BACKGROUND-Rheumatoid arthritis has a complex mode of inheritance. Although HLA-DRB1 and PTPN22 are well-established susceptibility loci, other genes that confer a modest level of risk have been identified recently. We carried out a genomewide association analysis to identify additional genetic loci associated with an increased risk of rheumatoid arthritis.
A haplotype of STAT4 is associated with increased risk for both rheumatoid arthritis and systemic lupus erythematosus, suggesting a shared pathway for these illnesses.
Autoimmune disorders constitute a diverse group of phenotypes with overlapping features and a tendency toward familial aggregation. It is likely that common underlying genes are involved in these disorders. Until very recently, no specific alleles--aside from a few common human leukocyte antigen class II genes--had been identified that clearly associate with multiple different autoimmune diseases. In this study, we describe a unique collection of 265 multiplex families assembled by the Multiple Autoimmune Disease Genetics Consortium (MADGC). At least two of nine "core" autoimmune diseases are present in each of these families. These core diseases include rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), type 1 diabetes (T1D), multiple sclerosis (MS), autoimmune thyroid disease (Hashimoto thyroiditis or Graves disease), juvenile RA, inflammatory bowel disease (Crohn disease or ulcerative colitis), psoriasis, and primary Sjogren syndrome. We report that a recently described functional single-nucleotide polymorphism (rs2476601, encoding R620W) in the intracellular tyrosine phosphatase (PTPN22) confers risk of four separate autoimmune phenotypes in these families: T1D, RA, SLE, and Hashimoto thyroiditis. MS did not show association with the PTPN22 risk allele. These findings suggest a common underlying etiologic pathway for some, but not all, autoimmune disorders, and they suggest that MS may have a pathogenesis that is distinct from RA, SLE, and T1D. DNA and clinical data for the MADGC families are available to the scientific community; these data will provide a valuable resource for the dissection of the complex genetic factors that underlie the various autoimmune phenotypes.
It is shown that the distribution of word frequencies for randomly generated texts is very similar to Zipf's law observed in natural languages such as the English. The facts that the frequency of occurrence of a word is almost an inverse power law function of its rank and the exponent of this inverse power law is very close to 1 are largely due to the transformation from the word's length to its rank, which stretches an exponential function to a power law function.
BackgroundSystemic lupus erythematosus (SLE) is a serious systemic autoimmune disorder that affects multiple organ systems and is characterized by unpredictable flares of disease. Recent evidence indicates a role for type I interferon (IFN) in SLE pathogenesis; however, the downstream effects of IFN pathway activation are not well understood. Here we test the hypothesis that type I IFN-regulated proteins are present in the serum of SLE patients and correlate with disease activity.Methods and FindingsWe performed a comprehensive survey of the serologic proteome in human SLE and identified dysregulated levels of 30 cytokines, chemokines, growth factors, and soluble receptors. Particularly striking was the highly coordinated up-regulation of 12 inflammatory and/or homeostatic chemokines, molecules that direct the movement of leukocytes in the body. Most of the identified chemokines were inducible by type I IFN, and their levels correlated strongly with clinical and laboratory measures of disease activity.ConclusionsThese data suggest that severely disrupted chemokine gradients may contribute to the systemic autoimmunity observed in human SLE. Furthermore, the levels of serum chemokines may serve as convenient biomarkers for disease activity in lupus.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.