Molecular Phenotypic Descriptors of Dupuytren’s Disease Defined Using Informatics Analysis of the Transcriptome

Abstract

Dupuytren's disease (DD) is a fibroproliferative disorder of unknown etiopathogenesis, which may cause progressive, permanent contracture of digits. Previous studies provide compelling evidence that genetic alterations play an important role. Macroscopically affected areas demonstrate phenotypic differences between the two structurally distinct fibrotic elements in DD (ie, the nodule and the cord). In this study, we set out to (1) compare gene expression profiles between DD and transverse carpal fascia of control subjects (external control); (2) profile DD cords and nodules from the palm against the unaffected transverse palmar fascia (internal control); and (3) identify biologically important candidate genes from the transcriptome profiles. RNA samples from DD nodules (n = 4), cords (n = 4), and internal control (n = 4) as well as external control (n = 4) from unaffected individuals were subjected to differential gene expression profile analysis. Changes of more than 2-fold in DD groups and controls were recorded. Quantitative reverse transcriptase-polymerase chain reactions were performed to validate 16 implicated genes, which included developmental control genes, matrix metalloproteinases, and apoptotic genes. Several genes associated with DD formation were common across all 6 pairwise analyses. Genes markedly upregulated shared common expression levels across all pairwise analysis studies. Pairs involving the DD nodule arrays were notably distinguishable from all other permutations. The majority of genes dysregulated in the DD cords demonstrated an increase in fold change when compared with the DD nodule tissues. Key collagens, collagenases, metalloproteinases, and inhibitors were identified. Genes involved in cytoskeleton development and lipid metabolism were markedly dysregulated. Confirmations of these alterations were obtained in quantitative reverse transcriptase-polymerase chain reaction. These data demonstrate a gradation in expression of certain genes in DD tissue phenotypes compared with control fascia. Transcriptome profiling is predictive not only of disease but also of disease phenotype. These results indicate a number of important candidate genes associated with DD formation, which may provide clues for molecular mechanisms involved in DD pathogenesis.