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Query: UMLS:C0003873 (rheumatoid arthritis)
53,068 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

We examined the potential gene x gene interactions and gene x smoking interactions in rheumatoid arthritis (RA) using the candidate gene data sets provided by Genetic Analysis Workshop 15 Problem 2. The multifactor dimensionality reduction (MDR) method was used to test gene x gene interactions among candidate genes. The case-only sample was used to test gene x smoking interactions. The best predictive model was the single-locus model with single-nucleotide polymorphism (SNP) rs2476601 in gene PTPN22. However, no clear gene x gene interaction was identified. Substantial departure from multiplicativity was observed between smoking and SNPs in genes CTLA4, PADI4, MIF, and SNPs on chromosome 5 and one haplotype of PTPN22. The strongest evidence of association was identified between the PTPN22 gene and RA status, which was consistently detected in single SNP association, gene x gene interaction and gene x smoking interaction analyses.
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PMID:Evaluating gene x gene and gene x smoking interaction in rheumatoid arthritis using candidate genes in GAW15. 1846 13

Rheumatoid arthritis (RA) is an autoimmune disease with a moderately strong genetic component. Previous linkage and candidate gene studies have identified several regions that predispose to RA, including the HLA-DRB1 and PTPN22. We conducted genome-wide linkage analysis with 128 affected individuals from 60 families in a Canadian cohort that were genotyped using the Illumina linkage panel and genome-wide association analysis with 158 affected individuals from the same cohort that were genotyped using the Affymetrix 100 K platform. Multipoint nonparametric linkage scan revealed three linkage peaks with LOD scores greater than 1.5. We also identified 13 significantly associated SNPs at the genome-wide level of 0.05 after Bonferroni adjustment for multiple testing. Several of the significantly associated SNPs are located close to previously identified linkage regions, but not in the linkage peaks identified in the same cohort. We could not replicate association with HLA-DRB1 and PTPN22. Our results indicate that high coverage and sufficient sample size are crucial for the success of genome-wide association studies.
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PMID:Genome-wide linkage and association analysis of rheumatoid arthritis in a Canadian population. 1846 15

Haplotype association analysis based on arbitrarily chosen markers might lower statistical power because of the larger number of degrees of freedom caused by irrelevant makers.On the other hand, an exhaustive search for all possible combinations of markers for haplotype analysis is computationally expensive for genome-wide association analysis.To improve power, we applied our recently developed sequential haplotype scan method to case-control data for rheumatoid arthritis, including the PTPN22 candidate gene on chromosome 1p and the association mapping data on chromosome 18q, from the Genetic Analysis Workshop 15. The results showed that our new approach is at least as powerful as the traditional single-locus analysis and sometimes can be more powerful.
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PMID:Application of sequential haplotype scan methods to case-control data. 1846 18

We performed a case-control association analysis of rheumatoid arthritis (RA) for several candidate genes using the North American Rheumatoid Arthritis Consortium (NARAC) data provided in Genetic Analysis Workshop 15. We conducted the case-control association analysis using all related cases and unrelated controls and compared the results with those from the analysis of samples using only one randomly selected case from each family and all unrelated controls. For both analyses we used a weighted composite likelihood ratio test based on single-nucleotide polymorphism (SNP) markers or haplotypes accounting for the correlation among samples within a family. Several SNPs, including R620W in the candidate gene PTPN22, showed an association with RA status, which confirmed previously reported results. Several other SNPs in the candidate genes, such as CTLA4, HAVCR1, and SUMO4, also had rather small p-values (<0.05), suggesting the associations between them and RA. Our results showed that the p-values obtained from the analysis including all related cases were generally smaller than those obtained from the analysis including only one randomly selected case per family. These results, together with the results, based on simulated data, showed that higher power could be achieved using all related cases.
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PMID:Case-control association analysis of rheumatoid arthritis with candidate genes using related cases. 1846 31

In order to model the effect of PTPN22 on rheumatoid arthritis (RA), we determined the combination of single-nucleotide-polymorphisms (SNPs) showing the strongest association with RA. Three SNPs (rs2476601-rs12730735-rs11102685) were selected for which we estimated the genotypic relative risks (GRRs) of the corresponding genotypes. On the basis of these GRRs we defined four at-risk genotypic classes. Relative to the class of reference risk, individuals had a risk approximately multiplied by two, three, or four. This classification was confirmed by the excess of identity-by-descent (IBD) sharing (IBD = 2) for the sibs of an index in the high-risk class and by excess of non-IBD sharing (IBD = 0) when the index belonged to the low-risk class. The observed data could not be explained by the role of a single variant but were compatible either with a joint effect of the three typed SNPs of PTPN22 on RA or with the role of two untyped variants.
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PMID:Modeling the effect of PTPN22 in rheumatoid arthritis. 1846 35

The identification of susceptibility genes for common, chronic disease presents great challenges. The development of novel statistical and computational methodologies to help identify these genes is an area of great necessity. Much research is ongoing and the Genetic Analysis Workshop (GAW) is a venue for the dissemination and comparison of many of these methods. GAW15 included real data sets to look for disease susceptibility genes for rheumatoid arthritis (RA). RA is a complex, chronic inflammatory disease with several replicated disease genes, but much of the genetic variation in the phenotype remains unexplained. We applied two computational methods, namely multifactor dimensionality reduction (MDR) and grammatical evolution neural networks (GENN), to three data sets from GAW15. While these analytic methods were applied with the intention of detecting of multilocus models of association, both methods identified a strong single locus effect of a single-nucleotide polymorphism (SNP) in PTPN22 that is significantly associated with RA. This SNP has previously been associated with RA in several other published studies. These results demonstrate that both MDR and GENN are capable of identifying a single-locus main effect, in addition to multilocus models of association. This is the first published comparison of the two methods. Because GENN employs an evolutionary computation search strategy in comparison to the exhaustive search strategy of MDR, it is encouraging that the two methods produced similar results. This comparison should be extended in future studies with both simulated and real data.
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PMID:Exploring epistasis in candidate genes for rheumatoid arthritis. 1846 72

Accounting for interactions with environmental factors in association studies may improve the power to detect genetic effects and may help identifying important environmental effect modifiers. The power of unphased genotype-versus haplotype-based methods in regions with high linkage disequilibrium (LD), as measured by D', for analyzing gene x environment (gene x sex) interactions was compared using the Genetic Analysis Workshop 15 (GAW15) simulated data on rheumatoid arthritis with prior knowledge of the answers. Stepwise and regular conditional logistic regression (CLR) was performed using a matched case-control sample for a HLA region interacting with sex. Haplotype-based analyses were performed using a haplotype-sharing-based Mantel statistic and a test for haplotype-trait association in a general linear model framework. A step-down minP algorithm was applied to derive adjusted p-values and to allow for power comparisons. These methods were also applied to the GAW15 real data set for PTPN22.For markers in strong LD, stepwise CLR performed poorly because of the correlation/collinearity between the predictors in the model. The power was high for detecting genetic main effects using simple CLR models and haplotype-based methods and for detecting joint effects using CLR and Mantel statistics. Only the haplotype-trait association test had high power to detect the gene x sex interaction.In the PTPN22 region with markers characterized by strong LD, all methods indicated a significant genotype x sex interaction in a sample of about 1000 subjects. The previously reported R620W single-nucleotide polymorphism was identified using logistic regression, but the haplotype-based methods did not provide any precise location information.
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PMID:Comparison of the power of haplotype-based versus single- and multilocus association methods for gene x environment (gene x sex) interactions and application to gene x smoking and gene x sex interactions in rheumatoid arthritis. 1846 75

Rheumatoid arthritis (RA) is a chronic, systemic autoimmune disease affecting both joints and extra-articular tissues. Although some genetic risk factors for RA are well-established, most notably HLA-DRB1 and PTPN22, these markers do not fully account for the observed heritability. To identify additional susceptibility loci, we carried out a multi-tiered, case-control association study, genotyping 25,966 putative functional SNPs in 475 white North American RA patients and 475 matched controls. Significant markers were genotyped in two additional, independent, white case-control sample sets (661 cases/1322 controls from North America and 596 cases/705 controls from The Netherlands) identifying a SNP, rs1953126, on chromosome 9q33.2 that was significantly associated with RA (OR(common) = 1.28, trend P(comb) = 1.45E-06). Through a comprehensive fine-scale-mapping SNP-selection procedure, 137 additional SNPs in a 668 kb region from MEGF9 to STOM on 9q33.2 were chosen for follow-up genotyping in a staged-approach. Significant single marker results (P(comb)<0.01) spanned a large 525 kb region from FBXW2 to GSN. However, a variety of analyses identified SNPs in a 70 kb region extending from the third intron of PHF19 across TRAF1 into the TRAF1-C5 intergenic region, but excluding the C5 coding region, as the most interesting (trend P(comb): 1.45E-06 --> 5.41E-09). The observed association patterns for these SNPs had heightened statistical significance and a higher degree of consistency across sample sets. In addition, the allele frequencies for these SNPs displayed reduced variability between control groups when compared to other SNPs. Lastly, in combination with the other two known genetic risk factors, HLA-DRB1 and PTPN22, the variants reported here generate more than a 45-fold RA-risk differential.
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PMID:A large-scale rheumatoid arthritis genetic study identifies association at chromosome 9q33.2. 1864 37

Rheumatoid arthritis is a chronic inflammatory polyarthritis whose etiology remains uncertain. Recently we have learned that autoimmunity to citrullinated protein antigens has specificity for rheumatoid arthritis and defines a clinically and genetically distinct form of the disease. Multiple genes contribute to disease susceptibility, with the HLA locus accounting for 30% to 50% of overall genetic risk. Five risk loci have been identified and validated: HLA-DRB1, PTPN22, STAT4, a region in 6q23, and the TRAF1/C5 locus. Also, there is renewed interest in the contribution of T cells to ongoing inflammation in rheumatoid arthritis. Autoantibodies to citrullinated protein epitopes are specific for rheumatoid arthritis, are associated with a more aggressive disease course, and are pathogenic in an animal model of autoimmune arthritis. There is a strong association between shared-epitope-expressing HLA-DRB1 alleles and the development of rheumatoid arthritis associated with autoimmunity to citrullinated protein antigens.
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PMID:The immunopathogenesis of rheumatoid arthritis. 1895 86

PTPN22 620W is regarded as the second most important risk factor for type 1 diabetes and rheumatoid arthritis. Here we describe aspects of the molecular biology of the enzyme and its function, the geographical distribution of the 620W variant, as well as its importance in less frequent rheumatic diseases.
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PMID:[Relevance of the gene variant PTPN22 620W for rheumatology]. 1895 5


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