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McCabe CF, Goodrich JM, Bakulski KM, Domino SE, Jones TR, Colacino J, Dolinoy DC, Padmanabhan V. Probing prenatal bisphenol exposures and tissue-specific DNA methylation responses in cord blood, cord tissue, and placenta. Reprod Toxicol 2023; 115:74-84. [PMID: 36473650 PMCID: PMC9851062 DOI: 10.1016/j.reprotox.2022.11.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 11/15/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022]
Abstract
The early-gestational fetal epigenome establishes the landscape for fetal development and is susceptible to disruption via environmental stressors including chemical exposures. Research has explored how cell- and tissue-type-specific epigenomic signatures contribute to human disease, but how the epigenome in each tissue comparatively responds to environmental exposures is largely unknown. This pilot study compared DNA methylation in four previously identified genes across matched cord blood (CB), cord tissue (CT), and placental (PL) samples from 28 mother-infant pairs in tthe Michigan Mother Infant Pairs study; evaluated association between prenatal exposure to bisphenols (BPA, BPF, and BPS) and DNA methylation (DNAm) by tissue type; compared epigenome-wide DNAm of CB and PL; and explored associations between prenatal bisphenol exposures and epigenome-wide DNAm in PL. Bisphenol concentrations were quantified in first-trimester maternal urine. DNAm was assessed at four genes via pyrosequencing in three tissues; epigenome-wide DNAm analysis via Infinium MethylationEPIC array was completed on CB and PL. Candidate gene analysis revealed tissue-specific differences across all genes. In adjusted linear regression, BPA and BPF were associated with DNAm across candidate genes in PL but not CB and CT. Epigenome-wide comparison of matched CB and PL DNAm revealed tissue-specific differences at most CpG sites and modest associations between maternal first-trimester bisphenol exposures and PL but not CB DNAm. These data endorse inclusion of a variety of tissues in prenatal exposure studies. Overlapping and divergent responses in CB, CT, and PL demonstrate their utility in combination to capture a fuller picture of the epigenetic effect of developmental exposures.
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Affiliation(s)
- Carolyn F McCabe
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Jaclyn M Goodrich
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Kelly M Bakulski
- Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Steven E Domino
- Department of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Tamara R Jones
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Justin Colacino
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Dana C Dolinoy
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA; Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA
| | - Vasantha Padmanabhan
- Department of Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI, USA; Department of Pediatrics, University of Michigan Medical School, Ann Arbor, MI, USA; Department of Obstetrics and Gynecology, University of Michigan Medical School, Ann Arbor, MI, USA.
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EpiVisR: exploratory data analysis and visualization in epigenome-wide association analyses. BMC Bioinformatics 2022; 23:292. [PMID: 35870905 PMCID: PMC9308245 DOI: 10.1186/s12859-022-04836-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 07/13/2022] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
With the widespread availability of microarray technology for epigenetic research, methods for calling differentially methylated probes or differentially methylated regions have become effective tools to analyze this type of data. Furthermore, visualization is usually employed for quality check of results and for further insights. Expert knowledge is required to leverage capabilities of these methods. To overcome this limitation and make visualization in epigenetic research available to the public, we designed EpiVisR.
Results
The EpiVisR tool allows to select and visualize combinations of traits (i.e., concentrations of chemical compounds) and differentially methylated probes/regions. It supports various modes of enriched presentation to get the most knowledge out of existing data: (1) enriched Manhattan plot and enriched volcano plot for selection of probes, (2) trait-methylation plot for visualization of selected trait values against methylation values, (3) methylation profile plot for visualization of a selected range of probes against selected trait values as well as, (4) correlation profile plot for selection and visualization of further probes that are correlated to the selected probe. EpiVisR additionally allows exporting selected data to external tools for tasks such as network analysis.
Conclusion
The key advantage of EpiVisR is the annotation of data in the enriched plots (and tied tables) as well as linking to external data sources for further integrated data analysis. Using the EpiVisR approach will allow users to integrate data from traits with epigenetic analyses that are connected by belonging to the same individuals. Merging data from various data sources among the same cohort and visualizing them will enable users to gain more insights from existing data.
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Bhat B, Jones GT. Data Analysis of DNA Methylation Epigenome-Wide Association Studies (EWAS): A Guide to the Principles of Best Practice. Methods Mol Biol 2022; 2458:23-45. [PMID: 35103960 DOI: 10.1007/978-1-0716-2140-0_2] [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] [Indexed: 06/14/2023]
Abstract
Array-based EWAS have become an increasingly popular technique to identify population epigenetic effects, particularly in humans. With the arrival of nonhuman species arrays, such as the mouse, this is likely to become an even more widely used technology. This chapter provides the less experienced researcher a guide to the analysis of data from the most widely used platform, the Illumina Infinium Methylation assay. This includes an overview of quality filtering, data normalization, analysis options, and techniques to improve the interpretation of results.
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Affiliation(s)
- Basharat Bhat
- Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand
| | - Gregory T Jones
- Department of Surgical Sciences, Dunedin School of Medicine, University of Otago, Dunedin, New Zealand.
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4
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Portilla-Fernández E, Hwang SJ, Wilson R, Maddock J, Hill WD, Teumer A, Mishra PP, Brody JA, Joehanes R, Ligthart S, Ghanbari M, Kavousi M, Roks AJM, Danser AHJ, Levy D, Peters A, Ghasemi S, Schminke U, Dörr M, Grabe HJ, Lehtimäki T, Kähönen M, Hurme MA, Bartz TM, Sotoodehnia N, Bis JC, Thiery J, Koenig W, Ong KK, Bell JT, Meisinger C, Wardlaw JM, Starr JM, Seissler J, Then C, Rathmann W, Ikram MA, Psaty BM, Raitakari OT, Völzke H, Deary IJ, Wong A, Waldenberger M, O'Donnell CJ, Dehghan A. Meta-analysis of epigenome-wide association studies of carotid intima-media thickness. Eur J Epidemiol 2021; 36:1143-1155. [PMID: 34091768 PMCID: PMC8629903 DOI: 10.1007/s10654-021-00759-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [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: 04/26/2021] [Indexed: 12/21/2022]
Abstract
Common carotid intima-media thickness (cIMT) is an index of subclinical atherosclerosis that is associated with ischemic stroke and coronary artery disease (CAD). We undertook a cross-sectional epigenome-wide association study (EWAS) of measures of cIMT in 6400 individuals. Mendelian randomization analysis was applied to investigate the potential causal role of DNA methylation in the link between atherosclerotic cardiovascular risk factors and cIMT or clinical cardiovascular disease. The CpG site cg05575921 was associated with cIMT (beta = -0.0264, p value = 3.5 × 10-8) in the discovery panel and was replicated in replication panel (beta = -0.07, p value = 0.005). This CpG is located at chr5:81649347 in the intron 3 of the aryl hydrocarbon receptor repressor gene (AHRR). Our results indicate that DNA methylation at cg05575921 might be in the pathway between smoking, cIMT and stroke. Moreover, in a region-based analysis, 34 differentially methylated regions (DMRs) were identified of which a DMR upstream of ALOX12 showed the strongest association with cIMT (p value = 1.4 × 10-13). In conclusion, our study suggests that DNA methylation may play a role in the link between cardiovascular risk factors, cIMT and clinical cardiovascular disease.
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Affiliation(s)
- Eliana Portilla-Fernández
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Division of Vascular Medicine and Pharmacology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Shih-Jen Hwang
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Rory Wilson
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alexander Teumer
- Intitute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Griefswald, Greifswald, Germany
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Symen Ligthart
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Anton J M Roks
- Department of Internal Medicine, Division of Vascular Medicine and Pharmacology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - A H Jan Danser
- Department of Internal Medicine, Division of Vascular Medicine and Pharmacology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Daniel Levy
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-Universität München, Munich, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Sahar Ghasemi
- Intitute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Griefswald, Greifswald, Germany
| | - Ulf Schminke
- Department of Neurology, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- DZHK (German Centre for Cardiovascular Research), Partner Site Griefswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Mikko A Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Joachim Thiery
- Institute of Laboratory Medicine, Clinical Chemistry and Molecular Diagnostics, University Hospital, Leipzig, Leipzig, Germany
| | - Wolfgang Koenig
- DZHK (German Centre for Cardiovascular Research), Partner Site Munich Heart Alliance, Munich, Germany
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Ken K Ong
- MRC Epidemiology Unit and Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Christine Meisinger
- Independent Research Group, Clinical Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg, Germany
- Ludwig-Maximilians-Universität München, UNIKA-T, Augsburg, Germany
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Jochen Seissler
- Diabetes Zentrum, Medizinische Klinik und Poliklinik IV - Campus Innenstadt, Klinikum Der Ludwig-Maximilians-Universität München, Munich, Germany
- Clinical Cooperation Group Diabetes, Ludwig-Maximilians-Universität München and Helmholtz Zentrum München, Munich, Germany
| | - Cornelia Then
- Diabetes Zentrum, Medizinische Klinik und Poliklinik IV - Campus Innenstadt, Klinikum Der Ludwig-Maximilians-Universität München, Munich, Germany
- Clinical Cooperation Group Diabetes, Ludwig-Maximilians-Universität München and Helmholtz Zentrum München, Munich, Germany
| | - Wolfgang Rathmann
- German Center for Diabetes Research, Neuherberg, Germany
- Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Institute at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and 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, Turku University Hospital, Turku, Finland
| | - Henry Völzke
- Intitute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Griefswald, Greifswald, Germany
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing at UCL, Institute of Cardiovascular Science, University College London, London, UK
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research, Neuherberg, Germany
| | - Christopher J O'Donnell
- Cardiology Section and Center for Population Genomics, VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands.
- Department of Epidemiology and Biostatistics, School of Public Health, Faculty of Medicine, Imperial College London, Room 157, Norfolk Place, St Mary's Campus, London, UK.
- UK Dementia Research Institute at Imperial College London, London, UK.
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK.
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5
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Anatomy of DNA methylation signatures: Emerging insights and applications. Am J Hum Genet 2021; 108:1359-1366. [PMID: 34297908 DOI: 10.1016/j.ajhg.2021.06.015] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Accepted: 06/16/2021] [Indexed: 01/05/2023] Open
Abstract
DNA methylation (DNAm) signatures are unique patterns of DNAm alterations defined for rare disorders caused by pathogenic variants in epigenetic regulatory genes. The potential of DNAm signatures (also known as "episignatures") is just beginning to emerge as there are >300 known epigenetic regulatory genes, ∼100 of which are linked to neurodevelopmental disorders. To date, approximately 50 signatures have been identified, which have proven unexpectedly successful as predictive tools for classifying variants of uncertain significance as pathogenic or benign. The molecular basis of these signatures is poorly understood. Furthermore, their relationships to primary disease pathophysiology have yet to be adequately investigated, despite clear demonstrations of potential connections. There are currently no published guidelines for signature development. As signatures are highly dependent on the samples and methods used to derive them, we propose a framework for consideration in signature development including sample size, statistical parameters, cell type of origin, and the value of detailed clinical and molecular information. We illustrate the relationship between signature output/efficacy and sample size by generating and testing 837 DNAm signatures of Kleefstra syndrome using downsampling analysis. Our findings highlight that no single DNAm signature encompasses all DNAm alterations present in a rare disorder, and that a substandard study design can generate a DNAm signature that misclassifies variants. Finally, we discuss the importance of further investigating DNAm signatures to inform disease pathophysiology and broaden their scope as a functional assay.
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Naithani N, Sinha S, Misra P, Vasudevan B, Sahu R. Precision medicine: Concept and tools. Med J Armed Forces India 2021; 77:249-257. [PMID: 34305276 PMCID: PMC8282508 DOI: 10.1016/j.mjafi.2021.06.021] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
Abstract
Precision medicine is the new age medicine and refers to tailoring treatments to a subpopulation who have a common susceptibility to a particular disease or similar response to a particular drug. Although the concept existed even during the times of Sir William Osler, it was given a shot in the arm with the Precision Medicine Initiative launched by Barack Obama in 2015. The main tools of precision medicine are Big data, artificial intelligence, the various omics, pharmaco-omics, environmental and social factors and the integration of these with preventive and population medicine. Big data can be acquired from electronic health records of patients and includes various biomarkers (clinical and omics based), laboratory and radiological investigations and these can be analysed through machine learning by various complex flowcharts setting up an algorithm for the management of specific subpopulations. So, there is a move away from the traditional "one size fits all" treatment to precision-based medicine. Research in "omics" has increased in leaps and bounds and advancements have included the fields of genomics, epigenomics, proteomics, transcriptomics, metabolomics and microbiomics. Pharmaco-omics has also come to the forefront with development of new drugs and suiting a particular drug to a particular subpopulation, thus avoiding their prescription to non-responders, preventing unwanted adverse effects and proving economical in the long run. Environmental, social and behavioural factors are as important or in fact more important than genetic factors in most complex diseases and managing these factors form an important part of precision medicine. Finally integrating precision with preventive and public health makes "precision medicine" a complete final product which will change the way medicine will be practised in future.
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Affiliation(s)
- Nardeep Naithani
- Director & Commandant, Armed Forces Medical College, Pune, India
| | - Sharmila Sinha
- Professor & Head, Department of Pharmacology, Armed Forces Medical College, Pune, India
| | - Pratibha Misra
- Professor & Head, Department of Biochemistry, Armed Forces Medical College, Pune, India
| | - Biju Vasudevan
- Professor & Head, Department of Dermatology, Armed Forces Medical College, Pune, India
| | - Rajesh Sahu
- Associate Professor, Department of Community Medicine, Armed Forces Medical College, Pune, India
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7
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Cosín-Tomás M, Bustamante M, Sunyer J. Epigenetic association studies at birth and the origin of lung function development. Eur Respir J 2021; 57:57/4/2100109. [PMID: 33858853 DOI: 10.1183/13993003.00109-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2021] [Accepted: 02/04/2021] [Indexed: 11/05/2022]
Affiliation(s)
- Marta Cosín-Tomás
- ISGlobal, Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de investigación biomédica en red en epidemiología y salud pública (ciberesp), Madrid, Spain
| | - Mariona Bustamante
- ISGlobal, Barcelona, Spain.,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de investigación biomédica en red en epidemiología y salud pública (ciberesp), Madrid, Spain
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain .,Universitat Pompeu Fabra, Barcelona, Spain.,Centro de investigación biomédica en red en epidemiología y salud pública (ciberesp), Madrid, Spain.,IMIM Parc Salut Mar, Barcelona, Spain
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8
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Cardenas A, Fadadu RP, Van Der Laan L, Ward-Caviness C, Granger L, Diaz-Sanchez D, Devlin RB, Bind MA. Controlled human exposures to diesel exhaust: a human epigenome-wide experiment of target bronchial epithelial cells. ENVIRONMENTAL EPIGENETICS 2021; 7:dvab003. [PMID: 33859829 PMCID: PMC8035831 DOI: 10.1093/eep/dvab003] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2021] [Revised: 03/05/2021] [Accepted: 03/11/2021] [Indexed: 05/28/2023]
Abstract
Diesel exhaust (DE) is a major contributor to ambient air pollution around the world. It is a known human carcinogen that targets the respiratory system and increases risk for many diseases, but there is limited research on the effects of DE exposure on the epigenome of human bronchial epithelial cells. Understanding the epigenetic impact of this environmental pollutant can elucidate biological mechanisms involved in the pathogenesis of harmful DE-related health effects. To estimate the causal effect of short-term DE exposure on the bronchial epithelial epigenome, we conducted a controlled single-blinded randomized crossover human experiment of exposure to DE and used bronchoscopy and Illumina 450K arrays for data collection and analysis, respectively. Of the 13 participants, 11 (85%) were male and 2 (15%) were female, and 12 (92%) were White and one (8%) was Hispanic; the mean age was 26 years (SD = 3.8 years). Eighty CpGs were differentially methylated, achieving the minimum possible exact P-value of P = 2.44 × 10-4 (i.e. 2/213). In regional analyses, we found two differentially methylated regions (DMRs) annotated to the chromosome 5 open reading frame 63 genes (C5orf63; 7-CpGs) and unc-45 myosin chaperone A gene (UNC45A; 5-CpGs). Both DMRs showed increased DNA methylation after DE exposure. The average causal effects for the DMRs ranged from 1.5% to 6.0% increases in DNA methylation at individual CpGs. In conclusion, we found that short-term DE alters DNA methylation of genes in target bronchial epithelial cells, demonstrating epigenetic level effects of exposure that could be implicated in pulmonary pathologies.
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Affiliation(s)
- Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley; Berkeley, CA 94704, USA
- Center for Computational Biology, University of California, Berkeley, Berkeley, CA 94704, USA
| | - Raj P Fadadu
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley; Berkeley, CA 94704, USA
- School of Medicine, University of California, San Francisco, San Francisco, CA 94143, USA
| | - Lars Van Der Laan
- Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley; Berkeley, CA 94704, USA
| | - Cavin Ward-Caviness
- Public Health and Integrated Toxicology Division, Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27709, USA
| | - Louis Granger
- Department of Statistics, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA
| | - David Diaz-Sanchez
- Public Health and Integrated Toxicology Division, Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27709, USA
| | - Robert B Devlin
- Public Health and Integrated Toxicology Division, Center for Public Health and Environmental Assessment, US Environmental Protection Agency, Chapel Hill, NC 27709, USA
| | - Marie-Abèle Bind
- Department of Statistics, Faculty of Arts and Sciences, Harvard University, Cambridge, MA 02138, USA
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9
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Abstract
Aim: Social scientists have placed particularly high expectations on the study of epigenomics to explain how exposure to adverse social factors like poverty, child maltreatment and racism - particularly early in childhood - might contribute to complex diseases. However, progress has stalled, reflecting many of the same challenges faced in genomics, including overhype, lack of diversity in samples, limited replication and difficulty interpreting significance of findings. Materials & methods: This review focuses on the future of social epigenomics by discussing progress made, ongoing methodological and analytical challenges and suggestions for improvement. Results & conclusion: Recommendations include more diverse sample types, cross-cultural, longitudinal and multi-generational studies. True integration of social and epigenomic data will require increased access to both data types in publicly available databases, enhanced data integration frameworks, and more collaborative efforts between social scientists and geneticists.
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Affiliation(s)
- Amy L Non
- Department of Anthropology at the University of California, San Diego, 92093 CA, USA
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10
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Krause C, Sievert H, Geißler C, Grohs M, El Gammal AT, Wolter S, Ohlei O, Kilpert F, Krämer UM, Kasten M, Klein C, Brabant GE, Mann O, Lehnert H, Kirchner H. Critical evaluation of the DNA-methylation markers ABCG1 and SREBF1 for Type 2 diabetes stratification. Epigenomics 2019; 11:885-897. [PMID: 31169416 DOI: 10.2217/epi-2018-0159] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aim: Validation of epigenome-wide association studies is sparse. Therefore, we evaluated the methylation markers cg06500161 (ABCG1) and cg11024682 (SREBF1) as classifiers for diabetes stratification. Patients & methods: DNA methylation was measured in blood (n = 167), liver (n = 99) and visceral adipose tissue (n = 99) of nondiabetic or Type 2 diabetic subjects by bisulfite pyrosequencing. Results: DNA methylation at cg11024682 in blood and liver correlated with BMI. Methylation at cg06500161 was influenced by the adjacent SNP rs9982016. Insulin-resistant and sensitive subjects could be stratified by DNA methylation status in blood or visceral adipose tissue. Conclusion: DNA methylation at both loci in blood presents a promising approach for risk group stratification and could be valuable for personalized Type 2 diabetes risk prediction in the future.
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Affiliation(s)
- Christin Krause
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Helen Sievert
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Cathleen Geißler
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Martina Grohs
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Alexander T El Gammal
- Department of General, Visceral & Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Stefan Wolter
- Department of General, Visceral & Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Integrative & Experimental Genomics, University of Lübeck, Lübeck, Germany
| | - Fabian Kilpert
- Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Integrative & Experimental Genomics, University of Lübeck, Lübeck, Germany
| | - Ulrike M Krämer
- Department of Neurology, University of Lübeck, Lübeck, Germany.,Institute of Psychology II, University of Lübeck, Lübeck, Germany
| | - Meike Kasten
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany.,Department of Psychiatry & Psychotherapy, University of Lübeck, Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck, Lübeck, Germany
| | - Georg E Brabant
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany
| | - Oliver Mann
- Department of General, Visceral & Thoracic Surgery, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Hendrik Lehnert
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
| | - Henriette Kirchner
- Medical Department I, Division Epigenetics & Metabolism, University of Lübeck, Lübeck, Germany.,German Center for Diabetes Research (DZD), München-Neuherberg, Germany
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11
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Hamza M, Halayem S, Bourgou S, Daoud M, Charfi F, Belhadj A. Epigenetics and ADHD: Toward an Integrative Approach of the Disorder Pathogenesis. J Atten Disord 2019; 23:655-664. [PMID: 28665177 DOI: 10.1177/1087054717696769] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
OBJECTIVE Epigenetic hypothesis is one of the research pathways used to explain the complex etiology of neurodevelopmental disorders. This review highlights the findings of recent studies in the field of epigenetics in ADHD. METHODS An electronic literature search using Medline. RESULTS In the Gene × Environment interaction model, several clinical, genetic and molecular arguments support the epigenetic hypothesis in ADHD etiology. Environmental ADHD risk factors including toxic, nutritional factors and stressful life events lead to changes in DNA methylation and in histone modification levels. One critical CpG site located in the promoter of the DRD4 gene exhibited a specific pattern in ADHD children. A methylome wide exploration of DNA showed decreased methylation in vasoactive intestinal peptide receptor 2 gene, which was not replicated by further research. CONCLUSION Current data require consolidation and could lead to the identification of biomarkers and the introduction of new modalities of treatment.
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Affiliation(s)
- Meriem Hamza
- 1 University of Tunis El Manar, Tunis, Tunisia.,2 Mongi Slim Hospital, Sidi Daoud, Tunisia
| | - Soumeyya Halayem
- 1 University of Tunis El Manar, Tunis, Tunisia.,3 Razi Hospital, Manouba, Tunisia
| | - Soumaya Bourgou
- 1 University of Tunis El Manar, Tunis, Tunisia.,2 Mongi Slim Hospital, Sidi Daoud, Tunisia
| | - Mona Daoud
- 1 University of Tunis El Manar, Tunis, Tunisia.,2 Mongi Slim Hospital, Sidi Daoud, Tunisia
| | - Fatma Charfi
- 1 University of Tunis El Manar, Tunis, Tunisia.,2 Mongi Slim Hospital, Sidi Daoud, Tunisia
| | - Ahlem Belhadj
- 1 University of Tunis El Manar, Tunis, Tunisia.,2 Mongi Slim Hospital, Sidi Daoud, Tunisia
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12
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Integration of DNA methylation patterns and genetic variation in human pediatric tissues help inform EWAS design and interpretation. Epigenetics Chromatin 2019; 12:1. [PMID: 30602389 PMCID: PMC6314079 DOI: 10.1186/s13072-018-0245-6] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2018] [Accepted: 12/18/2018] [Indexed: 02/06/2023] Open
Abstract
Background The widespread use of accessible peripheral tissues for epigenetic analyses has prompted increasing interest in the study of tissue-specific DNA methylation (DNAm) variation in human populations. To date, characterizations of inter-individual DNAm variability and DNAm concordance across tissues have been largely performed in adult tissues and therefore are limited in their relevance to DNAm profiles from pediatric samples. Given that DNAm patterns in early life undergo rapid changes and have been linked to a wide range of health outcomes and environmental exposures, direct investigations of tissue-specific DNAm variation in pediatric samples may help inform the design and interpretation of DNAm analyses from early life cohorts. In this study, we present a systematic comparison of genome-wide DNAm patterns between matched pediatric buccal epithelial cells (BECs) and peripheral blood mononuclear cells (PBMCs), two of the most widely used peripheral tissues in human epigenetic studies. Specifically, we assessed DNAm variability, cross-tissue DNAm concordance and genetic determinants of DNAm across two independent early life cohorts encompassing different ages. Results BECs had greater inter-individual DNAm variability compared to PBMCs and highly the variable CpGs are more likely to be positively correlated between the matched tissues compared to less variable CpGs. These sites were enriched for CpGs under genetic influence, suggesting that a substantial proportion of DNAm covariation between tissues can be attributed to genetic variation. Finally, we demonstrated the relevance of our findings to human epigenetic studies by categorizing CpGs from published DNAm association studies of pediatric BECs and peripheral blood. Conclusions Taken together, our results highlight a number of important considerations and practical implications in the design and interpretation of EWAS analyses performed in pediatric peripheral tissues. Electronic supplementary material The online version of this article (10.1186/s13072-018-0245-6) contains supplementary material, which is available to authorized users.
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13
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Lin X, Teh AL, Chen L, Lim IY, Tan PF, MacIsaac JL, Morin AM, Yap F, Tan KH, Saw SM, Lee YS, Holbrook JD, Godfrey KM, Meaney MJ, Kobor MS, Chong YS, Gluckman PD, Karnani N. Choice of surrogate tissue influences neonatal EWAS findings. BMC Med 2017; 15:211. [PMID: 29202839 PMCID: PMC5715509 DOI: 10.1186/s12916-017-0970-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Accepted: 10/31/2017] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Epigenomes are tissue specific and thus the choice of surrogate tissue can play a critical role in interpreting neonatal epigenome-wide association studies (EWAS) and in their extrapolation to target tissue. To develop a better understanding of the link between tissue specificity and neonatal EWAS, and the contributions of genotype and prenatal factors, we compared genome-wide DNA methylation of cord tissue and cord blood, two of the most accessible surrogate tissues at birth. METHODS In 295 neonates, DNA methylation was profiled using Infinium HumanMethylation450 beadchip arrays. Sites of inter-individual variability in DNA methylation were mapped and compared across the two surrogate tissues at birth, i.e., cord tissue and cord blood. To ascertain the similarity to target tissues, DNA methylation profiles of surrogate tissues were compared to 25 primary tissues/cell types mapped under the Epigenome Roadmap project. Tissue-specific influences of genotype on the variable CpGs were also analyzed. Finally, to interrogate the impact of the in utero environment, EWAS on 45 prenatal factors were performed and compared across the surrogate tissues. RESULTS Neonatal EWAS results were tissue specific. In comparison to cord blood, cord tissue showed higher inter-individual variability in the epigenome, with a lower proportion of CpGs influenced by genotype. Both neonatal tissues were good surrogates for target tissues of mesodermal origin. They also showed distinct phenotypic associations, with effect sizes of the overlapping CpGs being in the same order of magnitude. CONCLUSIONS The inter-relationship between genetics, prenatal factors and epigenetics is tissue specific, and requires careful consideration in designing and interpreting future neonatal EWAS. TRIAL REGISTRATION This birth cohort is a prospective observational study, designed to study the developmental origins of health and disease, and was retrospectively registered on 1 July 2010 under the identifier NCT01174875 .
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Affiliation(s)
- Xinyi Lin
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore.,Duke NUS Medical School, Singapore, 169857, Singapore
| | - Ai Ling Teh
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore
| | - Li Chen
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore
| | - Ives Yubin Lim
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore
| | - Pei Fang Tan
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore
| | - Julia L MacIsaac
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V5Z 4H4, Canada
| | - Alexander M Morin
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V5Z 4H4, Canada
| | - Fabian Yap
- KK Women's and Children's Hospital, Singapore, 229899, Singapore
| | - Kok Hian Tan
- KK Women's and Children's Hospital, Singapore, 229899, Singapore
| | - Seang Mei Saw
- Duke NUS Medical School, Singapore, 169857, Singapore.,Saw Swee Hock School of Public Health, National University of Singapore, Singapore, 117597, Singapore.,Singapore Eye Research Institute, Singapore, 169856, Singapore
| | - Yung Seng Lee
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore.,Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.,Division of Paediatric Endocrinology and Diabetes, Khoo Teck Puat-National University Children's Medical Institute, National University Health System, Singapore, 119228, Singapore
| | - Joanna D Holbrook
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore.,NIHR Biomedical Research Centre, University of Southampton, Southampton, SO16 6YD, UK
| | - Keith M Godfrey
- MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, SO16 6YD, UK
| | - Michael J Meaney
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore.,Ludmer Centre for Neuroinformatics and Mental Health, Douglas University Mental Health Institute, McGill University, Montreal, Quebec, H4H 1R3, Canada
| | - Michael S Kobor
- Centre for Molecular Medicine and Therapeutics, Child and Family Research Institute, Department of Medical Genetics, University of British Columbia, Vancouver, BC, V5Z 4H4, Canada
| | - Yap Seng Chong
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore.,Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore
| | - Peter D Gluckman
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore.,Centre for Human Evolution, Adaptation and Disease, Liggins Institute, University of Auckland, Auckland, 1142, New Zealand
| | - Neerja Karnani
- Singapore Institute for Clinical Sciences, A*STAR, Singapore, 117609, Singapore. .,Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, 119228, Singapore.
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14
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Schang AL, Sabéran-Djoneidi D, Mezger V. The impact of epigenomic next-generation sequencing approaches on our understanding of neuropsychiatric disorders. Clin Genet 2017; 93:467-480. [DOI: 10.1111/cge.13097] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Revised: 07/04/2017] [Accepted: 07/05/2017] [Indexed: 12/31/2022]
Affiliation(s)
- A.-L. Schang
- CNRS; UMR7216 Épigénétique et Destin Cellulaire; F-75205 Paris Cedex 13 France
- Univ Paris Diderot; Sorbonne Paris Cité, F-75205 Paris Cedex 13 France
- Département Hospitalo-Universitaire PROTECT; Paris France
| | - D. Sabéran-Djoneidi
- CNRS; UMR7216 Épigénétique et Destin Cellulaire; F-75205 Paris Cedex 13 France
- Univ Paris Diderot; Sorbonne Paris Cité, F-75205 Paris Cedex 13 France
| | - V. Mezger
- CNRS; UMR7216 Épigénétique et Destin Cellulaire; F-75205 Paris Cedex 13 France
- Univ Paris Diderot; Sorbonne Paris Cité, F-75205 Paris Cedex 13 France
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15
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Hamza M, Halayem S, Mrad R, Bourgou S, Charfi F, Belhadj A. Implication de l’épigénétique dans les troubles du spectre autistique : revue de la littérature. Encephale 2017; 43:374-381. [DOI: 10.1016/j.encep.2016.07.007] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2015] [Revised: 07/04/2016] [Accepted: 07/04/2016] [Indexed: 01/24/2023]
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16
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Solomon O, Yousefi P, Huen K, Gunier RB, Escudero-Fung M, Barcellos LF, Eskenazi B, Holland N. Prenatal phthalate exposure and altered patterns of DNA methylation in cord blood. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2017; 58:398-410. [PMID: 28556291 PMCID: PMC6488305 DOI: 10.1002/em.22095] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2016] [Revised: 04/11/2017] [Accepted: 04/12/2017] [Indexed: 05/18/2023]
Abstract
Epigenetic changes such as DNA methylation may be a molecular mechanism through which environmental exposures affect health. Phthalates are known endocrine disruptors with ubiquitous exposures in the general population including pregnant women, and they have been linked with a number of adverse health outcomes. We examined the association between in utero phthalate exposure and altered patterns of cord blood DNA methylation in 336 Mexican-American newborns. Concentrations of 11 phthalate metabolites were analyzed in maternal urine samples collected at 13 and 26 weeks gestation as a measure of fetal exposure. DNA methylation was assessed using the Infinium HumanMethylation 450K BeadChip adjusting for cord blood cell composition. To identify differentially methylated regions (DMRs) that may be more informative than individual CpG sites, we used two different approaches, DMRcate and comb-p. Regional assessment by both methods identified 27 distinct DMRs, the majority of which were in relation to multiple phthalate metabolites. Most of the significant DMRs (67%) were observed for later pregnancy (26 weeks gestation). Further, 51% of the significant DMRs were associated with the di-(2-ethylhexyl) phthalate metabolites. Five individual CpG sites were associated with phthalate metabolite concentrations after multiple comparisons adjustment (FDR), all showing hypermethylation. Genes with DMRs were involved in inflammatory response (IRAK4 and ESM1), cancer (BRCA1 and LASP1), endocrine function (CNPY1), and male fertility (IFT140, TESC, and PRDM8). These results on differential DNA methylation in newborns with prenatal phthalate exposure provide new insights and targets to explore mechanism of adverse effects of phthalates on human health. Environ. Mol. Mutagen. 58:398-410, 2017. © 2017 Wiley Periodicals, Inc.
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Affiliation(s)
- Olivia Solomon
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Paul Yousefi
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Karen Huen
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Robert B. Gunier
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Maria Escudero-Fung
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Lisa F. Barcellos
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Brenda Eskenazi
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
| | - Nina Holland
- School of Public Health, Center for Environmental Research and Children’s Health (CERCH), University
of California, Berkeley, Berkeley, CA 94720, USA
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17
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Holland N. Future of environmental research in the age of epigenomics and exposomics. REVIEWS ON ENVIRONMENTAL HEALTH 2017; 32:45-54. [PMID: 27768585 PMCID: PMC5346048 DOI: 10.1515/reveh-2016-0032] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/30/2016] [Accepted: 09/15/2016] [Indexed: 05/14/2023]
Abstract
Environmental research and public health in the 21st century face serious challenges such as increased air pollution and global warming, widespread use of potentially harmful chemicals including pesticides, plasticizers, and other endocrine disruptors, and radical changes in nutrition and lifestyle typical of modern societies. In particular, exposure to environmental and occupational toxicants may contribute to the occurrence of adverse birth outcomes, neurodevelopmental deficits, and increased risk of cancer and other multifactorial diseases such as diabetes and asthma. Rapidly evolving methodologies of exposure assessment and the conceptual framework of the Exposome, first introduced in 2005, are new frontiers of environmental research. Metabolomics and adductomics provide remarkable opportunities for a better understanding of exposure and prediction of potential adverse health outcomes. Metabolomics, the study of metabolism at whole-body level, involves assessment of the total repertoire of small molecules present in a biological sample, shedding light on interactions between gene expression, protein expression, and the environment. Advances in genomics, transcriptomics, and epigenomics are generating multidimensional structures of biomarkers of effect and susceptibility, increasingly important for the understanding of molecular mechanisms and the emergence of personalized medicine. Epigenetic mechanisms, particularly DNA methylation and miRNA expression, attract increasing attention as potential links between the genetic and environmental determinants of health and disease. Unlike genetics, epigenetic mechanisms could be reversible and an understanding of their role may lead to better protection of susceptible populations and improved public health.
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18
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Volberg V, Yousefi P, Huen K, Harley K, Eskenazi B, Holland N. CpG Methylation across the adipogenic PPARγ gene and its relationship with birthweight and child BMI at 9 years. BMC MEDICAL GENETICS 2017; 18:7. [PMID: 28122515 PMCID: PMC5267417 DOI: 10.1186/s12881-016-0365-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/19/2016] [Accepted: 12/26/2016] [Indexed: 01/05/2023]
Abstract
Background To examine methylation of the peroxisome proliferator-activated receptor γ (PPARγ) gene and its relationship with child weight status, at birth and 9 years. Methods We measured PPARγ methylation across 23 CpG sites using the Infinium Illumina 450 k array for children from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) cohort at birth (N = 373) and 9 years (N = 245). Results Methylation level correlation patterns across the 23 PPARγ CpG sites were conserved between birth and 9-year ages. We found high inter-CpG correlations between sites 1–3 (methylation block 1) and also between sites 18–23 (methylation block 2) for both time points, although these patterns were less pronounced at 9 years. Additionally, sites 1–3 (north shore) had the highest intra-CpG correlations over time (r = 0.24, 0.42, and 0.3; P = 0.002, P < 0.001, P < 0.001, respectively). PPARγ methylation levels tended to increase with age, and the largest differences were observed for north shore sites (7.4%). Adjusting for sex, both site 1 and site 20 (gene body) methylation at birth was significantly and inversely associated with birth weight (β = −0.13, P = 0.033; β = −0.09, P = 0.025, respectively). Similarly, we found that site 1 and site 20 methylation at 9 years was significantly and inversely associated with 9-year BMI z-score (β = −0.41, P = 0.015; β = −0.23, P = 0.045, respectively). Conclusion Our results indicate that PPARγ methylation is highly organized and conserved over time, and highlight the potential functional importance of north shore sites, adding to a better understanding of regional human methylome patterns. Overall, our results suggest that PPARγ methylation may be associated with child body size. Electronic supplementary material The online version of this article (doi:10.1186/s12881-016-0365-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Vitaly Volberg
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, 733 University Hall, Berkeley, CA, 94720-7360, USA
| | - Paul Yousefi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, 733 University Hall, Berkeley, CA, 94720-7360, USA
| | - Karen Huen
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, 733 University Hall, Berkeley, CA, 94720-7360, USA
| | - Kim Harley
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, 733 University Hall, Berkeley, CA, 94720-7360, USA
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, 733 University Hall, Berkeley, CA, 94720-7360, USA
| | - Nina Holland
- Center for Environmental Research and Children's Health (CERCH), School of Public Health, University of California, 733 University Hall, Berkeley, CA, 94720-7360, USA.
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19
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DNA methylation: conducting the orchestra from exposure to phenotype? Clin Epigenetics 2016; 8:92. [PMID: 27602172 PMCID: PMC5012062 DOI: 10.1186/s13148-016-0256-8] [Citation(s) in RCA: 126] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2016] [Accepted: 08/22/2016] [Indexed: 01/02/2023] Open
Abstract
DNA methylation, through 5-methyl- and 5-hydroxymethylcytosine (5mC and 5hmC), is considered to be one of the principal interfaces between the genome and our environment, and it helps explain phenotypic variations in human populations. Initial reports of large differences in methylation level in genomic regulatory regions, coupled with clear gene expression data in both imprinted genes and malignant diseases, provided easily dissected molecular mechanisms for switching genes on or off. However, a more subtle process is becoming evident, where small (<10 %) changes to intermediate methylation levels are associated with complex disease phenotypes. This has resulted in two clear methylation paradigms. The latter “subtle change” paradigm is rapidly becoming the epigenetic hallmark of complex disease phenotypes, although we are currently hampered by a lack of data addressing the true biological significance and meaning of these small differences. Our initial expectation of rapidly identifying mechanisms linking environmental exposure to a disease phenotype led to numerous observational/association studies being performed. Although this expectation remains unmet, there is now a growing body of literature on specific genes, suggesting wide ranging transcriptional and translational consequences of such subtle methylation changes. Data from the glucocorticoid receptor (NR3C1) has shown that a complex interplay between DNA methylation, extensive 5′UTR splicing, and microvariability gives rise to the overall level and relative distribution of total and N-terminal protein isoforms generated. Additionally, the presence of multiple AUG translation initiation codons throughout the complete, processed mRNA enables translation variability, hereby enhancing the translational isoforms and the resulting protein isoform diversity, providing a clear link between small changes in DNA methylation and significant changes in protein isoforms and cellular locations. Methylation changes in the NR3C1 CpG island alters the NR3C1 transcription and eventually protein isoforms in the tissues, resulting in subtle but visible physiological variability. This review addresses the current pathophysiological and clinical associations of such characteristically small DNA methylation changes, the ever-growing roles of DNA methylation and the evidence available, particularly from the glucocorticoid receptor of the cascade of events initiated by such subtle methylation changes, as well as addressing the underlying question as to what represents a genuine biologically significant difference in methylation.
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20
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Lin X, Barton S, Holbrook JD. How to make DNA methylome wide association studies more powerful. Epigenomics 2016; 8:1117-29. [PMID: 27052998 PMCID: PMC5066141 DOI: 10.2217/epi-2016-0017] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2016] [Accepted: 03/23/2016] [Indexed: 02/06/2023] Open
Abstract
Genome-wide association studies had a troublesome adolescence, while researchers increased statistical power, in part by increasing subject numbers. Interrogating the interaction of genetic and environmental influences raised new challenges of statistical power, which were not easily bested by the addition of subjects. Screening the DNA methylome offers an attractive alternative as methylation can be thought of as a proxy for the combined influences of genetics and environment. There are statistical challenges unique to DNA methylome data and also multiple features, which can be exploited to increase power. We anticipate the development of DNA methylome association study designs and new analytical methods, together with integration of data from other molecular species and other studies, which will boost statistical power and tackle causality. In this way, the molecular trajectories that underlie disease development will be uncovered.
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Affiliation(s)
- Xinyi Lin
- Singapore Institute for Clinical Sciences (SICS), Agency for Science & Technology Research (A*STAR), Brenner Centre for Molecular Medicine, 30 Medical Drive, 117609, Singapore
| | - Sheila Barton
- MRC Lifecourse Epidemiology Unit, Faculty of Medicine, University of Southampton, Southampton, SO16 6YD, UK
| | - Joanna D Holbrook
- Singapore Institute for Clinical Sciences (SICS), Agency for Science & Technology Research (A*STAR), Brenner Centre for Molecular Medicine, 30 Medical Drive, 117609, Singapore
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Abstract
PURPOSE OF REVIEW The interplay between lipids and epigenetic mechanisms has recently gained increased interest because of its relevance for common diseases and most notably atherosclerosis. This review discusses recent advances in unravelling this interplay with a particular focus on promising approaches and methods that will be able to establish causal relationships. RECENT FINDINGS Complementary approaches uncovered close links between circulating lipids and epigenetic mechanisms at multiple levels. A characterization of lipid-associated genetic variants suggests that these variants exert their influence on lipid levels through epigenetic changes in the liver. Moreover, exposure of monocytes to lipids persistently alters their epigenetic makeup resulting in more proinflammatory cells. Hence, epigenetic changes can both impact on and be induced by lipids. SUMMARY It is the combined application of technological advances to probe epigenetic modifications at a genome-wide scale and methodological advances aimed at causal inference (including Mendelian randomization and integrative genomics) that will elucidate the interplay between circulating lipids and epigenetics. Understanding its role in the development of atherosclerosis holds the promise of identifying a new category of therapeutic targets, since epigenetic changes are amenable to reversal.
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Affiliation(s)
- Koen F Dekkers
- aMolecular Epidemiology section bDepartment of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
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22
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Yousefi P, Huen K, Quach H, Motwani G, Hubbard A, Eskenazi B, Holland N. Estimation of blood cellular heterogeneity in newborns and children for epigenome-wide association studies. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2015; 56:751-8. [PMID: 26332589 PMCID: PMC4636959 DOI: 10.1002/em.21966] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/02/2015] [Revised: 07/01/2015] [Accepted: 07/03/2015] [Indexed: 05/16/2023]
Abstract
Confounding by cellular heterogeneity has become a major concern for epigenome-wide association studies (EWAS) in peripheral blood samples from population and clinical studies. Adjusting for white blood cell percentage estimates produced by the minfi implementation of the Houseman algorithm (minfi) during statistical analysis is now an established method to account for this bias in adults. However, minfi has not been benchmarked against white blood cell counts in children that may differ substantially from the reference dataset used in its estimation. We compared estimates of white blood cell type percentages produced by two methods, minfi and differential cell count (DCC), in a birth cohort at two time points (birth and 12 years of age). We found that both minfi and DCC had similar trends as children aged, and neither count method differed by sex among newborns (P > 0.10). However, minfi estimates did not correlate well with DCC in samples from newborns (ρ = -0.05 for granulocytes; ρ = -0.03 for lymphocytes). In older children, correlation improved substantially (ρ = 0.77 for granulocytes; ρ = 0.75 for lymphocytes), likely due to increasing similarity with minfi's adult reference data as children aged. Our findings suggest that the minfi method may provide suitable estimates of white blood cell composition for samples from adults and older children, but may not currently be appropriate for EWAS involving newborns or young children.
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Affiliation(s)
- Paul Yousefi
- School of Public Health, University of California, Berkeley, CA, USA
| | - Karen Huen
- School of Public Health, University of California, Berkeley, CA, USA
| | - Hong Quach
- School of Public Health, University of California, Berkeley, CA, USA
| | - Girish Motwani
- School of Public Health, University of California, Berkeley, CA, USA
| | - Alan Hubbard
- School of Public Health, University of California, Berkeley, CA, USA
| | - Brenda Eskenazi
- School of Public Health, University of California, Berkeley, CA, USA
| | - Nina Holland
- School of Public Health, University of California, Berkeley, CA, USA
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