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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2009-06-01
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doaj-ff4cc331981e449292132db7bb00d13e2020-11-24T21:41:39ZengPublic Library of Science (PLoS)PLoS Genetics1553-73901553-74042009-06-0156e100050410.1371/journal.pgen.1000504Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations.Melanie KolzToby JohnsonSerena SannaAlexander TeumerVeronique VitartMarkus PerolaMassimo ManginoEva AlbrechtChris WallaceMartin FarrallAsa JohanssonDale R NyholtYurii AulchenkoJacques S BeckmannSven BergmannMurielle BochudMorris BrownHarry CampbellEUROSPAN ConsortiumJohn ConnellAnna DominiczakGeorg HomuthClaudia LaminaMark I McCarthyENGAGE ConsortiumThomas MeitingerVincent MooserPatricia MunroeMatthias NauckJohn PedenHolger ProkischPerttu SaloVeikko SalomaaNilesh J SamaniDavid SchlessingerManuela UdaUwe VölkerGérard WaeberDawn WaterworthRui Wang-SattlerAlan F WrightJerzy AdamskiJohn B WhitfieldUlf GyllenstenJames F WilsonIgor RudanPeter PramstallerHugh WatkinsPROCARDIS ConsortiumAngela DoeringH-Erich WichmannKORA StudyTim D SpectorLeena PeltonenHenry VölzkeRamaiah NagarajaPeter VollenweiderMark CaulfieldWTCCCThomas IlligChristian GiegerElevated 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.http://europepmc.org/articles/PMC2683940?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
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 EUROSPAN Consortium John Connell Anna Dominiczak Georg Homuth Claudia Lamina Mark I McCarthy ENGAGE Consortium 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 PROCARDIS Consortium Angela Doering H-Erich Wichmann KORA Study Tim D Spector Leena Peltonen Henry Völzke Ramaiah Nagaraja Peter Vollenweider Mark Caulfield WTCCC Thomas Illig Christian Gieger |
spellingShingle |
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 EUROSPAN Consortium John Connell Anna Dominiczak Georg Homuth Claudia Lamina Mark I McCarthy ENGAGE Consortium 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 PROCARDIS Consortium Angela Doering H-Erich Wichmann KORA Study Tim D Spector Leena Peltonen Henry Völzke Ramaiah Nagaraja Peter Vollenweider Mark Caulfield WTCCC Thomas Illig Christian Gieger Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations. PLoS Genetics |
author_facet |
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 EUROSPAN Consortium John Connell Anna Dominiczak Georg Homuth Claudia Lamina Mark I McCarthy ENGAGE Consortium 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 PROCARDIS Consortium Angela Doering H-Erich Wichmann KORA Study Tim D Spector Leena Peltonen Henry Völzke Ramaiah Nagaraja Peter Vollenweider Mark Caulfield WTCCC Thomas Illig Christian Gieger |
author_sort |
Melanie Kolz |
title |
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_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_sort |
meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS Genetics |
issn |
1553-7390 1553-7404 |
publishDate |
2009-06-01 |
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 = 5.2x10(-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. |
url |
http://europepmc.org/articles/PMC2683940?pdf=render |
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