Rare and common genetic determinants of metabolic individuality and their effects on human health

• Published in: Nature medicine Vol. 28; no. 11; pp. 2321 - 2332
• Main Authors: Surendran, Praveen, Stewart, Isobel D., Au Yeung, Victoria P. W., Pietzner, Maik, Raffler, Johannes, Wörheide, Maria A., Li, Chen, Smith, Rebecca F., Wittemans, Laura B. L., Bomba, Lorenzo, Menni, Cristina, Zierer, Jonas, Rossi, Niccolò, Sheridan, Patricia A., Watkins, Nicholas A., Mangino, Massimo, Hysi, Pirro G., Di Angelantonio, Emanuele, Falchi, Mario, Spector, Tim D., Soranzo, Nicole, Michelotti, Gregory A., Arlt, Wiebke, Lotta, Luca A., Denaxas, Spiros, Hemingway, Harry, Gamazon, Eric R., Howson, Joanna M. M., Wood, Angela M., Danesh, John, Wareham, Nicholas J., Kastenmüller, Gabi, Fauman, Eric B., Suhre, Karsten, Butterworth, Adam S., Langenberg, Claudia
• Format: Journal Article
• Language: English
• Published: New York Nature Publishing Group US 01.11.2022; Nature Publishing Group
• Subjects: 3-Oxo-5-alpha-Steroid 4-Dehydrogenase - genetics; 3-Oxo-5-alpha-Steroid 4-Dehydrogenase - metabolism; 631/208/457; 631/208/480; Biomedical and Life Sciences; Biomedicine; Blood plasma; Cancer Research; Errors; Gene frequency; Genes; Genetic analysis; Humans; Inborn errors of metabolism; Infectious Diseases; Membrane Proteins - metabolism; Metabolic Diseases; Metabolism; Metabolism, Inborn Errors - genetics; Metabolites; Metabolome - genetics; Metabolomics; Molecular Medicine; Neurosciences; Phenotype; Phenotypes; Plasma - metabolism; Side effects
• ISSN: 1078-8956; 1546-170X; 1546-170X
• DOI: 10.1038/s41591-022-02046-0

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 × 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.