Genome-wide association study identifies multiple loci influencing human serum metabolite levels

Abstract

Nuclear magnetic resonance assays allow for measurement of a wide range of metabolic phenotypes. We report here the results of a GWAS on 8,330 Finnish individuals genotyped and imputed at 7.7 million SNPs for a range of 216 serum metabolic phenotypes assessed by NMR of serum samples. We identified significant associations (P < 2.31 × 10−10) at 31 loci, including 11 for which there have not been previous reports of associations to a metabolic trait or disorder. Analyses of Finnish twin pairs suggested that the metabolic measures reported here show higher heritability than comparable conventional metabolic phenotypes. In accordance with our expectations, SNPs at the 31 loci associated with individual metabolites account for a greater proportion of the genetic component of trait variance (up to 40%) than is typically observed for conventional serum metabolic phenotypes. The identification of such associations may provide substantial insight into cardiometabolic disorders.

Familial Resemblance for Serum Metabolite Concentrations

“…Therefore, these results suggest a substantial contribution of genetic factors to individual differences in serum metabolite concentrations. Consistent with previous reports of MZ twin correlations and heritability of blood metabolite concentrations (Alul et al, 2013;Kettunen et al, 2012;Nicholson et al, 2011;Shah et al, 2009), there was considerable heterogeneity in the MZ correlations across all metabolites. We observed more variation in MZ correlation estimates among the acylcarnitines, amino acids, and Table S1.…”

10 Years of GWAS Discovery: Biology, Function, and Translation

“…135 Conclusions from these studies are that most molecular phenotypes are just like other complex traits, in that differences between individuals are due to a combination of genetic factors and environmental exposures and that genetic loci can be mapped by GWASs. 136 This makes the discovery of causal pathways from genomes to phenomes challenging, in that variation between people in modifiable risk factors might be partially anchored in DNA sequence variation for these ''exposures.''…”

Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits

“…The coincidence is supported by reciprocal conditional analysis: after conditioning was performed on each lead eSNP, no GWAS variant remained significant (FDR < 1%), and after conditioning on each GWAS variant, 124 eSNP signals were no longer significant, and 16 were strongly attenuated (Dlog 10 (p) of 8.5 to 112 ) (Table S8). Of the 140 cis-eQTLs at GWAS loci, 93 (66.4%) were not previously reported by large-scale GWASs that interrogated available cis-eQTLs [14][15][16][17]38,45,48,[57][58][59][60][61][62][63][64][65][66][67][68] and 50 showed consistent direction of allelic effect at p < 0.05 in the MuTHER study. Table 1 shows 29 eQTLs for glycemic, obesity, and lipid traits at the LD threshold of r 2 > 0.9 between the GWAS variant and lead eSNP; three of these eQTLs were also identified with the SMR method.…”