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Chen Z, Satake E, Pezzolesi MG, Md Dom ZI, Stucki D, Kobayashi H, Syreeni A, Johnson AT, Wu X, Dahlström EH, King JB, Groop PH, Rich SS, Sandholm N, Krolewski AS, Natarajan R. Integrated analysis of blood DNA methylation, genetic variants, circulating proteins, microRNAs, and kidney failure in type 1 diabetes. Sci Transl Med 2024; 16:eadj3385. [PMID: 38776390 DOI: 10.1126/scitranslmed.adj3385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 04/30/2024] [Indexed: 05/25/2024]
Abstract
Variation in DNA methylation (DNAmet) in white blood cells and other cells/tissues has been implicated in the etiology of progressive diabetic kidney disease (DKD). However, the specific mechanisms linking DNAmet variation in blood cells with risk of kidney failure (KF) and utility of measuring blood cell DNAmet in personalized medicine are not clear. We measured blood cell DNAmet in 277 individuals with type 1 diabetes and DKD using Illumina EPIC arrays; 51% of the cohort developed KF during 7 to 20 years of follow-up. Our epigenome-wide analysis identified DNAmet at 17 CpGs (5'-cytosine-phosphate-guanine-3' loci) associated with risk of KF independent of major clinical risk factors. DNAmet at these KF-associated CpGs remained stable over a median period of 4.7 years. Furthermore, DNAmet variations at seven KF-associated CpGs were strongly associated with multiple genetic variants at seven genomic regions, suggesting a strong genetic influence on DNAmet. The effects of DNAmet variations at the KF-associated CpGs on risk of KF were partially mediated by multiple KF-associated circulating proteins and KF-associated circulating miRNAs. A prediction model for risk of KF was developed by adding blood cell DNAmet at eight selected KF-associated CpGs to the clinical model. This updated model significantly improved prediction performance (c-statistic = 0.93) versus the clinical model (c-statistic = 0.85) at P = 6.62 × 10-14. In conclusion, our multiomics study provides insights into mechanisms through which variation of DNAmet may affect KF development and shows that blood cell DNAmet at certain CpGs can improve risk prediction for KF in T1D.
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Affiliation(s)
- Zhuo Chen
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes and Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Eiichiro Satake
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Marcus G Pezzolesi
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Zaipul I Md Dom
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Devorah Stucki
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Hiroki Kobayashi
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
- Division of Nephrology, Hypertension, and Endocrinology, Nihon University School of Medicine, Tokyo, Japan
| | - Anna Syreeni
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
| | - Adam T Johnson
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Xiwei Wu
- Department of Computational and Quantitative Medicine, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
- Integrative Genomics Core, Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
| | - Emma H Dahlström
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
| | - Jaxon B King
- Department of Internal Medicine, Division of Nephrology and Hypertension, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Per-Henrik Groop
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
- Department of Diabetes, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia
| | - Stephen S Rich
- Center for Public Health Genomics and Department of Public Health Sciences, University of Virginia, Charlottesville, VA 22908, USA
| | - Niina Sandholm
- Folkhälsan Research Center, Helsinki, 00290, Finland
- Department of Nephrology, University of Helsinki and Helsinki University Hospital, Helsinki, 00290, Finland
- Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, 00290, Finland
| | - Andrzej S Krolewski
- Section on Genetics and Epidemiology, Research Division, Joslin Diabetes Center, Boston, MA 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA 02215, USA
| | - Rama Natarajan
- Department of Diabetes Complications and Metabolism, Arthur Riggs Diabetes and Metabolism Research Institute and Beckman Research Institute of City of Hope, Duarte, CA 91010, USA
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Yao Y, Wang X, Li H, Fan J, Qian X, Li H, Xu Y. Phospholipase D as a key modulator of cancer progression. Biol Rev Camb Philos Soc 2020; 95:911-935. [PMID: 32073216 DOI: 10.1111/brv.12592] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Revised: 02/01/2020] [Accepted: 02/06/2020] [Indexed: 12/15/2022]
Abstract
The phospholipase D (PLD) family has a ubiquitous expression in cells. PLD isoforms (PLDs) and their hydrolysate phosphatidic acid (PA) have been demonstrated to engage in multiple stages of cancer progression. Aberrant expression of PLDs, especially PLD1 and PLD2, has been detected in various cancers. Inhibition or elimination of PLDs activity has been shown to reduce tumour growth and metastasis. PLDs and PA also serve as downstream effectors of various cell-surface receptors, to trigger and regulate propagation of intracellular signals in the process of tumourigenesis and metastasis. Here, we discuss recent advances in understanding the functions of PLDs and PA in discrete stages of cancer progression, including cancer cell growth, invasion and migration, and angiogenesis, with special emphasis on the tumour-associated signalling pathways mediated by PLDs and PA and the functional importance of PLDs and PA in cancer therapy.
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Affiliation(s)
- Yuanfa Yao
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China.,Department of Endocrinology, The Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Xinyi Wang
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China.,Department of Clinical Medicine, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Hanbing Li
- Institute of Pharmacology, College of Pharmaceutical Science, Zhejiang University of Technology, Hangzhou, China
| | - Jiannan Fan
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China
| | - Xiaohan Qian
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China.,Department of Respiratory Disease, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Li
- Department of Endocrinology, The Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yingke Xu
- Department of Biomedical Engineering, Key Laboratory of Biomedical Engineering of Ministry of Education, Zhejiang Provincial Key Laboratory of Cardio-Cerebral Vascular Detection Technology and Medicinal Effectiveness Appraisal, Zhejiang University, Hangzhou, China.,Department of Endocrinology, The Affiliated Sir Run Run Shaw Hospital, Zhejiang University School of Medicine, Hangzhou, China
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