Data from: Insight in genome-wide association of metabolite quantitative traits by exome sequence analyses

Metabolite quantitative traits carry great promise for epidemiological
studies, and their genetic background has been addressed using Genome-Wide
Association Studies (GWAS). Thus far, the role of less common variants has
not been exhaustively studied. Here, we set out a GWAS for metabolite
quantitative traits in serum, followed by exome sequence analysis to zoom
in on putative causal variants in the associated genes. 1H Nuclear
Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful
quantification of 42 unique metabolites in 2,482 individuals from The
Erasmus Rucphen Family (ERF) study. Heritability of metabolites were
estimated by SOLAR. GWAS was performed by linear mixed models, using
HapMap imputations. Based on physical vicinity and pathway analyses,
candidate genes were screened for coding region variation using exome
sequence data. Heritability estimates for metabolites ranged between 10%
and 52%. GWAS replicated three known loci in the metabolome wide
significance: CPS1 with glycine (P-value = 1.27×10−32), PRODH with proline
(P-value = 1.11×10−19), SLC16A9 with carnitine level (P-value =
4.81×10−14) and uncovered a novel association between DMGDH and
dimethyl-glycine (P-value = 1.65×10−19) level. In addition, we found three
novel, suggestively significant loci: TNP1 with pyruvate (P-value =
1.26×10−8), KCNJ16 with 3-hydroxybutyrate (P-value = 1.65×10−8) and 2p12
locus with valine (P-value = 3.49×10−8). Exome sequence analysis
identified potentially causal coding and regulatory variants located in
the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for
CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected
by high-resolution 1H-NMR is a robust approach to uncover metabolite
quantitative trait loci (mQTL), and the likely causative variants in these
loci. It is anticipated that insight in the genetics of intermediate
phenotypes will provide additional insight into the genetics of complex
traits.