Epigenomics and Transcriptomics of Systemic Sclerosis CD4+ T cells reveal Long Range Dysregulation of Key Inflammatory Pathways mediated by disease-associated Susceptibility Loci

Abstract

System sclerosis (SSc) is a genetically complex autoimmune disease mediated by the interplay between genetic and epigenetic factors in a multitude of immune cells, with CD4+ T lymphocytes as one of the principle drivers of pathogenesis. In this study, we obtained DNA methylation and expression profiles of CD4+ T cells from 48 SSc patients and 16 healthy controls. Consequently, we identified 9112 and 3929 differentially methylated CpGs positions (DMPs) and differentially expressed genes (DEGs) respectively. These DMPs and DEGs are enriched in functional categories related to inflammation and T cell biology. Furthermore, correlation analysis identified 17,500 possible DMP-DEG interaction pairs within a window of 5 Mb, and utilizing promoter capture Hi-C data, we confirmed that 212 CD4+ T cel specific pairs of DMP-DEG physically interact involving CTCF. Finally, utilizing SSc GWAS data, we identified four important SSc-associated susceptibility loci, TNIP1 (rs3792783), GSDMB (rs9303277), IL12RB1 (rs2305743) and CSK (rs1378942) , that physically interact with DMP-DEG pairs cg17239269-ANXA6, cg19458020-CCR7, cg10808810-JUND and cg11062629-ULK3 respectively. Overall, our study reveals a solid link between genetic, epigenetic and transcriptional deregulation in CD4+ T cells of SSc patients, providing a novel integrated view of SSc pathogenic determinants.

Distinct genome-wide DNA methylation and gene expression signatures in classical monocytes from African American patients with systemic sclerosis

“…This is consistent with the recent finding that several tissue-specific repressed genomic regions enriched for disease-associated GWAS variants, and suggests that DMC may also have tissue-specific effect repressive regions [44]. Previous analyses of DNA methylation in other blood cell types and in larg European-descent groups [22,[51][52][53][54][55][56] report a larger difference in DNA methylation patterns between ca and controls, and an enrichment of genes involved in immune and inflammatory processes. In our study, o OAS3 and CD5 have been previously reported as differentially methylated in CD4+ T cells from Europ patients with SSc [56].…”

“…Different metabolic perturbations are expressed in different patients, reflecting the clinical heterogeneity of SSc [90]. Our enrichment of genes involved in metabolic processes contrasts with the prominent enrichment of genes involved in immune and inflammatory processes consistently reported in both DNA methylation [22, 51-55, 82] and gene expression analyses in blood cell types and in largely European-descent groups, including in classical monocytes [38, 68-81]. The distinct racial category of the participants might appear as the most obvious explanation for this difference.…”

“…Multiple DEGs found in our analysis have been previously reported as differentially expressed in different blood cells from patients with SSc, which provides further support for their potential dysregulation in SSc. These include the endoplasmic reticulum transmembrane channel-like TMC8 [82], the collagen COL9A2 [73], the Kruppel-like transcription factor KLF6 [68, 82], the zinc finger ZNF654 [82], the insulin-Induced INSIG2 [82], the transcription regulator SMARCA4 [82], the kynureninase KYNU [69, 70, 75], the telomere regulator POT1 [82], and the hydrolase ABHD5 [70, 75].…”

“…Previous analyses of DNA methylation in other blood cell types and in largely European-descent groups [22, 51-56] report a larger difference in DNA methylation patterns between cases and controls, and an enrichment of genes involved in immune and inflammatory processes. In our study, only OAS3 and CD5 have been previously reported as differentially methylated in CD4+ T cells from European patients with SSc [56]. OAS3 is an interferon-induced, dsRNA-activated antiviral enzyme which plays a role in cellular innate antiviral response and the immune response to the interferon pathway [57, 58].…”

Low input capture Hi-C (liCHi-C) identifies promoter-enhancer interactions at high-resolution

“…This approach allows systematic identification of the promoter interactome (i.e., genomic regions, including distal regulatory regions, in physical proximity with more than 31,000 promoters) independently of the activity status of the interacting regions. This method has allowed us to uncover new aspects of the diversity of transcriptional regulatory factors 7 and mechanisms in cell differentiation 8,9 and disease 5 , and it has broadened our capacity to identify hundreds of potential new disease-candidate genes and/or gene pathways potentially deregulated by non-coding disease-associated variants 5,10,[11][12][13][14][15][16][17][18][19][20][21] . However, PCHi-C relies on the availability of millions of cells, typically ranging between 30-50 million cells per biological replicate, which prohibits the analysis of rare cell populations such as those commonly obtained in clinical settings.…”