Genome-wide association study revealed novel loci which aggravate asymptomatic hyperuricaemia into gout

Objective The first ever genome-wide association study (GWAS) of clinically defined gout cases and asymptomatic hyperuricaemia (AHUA) controls was performed to identify novel gout loci that aggravate AHUA into gout. Methods We carried out a GWAS of 945 clinically defined gout cases and 1003 AHUA controls followed by 2 replication studies. In total, 2860 gout cases and 3149 AHUA controls (all Japanese men) were analysed. We also compared the ORs for each locus in the present GWAS (gout vs AHUA) with those in the previous GWAS (gout vs normouricaemia). Results This new approach enabled us to identify two novel gout loci (rs7927466 of CNTN5 and rs9952962 of MIR302F) and one suggestive locus (rs12980365 of ZNF724) at the genome-wide significance level (p<5.0×10– 8). The present study also identified the loci of ABCG2, ALDH2 and SLC2A9. One of them, rs671 of ALDH2, was identified as a gout locus by GWAS for the first time. Comparing ORs for each locus in the present versus the previous GWAS revealed three ‘gout vs AHUA GWAS’-specific loci (CNTN5, MIR302F and ZNF724) to be clearly associated with mechanisms of gout development which distinctly differ from the known gout risk loci that basically elevate serum uric acid level. Conclusions This meta-analysis is the first to reveal the loci associated with crystal-induced inflammation, the last step in gout development that aggravates AHUA into gout. Our findings should help to elucidate the molecular mechanisms of gout development and assist the prevention of gout attacks in high-risk AHUA individuals

Subtype-specific gout susceptibility loci and enrichment of selection pressure on ABCG2 and ALDH2 identified by subtype genome-wide meta-analyses of clinically defined gout patients

Objectives Genome-wide meta-analyses of clinically defined gout were performed to identify subtype-specific susceptibility loci. Evaluation using selection pressure analysis with these loci was also conducted to investigate genetic risks characteristic of the Japanese population over the last 2000–3000 years. Methods Two genome-wide association studies (GWASs) of 3053 clinically defined gout cases and 4554 controls from Japanese males were performed using the Japonica Array and Illumina Array platforms. About 7.2 million single-nucleotide polymorphisms were meta-analysed after imputation. Patients were then divided into four clinical subtypes (the renal underexcretion type, renal overload type, combined type and normal type), and meta-analyses were conducted in the same manner. Selection pressure analyses using singleton density score were also performed on each subtype. Results In addition to the eight loci we reported previously, two novel loci, PIBF1 and ACSM2B, were identified at a genome-wide significance level (p<5.0×10–8) from a GWAS meta-analysis of all gout patients, and other two novel intergenic loci, CD2-PTGFRN and SLC28A3-NTRK2, from normal type gout patients. Subtype-dependent patterns of Manhattan plots were observed with subtype GWASs of gout patients, indicating that these subtype-specific loci suggest differences in pathophysiology along patients’ gout subtypes. Selection pressure analysis revealed significant enrichment of selection pressure on ABCG2 in addition to ALDH2 loci for all subtypes except for normal type gout. Conclusions Our findings on subtype GWAS meta-analyses and selection pressure analysis of gout will assist elucidation of the subtype-dependent molecular targets and evolutionary involvement among genotype, phenotype and subtype-specific tailor-made medicine/prevention of gout and hyperuricaemia

E. coli expression of TIMP-4 and comparative kinetic studies with TIMP-1 and TIMP-2:insights into the interactions of TIMPs and matrix metalloproteinase 2 (gelatinase A)

The inhibitory properties of TIMP-4 for matrix metalloproteinases (MMPs) were compared to those of TIMP-1 and TIMP-2. Full-length human TIMP-4 was expressed in E. coli, folded from inclusion bodies, and the active component was purified by MMP-1 affinity chromatography. Progress curve analysis of MMP inhibition by TIMP-4 indicated that association rate constants (k(on)) and inhibition constants (K(i)) were similar to those for other TIMPs ( approximately 10(5) M(-)(1) s(-)(1) and 10(-)(9)-10(-)(12) M, respectively). Dissociation rate constants (k(off)) for MMP-1 and MMP-3 determined using alpha(2)-macroglobulin to capture MMP dissociating from MMP-TIMP complexes were in good agreement with values deduced from progress curves ( approximately 10(-)(4) s(-)(1)). K(i) and k(on) for the interactions of TIMP-1, -2, and -4 with MMP-1 and -3 were shown to be pH dependent. TIMP-4 retained higher reactivity with MMPs at more acidic conditions than either TIMP-1 or TIMP-2. Molecular interactions of TIMPs and MMPs investigated by IAsys biosensor analysis highlighted different modes of interaction between proMMP-2-TIMP-2 (or TIMP-4) and active MMP-2-TIMP-2 (or TIMP-4) complexes. The observation that both active MMP-2 and inactive MMP-2 (with the active site blocked either by the propeptide or a hydroxamate inhibitor) have essentially identical affinities for TIMP-2 suggests that there are two TIMP binding sites on the hemopexin domain of MMP-2: one with high affinity that is involved in proMMP-2 or hydroxamate-inhibited MMP-2; and the other with low affinity involved in formation of the complex of active MMP-2 and TIMP-2. Similar models of interaction may apply to TIMP-4. The latter low-affinity site functions in conjunction with the active site of MMP-2 to generate a tight enzyme-inhibitor complex