Unraveling the epigenetic code: human kidney DNA methylation and chromatin dynamics in renal disease development

Yu Yan, Hongbo Liu, Amin Abedini, Xin Sheng, Matthew Palmer, Hongzhe Li and Katalin Susztak ()
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Yu Yan: University of Pennsylvania, Perelman School of Medicine
Hongbo Liu: University of Pennsylvania, Perelman School of Medicine
Amin Abedini: University of Pennsylvania, Perelman School of Medicine
Xin Sheng: University of Pennsylvania, Perelman School of Medicine
Matthew Palmer: University of Pennsylvania, Perelman School of Medicine
Hongzhe Li: University of Pennsylvania, Perelman School of Medicine
Katalin Susztak: University of Pennsylvania, Perelman School of Medicine

Nature Communications, 2024, vol. 15, issue 1, 1-17

Abstract: Abstract Epigenetic changes may fill a critical gap in our understanding of kidney disease development, as they not only reflect metabolic changes but are also preserved and transmitted during cell division. We conducted a genome-wide cytosine methylation analysis of 399 human kidney samples, along with single-nuclear open chromatin analysis on over 60,000 cells from 14 subjects, including controls, and diabetes and hypertension attributed chronic kidney disease (CKD) patients. We identified and validated differentially methylated positions associated with disease states, and discovered that nearly 30% of these alterations were influenced by underlying genetic variations, including variants known to be associated with kidney disease in genome-wide association studies. We also identified regions showing both methylation and open chromatin changes. These changes in methylation and open chromatin significantly associated gene expression changes, most notably those playing role in metabolism and expressed in proximal tubules. Our study further demonstrated that methylation risk scores (MRS) can improve disease state annotation and prediction of kidney disease development. Collectively, our results suggest a causal relationship between epigenetic changes and kidney disease pathogenesis, thereby providing potential pathways for the development of novel risk stratification methods.

Date: 2024
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DOI: 10.1038/s41467-024-45295-y

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