Journal
NATURE MEDICINE
Volume 28, Issue 11, Pages 2321-+Publisher
NATURE PORTFOLIO
DOI: 10.1038/s41591-022-02046-0
Keywords
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Funding
- Medical Research Council [MR/N003284/1 MC-UU_12015/1, MC_UU_00006/1, MC_PC_13048]
- Cancer Research UK [C864/A14136]
- MRC Cambridge Initiative in Metabolic Science [MR/L00002/1]
- Innovative Medicines Initiative Joint Undertaking under EMIF [115372]
- National Institute for Health Research (NIHR)
- NIHR BioResource
- NIHR Cambridge Biomedical Research Centre [BRC-1215-20014]
- Wellcome Trust [206194, 203810/Z/16/A, 221651/Z/20/Z]
- NIHR Cambridge BRC [BRC-1215-20014]
- NIHR Blood and Transplant Research Unit in Donor Health and Genomics [NIHR BTRU-2014-10024]
- UK Medical Research Council [MR/L003120/1]
- British Heart Foundation [SP/09/002, RG/13/13/30194, RG/18/13/33946]
- Health Data Research UK - UK Medical Research Council
- Engineering and Physical Sciences Research Council
- Economic and Social Research Council
- Department of Health and Social Care (England)
- Chief Scientist Office of the Scottish Government Health and Social Care Directorates
- Health and Social Care Research and Development Division (Welsh Government)
- Public Health Agency (Northern Ireland)
- British Heart Foundation
- Wellcome
- Rutherford Fund Fellowship from the Medical Research Council [MR/S003746/1]
- Cambridge Trust
- German Federal Ministry of Education and Research [01ZX1912D]
- Chronic Disease Research Foundation
- European Commission H2020 grants SYSCID [733100]
- National Institute for Health Research (NIHR) Clinical Research Facility
- Biomedical Research Centre based at Guy's and St Thomas' NHS Foundation Trust
- King's College London
- BrightFocus Foundation [G2021011S]
- Wellcome Trust Investigator grant [WT209492/Z/17/Z]
- NIHR Birmingham Biomedical Research Centre [BRC-1215-20014, BRC-1215-20009]
- National Institutes of Health [R35HG010718, R01HG011138, R01GM140287, NIH/NIA AG068026]
- BHF Programme grant [RG/13/13/30194]
- Innovative Medicines Initiative-2 Joint Undertaking [116074]
- BHF-Turing Cardiovascular Data Science Award [BCDSA\100005]
- NIHR Biomedical Research Centre at University College London (UCL) Hospital NHS Trust
- BHF Data Science Centre
- NIHR-UKRI CONVALESCENCE study
- BHF Accelerator Award [AA/18/6/24223]
- British Heart Foundation Professorship
- NIHR Senior Investigator Award
- National Institute on Aging (NIA) [U01 AG061359, RF1 AG057452, RF1 AG059093, U19 AG063744]
- Biomedical Research Program at Weill Cornell Medicine in Qatar
- Qatar Foundation
- QNRF [NPRP11C-0115-180010]
- Wellcome Trust [203810/Z/16/A, 221651/Z/20/Z] Funding Source: Wellcome Trust
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Garrod's concept of 'chemical individuality' contributes to understanding the molecular origins of human diseases. The genetic architecture of the human plasma metabolome was studied using high-throughput metabolomic technologies, revealing associations between genetic variants and metabolite levels.
Garrod's concept of 'chemical individuality' has contributed to comprehension of the molecular origins of human diseases. Untargeted high-throughput metabolomic technologies provide an in-depth snapshot of human metabolism at scale. We studied the genetic architecture of the human plasma metabolome using 913 metabolites assayed in 19,994 individuals and identified 2,599 variant-metabolite associations (P < 1.25 x 10(-11)) within 330 genomic regions, with rare variants (minor allele frequency <= 1%) explaining 9.4% of associations. Jointly modeling metabolites in each region, we identified 423 regional, co-regulated, variant-metabolite clusters called genetically influenced metabotypes. We assigned causal genes for 62.4% of these genetically influenced metabotypes, providing new insights into fundamental metabolite physiology and clinical relevance, including metabolite-guided discovery of potential adverse drug effects (DPYD and SRD5A2). We show strong enrichment of inborn errors of metabolism-causing genes, with examples of metabolite associations and clinical phenotypes of non-pathogenic variant carriers matching characteristics of the inborn errors of metabolism. Systematic, phenotypic follow-up of metabolite-specific genetic scores revealed multiple potential etiological relationships. Analyses of the genetic architecture of the human plasma metabolome in two large population-based cohorts identify associations between genetically determined metabolite levels and health.
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