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Functional methylome analysis of human diabetic kidney disease
Jihwan Park, … , Matthew Palmer, Katalin Susztak
Jihwan Park, … , Matthew Palmer, Katalin Susztak
Published June 6, 2019
Citation Information: JCI Insight. 2019;4(11):e128886. https://doi.org/10.1172/jci.insight.128886.
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Research Article Genetics

Functional methylome analysis of human diabetic kidney disease

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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.

Authors

Jihwan Park, Yuting Guan, Xin Sheng, Caroline Gluck, Matthew J. Seasock, A. Ari Hakimi, Chengxiang Qiu, James Pullman, Amit Verma, Hongzhe Li, Matthew Palmer, Katalin Susztak

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Figure 1

Whole-genome cytosine methylation analysis of control and DKD kidney tubule samples at base resolution.

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Whole-genome cytosine methylation analysis of control and DKD kidney tub...
(A) Volcano plot for the DMRs between control and DKD samples. The x axis represents methylation level difference. The y axis represents statistical significance of the DMRs shown by areaStat value from bsseq program. (B) The correlation between Infinium array and WGBS data. (C) Methylation patterns of the Infinium probes in the DMR regions identified by WGBS. The x axis represents correlation level (effective values calculated by linear regression) with interstitial fibrosis (upper panel) and GFR (lower panel). The y axis represents the significance of the correlation. The significant probes are colored in red (FDR < 0.05). (D) Genomic distribution of the DMRs in kidney-specific functional elements. Functional elements were defined by ChromHMM-based histone ChIP data. (E) Enrichment patterns of 6 different histone modifications in hyper- and hypo-DMRs. Normalized ChIP-seq read density was calculated for every 25-bp window in ±3 kb flanking DMR center.

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