CD4+ T cells from children with active juvenile idiopathic arthritis show altered chromatin features associated with transcriptional abnormalities

Abstract

Juvenile idiopathic arthritis (JIA) is one of the most common chronic diseases in children. While clinical outcomes for patients with juvenile JIA have improved, the underlying biology of the disease and mechanisms underlying therapeutic response/non-response are poorly understood. We have shown that active JIA is associated with distinct transcriptional abnormalities, and that the attainment of remission is associated with reorganization of transcriptional networks. In this study, we used a multi-omics approach to identify mechanisms driving the transcriptional abnormalities in peripheral blood CD4+ T cells of children with active JIA. We demonstrate that active JIA is associated with alterations in CD4+ T cell chromatin, as assessed by ATACseq studies. However, 3D chromatin architecture, assessed by HiChIP and simultaneous mapping of CTCF anchors of chromatin loops, reveals that normal 3D chromatin architecture is largely preserved. Overlapping CTCF binding, ATACseq, and RNAseq data with known JIA genetic risk loci demonstrated the presence of genetic influences on the observed transcriptional abnormalities and identified candidate target genes. These studies demonstrate the utility of multi-omics approaches for unraveling important questions regarding the pathobiology of autoimmune diseases.

Figure 1

Attainment of clinical remission in JIA normalizes gene expression in CD4+ T-cells. (A) Volcano plots for each of the pairwise comparisons of gene expression between groups. (B) Heatmap showing the expression of all genes that were considered differentially expressed between any two groups. Kmeans clustering was applied to separate genes into one of 5 clusters and hierarchal clustering was applied to cluster the groups.

Figure 2

Chromatin re-arrangement occurs in the absence of three-dimensional changes. (A) Overlap between the group-consistent accessible peaks identified in HC, ADT and CRM samples. (B) Volcano plot showing the differences in CTCF binding affinity between 5 HC samples and 5 ADT samples. Blue dots represent sites whose log10(fold-change) was at least 1 and whose FDR was less than or equal to 0.05.

Figure 3

Identifying regulatory hubs. Snapshot showing the regulatory hub anchored on JIA risk variants rs6946509, rs7808122, rs10280937 and rs73300638. Top row shows LD blocks of the risk variants, followed by averaged ATAC-seq, RNA-seq, CTCF ChIP-seq signal across the three sample groups, as well as the HiChIP loops for the healthy control and active disease groups, followed by differentially expressed genes and all RefSeq genes.