Ischemia-Induced DNA Hypermethylation during Kidney Transplant Predicts Chronic Allograft Injury

Abstract

Background Ischemia during kidney transplant causes chronic allograft injury and adversely affects outcome, but the underlying mechanisms are incompletely understood. In tumors, oxygen shortage reduces the DNA demethylating activity of the ten-11 translocation (TET) enzymes, yielding hypermethylated genomes that promote tumor progression. We investigated whether ischemia similarly induces DNA hypermethylation in kidney transplants and contributes to chronic injury.Methods We profiled genome-wide DNA methylation in three cohorts of brain-dead donor kidney allograft biopsy specimens: a longitudinal cohort with paired biopsy specimens obtained at allograft procurement (preischemia; n=13), after implantation and reperfusion (postischemia; n=13), and at 3 or 12 months after transplant (n=5 each); a cross-sectional cohort with preimplantation biopsy specimens (n=82); and a cross-sectional cohort with postreperfusion biopsy specimens (n=46).Results Analysis of the paired preischemia and postischemia specimens revealed that methylation increased drastically in all allografts on ischemia. Hypermethylation was caused by loss of 5-hydroxymethylcytosine, the product of TET activity, and it was stable 1 year after transplant. In the preimplantation cohort, CpG hypermethylation directly correlated with ischemia time and for some CpGs, increased 2.6% per additional hour of ischemia. Hypermethylation preferentially affected and reduced the expression of genes involved in suppressing kidney injury and fibrosis. Moreover, CpG hypermethylation in preimplantation specimens predicted chronic injury, particularly fibrosis and glomerulosclerosis, 1 year after transplant. This finding was validated in the independent postreperfusion cohort, in which hypermethylation also predicted reduced allograft function 1 year after transplant, outperforming established clinical variables.Conclusions We highlight a novel epigenetic basis for ischemia-induced chronic allograft injury with biomarker potential.

Keywords: DNA methylation; chronic allograft nephropathy; epigenetics; fibrosis; ischemia; renal transplantation.

Copyright © 2018 by the American Society of Nephrology.

Figures

Graphical abstract

Figure 1.

Schematic overview of the study cohorts to identify ischemia-induced DNA hypermethylation during kidney transplantation and evaluate its functional implications. 5mC, 5-methylcytosine; Tx, transplant.

Figure 2.

DNA of kidney transplants becomes hypermethylated after ischemia. (A) Median overall DNA methylation levels of kidney transplants before and after ischemia. The increase in methylation is significant for each individual transplant pair (P<0.001; paired Mann–Whitney U test) and also when comparing the fold increase between median preischemic and postischemic biopsies (P<0.001). (B) Logarithmic P values of changes in methylation at individual CpG dinucleotides (CpGs) in paired kidney transplants comparing post- with preischemia conditions. Peaks with a gain (red) or loss (blue) in 5-methylcytosine are highlighted at P<0.05. (C) Distribution of the T statistics of paired tests on CpGs combined per island for all islands, showing the skewing toward hypermethylation of kidney transplants after ischemia. (D) Difference in DNA methylation after ischemia in and around the CpG island chr6:30852102–30852676 located in the promoter of DDR1, showing diffuse hypermethylation of this region.

Figure 3.

DNA hydroxymethylation levels decrease in kidney transplants on ischemia. (A) Overall DNA hydroxymethylation levels of transplants before (blue) and after (red) ischemia. The decrease in hydroxymethylation is significant for all transplants (P<0.001; paired t test). Boxes are interquartile ranges, means are white dots, and medians are darker lines. (B) 5-Hydroxymethylcytosine (5hmC) levels measured by liquid chromatography/mass spectrometry (LC/MS) show a significant loss of 5hmC in kidney transplant biopsies from deceased donation (mean of 17 hours cold ischemia time; n=5) compared with living donation (<1 hour; n=5). (C) Changes in 5-methylcytosine (5mC) levels against changes in 5hmC after ischemia. Colored points depict CpG dinucleotides for which the changes in 5hmC and 5mC are significant at P<0.05, with red used for the inverse relationship between 5mC and 5hmC and blue used for the direct relationship.

Figure 4.

Cold ischemia time correlates with the extent of ischemia-induced methylation changes. (A) Logarithmic P values obtained for individual CpG dinucleotides (CpGs) that were correlated with the duration of cold ischemia time while adjusting for donor age and sex. Peaks with a gain (red) or loss (blue) in 5-methylcytosine (5mC) are highlighted at P<0.05. (B) Distribution of the CpGs hypermethylated on ischemia in both cohorts (red) versus all probes (gray) according to their relationship with CpG islands. (C) Observed/expected fraction of ischemia-hypermethylated CpGs overlapping different kidney chromatin states. (D) Logarithmic P values obtained for CpG islands, which were correlated with the duration of cold ischemia time while adjusting for donor age and sex. Peaks gaining (red) and losing (blue) are highlighted at false discovery rate (FDR)<0.05 and P<0.05 (light colors). (E) CpG islands hypermethylated in the preimplantation cohort were also more likely to be hypermethylated in the longitudinal cohort.

Figure 5.

DNA hypermethylation preferentially affects genes involved in suppression of kidney fibrosis and injury. (A) Pathway enrichment and (B) gene ontology enrichment of the genes associated with the 66 CpG islands that were hypermethylated after ischemia in both the longitudinal and preimplantation cohorts. (C) Log fold change in the expression of hypermethylated genes after versus before ischemia in the longitudinal cohort (n=2×13). Each boxplot represents one transcript: red indicates that expression is reduced after ischemia (median log fold change below one), and blue indicates that expression in increased after ischemia (median log fold change above one). BMP, bone morphogenetic protein. *P<0.05 by Wilcoxon test.

Figure 6.

DNA hypermethylation predicts chronic allograft injury. (A) Average DNA methylation changes of CpG dinucleotides in the 66 CpG islands of kidney transplants postischemia and postreperfusion at 3 months and 1 year after transplantation in the longitudinal cohort compared with their preischemia procurement samples, showing the stability of the hypermethylation. (B) Relative risk of chronic allograft injury at 1 year after transplantation after stratifying patients into tertiles on the basis of the methylation risk score. Odds ratios are shown for the preimplantation cohort and replicated in the postreperfusion cohort. (C and D) Receiver-operating characteristic curves for the methylation risk score (red) to predict chronic injury at 1 year after transplantation compared with baseline clinical variables (donor age, donor last serum creatinine, expanded versus standard criteria donation, cold and warm ischemia times, and number of HLA mismatches; blue). Curves are shown for (C) the preimplantation cohort and replicated in (D) the postreperfusion cohort (P<0.01). (E and F) Chronic Allograft Damage Index (CADI) score for each tertile on the basis of the methylation risk score in the preimplantation and postreperfusion cohort. (G and H) Allograft function by tertile of methylation risk score in the preimplantation and postreperfusion cohort. Although eGFR levels at 12 months were available for 71 patients, CADI scores were available for only 59 patients. AUC, area under the curve.