Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
06/05/2014 - Room Garden Room at 14:00 - External Seminar
(University of Lausanne)
Metabolic traits are molecular phenotypes that can drive clinical phenotypes and may predict disease progression. I will present results from a metabolome- and genome-wide association study on 1H-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. My talk will focus on the the bioinformatics aspects of our work which has been has been published in PLoS Genetics 10(2): e1004132.