Abstract
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 STAT4, BLK, IRF7, NOTCH4, PLAUR, CSK, IRAK1, 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.
Highlights
Genome-scale gene expression profiling of systemic sclerosis (SSc) skin has identified distinct intrinsic molecular subsets within the subset of patients diagnosed with diffuse cutaneous Systemic sclerosis (SSc) based upon the extent of skin involvement
Using previously published gene expression data from skin biopsies from patients with SSc recruited at three independent academic centers [1,4,11] and new samples analyzed as part of this study (Table 1), we identified the consensus clusters that were present in all datasets
Our major findings include the following: 1. We show that the subset-specific consensus clusters are part of a gene-gene network and for the first time to our knowledge, demonstrate putative connections between the intrinsic gene expression subsets of SSc and SSc-associated genetic polymorphisms identified by candidate and genome-wide association studies (GWAS). 2
Summary
Genome-scale gene expression profiling of systemic sclerosis (SSc) skin has identified distinct intrinsic molecular subsets (inflammatory, fibroproliferative, and normal-like) within the subset of patients diagnosed with diffuse cutaneous SSc (dSSc) based upon the extent of skin involvement. These subsets are identified by an intrinsic gene analysis [1] that shifts the focus to differences between patients rather than patient biopsies. The presence of three distinct molecular SSc subsets within patients diagnosed with dSSc underscores the molecular heterogeneity of SSc. The presence of three distinct molecular SSc subsets within patients diagnosed with dSSc underscores the molecular heterogeneity of SSc It is unclear whether the subsets represent distinct diseases with different etiologies or whether they represent disease progression.
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