Identification of seven novel loci associated with amino acid levels using single variant and gene-based tests in 8,545 Finnish men from the METSIM study.

Comprehensive metabolite profiling captures many highly heritable traits, including amino acid levels, which are potentially sensitive biomarkers for disease pathogenesis. To better understand the contribution of genetic variation to amino acid levels, we performed single variant and gene-based tests of association between nine serumamino acids (alanine, glutamine, glycine, histidine, isoleucine, leucine, phenylalanine, tyrosine, and valine) and 16.6 million genotyped and imputed variants in 8545 nondiabetic Finnishmen from the METabolic Syndrome In Men (METSIM) study with replication in Northern Finland Birth Cohort (NFBC1966). We identified five novel loci associated with amino acid levels (P = < 5 x 10(-8)): LOC157273/PPP1R3B with glycine (rs9987289, P = 2.3x10(-26)); ZFHX3 (chr16:73326579, minor allele frequency (MAF) = 0.42%, P = 3.6x10(-9)), LIPC (rs10468017, P = 1.5x10(-8)), and WWOX (rs9937914, P = 3.8x10(-8)) with alanine; and TRIB1 with tyrosine (rs28601761, P = 8x10(-9)). Gene-based tests identified two novel genes harboring missense variants of MAF < 1% that show aggregate association with amino acid levels: PYCR1 with glycine (P-gene = 1.5x10(-6)) and BCAT2 with valine (P-gene = 7.4x10(-7)); neither gene was implicated by single variant association tests. These findings are among the first applications of gene-based tests to identify new loci for amino acid levels. In addition to the seven novel gene associations, we identified five independent signals at established amino acid loci, including two rare variant signals at GLDC (rs138640017, MAF= 0.95%, P-conditional = 5.8x10(-40)) with glycine levels and HAL (rs141635447, MAF = 0.46%, P-conditional = 9.4x10(-11)) with histidine levels. Examination of all single variant association results in our data revealed a strong inverse relationship between effect size and MAF (P-trend < 0.001). These novel signals provide further insight into the molecularmechanisms of amino acid metabolismand potentially, their perturbations in disease.