Identification of a genetic variant for joint damage progression in autoantibody-positive rheumatoid arthritis

BACKGROUND: Joint destruction is a hallmark of autoantibody-positive rheumatoid arthritis (RA), though the severity is highly variable between patients. The processes underlying these interindividual differences are incompletely understood. METHODS: We performed a genome-wide association study on the radiological progression rate in 384 autoantibody-positive patients with RA. In stage-II 1557 X-rays of 301 Dutch autoantibody-positive patients with RA were studied and in stage-III 861 X-rays of 742 North American autoantibody-positive patients with RA. Sperm-Associated Antigen 16 (SPAG16) expression in RA synovium and fibroblast-like synoviocytes (FLS) was examined using Real-Time Quantitative Polymerase Chain Reaction (RT-qPCR) and immunohistochemistry. FLS secrete metalloproteinases that degrade cartilage and bone. SPAG16 genotypes were related to matrix metalloproteinase (MMP)-3 and MMP-1 expression by FLS in vitro and MMP-3 production ex vivo. RESULTS: A cluster of single nucleotide polymorphisms (SNPs) at 2q34, located at SPAG16, associated with the radiological progression rate; rs7607479 reached genome-wide significance. A protective role of rs7607479 was replicated in European and North American patients with RA. Per minor allele, patients had a 0.78-fold (95% CI 0.67 to 0.91) progression rate over 7 years. mRNA and protein expression of SPAG16 in RA synovium and FLS was verified. FLS carrying the minor allele secreted less MMP-3 (p=1.60x10(-2)). Furthermore, patients with RA carrying the minor allele had lower serum levels of MMP-3 (p=4.28x10(-2)). In a multivariate analysis on rs7607479 and MMP-3, only MMP-3 associated with progression (p=2.77x10(-4)), suggesting that the association between SPAG16-rs7607479 and joint damage is mediated via an effect on MMP-3 secretion. CONCLUSIONS: Genetic and functional analyses indicate that SPAG16 influences MMP-3 regulation and protects against joint destruction in autoantibody-positive RA. These findings could enhance risk stratification in autoantibody-positive RA

Systems Level Analysis of Systemic Sclerosis Shows a Network of Immune and Profibrotic Pathways Connected with Genetic Polymorphisms

<div><p>Systemic sclerosis (SSc) is a rare systemic autoimmune disease characterized by skin and organ fibrosis. The pathogenesis of SSc and its progression are poorly understood. The SSc intrinsic gene expression subsets (inflammatory, fibroproliferative, normal-like, and limited) are observed in multiple clinical cohorts of patients with SSc. Analysis of longitudinal skin biopsies suggests that a patient's subset assignment is stable over 6–12 months. Genetically, SSc is multi-factorial with many genetic risk loci for SSc generally and for specific clinical manifestations. Here we identify the genes consistently associated with the intrinsic subsets across three independent cohorts, show the relationship between these genes using a gene-gene interaction network, and place the genetic risk loci in the context of the intrinsic subsets. To identify gene expression modules common to three independent datasets from three different clinical centers, we developed a consensus clustering procedure based on mutual information of partitions, an information theory concept, and performed a meta-analysis of these genome-wide gene expression datasets. We created a gene-gene interaction network of the conserved molecular features across the intrinsic subsets and analyzed their connections with SSc-associated genetic polymorphisms. The network is composed of distinct, but interconnected, components related to interferon activation, M2 macrophages, adaptive immunity, extracellular matrix remodeling, and cell proliferation. The network shows extensive connections between the inflammatory- and fibroproliferative-specific genes. The network also shows connections between these subset-specific genes and 30 SSc-associated polymorphic genes including <i>STAT4</i>, <i>BLK</i>, <i>IRF7</i>, <i>NOTCH4</i>, <i>PLAUR</i>, <i>CSK</i>, <i>IRAK1</i>, and several human leukocyte antigen (HLA) genes. Our analyses suggest that the gene expression changes underlying the SSc subsets may be long-lived, but mechanistically interconnected and related to a patients underlying genetic risk.</p></div