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Zhang J, Cheng X, Wei Y, Zhang Z, Zhou Q, Guan Y, Yan Y, Wang R, Jia C, An J, He M. Epigenome-wide perspective of cadmium-associated DNA methylation and its mediation role in the associations of cadmium with lipid levels and dyslipidemia risk. Food Chem Toxicol 2024; 184:114409. [PMID: 38128686 DOI: 10.1016/j.fct.2023.114409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Revised: 12/13/2023] [Accepted: 12/18/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND Studies demonstrated the associations of cadmium (Cd) with lipid levels and dyslipidemia risk, but the mechanisms involved need further exploration. OBJECTIVES We aimed to explore the role of DNA methylation (DNAM) in the relationship of Cd with lipid levels and dyslipidemia risk. METHODS Urinary cadmium levels (UCd) were measured by inductively coupled plasma mass spectrometry, serum high-density lipoprotein (HDL), total cholesterol, triglyceride, and low-density lipoprotein were measured with kits, and DNAM was measured using the Infinium MethylationEPIC BeadChip. Robust linear regressions were conducted for epigenome-wide association study. Multivariate linear and logistic regressions were performed to explore the associations of UCd with lipid levels and dyslipidemia risk, respectively. Mediation analyses were conducted to explore potential mediating role of DNAM in the associations of Cd with lipid levels and dyslipidemia risk. RESULTS UCd was negatively associated with HDL levels (p = 0.01) and positively associated with dyslipidemia (p < 0.01). There were 92/11 DMPs/DMRs (FDR<0.05) associated with UCd. Cd-associated DNAM and pathways were connected with cardiometabolic diseases and immunity. Cg07829377 (LINC01060) mediated 42.05%/22.88% of the UCd-HDL/UCd-dyslipidemia associations (p = 0.02 and 0.01, respectively). CONCLUSIONS Cadmium caused site-specific DNAM alterations and the associations of UCd with lipid levels and dyslipidemia risk may be partially mediated by DNAM.
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Affiliation(s)
- Jiazhen Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Xu Cheng
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yue Wei
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China; Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Zefang Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China; Department of Tuberculosis Control, Wuhan Pulmonary Hospital, Wuhan, Hubei, China
| | - Qihang Zhou
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Youbing Guan
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Yan Yan
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Ruixin Wang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Chengyong Jia
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Jun An
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, Hubei, China.
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Geiger M, Gorica E, Mohammed SA, Mongelli A, Mengozi A, Delfine V, Ruschitzka F, Costantino S, Paneni F. Epigenetic Network in Immunometabolic Disease. Adv Biol (Weinh) 2024; 8:e2300211. [PMID: 37794610 DOI: 10.1002/adbi.202300211] [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: 06/08/2023] [Revised: 09/08/2023] [Indexed: 10/06/2023]
Abstract
Although a large amount of data consistently shows that genes affect immunometabolic characteristics and outcomes, epigenetic mechanisms are also heavily implicated. Epigenetic changes, including DNA methylation, histone modification, and noncoding RNA, determine gene activity by altering the accessibility of chromatin to transcription factors. Various factors influence these alterations, including genetics, lifestyle, and environmental cues. Moreover, acquired epigenetic signals can be transmitted across generations, thus contributing to early disease traits in the offspring. A closer investigation is critical in this aspect as it can help to understand the underlying molecular mechanisms further and gain insights into potential therapeutic targets for preventing and treating diseases arising from immuno-metabolic dysregulation. In this review, the role of chromatin alterations in the transcriptional modulation of genes involved in insulin resistance, systemic inflammation, macrophage polarization, endothelial dysfunction, metabolic cardiomyopathy, and nonalcoholic fatty liver disease (NAFLD), is discussed. An overview of emerging chromatin-modifying drugs and the importance of the individual epigenetic profile for personalized therapeutic approaches in patients with immuno-metabolic disorders is also presented.
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Affiliation(s)
- Martin Geiger
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Era Gorica
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Shafeeq Ahmed Mohammed
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Alessia Mongelli
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Alessandro Mengozi
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Valentina Delfine
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Frank Ruschitzka
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Sarah Costantino
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
- University Heart Center, University Hospital Zurich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
| | - Francesco Paneni
- Center for Translational and Experimental Cardiology, University Hospital Zürich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
- University Heart Center, University Hospital Zurich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
- Department of Research and Education, University Hospital Zurich and University of Zürich, Wagistrasse 12, Schlieren, Zurich, 8952, Switzerland
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Bruce KD, Eckel RH. Can DNA Methylation Predict the Lipid Response to Dietary Intervention? There's a Fat Chance. J Clin Endocrinol Metab 2023; 108:e1747-e1748. [PMID: 37191137 PMCID: PMC10655505 DOI: 10.1210/clinem/dgad274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 05/12/2023] [Indexed: 05/17/2023]
Affiliation(s)
- Kimberley D Bruce
- Division of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
| | - Robert H Eckel
- Division of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO 80045, USA
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Sarnowski C, Huan T, Ma Y, Joehanes R, Beiser A, DeCarli CS, Heard-Costa NL, Levy D, Lin H, Liu CT, Liu C, Meigs JB, Satizabal CL, Florez JC, Hivert MF, Dupuis J, De Jager PL, Bennett DA, Seshadri S, Morrison AC. Multi-tissue epigenetic analysis identifies distinct associations underlying insulin resistance and Alzheimer's disease at CPT1A locus. Clin Epigenetics 2023; 15:173. [PMID: 37891690 PMCID: PMC10612362 DOI: 10.1186/s13148-023-01589-4] [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: 07/17/2023] [Accepted: 10/20/2023] [Indexed: 10/29/2023] Open
Abstract
BACKGROUND Insulin resistance (IR) is a major risk factor for Alzheimer's disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD. METHODS We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P < 1.1 × 10-7) and evaluated their association with neurological traits in participants from the FHS (N = 3040) and the Religious Orders Study/Memory and Aging Project (ROSMAP, N = 707). DNA methylation profiles were measured in blood (FHS) or dorsolateral prefrontal cortex (ROSMAP) using the Illumina HumanMethylation450 BeadChip. Linear regressions (ROSMAP) or mixed-effects models accounting for familial relatedness (FHS) adjusted for age, sex, cohort, self-reported race, batch, and cell type proportions were used to assess associations between DNA methylation and neurological traits accounting for multiple testing. RESULTS We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10-11 and P = 9.0 × 10-8), larger total brain volumes (P = 0.03 and P = 9.7 × 10-4), and smaller log lateral ventricular volumes (P = 0.07 and P = 0.03). In ROSMAP, higher levels of brain DNA methylation at the same two CPT1A markers were associated with greater risk of cognitive impairment (P = 0.005 and P = 0.02) and higher AD-related indices (CERAD score: P = 5 × 10-4 and 0.001; Braak stage: P = 0.004 and P = 0.01). CONCLUSIONS Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus.
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Affiliation(s)
- Chloé Sarnowski
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA.
| | - Tianxiao Huan
- Population Sciences Branch, National Heart, Lung and Blood Institutes of Health, Bethesda, MD, USA
| | - Yiyi Ma
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung and Blood Institutes of Health, Bethesda, MD, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Alexa Beiser
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | | | - Nancy L Heard-Costa
- The Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Daniel Levy
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- The Framingham Heart Study, Framingham, MA, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, Worcester, MA, USA
| | - Ching-Ti Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - Chunyu Liu
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Claudia L Satizabal
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
- Department of Population Health Sciences, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Jose C Florez
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Programs in Metabolism and Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Center for Genomic Medicine and Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Harvard University, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Josée Dupuis
- Department of Biostatistics, School of Public Health, Boston University, Boston, MA, USA
- Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, McGill University, Montreal, Canada
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, The University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
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Topriceanu CC, Dev E, Ahmad M, Hughes R, Shiwani H, Webber M, Direk K, Wong A, Ugander M, Moon JC, Hughes AD, Maddock J, Schlegel TT, Captur G. Accelerated DNA methylation age plays a role in the impact of cardiovascular risk factors on the human heart. Clin Epigenetics 2023; 15:164. [PMID: 37853450 PMCID: PMC10583368 DOI: 10.1186/s13148-023-01576-9] [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: 06/27/2023] [Accepted: 09/29/2023] [Indexed: 10/20/2023] Open
Abstract
BACKGROUND DNA methylation (DNAm) age acceleration (AgeAccel) and cardiac age by 12-lead advanced electrocardiography (A-ECG) are promising biomarkers of biological and cardiac aging, respectively. We aimed to explore the relationships between DNAm age and A-ECG heart age and to understand the extent to which DNAm AgeAccel relates to cardiovascular (CV) risk factors in a British birth cohort from 1946. RESULTS We studied four DNAm ages (AgeHannum, AgeHorvath, PhenoAge, and GrimAge) and their corresponding AgeAccel. Outcomes were the results from two publicly available ECG-based cardiac age scores: the Bayesian A-ECG-based heart age score of Lindow et al. 2022 and the deep neural network (DNN) ECG-based heart age score of Ribeiro et al. 2020. DNAm AgeAccel was also studied relative to results from two logistic regression-based A-ECG disease scores, one for left ventricular (LV) systolic dysfunction (LVSD), and one for LV electrical remodeling (LVER). Generalized linear models were used to explore the extent to which any associations between biological cardiometabolic risk factors (body mass index, hypertension, diabetes, high cholesterol, previous cardiovascular disease [CVD], and any CV risk factor) and the ECG-based outcomes are mediated by DNAm AgeAccel. We derived the total effects, average causal mediation effects (ACMEs), average direct effects (ADEs), and the proportion mediated [PM] with their 95% confidence intervals [CIs]. 498 participants (all 60-64 years) were included, with the youngest ECG heart age being 27 and the oldest 90. When exploring the associations between cardiometabolic risk factors and Bayesian A-ECG cardiac age, AgeAccelPheno appears to be a partial mediator, as ACME was 0.23 years [0.01, 0.52] p = 0.028 (i.e., PM≈18%) for diabetes, 0.34 [0.03, 0.74] p = 0.024 (i.e., PM≈15%) for high cholesterol, and 0.34 [0.03, 0.74] p = 0.024 (PM≈15%) for any CV risk factor. Similarly, AgeAccelGrim mediates ≈30% of the relationship between diabetes or high cholesterol and the DNN ECG-based heart age. When exploring the link between cardiometabolic risk factors and the A-ECG-based LVSD and LVER scores, it appears that AgeAccelPheno or AgeAccelGrim mediate 10-40% of these associations. CONCLUSION By the age of 60, participants with accelerated DNA methylation appear to have older, weaker, and more electrically impaired hearts. We show that the harmful effects of CV risk factors on cardiac age and health, appear to be partially mediated by DNAm AgeAccelPheno and AgeAccelGrim. This highlights the need to further investigate the potential cardioprotective effects of selective DNA methyltransferases modulators.
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Affiliation(s)
- Constantin-Cristian Topriceanu
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
- Cardiac MRI Unit, Barts Heart Centre, West Smithfield, London, UK
| | - Eesha Dev
- UCL Medical School, Gower Street, London, UK
| | - Mahmood Ahmad
- Centre for Inherited Heart Muscle Conditions, The Royal Free Hospital, Pond Street, Hampstead, London, UK
| | - Rebecca Hughes
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
- Cardiac MRI Unit, Barts Heart Centre, West Smithfield, London, UK
| | - Hunain Shiwani
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
- Cardiac MRI Unit, Barts Heart Centre, West Smithfield, London, UK
| | - Matthew Webber
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
| | - Kenan Direk
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK
| | - Andrew Wong
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK
| | - Martin Ugander
- Kolling Institute Royal North Shore Hospital, and Charles Perkins Centre, Faculty of Medicine and Health, University of Sydney, Sydney, Australia
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
| | - James C Moon
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
- Cardiac MRI Unit, Barts Heart Centre, West Smithfield, London, UK
| | - Alun D Hughes
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
| | - Jane Maddock
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK
| | - Todd T Schlegel
- Department of Clinical Physiology, Karolinska University Hospital, and Karolinska Institutet, Stockholm, Sweden
- Nicollier-Schlegel SARL, Trélex, Switzerland
| | - Gabriella Captur
- UCL MRC Unit for Lifelong Health and Ageing, University College London, 1-19 Torrington Place, London, UK.
- UCL Institute of Cardiovascular Science, University College London, 62 Huntley St, London, WC1E 6BT, UK.
- Centre for Inherited Heart Muscle Conditions, The Royal Free Hospital, Pond Street, Hampstead, London, UK.
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Jones AC, Ament Z, Patki A, Chaudhary NS, Srinivasasainagendra V, Kijpaisalratana N, Absher DM, Tiwari HK, Arnett DK, Kimberly WT, Irvin MR. Metabolite profiles and DNA methylation in metabolic syndrome: a two-sample, bidirectional Mendelian randomization. Front Genet 2023; 14:1184661. [PMID: 37779905 PMCID: PMC10540781 DOI: 10.3389/fgene.2023.1184661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 09/07/2023] [Indexed: 10/03/2023] Open
Abstract
Introduction: Metabolic syndrome (MetS) increases the risk of cardiovascular disease and death. Previous '-omics' studies have identified dysregulated serum metabolites and aberrant DNA methylation in the setting of MetS. However, the relationship between the metabolome and epigenome have not been elucidated. In this study, we identified serum metabolites associated with MetS and DNA methylation, and we conducted bidirectional Mendelian randomization (MR) to assess causal relationships between metabolites and methylation. Methods: We leveraged metabolomic and genomic data from a national United States cohort of older adults (REGARDS), as well as metabolomic, epigenomic, and genomic data from a family-based study of hypertension (HyperGEN). We conducted metabolite profiling for MetS in REGARDS using weighted logistic regression models and validated them in HyperGEN. Validated metabolites were selected for methylation studies which fit linear mixed models between metabolites and six CpG sites previously linked to MetS. Statistically significant metabolite-CpG pairs were selected for two-sample, bidirectional MR. Results: Forward MR indicated that glucose and serine metabolites were causal on CpG methylation near CPT1A [B(SE): -0.003 (0.002), p = 0.028 and B(SE): 0.029 (0.011), p = 0.030, respectively] and that serine metabolites were causal on ABCG1 [B(SE): -0.008(0.003), p = 0.006] and SREBF1 [B(SE): -0.009(0.004), p = 0.018] methylation, which suggested a protective effect of serine. Reverse MR showed a bidirectional relationship between cg06500161 (ABCG1) and serine [B(SE): -1.534 (0.668), p = 0.023]. Discussion: The metabolome may contribute to the relationship between MetS and epigenetic modifications.
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Affiliation(s)
- Alana C. Jones
- Medical Scientist Training Program, University of Alabama at Birmingham, Birmingham, AL, United States
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Zsuzsanna Ament
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Amit Patki
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Ninad S. Chaudhary
- Department of Epidemiology, University of Texas Health Science Center, Houston, TX, United States
| | | | - Naruchorn Kijpaisalratana
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
- Division of Neurology, Department of Medicine and Division of Academic Affairs, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Devin M. Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, United States
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Donna K. Arnett
- Office of the Provost, University of South Carolina, Columbia, SC, United States
| | - W. Taylor Kimberly
- Department of Neurology, Massachusetts General Hospital, Boston, MA, United States
| | - Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL, United States
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Liu D, Aziz NA, Landstra EN, Breteler MMB. The lipidomic correlates of epigenetic aging across the adult lifespan: A population-based study. Aging Cell 2023; 22:e13934. [PMID: 37496173 PMCID: PMC10497837 DOI: 10.1111/acel.13934] [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: 04/03/2023] [Revised: 07/05/2023] [Accepted: 07/07/2023] [Indexed: 07/28/2023] Open
Abstract
Lipid signaling is involved in longevity regulation, but which specific lipid molecular species affect human biological aging remains largely unknown. We investigated the relation between complex lipids and DNA methylation-based metrics of biological aging among 4181 participants (mean age 55.1 years (range 30.0-95.0)) from the Rhineland Study, an ongoing population-based cohort study in Bonn, Germany. The absolute concentration of 14 lipid classes, covering 964 molecular species and 267 fatty acid composites, was measured by Metabolon Complex Lipid Panel. DNA methylation-based metrics of biological aging (AgeAccelPheno and AgeAccelGrim) were calculated based on published algorithms. Epigenome-wide association analyses (EWAS) of biological aging-associated lipids and pathway analysis were performed to gain biological insights into the mechanisms underlying the effects of lipidomics on biological aging. We found that higher levels of molecular species belonging to neutral lipids, phosphatidylethanolamines, phosphatidylinositols, and dihydroceramides were associated with faster biological aging, whereas higher levels of lysophosphatidylcholine, hexosylceramide, and lactosylceramide species were associated with slower biological aging. Ceramide, phosphatidylcholine, and lysophosphatidylethanolamine species with odd-numbered fatty acid tail lengths were associated with slower biological aging, whereas those with even-numbered chain lengths were associated with faster biological aging. EWAS combined with functional pathway analysis revealed several complex lipids associated with biological aging as important regulators of known longevity and aging-related pathways.
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Affiliation(s)
- Dan Liu
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
| | - N. Ahmad Aziz
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Department of Neurology, Faculty of MedicineUniversity of BonnBonnGermany
| | - Elvire Nadieh Landstra
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
| | - Monique M. B. Breteler
- Population Health SciencesGerman Center for Neurodegenerative Diseases (DZNE)BonnGermany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of MedicineUniversity of BonnBonnGermany
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Jin J, Zhao X, Zhu C, Li M, Wang J, Fan Y, Liu C, Shen C, Yang R. Hypomethylation of ABCG1 in peripheral blood as a potential marker for the detection of coronary heart disease. Clin Epigenetics 2023; 15:120. [PMID: 37507725 PMCID: PMC10375639 DOI: 10.1186/s13148-023-01533-6] [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: 06/07/2023] [Accepted: 07/13/2023] [Indexed: 07/30/2023] Open
Abstract
BACKGROUND Novel molecular biomarkers for the risk assessment and early detection of coronary heart disease (CHD) are urgently needed for disease prevention. Altered methylation of ATP-binding cassette subfamily G member 1 (ABCG1) has been implicated in CHD but was mostly studied in Caucasians. Exploring the potential relationship between ABCG1 methylation in blood and CHD among the Chinese population would yield valuable insights. METHODS Peripheral blood samples were obtained from a case-control study (287 CHD patients vs. 277 controls) and a prospective nested case-control study (171 CHD patients and 197 matched controls). DNA extraction and bisulfite-specific PCR amplification techniques were employed for sample processing. Quantitative assessment of methylation levels was conducted using mass spectrometry. Statistical analyses involved the utilization of logistic regression and nonparametric tests. RESULTS We found hypomethylation of ABCG1 in whole blood was associated with the risk of CHD in both studies, which was enhanced in heart failure (HF) patients, female and younger subjects. When combined with baseline characteristics, altered ABCG1 methylation showed improved predictive effect for differentiating CHD cases, ischemic cardiomyopathy (ICM) cases, younger than 60 years CHD cases, and female CHD cases from healthy controls (area under the curve (AUC) = 0.68, 0.71, 0.74, and 0.73, respectively). CONCLUSIONS We demonstrated a robust link between ABCG1 hypomethylation in whole blood and CHD risk in the Chinese population and provided novel evidence indicating that aberrant ABCG1 methylation in peripheral blood can serve as an early detection biomarker for CHD patients.
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Affiliation(s)
- Jialie Jin
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Xiaojing Zhao
- Military Translational Medicine Lab, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100000, People's Republic of China
- Beijing Key Laboratory of Chronic Heart Failure Precision Medicine, Medical Innovation Research Division, Chinese PLA General Hospital, Beijing, 100000, People's Republic of China
| | - Chao Zhu
- Department of Cardiology, Beijing Friendship Hospital, Capital Medical University, Beijing, 100000, People's Republic of China
| | - Mengxia Li
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Jinxin Wang
- Department of Cardiology, The Second Medical Centre, Chinese PLA General Hospital, Beijing, 100000, People's Republic of China
| | - Yao Fan
- Division of Clinical Epidemiology, Affiliated Geriatric Hospital of Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Chunlan Liu
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 210000, People's Republic of China
| | - Chong Shen
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 210000, People's Republic of China.
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, 211166, Nanjing, China.
| | - Rongxi Yang
- Department of Epidemiology, School of Public Health, Nanjing Medical University, Nanjing, 210000, People's Republic of China.
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9
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Li X, Shao X, Xue Q, Kou M, Champagne CM, Koseva BS, Heianza Y, Grundberg E, Bazzano LA, Bray GA, Sacks FM, Qi L. DNA Methylation Near CPT1A and Changes in Triglyceride-rich Lipoproteins in Response to Weight-loss Diet Interventions. J Clin Endocrinol Metab 2023; 108:e542-e549. [PMID: 36800272 PMCID: PMC10348458 DOI: 10.1210/clinem/dgad086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 02/08/2023] [Accepted: 02/09/2023] [Indexed: 02/18/2023]
Abstract
CONTEXT Carnitine palmitoyltransferase-1A, encoded by the CPT1A gene, plays a key role in the oxidation of long-chain fatty acids in the mitochondria and may be important in triglyceride metabolism. Previous work has shown that high fat intake was negatively associated with CPT1A methylation and positively associated with CPT1A expression. OBJECTIVE We aim to investigate the association of DNA methylation (DNAm) at the CPT1A gene with reductions in triglycerides and triglyceride-rich lipoproteins (TRLs) in response to weight-loss diet interventions. METHODS The current study included 538 White participants, who were randomly assigned to 1 of 4 diets varying in macronutrient components. We defined the regional DNAm at CPT1A as the average methylation level over CpGs within 500 bp of the 3 triglyceride-related DNAm sites. RESULTS Dietary fat intake significantly modified the association between baseline DNAm at CPT1A and 2-year changes in total plasma triglycerides, independent of concurrent weight loss. Among participants assigned to a low-fat diet, a higher regional DNAm level at CPT1A was associated with a greater reduction in total plasma triglycerides at 2 years (P = .01), compared with those assigned to a high-fat diet (P = .64) (P interaction = .018). Further investigation on lipids and apolipoproteins in very low-density lipoprotein (VLDL) revealed similar interaction patterns for 2-year changes in VLDL-triglycerides, VLDL-cholesterol, and VLDL-apolipoprotein B (P interaction = .009, .002, and .016, respectively), but not for VLDL-apoC-III (P interaction = .36). CONCLUSION Participants with a higher regional DNAm level at CPT1A benefit more in long-term improvement in triglycerides, particularly in the TRLs and related apolipoproteins when consuming a low-fat weight-loss diet.
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Affiliation(s)
- Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Xiaojian Shao
- Digital Technologies Research Centre, National Research Council Canada, Ottawa, Ontario K1C 0R6, Canada
| | - Qiaochu Xue
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Minghao Kou
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Catherine M Champagne
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
| | - Boryana S Koseva
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO 64108, USA
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Elin Grundberg
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO 64108, USA
| | - Lydia A Bazzano
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA 70808, USA
| | - Frank M Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
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10
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Jung SY, Bhatti P, Pellegrini M. DNA methylation in peripheral blood leukocytes for the association with glucose metabolism and invasive breast cancer. Clin Epigenetics 2023; 15:23. [PMID: 36782224 PMCID: PMC9926571 DOI: 10.1186/s13148-023-01435-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Accepted: 01/26/2023] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND Insulin resistance (IR) is a well-established factor for breast cancer (BC) risk in postmenopausal women, but the interrelated molecular pathways on the methylome are not explicitly described. We conducted a population-level epigenome-wide association (EWA) study for DNA methylation (DNAm) probes that are associated with IR and prospectively correlated with BC development, both overall and in BC subtypes among postmenopausal women. METHODS We used data from Women's Health Initiative (WHI) ancillary studies for our EWA analyses and evaluated the associations of site-specific DNAm across the genome with IR phenotypes by multiple regressions adjusting for age and leukocyte heterogeneities. For our analysis of the top 20 IR-CpGs with BC risk, we used the WHI and the Cancer Genomic Atlas (TCGA), using multiple Cox proportional hazards and logit regressions, respectively, accounting for age, diabetes, obesity, leukocyte heterogeneities, and tumor purity (for TCGA). We further conducted a Gene Set Enrichment Analysis. RESULTS We detected several EWA-CpGs in TXNIP, CPT1A, PHGDH, and ABCG1. In particular, cg19693031 in TXNIP was replicated in all IR phenotypes, measured by fasting levels of glucose, insulin, and homeostatic model assessment-IR. Of those replicated IR-genes, 3 genes (CPT1A, PHGDH, and ABCG1) were further correlated with BC risk; and 1 individual CpG (cg01676795 in POR) was commonly detected across the 2 cohorts. CONCLUSIONS Our study contributes to better understanding of the interconnected molecular pathways on the methylome between IR and BC carcinogenesis and suggests potential use of DNAm markers in the peripheral blood cells as preventive targets to detect an at-risk group for IR and BC in postmenopausal women.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, School of Nursing, University of California, Los Angeles, 700 Tiverton Ave, 3-264 Factor Building, Los Angeles, CA, 90095, USA.
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, 90095, USA.
| | - Parveen Bhatti
- Cancer Control Research, BC Cancer Research Institute, Vancouver, BC, Canada
- School of Population and Public Health, University of British Columbia, Vancouver, BC, Canada
| | - Matteo Pellegrini
- Department of Molecular, Cell and Developmental Biology, Life Sciences Division, University of California, Los Angeles, Los Angeles, CA, 90095, USA
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11
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Lai CQ, Parnell LD, Lee YC, Zeng H, Smith CE, McKeown NM, Arnett DK, Ordovás JM. The impact of alcoholic drinks and dietary factors on epigenetic markers associated with triglyceride levels. Front Genet 2023; 14:1117778. [PMID: 36873949 PMCID: PMC9975169 DOI: 10.3389/fgene.2023.1117778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Accepted: 01/30/2023] [Indexed: 02/17/2023] Open
Abstract
Background: Many epigenetic loci have been associated with plasma triglyceride (TG) levels, but epigenetic connections between those loci and dietary exposures are largely unknown. This study aimed to characterize the epigenetic links between diet, lifestyle, and TG. Methods: We first conducted an epigenome-wide association study (EWAS) for TG in the Framingham Heart Study Offspring population (FHS, n = 2,264). We then examined relationships between dietary and lifestyle-related variables, collected four times in 13 years, and differential DNA methylation sites (DMSs) associated with the last TG measures. Third, we conducted a mediation analysis to evaluate the causal relationships between diet-related variables and TG. Finally, we replicated three steps to validate identified DMSs associated with alcohol and carbohydrate intake in the Genetics of Lipid-Lowering Drugs and Diet Network (GOLDN) study (n = 993). Results: In the FHS, the EWAS revealed 28 TG-associated DMSs at 19 gene regions. We identified 102 unique associations between these DMSs and one or more dietary and lifestyle-related variables. Alcohol and carbohydrate intake showed the most significant and consistent associations with 11 TG-associated DMSs. Mediation analyses demonstrated that alcohol and carbohydrate intake independently affect TG via DMSs as mediators. Higher alcohol intake was associated with lower methylation at seven DMSs and higher TG. In contrast, increased carbohydrate intake was associated with higher DNA methylation at two DMSs (CPT1A and SLC7A11) and lower TG. Validation in the GOLDN further supports the findings. Conclusion: Our findings imply that TG-associated DMSs reflect dietary intakes, particularly alcoholic drinks, which could affect the current cardiometabolic risk via epigenetic changes. This study illustrates a new method to map epigenetic signatures of environmental factors for disease risk. Identification of epigenetic markers of dietary intake can provide insight into an individual's risk of cardiovascular disease and support the application of precision nutrition. Clinical Trial Registration: www.ClinicalTrials.gov, the Framingham Heart Study (FHS), NCT00005121; the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), NCT01023750.
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Affiliation(s)
- Chao-Qiang Lai
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Laurence D Parnell
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Yu-Chi Lee
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Haihan Zeng
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Caren E Smith
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Nicola M McKeown
- Programs of Nutrition, Department of Health Sciences, Sargent College of Health and Rehabilitation Sciences, Boston University, Boston, MA, United States.,Nutrition Epidemiology and Data Science Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
| | - Donna K Arnett
- Office of the Provost, University of South Carolina, Columbia, SC, United States
| | - José M Ordovás
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States.,IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
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12
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Epigenetics and Gut Microbiota Crosstalk: A potential Factor in Pathogenesis of Cardiovascular Disorders. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 9:bioengineering9120798. [PMID: 36551003 PMCID: PMC9774431 DOI: 10.3390/bioengineering9120798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Cardiovascular diseases (CVD) are the leading cause of mortality, morbidity, and "sudden death" globally. Environmental and lifestyle factors play important roles in CVD susceptibility, but the link between environmental factors and genetics is not fully established. Epigenetic influence during CVDs is becoming more evident as its direct involvement has been reported. The discovery of epigenetic mechanisms, such as DNA methylation and histone modification, suggested that external factors could alter gene expression to modulate human health. These external factors also influence our gut microbiota (GM), which participates in multiple metabolic processes in our body. Evidence suggests a high association of GM with CVDs. Although the exact mechanism remains unclear, the influence of GM over the epigenetic mechanisms could be one potential pathway in CVD etiology. Both epigenetics and GM are dynamic processes and vary with age and environment. Changes in the composition of GM have been found to underlie the pathogenesis of metabolic diseases via modulating epigenetic changes in the form of DNA methylation, histone modifications, and regulation of non-coding RNAs. Several metabolites produced by the GM, including short-chain fatty acids, folates, biotin, and trimethylamine-N-oxide, have the potential to regulate epigenetics, apart from playing a vital role in normal physiological processes. The role of GM and epigenetics in CVDs are promising areas of research, and important insights in the field of early diagnosis and therapeutic approaches might appear soon.
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13
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Zhang X, Ammous F, Lin L, Ratliff SM, Ware EB, Faul JD, Zhao W, Kardia SLR, Smith JA. The Interplay of Epigenetic, Genetic, and Traditional Risk Factors on Blood Pressure: Findings from the Health and Retirement Study. Genes (Basel) 2022; 13:genes13111959. [PMID: 36360196 PMCID: PMC9689874 DOI: 10.3390/genes13111959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 10/11/2022] [Accepted: 10/19/2022] [Indexed: 01/21/2023] Open
Abstract
The epigenome likely interacts with traditional and genetic risk factors to influence blood pressure. We evaluated whether 13 previously reported DNA methylation sites (CpGs) are associated with systolic (SBP) or diastolic (DBP) blood pressure, both individually and aggregated into methylation risk scores (MRS), in 3070 participants (including 437 African ancestry (AA) and 2021 European ancestry (EA), mean age = 70.5 years) from the Health and Retirement Study. Nine CpGs were at least nominally associated with SBP and/or DBP after adjusting for traditional hypertension risk factors (p < 0.05). MRSSBP was positively associated with SBP in the full sample (β = 1.7 mmHg per 1 standard deviation in MRSSBP; p = 2.7 × 10-5) and in EA (β = 1.6; p = 0.001), and MRSDBP with DBP in the full sample (β = 1.1; p = 1.8 × 10-6), EA (β = 1.1; p = 7.2 × 10-5), and AA (β = 1.4; p = 0.03). The MRS and BP-genetic risk scores were independently associated with blood pressure in EA. The effects of both MRSs were weaker with increased age (pinteraction < 0.01), and the effect of MRSDBP was higher among individuals with at least some college education (pinteraction = 0.02). In AA, increasing MRSSBP was associated with higher SBP in females only (pinteraction = 0.01). Our work shows that MRS is a potential biomarker of blood pressure that may be modified by traditional hypertension risk factors.
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Affiliation(s)
- Xinman Zhang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Lisha Lin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Erin B. Ware
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Jessica D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
- Correspondence:
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14
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Zheng Y, Joyce B, Hwang SJ, Ma J, Liu L, Allen N, Krefman A, Wang J, Gao T, Nannini D, Zhang H, Jacobs DR, Gross M, Fornage M, Lewis CE, Schreiner PJ, Sidney S, Chen D, Greenland P, Levy D, Hou L, Lloyd-Jones D. Association of Cardiovascular Health Through Young Adulthood With Genome-Wide DNA Methylation Patterns in Midlife: The CARDIA Study. Circulation 2022; 146:94-109. [PMID: 35652342 PMCID: PMC9348746 DOI: 10.1161/circulationaha.121.055484] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cardiovascular health (CVH) from young adulthood is strongly associated with an individual's future risk of cardiovascular disease (CVD) and total mortality. Defining epigenomic biomarkers of lifelong CVH exposure and understanding their roles in CVD development may help develop preventive and therapeutic strategies for CVD. METHODS In 1085 CARDIA study (Coronary Artery Risk Development in Young Adults) participants, we defined a clinical cumulative CVH score that combines body mass index, blood pressure, total cholesterol, and fasting glucose measured longitudinally from young adulthood through middle age over 20 years (mean age, 25-45). Blood DNA methylation at >840 000 methylation markers was measured twice over 5 years (mean age, 40 and 45). Epigenome-wide association analyses on the cumulative CVH score were performed in CARDIA and compared in the FHS (Framingham Heart Study). We used penalized regression to build a methylation-based risk score to evaluate the risk of incident coronary artery calcification and clinical CVD events. RESULTS We identified 45 methylation markers associated with cumulative CVH at false discovery rate <0.01 (P=4.7E-7-5.8E-17) in CARDIA and replicated in FHS. These associations were more pronounced with methylation measured at an older age. CPT1A, ABCG1, and SREBF1 appeared as the most prominent genes. The 45 methylation markers were mostly located in transcriptionally active chromatin and involved lipid metabolism, insulin secretion, and cytokine production pathways. Three methylation markers located in genes SARS1, SOCS3, and LINC-PINT statistically mediated 20.4% of the total effect between CVH and risk of incident coronary artery calcification. The methylation risk score added information and significantly (P=0.004) improved the discrimination capacity of coronary artery calcification status versus CVH score alone and showed association with risk of incident coronary artery calcification 5 to 10 years later independent of cumulative CVH score (odds ratio, 1.87; P=9.66E-09). The methylation risk score was also associated with incident clinical CVD in FHS (hazard ratio, 1.28; P=1.22E-05). CONCLUSIONS Cumulative CVH from young adulthood contributes to midlife epigenetic programming over time. Our findings demonstrate the role of epigenetic markers in response to CVH changes and highlight the potential of epigenomic markers for precision CVD prevention, and earlier detection of subclinical CVD, as well.
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Affiliation(s)
- Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Brian Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jiantao Ma
- Tufts University Friedman School of Nutrition Science and Policy, Boston, Massachusetts, USA
| | - Lei Liu
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Norrina Allen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Amy Krefman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tao Gao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Drew Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Haixiang Zhang
- Center for Applied Mathematics, Tianjin University, Tianjin, China
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Dongquan Chen
- Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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15
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Studying Epigenetics of Cardiovascular Diseases on Chip Guide. CARDIOGENETICS 2022. [DOI: 10.3390/cardiogenetics12030021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Epigenetics is defined as the study of inheritable changes in the gene expressions and phenotypes that occurs without altering the normal DNA sequence. These changes are mainly due to an alteration in chromatin or its packaging, which changes the DNA accessibility. DNA methylation, histone modification, and noncoding or microRNAs can best explain the mechanism of epigenetics. There are various DNA methylated enzymes, histone-modifying enzymes, and microRNAs involved in the cause of various CVDs (cardiovascular diseases) such as cardiac hypertrophy, heart failure, and hypertension. Moreover, various CVD risk factors such as diabetes mellitus, hypoxia, aging, dyslipidemia, and their epigenetics are also discussed together with CVDs such as CHD (coronary heart disease) and PAH (pulmonary arterial hypertension). Furthermore, different techniques involved in epigenetic chromatin mapping are explained. Among these techniques, the ChIP-on-chip guide is explained with regard to its role in cardiac hypertrophy, a final form of heart failure. This review focuses on different epigenetic factors that are involved in causing cardiovascular diseases.
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16
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Jeje SO, Adenawoola M, Abosede C. Gestational Nutrition as a Predisposing Factor to Obesity Onset in Offspring: Role for Involvement of Epigenetic Mechanism. Niger J Physiol Sci 2022; 37:1-7. [PMID: 35947841 DOI: 10.54548/njps.v37i1.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2021] [Accepted: 04/12/2022] [Indexed: 06/15/2023]
Abstract
Maternal lifestyle has been implicated as a predisposing factor in the development of metabolic disorders in adulthood. This lifestyle includes the immediate environment, physical activity and nutrition. Maternal nutrition has direct influence on the developmental programming through biochemical alterations and can lead to modifications in the fetal genome through epigenetic mechanisms. Imbalance in basic micro or macro nutrients due to famine or food deficiency during delicate gestational periods can lead to onset of metabolic syndrome including obesity. A major example is the Dutch famine which led to a serious metabolic disorder in adulthood of affected infants. Notably due to gene variants, individualized responses to nutritional deficiencies are unconventional, therefore intensifying the need to study nutritional genomics during fetal programming. Epigenetic mechanisms can cause hereditary changes without changing the DNA sequence; the major mechanisms include small non-coding RNAs, histone modifications and most stable of all is DNA methylation. The significance association between obesity and DNA methylation is through regulation of genes implicated in lipid and glucose metabolism either directly or indirectly by hypomethylation or hypermethylation. Examples include CPT1A, APOA2, ADRB3 and POMC. Any maternal exposure to malnutrition or overnutrition that can affect genes regulating major metabolic pathways in the fetus, will eventually cause underlying changes that can predispose or cause the onset of metabolic disorder in adulthood. In this review, we examined the interaction between nutrition during gestation and epigenetic programming of metabolic syndrome.
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Mazaheri-Tehrani S, Khoshhali M, Heidari-Beni M, Poursafa P, Kelishadi R. A systematic review and metaanalysis of observational studies on the effects of epigenetic factors on serum triglycerides. ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2022; 66:2359-3997000000472. [PMID: 35551677 PMCID: PMC9832862 DOI: 10.20945/2359-3997000000472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 12/22/2021] [Indexed: 11/23/2022]
Abstract
Epigenetic modifications might be associated with serum triglycerides (TG) levels. This study aims to systematically review the studies on the relationship between the methylation of specific cytosine-phosphate-guanine (CpG) sites and serum TG levels. This systematic review and meta-analysis study was conducted according to the PRISMA 2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) statement. A systematic literature search was conducted in Medline database (PubMed), Scopus, and Cochrane library up to end of 2020. All observational studies (cross-sectional, case-control, and cohort) were included. Studies that assessed the effect of DNA methylation of different CpG sites of ABCG1, CPT1A, and SREBF1 genes on serum TG levels were selected. The National Institutes of Health (NIH) checklist was used to assess the quality of included articles. Among 2790 articles, ten studies were included in the quantitative analysis and fourteen studies were included in the systematic review. DNA methylation of ABCG1 gene had significant positive association with TG levels (β = 0.05, 95% CI = 0.04, 0.05, P heterogeneity < 0.001). There was significant inverse association between DNA methylation of CPT1A gene and serum TG levels (β = -0.03, 95% CI = -0.03, -0.02, P heterogeneity < 0.001). DNA methylation of SREBF1 gene was positively and significantly associated with serum TG levels (β = 0.03; 95% CI = 0.02-0.04, P heterogeneity < 0.001). DNA methylation of ABCG1 and SREBF1 genes has positive association with serum TG level, whereas this association is opposite for CPT1A gene. The role of epigenetic factors should be considered in some populations with high prevalence of hypertriglyceridemia.
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Affiliation(s)
- Sadegh Mazaheri-Tehrani
- MD student, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mehri Khoshhali
- PhD of Biostatistics. Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Motahar Heidari-Beni
- Assistant Professor, Department of Nutrition, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non- Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran,
| | - Parnian Poursafa
- MSc Student, Department of Cellular and Molecular Biology, Faculty of Science, University of Isfahan, Isfahan, Iran
| | - Roya Kelishadi
- Professor, Department of Pediatrics, Child Growth and Development Research Center, Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan, Iran,
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Lee YC, Christensen JJ, Parnell LD, Smith CE, Shao J, McKeown NM, Ordovás JM, Lai CQ. Using Machine Learning to Predict Obesity Based on Genome-Wide and Epigenome-Wide Gene-Gene and Gene-Diet Interactions. Front Genet 2022; 12:783845. [PMID: 35047011 PMCID: PMC8763388 DOI: 10.3389/fgene.2021.783845] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 11/29/2021] [Indexed: 12/15/2022] Open
Abstract
Obesity is associated with many chronic diseases that impair healthy aging and is governed by genetic, epigenetic, and environmental factors and their complex interactions. This study aimed to develop a model that predicts an individual's risk of obesity by better characterizing these complex relations and interactions focusing on dietary factors. For this purpose, we conducted a combined genome-wide and epigenome-wide scan for body mass index (BMI) and up to three-way interactions among 402,793 single nucleotide polymorphisms (SNPs), 415,202 DNA methylation sites (DMSs), and 397 dietary and lifestyle factors using the generalized multifactor dimensionality reduction (GMDR) method. The training set consisted of 1,573 participants in exam 8 of the Framingham Offspring Study (FOS) cohort. After identifying genetic, epigenetic, and dietary factors that passed statistical significance, we applied machine learning (ML) algorithms to predict participants' obesity status in the test set, taken as a subset of independent samples (n = 394) from the same cohort. The quality and accuracy of prediction models were evaluated using the area under the receiver operating characteristic curve (ROC-AUC). GMDR identified 213 SNPs, 530 DMSs, and 49 dietary and lifestyle factors as significant predictors of obesity. Comparing several ML algorithms, we found that the stochastic gradient boosting model provided the best prediction accuracy for obesity with an overall accuracy of 70%, with ROC-AUC of 0.72 in test set samples. Top predictors of the best-fit model were 21 SNPs, 230 DMSs in genes such as CPT1A, ABCG1, SLC7A11, RNF145, and SREBF1, and 26 dietary factors, including processed meat, diet soda, French fries, high-fat dairy, artificial sweeteners, alcohol intake, and specific nutrients and food components, such as calcium and flavonols. In conclusion, we developed an integrated approach with ML to predict obesity using omics and dietary data. This extends our knowledge of the drivers of obesity, which can inform precision nutrition strategies for the prevention and treatment of obesity. Clinical Trial Registration: [www.ClinicalTrials.gov], the Framingham Heart Study (FHS), [NCT00005121].
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Affiliation(s)
- Yu-Chi Lee
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Jacob J. Christensen
- Department of Nutrition, Norwegian National Advisory Unit on FH, Oslo University Hospital, University of Oslo, Oslo, Norway
| | - Laurence D. Parnell
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Caren E. Smith
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
| | - Jonathan Shao
- Statistical and Bioinformatics Group, Northeast Area, USDA ARS, Beltsville, MD, United States
| | - Nicola M. McKeown
- Nutritional Epidemiology Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, United States
| | - José M. Ordovás
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
- CEI UAM + CSIC, IMDEA Food Institute, Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
| | - Chao-Qiang Lai
- USDA ARS, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, United States
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19
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Hidalgo BA, Minniefield B, Patki A, Tanner R, Bagheri M, Tiwari HK, Arnett DK, Irvin MR. A 6-CpG validated methylation risk score model for metabolic syndrome: The HyperGEN and GOLDN studies. PLoS One 2021; 16:e0259836. [PMID: 34780523 PMCID: PMC8592434 DOI: 10.1371/journal.pone.0259836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 10/27/2021] [Indexed: 12/23/2022] Open
Abstract
There has been great interest in genetic risk prediction using risk scores in recent years, however, the utility of scores developed in European populations and later applied to non-European populations has not been successful. The goal of this study was to create a methylation risk score (MRS) for metabolic syndrome (MetS), demonstrating the utility of MRS across race groups using cross-sectional data from the Hypertension Genetic Epidemiology Network (HyperGEN, N = 614 African Americans (AA)) and the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN, N = 995 European Americans (EA)). To demonstrate this, we first selected cytosine-guanine dinucleotides (CpG) sites measured on Illumina Methyl450 arrays previously reported to be significantly associated with MetS and/or component conditions in more than one race/ethnic group (CPT1A cg00574958, PHOSPHO1 cg02650017, ABCG1 cg06500161, SREBF1 cg11024682, SOCS3 cg18181703, TXNIP cg19693031). Second, we calculated the parameter estimates for the 6 CpGs in the HyperGEN data (AA) and used the beta estimates as weights to construct a MRS in HyperGEN (AA), which was validated in GOLDN (EA). We performed association analyses using logistic mixed models to test the association between the MRS and MetS, adjusting for covariates. Results showed the MRS was significantly associated with MetS in both populations. In summary, a MRS for MetS was a strong predictor for the condition across two race groups, suggesting MRS may be useful to examine metabolic disease risk or related complications across race/ethnic groups.
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Affiliation(s)
- Bertha A. Hidalgo
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Bre Minniefield
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Amit Patki
- Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Rikki Tanner
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Minoo Bagheri
- Center for Precision Medicine, Vanderbilt University Medical Center, Nashville, TN, United States of America
| | - Hemant K. Tiwari
- Department of Biostatistics, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, KY, United States of America
| | - Marguerite Ryan Irvin
- Department of Epidemiology, Ryals School of Public Health, University of Alabama at Birmingham, Birmingham, AL, United States of America
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20
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Irvin MR, Montasser ME, Kind T, Fan S, Barupal DK, Patki A, Tanner RM, Armstrong ND, Ryan KA, Claas SA, O’Connell JR, Tiwari HK, Arnett DK. Genomics of Postprandial Lipidomics in the Genetics of Lipid-Lowering Drugs and Diet Network Study. Nutrients 2021; 13:4000. [PMID: 34836252 PMCID: PMC8617762 DOI: 10.3390/nu13114000] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2021] [Revised: 11/05/2021] [Accepted: 11/08/2021] [Indexed: 12/25/2022] Open
Abstract
Postprandial lipemia (PPL) is an important risk factor for cardiovascular disease. Inter-individual variation in the dietary response to a meal is known to be influenced by genetic factors, yet genes that dictate variation in postprandial lipids are not completely characterized. Genetic studies of the plasma lipidome can help to better understand postprandial metabolism by isolating lipid molecular species which are more closely related to the genome. We measured the plasma lipidome at fasting and 6 h after a standardized high-fat meal in 668 participants from the Genetics of Lipid-Lowering Drugs and Diet Network study (GOLDN) using ultra-performance liquid chromatography coupled to (quadrupole) time-of-flight mass spectrometry. A total of 413 unique lipids were identified. Heritable and responsive lipid species were examined for association with single-nucleotide polymorphisms (SNPs) genotyped on the Affymetrix 6.0 array. The most statistically significant SNP findings were replicated in the Amish Heredity and Phenotype Intervention (HAPI) Heart Study. We further followed up findings from GOLDN with a regional analysis of cytosine-phosphate-guanine (CpGs) sites measured on the Illumina HumanMethylation450 array. A total of 132 lipids were both responsive to the meal challenge and heritable in the GOLDN study. After correction for multiple testing of 132 lipids (α = 5 × 10-8/132 = 4 × 10-10), no SNP was statistically significantly associated with any lipid response. Four SNPs in the region of a known lipid locus (fatty acid desaturase 1 and 2/FADS1 and FADS2) on chromosome 11 had p < 8.0 × 10-7 for arachidonic acid FA(20:4). Those SNPs replicated in HAPI Heart with p < 3.3 × 10-3. CpGs around the FADS1/2 region were associated with arachidonic acid and the relationship of one SNP was partially mediated by a CpG (p = 0.005). Both SNPs and CpGs from the fatty acid desaturase region on chromosome 11 contribute jointly and independently to the diet response to a high-fat meal.
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Affiliation(s)
- Marguerite R. Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (R.M.T.); (N.D.A.)
| | - May E. Montasser
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA; (M.E.M.); (K.A.R.); (J.R.O.)
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD 21201, USA
| | - Tobias Kind
- NIH West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA; (T.K.); (S.F.)
| | - Sili Fan
- NIH West Coast Metabolomics Center, UC Davis Genome Center, University of California, Davis, CA 95616, USA; (T.K.); (S.F.)
| | - Dinesh K. Barupal
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA;
| | - Amit Patki
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (A.P.); (H.K.T.)
| | - Rikki M. Tanner
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (R.M.T.); (N.D.A.)
| | - Nicole D. Armstrong
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (R.M.T.); (N.D.A.)
| | - Kathleen A. Ryan
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA; (M.E.M.); (K.A.R.); (J.R.O.)
| | - Steven A. Claas
- College of Public Health, University of Kentucky, Lexington, KY 40536, USA; (S.A.C.); (D.K.A.)
| | - Jeffrey R. O’Connell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD 21201, USA; (M.E.M.); (K.A.R.); (J.R.O.)
| | - Hemant K. Tiwari
- Department of Biostatistics, University of Alabama at Birmingham, Birmingham, AL 35294, USA; (A.P.); (H.K.T.)
| | - Donna K. Arnett
- College of Public Health, University of Kentucky, Lexington, KY 40536, USA; (S.A.C.); (D.K.A.)
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21
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Xia Y, Brewer A, Bell JT. DNA methylation signatures of incident coronary heart disease: findings from epigenome-wide association studies. Clin Epigenetics 2021; 13:186. [PMID: 34627379 PMCID: PMC8501606 DOI: 10.1186/s13148-021-01175-6] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 09/19/2021] [Indexed: 12/12/2022] Open
Abstract
Coronary heart disease (CHD) is a type of cardiovascular disease (CVD) that affects the coronary arteries, which provide oxygenated blood to the heart. It is a major cause of mortality worldwide. Various prediction methods have been developed to assess the likelihood of developing CHD, including those based on clinical features and genetic variation. Recent epigenome-wide studies have identified DNA methylation signatures associated with the development of CHD, indicating that DNA methylation may play a role in predicting future CHD. This narrative review summarises recent findings from DNA methylation studies of incident CHD (iCHD) events from epigenome-wide association studies (EWASs). The results suggest that DNA methylation signatures may identify new mechanisms involved in CHD progression and could prove a useful adjunct for the prediction of future CHD.
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Affiliation(s)
- Yujing Xia
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK
| | - Alison Brewer
- School of Cardiovascular Medicine and Sciences, James Black Centre, King's College London British Heart Foundation Centre of Excellence, 125 Coldharbour Lane, London, SE5 9NU, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, SE1 7EH, UK.
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22
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Si J, Yang S, Sun D, Yu C, Guo Y, Lin Y, Millwood IY, Walters RG, Yang L, Chen Y, Du H, Hua Y, Liu J, Chen J, Chen Z, Chen W, Lv J, Liang L, Li L. Epigenome-wide analysis of DNA methylation and coronary heart disease: a nested case-control study. eLife 2021; 10:e68671. [PMID: 34515027 PMCID: PMC8585480 DOI: 10.7554/elife.68671] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 09/12/2021] [Indexed: 02/05/2023] Open
Abstract
Background Identifying environmentally responsive genetic loci where DNA methylation is associated with coronary heart disease (CHD) may reveal novel pathways or therapeutic targets for CHD. We conducted the first prospective epigenome-wide analysis of DNA methylation in relation to incident CHD in the Asian population. Methods We did a nested case-control study comprising incident CHD cases and 1:1 matched controls who were identified from the 10 year follow-up of the China Kadoorie Biobank. Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip. We performed the single cytosine-phosphate-guanine (CpG) site association analysis and network approach to identify CHD-associated CpG sites and co-methylation gene module. Results After quality control, 982 participants (mean age 50.1 years) were retained. Methylation level at 25 CpG sites across the genome was associated with incident CHD (genome-wide false discovery rate [FDR] < 0.05 or module-specific FDR < 0.01). One SD increase in methylation level of identified CpGs was associated with differences in CHD risk, ranging from a 47 % decrease to a 118 % increase. Mediation analyses revealed 28.5 % of the excessed CHD risk associated with smoking was mediated by methylation level at the promoter region of ANKS1A gene (P for mediation effect = 0.036). Methylation level at the promoter region of SNX30 was associated with blood pressure and subsequent risk of CHD, with the mediating proportion to be 7.7 % (P = 0.003) via systolic blood pressure and 6.4 % (P = 0.006) via diastolic blood pressure. Network analysis revealed a co-methylation module associated with CHD. Conclusions We identified novel blood methylation alterations associated with incident CHD in the Asian population and provided evidence of the possible role of epigenetic regulations in the smoking- and blood pressure-related pathways to CHD risk. Funding This work was supported by National Natural Science Foundation of China (81390544 and 91846303). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (202922/Z/16/Z, 088158/Z/09/Z, 104085/Z/14/Z), grant (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, and Chinese Ministry of Science and Technology (2011BAI09B01).
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Affiliation(s)
- Jiahui Si
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public HealthBostonUnited States
| | - Songchun Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | - Yu Guo
- Chinese Academy of Medical SciencesBeijingChina
| | - Yifei Lin
- Department of Urology, West China Hospital, Sichuan UniversityChengduChina
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Yujie Hua
- NCDs Prevention and Control Department, Suzhou CDCJiangsuChina
| | - Jingchao Liu
- NCDs Prevention and Control Department, Wuzhong CDCJiangsuChina
| | - Junshi Chen
- China National Center for Food Safety Risk AssessmentBeijingChina
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane UniversityNew OrleansUnited States
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of EducationBeijingChina
- Peking University Institute of Environmental MedicineBeijingChina
| | - Liming Liang
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public HealthBostonUnited States
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
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23
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Jones AC, Irvin MR, Claas SA, Arnett DK. Lipid Phenotypes and DNA Methylation: a Review of the Literature. Curr Atheroscler Rep 2021; 23:71. [PMID: 34468868 DOI: 10.1007/s11883-021-00965-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW Epigenetic modifications via DNA methylation have previously been linked to blood lipid levels, dyslipidemias, and atherosclerosis. The purpose of this review is to discuss current literature on the role of DNA methylation on lipid traits and their associated pathologies. RECENT FINDINGS Candidate gene and epigenome-wide approaches have identified differential methylation of genes associated with lipid traits (particularly CPT1A, ABCG1, SREBF1), and novel approaches are being implemented to further characterize these relationships. Moreover, studies on environmental factors have shown that methylation variations at lipid-related genes are associated with diet and pollution exposure. Further investigation is needed to elucidate the directionality of the associations between the environment, lipid traits, and epigenome. Future studies should also seek to increase the diversity of cohorts, as European and Asian ancestry populations are the predominant study populations in the current literature.
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Affiliation(s)
- Alana C Jones
- Medical Scientist Training Program, University of Alabama-Birmingham, Birmingham, AL, USA.,Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Steven A Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA
| | - Donna K Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA.
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24
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Rohner M, Heiz R, Feldhaus S, Bornstein SR. Hepatic-Metabolite-Based Intermittent Fasting Enables a Sustained Reduction in Insulin Resistance in Type 2 Diabetes and Metabolic Syndrome. Horm Metab Res 2021; 53:529-540. [PMID: 34192792 PMCID: PMC8360708 DOI: 10.1055/a-1510-8896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Accepted: 05/12/2021] [Indexed: 11/03/2022]
Abstract
Insulin resistance is the hallmark of Type 2 Diabetes and is still an unmet medical need. Insulin resistance lies at the crossroads of non-alcoholic fatty liver disease, obesity, weight loss and exercise resistance, heart disease, stroke, depression, and brain health. Insulin resistance is purely nutrition related, with a typical molecular disease food intake pattern. The insulin resistant state is accessible by TyG as the appropriate surrogate marker, which is found to lead the personalized molecular hepatic nutrition system for highly efficient insulin resistance remission. Treating insulin resistance with a molecular nutrition-centered approach shifts the treatment paradigm of Type 2 Diabetes from management to cure. This allows remission within five months, with a high efficiency rate of 85%. With molecular intermittent fasting a very efficient treatment for prediabetes and metabolic syndrome is possible, improving the non-alcoholic fatty liver disease (NAFL) state and enabling the body to lose weight in a sustainable manner.
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Affiliation(s)
| | - Robert Heiz
- Zentrum für Komplementärmedizin AG, Uster,
Switzerland
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25
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Jhun MA, Mendelson M, Wilson R, Gondalia R, Joehanes R, Salfati E, Zhao X, Braun KVE, Do AN, Hedman ÅK, Zhang T, Carnero-Montoro E, Shen J, Bartz TM, Brody JA, Montasser ME, O'Connell JR, Yao C, Xia R, Boerwinkle E, Grove M, Guan W, Liliane P, Singmann P, Müller-Nurasyid M, Meitinger T, Gieger C, Peters A, Zhao W, Ware EB, Smith JA, Dhana K, van Meurs J, Uitterlinden A, Ikram MA, Ghanbari M, Zhi D, Gustafsson S, Lind L, Li S, Sun D, Spector TD, Chen YDI, Damcott C, Shuldiner AR, Absher DM, Horvath S, Tsao PS, Kardia S, Psaty BM, Sotoodehnia N, Bell JT, Ingelsson E, Chen W, Dehghan A, Arnett DK, Waldenberger M, Hou L, Whitsel EA, Baccarelli A, Levy D, Fornage M, Irvin MR, Assimes TL. A multi-ethnic epigenome-wide association study of leukocyte DNA methylation and blood lipids. Nat Commun 2021; 12:3987. [PMID: 34183656 PMCID: PMC8238961 DOI: 10.1038/s41467-021-23899-y] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2019] [Accepted: 05/25/2021] [Indexed: 02/06/2023] Open
Abstract
Here we examine the association between DNA methylation in circulating leukocytes and blood lipids in a multi-ethnic sample of 16,265 subjects. We identify 148, 35, and 4 novel associations among Europeans, African Americans, and Hispanics, respectively, and an additional 186 novel associations through a trans-ethnic meta-analysis. We observe a high concordance in the direction of effects across racial/ethnic groups, a high correlation of effect sizes between high-density lipoprotein and triglycerides, a modest overlap of associations with epigenome-wide association studies of other cardio-metabolic traits, and a largely non-overlap with lipid loci identified to date through genome-wide association studies. Thirty CpGs reached significance in at least 2 racial/ethnic groups including 7 that showed association with the expression of an annotated gene. CpGs annotated to CPT1A showed evidence of being influenced by triglycerides levels. DNA methylation levels of circulating leukocytes show robust and consistent association with blood lipid levels across multiple racial/ethnic groups.
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Affiliation(s)
- Min-A Jhun
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA.
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
| | - Michael Mendelson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Cardiology, Boston Children's Hospital, Boston, MA, USA
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Rahul Gondalia
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
| | - Roby Joehanes
- Hebrew SeniorLife, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Xiaoping Zhao
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | | | - Anh Nguyet Do
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Åsa K Hedman
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tao Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Elena Carnero-Montoro
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
- GENYO, Center for Genomics and Oncological Research Pfizer/University of Granada/Andalusian Regional Government, Granada, Spain
| | - Jincheng Shen
- Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Jeff R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Chen Yao
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rui Xia
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Eric Boerwinkle
- School of Public Health, University of Texas Health Science Center at Houston, Huston, TX, USA
| | - Megan Grove
- School of Public Health, University of Texas Health Science Center at Houston, Huston, TX, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Pfeiffer Liliane
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Paula Singmann
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Thomas Meitinger
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Human Genetics, Technical University Munich, Munich, Germany
| | - Christian Gieger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany
| | - Wei Zhao
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Erin B Ware
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, Ann Arbor, MI, USA
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research, Ann Arbor, MI, USA
| | - Klodian Dhana
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, USA
| | - Joyce van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Andre Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohammad Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Deugi Zhi
- School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Stefan Gustafsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Lars Lind
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Shengxu Li
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Dianjianyi Sun
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Yii-der Ida Chen
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute, and Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Coleen Damcott
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Alan R Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD, USA
- Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA
| | - Devin M Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
| | - Philip S Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
| | - Sharon Kardia
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine, and Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, UK
| | - Erik Ingelsson
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA
- Stanford Diabetes Research Center, Stanford University, Stanford, CA, USA
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Biostatistics and Epidemiology, MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Donna K Arnett
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich, Germany
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Eric A Whitsel
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC, USA
- Department of Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Myriam Fornage
- The Brown Foundation Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Themistocles L Assimes
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA.
- VA Palo Alto Healthcare System, Palo Alto, CA, USA.
- Stanford Cardiovascular Institute, Stanford University, Stanford, CA, USA.
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26
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Sun YV, Liu C, Staimez L, Ali MK, Chang H, Kondal D, Patel S, Jones D, Mohan V, Tandon N, Prabhakaran D, Quyyumi AA, Narayan KMV, Agrawal A. Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light? Wellcome Open Res 2021; 5:255. [PMID: 34136649 PMCID: PMC8176264 DOI: 10.12688/wellcomeopenres.16336.2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/11/2021] [Indexed: 12/12/2022] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes (T2DM) and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.
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Affiliation(s)
- Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.,Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, 30322, USA
| | - Chang Liu
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Lisa Staimez
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Mohammed K Ali
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA.,Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, GA, 30322, USA
| | - Howard Chang
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | | | - Shivani Patel
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Dean Jones
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, School of Medicine, Emory University, Atlanta, GA, 30322, USA
| | | | - Nikhil Tandon
- All India Institute of Medical Sciences, New Delhi, India
| | | | - Arshed A Quyyumi
- Department of Medicine, Division of Cardiology, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - K M Venkat Narayan
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, 30322, USA
| | - Anurag Agrawal
- Institute of Genomics and Integrative Biology, Council of Scientific and Industrial Research, New Delhi, India
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27
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Irvin MR, Jones AC, Claas SA, Arnett DK. DNA Methylation and Blood Pressure Phenotypes: A Review of the Literature. Am J Hypertens 2021; 34:267-273. [PMID: 33821945 DOI: 10.1093/ajh/hpab026] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Revised: 01/23/2021] [Accepted: 01/27/2021] [Indexed: 12/20/2022] Open
Abstract
Genetic studies of DNA have been unable to explain a significant portion of the variance of the estimated heritability of blood pressure (BP). Epigenetic mechanisms, particularly DNA methylation, have helped explain additional biological processes linked to BP phenotypes and diseases. Candidate gene methylation studies and genome-wide methylation studies of BP have highlighted impactful cytosine-phosphate-guanine (CpG) markers across different ethnicities. Furthermore, many of these BP-related CpG sites are also linked to metabolism-related phenotypes. Integrating epigenome-wide association study data with other layers of molecular data such as genotype data (from single nucleotide polymorphism arrays or sequencing), other epigenetic data, and/or transcriptome data can provide additional information about the significance and complexity of these relationships. Recent data suggest that epigenetic changes can be consequences rather than causes of BP variation. Finally, these data can give insight into downstream effects of long-standing high BP (due to target organ damage (TOD)). The current review provides a literature overview of epigenetic modifications in BP and TOD. Recent studies strongly support the importance of epigenetic modifications, such as DNA methylation, in BP and TOD for relevant biological insights, reliable biomarkers, and possible future therapeutics.
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Affiliation(s)
- Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Alana C Jones
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Steven A Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, Kentucky, USA
| | - Donna K Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, Lexington, Kentucky, USA
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28
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Pagiatakis C, Musolino E, Gornati R, Bernardini G, Papait R. Epigenetics of aging and disease: a brief overview. Aging Clin Exp Res 2021; 33:737-745. [PMID: 31811572 PMCID: PMC8084772 DOI: 10.1007/s40520-019-01430-0] [Citation(s) in RCA: 60] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2019] [Accepted: 11/21/2019] [Indexed: 12/17/2022]
Abstract
Aging is an important risk factor for several human diseases such as cancer, cardiovascular disease and neurodegenerative disorders, resulting from a combination of genetic and environmental factors (e.g., diet, smoking, obesity and stress), which, at molecular level, cause changes in gene expression underlying the decline of physiological function. Epigenetics, which include mechanisms regulating gene expression independently of changes to DNA sequence, regulate gene expression by modulating the structure of chromatin or by regulating the binding of transcriptional machinery to DNA. Several studies showed that an impairment of epigenetic mechanisms promotes alteration of gene expression underlying several aging-related diseases. Alteration of these mechanisms is also linked with changes of gene expression that occurs during aging processes of different tissues. In this review, we will outline the potential role of epigenetics in the onset of two age-related pathologies, cancer and cardiovascular diseases.
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29
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The Therapeutic Potential of Epigenome-Modifying Drugs in Cardiometabolic Disease. CURRENT GENETIC MEDICINE REPORTS 2021. [DOI: 10.1007/s40142-021-00198-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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30
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Lent S, Cardenas A, Rifas-Shiman SL, Perron P, Bouchard L, Liu CT, Hivert MF, Dupuis J. Detecting differentially methylated regions with multiple distinct associations. Epigenomics 2021; 13:451-464. [PMID: 33641349 DOI: 10.2217/epi-2020-0344] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
Aim: We evaluated five methods for detecting differentially methylated regions (DMRs): DMRcate, comb-p, seqlm, GlobalP and dmrff. Materials & methods: We used a simulation study and real data analysis to evaluate performance. Additionally, we evaluated the use of an ancestry-matched reference cohort to estimate correlations between CpG sites in cord blood. Results: Several methods had inflated Type I error, which increased at more stringent significant levels. In power simulations with 1-2 causal CpG sites with the same direction of effect, dmrff was consistently among the most powerful methods. Conclusion: This study illustrates the need for more thorough simulation studies when evaluating novel methods. More work must be done to develop methods with well-controlled Type I error that do not require individual-level data.
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Affiliation(s)
- Samantha Lent
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, Berkeley, CA, 94704, USA
| | - Sheryl L Rifas-Shiman
- Department of Population Medicine, Harvard Medical School & Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA
| | - Patrice Perron
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Centre de Recherche, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada
| | - Luigi Bouchard
- Centre de Recherche, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Department of Biochemistry & Functional Genomics, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean, Hôpital de Chicoutimi, Saguenay, QC, G7H 5H6, Canada
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School & Harvard Pilgrim Health Care Institute, Boston, MA, 02215, USA.,Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, J1H 5N4, Canada.,Diabetes Unit, Massachusetts General Hospital, Boston, MA, 02114, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
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31
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Juvinao-Quintero DL, Marioni RE, Ochoa-Rosales C, Russ TC, Deary IJ, van Meurs JBJ, Voortman T, Hivert MF, Sharp GC, Relton CL, Elliott HR. DNA methylation of blood cells is associated with prevalent type 2 diabetes in a meta-analysis of four European cohorts. Clin Epigenetics 2021; 13:40. [PMID: 33622391 PMCID: PMC7903628 DOI: 10.1186/s13148-021-01027-3] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2020] [Accepted: 02/11/2021] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Type 2 diabetes (T2D) is a heterogeneous disease with well-known genetic and environmental risk factors contributing to its prevalence. Epigenetic mechanisms related to changes in DNA methylation (DNAm), may also contribute to T2D risk, but larger studies are required to discover novel markers, and to confirm existing ones. RESULTS We performed a large meta-analysis of individual epigenome-wide association studies (EWAS) of prevalent T2D conducted in four European studies using peripheral blood DNAm. Analysis of differentially methylated regions (DMR) was also undertaken, based on the meta-analysis results. We found three novel CpGs associated with prevalent T2D in Europeans at cg00144180 (HDAC4), cg16765088 (near SYNM) and cg24704287 (near MIR23A) and confirmed three CpGs previously identified (mapping to TXNIP, ABCG1 and CPT1A). We also identified 77 T2D associated DMRs, most of them hypomethylated in T2D cases versus controls. In adjusted regressions among diabetic-free participants in ALSPAC, we found that all six CpGs identified in the meta-EWAS were associated with white cell-types. We estimated that these six CpGs captured 11% of the variation in T2D, which was similar to the variation explained by the model including only the common risk factors of BMI, sex, age and smoking (R2 = 10.6%). CONCLUSIONS This study identifies novel loci associated with T2D in Europeans. We also demonstrate associations of the same loci with other traits. Future studies should investigate if our findings are generalizable in non-European populations, and potential roles of these epigenetic markers in T2D etiology or in determining long term consequences of T2D.
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Affiliation(s)
- Diana L. Juvinao-Quintero
- MRC Integrative Epidemiology, Bristol Medical School, Bristol, BS8 2BN UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN UK
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA 02215 USA
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Carolina Ochoa-Rosales
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA The Netherlands
- Centro de Vida Saludable de La Universidad de Concepción, Victoria 580, Concepción, Chile
| | - Tom C. Russ
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ UK
- Edinburgh Dementia Prevention Research Group, University of Edinburgh, Edinburgh, EH16 4UX UK
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Ian J. Deary
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Joyce B. J. van Meurs
- Department of Internal Medicine, Erasmus MC University Medical Center, Rotterdam, 3000 CA The Netherlands
| | - Trudy Voortman
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, 3000 CA The Netherlands
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care, Boston, MA 02215 USA
| | - Gemma C. Sharp
- MRC Integrative Epidemiology, Bristol Medical School, Bristol, BS8 2BN UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN UK
| | - Caroline L. Relton
- MRC Integrative Epidemiology, Bristol Medical School, Bristol, BS8 2BN UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN UK
- Bristol NIHR Biomedical Research Centre, Oakfield House, Oakfield Grove, Bristol, BS8 2BN UK
| | - Hannah R. Elliott
- MRC Integrative Epidemiology, Bristol Medical School, Bristol, BS8 2BN UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, BS8 2BN UK
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32
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Gomez-Alonso MDC, Kretschmer A, Wilson R, Pfeiffer L, Karhunen V, Seppälä I, Zhang W, Mittelstraß K, Wahl S, Matias-Garcia PR, Prokisch H, Horn S, Meitinger T, Serrano-Garcia LR, Sebert S, Raitakari O, Loh M, Rathmann W, Müller-Nurasyid M, Herder C, Roden M, Hurme M, Jarvelin MR, Ala-Korpela M, Kooner JS, Peters A, Lehtimäki T, Chambers JC, Gieger C, Kettunen J, Waldenberger M. DNA methylation and lipid metabolism: an EWAS of 226 metabolic measures. Clin Epigenetics 2021; 13:7. [PMID: 33413638 PMCID: PMC7789600 DOI: 10.1186/s13148-020-00957-8] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 10/22/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The discovery of robust and trans-ethnically replicated DNA methylation markers of metabolic phenotypes, has hinted at a potential role of epigenetic mechanisms in lipid metabolism. However, DNA methylation and the lipid compositions and lipid concentrations of lipoprotein sizes have been scarcely studied. Here, we present an epigenome-wide association study (EWAS) (N = 5414 total) of mostly lipid-related metabolic measures, including a fine profiling of lipoproteins. As lipoproteins are the main players in the different stages of lipid metabolism, examination of epigenetic markers of detailed lipoprotein features might improve the diagnosis, prognosis, and treatment of metabolic disturbances. RESULTS We conducted an EWAS of leukocyte DNA methylation and 226 metabolic measurements determined by nuclear magnetic resonance spectroscopy in the population-based KORA F4 study (N = 1662) and replicated the results in the LOLIPOP, NFBC1966, and YFS cohorts (N = 3752). Follow-up analyses in the discovery cohort included investigations into gene transcripts, metabolic-measure ratios for pathway analysis, and disease endpoints. We identified 161 associations (p value < 4.7 × 10-10), covering 16 CpG sites at 11 loci and 57 metabolic measures. Identified metabolic measures were primarily medium and small lipoproteins, and fatty acids. For apolipoprotein B-containing lipoproteins, the associations mainly involved triglyceride composition and concentrations of cholesterol esters, triglycerides, free cholesterol, and phospholipids. All associations for HDL lipoproteins involved triglyceride measures only. Associated metabolic measure ratios, proxies of enzymatic activity, highlight amino acid, glucose, and lipid pathways as being potentially epigenetically implicated. Five CpG sites in four genes were associated with differential expression of transcripts in blood or adipose tissue. CpG sites in ABCG1 and PHGDH showed associations with metabolic measures, gene transcription, and metabolic measure ratios and were additionally linked to obesity or previous myocardial infarction, extending previously reported observations. CONCLUSION Our study provides evidence of a link between DNA methylation and the lipid compositions and lipid concentrations of different lipoprotein size subclasses, thus offering in-depth insights into well-known associations of DNA methylation with total serum lipids. The results support detailed profiling of lipid metabolism to improve the molecular understanding of dyslipidemia and related disease mechanisms.
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Affiliation(s)
- Monica Del C Gomez-Alonso
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Anja Kretschmer
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Liliane Pfeiffer
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Ville Karhunen
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
| | - Kirstin Mittelstraß
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Simone Wahl
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Pamela R Matias-Garcia
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Holger Prokisch
- Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany
| | - Sacha Horn
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Luis R Serrano-Garcia
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Chair of Microbiology, Technical University of Munich, Freising, Germany
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku, Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Turku, Turku University Hospital, Turku, Finland
| | - Marie Loh
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Martina Müller-Nurasyid
- Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, 55101, Mainz, Germany
| | - Christian Herder
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Michael Roden
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
- Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Mikko Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- UKMRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Mika Ala-Korpela
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
- National Heart and Lung Institute, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Pirkanmaa Hospital District, Fimlab Laboratories, and Finnish Cardiovascular Research Center, Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, London, Middlesex, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
- Imperial College Healthcare NHS Trust, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany
| | - Johannes Kettunen
- Center for Life Course Health Research, University of Oulu, Oulu University Hospital, Oulu, Finland
- Computational Medicine, Faculty of Medicine, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Ingolstaedter Landstraße 1, 85764, Neuherberg, Germany.
- Institute of Epidemiology, Helmholtz Zentrum München German Research Center for Environmental Health, Neuherberg, Germany.
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany.
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Jiang S, Cai Q, Zhang D, Fan J, Hu S, Venners SA. Effect of ABCG1 gene DNA methylations on the lipid-lowering efficacy of simvastatin. Pharmacogenomics 2020; 22:27-39. [PMID: 33356546 DOI: 10.2217/pgs-2020-0068] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: We investigated the effect of ABCG1 gene DNA methylation in the lipid-lowering efficacy of simvastatin. Materials & methods: An extreme sampling approach was used to select 211 individuals from the top and bottom 15% of adjusted lipid-lowering response residuals to simvastatin after eight consecutive weeks. DNA methylation was measured before treatment by the MethylTarget bisulfite sequencing method. Results: ABCG1_A DNA methylations were negatively associated with baseline high-density lipoprotein cholesterol (HDL-C) and the change in HDL-C after treatment. ABCG1_C methylations were also related to the change in triglyceride and HDL-C. Moreover, mean ABCG1_A and ABCG1_C methylations explain 7.2% of the ΔTC (total cholesterol) and 17.5% of the ΔHDL-C level variability, respectively. Conclusion: DNA methylations at the ABCG1 gene play significant inhibitory effects in the lipid-lowering therapy of simvastatin.
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Affiliation(s)
- Shanqun Jiang
- School of Life Sciences, Anhui University, Hefei, 230601, China.,Institute of Physical Science & Information Technology, Anhui University, Hefei, 230601, China.,Institute of Biomedicine, Anhui Medical University, Hefei, 230032, China
| | - Qianru Cai
- School of Life Sciences, Anhui University, Hefei, 230601, China
| | - Di Zhang
- School of Life Sciences, Anhui University, Hefei, 230601, China
| | - Juanlin Fan
- School of Life Sciences, Anhui University, Hefei, 230601, China
| | - Shengnan Hu
- School of Life Sciences, Anhui University, Hefei, 230601, China
| | - Scott A Venners
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC V5A1S6, Canada
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Khomtchouk BB, Tran DT, Vand KA, Might M, Gozani O, Assimes TL. Cardioinformatics: the nexus of bioinformatics and precision cardiology. Brief Bioinform 2020; 21:2031-2051. [PMID: 31802103 PMCID: PMC7947182 DOI: 10.1093/bib/bbz119] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 08/08/2019] [Accepted: 08/13/2019] [Indexed: 12/12/2022] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide, causing over 17 million deaths per year, which outpaces global cancer mortality rates. Despite these sobering statistics, most bioinformatics and computational biology research and funding to date has been concentrated predominantly on cancer research, with a relatively modest footprint in CVD. In this paper, we review the existing literary landscape and critically assess the unmet need to further develop an emerging field at the multidisciplinary interface of bioinformatics and precision cardiovascular medicine, which we refer to as 'cardioinformatics'.
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Affiliation(s)
- Bohdan B Khomtchouk
- Department of Biology, Stanford University, Stanford, CA, USA
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
- Department of Medicine, Section of Computational Biomedicine and Biomedical Data Science, University of Chicago, Chicago, IL, USA
| | - Diem-Trang Tran
- School of Computing, University of Utah, Salt Lake City, UT, USA
| | | | - Matthew Might
- Hugh Kaul Personalized Medicine Institute, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Or Gozani
- Department of Biology, Stanford University, Stanford, CA, USA
| | - Themistocles L Assimes
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Stanford, CA, USA
- VA Palo Alto Health Care System, Palo Alto, CA, USA
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35
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Lai CQ, Parnell LD, Smith CE, Guo T, Sayols-Baixeras S, Aslibekyan S, Tiwari HK, Irvin MR, Bender C, Fei D, Hidalgo B, Hopkins PN, Absher DM, Province MA, Elosua R, Arnett DK, Ordovas JM. Carbohydrate and fat intake associated with risk of metabolic diseases through epigenetics of CPT1A. Am J Clin Nutr 2020; 112:1200-1211. [PMID: 32930325 PMCID: PMC7657341 DOI: 10.1093/ajcn/nqaa233] [Citation(s) in RCA: 42] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Accepted: 07/23/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Epigenome-wide association studies identified the cg00574958 DNA methylation site at the carnitine palmitoyltransferase-1A (CPT1A) gene to be associated with reduced risk of metabolic diseases (hypertriglyceridemia, obesity, type 2 diabetes, hypertension, metabolic syndrome), but the mechanism underlying these associations is unknown. OBJECTIVES We aimed to elucidate whether carbohydrate and fat intakes modulate cg00574958 methylation and the risk of metabolic diseases. METHODS We examined associations between carbohydrate (CHO) and fat (FAT) intake, as percentages of total diet energy, and the CHO/FAT ratio with CPT1A-cg00574958, and the risk of metabolic diseases in 3 populations (Genetics of Lipid Lowering Drugs and Diet Network, n = 978; Framingham Heart Study, n = 2331; and REgistre GIroní del COR study, n = 645) while adjusting for confounding factors. To understand possible causal effects of dietary intake on the risk of metabolic diseases, we performed meta-analysis, CPT1A transcription analysis, and mediation analysis with CHO and FAT intakes as exposures and cg00574958 methylation as the mediator. RESULTS We confirmed strong associations of cg00574958 methylation with metabolic phenotypes (BMI, triglyceride, glucose) and diseases in all 3 populations. Our results showed that CHO intake and CHO/FAT ratio were positively associated with cg00574958 methylation, whereas FAT intake was negatively correlated with cg00574958 methylation. Meta-analysis further confirmed this strong correlation, with β = 58.4 ± 7.27, P = 8.98 x 10-16 for CHO intake; β = -36.4 ± 5.95, P = 9.96 x 10-10 for FAT intake; and β = 3.30 ± 0.49, P = 1.48 x 10-11 for the CHO/FAT ratio. Furthermore, CPT1A mRNA expression was negatively associated with CHO intake, and positively associated with FAT intake, and metabolic phenotypes. Mediation analysis supports the hypothesis that CHO intake induces CPT1A methylation, hence reducing the risk of metabolic diseases, whereas FAT intake inhibits CPT1A methylation, thereby increasing the risk of metabolic diseases. CONCLUSIONS Our results suggest that the proportion of total energy supplied by CHO and FAT can have a causal effect on the risk of metabolic diseases via the epigenetic status of CPT1A.Study registration at https://www.clinicaltrials.gov/: the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)-NCT01023750; and the Framingham Heart Study (FHS)-NCT00005121.
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Affiliation(s)
- Chao-Qiang Lai
- USDA Agricultural Research Service, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Laurence D Parnell
- USDA Agricultural Research Service, Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Caren E Smith
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Tao Guo
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Catalonia, Spain
- CIBER Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain
- Molecular Epidemiology, Department of Medical Sciences, Uppsala Universitet, Uppsala, Sweden
| | - Stella Aslibekyan
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Hemant K Tiwari
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Carl Bender
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - David Fei
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Bertha Hidalgo
- Department of Epidemiology, School of Public Health, University of Alabama, Birmingham, AL, USA
| | - Paul N Hopkins
- Department of Cardiovascular Genetics, University of Utah, Salt Lake City, UT, USA
| | - Devin M Absher
- Hudson Alpha Institute for Biotechnology, Huntsville, AL, USA
| | - Michael A Province
- Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Research Group, IMIM (Hospital del Mar Medical Research Institute), Barcelona, Catalonia, Spain
- CIBER Cardiovascular Diseases (CIBERCV), Barcelona, Catalonia, Spain
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY, USA
| | - Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
- IMDEA Food Institute, CEI UAM + CSIC, Madrid, Spain
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain
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36
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Shen S, Wang K, Zhi Y, Shen W, Huang L. Gypenosides improves nonalcoholic fatty liver disease induced by high-fat diet induced through regulating LPS/TLR4 signaling pathway. Cell Cycle 2020; 19:3042-3053. [PMID: 33121337 DOI: 10.1080/15384101.2020.1829800] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023] Open
Abstract
Background The contents of lipopolysaccharide (LPS) and Toll-like receptor 4 (TLR4) are significantly increased during the progression of nonalcoholic fatty liver disease (NAFLD). The study investigated the role of the LPS/TLR4 signaling pathway in improving gypenosides (Gyp) on NAFLD. Methods NAFLD model were established in rats and treated by Gyp. Pathological changes of liver tissues were observed by Hematoxylin and Eosin (HE) staining. Lipid metabolism and insulin resistance were measured. Expressions of inflammatory factors and protein of LPS/TLR4 downstream pathway were detected by qRT-PCR and Western blotting. THLE-2 cells were treated by free-fatty acid (FFA), Gyp, and LPS, and then transfected with TLR4. Next, cell viability was detected by MTT. Lipid droplet deposition and Triglyceride (TG) content were determined by Oil Red O staining and ELISA. Results Gyp protected fatty liver tissues in NAFLD model, and significantly reversed cholesterol increased by high-fat diet. Moreover, Gyp increased SOD content and decreased the contents of AST, ALT, MDA, HSI, FBG, FINS, HOMA-IR, IL-1β, and TNF-α, and promoted the expressions of TLR4, LPS, MyD88, p-IκBα, and reduced the expressions of p-p65 and IκBα in the NAFLD model. Gyp treatment significantly reduced lipid droplet deposition, increased TG content and MyD88, p-IκBα, p-p65 in FFA-induced liver cells, but LPS and TLR4 greatly reversed improvement of FFA by Gyp. Conclusion Gypenosides could improve liver function, lipid metabolism, insulin resistance, and levels of inflammatory factors in NAFLD model by regulating LPS/TLR4 signaling pathway in vitro and in vivo.
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Affiliation(s)
- Shuhua Shen
- Disease Prevention and Health Management Center, The First Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine , Hangzhou, Zhejiang Province, China
| | - Kungen Wang
- Department of Traditional Chinese Internal Medicine, The First Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine , Hangzhou, Zhejiang Province, China
| | - Yihui Zhi
- Department of Traditional Chinese Internal Medicine, The First Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine , Hangzhou, Zhejiang Province, China
| | - Wei Shen
- Center of Hospital-made Preparations, The First Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine , Hangzhou, Zhejiang Province, China
| | - Liquan Huang
- Department of Traditional Chinese Internal Medicine, The First Affiliated Hospital of Zhejiang University of Traditional Chinese Medicine , Hangzhou, Zhejiang Province, China
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Sun YV, Liu C, Staimez L, Ali MK, Chang H, Kondal D, Patel S, Jones D, Mohan V, Tandon N, Prabhakaran D, Quyyumi AA, Narayan KMV, Agrawal A. Cardiovascular disease risk and pathophysiology in South Asians: can longitudinal multi-omics shed light? Wellcome Open Res 2020; 5:255. [DOI: 10.12688/wellcomeopenres.16336.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 09/30/2020] [Indexed: 11/20/2022] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of mortality in South Asia, with rapidly increasing prevalence of hypertension, type 2 diabetes and hyperlipidemia over the last two decades. Atherosclerotic CVD (ASCVD) affects South Asians earlier in life and at lower body weights, which is not fully explained by differential burden of conventional risk factors. Heart failure (HF) is a complex clinical syndrome of heterogeneous structural phenotypes including two major clinical subtypes, HF with preserved (HFpEF) and reduced ejection fraction (HFrEF). The prevalence of HF in South Asians is also rising with other metabolic diseases, and HFpEF develops at younger age and leaner body mass index in South Asians than in Whites. Recent genome-wide association studies, epigenome-wide association studies and metabolomic studies of ASCVD and HF have identified genes, metabolites and pathways associated with CVD traits. However, these findings were mostly driven by samples of European ancestry, which may not accurately represent the CVD risk at the molecular level, and the unique risk profile of CVD in South Asians. Such bias, while formulating hypothesis-driven research studies, risks missing important causal or predictive factors unique to South Asians. Importantly, a longitudinal design of multi-omic markers can capture the life-course risk and natural history related to CVD, and partially disentangle putative causal relationship between risk factors, multi-omic markers and subclinical and clinical ASCVD and HF. In conclusion, combining high-resolution untargeted metabolomics with epigenomics of rigorous, longitudinal design will provide comprehensive unbiased molecular characterization of subclinical and clinical CVD among South Asians. A thorough understanding of CVD-associated metabolomic profiles, together with advances in epigenomics and genomics, will lead to more accurate estimates of CVD progression and stimulate new strategies for improving cardiovascular health.
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Ambrosini S, Mohammed SA, Costantino S, Paneni F. Disentangling the epigenetic landscape in cardiovascular patients: a path toward personalized medicine. Minerva Cardiol Angiol 2020; 69:331-345. [PMID: 32996305 DOI: 10.23736/s2724-5683.20.05326-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Despite significant advances in our understanding of cardiovascular disease (CVD) we are still far from having developed breakthrough strategies to combat coronary atherosclerosis and heart failure, which account for most of CV deaths worldwide. Available cardiovascular therapies have failed to show to be equally effective in all patients, suggesting that inter-individual diversity is an important factor when it comes to conceive and deliver effective personalized treatments. Genome mapping has proved useful in identifying patients who could benefit more from specific drugs depending on genetic variances; however, our genetic make-up determines only a limited part of an individual's risk profile. Recent studies have demonstrated that epigenetic changes - defined as dynamic changes of DNA and histones which do not affect DNA sequence - are key players in the pathophysiology of cardiovascular disease and may participate to delineate cardiovascular risk trajectories over the lifetime. Epigenetic modifications include changes in DNA methylation, histone modifications and non-coding RNAs and these epigenetic signals have shown to cooperate in modulating chromatin accessibility to transcription factors and gene expression. Environmental factors such as air pollution, smoking, psychosocial context, and unhealthy diet regimens have shown to significantly modify the epigenome thus leading to altered transcriptional programs and CVD phenotypes. Therefore, the integration of genetic and epigenetic information might be invaluable to build individual maps of cardiovascular risk and hence, could be employed for the design of customized diagnostic and therapeutic strategies. In the present review, we discuss the growing importance of epigenetic information and its putative implications in cardiovascular precision medicine.
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Affiliation(s)
- Samuele Ambrosini
- Center for Molecular Cardiology, University of Zürich, Zurich, Switzerland
| | - Shafeeq A Mohammed
- Center for Molecular Cardiology, University of Zürich, Zurich, Switzerland
| | - Sarah Costantino
- Center for Molecular Cardiology, University of Zürich, Zurich, Switzerland
| | - Francesco Paneni
- Center for Molecular Cardiology, University of Zürich, Zurich, Switzerland - .,Department of Cardiology, University Heart Center, University Hospital Zurich, Zurich, Switzerland.,Department of Research and Education, University Hospital Zurich, Zurich, Switzerland
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Cao J, Zhang L, Li J, Sun L, Liu S, Zhang J, Zhao H. Pubertal maturation and weight status are associated with dyslipidemia among children and adolescents in Northwest China. Sci Rep 2020; 10:16344. [PMID: 33004971 PMCID: PMC7530767 DOI: 10.1038/s41598-020-73507-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Accepted: 09/18/2020] [Indexed: 01/19/2023] Open
Abstract
Dyslipidemia is one of major risk factors for cardiovascular disease. The early detection and treatment of dyslipidemia can reduce cardiovascular disease risk. A cross-sectional study was carried out in Ningxia, China to determine the prevalence of dyslipidemia and its association with body mass index (BMI) and pubertal stage. A total of 1783 students were selected from middle schools and high schools in September 2014 using stratified random cluster sampling. Serum triglyceride (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) were measured by using MOL-300 automatic biochemical analyzer with associated kits. The prevalence of adolescents with one abnormal serum lipid component was 43.2% and was significantly different across three pubertal stages (p < 0.0001). The abnormal rates of HDL-C and TG increased as the students maturated through the early, middle, and late stages of puberty (all p < 0.0001). Similar results were obtained when separate analyses were performed for boys and girls. In linear regression analysis, BMI was positively associated with serum levels of TC, LDL-C, and TG, but inversely associated with serum levels of HDL-C after the adjustment for age, sex, and race. In multivariable logistic regression analysis, obesity was associated with an increased risk of developing high TC, while pubertal maturation was associated with an elevated risk of experiencing low HDL-C and high TG (all p < 0.05). In conclusions, dyslipidemia is common in an adolescent population of Northwest China and its prevalence rates substantially vary with weight status and pubertal stage.
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Affiliation(s)
- Juan Cao
- Department of Child and Adolescent Health, School of Public Health and Management, Ningxia Medical University, Shengli Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China
| | - Ling Zhang
- Department of Child and Adolescent Health, School of Public Health and Management, Ningxia Medical University, Shengli Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China
| | - Jing Li
- Department of Child and Adolescent Health, School of Public Health and Management, Ningxia Medical University, Shengli Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China
| | - Lijiao Sun
- Department of Child and Adolescent Health, School of Public Health and Management, Ningxia Medical University, Shengli Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China
| | - Shanghong Liu
- Department of Child and Adolescent Health, School of Public Health and Management, Ningxia Medical University, Shengli Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China
| | - Jianjun Zhang
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, 1050 Wishard Boulevard, RG5118, Indianapolis, IN, 46202, USA.
| | - Haiping Zhao
- Department of Child and Adolescent Health, School of Public Health and Management, Ningxia Medical University, Shengli Street, Yinchuan, 750004, Ningxia Hui Autonomous Region, China.
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40
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Justice AE, Chittoor G, Gondalia R, Melton PE, Lim E, Grove ML, Whitsel EA, Liu CT, Cupples LA, Fernandez-Rhodes L, Guan W, Bressler J, Fornage M, Boerwinkle E, Li Y, Demerath E, Heard-Costa N, Levy D, Stewart JD, Baccarelli A, Hou L, Conneely K, Mori TA, Beilin LJ, Huang RC, Gordon-Larsen P, Howard AG, North KE. Methylome-wide association study of central adiposity implicates genes involved in immune and endocrine systems. Epigenomics 2020; 12:1483-1499. [PMID: 32901515 PMCID: PMC7923253 DOI: 10.2217/epi-2019-0276] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 05/22/2020] [Indexed: 12/14/2022] Open
Abstract
Aim: We conducted a methylome-wide association study to examine associations between DNA methylation in whole blood and central adiposity and body fat distribution, measured as waist circumference, waist-to-hip ratio and waist-to-height ratio adjusted for body mass index, in 2684 African-American adults in the Atherosclerosis Risk in Communities study. Materials & methods: We validated significantly associated cytosine-phosphate-guanine methylation sites (CpGs) among adults using the Women's Health Initiative and Framingham Heart Study participants (combined n = 5743) and generalized associations in adolescents from The Raine Study (n = 820). Results & conclusion: We identified 11 CpGs that were robustly associated with one or more central adiposity trait in adults and two in adolescents, including CpG site associations near TXNIP, ADCY7, SREBF1 and RAP1GAP2 that had not previously been associated with obesity-related traits.
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Affiliation(s)
- Anne E Justice
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | - Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Phillip E Melton
- School of Biomedical Science, Faculty of Health & Medical Sciences, The University of Western Australia, Perth, WA 6000, Australia
- School of Pharmacy & Biomedical Sciences, Faculty of Health Sciences, Curtin University, MRF Building, Perth, WA 6000, Australia
- Menzies Institute for Medical Research, College of Health & Medicine, University of Tasmania, Hobart, TA, 7000 Australia
| | - Elise Lim
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA, 01701, USA
| | - Lindsay Fernandez-Rhodes
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA 16802, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Myriam Fornage
- Center for Human Genetics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yun Li
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Ellen Demerath
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Dan Levy
- Population sciences branch, NHLBI Framingham Heart Study, Framingham, MA 01702, USA
- Department of Medicine, Boston University, Boston, MA 02118, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Andrea Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences & Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Karen Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Trevor A Mori
- Medical School, University of Western Australia, Perth, Australia
| | | | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
| | - Annie Green Howard
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
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Ouidir M, Zeng X, Workalemahu T, Shrestha D, Grantz KL, Mendola P, Zhang C, Tekola-Ayele F. Early pregnancy dyslipidemia is associated with placental DNA methylation at loci relevant for cardiometabolic diseases. Epigenomics 2020; 12:921-934. [PMID: 32677467 PMCID: PMC7466909 DOI: 10.2217/epi-2019-0293] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
Aim: To identify placental DNA methylation changes that are associated with early pregnancy maternal dyslipidemia. Materials & methods: We analyzed placental genome-wide DNA methylation (n = 262). Genes annotating differentially methylated CpGs were evaluated for gene expression in placenta (n = 64). Results: We found 11 novel significant differentially methylated CpGs associated with high total cholesterol, low-density lipoprotein cholesterol and triglycerides, and low high-density lipoprotein cholesterol. High triglycerides were associated with decreased methylation of cg02785814 (ALX4) and decreased expression of ALX4 in placenta. Genes annotating the differentially methylated CpGs play key roles in lipid metabolism and were enriched in dyslipidemia pathways. Functional annotation found cis-methylation quantitative trait loci for genetic loci in ALX4 and EXT2. Conclusion: Our findings lend novel insights into potential placental epigenetic mechanisms linked with maternal dyslipidemia. Trial Registration: ClinicalTrials.gov, NCT00912132.
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Affiliation(s)
- Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Xuehuo Zeng
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Katherine L. Grantz
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Pauline Mendola
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Cuilin Zhang
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
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Murphy PJ, Guo J, Jenkins TG, James ER, Hoidal JR, Huecksteadt T, Broberg DS, Hotaling JM, Alonso DF, Carrell DT, Cairns BR, Aston KI. NRF2 loss recapitulates heritable impacts of paternal cigarette smoke exposure. PLoS Genet 2020; 16:e1008756. [PMID: 32520939 PMCID: PMC7307791 DOI: 10.1371/journal.pgen.1008756] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Revised: 06/22/2020] [Accepted: 04/03/2020] [Indexed: 12/16/2022] Open
Abstract
Paternal cigarette smoke (CS) exposure is associated with increased risk of behavioral disorders and cancer in offspring, but the mechanism has not been identified. Here we use mouse models to investigate mechanisms and impacts of paternal CS exposure. We demonstrate that CS exposure induces sperm DNAme changes that are partially corrected within 28 days of removal from CS exposure. Additionally, paternal smoking is associated with changes in prefrontal cortex DNAme and gene expression patterns in offspring. Remarkably, the epigenetic and transcriptional effects of CS exposure that we observed in wild type mice are partially recapitulated in Nrf2-/- mice and their offspring, independent of smoking status. Nrf2 is a central regulator of antioxidant gene transcription, and mice lacking Nrf2 consequently display elevated oxidative stress, suggesting that oxidative stress may underlie CS-induced heritable epigenetic changes. Importantly, paternal sperm DNAme changes do not overlap with DNAme changes measured in offspring prefrontal cortex, indicating that the observed DNAme changes in sperm are not directly inherited. Additionally, the changes in sperm DNAme associated with CS exposure were not observed in sperm of unexposed offspring, suggesting the effects are likely not maintained across multiple generations.
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Affiliation(s)
- Patrick J. Murphy
- Department of Biomedical Genetics, Wilmot Cancer Institute, University of Rochester Medical Center, Rochester, New York, United States of America
- Howard Hughes Medical Institute, Department of Oncological Sciences and Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Jingtao Guo
- Howard Hughes Medical Institute, Department of Oncological Sciences and Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Timothy G. Jenkins
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Emma R. James
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
- Department of Obstetrics and Gynecology, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - John R. Hoidal
- Department of Internal Medicine, University of Utah School of Medicine and Salt Lake VA Medical Center, Salt Lake City, Utah, United States of America
| | - Thomas Huecksteadt
- Department of Internal Medicine, University of Utah School of Medicine and Salt Lake VA Medical Center, Salt Lake City, Utah, United States of America
| | - Dallin S. Broberg
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - James M. Hotaling
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - David F. Alonso
- Department of Psychology, University of Utah, Salt Lake City, Utah, United States of America
| | - Douglas T. Carrell
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
- Department of Obstetrics and Gynecology, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
- Department of Genetics, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Bradley R. Cairns
- Howard Hughes Medical Institute, Department of Oncological Sciences and Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
| | - Kenneth I. Aston
- Andrology and IVF Laboratories, Department of Surgery, University of Utah School of Medicine, Salt Lake City, Utah, United States of America
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Thibord F, Munsch G, Perret C, Suchon P, Roux M, Ibrahim-Kosta M, Goumidi L, Deleuze JF, Morange PE, Trégouët DA. Bayesian network analysis of plasma microRNA sequencing data in patients with venous thrombosis. Eur Heart J Suppl 2020; 22:C34-C45. [PMID: 32368197 PMCID: PMC7189740 DOI: 10.1093/eurheartj/suaa008] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
MicroRNAs (miRNAs) are small regulatory RNAs participating to several biological processes and known to be involved in various pathologies. Measurable in body fluids, miRNAs have been proposed to serve as efficient biomarkers for diseases and/or associated traits. Here, we performed a next-generation-sequencing based profiling of plasma miRNAs in 344 patients with venous thrombosis (VT) and assessed the association of plasma miRNA levels with several haemostatic traits and the risk of VT recurrence. Among the most significant findings, we detected an association between hsa-miR-199b-3p and haematocrit levels (P = 0.0016), these two markers having both been independently reported to associate with VT risk. We also observed suggestive evidence for association of hsa-miR-370-3p (P = 0.019), hsa-miR-27b-3p (P = 0.016) and hsa-miR-222-3p (P = 0.049) with VT recurrence, the observations at the latter two miRNAs confirming the recent findings of Wang et al. Besides, by conducting Genome-Wide Association Studies on miRNA levels and meta-analyzing our results with some publicly available, we identified 21 new associations of single nucleotide polymorphisms with plasma miRNA levels at the statistical significance threshold of P < 5 × 10-8, some of these associations pertaining to thrombosis associated mechanisms. In conclusion, this study provides novel data about the impact of miRNAs' variability in haemostasis and new arguments supporting the association of few miRNAs with the risk of recurrence in patients with venous thrombosis.
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Affiliation(s)
- Florian Thibord
- Institut National pour la Santé et la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR_S) 1219, Bordeaux Population Health Research Center, University of Bordeaux, 146 rue Léo Saignat, Bordeaux 33076, France
- Pierre Louis Doctoral School of Public Health, Sorbonne-Université, 15 rue de l’école de médecine, Paris 75006, France
| | - Gaëlle Munsch
- Institut National pour la Santé et la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR_S) 1219, Bordeaux Population Health Research Center, University of Bordeaux, 146 rue Léo Saignat, Bordeaux 33076, France
| | - Claire Perret
- Sorbonne Universités, Université Pierre et Marie Curie (UPMC Univ Paris 06), INSERM UMR_S 1166, 91 Boulevard de l’Hôpital, Paris 75013, France
| | - Pierre Suchon
- Laboratory of Haematology, La Timone Hospital, 278 rue Saint Pierre, Marseille 13385, France
| | - Maguelonne Roux
- Sorbonne Universités, Université Pierre et Marie Curie (UPMC Univ Paris 06), INSERM UMR_S 1166, 91 Boulevard de l’Hôpital, Paris 75013, France
| | - Manal Ibrahim-Kosta
- Laboratory of Haematology, La Timone Hospital, 278 rue Saint Pierre, Marseille 13385, France
- INSERM UMR_S 1062, Nutrition Obesity and Risk of Thrombosis, Center for CardioVascular and Nutrition research (C2VN), Aix-Marseille University, 278 rue Saint Pierre, Marseille 13385, France
| | - Louisa Goumidi
- INSERM UMR_S 1062, Nutrition Obesity and Risk of Thrombosis, Center for CardioVascular and Nutrition research (C2VN), Aix-Marseille University, 278 rue Saint Pierre, Marseille 13385, France
| | - Jean-François Deleuze
- Centre National de Recherche en Génomique Humaine, Direction de la Recherche Fondamentale, CEA, 2 rue Gaston Crémieux, Evry 91057, France
- CEPH, Fondation Jean Dausset, 27 rue Juliette Dodu, Paris 75010, France
| | - Pierre-Emmanuel Morange
- Laboratory of Haematology, La Timone Hospital, 278 rue Saint Pierre, Marseille 13385, France
- INSERM UMR_S 1062, Nutrition Obesity and Risk of Thrombosis, Center for CardioVascular and Nutrition research (C2VN), Aix-Marseille University, 278 rue Saint Pierre, Marseille 13385, France
| | - David-Alexandre Trégouët
- Institut National pour la Santé et la Recherche Médicale (INSERM), Unité Mixte de Recherche en Santé (UMR_S) 1219, Bordeaux Population Health Research Center, University of Bordeaux, 146 rue Léo Saignat, Bordeaux 33076, France
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44
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Dimauro I, Paronetto MP, Caporossi D. Exercise, redox homeostasis and the epigenetic landscape. Redox Biol 2020; 35:101477. [PMID: 32127290 PMCID: PMC7284912 DOI: 10.1016/j.redox.2020.101477] [Citation(s) in RCA: 36] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 02/12/2020] [Accepted: 02/23/2020] [Indexed: 02/07/2023] Open
Abstract
Physical exercise represents one of the strongest physiological stimuli capable to induce functional and structural modifications in all biological systems. Indeed, beside the traditional genetic mechanisms, physical exercise can modulate gene expression through epigenetic modifications, namely DNA methylation, post-translational histone modification and non-coding RNA transcripts. Initially considered as merely damaging molecules, it is now well recognized that both reactive oxygen (ROS) and nitrogen species (RNS) produced under voluntary exercise play an important role as regulatory mediators in signaling processes. While robust scientific evidences highlight the role of exercise-associated redox modifications in modulating gene expression through the genetic machinery, the understanding of their specific impact on epigenomic profile is still at an early stage. This review will provide an overview of the role of ROS and RNS in modulating the epigenetic landscape in the context of exercise-related adaptations. Physical exercise can modulate gene expression through epigenetic modifications. Epigenetic regulation of ROS/RNS generating, sensing and neutralizing enzymes can impact the cellular levels of ROS and RNS. ROS might act as modulators of epigenetic machinery, interfering with DNA methylation, hPTMs and ncRNAs expression. Redox homeostasis might hold a relevant role in the epigenetic landscape modulating exercise-related adaptations.
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Affiliation(s)
- Ivan Dimauro
- Unit of Biology and Genetics of Movement, Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Piazza Lauro de Bosis 15, 00135, Rome, Italy
| | - Maria Paola Paronetto
- Unit of Biology and Genetics of Movement, Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Piazza Lauro de Bosis 15, 00135, Rome, Italy; Laboratory of Cellular and Molecular Neurobiology, IRCCS Fondazione Santa Lucia, Via Del Fosso di Fiorano, Rome, Italy
| | - Daniela Caporossi
- Unit of Biology and Genetics of Movement, Department of Movement, Human and Health Sciences, University of Rome Foro Italico, Piazza Lauro de Bosis 15, 00135, Rome, Italy.
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45
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Westerman K, Sebastiani P, Jacques P, Liu S, DeMeo D, Ordovás JM. DNA methylation modules associate with incident cardiovascular disease and cumulative risk factor exposure. Clin Epigenetics 2019; 11:142. [PMID: 31615550 PMCID: PMC6792327 DOI: 10.1186/s13148-019-0705-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Accepted: 07/12/2019] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Epigenome-wide association studies using DNA methylation have the potential to uncover novel biomarkers and mechanisms of cardiovascular disease (CVD) risk. However, the direction of causation for these associations is not always clear, and investigations to-date have often failed to replicate at the level of individual loci. METHODS Here, we undertook module- and region-based DNA methylation analyses of incident CVD in the Women's Health Initiative (WHI) and Framingham Heart Study Offspring Cohort (FHS) in order to find more robust epigenetic biomarkers for cardiovascular risk. We applied weighted gene correlation network analysis (WGCNA) and the Comb-p algorithm to find methylation modules and regions associated with incident CVD in the WHI dataset. RESULTS We discovered two modules whose activation correlated with CVD risk and replicated across cohorts. One of these modules was enriched for development-related processes and overlaps strongly with epigenetic aging sites. For the other, we showed preliminary evidence for monocyte-specific effects and statistical links to cumulative exposure to traditional cardiovascular risk factors. Additionally, we found three regions (associated with the genes SLC9A1, SLC1A5, and TNRC6C) whose methylation associates with CVD risk. CONCLUSIONS In sum, we present several epigenetic associations with incident CVD which reveal disease mechanisms related to development and monocyte biology. Furthermore, we show that epigenetic modules may act as a molecular readout of cumulative cardiovascular risk factor exposure, with implications for the improvement of clinical risk prediction.
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Affiliation(s)
- Kenneth Westerman
- JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Paul Jacques
- JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Simin Liu
- Department of Epidemiology, Brown University, Providence, RI, USA
| | - Dawn DeMeo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - José M Ordovás
- JM-USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA.
- IMDEA Alimentación, CEI, UAM, Madrid, Spain.
- Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
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46
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Sun D, Zhang T, Su S, Hao G, Chen T, Li QZ, Bazzano L, He J, Wang X, Li S, Chen W. Body Mass Index Drives Changes in DNA Methylation: A Longitudinal Study. Circ Res 2019; 125:824-833. [PMID: 31510868 DOI: 10.1161/circresaha.119.315397] [Citation(s) in RCA: 43] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
RATIONALE Previous EWASs (Epigenome-Wide Association Studies) suggest that obesity may be the cause, not a consequence, of changes in DNA methylation (DNAm). However, longitudinal observations are lacking. OBJECTIVE To identify 5'-cytosine-phosphate-guanine-3' in DNA (CpG) sites associated with body mass index (BMI) and examine the temporal relationship between dynamic changes in DNAm and BMI in a longitudinal cohort. METHODS AND RESULTS Race-specific EWASs were performed in 995 whites and 490 blacks from the Bogalusa Heart Study. Suggestive CpG sites were further replicated in 252 whites and 228 blacks from the Georgia Stress and Heart Study. Cross-lagged panel analysis was used to examine the temporal relationship between DNAm and BMI in 439 whites and 201 blacks who were examined twice 6.2 years apart. In discovery and replication samples, 349 CpG sites (266 novel) in whites and 36 (21 novel) in blacks were identified to be robustly associated with BMI, with 8 (1 novel) CpG sites overlapping between the 2 races. Cross-lagged panel analyses showed significant unidirectional paths (PFDR <0.05) from baseline BMI to follow-up DNAm at 18 CpG sites in whites and 7 in blacks; no CpG sites showed significant paths from DNAm at baseline to BMI at follow-up. Baseline BMI was associated with a DNAm score (calculated from DNAm levels at the associated CpG sites) at follow-up (P<0.001 both in blacks and in whites). CONCLUSIONS The findings provide strong evidence that obesity is the cause, not a consequence, of changes in DNAm over time.
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Affiliation(s)
- Dianjianyi Sun
- From the Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China (D.S.).,Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Tao Zhang
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.).,Department of Biostatistics, School of Public Health, Shandong University, Jinan, China (T.Z.)
| | - Shaoyong Su
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Guang Hao
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Tao Chen
- Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX (T.C., Z.L.)
| | - Quan-Zhen Li
- Microarray Core Facility, University of Texas Southwestern Medical Center, Dallas, TX (T.C., Z.L.)
| | - Lydia Bazzano
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Jiang He
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
| | - Xiaoling Wang
- Georgia Prevention Institute, Department of Population Health Sciences, Medical College of Georgia, Augusta University (S.S., G.H., X.W)
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Hospitals and Clinics of Minnesota, Minneapolis (S.L.)
| | - Wei Chen
- Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA (D.S., T.Z., L.B., J.H., W.C.)
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47
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Agha G, Mendelson MM, Ward-Caviness CK, Joehanes R, Huan T, Gondalia R, Salfati E, Brody JA, Fiorito G, Bressler J, Chen BH, Ligthart S, Guarrera S, Colicino E, Just AC, Wahl S, Gieger C, Vandiver AR, Tanaka T, Hernandez DG, Pilling LC, Singleton AB, Sacerdote C, Krogh V, Panico S, Tumino R, Li Y, Zhang G, Stewart JD, Floyd JS, Wiggins KL, Rotter JI, Multhaup M, Bakulski K, Horvath S, Tsao PS, Absher DM, Vokonas P, Hirschhorn J, Fallin MD, Liu C, Bandinelli S, Boerwinkle E, Dehghan A, Schwartz JD, Psaty BM, Feinberg AP, Hou L, Ferrucci L, Sotoodehnia N, Matullo G, Peters A, Fornage M, Assimes TL, Whitsel EA, Levy D, Baccarelli AA. Blood Leukocyte DNA Methylation Predicts Risk of Future Myocardial Infarction and Coronary Heart Disease. Circulation 2019; 140:645-657. [PMID: 31424985 PMCID: PMC6812683 DOI: 10.1161/circulationaha.118.039357] [Citation(s) in RCA: 127] [Impact Index Per Article: 25.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Accepted: 07/17/2019] [Indexed: 01/08/2023]
Abstract
BACKGROUND DNA methylation is implicated in coronary heart disease (CHD), but current evidence is based on small, cross-sectional studies. We examined blood DNA methylation in relation to incident CHD across multiple prospective cohorts. METHODS Nine population-based cohorts from the United States and Europe profiled epigenome-wide blood leukocyte DNA methylation using the Illumina Infinium 450k microarray, and prospectively ascertained CHD events including coronary insufficiency/unstable angina, recognized myocardial infarction, coronary revascularization, and coronary death. Cohorts conducted race-specific analyses adjusted for age, sex, smoking, education, body mass index, blood cell type proportions, and technical variables. We conducted fixed-effect meta-analyses across cohorts. RESULTS Among 11 461 individuals (mean age 64 years, 67% women, 35% African American) free of CHD at baseline, 1895 developed CHD during a mean follow-up of 11.2 years. Methylation levels at 52 CpG (cytosine-phosphate-guanine) sites were associated with incident CHD or myocardial infarction (false discovery rate<0.05). These CpGs map to genes with key roles in calcium regulation (ATP2B2, CASR, GUCA1B, HPCAL1), and genes identified in genome- and epigenome-wide studies of serum calcium (CASR), serum calcium-related risk of CHD (CASR), coronary artery calcified plaque (PTPRN2), and kidney function (CDH23, HPCAL1), among others. Mendelian randomization analyses supported a causal effect of DNA methylation on incident CHD; these CpGs map to active regulatory regions proximal to long non-coding RNA transcripts. CONCLUSION Methylation of blood-derived DNA is associated with risk of future CHD across diverse populations and may serve as an informative tool for gaining further insight on the development of CHD.
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Affiliation(s)
- Golareh Agha
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, NY, NY 10032, USA
| | - Michael M. Mendelson
- Population Sciences Branch, National Heart, Lung, and Blood Institute, NIH, Bethesda, MD 20892, USA; Framingham Heart Study, Framingham, MA 01702, USA; Department of Cardiology, Boston Children’s Hospital, Boston, MA 02115, USA
| | - Cavin K. Ward-Caviness
- National Health and Environmental Effects Research Laboratory, Environmental Public Health Division, Chapel Hill NC 27514, USA; Institute of Epidemiology II, Helmholtz Institute, Ingolstaedter Landstrasse 1, Neuherberg, Germany 85764
| | - Roby Joehanes
- National Heart, Lung and Blood Institute, Bethesda, MD 20824-0105, USA; Hebrew SeniorLife, Harvard Medical School, Boston, MA 02115, USA
| | - TianXiao Huan
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD 20892, USA
| | - Rahul Gondalia
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Elias Salfati
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Jennifer A. Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Giovanni Fiorito
- Italian Institute for Genomic Medicine (IIGM/HuGeF) and Department of Medical Sciences, University of Turin, Turin, Italy
| | - Jan Bressler
- Human Genetics Center, School of Public Health, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Brian H. Chen
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21250, USA
| | - Symen Ligthart
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands
| | - Simonetta Guarrera
- Italian Institute for Genomic Medicine (IIGM/HuGeF) and Department of Medical Sciences, University of Turin, Turin, Italy
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Allan C. Just
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Simone Wahl
- Research Unit Molecualr Epidemiology, Helmholtz Zentrum München, 1 InglastaedterLandstrasse 1 85764, München, Germany
| | - Christian Gieger
- Research Unit Molecualr Epidemiology, Helmholtz Zentrum München, 1 InglastaedterLandstrasse 1 85764, München, Germany
| | - Amy R. Vandiver
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21250, USA
| | - Dena G. Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Luke C. Pilling
- Epidemiology and Public Health Group, University of Exeter Medical School, Barrack Road, Exeter, EX2 5DW, UK
| | - Andrew B. Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20892, USA
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza University-Hospital and Center for Cancer Prevention (CPO), Turin, Italy
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Rosario Tumino
- Cancer Registry And Histopathology Department, “Civic- M.P. Arezzo2 Hospital, Asp Ragusa, Italy
| | - Yun Li
- Department of Genetics, Department of Biostatistics, Department of Computer Science, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Guosheng Zhang
- Curriculum in Bioinformatics and Computational Biology, and Department of Genetics, and Department of Statistics, University of North Carolina, Chapel Hill, NC 27514, USA
| | - James D. Stewart
- Carolina Population Center and Department of Epidemiology, University of North Carolina at Chapel Hill, NC 27514, USA
| | - James S Floyd
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Kerri L. Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Michael Multhaup
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Kelly Bakulski
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Steven Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Philip S. Tsao
- Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Pantel Vokonas
- VA Normative Aging Study, VA Boston Healthcare System, Department of Medicine, Boston University School of Medicine, Boston, MA 02118, USA
| | - Joel Hirschhorn
- Department of Medicine, Division of Endocrinology, Boston Children’s Hospital, Boston, MA 02115, USA; Departments of Medicine and Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - M Daniele Fallin
- Department of Mental Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | | | - Eric Boerwinkle
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, Texas, USA
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, MRC–PHE Centre for Environment & Health, School of 346 Public Health, Imperial College London, UK
| | - Joel D. Schwartz
- Department of Epidemiology, and Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA 98195, USA; Kaier Permanente Washington Health Research Institute, Seattle, WA 98195, USA
| | - Andrew P. Feinberg
- Departments of Medicine, Biomedical Engineering and Mental Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Lifang Hou
- Center for Population Epigenetics, Robert H. Lurie Comprehensive Cancer Center and Department of Preventive Medicine, Northwestern University , Feinberg School of Medicine, Chicago, IL 60611, USA
| | - Luigi Ferrucci
- Intramural Research Program, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
| | - Nona Sotoodehnia
- Division of Cardiology, Departments of Medicine and Epidemiology, Cardiovascular Health Research Unit, University of Washington, Seattle, WA 98101, USA
| | - Giuseppe Matullo
- Italian Institute for Genomic Medicine (IIGM/HuGeF) and Department of Medical Sciences, University of Turin, Turin, Italy
| | - Annette Peters
- Helmholtz Zentrum München, Institute of Epidemiology, Neuherberg, Germany; German Research Center for Cardiovascular Disease (DzHK e.V. - partner site Munich), Munich, Germany; Ludwig-Maximilians University, Institute for Biometry, Medical Information Science and Epidemiology, Munich, Germany
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine McGovern Medical School, and Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Themistocles L. Assimes
- Department of Medicine (Cardiovascular Medicine), and Department of Health Research & Policy, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Eric A. Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, and Department of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27514, USA
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA 01702, USA; Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, NY, NY 10032, USA
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48
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Huan T, Mendelson M, Joehanes R, Yao C, Liu C, Song C, Bhattacharya A, Rong J, Tanriverdi K, Keefe J, Murabito JM, Courchesne P, Larson MG, Freedman JE, Levy D. Epigenome-wide association study of DNA methylation and microRNA expression highlights novel pathways for human complex traits. Epigenetics 2019; 15:183-198. [PMID: 31282290 DOI: 10.1080/15592294.2019.1640547] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
DNA methylation (DNAm) and microRNAs (miRNAs) have been implicated in a wide-range of human diseases. While often studied in isolation, DNAm and miRNAs are not independent. We analyzed associations of expression of 283 miRNAs with DNAm at >400K CpG sites in whole blood obtained from 3565 individuals and identified 227 CpGs at which differential methylation was associated with the expression of 40 nearby miRNAs (cis-miR-eQTMs) at FDR<0.01, including 91 independent CpG sites at r2 < 0.2. cis-miR-eQTMs were enriched for CpGs in promoter and polycomb-repressed state regions, and 60% were inversely associated with miRNA expression. Bidirectional Mendelian randomization (MR) analysis further identified 58 cis-miR-eQTMCpG-miRNA pairs where DNAm changes appeared to drive miRNA expression changes and opposite directional effects were unlikely. Integration of genetic variants in joint analyses revealed an average partial between cis-miR-eQTM CpGs and miRNAs of 2% after conditioning on site-specific genetic variation, suggesting that DNAm is an important epigenetic regulator of miRNA expression. Finally, two-step MR analysis was performed to identify putatively causal CpGs driving miRNA expression in relation to human complex traits. We found that an imprinted region on 14q32 that was previously identified in relation to age at menarche is enriched with cis-miR-eQTMs. Nine CpGs and three miRNAs at this locus tested causal for age at menarche, reflecting novel epigenetic-driven molecular pathways underlying this complex trait. Our study sheds light on the joint genetic and epigenetic regulation of miRNA expression and provides insights into the relations of miRNAs to their targets and to complex phenotypes.
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Affiliation(s)
- Tianxiao Huan
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Michael Mendelson
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Roby Joehanes
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Chen Yao
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Chunyu Liu
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA.,Department of Biostatistics, Boston University School of Public Health, Boston University, Boston, MA, USA
| | - Ci Song
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Anindya Bhattacharya
- Department of Computer Science and Engineering, University of California, San Diego, CA, USA
| | - Jian Rong
- Department of Mathematics and Statistics, Boston University, Boston, MA, USA
| | - Kahraman Tanriverdi
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Joshua Keefe
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Joanne M Murabito
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Paul Courchesne
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
| | - Martin G Larson
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,Department of Mathematics and Statistics, Boston University, Boston, MA, USA
| | - Jane E Freedman
- Department of Medicine, University of Massachusetts Medical School, Worcester, MA, USA
| | - Daniel Levy
- The National Heart, Lung, and Blood Institute, Boston University's Framingham Heart Study, Framingham, MA, USA.,The Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, Bethesda, MD, USA
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49
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He XW, Zhao Y, Shi YH, Zhao R, Liu YS, Hu Y, Zhuang MT, Wu YL, Li GF, Yin JW, Cui GH, Liu JR. DNA Methylation Analysis Identifies Differentially Methylated Sites Associated with Early-Onset Intracranial Atherosclerotic Stenosis. J Atheroscler Thromb 2019; 27:71-99. [PMID: 31142690 PMCID: PMC6976716 DOI: 10.5551/jat.47704] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Aim: Studies have suggested that genetic and environmental factors do not account for all risks and mechanisms of intracranial atherosclerotic stenosis (ICAS). DNA methylation may play a role in the progression of ICAS. Methods: DNA methylation profiles of peripheral blood leucocytes from 7 patients with early-onset ICAS and 7 perfectly matched controls were interrogated for the first time using the Illumina Infinium Human MethylationEPIC BeadChip. Afterward, functional analysis for differentially methylated genes was conducted. In addition, pyrosequencing verification was performed in an independent cohort comprising 21 patients with earlyonset ICAS and 21 age- and gender-matched controls. Results: A total of 318 cytosine-phosphate-guanine sites were found to be differentially methylated based on the established standards. Functional analysis annotated differentially methylated sites to atherosclerosis-related processes and pathways, such as the negative regulation of hydrolase activity (GO 0051346), type II diabetes mellitus (KEGG hsa04930), and the insulin signaling pathway (KEGG hsa04910). In addition, a differentially methylated site was also validated, cg22443212 in gene Rnf213, which showed significant hypermethylation in patients with early-onset ICAS compared with controls 59.56% (49.77%, 88.55%) vs. 44.65% (25.07%, 53.21%), respectively; P = 0.010). Receiver operating characteristic curve analysis showed that the area under the curve value of cg22443212 was 0.744 (95% confidence interval, 0.586–0.866; P = 0.002). Conclusions: We revealed that altered DNA methylation may play a role in the occurrence and development of ICAS. These results provided new epigenetic insights into ICAS.
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Affiliation(s)
- Xin-Wei He
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Ying Zhao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Yan-Hui Shi
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Rong Zhao
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Yi-Sheng Liu
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Yue Hu
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Mei-Ting Zhuang
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Yi-Lan Wu
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Ge-Fei Li
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Jia-Wen Yin
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Guo-Hong Cui
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
| | - Jian-Ren Liu
- Department of Neurology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.,Clinical Research Center, Shanghai Jiao Tong University School of Medicine
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50
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Liu P, Liu Y, Liu H, Pan X, Li Y, Usa K, Mishra MK, Nie J, Liang M. Role of DNA De Novo (De)Methylation in the Kidney in Salt-Induced Hypertension. Hypertension 2019; 72:1160-1171. [PMID: 30354815 DOI: 10.1161/hypertensionaha.118.11650] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Numerous adult diseases involving tissues consisting primarily of nondividing cells are associated with changes in DNA methylation. It suggests a pathophysiological role for de novo methylation or demethylation of DNA, which is catalyzed by DNA methyltransferase 3 and ten-eleven translocases. However, the contribution of DNA de novo (de)methylation to these diseases remains almost completely unproven. Broad changes in DNA methylation occurred within days in the renal outer medulla of Dahl SS rats fed a high-salt diet, a classic model of hypertension. Intrarenal administration of anti-DNA methyltransferase 3a/ten-eleven translocase 3 GapmeRs attenuated high salt-induced hypertension in SS rats. The high-salt diet induced differential expression of 1712 genes in the renal outer medulla. Remarkably, the differential expression of 76% of these genes was prevented by anti-DNA methyltransferase 3a/ten-eleven translocase 3 GapmeRs. The genes differentially expressed in response to the GapmeRs were involved in the regulation of metabolism and inflammation and were significantly enriched for genes showing differential methylation in response to the GapmeRs. These data indicate a significant role of DNA de novo (de)methylation in the kidney in the development of hypertension in SS rats. The findings should help to shift the paradigm of DNA methylation research in diseases involving nondividing cells from correlative analysis to functional and mechanistic studies.
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Affiliation(s)
- Pengyuan Liu
- From the Sir Run Run Shaw Hospital, Institute of Translational Medicine, Zhejiang University, China (P.L.).,Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.)
| | - Yong Liu
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.)
| | - Han Liu
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China (H.L., J.N., M.L.)
| | - Xiaoqing Pan
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.)
| | - Yingchuan Li
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.).,Department of Critical Care Medicine, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, China (Y. Li)
| | - Kristie Usa
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.)
| | - Manoj K Mishra
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.)
| | - Jing Nie
- Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China (H.L., J.N., M.L.)
| | - Mingyu Liang
- Center of Systems Molecular Medicine, Department of Physiology, Medical College of Wisconsin, Milwaukee (P.L., Y. Liu, X.P., Y. Li, K.U., M.K.M., M.L.).,Division of Nephrology, Nanfang Hospital, Southern Medical University, National Clinical Research Center for Kidney Disease, State Key Laboratory of Organ Failure Research, Guangzhou, China (H.L., J.N., M.L.)
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