Genome-wide association studies (GWAS) have identified many risk loci for complex diseases, but effect sizes are typically small and information on the underlying biological processes is often lacking. Associations with metabolic traits as functional intermediates can overcome these problems and potentially inform individualized therapy. Here we report a comprehensive analysis of genotype-dependent metabolic phenotypes using a GWAS with non-targeted metabolomics. We identified 37 genetic loci associated with blood metabolite concentrations, of which 25 show effect sizes that are unusually high for GWAS and account for 10–60% differences in metabolite levels per allele copy. Our associations provide new functional insights for many disease-related associations that have been reported in previous studies, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn’s disease. The study advances our knowledge of the genetic basis of metabolic individuality in humans and generates many new hypotheses for biomedical and pharmaceutical research. The interaction of genetic predispositions with environmental factors is key to the pathogenesis of complex diseases. A promising approach to understanding this relationship combines a genome-wide association study (GWAS) with the analysis of blood metabolites as functional intermediate phenotypes. The potential of this method is demonstrated by a large-scale cooperation combining data from the German KORA F4 and the British TwinsUK population studies. GWAS data, together with non-targeted metabolomics covering 60 biochemical pathways in 2,820 individuals, have identified 37 genetic loci associated with blood metabolite concentrations, 25 of them with unusually high effect sizes for a GWAS. These associations provide new functional insights for many previously reported associations, including those for cardiovascular and kidney disorders, type 2 diabetes, cancer, gout, venous thromboembolism and Crohn's disease.

Human metabolic individuality in biomedical and pharmaceutical research