Genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links

Abstract

Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. Here, we report results from a metabolome- and genome-wide association study on (1)H-NMR urine metabolic profiles. The study was conducted within an untargeted approach, employing a novel method for compound identification. From our discovery cohort of 835 Caucasian individuals who participated in the CoLaus study, we identified 139 suggestively significant (P<5×10(-8)) and independent associations between single nucleotide polymorphisms (SNP) and metabolome features. Fifty-six of these associations replicated in the TasteSensomics cohort, comprising 601 individuals from São Paulo of vastly diverse ethnic background. They correspond to eleven gene-metabolite associations, six of which had been previously identified in the urine metabolome and three in the serum metabolome. Our key novel findings are the associations of two SNPs with NMR spectral signatures pointing to fucose (rs492602, P = 6.9×10(-44)) and lysine (rs8101881, P = 1.2×10(-33)), respectively. Fine-mapping of the first locus pinpointed the FUT2 gene, which encodes a fucosyltransferase enzyme and has previously been associated with Crohn's disease. This implicates fucose as a potential prognostic disease marker, for which there is already published evidence from a mouse model. The second SNP lies within the SLC7A9 gene, rare mutations of which have been linked to severe kidney damage. The replication of previous associations and our new discoveries demonstrate the potential of untargeted metabolomics GWAS to robustly identify molecular disease markers.

Figure 1. Genome- and metabolome-wide analysis results, first stage.

(A) Manhattan plot for feature 1.2025. (B) Genome- and metabolome-wide P-value heat map, showing associations with P_C<5×10⁻⁸ in CoLaus. (C) Pseudo-spectrum for SNP rs37369, obtained by plotting the association P-values between rs37369 and all metabolic features.

Figure 2. Metabomatching.

Each subfigure compares the CoLaus pseudo-spectrum (bottom half) with the NMR spectrum (top half) of the most likely candidate for the associated metabolite. (A) rs37369 vs. 3-aminoisobutyrate. (B) rs2147896 in PYROXD2 vs. trimethylamine (C) rs8101881 in SLC7A9 vs. lysine (D) rs281408 in FUT2 vs. fucose.

Figure 3. Local Manhattan plots.

The Manhattan plots show combined −log(P-values) in the neighborhood of the most strongly associated SNP for (A) the FUT2 with fucose association, and (B) the SLC7A9 with lysine association.

Figure 4. Genotype-Metabotype-Phenotype associations.

The two novel gene-metabolite associations of this study implicate SNPs that had previously been associated with disease-related phenotypes by the indicated publications: (A) Fucose–Crohn's disease–FUT2 (rs492602), (B) Lysine–eGFR–SLC7A9 (rs8101881). A link between the metabolite and the phenotype has been established for (A) based on a mouse model and for (B) by a direct correlation with the indicated significance and effect size. Abbreviations: OR refers to the odds ratio, x to the linear regression effect size, P to the corresponding P-value, and the m-index indicates values obtained in the combined CoLaus and TasteSensomics sample.