricemia in the dog. PLoS Genet. 4, e1000246 (2008). - PubMed
  64. Hoque, K. M. et al. The ABCG2 Q141K hyperuricemia and gout associated variant illuminates the physiology of human urate excretion. Nat. Commun. 11, 2767 (2020). - PubMed
  65. DeBosch, B. J., Kluth, O., Fujiwara, H., Schürmann, A. & Moley, K. Early-onset metabolic syndrome in mice lacking the intestinal uric acid transporter SLC2A9. Nat. Commun. 5, 4642 (2014). - PubMed
  66. Reid, M. A. et al. Serine synthesis through PHGDH coordinates nucleotide levels by maintaining central carbon metabolism. Nat. Commun. 9, 5442 (2018). - PubMed
  67. Karabegović, I. et al. Epigenome-wide association meta-analysis of DNA methylation with coffee and tea consumption. Nat. Commun. 12, 2830 (2021). - PubMed
  68. Kanai, Y. et al. The SLC1 high-affinity glutamate and neutral amino acid transporter family. Mol. Asp. Med. 34, 108–120 (2013). - PubMed
  69. Fotiadis, D., Kanai, Y. & Palacín, M. The SLC3 and SLC7 families of amino acid transporters. Mol. Asp. Med. 34, 139–158 (2013). - PubMed
  70. Bodoy, S., Fotiadis, D., Stoeger, C., Kanai, Y. & Palacín, M. The small SLC43 family: facilitator system l amino acid transporters and the orphan EEG1. Mol. Asp. Med. 34, 638–645 (2013). - PubMed
  71. Nigam, S. K. & Bhatnagar, V. The systems biology of uric acid transporters: the role of remote sensing and signaling. Curr. Opin. Nephrol. Hypertens. 27, 305–313 (2018). - PubMed
  72. Takada, T. et al. ABCG2 dysfunction increases serum uric acid by decreased intestinal urate excretion. Nucleosides Nucleotides Nucleic Acids 33, 275–281 (2014). - PubMed
  73. Yano, H., Tamura, Y., Kobayashi, K., Tanemoto, M. & Uchida, S. Uric acid transporter ABCG2 is increased in the intestine of the 5/6 nephrectomy rat model of chronic kidney disease. Clin. Exp. Nephrol. 18, 50–55 (2014). - PubMed
  74. Houseman, E. A. et al. DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinforma. 13, 86 (2012). - PubMed
  75. van Iterson, M., van Zwet, E. W., Heijmans, B. T. & the, B. C. Controlling bias and inflation in epigenome- and transcriptome-wide association studies using the empirical null distribution. Genome Biol. 18, 19 (2017). - PubMed
  76. Viechtbauer, W. Conducting Meta-Analyses in R with the metafor Package. J. Stat. Softw. 36, 1–48 (2010). - PubMed
  77. Burgess, S. et al. Guidelines for performing Mendelian randomization investigations. Wellcome Open Res. 4, 186 (2020). - PubMed
  78. Burgess, S., Butterworth, A. & Thompson, S. G. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet. Epidemiol. 37, 658–665 (2013). - PubMed
  79. Hemani, G. et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife 7, e34408 (2018). - PubMed
  80. Hemani, G., Tilling, K. & Davey Smith, G. Orienting the causal relationship between imprecisely measured traits using GWAS summary data. PLoS Genet. 13, e1007081 (2017). - PubMed
  81. Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. Genome-wide complex trait analysis (GCTA): methods, data analyses, and interpretations. Methods Mol. Biol. 1019, 215–236 (2013). - PubMed
  82. Min, J. L. et al. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation. Nat. Genet. 53, 1311–1321 (2021). - PubMed
  83. Bowden, J., Davey Smith, G. & Burgess, S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 44, 512–525 (2015). - PubMed
  84. Cochran, W. G. The comparison of percentages in matched samples. Biometrika 37, 256–266 (1950). - PubMed
  85. Rees, J. M. B., Wood, A. M. & Burgess, S. Extending the MR-Egger method for multivariable Mendelian randomization to correct for both measured and unmeasured pleiotropy. Stat. Med. 36, 4705–4718 (2017). - PubMed
  86. Hartwig, F. P., Davey Smith, G. & Bowden, J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int. J. Epidemiol. 46, 1985–1998 (2017). - PubMed
  87. Bowden, J., Davey Smith, G., Haycock, P. C. & Burgess, S. Consistent estimation in Mendelian randomization with some invalid instruments using a weighted median estimator. Genet. Epidemiol. 40, 304–314 (2016). - PubMed
  88. Yang, J., Lee, S. H., Goddard, M. E. & Visscher, P. M. GCTA: a tool for genome-wide complex trait analysis. Am. J. Hum. Genet. 88, 76–82 (2011). - PubMed
  89. Huan, T. et al. Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease. Nat. Commun. 10, 4267 (2019). - PubMed
  90. Imai, K., Keele, L. & Yamamoto, T. Identification, inference and sensitivity analysis for causal mediation effects. Stat. Sci. 25, 51–71 (2010). - PubMed
  91. Park, J. et al. Functional methylome analysis of human diabetic kidney disease. JCI Insight 4, e128886 (2019). - PubMed
  92. Ashburner, M. et al. Gene Ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat. Genet. 25, 25–29 (2000). - PubMed
  93. The Gene Ontology Consortium. The Gene Ontology Resource: 20 years and still GOing strong. Nucleic Acids Res. 47, D330–D338 (2019). - PubMed
  94. Kanehisa, M. & Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27–30 (2000). - PubMed
  95. Fabregat, A. et al. The Reactome Pathway Knowledgebase. Nucleic Acids Res. 46, D649–D655 (2018). - PubMed
  96. Breeze, C. E. et al. eFORGE: a tool for identifying cell type-specific signal in epigenomic data. Cell Rep. 17, 2137–2150 (2016). - PubMed
  97. Sabo, P. J. et al. Discovery of functional noncoding elements by digital analysis of chromatin structure. Proc. Natl Acad. Sci. USA. 101, 16837 (2004). - PubMed
  98. ENCODE Project Consortium. The ENCODE (ENCyclopedia Of DNA Elements) Project. Science 306, 636–640 (2004). - PubMed
  99. Kundaje, A. et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015). - PubMed
  100. Ren, X. & Kuan, P. F. methylGSA: a Bioconductor package and Shiny app for DNA methylation data length bias adjustment in gene set testing. Bioinformatics 35, 1958–1959 (2019). - PubMed
  101. Benjamini, Y. & Hochberg, Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Series B Methodol. 57, 289–300. http://www.jstor.org/stable/2346101 (1995). - PubMed
  102. Schlosser, P., Teumer, A., Tin, A. & Köttgen, A. Phenotype generation code: epigenome-wide association studies identify DNA methylation associated with kidney function and damage. genepi-freiburg/ckdgen-pheno-ewas. GitHub. https://doi.org/10.5281/zenodo.5578240 (2021). - PubMed

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