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Integrative Omics analyses reveal epigenetic memory in diabetic renal cells regulating genes associated with kidney dysfunction.

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posted on 03.08.2020 by Ada Admin, Anita Bansal, Sreeram Balasubramanian, Sangeeta Dhawan, Amy Leung, Zhen Chen, Rama Natarajan
Diabetic kidney disease (DKD) is a major complication of diabetes and the leading cause of end-stage renal failure. Epigenetics has been associated with metabolic memory, in which prior periods of hyperglycemia enhance the future risk of developing DKD despite subsequent glycemic control. To understand the mechanistic role of such epigenetic memory in human DKD and identify new therapeutic targets, we profiled gene expression, DNA methylation, and chromatin accessibility in kidney proximal tubule epithelial cells (PTECs) derived from non-diabetic and Type-2 diabetic (T2D) subjects. T2D-PTECs displayed persistent gene expression and epigenetic changes with and without TGFβ1 treatment, even after culturing in vitro under similar conditions as non-diabetic PTECs, signified by deregulation of fibrotic and transport associated genes (TAGs). Motif-analysis of differential DNA methylation and chromatin accessibility regions associated with genes differentially regulated in T2D revealed enrichment for SMAD3, HNF4A, and CTCF transcription factor binding sites. Furthermore, the downregulation of several TAGs in T2D (including CLDN10, CLDN14, CLDN16, SLC16A2, SLC16A5) was associated with promoter hypermethylation, decreased chromatin accessibility and reduced enrichment of HNF4A, histone H3-lysine-27-acetylation, and CTCF. Together, these integrative analyses reveal epigenetic memory underlying the deregulation of key target genes in T2D-PTECs that may contribute to sustained renal dysfunction in DKD.


This work was supported by grants from the National Institutes of Health (NIH), R01 DK081705, R01 DK058191 and R01 HL106089 (to R.N.), and R00HL122368, R01HL145170, and Ella Fitzgerald Foundation (to Z.C.). The research reported here included work performed in the Integrative Genomics Core supported by the National Cancer Institute of the NIH under grant number P30CA033572.



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