Genome-wide association study of clinically defined Gout identifies multiple risk loci and its association with clinical subtypes

Hirotaka Matsuo, Ken Yamamoto, Hirofumi Nakaoka, Akiyoshi Nakayama, Masayuki Sakiyama, Toshinori Chiba, Atsushi Takahashi, Takahiro Nakamura, Hiroshi Nakashima, Yuzo Takada, Inaho Danjoh, Seiko Shimizu, Junko Abe, Yusuke Kawamura, Sho Terashige, Hiraku Ogata, Seishiro Tatsukawa, Guang Yin, Rieko Okada, Emi MoritaMariko Naito, Atsumi Tokumasu, Hiroyuki Onoue, Keiichi Iwaya, Toshimitsu Ito, Tappei Takada, Katsuhisa Inoue, Yukio Kato, Yukio Nakamura, Yutaka Sakurai, Hiroshi Suzuki, Yoshikatsu Kanai, Tatsuo Hosoya, Nobuyuki Hamajima, Ituro Inoue, Michiaki Kubo, Kimiyoshi Ichida, Hiroshi Ooyama, Toru Shimizu, Nariyoshi Shinomiya

Research output: Contribution to journalArticlepeer-review

127 Citations (Scopus)


Objective: Gout, caused by hyperuricaemia, is a multifactorial disease. Although genome-wide association studies (GWASs) of gout have been reported, they included self-reported gout cases in which clinical information was insufficient. Therefore, the relationship between genetic variation and clinical subtypes of gout remains unclear. Here, we first performed a GWAS of clinically defined gout cases only. Methods: A GWAS was conducted with 945 patients with clinically defined gout and 1213 controls in a Japanese male population, followed by replication study of 1048 clinically defined cases and 1334 controls. Results: Five gout susceptibility loci were identified at the genome-wide significance level (p<5.0×10-8), which contained well-known urate transporter genes (ABCG2 and SLC2A9) and additional genes: rs1260326 (p=1.9×10-12; OR=1.36) of GCKR (a gene for glucose and lipid metabolism), rs2188380 (p=1.6×10-23; OR=1.75) of MYL2-CUX2 (genes associated with cholesterol and diabetes mellitus) and rs4073582 (p=6.4×10-9; OR=1.66) of CNIH-2 (a gene for regulation of glutamate signalling). The latter two are identified as novel gout loci. Furthermore, among the identified single-nucleotide polymorphisms (SNPs), we demonstrated that the SNPs of ABCG2 and SLC2A9 were differentially associated with types of gout and clinical parameters underlying specific subtypes (renal underexcretion type and renal overload type). The effect of the risk allele of each SNP on clinical parameters showed significant linear relationships with the ratio of the case-control ORs for two distinct types of gout (r=0.96 [p=4.8×10-4] for urate clearance and r=0.96 [p=5.0×10-4] for urinary urate excretion). Conclusions Our findings provide clues to better understand the pathogenesis of gout and will be useful for development of companion diagnostics.

Original languageEnglish
Pages (from-to)652-659
Number of pages8
JournalAnnals of the Rheumatic Diseases
Issue number4
Publication statusPublished - 04-2016
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Rheumatology
  • Immunology and Allergy
  • Immunology
  • Biochemistry, Genetics and Molecular Biology(all)


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