Journal
NATURE GENETICS
Volume 46, Issue 6, Pages 543-550Publisher
NATURE PUBLISHING GROUP
DOI: 10.1038/ng.2982
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Funding
- Pfizer Worldwide Research and Development
- Wellcome Trust
- European Community
- National Institute for Health Research (NIHR) BioResource Clinical Research Facility
- Biomedical Research Centre baled at Guy's and St Thomas' National Health Service (NHS) Foundation Trust
- King's College London
- Helmholtz Zentrum Miinchen National Research Center for Environmental Health
- German Federal Ministry of Education, Science, Research and Technology
- State of Bavaria
- German Federal Ministry of Education and Research (BMBF)
- German National Genome Research Network [01GS0823]
- Oak Foundation
- ERC German Research Foundation [SPP 1395]
- German Helmholtz Postdoctoral Programme
- Biomedical Research Program funds at Well Cornell Medical College in Qatar, a program
- Qatar Foundation
- European Union
- Russian Foundation for Basic Research (RFBR)-Helmholtz research group program
- Wellcome Trust [WT098051, WT091310]
- European Commission [257082, HEALTH-F5-2011-282510]
- Canadian Institutes of Health Research, Fonds du Recherche du Science Quebec
- Quebec Consortium for Drug Discovery
- Medical Research Council [MC_UU_12013/1] Funding Source: researchfish
- 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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