Genetic influences on human blood metabolites in the Japanese population
Takeshi Iwasaki,
Yoichiro Kamatani,
Kazuhiro Sonomura,
Shuji Kawaguchi,
Takahisa Kawaguchi,
Meiko Takahashi,
Koichiro Ohmura,
Taka-Aki Sato,
Fumihiko Matsuda
Affiliations
Takeshi Iwasaki
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan; Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
Yoichiro Kamatani
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
Kazuhiro Sonomura
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan; Life Science Research Center, Shimadzu Corporation, Kyoto 604-8511, Japan
Shuji Kawaguchi
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
Takahisa Kawaguchi
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
Meiko Takahashi
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
Koichiro Ohmura
Department of Rheumatology and Clinical Immunology, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan
Taka-Aki Sato
Life Science Research Center, Shimadzu Corporation, Kyoto 604-8511, Japan
Fumihiko Matsuda
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto 606-8507, Japan; Corresponding author
Summary: An increase in ethnic diversity in genetic studies has the potential to provide unprecedented insights into how genetic variations influence human phenotypes. In this study, we conducted a quantitative trait locus (QTL) analysis of 121 metabolites measured using gas chromatography-mass spectrometry with plasma samples from 4,888 Japanese individuals. We found 60 metabolite-gene associations, of which 13 have not been previously reported. Meta-analyses with another Japanese and a European study identified six and two additional unreported loci, respectively. Genetic variants influencing metabolite levels were more enriched in protein-coding regions than in the regulatory regions while being associated with the risk of various diseases. Finally, we identified a signature of strong negative selection for uric acid (Sˆ = −1.53, p = 6.2 × 10−18). Our study expanded the knowledge of genetic influences on human blood metabolites, providing valuable insights into their physiological, pathological, and selective properties.
