We provide the first evidence for association with gout at four loci (IGF1R, PDZK1, MAF, HLF). Understanding why there is lack of correlation between urate and gout effect sizes will be important in understanding the aetiology of gout.

A pragmatic approach that balances the benefit of a whole-genome association (WGA) experiment against the cost of individual genotyping is to use pooled genomic DNA samples. We aimed to determine the feasibility of this approach in a WGA scan in rheumatoid arthritis (RA) using the validated human leucocyte antigen (HLA) and PTPN22 associations as test loci. A total of 203 269 single-nucleotide polymorphisms (SNPs) on the Affymetrix 100K GeneChip and Illumina Infinium microarrays were examined. A new approach to the estimation of allele frequencies from Affymetrix hybridization intensities was developed involving weighting for quality signals from the probe quartets. SNPs were ranked by z-scores, combined from United Kingdom and New Zealand case-control cohorts. Within a 1.7 Mb HLA region, 33 of the 257 SNPs and at PTPN22, 21 of the 45 SNPs, were ranked within the top 100 associated SNPs genome wide. Within PTPN22, individual genotyping of SNP rs1343125 within MAGI3 confirmed association and provided some evidence for association independent of the PTPN22 620W variant (P ¼ 0.03). Our results emphasize the feasibility of using genomic DNA pooling for the detection of association with complex disease susceptibility alleles. The results also underscore the importance of the HLA and PTPN22 loci in RA aetiology.

BackgroundGout progresses through three stages: hyperuricemia, deposition of monosodium urate (MSU) crystals, and innate immune system response to MSU crystals. Genome wide association studies (GWAS) have provided insight into the molecular control of progression to hyperuricemia. However, less is known about the progression from hyperuricemia to gout.ObjectivesTo conduct a GWAS for gout (where an immune response to MSU crystals has occurred) using 5,835 cases - the largest GWAS of gout to date.MethodsThe GWAS comprised 3 data sets: NZ/Eurogout (2,365 clinically-ascertained cases; 1,485 controls), the Health Professionals Follow-Up (HPFS) and Nurses' Health Studies (NHS) (1,038 cases, self-ascertained using ACR criteria; 1,095 controls), and UK Biobank (2,432 cases, ascertained by self-report of gout, hospital records, and/or use of urate-lowering therapy; 102,989 controls). The NZ/Eurogout samples were genotyped using the Illumina CoreExome v24 bead chip array (547,644 markers), the HPFS/NHS samples using the Illumina OmniExpress v12 bead chip array (730,525 markers), and the UK Biobank samples using an Affymetrix Axiom array (820,967 markers). UK Biobank genotypes had been imputed to ∼73.3M SNPs. Neither the NZ/Eurogout nor NHS/HPFS genotype sets were imputed. Markers common to all three data sets (279,939) were associated with gout (adjusted for sex, age) within each data set separately using PLINK 1.9. An inverse-variance weighted meta-analysis was done with meta v4.4 in R.ResultsThere were seven loci with genome-wide significant (P<5x10-8) evidence for association with gout: SLC2A9 (OR=1.67), ABCG2(OR=1.72), GCKR (OR=1.24), SLC17A1-A4 (OR=1.20), SLC22A12 (OR=1.21), PDZK1 (OR=1.14), TRIM46 (OR=1.18).ConclusionsAll seven loci have been previously associated with serum urate levels in GWAS. Our data emphasise the relative importance of genetic control of serum urate, compared to the genetic control of MSU crystal formation or the innate immune response, in determining gout.Disclosure of InterestNone declared