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

EUROSPAN Consortium; Melanie Kolz; Toby Johnson; Serena Sanna; Alexander Teumer; Veronique Vitart; Markus Perola; Massimo Mangino; Eva Albrecht; Chris Wallace; Martin Farrall; Asa Johansson; Dale R Nyholt; Yurii Aulchenko; Jacques S Beckmann; Sven Bergmann; Murielle Bochud; Morris Brown; Harry Campbell; John Connell; Anna Dominiczak; Georg Homuth; Claudia Lamina; Mark I McCarthy; Thomas Meitinger; Vincent Mooser; Patricia Munroe; Matthias Nauck; John Peden; Holger Prokisch; Perttu Salo; Veikko Salomaa; Nilesh J Samani; David Schlessinger; Manuela Uda; Uwe Völker; Gérard Waeber; Dawn Waterworth; Rui Wang-Sattler; Alan F Wright; Jerzy Adamski; John B Whitfield; Ulf Gyllensten; James F Wilson; Igor Rudan; Peter Pramstaller; Hugh Watkins; Angela Doering; H-Erich Wichmann; Tim D Spector; Leena Peltonen

doi:10.1371/journal.pgen.1000504

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

EUROSPAN Consortium, Melanie Kolz, Toby Johnson, Serena Sanna, Alexander Teumer, Veronique Vitart, Markus Perola, Massimo Mangino, Eva Albrecht, Chris Wallace, Martin Farrall, Asa Johansson, Dale R Nyholt, Yurii Aulchenko, Jacques S Beckmann, Sven Bergmann, Murielle Bochud, Morris Brown, Harry Campbell, John ConnellAnna Dominiczak, Georg Homuth, Claudia Lamina, Mark I McCarthy, Thomas Meitinger, Vincent Mooser, Patricia Munroe, Matthias Nauck, John Peden, Holger Prokisch, Perttu Salo, Veikko Salomaa, Nilesh J Samani, David Schlessinger, Manuela Uda, Uwe Völker, Gérard Waeber, Dawn Waterworth, Rui Wang-Sattler, Alan F Wright, Jerzy Adamski, John B Whitfield, Ulf Gyllensten, James F Wilson, Igor Rudan, Peter Pramstaller, Hugh Watkins, Angela Doering, H-Erich Wichmann, Tim D Spector, Leena Peltonen

Research output: Contribution to journal › Article › peer-review

Abstract

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 = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-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 = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-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.

Original language	English
Article number	e1000504
Pages (from-to)	-
Number of pages	10
Journal	PLoS Genetics
Volume	5
Issue number	6
DOIs	https://doi.org/10.1371/journal.pgen.1000504
Publication status	Published - Jun 2009

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10.1371/journal.pgen.1000504

Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations
Copyright: © 2009 Kolz et al. 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 credited.
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EUROSPAN Consortium, Kolz, M., Johnson, T., Sanna, S., Teumer, A., Vitart, V., Perola, M., Mangino, M., Albrecht, E., Wallace, C., Farrall, M., Johansson, A., Nyholt, D. R., Aulchenko, Y., Beckmann, J. S., Bergmann, S., Bochud, M., Brown, M., Campbell, H., ... Peltonen, L. (2009). Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations. PLoS Genetics, 5(6), -. [e1000504]. https://doi.org/10.1371/journal.pgen.1000504

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

abstract = "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 = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-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 = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-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.",

author = "{EUROSPAN Consortium} and Melanie Kolz and Toby Johnson and Serena Sanna and Alexander Teumer and Veronique Vitart and Markus Perola and Massimo Mangino and Eva Albrecht and Chris Wallace and Martin Farrall and Asa Johansson and Nyholt, {Dale R} and Yurii Aulchenko and Beckmann, {Jacques S} and Sven Bergmann and Murielle Bochud and Morris Brown and Harry Campbell and John Connell and Anna Dominiczak and Georg Homuth and Claudia Lamina and McCarthy, {Mark I} and Thomas Meitinger and Vincent Mooser and Patricia Munroe and Matthias Nauck and John Peden and Holger Prokisch and Perttu Salo and Veikko Salomaa and Samani, {Nilesh J} and David Schlessinger and Manuela Uda and Uwe V{\"o}lker and G{\'e}rard Waeber and Dawn Waterworth and Rui Wang-Sattler and Wright, {Alan F} and Jerzy Adamski and Whitfield, {John B} and Ulf Gyllensten and Wilson, {James F} and Igor Rudan and Peter Pramstaller and Hugh Watkins and Angela Doering and H-Erich Wichmann and Spector, {Tim D} and Leena Peltonen",

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EUROSPAN Consortium, Kolz, M, Johnson, T, Sanna, S, Teumer, A, Vitart, V, Perola, M, Mangino, M, Albrecht, E, Wallace, C, Farrall, M, Johansson, A, Nyholt, DR, Aulchenko, Y, Beckmann, JS, Bergmann, S, Bochud, M, Brown, M, Campbell, H, Connell, J, Dominiczak, A, Homuth, G, Lamina, C, McCarthy, MI, Meitinger, T, Mooser, V, Munroe, P, Nauck, M, Peden, J, Prokisch, H, Salo, P, Salomaa, V, Samani, NJ, Schlessinger, D, Uda, M, Völker, U, Waeber, G, Waterworth, D, Wang-Sattler, R, Wright, AF, Adamski, J, Whitfield, JB, Gyllensten, U, Wilson, JF , Rudan, I, Pramstaller, P, Watkins, H, Doering, A, Wichmann, H-E, Spector, TD & Peltonen, L 2009, 'Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations', PLoS Genetics, vol. 5, no. 6, e1000504, pp. -. https://doi.org/10.1371/journal.pgen.1000504

TY - JOUR

T1 - Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

AU - EUROSPAN Consortium

AU - Kolz, Melanie

AU - Johnson, Toby

AU - Sanna, Serena

AU - Teumer, Alexander

AU - Vitart, Veronique

AU - Perola, Markus

AU - Mangino, Massimo

AU - Albrecht, Eva

AU - Wallace, Chris

AU - Farrall, Martin

AU - Johansson, Asa

AU - Nyholt, Dale R

AU - Aulchenko, Yurii

AU - Beckmann, Jacques S

AU - Bergmann, Sven

AU - Bochud, Murielle

AU - Brown, Morris

AU - Campbell, Harry

AU - Connell, John

AU - Dominiczak, Anna

AU - Homuth, Georg

AU - Lamina, Claudia

AU - McCarthy, Mark I

AU - Meitinger, Thomas

AU - Mooser, Vincent

AU - Munroe, Patricia

AU - Nauck, Matthias

AU - Peden, John

AU - Prokisch, Holger

AU - Salo, Perttu

AU - Salomaa, Veikko

AU - Samani, Nilesh J

AU - Schlessinger, David

AU - Uda, Manuela

AU - Völker, Uwe

AU - Waeber, Gérard

AU - Waterworth, Dawn

AU - Wang-Sattler, Rui

AU - Wright, Alan F

AU - Adamski, Jerzy

AU - Whitfield, John B

AU - Gyllensten, Ulf

AU - Wilson, James F

AU - Rudan, Igor

AU - Pramstaller, Peter

AU - Watkins, Hugh

AU - Doering, Angela

AU - Wichmann, H-Erich

AU - Spector, Tim D

AU - Peltonen, Leena

PY - 2009/6

Y1 - 2009/6

N2 - 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 = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-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 = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-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.

AB - 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 = 5.2x10(-201)), ABCG2 (p = 3.1x10(-26)), SLC17A1 (p = 3.0x10(-14)), SLC22A11 (p = 6.7x10(-14)), SLC22A12 (p = 2.0x10(-9)), SLC16A9 (p = 1.1x10(-8)), GCKR (p = 1.4x10(-9)), LRRC16A (p = 8.5x10(-9)), and near PDZK1 (p = 2.7x10(-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 = 4.0x10(-26)) and propionyl-L-carnitine (p = 5.0x10(-8)) concentrations, which in turn were associated with serum UA levels (p = 1.4x10(-57) and p = 8.1x10(-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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DO - 10.1371/journal.pgen.1000504

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SN - 1553-7390

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M1 - e1000504

ER -

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

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