Background Transcriptional regulation of liver transplant (LT) rejection may reveal novel predictive and therapeutic targets. Purpose To test the role of differential DNA methylation in children with biopsy-proven acute cellular… Click to show full abstract
Background Transcriptional regulation of liver transplant (LT) rejection may reveal novel predictive and therapeutic targets. Purpose To test the role of differential DNA methylation in children with biopsy-proven acute cellular rejection (rejectors, R) after LT. Methods Paired peripheral blood DNA samples were obtained before and after LT from 17 children, including 4R and 13 non-rejector (NR), and assayed with MethylC capture sequencing (MCC-Seq) approach covering 5 million CpGs in immune-cell specific regulatory elements. Differentially methylated CpGs (DMCs) were identified using generalized linear regression models adjusting for sex and age and merged into differentially methylated regions (DMR) comprising 3 or more DMCs. Results Contrasting R vs NR, we identified 2238 DMCs in post-LT and 2620 DMCs in pre-LT samples, which clustered in 216 and 282 DMRs respectively. DMCs associated with R were enriched in enhancers and depleted in promoters. The proportion of hypomethylated versus hypermethylated DMRs increased from 22% to 48% (p<0.0001) in pre-LT vs. post-LT DMCs, respectively. The highest-ranked biological processes enriched in post-LT DMCs were antigen processing and presentation via MHC class I, MHC class I complex, and peptide binding (p<7.92E-17), respectively. Top-ranked DMRs mapped to genes which mediate B-cell receptor signaling (ADAP1) or regulate several immune cells (ARRB2) (p<3.75E-08). DMRs in MHC class I genes were enriched for SNPs which bind TFs, affect gene expression and splicing, or alter peptide-binding amino acid sequences. Conclusions Dynamic methylation in distal regulatory regions reveals known transplant-relevant MHC-dependent rejection pathways, and identifies novel loci for future mechanistic evaluations in pediatric transplant subcohorts.
               
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