Searching across hundreds of databases
Psoriatic arthritis (PsA) is a chronic inflammatory musculoskeletal disease affecting up to 30% of psoriasis vulgaris (PsV) cases and approximately 0.25 to 1% of the general population. To identify common susceptibility loci, we performed a meta-analysis of three imputed genome-wide association studies (GWAS) on psoriasis, stratified for PsA. A total of 1,160,703 single-nucleotide polymorphisms (SNPs) were analyzed in the discovery set consisting of 535 PsA cases and 3,432 controls from Germany, the United States, and Canada. We followed up two SNPs in 1,931 PsA cases and 6,785 controls comprising six independent replication panels from Germany, Estonia, the United States, and Canada. In the combined analysis, a genome-wide significant association was detected at 2p16 near the REL locus encoding c-Rel (rs13017599, P=1.18 × 10(-8), odds ratio (OR)=1.27, 95% confidence interval (CI)=1.18-1.35). The rs13017599 polymorphism is known to associate with rheumatoid arthritis (RA), and another SNP near REL (rs702873) was recently implicated in PsV susceptibility. However, conditional analysis indicated that rs13017599, rather than rs702873, accounts for the PsA association at REL. We hypothesize that c-Rel, as a member of the Rel/NF-κB family, is associated with PsA in the context of disease pathways that involve other identified PsA and PsV susceptibility genes including TNIP1, TNFAIP3, and NFκBIA.
Pubmed ID: 22170493 RIS Download
Publication data is provided by the National Library of Medicine ® and PubMed ®. Data is retrieved from PubMed ® on a weekly schedule. For terms and conditions see the National Library of Medicine Terms and Conditions.
A portal to biomedical and genomic information. NCBI creates public databases, conducts research in computational biology, develops software tools for analyzing genome data, and disseminates biomedical information for the better understanding of molecular processes affecting human health and disease.
View all literature mentionsOpen source whole genome association analysis toolset, designed to perform range of basic, large scale analyses in computationally efficient manner. Used for analysis of genotype/phenotype data. Through integration with gPLINK and Haploview, there is some support for subsequent visualization, annotation and storage of results. PLINK 1.9 is improved and second generation of the software.
View all literature mentionsSoftware application designed to facilitate meta-analysis of large datasets (such as several whole genome scans) in a convenient, rapid and memory efficient manner. (entry from Genetic Analysis Software)
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
scicrunch.org
