Search

BackgroundA 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.ResultsTop-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.ConclusionsEpigenetic 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.

AimTo evaluate the association with diabetic kidney disease of single nucleotide polymorphisms (SNPs) that may contribute to mitochondrial dysfunction.MethodsThe mitochondrial genome and 1039 nuclear genes that are integral to mitochondrial function were investigated using a case (n = 823 individuals with diabetic kidney disease) vs. control (n = 903 individuals with diabetes and no renal disease) approach. All people included in the analysis were of white European origin and were diagnosed with Type 1 diabetes before the age of 31 years. Replication was conducted in 5093 people with similar phenotypes to those of the discovery collection. Association analyses were performed using the plink genetic analysis toolset, with adjustment for relevant covariates.ResultsA total of 25 SNPs were evaluated in the mitochondrial genome, but none were significantly associated with diabetic kidney disease or end-stage renal disease. A total of 38 SNPs in nuclear genes influencing mitochondrial function were nominally associated with diabetic kidney disease and 16 SNPS were associated with end-stage renal disease, secondary to diabetic kidney disease, with meta-analyses confirming the same direction of effect. Three independent signals (seven SNPs) were common to the replication data for both phenotypes with Type 1 diabetes and persistent proteinuria or end-stage renal disease.ConclusionsOur results suggest that SNPs in nuclear genes that influence mitochondrial function are significantly associated with diabetic kidney disease in a white European population.