Genetic variants shape rheumatoid arthritis-specific transcriptomic features in CD4+ T cells through differential DNA methylation, explaining a substantial proportion of heritability.

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CD4+ T cells have been suggested as the most disease-relevant cell type in rheumatoid arthritis (RA) in which RA-risk non-coding variants exhibit allele-specific effects on regulation of RA-driving genes. This study aimed to understand RA-specific signatures in CD4+ T cells using multi-omics data, interpreting inter-omics relationships in shaping the RA transcriptomic landscape.We profiled genome-wide variants, gene expression and DNA methylation in CD4+ T cells from 82 patients with RA and 40 healthy controls using high-throughput technologies. We investigated differentially expressed genes (DEGs) and differential methylated regions (DMRs) in RA and localised quantitative trait loci (QTLs) for expression and methylation. We then integrated these based on individual-level correlations to inspect DEG-regulating sources and investigated the potential regulatory roles of RA-risk variants by a partitioned-heritability enrichment analysis with RA genome-wide association summary statistics.A large number of RA-specific DEGs were identified (n=2575), highlighting T cell differentiation and activation pathways. RA-specific DMRs, preferentially located in T cell regulatory regions, were correlated with the expression levels of 548 DEGs mostly in the same topologically associating domains. In addition, expressional variances in 771 and 83 DEGs were partially explained by expression QTLs for DEGs and methylation QTLs (meQTLs) for DEG-correlated DMRs, respectively. A large number of RA variants were moderately to strongly correlated with meQTLs. DEG-correlated DMRs, enriched with meQTLs, had strongly enriched heritability of RA.Our findings revealed that the methylomic changes, driven by RA heritability-explaining variants, shape the differential expression of a substantial fraction of DEGs in CD4+ T cells in patients with RA, reinforcing the importance of a multidimensional approach in disease-relevant tissues.


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