Systemic lupus erythematosus (SLE) has a strong but incompletely understood genetic architecture. We conducted an association study with replication in 4,492 SLE cases and 12,675 controls from six East-Asian cohorts, to identify novel and better localize known SLE susceptibility loci. We identified 10 novel loci as well as 20 known loci with genome-wide significance. Among the novel loci, the most significant was GTF2IRD1-GTF2I at 7q11.23 (rs73366469, Pmeta=3.75×10−117, OR=2.38), followed by DEF6, IL12B, TCF7, TERT, CD226, PCNXL3, RASGRP1, SYNGR1 and SIGLEC6. We localized the most likely functional variants for each locus by analyzing epigenetic marks and gene regulation data. Ten putative variants are known to alter cis- or trans-gene expression. Enrichment analysis highlights the importance of these loci in B- and T-cell biology. Together with previously known loci, the explained heritability of SLE increases to 24%. Novel loci share functional and ontological characteristics with previously reported loci, and are possible drug targets for SLE therapeutics.

ObjectiveSystemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations.MethodsWe newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations.ResultsWe identified 113 genetic regions including 46 novel loci at genome-wide significance (p<5×10−8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (rg=−0.242) and non-albumin protein (rg=0.238).ConclusionThis study reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.

Objective A highly polygenic etiology and high degree of allele-sharing between ancestries have been well-elucidated in genetic studies of rheumatoid arthritis. Recently, the high-density genotyping array Immunochip for immune disease loci identified 14 new rheumatoid arthritis risk loci among individuals of European ancestry. Here, we aimed to identify new rheumatoid arthritis risk loci using Korean-specific Immunochip data. Methods We analyzed Korean rheumatoid arthritis case-control samples using the Immunochip and GWAS array to search for new risk alleles of rheumatoid arthritis with anti-citrullinated peptide antibodies. To increase power, we performed a meta-analysis of Korean data with previously published European Immunochip and GWAS data, for a total sample size of 9,299 Korean and 45,790 European case-control samples. Results We identified 8 new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1–FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p<5×10−8), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the 7 new loci except for the TNFSF4 locus (monomorphic in Koreans), together with risk alleles from previously established RA risk loci, exhibited a high correlation of effect sizes between ancestries. Further, we refined the number of SNPs that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs. Conclusion This study demonstrates the advantage of dense-mapping and trans-ancestral analysis for identification of potentially causal SNPs. In addition, our findings support the importance of T cells in the pathogenesis and the fact of frequent overlap of risk loci among diverse autoimmune diseases.

It has been suggested that hyperuricemia and possibly gout are associated with the metabolic syndrome, but there have been no direct studies. This study was undertaken to obtain the prevalence of the metabolic syndrome in patients with gout and to compare it with those from the general population studies. This was a 4-institutional case-historical control study composed of 168 patients with gout. We assessed the prevalence of metabolic syndrome according to the ATP III criteria and compared the prevalence with that of the historical controls. To elucidate the factors in gout that were associated with metabolic syndrome, a multivariate analysis was done. The age-adjusted prevalence of metabolic syndrome in gout patients was 43.6%, which was significantly higher than that of the Korean control population (5.2%) from the previous studies. Patients with gout had more components of metabolic syndrome than did the controls. Body mass index (BMI, OR=1.357 (95%CI 1.111-1.657)) and high density lipoprotein (HDL, OR=0.774 (95%CI 0.705-0.850)) were the variables most significantly associated with the occurrence of metabolic syndrome in gout, but alcohol consumption did not show such associations. Gout is associated with the metabolic syndrome, and furthermore, obesity and dyslipidemia were the factors most associated with the syndrome in these patients.

Objective Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder whose etiology is incompletely understood, but likely involves environmental triggers in genetically susceptible individuals. We sought to identify the genetic loci associated with SLE in a Korean population by performing an unbiased genome-wide association scan. Methods A total of 1,174 Korean SLE cases and 4,248 population controls were genotyped with strict quality control measures and analyzed for association. For select variants, replication was tested in an independent set of 1,412 SLE cases and 1,163 population controls of Korean and Chinese ancestries. Results Eleven regions outside the HLA exceeded genome-wide significance (P<5×10−8). A novel SNP-SLE association was identified between FCHSD2 and P2RY2 peaking at rs11235667 (P = 1.0×10−8, odds ratio (OR) = 0.59) on a 33kb haplotype upstream to ATG16L2. Replication for rs11235667 resulted in Pmeta-rep=0.001 and Pmeta-overall=6.67×10−11 (OR=0.63). Within the HLA region, association peaked in the Class II region at rs116727542 with multiple independent effects. Classical HLA allele imputation identified HLA-DRB1*1501 and HLA-DQB1*0602, both highly correlated, as most strongly associated with SLE. We replicated ten previously established SLE risk loci: STAT1-STAT4, TNFSF4, TNFAIP3, IKZF1, HIP1, IRF5, BLK, WDFY4, ETS1 and IRAK1-MECP2. Of these loci, we identified previously unreported independent second effects in TNFAIP3 and TNFSF4 as well as differences in the association for a putative causal variant in the WDFY4 region. Conclusions Further studies are needed to identify true SLE risk effects in other suggestive loci and to identify the causal variant(s) in the regions of ATG16L2, FCHSD2, and P2RY2.