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Molecular subsets in the gene expression signatures of scleroderma skin.

Milano A, Pendergrass SA, Sargent JL, George LK, McCalmont TH, Connolly MK, Whitfield ML - PLoS ONE (2008)

Bottom Line: The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings.Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Dartmouth Medical School, Hanover, New Hampshire, United States of America.

ABSTRACT

Background: Scleroderma 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.

Methodology and findings: We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc) with diffuse scleroderma (dSSc), 7 patients with SSc with limited scleroderma (lSSc), 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. 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. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001) and each has been mapped to clinical covariates of 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 demonstrates multiple distinct gene expression programs in the skin of patients with scleroderma.

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Genes correlated with MRSS.We selected the genes from the 995 intrinsic list that had a correlation greater than 0.5 or less than −0.5 to the MRSS. This list of 177 genes was then used to organize the skin biopsies. Forearm-back pairs from 14 patients with dSSc (mean MRSS of 26.34±9.42) clustered onto one branch of the dendrogram tree. The forearm-back pairs of 4 patients with dSSc (Mean MRSS 18.11±6.45) clustered onto a different branch of the dendrogram tree. The difference in skin score between these two groups is statistically significant (p<0.0197).
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pone-0002696-g006: Genes correlated with MRSS.We selected the genes from the 995 intrinsic list that had a correlation greater than 0.5 or less than −0.5 to the MRSS. This list of 177 genes was then used to organize the skin biopsies. Forearm-back pairs from 14 patients with dSSc (mean MRSS of 26.34±9.42) clustered onto one branch of the dendrogram tree. The forearm-back pairs of 4 patients with dSSc (Mean MRSS 18.11±6.45) clustered onto a different branch of the dendrogram tree. The difference in skin score between these two groups is statistically significant (p<0.0197).

Mentions: To identify genes associated with MRSS we selected the subset of genes most highly correlated with each covariate from the intrinsic list using Pearson correlations. 177 genes were selected from the 995 intrinsic genes that had Pearson correlations with MRSS >0.5 or <−0.5. We then used this list of 177 genes to organize the skin biopsies by average linkage hierarchical clustering (Figure 6; Supplementary Data File S4). We find that both forearm and back skin biopsies from 14 patients with dSSc (mean MRSS of 26.34±9.42) clustered onto a single branch of the dendrogram. All other samples, including the forearm-back pairs of 4 patients with dSSc (mean MRSS 18.11±6.45) clustered onto a separate branch of the dendrogram. Using a two-tailed Student's t-test we find that the difference in skin score between the two groups of dSSc is statistically significant (p = 0.0197).


Molecular subsets in the gene expression signatures of scleroderma skin.

Milano A, Pendergrass SA, Sargent JL, George LK, McCalmont TH, Connolly MK, Whitfield ML - PLoS ONE (2008)

Genes correlated with MRSS.We selected the genes from the 995 intrinsic list that had a correlation greater than 0.5 or less than −0.5 to the MRSS. This list of 177 genes was then used to organize the skin biopsies. Forearm-back pairs from 14 patients with dSSc (mean MRSS of 26.34±9.42) clustered onto one branch of the dendrogram tree. The forearm-back pairs of 4 patients with dSSc (Mean MRSS 18.11±6.45) clustered onto a different branch of the dendrogram tree. The difference in skin score between these two groups is statistically significant (p<0.0197).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2481301&req=5

pone-0002696-g006: Genes correlated with MRSS.We selected the genes from the 995 intrinsic list that had a correlation greater than 0.5 or less than −0.5 to the MRSS. This list of 177 genes was then used to organize the skin biopsies. Forearm-back pairs from 14 patients with dSSc (mean MRSS of 26.34±9.42) clustered onto one branch of the dendrogram tree. The forearm-back pairs of 4 patients with dSSc (Mean MRSS 18.11±6.45) clustered onto a different branch of the dendrogram tree. The difference in skin score between these two groups is statistically significant (p<0.0197).
Mentions: To identify genes associated with MRSS we selected the subset of genes most highly correlated with each covariate from the intrinsic list using Pearson correlations. 177 genes were selected from the 995 intrinsic genes that had Pearson correlations with MRSS >0.5 or <−0.5. We then used this list of 177 genes to organize the skin biopsies by average linkage hierarchical clustering (Figure 6; Supplementary Data File S4). We find that both forearm and back skin biopsies from 14 patients with dSSc (mean MRSS of 26.34±9.42) clustered onto a single branch of the dendrogram. All other samples, including the forearm-back pairs of 4 patients with dSSc (mean MRSS 18.11±6.45) clustered onto a separate branch of the dendrogram. Using a two-tailed Student's t-test we find that the difference in skin score between the two groups of dSSc is statistically significant (p = 0.0197).

Bottom Line: The disease is characterized by vascular dysfunction, tissue fibrosis, internal organ dysfunction, and immune dysfunction resulting in autoantibody production.Using this property of the gene expression, we selected a set of 'intrinsic' genes and analyzed the inherent data-driven groupings.Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program.

View Article: PubMed Central - PubMed

Affiliation: Department of Genetics, Dartmouth Medical School, Hanover, New Hampshire, United States of America.

ABSTRACT

Background: Scleroderma 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.

Methodology and findings: We analyzed the genome-wide patterns of gene expression with DNA microarrays in skin biopsies from distinct scleroderma subsets including 17 patients with systemic sclerosis (SSc) with diffuse scleroderma (dSSc), 7 patients with SSc with limited scleroderma (lSSc), 3 patients with morphea, and 6 healthy controls. 61 skin biopsies were analyzed in a total of 75 microarray hybridizations. Analysis by hierarchical clustering demonstrates nearly identical patterns of gene expression in 17 out of 22 of the forearm and back skin pairs of SSc patients. 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. Our data show three distinct patient groups among the patients with dSSc and two groups among patients with lSSc. Each group can be distinguished by unique gene expression signatures indicative of proliferating cells, immune infiltrates and a fibrotic program. The intrinsic groups are statistically significant (p<0.001) and each has been mapped to clinical covariates of 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 demonstrates multiple distinct gene expression programs in the skin of patients with scleroderma.

Show MeSH
Related in: MedlinePlus