Molecular "omic" signatures in systemic sclerosis

Abstract

Systemic sclerosis (SSc) is a connective tissue disorder characterized by immunologic, vascular, and extracellular matrix abnormalities. Variation in the proportion and/or timing of activation in the deregulated molecular pathways that underlie SSc may explain the observed clinical heterogeneity in terms of disease phenotype and treatment response. In recent years, SSc research has generated massive amounts of "omics" level data. In this review, we discuss the body of "omics" level work in SSc and how each layer provides unique insight to our understanding of SSc. We posit that effective integration of genomic, transcriptomic, metagenomic, and epigenomic data is an important step toward precision medicine and is vital to the identification of effective therapeutic options for patients with SSc.

Figure 1

Molecular subsets in systemic sclerosis skin. Hierarchical clustering of microarray data (n=2,189 genes) from the skin of patients with systemic sclerosis clearly identifies distinct subsets of patients—yellow=limited, green=normal-like, purple=inflammatory, red=fibroproliferative, and black=unassigned. Adapted with permission from Hinchcliff et al. (15).

Figure 2

Model of the gene-gene network constructed from multiple transcriptomic studies of SSc skin. This illustration identifies key pathways of disease in SSc and how specific polymorphisms link disease pathways. Purple represents processes associated with the inflammatory subset. Red represents processes associated with the fibroproliferative subset. Adapted with permission from Mahoney et al. (27).