4.8 Article

An atlas of genetic influences on human blood metabolites

期刊

NATURE GENETICS
卷 46, 期 6, 页码 543-550

出版社

NATURE PUBLISHING GROUP
DOI: 10.1038/ng.2982

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资金

  1. Pfizer Worldwide Research and Development
  2. Wellcome Trust
  3. European Community
  4. National Institute for Health Research (NIHR) BioResource Clinical Research Facility
  5. Biomedical Research Centre baled at Guy's and St Thomas' National Health Service (NHS) Foundation Trust
  6. King's College London
  7. Helmholtz Zentrum Miinchen National Research Center for Environmental Health
  8. German Federal Ministry of Education, Science, Research and Technology
  9. State of Bavaria
  10. German Federal Ministry of Education and Research (BMBF)
  11. German National Genome Research Network [01GS0823]
  12. Oak Foundation
  13. ERC German Research Foundation [SPP 1395]
  14. German Helmholtz Postdoctoral Programme
  15. Biomedical Research Program funds at Well Cornell Medical College in Qatar, a program
  16. Qatar Foundation
  17. European Union
  18. Russian Foundation for Basic Research (RFBR)-Helmholtz research group program
  19. Wellcome Trust [WT098051, WT091310]
  20. European Commission [257082, HEALTH-F5-2011-282510]
  21. Canadian Institutes of Health Research, Fonds du Recherche du Science Quebec
  22. Quebec Consortium for Drug Discovery
  23. Medical Research Council [MC_UU_12013/1] Funding Source: researchfish
  24. MRC [MC_UU_12013/1] Funding Source: UKRI

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Genome-wide association scans with high-throughput metabolic profiling provide unprecedented insights into how genetic variation influences metabolism and complex disease. Here we report the most comprehensive exploration of genetic loci influencing human metabolism thus far, comprising 7,824 adult individuals from 2 European population studies. We report genome-wide significant associations at 145 metabolic loci and their biochemical connectivity with more than 400 metabolites in human blood. We extensively characterize the resulting in vivo blueprint of metabolism in human blood by integrating it with information on gene expression, heritability and overlap with known loci for complex disorders, inborn errors of metabolism and pharmacological targets. We further developed a database and web-based resources for data mining and results visualization. Our findings provide new insights into the role of inherited variation in blood metabolic diversity and identify potential new opportunities for drug development and for understanding disease.

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