Unraveling the epigenetic code: human kidney DNA methylation and chromatin dynamics in renal disease development
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 sing...
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| Vydáno v: | Nature communications Ročník 15; číslo 1; s. 873 - 17 |
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29.01.2024
Nature Publishing Group Nature Portfolio |
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| ISSN: | 2041-1723, 2041-1723 |
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| 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.
Kidney disease affects more than 850 million people worldwide, but the development of drug therapeutics has been limited by poor mechanistic understanding. Here, the authors perform epigenome-wide analyses to find methylation changes, and disease mechanisms associated with kidney disease. |
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| AbstractList | 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. 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. Kidney disease affects more than 850 million people worldwide, but the development of drug therapeutics has been limited by poor mechanistic understanding. Here, the authors perform epigenome-wide analyses to find methylation changes, and disease mechanisms associated with kidney disease. 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.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. 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. 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. Kidney disease affects more than 850 million people worldwide, but the development of drug therapeutics has been limited by poor mechanistic understanding. Here, the authors perform epigenome-wide analyses to find methylation changes, and disease mechanisms associated with kidney disease. |
| ArticleNumber | 873 |
| Author | Abedini, Amin Sheng, Xin Li, Hongzhe Yan, Yu Susztak, Katalin Palmer, Matthew Liu, Hongbo |
| Author_xml | – sequence: 1 givenname: Yu surname: Yan fullname: Yan, Yu organization: Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine – sequence: 2 givenname: Hongbo orcidid: 0000-0002-0733-8616 surname: Liu fullname: Liu, Hongbo organization: Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine – sequence: 3 givenname: Amin orcidid: 0000-0002-8875-0070 surname: Abedini fullname: Abedini, Amin organization: Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine – sequence: 4 givenname: Xin orcidid: 0000-0002-3620-3577 surname: Sheng fullname: Sheng, Xin organization: Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine – sequence: 5 givenname: Matthew surname: Palmer fullname: Palmer, Matthew organization: Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine, Department of Epidemiology and Biostatistics, Perelman School of Medicine – sequence: 6 givenname: Hongzhe surname: Li fullname: Li, Hongzhe organization: Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine, Department of Pathology, Perelman School of Medicine – sequence: 7 givenname: Katalin orcidid: 0000-0002-1005-3726 surname: Susztak fullname: Susztak, Katalin email: ksusztak@pennmedicine.upenn.edu organization: Renal, Electrolyte, and Hypertension Division, Department of Medicine, University of Pennsylvania, Perelman School of Medicine, Institute for Diabetes, Obesity, and Metabolism, University of Pennsylvania, Perelman School of Medicine, Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Kidney Innovation Center, University of Pennsylvania, Perelman School of Medicine |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/38287030$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | 38 49/39 692/308 692/4022/1585 Annotations Cell division Chromatin Cytosine Diabetes mellitus DNA methylation Drug development Epigenetics Gene expression Genetic diversity Genome-wide association studies Genomes Humanities and Social Sciences Hypertension Kidney diseases Kidneys multidisciplinary Pathogenesis Proximal tubules Science Science (multidisciplinary) |
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