Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease

Smyth, L. J.; Kilner, J.; Nair, V.; Liu, H.; Brennan, E.; Kerr, K.; Sandholm, N.; Cole, J.; Dahlstrom, E.; Syreeni, A.; Salem, R. M.; Nelson, R. G.; Looker, H. C.; Wooster, C.; Anderson, K.; McKay, G.; Kee, F.; Young, I.; NICOLA Collaborative Team,; Warren 3 and Genetics of Kidneys in Diabetes (GoKinD) Study Group,; Andrews, D.; Forsblom, C.; Hirschhorn, J. N.; Godson, C.; Groop, P.-H.; Maxwell, A. P.; Susztak, K.; Kretzler, M.; Florez, J. C.; McKnight, A. J.; GENIE consortium,

doi:10.1101/2020.07.30.228734

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bioRxiv · 10.1101/2020.07.30.228734

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease

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Abstract

A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), which is 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 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. 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 Illuminas Infinium MethylationEPIC BeadChip arrays (n=862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p[≤]x10-8 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. Top-ranked genes within which several dmCpGs were located and supported by in silico functional data, and replication where possible, include; AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9, and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-{beta} signalling and Th17 cell differentiation. Epigenetic alterations provide a dynamic link between an individuals 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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Smyth, L. J., Kilner, J., Nair, V., Liu, H., Brennan, E., Kerr, K., Sandholm, N., Cole, J., Dahlstrom, E., Syreeni, A., Salem, R. M., Nelson, R. G., Looker, H. C., Wooster, C., Anderson, K., McKay, G., Kee, F., Young, I., NICOLA Collaborative Team,, Warren 3 and Genetics of Kidneys in Diabetes (GoKinD) Study Group,, Andrews, D., Forsblom, C., Hirschhorn, J. N., Godson, C., Groop, P.-H., Maxwell, A. P., Susztak, K., Kretzler, M., Florez, J. C., McKnight, A. J., GENIE consortium,. 2020-07-31. Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease. https://doi.org/10.1101/2020.07.30.228734

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