An Integrative Transcriptomic Analysis of Systemic Juvenile Idiopathic Arthritis for Identifying Potential Genetic Markers and Drug Candidates

Abstract

Systemic juvenile idiopathic arthritis (sJIA) is a rare subtype of juvenile idiopathic arthritis, whose clinical features are systemic fever and rash accompanied by painful joints and inflammation. Even though sJIA has been reported to be an autoinflammatory disorder, its exact pathogenesis remains unclear. In this study, we integrated a meta-analysis with a weighted gene co-expression network analysis (WGCNA) using 5 microarray datasets and an RNA sequencing dataset to understand the interconnection of susceptibility genes for sJIA. Using the integrative analysis, we identified a robust sJIA signature that consisted of 2 co-expressed gene sets comprising 103 up-regulated genes and 25 down-regulated genes in sJIA patients compared with healthy controls. Among the 128 sJIA signature genes, we identified an up-regulated cluster of 11 genes and a down-regulated cluster of 4 genes, which may play key roles in the pathogenesis of sJIA. We then detected 10 bioactive molecules targeting the significant gene clusters as potential novel drug candidates for sJIA using an in silico drug repositioning analysis. These findings suggest that the gene clusters may be potential genetic markers of sJIA and 10 drug candidates can contribute to the development of new therapeutic options for sJIA.

Keywords: drug repositioning; meta-analysis; systemic juvenile idiopathic arthritis; weighted gene co-expression network analysis (WGCNA).

Figure 1

Identification of a meta-signature for systemic juvenile idiopathic arthritis (sJIA). (A) A volcano plot showing differentially expressed genes (DEGs) derived from a meta-analysis using microarray datasets. Red and blue dots represent 497 up-regulated genes and 102 down-regulated genes, respectively. The grey dashed vertical and horizontal lines indicate the significance thresholds of log₂FC (|log₂FC| > 0.5) and false discovery rate (FDR) (FDR < 0.05), respectively. (B) A volcano plot showing DEGs obtained from the RNA-seq dataset. Red and blue dots represent 1041 up-regulated genes and 253 down-regulated genes, respectively. The grey dashes indicate the same significant thresholds as in (A). (C) A Venn diagram showing the overlap between DEGs identified by the meta-analysis using microarray datasets and the analysis of the RNA-seq dataset. (D) A heatmap showing expression patterns of the meta-signature between 81 sJIA and 176 control samples after adjusting for batch effects from five microarray datasets. Rows and columns indicate each gene in the meta-signature and individual samples, respectively. (E) A heatmap showing the expression profiles of the meta-signature between 26 sJIA and 12 control samples from the RNA-seq dataset.

Figure 2

Significant co-expression modules that were enriched with the meta-signature. (A) A dendrogram for co-expression modules based on the dissimilarity of topological overlap measurements. Among the three rows at the bottom of the plot, color bars in the first row indicate the randomly assigned colors for the co-expression module names. The orders of the randomly assigned colors for the co-expression module names were light yellow, royal blue, brown, red, orange, turquoise, green-yellow, black, blue, magenta, dark orange, midnight blue, hot pink, dark turquoise, purple, green, tan, yellow, cyan, pink, dark red, salmon, and light cyan. In the second row, each gene in the meta-signature was represented by black lines. Red and blue lines in the final row indicate up- and down-regulation, respectively. (B) A heatmap showing the correlations between each module and sJIA. The color blocks shown on the left indicate the randomly selected colors for the module names. Correlation coefficients and the p-value for each module are labeled on the heatmap. The range of correlation coefficients is represented by a color bar on the right. (C) A scatter plot showing the correlation between the gene significance for sJIA and module membership in the red module, using all of the genes from the module. (D) A scatter plot showing the correlation of all of the genes from the dark orange module between gene significance for sJIA and module membership (E) A scatter plot showing the correlation between gene significance for sJIA and module membership in the red module, using the meta-signature enriched in the module. (F) A scatter plot showing the correlation of the meta-signature enriched in the dark orange module between gene significance for sJIA and module membership. The blue lines in (C–F) represent the regression lines of the scatter plots.

Figure 3

Functional enrichment analysis of the sJIA signature. The sJIA signature used as an input to the database for annotation, visualization, and integrated discovery (DAVID) is composed of 103 up- and 25 down-regulated genes. (A) A barplot showing biological pathways significantly associated with the up-regulated genes of the sJIA signature (p < 0.01). (B) A barplot showing biological processes significantly associated with the down-regulated genes of the sJIA signature (p < 0.01).

Figure 4

The significant gene clusters within the PPI network comprising the sJIA signature. (A) A gene cluster with the highest rank score, comprising the up-regulated genes of the sJIA signature. (B) A gene cluster with the highest rank score made up of down-regulated genes of the sJIA signature. The range of the mean log₂FC values of the nodes is represented as a color bar at the bottom. Red and blue color nodes correspond to up- and down-regulated genes. The seed nodes are represented by rhombi.

Figure 5

Drug interactive network between methotrexate and potential drug candidates for sJIA. Drug candidates were connected to methotrexate, the reference node, with up to 2 stopover neighboring nodes on their way. Methotrexate and the drug candidates are represented by red nodes and their neighboring drugs are displayed with grey circles. Only the drug candidates and the stopover neighbors en route to the reference node were labeled on the network.

Figure 6

The summary of an integrative transcriptomic analysis of sJIA. sJIA, systemic juvenile idiopathic arthritis; WGCNA, weighted gene co-expression network analysis; PPI, protein-protein interaction; GO, gene ontology.