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Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, r...

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Autores principales: Kolz, Melanie, Johnson, Toby, Sanna, Serena, Teumer, Alexander, Vitart, Veronique, Perola, Markus, Mangino, Massimo, Albrecht, Eva, Wallace, Chris, Farrall, Martin, Johansson, Åsa, Nyholt, Dale R., Aulchenko, Yurii, Beckmann, Jacques S., Bergmann, Sven, Bochud, Murielle, Brown, Morris, Campbell, Harry, Connell, John, Dominiczak, Anna, Homuth, Georg, Lamina, Claudia, McCarthy, Mark I., Meitinger, Thomas, Mooser, Vincent, Munroe, Patricia, Nauck, Matthias, Peden, John, Prokisch, Holger, Salo, Perttu, Salomaa, Veikko, Samani, Nilesh J., Schlessinger, David, Uda, Manuela, Völker, Uwe, Waeber, Gérard, Waterworth, Dawn, Wang-Sattler, Rui, Wright, Alan F., Adamski, Jerzy, Whitfield, John B., Gyllensten, Ulf, Wilson, James F., Rudan, Igor, Pramstaller, Peter, Watkins, Hugh, Doering, Angela, Wichmann, H.-Erich, Spector, Tim D., Peltonen, Leena, Völzke, Henry, Nagaraja, Ramaiah, Vollenweider, Peter, Caulfield, Mark, Illig, Thomas, Gieger, Christian
Formato: Texto
Lenguaje:English
Publicado: Public Library of Science 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2683940/
https://www.ncbi.nlm.nih.gov/pubmed/19503597
http://dx.doi.org/10.1371/journal.pgen.1000504
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author Kolz, Melanie
Johnson, Toby
Sanna, Serena
Teumer, Alexander
Vitart, Veronique
Perola, Markus
Mangino, Massimo
Albrecht, Eva
Wallace, Chris
Farrall, Martin
Johansson, Åsa
Nyholt, Dale R.
Aulchenko, Yurii
Beckmann, Jacques S.
Bergmann, Sven
Bochud, Murielle
Brown, Morris
Campbell, Harry
Connell, John
Dominiczak, Anna
Homuth, Georg
Lamina, Claudia
McCarthy, Mark I.
Meitinger, Thomas
Mooser, Vincent
Munroe, Patricia
Nauck, Matthias
Peden, John
Prokisch, Holger
Salo, Perttu
Salomaa, Veikko
Samani, Nilesh J.
Schlessinger, David
Uda, Manuela
Völker, Uwe
Waeber, Gérard
Waterworth, Dawn
Wang-Sattler, Rui
Wright, Alan F.
Adamski, Jerzy
Whitfield, John B.
Gyllensten, Ulf
Wilson, James F.
Rudan, Igor
Pramstaller, Peter
Watkins, Hugh
Doering, Angela
Wichmann, H.-Erich
Spector, Tim D.
Peltonen, Leena
Völzke, Henry
Nagaraja, Ramaiah
Vollenweider, Peter
Caulfield, Mark
Illig, Thomas
Gieger, Christian
author_facet Kolz, Melanie
Johnson, Toby
Sanna, Serena
Teumer, Alexander
Vitart, Veronique
Perola, Markus
Mangino, Massimo
Albrecht, Eva
Wallace, Chris
Farrall, Martin
Johansson, Åsa
Nyholt, Dale R.
Aulchenko, Yurii
Beckmann, Jacques S.
Bergmann, Sven
Bochud, Murielle
Brown, Morris
Campbell, Harry
Connell, John
Dominiczak, Anna
Homuth, Georg
Lamina, Claudia
McCarthy, Mark I.
Meitinger, Thomas
Mooser, Vincent
Munroe, Patricia
Nauck, Matthias
Peden, John
Prokisch, Holger
Salo, Perttu
Salomaa, Veikko
Samani, Nilesh J.
Schlessinger, David
Uda, Manuela
Völker, Uwe
Waeber, Gérard
Waterworth, Dawn
Wang-Sattler, Rui
Wright, Alan F.
Adamski, Jerzy
Whitfield, John B.
Gyllensten, Ulf
Wilson, James F.
Rudan, Igor
Pramstaller, Peter
Watkins, Hugh
Doering, Angela
Wichmann, H.-Erich
Spector, Tim D.
Peltonen, Leena
Völzke, Henry
Nagaraja, Ramaiah
Vollenweider, Peter
Caulfield, Mark
Illig, Thomas
Gieger, Christian
author_sort Kolz, Melanie
collection PubMed
description Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10(−201)), ABCG2 (p = 3.1×10(−26)), SLC17A1 (p = 3.0×10(−14)), SLC22A11 (p = 6.7×10(−14)), SLC22A12 (p = 2.0×10(−9)), SLC16A9 (p = 1.1×10(−8)), GCKR (p = 1.4×10(−9)), LRRC16A (p = 8.5×10(−9)), and near PDZK1 (p = 2.7×10(−9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10(−26)) and propionyl-L-carnitine (p = 5.0×10(−8)) concentrations, which in turn were associated with serum UA levels (p = 1.4×10(−57) and p = 8.1×10(−54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels.
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spelling pubmed-26839402009-06-05 Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations Kolz, Melanie Johnson, Toby Sanna, Serena Teumer, Alexander Vitart, Veronique Perola, Markus Mangino, Massimo Albrecht, Eva Wallace, Chris Farrall, Martin Johansson, Åsa Nyholt, Dale R. Aulchenko, Yurii Beckmann, Jacques S. Bergmann, Sven Bochud, Murielle Brown, Morris Campbell, Harry Connell, John Dominiczak, Anna Homuth, Georg Lamina, Claudia McCarthy, Mark I. Meitinger, Thomas Mooser, Vincent Munroe, Patricia Nauck, Matthias Peden, John Prokisch, Holger Salo, Perttu Salomaa, Veikko Samani, Nilesh J. Schlessinger, David Uda, Manuela Völker, Uwe Waeber, Gérard Waterworth, Dawn Wang-Sattler, Rui Wright, Alan F. Adamski, Jerzy Whitfield, John B. Gyllensten, Ulf Wilson, James F. Rudan, Igor Pramstaller, Peter Watkins, Hugh Doering, Angela Wichmann, H.-Erich Spector, Tim D. Peltonen, Leena Völzke, Henry Nagaraja, Ramaiah Vollenweider, Peter Caulfield, Mark Illig, Thomas Gieger, Christian PLoS Genet Research Article Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10(−201)), ABCG2 (p = 3.1×10(−26)), SLC17A1 (p = 3.0×10(−14)), SLC22A11 (p = 6.7×10(−14)), SLC22A12 (p = 2.0×10(−9)), SLC16A9 (p = 1.1×10(−8)), GCKR (p = 1.4×10(−9)), LRRC16A (p = 8.5×10(−9)), and near PDZK1 (p = 2.7×10(−9)). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10(−26)) and propionyl-L-carnitine (p = 5.0×10(−8)) concentrations, which in turn were associated with serum UA levels (p = 1.4×10(−57) and p = 8.1×10(−54), respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels. Public Library of Science 2009-06-05 /pmc/articles/PMC2683940/ /pubmed/19503597 http://dx.doi.org/10.1371/journal.pgen.1000504 Text en Kolz 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
Kolz, Melanie
Johnson, Toby
Sanna, Serena
Teumer, Alexander
Vitart, Veronique
Perola, Markus
Mangino, Massimo
Albrecht, Eva
Wallace, Chris
Farrall, Martin
Johansson, Åsa
Nyholt, Dale R.
Aulchenko, Yurii
Beckmann, Jacques S.
Bergmann, Sven
Bochud, Murielle
Brown, Morris
Campbell, Harry
Connell, John
Dominiczak, Anna
Homuth, Georg
Lamina, Claudia
McCarthy, Mark I.
Meitinger, Thomas
Mooser, Vincent
Munroe, Patricia
Nauck, Matthias
Peden, John
Prokisch, Holger
Salo, Perttu
Salomaa, Veikko
Samani, Nilesh J.
Schlessinger, David
Uda, Manuela
Völker, Uwe
Waeber, Gérard
Waterworth, Dawn
Wang-Sattler, Rui
Wright, Alan F.
Adamski, Jerzy
Whitfield, John B.
Gyllensten, Ulf
Wilson, James F.
Rudan, Igor
Pramstaller, Peter
Watkins, Hugh
Doering, Angela
Wichmann, H.-Erich
Spector, Tim D.
Peltonen, Leena
Völzke, Henry
Nagaraja, Ramaiah
Vollenweider, Peter
Caulfield, Mark
Illig, Thomas
Gieger, Christian
Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
title Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
title_full Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
title_fullStr Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
title_full_unstemmed Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
title_short Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
title_sort meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2683940/
https://www.ncbi.nlm.nih.gov/pubmed/19503597
http://dx.doi.org/10.1371/journal.pgen.1000504
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