[HTML][HTML] Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study

LJ Smyth, J Kilner, V Nair, H Liu, E Brennan, K Kerr… - Clinical …, 2021 - Springer
LJ Smyth, J Kilner, V Nair, H Liu, E Brennan, K Kerr, N Sandholm, J Cole, E Dahlström
Clinical epigenetics, 2021Springer
Background A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to
developing diabetic kidney disease (DKD), the most common cause globally of end-stage
kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA
methylation may have a causal role in both T1DM and DKD. The aim of this exploratory
investigation was to assess differences in blood-derived DNA methylation patterns between
individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of …
Background
A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina’s Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10–8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM.
Results
Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation.
Conclusions
Epigenetic alterations provide a dynamic link between an individual’s genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.
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