Global expression and CpG methylation analysis of primary endothelial cells before and after TNFa stimulation reveals gene modules enriched in inflammatory and infectious diseases and associated DMRs.
PLoS One. 2020;15(3):e0230884
Authors: Rhead B, Shao X, Quach H, Ghai P, Barcellos LF, Bowcock AM
Endothelial cells are a primary site of leukocyte recruitment during inflammation. An increase in tumor necrosis factor-alpha (TNFa) levels as a result of infection or some autoimmune diseases can trigger this process. Several autoimmune diseases are now treated with TNFa inhibitors. However, genomic alterations that occur as a result of TNF-mediated inflammation are not well understood. To investigate molecular targets and networks resulting from increased TNFa, we measured DNA methylation and gene expression in 40 human umbilical vein endothelial cell primary cell lines before and 24 hours after stimulation with TNFa via microarray. Weighted gene co-expression network analysis identified 15 gene groups (modules) with similar expression correlation patterns; four modules showed a strong association with TNFa treatment. Genes in the top TNFa-associated module were all up-regulated, had the highest proportion of hypomethylated regions, and were associated with 136 Disease Ontology terms, including autoimmune/inflammatory, infectious and cardiovascular diseases, and cancers. They included chemokines CXCL1, CXCL10 and CXCL8, and genes associated with autoimmune diseases including HLA-C, DDX58, IL4, NFKBIA and TNFAIP3. Cardiovascular and metabolic disease genes, including APOC1, ACLY, ELOVL6, FASN and SCD, were overrepresented in a module that was not associated with TNFa treatment. Of 223 hypomethylated regions identified, several were in promoters of autoimmune disease GWAS loci (ARID5B, CD69, HDAC9, IL7R, TNIP1 and TRAF1). Results reveal specific gene groups acting in concert in endothelial cells, delineate those driven by TNFa, and establish their relationship to DNA methylation changes, which has strong implications for understanding disease etiology and precision medicine approaches.
PMID: 32231389 [PubMed – indexed for MEDLINE]