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Saedi S, Tan Y, Watson SE, Wintergerst KA, Cai L. Potential pathogenic roles of ferroptosis and cuproptosis in cadmium-induced or exacerbated cardiovascular complications in individuals with diabetes. Front Endocrinol (Lausanne) 2024; 15:1461171. [PMID: 39415790 PMCID: PMC11479913 DOI: 10.3389/fendo.2024.1461171] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2024] [Accepted: 09/16/2024] [Indexed: 10/19/2024] Open
Abstract
Diabetes and its complications are major diseases that affect human health. Diabetic cardiovascular complications such as cardiovascular diseases (CVDs) are the major complications of diabetes, which are associated with the loss of cardiovascular cells. Pathogenically the role of ferroptosis, an iron-dependent cell death, and cuproptosis, a copper-dependent cell death has recently been receiving attention for the pathogenesis of diabetes and its cardiovascular complications. How exposure to environmental metals affects these two metal-dependent cell deaths in cardiovascular pathogenesis under diabetic and nondiabetic conditions remains largely unknown. As an omnipresent environmental metal, cadmium exposure can cause oxidative stress in the diabetic cardiomyocytes, leading to iron accumulation, glutathione depletion, lipid peroxidation, and finally exacerbate ferroptosis and disrupt the cardiac. Moreover, cadmium-induced hyperglycemia can enhance the circulation of advanced glycation end products (AGEs). Excessive AGEs in diabetes promote the upregulation of copper importer solute carrier family 31 member 1 through activating transcription factor 3/transcription factor PU.1, thereby increasing intracellular Cu+ accumulation in cardiomyocytes and disturbing Cu+ homeostasis, leading to a decline of Fe-S cluster protein and reactive oxygen species accumulation in cardiomyocytes mitochondria. In this review, we summarize the available evidence and the most recent advances exploring the underlying mechanisms of ferroptosis and cuproptosis in CVDs and diabetic cardiovascular complications, to provide critical perspectives on the potential pathogenic roles of ferroptosis and cuproptosis in cadmium-induced or exacerbated cardiovascular complications in diabetic individuals.
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Affiliation(s)
- Saman Saedi
- Department of Animal Science, College of Agriculture, Shiraz University, Shiraz, Iran
| | - Yi Tan
- Pediatric Research Institute, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, United States
- Wendy Novak Diabetes Institute, Norton Children’s Hospital, Louisville, KY, United States
- Department of Pharmacology and Toxicology, University of Louisville School of Medicine, Louisville, KY, United States
| | - Sara E. Watson
- Pediatric Research Institute, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, United States
- Wendy Novak Diabetes Institute, Norton Children’s Hospital, Louisville, KY, United States
- Division of Endocrinology, Department of Pediatrics, University of Louisville, Norton Children’s Hospital, Louisville, KY, United States
| | - Kupper A. Wintergerst
- Pediatric Research Institute, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, United States
- Wendy Novak Diabetes Institute, Norton Children’s Hospital, Louisville, KY, United States
- Division of Endocrinology, Department of Pediatrics, University of Louisville, Norton Children’s Hospital, Louisville, KY, United States
- The Center for Integrative Environmental Health Sciences, University of Louisville School of Medicine, Louisville, KY, United States
| | - Lu Cai
- Pediatric Research Institute, Department of Pediatrics, University of Louisville School of Medicine, Louisville, KY, United States
- Wendy Novak Diabetes Institute, Norton Children’s Hospital, Louisville, KY, United States
- Department of Pharmacology and Toxicology, University of Louisville School of Medicine, Louisville, KY, United States
- The Center for Integrative Environmental Health Sciences, University of Louisville School of Medicine, Louisville, KY, United States
- Department of Radiation Oncology, University of Louisville School of Medicine, Louisville, KY, United States
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Nadiger N, Veed JK, Chinya Nataraj P, Mukhopadhyay A. DNA methylation and type 2 diabetes: a systematic review. Clin Epigenetics 2024; 16:67. [PMID: 38755631 PMCID: PMC11100087 DOI: 10.1186/s13148-024-01670-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 04/11/2024] [Indexed: 05/18/2024] Open
Abstract
OBJECTIVE DNA methylation influences gene expression and function in the pathophysiology of type 2 diabetes mellitus (T2DM). Mapping of T2DM-associated DNA methylation could aid early detection and/or therapeutic treatment options for diabetics. DESIGN A systematic literature search for associations between T2DM and DNA methylation was performed. Prospero registration ID: CRD42020140436. METHODS PubMed and ScienceDirect databases were searched (till October 19, 2023). Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines and New Castle Ottawa scale were used for reporting the selection and quality of the studies, respectively. RESULT Thirty-two articles were selected. Four of 130 differentially methylated genes in blood, adipose, liver or pancreatic islets (TXNIP, ABCG1, PPARGC1A, PTPRN2) were reported in > 1 study. TXNIP was hypomethylated in diabetic blood across ethnicities. Gene enrichment analysis of the differentially methylated genes highlighted relevant disease pathways (T2DM, type 1 diabetes and adipocytokine signaling). Three prospective studies reported association of methylation in IGFBP2, MSI2, FTO, TXNIP, SREBF1, PHOSPHO1, SOCS3 and ABCG1 in blood at baseline with incident T2DM/hyperglycemia. Sex-specific differential methylation was reported only for HOOK2 in visceral adipose tissue (female diabetics: hypermethylated, male diabetics: hypomethylated). Gene expression was inversely associated with methylation status in 8 studies, in genes including ABCG1 (blood), S100A4 (adipose tissue), PER2 (pancreatic islets), PDGFA (liver) and PPARGC1A (skeletal muscle). CONCLUSION This review summarizes available evidence for using DNA methylation patterns to unravel T2DM pathophysiology. Further validation studies in diverse populations will set the stage for utilizing this knowledge for identifying early diagnostic markers and novel druggable pathways.
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Affiliation(s)
- Nikhil Nadiger
- Research Scholar, Manipal Academy of Higher Education, Manipal, India
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, St Johns National Academy of Health Sciences, Sarjapura Road, Koramangala, Bangalore, 560034, India
| | - Jyothisha Kana Veed
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, St Johns National Academy of Health Sciences, Sarjapura Road, Koramangala, Bangalore, 560034, India
| | - Priyanka Chinya Nataraj
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, St Johns National Academy of Health Sciences, Sarjapura Road, Koramangala, Bangalore, 560034, India
- Vedantu, Bangalore, India
| | - Arpita Mukhopadhyay
- Division of Nutrition, St. John's Research Institute, St. John's Medical College, St Johns National Academy of Health Sciences, Sarjapura Road, Koramangala, Bangalore, 560034, India.
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Seo H, Park JH, Hwang JT, Choi HK, Park SH, Lee J. Epigenetic Profiling of Type 2 Diabetes Mellitus: An Epigenome-Wide Association Study of DNA Methylation in the Korean Genome and Epidemiology Study. Genes (Basel) 2023; 14:2207. [PMID: 38137029 PMCID: PMC10743302 DOI: 10.3390/genes14122207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 12/08/2023] [Accepted: 12/12/2023] [Indexed: 12/24/2023] Open
Abstract
Diabetes is characterized by persistently high blood glucose levels and severe complications and affects millions of people worldwide. In this study, we explored the epigenetic landscape of diabetes using data from the Korean Genome and Epidemiology Study (KoGES), specifically the Ansung-Ansan (AS-AS) cohort. Using epigenome-wide association studies, we investigated DNA methylation patterns in patients with type 2 diabetes mellitus (T2DM) and those with normal glucose regulation. Differential methylation analysis revealed 106 differentially methylated probes (DMPs), with the 10 top DMPs prominently associated with TXNIP, PDK4, NBPF20, ARRDC4, UFM1, PFKFB2, C7orf50, and ABCG1, indicating significant changes in methylation. Correlation analysis highlighted the association between the leading DMPs (e.g., cg19693031 and cg26974062 for TXNIP and cg26823705 for NBPF20) and key glycemic markers (fasting plasma glucose and hemoglobin A1c), confirming their relevance in T2DM. Moreover, we identified 62 significantly differentially methylated regions (DMRs) spanning 61 genes. A DMR associated with PDE1C showed hypermethylation, whereas DMRs associated with DIP2C, FLJ90757, PRSS50, and TDRD9 showed hypomethylation. PDE1C and TDRD9 showed a strong positive correlation between the CpG sites included in each DMR, which have previously been implicated in T2DM-related processes. This study contributes to the understanding of epigenetic modifications in T2DM. These valuable insights can be utilized in identifying potential biomarkers and therapeutic targets for effective management and prevention of diabetes.
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Affiliation(s)
| | | | | | | | | | - Jangho Lee
- Korea Food Research Institute, Wanju-gun 55365, Jeollabuk-do, Republic of Korea; (H.S.); (J.-H.P.); (J.-T.H.); (H.-K.C.); (S.-H.P.)
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Clark-Boucher D, Zhou X, Du J, Liu Y, Needham BL, Smith JA, Mukherjee B. Methods for mediation analysis with high-dimensional DNA methylation data: Possible choices and comparisons. PLoS Genet 2023; 19:e1011022. [PMID: 37934796 PMCID: PMC10655967 DOI: 10.1371/journal.pgen.1011022] [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: 05/23/2023] [Revised: 11/17/2023] [Accepted: 10/18/2023] [Indexed: 11/09/2023] Open
Abstract
Epigenetic researchers often evaluate DNA methylation as a potential mediator of the effect of social/environmental exposures on a health outcome. Modern statistical methods for jointly evaluating many mediators have not been widely adopted. We compare seven methods for high-dimensional mediation analysis with continuous outcomes through both diverse simulations and analysis of DNAm data from a large multi-ethnic cohort in the United States, while providing an R package for their seamless implementation and adoption. Among the considered choices, the best-performing methods for detecting active mediators in simulations are the Bayesian sparse linear mixed model (BSLMM) and high-dimensional mediation analysis (HDMA); while the preferred methods for estimating the global mediation effect are high-dimensional linear mediation analysis (HILMA) and principal component mediation analysis (PCMA). We provide guidelines for epigenetic researchers on choosing the best method in practice and offer suggestions for future methodological development.
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Affiliation(s)
- Dylan Clark-Boucher
- Department of Biostatistics, Harvard T.H. Chan School of Public Health; Boston, Massachusetts, United States of America
| | - Xiang Zhou
- Department of Biostatistics, University of Michigan; Ann Arbor, Michigan, United States of America
| | - Jiacong Du
- Department of Biostatistics, University of Michigan; Ann Arbor, Michigan, United States of America
| | - Yongmei Liu
- Department of Medicine, Divisions of Cardiology and Neurology, Duke University Medical Center; Durham, North Carolina, United States of America
| | - Belinda L. Needham
- Department of Epidemiology, University of Michigan; Ann Arbor, Michigan, United States of America
| | - Jennifer A. Smith
- Department of Epidemiology, University of Michigan; Ann Arbor, Michigan, United States of America
- Survey Research Center, Institute for Social Research, University of Michigan; Ann Arbor, Michigan, United States of America
| | - Bhramar Mukherjee
- Department of Biostatistics, University of Michigan; Ann Arbor, Michigan, United States of America
- Department of Epidemiology, University of Michigan; Ann Arbor, Michigan, United States of America
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Hong X, Wu Z, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Gao W, Li L. Longitudinal Association of DNA Methylation With Type 2 Diabetes and Glycemic Traits: A 5-Year Cross-Lagged Twin Study. Diabetes 2022; 71:2804-2817. [PMID: 36170668 DOI: 10.2337/db22-0513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/20/2022] [Indexed: 01/11/2023]
Abstract
Investigators of previous cross-sectional epigenome-wide association studies (EWAS) in adults have reported hundreds of 5'-cytosine-phosphate-guanine-3' (CpG) sites associated with type 2 diabetes mellitus (T2DM) and glycemic traits. However, the results from EWAS have been inconsistent, and longitudinal observations of these associations are scarce. Furthermore, few studies have investigated whether DNA methylation (DNAm) could be modified by smoking, drinking, and glycemic traits, which have broad impacts on genome-wide DNAm and result in altering the risk of T2DM. Twin studies provide a valuable tool for epigenetic studies, as twins are naturally matched for genetic information. In this study, we conducted a systematic literature search in PubMed and Embase for EWAS, and 214, 33, and 117 candidate CpG sites were selected for T2DM, HbA1c, and fasting blood glucose (FBG). Based on 1,070 twins from the Chinese National Twin Registry, 67, 17, and 16 CpG sites from previous studies were validated for T2DM, HbA1c, and FBG. Longitudinal review and blood sampling for phenotypic information and DNAm were conducted twice in 2013 and 2018 for 308 twins. A cross-lagged analysis was performed to examine the temporal relationship between DNAm and T2DM or glycemic traits in the longitudinal data. A total of 11 significant paths from T2DM to subsequent DNAm and 15 paths from DNAm to subsequent T2DM were detected, suggesting both directions of associations. For glycemic traits, we detected 17 cross-lagged associations from baseline glycemic traits to subsequent DNAm, and none were from the other cross-lagged direction, indicating that CpG sites may be the consequences, not the causes, of glycemic traits. Finally, a longitudinal mediation analysis was performed to explore the mediation effects of DNAm on the associations of smoking, drinking, and glycemic traits with T2DM. No significant mediations of DNAm in the associations linking smoking and drinking with T2DM were found. In contrast, our study suggested a potential role of DNAm of cg19693031, cg00574958, and cg04816311 in mediating the effect of altered glycemic traits on T2DM.
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Affiliation(s)
- Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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