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Functional methylome analysis of human diabetic kidney disease.

Citation
Park, J., et al. “Functional Methylome Analysis Of Human Diabetic Kidney Disease.”. Jci Insight.
Center University of Pennsylvania
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Author Jihwan Park, Yuting Guan, Xin Sheng, Caroline Gluck, Matthew J Seasock, Ari Hakimi, Chengxiang Qiu, James Pullman, Amit Verma, Hongzhe Li, Matthew Palmer, Katalin Susztak
Keywords Chronic kidney disease, diabetes, Epigenetics, Genetics
Abstract

In patients with diabetes mellitus, poor metabolic control has a long-lasting impact on kidney disease development. Epigenetic changes, including cytosine methylation, have been proposed as potential mediators of the long-lasting effect of adverse metabolic events. Our understanding of the presence and contribution of methylation changes to disease development is limited because of the lack of comprehensive base-resolution methylome information of human kidney tissue samples and site-specific methylation editing. Base resolution, whole-genome bisulfite sequencing methylome maps of human diabetic kidney disease (DKD) tubule samples, and associated gene expression measured by RNA sequencing highlighted widespread methylation changes in DKD. Pathway analysis highlighted coordinated (methylation and gene expression) changes in immune signaling, including tumor necrosis factor alpha (TNF). Changes in TNF methylation correlated with kidney function decline. dCas9-Tet1-based lowering of the cytosine methylation level of the TNF differentially methylated region resulted in an increase in the TNF transcript level, indicating that methylation of this locus plays an important role in controlling TNF expression. Increasing the TNF level in diabetic mice increased disease severity, such as albuminuria. In summary, our results indicate widespread methylation differences in DKD kidneys and highlights epigenetic changes in the TNF locus and its contribution to the development of nephropathy in patients with diabetes mellitus.

Year of Publication
2019
Journal
JCI insight
Volume
4
Issue
11
Date Published
12/2019
ISSN Number
2379-3708
DOI
10.1172/jci.insight.128886
Alternate Journal
JCI Insight
PMID
31167971
PMCID
PMC6629092
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