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Abstract: FR-OR49

Epigenome-Wide Microarray Analysis of Pre- and Post-Transplant Methylation Profiles in Kidney Transplant Recipients

Session Information

Category: Transplantation

  • 1901 Transplantation: Basic

Authors

  • Kerr, Katie, Queen's University Belfast, Belfast, Belfast, United Kingdom
  • Smyth, Laura Jane, Queen's University Belfast, Belfast, Belfast, United Kingdom
  • Kilner, Jill, Queen's University Belfast, Belfast, Belfast, United Kingdom
  • Maxwell, Alexander P., Belfast City Hospital Nephrology Service, Belfast, United Kingdom
  • Mcaneney, Helen, Queen's University Belfast, Belfast, Belfast, United Kingdom
  • Mcknight, A.J., Queen's University Belfast, Belfast, Belfast, United Kingdom
Background

Kidney transplantation is the optimal treatment for suitable individuals with end-stage kidney disease (ESKD). Serious post-transplant complications include infections, cardiovascular events, malignancy, and new onset of diabetes after transplant (NODAT). Our regional nephrology centre has the highest living kidney donor transplant rate per million population in Europe, and promotes research to improve patient outcomes. We compared pre and post-transplant methylation profiles in samples derived from matched participants.

Methods

Epigenome-wide analysis was conducted using the Illumina Infinium MethylationEPIC array to interrogate 862,987 sites across the genome and identify any differentially methylated regions (DMR) in samples derived from peripheral blood mononuclear cells of age and sex matched pre (n=25) and post (n=25) kidney transplant recipients. DNA was extracted in a uniform manner and stored carefully undergoing minimal freeze thaw cycles. Samples were run on the same instrument and regression calibration was performed in R to estimate leukocyte cell proportions.

Results

Association analysis using Partek® GenomicsSuite® identified 53 DMR (FDR adjusted p≤0.1 x 10-8, fold change +/-2). Within the top ranked CpG probes we identified DMR within genes dysregulated in melanoma (e.g. EXOC2, VEPH1), genes encoding extracellular matrix proteins that could influence structural glomerular changes (e.g. SPAM1) and genes with prior chronic kidney disease associations (e.g. FNTA). A DMR was also identified within the long intergenic non-protein coding RNA LINC01544, suggesting possible regulatory function. Additionally, Partek® Pathway™ identified enrichment of DMR in the mitogen-activated protein kinase (MAPK) signalling pathway, primarily implicated in malignancy but also ESKD and cardiovascular disease. Gene ontology analysis identified enrichment of terms associated with localization and binding within cells.

Conclusion

This analysis provides a novel epigenomic perspective on molecular changes caused by kidney transplantation, and highlights markers that may be of relevance to post-transplant complications. We provide evidence supporting further methylation and transcriptomic analyses in larger cohorts to help identify epigenetic risk factors associated with post-transplant complications.