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Molecular subsets in the gene expression signatures of scleroderma skin

A. Milano et al.


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Molecular subsets in the gene expression signatures of scleroderma skin

Ausra Milano1, Sarah A. Pendergrass1, Jennifer L. Sargent1, Lacy K. George1, Timothy H. McCalmont5, M. Kari Connolly3,4, and Michael L. Whitfield1,2,§

1 Department of Genetics, Dartmouth Medical School
2 Norris Cotton Cancer Center, Dartmouth Medical School
3 Department of Dermatology, UCSF
4 Department of Medicine (Rheumatology), UCSF
5 Department of Pathology, UCSF

§ Corresponding author

Abstract

Background
Scleroderma (Systemic sclerosis; SSc) is a clinically heterogeneous disease with a complex phenotype. The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production. The cause and effect relationships among these different pathological processes are poorly understood.
Methodology and Findings
We have analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from 34 subjects: 17 patients with SSc with diffuse scleroderma (dSSc), 7 patients with SSc with limited scleroderma (lSSc), 3 patients with morphea and 6 healthy controls. In total, 61 skin biopsies were analyzed. The addition of 14 technical replicates resulted in a total of 75 microarray hybridizations. Unsupervised hierarchical clustering recapitulates prior findings [1] by demonstrating nearly identical patterns of gene expression in the clinically affected forearm and unaffected back skin of SSc patients. In total, 17 out of 22 forearm-back pairs cluster together illustrating the systemic nature of the disease. Using this property of the gene expression, we selected a set of ‘intrinsic’ genes and analyzed the inherent data-driven groupings. Distinct patterns of gene expression separate patients with dSSc from those with lSSc and both are easily distinguished from normal controls. Most importantly, our data show evidence of at least two distinct patient subgroups among the patients with dSSc that can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and the fibrotic program. Each intrinsic subgroup has been mapped to clinical covariates such as Modified Rodnan Skin Score, interstitial lung disease, gastrointestinal involvement, digital ulcers, Raynaud’s phenomenon and disease duration. We report a 177-gene signature that is associated with severity of skin disease in dSSc.
Conclusions and significance
Genome-wide gene expression profiling of skin biopsies demonstrates that the heterogeneity in scleroderma can be measured quantitatively with DNA microarrays. The diversity in gene expression demonstrate multiple distinct gene expression programs in the skin of patients with scleroderma.




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