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Brief Report: IRF4 Newly Identified as a Common Susceptibility Locus for Systemic Sclerosis and Rheumatoid Arthritis in a Cross-Disease Meta-Analysis of Genome-Wide Association Studies.

Arthritis Rheumatol; 68(9): 2338-44, 2016 09.
Artigo em Inglês | MEDLINE | ID: mdl-27111665

OBJECTIVE:

Systemic sclerosis (SSc) and rheumatoid arthritis (RA) are autoimmune diseases that have similar clinical and immunologic characteristics. To date, several shared SSc-RA genetic loci have been identified independently. The aim of the current study was to systematically search for new common SSc-RA loci through an interdisease meta-genome-wide association (meta-GWAS) strategy.

METHODS:

The study was designed as a meta-analysis combining GWAS data sets of patients with SSc and patients with RA, using a strategy that allowed identification of loci with both same-direction and opposite-direction allelic effects. The top single-nucleotide polymorphisms were followed up in independent SSc and RA case-control cohorts. This allowed an increase in the sample size to a total of 8,830 patients with SSc, 16,870 patients with RA, and 43,393 healthy controls.

RESULTS:

This cross-disease meta-analysis of the GWAS data sets identified several loci with nominal association signals (P < 5 × 10(-6) ) that also showed evidence of association in the disease-specific GWAS scans. These loci included several genomic regions not previously reported as shared loci, as well as several risk factors that were previously found to be associated with both diseases. Follow-up analyses of the putatively new SSc-RA loci identified IRF4 as a shared risk factor for these 2 diseases (Pcombined = 3.29 × 10(-12) ). Analysis of the biologic relevance of the known SSc-RA shared loci identified the type I interferon and interleukin-12 signaling pathways as the main common etiologic factors.

CONCLUSION:

This study identified a novel shared locus, IRF4, for the risk of SSc and RA, and highlighted the usefulness of a cross-disease GWAS meta-analysis strategy in the identification of common risk loci.