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

We recently proposed a new strategy: 2-locus TDT for detecting two susceptibility genes through their interaction in trio families. We apply our method to two candidate genes, A and C, on the Genetic Analysis Workshop 15 (GAW15) simulated rheumatoid arthritis data and study the power to identify an interactive effect of these genes.This study was performed with full knowledge of the answers.
BMC Proc 2007
PMID:Power of the 2-locus TDT for testing the interaction of two susceptibility genes. 1846 66

Rheumatoid arthritis (RA) is a multifactorial disease with complex genetic etiology, about which little is known. Here, we apply a two-stage procedure in which a quick first-stage analysis was used to narrow down targets for a more thorough and detailed testing for gene x gene interaction. Potentially interesting regions were first identified by testing for major gene effects using non-parametric linkage methods. To select regions of interest, we first tested for linkage to three different RA-related traits one at a time: RA affection status and the quantitative phenotypes rheumatoid factor IgM and anti-cyclic citrullinated peptide levels. These linkage analyses identified regions on chromosomes 3, 5, 6, 8, 16, 18, 19, and 20. We subsequently analyzed the selected regions in a pairwise manner to detect gene x gene interactions influencing RA using a recently developed two-dimensional linkage method. We found evidence of interacting loci on chromosomes 5, 6, and 18.
BMC Proc 2007
PMID:Two-dimensional linkage analyses of rheumatoid arthritis. 1846 69

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.
BMC Proc 2007
PMID:Exploring epistasis in candidate genes for rheumatoid arthritis. 1846 72

Rheumatoid arthritis (RA) is a complex disease that involves both environmental and genetic factors. Elucidation of the basic etiologic factors involved in RA is essential for preventing and treating this disease. However, the etiology of RA, like that of other complex diseases, is largely unknown. In the present study, we conducted autosomal multipoint linkage scans using affected sib pairs by incorporating the smoking status into analysis. We divided the affected sib pairs into three subgroups based on smoking status (ever, current, or never). Interactions between the susceptibility genes and smoking could then be assessed through linkage mapping. Results suggested that the genetic effect of chromosome 6p21.2-3 in concordant current smoker pairs was about two-fold greater than that of the concordant non-current smoker pairs or discordant pairs. With incorporation of smoking status, additional regions with evidence of linkage were identified, including chromosomes 4q and 20q; while evidence of linkage remained in the regions of chromosomes 6p, 8p, and 9p. The interaction effects varied in different regions. Results from our analyses suggested that incorporating smoking status into linkage analyses could increase the statistical power of the multipoint linkage approach applied here and help elucidate the etiology of RA.
BMC Proc 2007
PMID:Assessing genotype x environment interaction in linkage mapping using affected sib pairs. 1846 73

The restricted partition method (RPM) provides a way to detect qualitative factors (e.g. genotypes, environmental exposures) associated with variation in quantitative or binary phenotypes, even if the contribution is predominantly an interaction displaying little or no signal in univariate analyses. The RPM provides a model (possibly non-linear) of the relationship between the predictor covariates and the phenotype as well as measures of statistical and clinical significance for the model.Blind to the generating model, we used the RPM to screen a data set consisting 1500 unrelated cases and 2000 unrelated controls from Replicate 1 of the Genetic Analysis Workshop 15 Problem 3 data for genetic and environmental factors contributing to rheumatoid arthritis (RA) risk. Both univariate and pair-wise analyses were performed using sex, smoking, parental DRB1 HLA microsatellite alleles, and 9187 single-nucleotide polymorphisms genotypes from across the genome. With this approach we correctly identified three genetic loci contributing directly to RA risk, and one quantitative trait locus for the endophenotype IgM level. We did not mistakenly identify any factors not in the generating model. All the factors we found were detectable with univariate RPM analyses. We failed to identify two genetic loci modifying the risk of RA. After breaking the blind, we examined the true modeling factors in the first 50 data replicates and found that we would not have identified the additional factors as important even had we combined all the data from the first 50 replicates in a single data set.
BMC Proc 2007
PMID:Gene x gene and gene x environment interactions for complex disorders. 1846 74

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.
BMC Proc 2007
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

We incorporate population effects of sex and antibodies directed against cyclic citrullinated peptides (anti-CCP) into the linkage analysis of rheumatoid arthritis (RA) with microsatellites data provided by the North American Rheumatoid Arthritis Consortium in Genetic Analysis Workshop 15.The method stems from a generalized linear mixed model that incorporates the marginal population effects of important covariates. The resulting test for linkage is based on a score test in a pseudo-likelihood of this model. The mathematical derivation is given elsewhere but the test has a simple and appealing form: it assigns weights to excess identity-by-descent sharing between pairs of related individuals depending on the individual-specific values of the covariates and phenotypes.Although RA is three times more prevalent in women than in men, the weights derived for male-male, female-male, and female-female affected sib pairs turn out to be very similar and the sex-adjusted analysis hardly differs from an unadjusted analysis. High anti-CCP levels are known to strongly predict RA. Our test assigns very small weights to pairs whose anti-CCP levels are high for the two siblings, sib pairs with two low anti-CCP levels are those most contributing to the evidence for linkage. Comparison of the unadjusted and the anti-CCP-adjusted analyses identifies persisting peaks mapping to regions that can be attributed to a 'dimension' of RA independent of anti-CCP.
BMC Proc 2007
PMID:Adjusting for sex and anti-CCP levels in linkage analysis of rheumatoid arthritis. 1846 77

Focusing on chromosome 1, a recursive partitioning linkage algorithm (RP) was applied to perform linkage analysis on the rheumatoid arthritis NARAC data, incorporating covariates such as HLA-DRB1 genotype, age at onset, severity, anti-cyclic citrullinated peptide (anti-CCP), and life time smoking. All 617 affected sib pairs from the ascertained families were used, and an RP linkage model was used to identify linkage possibly influenced by covariates. This algorithm includes a likelihood ratio (LR)-based splitting rule, a pruning algorithm to identify optimal tree size, and a bootstrap method for final tree selection.The strength of the linkage signals was evaluated by empirical p-values, obtained by simulating marker data under null hypothesis of no linkage. Two suggestive linkage regions on chromosome 1 were detected by the RP linkage model, with identified associated covariates HLA-DRB1 genotype and age at onset. These results suggest possible gene x gene and gene x environment interactions at chromosome 1 loci and provide directions for further gene mapping.
BMC Proc 2007
PMID:Evidence of linkage to chromosome 1 for early age of onset of rheumatoid arthritis and HLA marker DRB1 genotype in NARAC data. 1846 80

Genome scan meta-analysis (GSMA) can prove very useful in detecting genetic effects too small to be detected in an individual linkage study and can also lead to more consistent results. In this paper, we propose a new kernel-based estimation procedure for GSMA. Instead of estimating identity by descent between markers, as performed in interval mapping approaches, we estimated directly the nonparametric linkage score between markers using a kernel procedure. The GSMA is then extended to take into account the kernel estimate of the nonparametric linkage score and its variance at a given chromosomal position. The method is applied to the rheumatoid arthritis genome scan data (Genetic Analysis Workshop 15 Problem 2).
BMC Proc 2007
PMID:Novel approach for genome scan meta-analysis of rheumatoid arthritis: a kernel-based estimation procedure. 1846

We performed linkage analysis on families with rheumatoid arthritis, stratifying by ethnic origin. We compared results using either Kong and Cox nonparametric LOD scores or MOD score analysis using the software GeneHunter MODSCORE. We first applied SNPLINK to remove markers showing excess linkage disequilibrium from the SNPs in the Illumina IV SNP Linkage panel. In this analysis there were 659 self-reported Caucasian families and 29 self-reported Hispanic families in the NARAC collection. Chromosome 19 yielded MOD scores > 3.00 in the Hispanic group, while chromosomes 2, 6, 7, 11, and XY had MOD scores > 3.00 in the Caucasian group. We performed simulation studies to evaluate the empirical distribution of the MOD score for autosomal loci separately in Hispanics and Caucasians. Results showed genome-wide significant evidence for linkage in Caucasians for chromosomes 2q and 6p, but no significant evidence for any linkages in the Hispanics, including little evidence for linkage to chromosome 6p in this group. An examination of the difference of phenotypes in two ethnic groups suggested significantly earlier mean age of onset, higher percentage of anti-cyclic citrullinated peptide positive people, and lower percentage of affected people carrying shared epitopes in Hispanics than those in Caucasians. A larger sample size of the Hispanic group is needed to identify linkage regions.
BMC Proc 2007
PMID:Comparison of genome-wide single-nucleotide polymorphism linkage analyses in Caucasian and Hispanic NARAC families. 1846 1


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