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Träfflista för sökning "WFRF:(Plenge Robert M.) ;lar1:(ki)"

Search: WFRF:(Plenge Robert M.) > Karolinska Institutet

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1.
  • Graham, R. Robert, et al. (author)
  • Three functional variants of IFN regulatory factor 5 (IRF5) define risk and protective haplotypes for human lupus
  • 2007
  • In: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424 .- 1091-6490. ; 104:16, s. 6758-6763
  • Journal article (peer-reviewed)abstract
    • Systematic genome-wide studies to map genomic regions associated with human diseases are becoming more practical. Increasingly, efforts will be focused on the identification of the specific functional variants responsible for the disease. The challenges of identifying causal variants include the need for complete ascertainment of genetic variants and the need to consider the possibility of multiple causal alleles. We recently reported that risk of systemic lupus erythematosus (SLE) is strongly associated with a common SNP in IFN regulatory factor 5 (IRF5), and that this variant altered spicing in a way that might provide a functional explanation for the reproducible association to SLE risk. Here, by resequencing and genotyping in patients with SLE, we find evidence for three functional alleles of IRF5: the previously described exon 1B splice site variant, a 30-bp in-frame insertion/deletion variant of exon 6 that alters a proline-, glutamic acid-, serine- and threonine-rich domain region, and a variant in a conserved polyA+ signal sequence that alters the length of the 3' UTR and stability of IRF5 mRNAs. Haplotypes of these three variants define at least three distinct levels of risk to SLE. Understanding how combinations of variants influence IRF5 function may offer etiological and therapeutic insights in SLE; more generally, IRF5 and SLE illustrates how multiple common variants of the same gene can together influence risk of common disease.
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2.
  • Okada, Yukinori, et al. (author)
  • Genetics of rheumatoid arthritis contributes to biology and drug discovery
  • 2014
  • In: Nature. - : Nature Publishing Group. - 0028-0836 .- 1476-4687. ; 506:7488, s. 376-381
  • Journal article (peer-reviewed)abstract
    • A major challenge in human genetics is to devise a systematic strategy to integrate disease-associated variants with diverse genomic and biological data sets to provide insight into disease pathogenesis and guide drug discovery for complex traits such as rheumatoid arthritis (RA)(1). Here we performed a genome-wide association study meta-analysis in a total of >100,000 subjects of European and Asian ancestries (29,880 RA cases and 73,758 controls), by evaluating similar to 10 million single-nucleotide polymorphisms. We discovered 42 novel RA risk loci at a genome-wide level of significance, bringing the total to 101 (refs 2-4). We devised an in silico pipeline using established bioinformatics methods based on functional annotation(5), cis-acting expression quantitative trait loci(6) and pathway analyses(7-9)-as well as novel methods based on genetic overlap with human primary immunodeficiency, haematological cancer somatic mutations and knockout mouse phenotypes-to identify 98 biological candidate genes at these 101 risk loci. We demonstrate that these genes are the targets of approved therapies for RA, and further suggest that drugs approved for other indications may be repurposed for the treatment of RA. Together, this comprehensive genetic study sheds light on fundamental genes, pathways and cell types that contribute to RA pathogenesis, and provides empirical evidence that the genetics of RA can provide important information for drug discovery.
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3.
  • Källberg, Henrik, et al. (author)
  • Gene-gene and gene-environment interactions involving HLA-DRB1, PTPN22, and smoking in two subsets of rheumatoid arthritis
  • 2007
  • In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 80:5, s. 867-875
  • Journal article (peer-reviewed)abstract
    • Gene-gene and gene-environment interactions are key features in the development of rheumatoid arthritis (RA) and other complex diseases. The aim of this study was to use and compare three different definitions of interaction between the two major genetic risk factors of RA—the HLA-DRB1 shared epitope (SE) alleles and the PTPN22 R620W allele—in three large case-control studies: the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) study, the North American RA Consortium (NARAC) study, and the Dutch Leiden Early Arthritis Clinic study (in total, 1,977 cases and 2,405 controls). The EIRA study was also used to analyze interactions between smoking and the two genes. “Interaction” was defined either as a departure from additivity, as interaction in a multiplicative model, or in terms of linkage disequilibrium—for example, deviation from independence of penetrance of two unlinked loci. Consistent interaction, defined as departure from additivity, between HLA-DRB1 SE alleles and the A allele of PTPN22 R620W was seen in all three studies regarding anti-CCP–positive RA. Testing for multiplicative interactions demonstrated an interaction between the two genes only when the three studies were pooled. The linkage disequilibrium approach indicated a gene-gene interaction in EIRA and NARAC, as well as in the pooled analysis. No interaction was seen between smoking and PTPN22 R620W. A new pattern of interactions is described between the two major known genetic risk factors and the major environmental risk factor concerning the risk of developing anti-CCP–positive RA. The data extend the basis for a pathogenetic hypothesis for RA involving genetic and environmental factors. The study also raises and illustrates principal questions concerning ways to define interactions in complex diseases.
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4.
  • Kim, Kwangwoo, et al. (author)
  • High-density genotyping of immune loci in Koreans and Europeans identifies eight new rheumatoid arthritis risk loci
  • 2015
  • In: Annals of the Rheumatic Diseases. - : BMJ. - 0003-4967 .- 1468-2060. ; 74:3
  • Journal article (peer-reviewed)abstract
    • Objective A highly polygenic aetiology 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 analysed Korean rheumatoid arthritis case-control samples using the Immunochip and genome-wide association studies (GWAS) array to search for new risk alleles of rheumatoid arthritis with anticitrullinated 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 9299 Korean and 45 790 European case-control samples. Results We identified eight new rheumatoid arthritis susceptibility loci (TNFSF4, LBH, EOMES, ETS1-FLI1, COG6, RAD51B, UBASH3A and SYNGR1) that passed a genome-wide significance threshold (p<5x10(-8)), with evidence for three independent risk alleles at 1q25/TNFSF4. The risk alleles from the seven 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 single nucleotide polymorphisms (SNPs) that represent potentially causal variants through a trans-ethnic comparison of densely genotyped SNPs. Conclusions 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.
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5.
  • Han, Buhm, et al. (author)
  • Fine Mapping Seronegative and Seropositive Rheumatoid Arthritis to Shared and Distinct HLA Alleles by Adjusting for the Effects of Heterogeneity
  • 2014
  • In: American Journal of Human Genetics. - : Elsevier BV. - 0002-9297 .- 1537-6605. ; 94:4, s. 522-532
  • Journal article (peer-reviewed)abstract
    • Despite progress in defining human leukocyte antigen (HLA) alleles for anti-citrullinated-protein-autoantibody-positive (ACPA(+)) rheumatoid arthritis (RA), identifying HLA alleles for ACPA-negative (ACPA(-)) RA has been challenging because of clinical heterogeneity within clinical cohorts. We imputed 8,961 classical HLA alleles, amino acids, and SNPs from Immunochip data in a discovery set of 2,406 ACPA(-) RA case and 13,930 control individuals. We developed a statistical approach to identify and adjust for clinical heterogeneity within ACPA RA and observed independent associations for serine and leucine at position 11 in HLA-DR beta 1 (p = 1.4 x 10 (13), odds ratio [OR] = 1.30) and for aspartate at position 9 in HLA-B (p = 2.7 x 10(-12), OR = 1.39) within the peptide binding grooves. These amino acid positions induced associations at HLA-DRB1*03 (encoding serine at 11) and HLA-B*08 (encoding aspartate at 9). We validated these findings in an independent set of 427 ACPA(-) case subjects, carefully phenotyped with a highly sensitive ACPA assay, and 1,691 control subjects (HLA-DR beta 1 Ser11+Leu11: p = 5.8 x 10(-4), OR = 1.28; HLA-B Asp9: p = 2.6 x 10(-3), OR = 1.34). Although both amino acid sites drove risk of ACPA(+) and ACPA(-) disease, the effects of individual residues at HLA-DR beta 1 position 11 were distinct (p < 2.9 x 10(-107)). We also identified an association with ACPA(+) RA at HLA-A position 77 (p = 2.7 x 10(-8), OR = 0.85) in 7,279 ACPA(+) RA case and 15,870 control subjects. These results contribute to mounting evidence that ACPA(+) and ACPA(-) RA are genetically distinct and potentially have separate autoantigens contributing to pathogenesis. We expect that our approach might have broad applications in analyzing clinical conditions with heterogeneity at both major histocompatibility complex (MHC) and non-MHC regions.
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