Title |
Identification of low-frequency variants associated with gout and serum uric acid levels
|
---|---|
Published in |
Nature Genetics, October 2011
|
DOI | 10.1038/ng.972 |
Pubmed ID | |
Authors |
Patrick Sulem, Daniel F Gudbjartsson, G Bragi Walters, Hafdis T Helgadottir, Agnar Helgason, Sigurjon A Gudjonsson, Carlo Zanon, Soren Besenbacher, Gyda Bjornsdottir, Olafur T Magnusson, Gisli Magnusson, Eirikur Hjartarson, Jona Saemundsdottir, Arnaldur Gylfason, Adalbjorg Jonasdottir, Hilma Holm, Ari Karason, Thorunn Rafnar, Hreinn Stefansson, Ole A Andreassen, Jesper H Pedersen, Allan I Pack, Marieke C H de Visser, Lambertus A Kiemeney, Arni J Geirsson, Gudmundur I Eyjolfsson, Isleifur Olafsson, Augustine Kong, Gisli Masson, Helgi Jonsson, Unnur Thorsteinsdottir, Ingileif Jonsdottir, Kari Stefansson |
Abstract |
We tested 16 million SNPs, identified through whole-genome sequencing of 457 Icelanders, for association with gout and serum uric acid levels. Genotypes were imputed into 41,675 chip-genotyped Icelanders and their relatives, for effective sample sizes of 968 individuals with gout and 15,506 individuals for whom serum uric acid measurements were available. We identified a low-frequency missense variant (c.1580C>G) in ALDH16A1 associated with gout (OR = 3.12, P = 1.5 × 10(-16), at-risk allele frequency = 0.019) and serum uric acid levels (effect = 0.36 s.d., P = 4.5 × 10(-21)). We confirmed the association with gout by performing Sanger sequencing on 6,017 Icelanders. The association with gout was stronger in males relative to females. We also found a second variant on chromosome 1 associated with gout (OR = 1.92, P = 0.046, at-risk allele frequency = 0.986) and serum uric acid levels (effect = 0.48 s.d., P = 4.5 × 10(-16)). This variant is close to a common variant previously associated with serum uric acid levels. This work illustrates how whole-genome sequencing data allow the detection of associations between low-frequency variants and complex traits. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 2 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 2 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Hungary | 1 | <1% |
Australia | 1 | <1% |
United Kingdom | 1 | <1% |
Iceland | 1 | <1% |
Mexico | 1 | <1% |
Japan | 1 | <1% |
Unknown | 111 | 95% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 32 | 27% |
Student > Ph. D. Student | 25 | 21% |
Professor > Associate Professor | 8 | 7% |
Student > Master | 8 | 7% |
Student > Postgraduate | 6 | 5% |
Other | 24 | 21% |
Unknown | 14 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 42 | 36% |
Medicine and Dentistry | 25 | 21% |
Biochemistry, Genetics and Molecular Biology | 19 | 16% |
Computer Science | 5 | 4% |
Nursing and Health Professions | 2 | 2% |
Other | 8 | 7% |
Unknown | 16 | 14% |