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Eur J Hum Genet. 2019 Apr;27(4):621-630. doi: 10.1038/s41431-018-0296-y. Epub 2019 Jan 18.

Genetic basis for plasma amino acid concentrations based on absolute quantification: a genome-wide association study in the Japanese population.

Author information

1
Institute for Innovation, Ajinomoto Co., Inc., Kawasaki, Kanagawa, 210-8681, Japan. akira_imaizumi@ajinomoto.com.
2
Institute for Innovation, Ajinomoto Co., Inc., Kawasaki, Kanagawa, 210-8681, Japan.
3
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan.
4
Department of Genome Analysis, Institute of Biomedical Science, Kansai Medical University, Hirakata, Osaka, 573-1010, Japan.
5
Life Science Laboratories, Shimadzu Corporation, Seika, Kyoto, 619-0237, Japan.
6
R&D Planning Dept., Ajinomoto Co., Inc, Tokyo, 104-8315, Japan.
7
Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8507, Japan. fumi@genome.med.kyoto-u.ac.jp.

Abstract

To assess the use of plasma free amino acids (PFAAs) as biomarkers for metabolic disorders, it is essential to identify genetic factors that influence PFAA concentrations. PFAA concentrations were absolutely quantified by liquid chromatography-mass spectrometry using plasma samples from 1338 Japanese individuals, and genome-wide quantitative trait locus (QTL) analysis was performed for the concentrations of 21 PFAAs. We next conducted a conditional QTL analysis using the concentration of each PFAA adjusted by the other 20 PFAAs as covariates to elucidate genetic determinants that influence PFAA concentrations. We identified eight genes that showed a significant association with PFAA concentrations, of which two, SLC7A2 and PKD1L2, were identified. SLC7A2 was associated with the plasma levels of arginine and ornithine, and PKD1L2 with the level of glycine. The significant associations of these two genes were revealed in the conditional QTL analysis, but a significant association between serine and the CPS1 gene disappeared when glycine was used as a covariate. We demonstrated that conditional QTL analysis is useful for determining the metabolic pathways predominantly used for PFAA metabolism. Our findings will help elucidate the physiological roles of genetic components that control the metabolism of amino acids.

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