Integrative genomic and transcriptomic analysis of genetic markers in Dupuytren's disease

Abstract

Background: Dupuytren's disease (DD) is a fibroproliferative disorder characterized by thickening and contracting palmar fascia. The exact pathogenesis of DD remains unknown.

Results: In this study, we identified co-expressed gene set (DD signature) consisting of 753 genes via weighted gene co-expression network analysis. To confirm the robustness of DD signature, module enrichment analysis and meta-analysis were performed. Moreover, this signature effectively classified DD disease samples. The DD signature were significantly enriched in unfolded protein response (UPR) related to endoplasmic reticulum (ER) stress. Next, we conducted multiple-phenotype regression analysis to identify trans-regulatory hotspots regulating expression levels of DD signature using Genotype-Tissue Expression data. Finally, 10 trans-regulatory hotspots and 16 eGenes genes that are significantly associated with at least one cis-eQTL were identified.

Conclusions: Among these eGenes, major histocompatibility complex class II genes and ZFP57 zinc finger protein were closely related to ER stress and UPR, suggesting that these genetic markers might be potential therapeutic targets for DD.

Keywords: Dupuytren’s disease; Endoplasmic reticulum (ER) stress; Major histocompatibility complex class II; Multiple-phenotype analysis; Unfolded protein response (UPR); ZFP57 zinc finger protein; trans-regulatory hotspots.

Fig. 1

Identification of modules associated with gene expression of DD. a Dendrogram showing modules based on the dissimilarity of TOM (1-TOM). Color bars below show assignment of modules. b Heatmap showing the gene expression pattern of modules. Red and blue color lines indicate up- and down-regulation, respectively. c A Heatmap showing the results of the meta-analysis derived from one-color microarray dataset. Black indicates DEGs (FDR < 0.01). d A Heatmap showing results of DEGs analysis of two-color microarray dataset. Black color lines indicate DEGs (FDR < 0.01). e A Heatmap showing expression patterns of genes for red module. Black color lines indicate DEGs (FDR < 0.01). f A scatter plot of principal component analysis (PCA) showing a distinct separation of the expression level of red module genes between patients with DD and normal subjects

Fig. 2

Robustness of DD signature and its functional annotations. a Bar plots showing the results of module enrichment analysis using GSEA. Black dotted lines indicate significant threshold (FDR < 0.05). b Bar plots showing normalized enrichment score (NES) for results of module concentration analysis using GSEA. c ROC analysis with AUC showing the performance of classification using red module in (a). Randomly selected genes consist of the same number of the red module gene. d Bar plots showing the results of functional enrichment analysis. Red and orange color bars represent GO biological process and KEGG pathway, respectively. Black dotted lines indicate significant threshold (FDR < 0.05)

Fig. 3

Identification of trans-regulatory hotspots associated with DD signature. a The GAMMA results applied to GTEx dataset using DD signature. b Box plots of gene expression levels of eGenes by each trans-regulatory hotspot between the different genotype groups

Fig. 4

A Heatmap showing gene expression levels of eGene using microarray data derived from ER stress-inducing agent (tunicamycin) treated MEFs. Color bars give information on tunicamycin treatment condition, DEGs, and direction of effect of SNP. Mouse gene symbol (human gene symbol) was represented by row names of the heatmap