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Meta-analysis of 28,141 individuals identifies common variants within five new loci that influence uric acid concentrations.

Authors :
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
Source :
PLoS Genetics, Vol 5, Iss 6, p e1000504 (2009)
Publication Year :
2009
Publisher :
Public Library of Science (PLoS), 2009.

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.

Subjects

Subjects :
Genetics
QH426-470

Details

Language :
English
ISSN :
15537390 and 15537404
Volume :
5
Issue :
6
Database :
Directory of Open Access Journals
Journal :
PLoS Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.ff4cc331981e449292132db7bb00d13e
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pgen.1000504