Genome-wide DNA methylation analysis for diabetic kidney disease in a UK-ROI population: Oral Presentation

Laura Smyth, Niina Sandholm, Christopher Wooster, Jill Kilner, Carol Forsblom, Per-Henrik Groop, Alexander Maxwell, Amy McKnight, GENIE Consortium

Research output: Contribution to conferenceAbstractpeer-review

13 Downloads (Pure)


IntroductionDiabetic kidney disease (DKD), as characterised by progressive development of proteinuria and loss of renal function, is a common complication of diabetes. DKD is the most common cause of end-stage renal disease, wherein individuals require renal replacement therapy. Increasing evidence suggests that epigenetic alterations, including DNA methylation, are involved in the development and progression of DKD. This investigation compared methylation profiles between individuals from the British Isles with type 1 diabetes (T1D) and DKD to individuals with T1D and no evidence of renal failure, to identify potential methylation-based biomarkers of DKD. MethodsUsing the Zymo EZ DNA methylation kit to bisulphite treat the blood-derived DNA and the Infinium HD Methylation Assay, MethylationEPIC BeadChips (Illumina), the methylation status of >850,000 CpG sites on gene bodies, promoters and CpG islands were determined for 492 individuals with T1D. Of these, 241 individuals had DKD and 251 controls had no evidence of renal disease. Cases and controls were matched carefully for ethnicity, sex, age and duration of diabetes. DNA obtained from each individual was treated consistently, with standard quality control and bioinformatic analyses conducted. ResultsMethylation data was analysed using Partek Genomics Suite v7.0. A total of 486 CpG sites had significantly different levels of methylation in cases compared with controls (p10-8). The top-ranked gene, FKBP5 (p=1.23x10-23) contained several significantly associated CpG sites and has previously been linked with T1D, ageing and CKD. Additional significant genes included BCL2 and PSD3, both have been previously linked to diabetes. High concordance (r2=0.994) between duplicate samples (n=7) was observed. Pathway analysis revealed Notch signalling with the greatest enrichment score (16.96) where p=4.29x10-8.DiscussionWe previously reported results for methylation sites differentially regulated in individuals with T1D with and without renal disease using Illumina’s HumanMethylation450K BeadChip and HumanMethylation27K BeadChip arrays. The FKBP5 gene demonstrated different methylation levels in the 27K, 450K, and now EPIC arrays with a consistent direction of methylation change. This research confirmed earlier loci for DKD, adds new information on previously unexplored regions of the methylome, and identified new associations demonstrating blood-derived methylation signatures may serve as minimally invasive biomarkers of DKD.
Original languageEnglish
Publication statusPublished - 18 Feb 2020
EventThe American Society of Human Genetics - Houston, United States
Duration: 15 Oct 201919 Oct 2019


ConferenceThe American Society of Human Genetics
Abbreviated titleASHG
Country/TerritoryUnited States


Dive into the research topics of 'Genome-wide DNA methylation analysis for diabetic kidney disease in a UK-ROI population: Oral Presentation'. Together they form a unique fingerprint.

Cite this