FLT3 stop mutation increases FLT3 ligand level and risk of autoimmune thyroid disease

The type I interferon pathway has been implicated in the pathogenesis of a number of rheumatic diseases, including systemic lupus erythematosus, Sjögren syndrome, myositis, systemic sclerosis, and rheumatoid arthritis. In normal immune responses, type I interferons have a critical role in the defence against viruses, yet in many rheumatic diseases, large subgroups of patients demonstrate persistent activation of the type I interferon pathway. Genetic variations in type I interferon-related genes are risk factors for some rheumatic diseases, and can explain some of the heterogeneity in type I interferon responses seen between patients within a given disease. Inappropriate activation of the immune response via Toll-like receptors and other nucleic acid sensors also contributes to the dysregulation of the type I interferon pathway in a number of rheumatic diseases. Theoretically, differences in type I interferon activity between patients might predict response to immune-based therapies, as has been demonstrated for rheumatoid arthritis. A number of type I interferon and type I interferon pathway blocking therapies are currently in clinical trials, the results of which are promising thus far. This Review provides an overview of the many ways in which the type I interferon system affects rheumatic diseases.

Graves' disease is a common autoimmune disorder characterized by thyroid stimulating hormone receptor autoantibodies (TRAb) and hyperthyroidism. To investigate the genetic architecture of Graves' disease, we conducted a genome-wide association study in 1,536 individuals with Graves' disease (cases) and 1,516 controls. We further evaluated a group of associated SNPs in a second set of 3,994 cases and 3,510 controls. We confirmed four previously reported loci (in the major histocompatibility complex, TSHR, CTLA4 and FCRL3) and identified two new susceptibility loci (the RNASET2-FGFR1OP-CCR6 region at 6q27 (P(combined) = 6.85 × 10(-10) for rs9355610) and an intergenic region at 4p14 (P(combined) = 1.08 × 10(-13) for rs6832151)). These newly associated SNPs were correlated with the expression levels of RNASET2 at 6q27, of CHRNA9 and of a previously uncharacterized gene at 4p14, respectively. Moreover, we identified strong associations of TSHR and major histocompatibility complex class II variants with persistently TRAb-positive Graves' disease.

We repurposed existing genotypes in DNA biobanks across the Electronic Medical Records and Genomics network to perform a genome-wide association study for primary hypothyroidism, the most common thyroid disease. Electronic selection algorithms incorporating billing codes, laboratory values, text queries, and medication records identified 1317 cases and 5053 controls of European ancestry within five electronic medical records (EMRs); the algorithms' positive predictive values were 92.4% and 98.5% for cases and controls, respectively. Four single-nucleotide polymorphisms (SNPs) in linkage disequilibrium at 9q22 near FOXE1 were associated with hypothyroidism at genome-wide significance, the strongest being rs7850258 (odds ratio [OR] 0.74, p = 3.96 × 10(-9)). This association was replicated in a set of 263 cases and 1616 controls (OR = 0.60, p = 5.7 × 10(-6)). A phenome-wide association study (PheWAS) that was performed on this locus with 13,617 individuals and more than 200,000 patient-years of billing data identified associations with additional phenotypes: thyroiditis (OR = 0.58, p = 1.4 × 10(-5)), nodular (OR = 0.76, p = 3.1 × 10(-5)) and multinodular (OR = 0.69, p = 3.9 × 10(-5)) goiters, and thyrotoxicosis (OR = 0.76, p = 1.5 × 10(-3)), but not Graves disease (OR = 1.03, p = 0.82). Thyroid cancer, previously associated with this locus, was not significantly associated in the PheWAS (OR = 1.29, p = 0.09). The strongest association in the PheWAS was hypothyroidism (OR = 0.76, p = 2.7 × 10(-13)), which had an odds ratio that was nearly identical to that of the curated case-control population in the primary analysis, providing further validation of the PheWAS method. Our findings indicate that EMR-linked genomic data could allow discovery of genes associated with many diseases without additional genotyping cost. Copyright © 2011 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.