Amino acids are the building blocks of protein. Tracking metabolic function and amino acid concentrations in the body can serve as useful markers for the diagnosis, prognosis, and risk assessment of the various types of diseases. Among these, amino acids in plasma (PFAAs) are key regulators of metabolism. The concentrations are influenced by genetic and environmental factors, such as diet.
Recently, several genome-wide association studies (GWAS) identified genetic variations associated with PFAAs in European populations. However, the influence of heritability and whether these loci are shared among other human populations are unknown. Therefore, genome-wide quantitative trait locus (QTL) analyses on the other amino acids shared in the pathway are necessary.
Researchers sought to determine the genetics that influences PFAA concentrations in this study. Researchers conducted a genome-wide QTL analysis of free amino acids in plasma (PFAAs) measured by an absolute quantification method using plasma samples from 1338 Japanese individuals to identify genetic factors that influence PFAA concentration. For the QTL analysis, three adjusted PFAA concentrations from the measured absolute concentrations of PFAAs (GWAS 1-3). The first adjusted concentration was adjusted for sex and age (GWAS-1), the other 20 PFAAs adjusted the second, and the third was adjusted by one of the other PFAAs. Results suggest the following relationship; rs12613336 with glycine and serine, rs13244654 in the PSPH gene with serine, rs7302925 in the GLS2 gene with glutamine, rs17450273 with phenylalanine, rs56335308 in the SLC7A2 gene with arginine and ornithine, rs8059153 in the PKD1L2 gene with glycine, rs1744297 in the ASPG gene with asparagine, rs2238732 in the PRODH gene with proline. Additionally, the study showed additional associations with ten PFAAs: alanine, glutamine, histidine, lysine, methionine, ornithine, serine, threonine, tryptophan, and tyrosine. Rs2238732 in the PRODH locus also showed an association with seven PFAAs (alanine, isoleucine, leucine, ornithine, threonine, tyrosine, and valine) using proline as a covariate.
This suggests a significant association between serine and CPS1 and that one type of study called a QTL analysis is suitable for discovering metabolism pathways. These findings help add to the knowledge of how amino acids are metabolized. Read more about the study here:
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