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Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links

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 nove...

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Autores principales: Rueedi, Rico, Ledda, Mirko, Nicholls, Andrew W., Salek, Reza M., Marques-Vidal, Pedro, Morya, Edgard, Sameshima, Koichi, Montoliu, Ivan, Da Silva, Laeticia, Collino, Sebastiano, Martin, François-Pierre, Rezzi, Serge, Steinbeck, Christoph, Waterworth, Dawn M., Waeber, Gérard, Vollenweider, Peter, Beckmann, Jacques S., Le Coutre, Johannes, Mooser, Vincent, Bergmann, Sven, Genick, Ulrich K., Kutalik, Zoltán
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3930510/
https://www.ncbi.nlm.nih.gov/pubmed/24586186
http://dx.doi.org/10.1371/journal.pgen.1004132
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author Rueedi, Rico
Ledda, Mirko
Nicholls, Andrew W.
Salek, Reza M.
Marques-Vidal, Pedro
Morya, Edgard
Sameshima, Koichi
Montoliu, Ivan
Da Silva, Laeticia
Collino, Sebastiano
Martin, François-Pierre
Rezzi, Serge
Steinbeck, Christoph
Waterworth, Dawn M.
Waeber, Gérard
Vollenweider, Peter
Beckmann, Jacques S.
Le Coutre, Johannes
Mooser, Vincent
Bergmann, Sven
Genick, Ulrich K.
Kutalik, Zoltán
author_facet Rueedi, Rico
Ledda, Mirko
Nicholls, Andrew W.
Salek, Reza M.
Marques-Vidal, Pedro
Morya, Edgard
Sameshima, Koichi
Montoliu, Ivan
Da Silva, Laeticia
Collino, Sebastiano
Martin, François-Pierre
Rezzi, Serge
Steinbeck, Christoph
Waterworth, Dawn M.
Waeber, Gérard
Vollenweider, Peter
Beckmann, Jacques S.
Le Coutre, Johannes
Mooser, Vincent
Bergmann, Sven
Genick, Ulrich K.
Kutalik, Zoltán
author_sort Rueedi, Rico
collection PubMed
description 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.
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spelling pubmed-39305102014-02-25 Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links Rueedi, Rico Ledda, Mirko Nicholls, Andrew W. Salek, Reza M. Marques-Vidal, Pedro Morya, Edgard Sameshima, Koichi Montoliu, Ivan Da Silva, Laeticia Collino, Sebastiano Martin, François-Pierre Rezzi, Serge Steinbeck, Christoph Waterworth, Dawn M. Waeber, Gérard Vollenweider, Peter Beckmann, Jacques S. Le Coutre, Johannes Mooser, Vincent Bergmann, Sven Genick, Ulrich K. Kutalik, Zoltán PLoS Genet Research Article 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. Public Library of Science 2014-02-20 /pmc/articles/PMC3930510/ /pubmed/24586186 http://dx.doi.org/10.1371/journal.pgen.1004132 Text en © 2014 Rueedi et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Rueedi, Rico
Ledda, Mirko
Nicholls, Andrew W.
Salek, Reza M.
Marques-Vidal, Pedro
Morya, Edgard
Sameshima, Koichi
Montoliu, Ivan
Da Silva, Laeticia
Collino, Sebastiano
Martin, François-Pierre
Rezzi, Serge
Steinbeck, Christoph
Waterworth, Dawn M.
Waeber, Gérard
Vollenweider, Peter
Beckmann, Jacques S.
Le Coutre, Johannes
Mooser, Vincent
Bergmann, Sven
Genick, Ulrich K.
Kutalik, Zoltán
Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
title Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
title_full Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
title_fullStr Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
title_full_unstemmed Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
title_short Genome-Wide Association Study of Metabolic Traits Reveals Novel Gene-Metabolite-Disease Links
title_sort genome-wide association study of metabolic traits reveals novel gene-metabolite-disease links
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3930510/
https://www.ncbi.nlm.nih.gov/pubmed/24586186
http://dx.doi.org/10.1371/journal.pgen.1004132
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