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Klareskog, L.

Publications and source records attributed to Klareskog, L..

3 recordsLinked to original sources

Sequencing of the MHC region defines HLA-DQA1 as the major independent risk for anti-citrullinated protein antibodies (ACPA)-positive rheumatoid arthritis in Han population

The strong genetic contribution of the major histocompatibility complex (MHC) to rheumatoid arthritis (RA) susceptibility has been generally attributed to HLA-DRB1. However, due to the high linkage disequilibrium in the MHC region, it is difficult to define the real or/and additional independent genetic risks using the conventional HLA genotyping or chip-based microarray technology. By the capture sequencing of entire MHC region for discovery and HLA-typing for validation in 2,773 subjects of Han ancestry, we identified HLA-DQ1:160D as the strongest independent genetic risk for anti-citrullinated protein antibodies (ACPA)-positive RA in Han population (P = 6.16 x 10-36, OR=2.29). Further stepwise conditional analysis revealed that DR{beta}1:37N has an independent protective effect on ACPA-positive RA (P = 5.81 x 10-16, OR=0.49). The DQ1:160 coding allele DQA1*0303 displayed high impact on joint radiographic severity, especially in patients with early disease and smoking (P = 3.02 x 10-5). Interaction analysis by comparative molecular modeling revealed that the negative charge of DQ1:160D stabilizes the dimer of dimers, leading to an increased T cell activation. The electrostatic potential surface analysis indicated that the negative charged DR{beta}1:37N encoding alleles could bind with epitope P9 arginine, thus may result in a decreased RA susceptibility.\n\nIn this study, we provide the first evidence that HLA-DQA1, instead of HLA-DRB1, is the strongest and independent genetic risk for ACPA-positive RA in Chinese Han population. Our study also illustrates the value of MHC deep sequencing for fine mapping disease risk variants in the MHC region.

genetics

The association between the HLA-DRB1 shared epitope alleles and the risk of rheumatoid arthritis is influenced by massive gene-gene interactions.

In anti-citrullinated protein antibody positive rheumatoid arthritis (ACPA-positive RA), a particular subset of HLA-DRB1 alleles, called shared epitope alleles (SE), is the highest genetic risk factor. Here, we aimed to investigate whether gene-gene interactions influence this HLA-DRB1 related major disease risk; specifically, we set out to test if non-HLA SNPs, conferring low diseases risk on their own, can modulate the HLA-DRB1 SE effect to develop ACPA-positive RA.\n\nTo address this question, we computed the attributable proportion (AP) due to additive interaction at genome-wide level for two independent ACPA-positive RA cohorts: the Swedish EIRA and the North American NARAC. We found a strong enrichment of significant interactions (AP p-values<0.05) between the HLA-DRB1 SE alleles and a group of SNPs associated with ACPA-positive RA in both cohorts (Kolmogorov-Smirnov [KS] test D=0.35 for EIRA and D=0.25 for NARAC, p<2.2e-16 for both). Interestingly, 201 out of 1,492 SNPs in consistent interaction for both cohorts, were eQTLs in SE alleles context in PBMCs from ACPA-positive RA patients. Finally, we observed that the effect size of HLA-DRB1 SE alleles for disease decreases from 5.2 to 2.5 after discounting the risk alleles of the two top interacting SNPs (rs2476601 and rs10739581, AP FDR corrected p <0.05).\n\nOur data demonstrate that the association between the HLA-DRB1 SE alleles and the risk of ACPA-positive RA is modulated by massive genetic interactions with non-HLA genetic variants.

genetics

Fine-mapping identifies causal variants for RA and T1D in DNASE1L3, SIRPG, MEG3, TNFAIP3 and CD28/CTLA4 loci

We fine-mapped 76 rheumatoid arthritis (RA) and type 1 diabetes (T1D) loci outside of the MHC. After sequencing 799 1kb regulatory (H3K4me3) regions within these loci in 568 individuals, we observed accurate imputation for 89% of common variants. We fine-mapped1,2 these loci in RA (11,475 cases, 15,870 controls)3, T1D (9,334 cases and 11,111 controls) 4 and combined datasets. We reduced the number of potential causal variants to [&le;]5 in 8 RA and 11 T1D loci. We identified causal missense variants in five loci (DNASE1L3, SIRPG, PTPN22, SH2B3 and TYK2) and likely causal non-coding variants in six loci (MEG3, TNFAIP3, CD28/CTLA4, ANKRD55, IL2RA, REL/PUS10). Functional analysis confirmed allele specific binding and differential enhancer activity for three variants: the CD28/CTLA4 rs117701653 SNP, the TNFAIP3 rs35926684 indel, and the MEG3 rs34552516 indel. This study demonstrates the potential for dense genotyping and imputation to pinpoint missense and non-coding causal alleles.

genetics