Functional genomics in primary T cells and monocytes identifies mechanisms by which genetic susceptibility loci influence systemic sclerosis risk

Abstract

ObjectivesSystemic sclerosis (SSc) is a complex autoimmune disease with a strong genetic component. However, most of the causal genes and variants are still unknown. The challenge in the post-GWAS era is to use functional genomics to translate genetic findings into patients’ benefit, particularly in disease-relevant cell types.MethodsPromoter capture Hi-C (pCHi-C) and RNA sequencing experiments were performed in a total of 30 samples corresponding to CD4+ T cells and CD14+ monocytes (15 samples each) from SSc patients and healthy controls to link SSc-associated variants with their target genes, followed by differential expression and differential interaction analyses between both cell types. We also aimed to identify potential drugs that could be repurposed for its use in SSc.ResultsWe linked SSc-associated loci to 39 new potential target genes, confirming 7 previously assigned genes. We highlight novel causal genes, such as CXCR5 as the most probable candidate gene for the DDX6 locus. Some SSc confirmed genes such as IRF8, STAT4, or CD247 interestingly showed cell type specific interactions. We also identified 15 potential drug targets already in use in other similar immune-mediated diseases that could be repurposed for SSc treatment. Furthermore, we observed that interactions are directly related with the expression of important genes implicated in cell type specific pathways.ConclusionsOur study reveals potential causal genes for SSc-associated loci, some of them acting in a cell type specific manner, suggesting novel biological mechanisms that may mediate SSc pathogenesis.

Recent advances in elucidating the genetic basis of systemic sclerosis

“…Nonetheless, there is still a lack of integration of multiple layers of genomic, epigenomic and transcriptomic information into a systems biology setting to characterize each SSc patient and address their care and treatment in a personalized way. Novel technologies, such as nuclear DNA conformation analysis [55], characterization of alternative RNA splicing, noncoding RNAs or single cell RNAsequencing [56][57][58][59][60][61] are being successfully implemented in SSc. The combination of all these sources of information with the SSc genetic risk factors will certainly contribute to breaking down the events and cellular settings that lead the SSc.…”

Unraveling a novel dual-function regulatory element showing epistatic interaction with a variant that escapes genome-wide association studies

“…Promoter capture Hi-C data from CD4+ T cells 27 , revealed a significant T-cell specific interaction between ATP2B4 Epromoter and both LAX1 and ATP2B4 promoters (Figure 1B, Figure S1). However, no significant interaction was detected between the ATP2B4 Epromoter and the ZC3H11A and OPTC genes in CD4+ T cells 27 .…”

“…The data of physical chromatin interactions were obtained from Genehancer data prediction 59 and from GEO: GSM6509371 27 . The circos plot was built using ClicO FS 60 .…”

3D genome organization links non-coding disease-associated variants to genes

“…High resolution chromatin capture techniques, such as PCHi-C, can determine the physical links between the GWAS implicated enhancers and the genes they regulate (Martin et al, 2015;Javierre et al, 2016;González-Serna et al, 2022).…”

“…High resolution chromatin capture techniques, such as PCHi-C, can determine the physical links between the GWAS implicated enhancers and the genes they regulate ( Martin et al, 2015 ; Javierre et al, 2016 ; González-Serna et al, 2022 ). Overlaying the ATAC-seq, ChIP-seq, RNA-seq, and QTL data with chromatin interaction data can provide more confidence as to the gene/enhancer relationship, in the identified cellular context.…”