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      DNA methylation: a potential mediator between air pollution and metabolic syndrome

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          Abstract

          Given the global increase in air pollution and its crucial role in human health, as well as the steep rise in prevalence of metabolic syndrome (MetS), a better understanding of the underlying mechanisms by which environmental pollution may influence MetS is imperative. Exposure to air pollution is known to impact DNA methylation, which in turn may affect human health. This paper comprehensively reviews the evidence for the hypothesis that the effect of air pollution on the MetS is mediated by DNA methylation in blood. First, we present a summary of the impact of air pollution on metabolic dysregulation, including the components of MetS, i.e., disorders in blood glucose, lipid profile, blood pressure, and obesity. Then, we provide evidence on the relation between air pollution and endothelial dysfunction as one possible mechanism underlying the relation between air pollution and MetS. Subsequently, we review the evidence that air pollution (PM, ozone, NO 2 and PAHs) influences DNA methylation. Finally, we summarize association studies between DNA methylation and MetS. Integration of current evidence supports our hypothesis that methylation may partly mediate the effect of air pollution on MetS.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13148-022-01301-y.

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          Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: an analysis of data from the Global Burden of Diseases Study 2015

          AARON COHEN, Michael Brauer, Richard Burnett … (2017)
          Summary Background Exposure to ambient air pollution increases morbidity and mortality, and is a leading contributor to global disease burden. We explored spatial and temporal trends in mortality and burden of disease attributable to ambient air pollution from 1990 to 2015 at global, regional, and country levels. Methods We estimated global population-weighted mean concentrations of particle mass with aerodynamic diameter less than 2·5 μm (PM2·5) and ozone at an approximate 11 km × 11 km resolution with satellite-based estimates, chemical transport models, and ground-level measurements. Using integrated exposure–response functions for each cause of death, we estimated the relative risk of mortality from ischaemic heart disease, cerebrovascular disease, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infections from epidemiological studies using non-linear exposure–response functions spanning the global range of exposure. Findings Ambient PM2·5 was the fifth-ranking mortality risk factor in 2015. Exposure to PM2·5 caused 4·2 million (95% uncertainty interval [UI] 3·7 million to 4·8 million) deaths and 103·1 million (90·8 million 115·1 million) disability-adjusted life-years (DALYs) in 2015, representing 7·6% of total global deaths and 4·2% of global DALYs, 59% of these in east and south Asia. Deaths attributable to ambient PM2·5 increased from 3·5 million (95% UI 3·0 million to 4·0 million) in 1990 to 4·2 million (3·7 million to 4·8 million) in 2015. Exposure to ozone caused an additional 254 000 (95% UI 97 000–422 000) deaths and a loss of 4·1 million (1·6 million to 6·8 million) DALYs from chronic obstructive pulmonary disease in 2015. Interpretation Ambient air pollution contributed substantially to the global burden of disease in 2015, which increased over the past 25 years, due to population ageing, changes in non-communicable disease rates, and increasing air pollution in low-income and middle-income countries. Modest reductions in burden will occur in the most polluted countries unless PM2·5 values are decreased substantially, but there is potential for substantial health benefits from exposure reduction. Funding Bill & Melinda Gates Foundation and Health Effects Institute.
          Article 0 comments Cited 1213 times – based on 0 reviews     Review now
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            The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses.

            Gil Stelzer, Naomi Rosen, Inbar Plaschkes … (2016)
            GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It automatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. VarElect's capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. © 2016 by John Wiley & Sons, Inc.
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              10 Years of GWAS Discovery: Biology, Function, and Translation.

              Peter Visscher, Naomi R. Wray, Qian Zhang … (2017)
              Application of the experimental design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review the remarkable range of discoveries it has facilitated in population and complex-trait genetics, the biology of diseases, and translation toward new therapeutics. We predict the likely discoveries in the next 10 years, when GWASs will be based on millions of samples with array data imputed to a large fully sequenced reference panel and on hundreds of thousands of samples with whole-genome sequencing data.
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                Author and article information

                Contributors
                Ahmad Vaez: a.vaez@umcg.nl
                Harold Snieder: h.snieder@umcg.nl
                Journal
                Journal ID (nlm-ta): Clin Epigenetics
                Journal ID (iso-abbrev): Clin Epigenetics
                Title: Clinical Epigenetics
                Publisher: BioMed Central (London )
                ISSN (Print): 1868-7075
                ISSN (Electronic): 1868-7083
                Publication date (Electronic): 30 June 2022
                Publication date PMC-release: 30 June 2022
                Publication date Collection: 2022
                Volume: 14
                Electronic Location Identifier: 82
                Affiliations
                [1 ]GRID grid.4494.d, ISNI 0000 0000 9558 4598, Department of Epidemiology, University of Groningen, , University Medical Center Groningen, ; Groningen, the Netherlands
                [2 ]GRID grid.411036.1, ISNI 0000 0001 1498 685X, Department of Bioinformatics, , Isfahan University of Medical Sciences, ; Isfahan, Iran
                Article
                Publisher ID: 1301
                DOI: 10.1186/s13148-022-01301-y
                PMC ID: 9245491
                PubMed ID: 35773726
                SO-VID: 405836e7-b723-4891-8088-d1f797eaca91
                Copyright © © The Author(s) 2022
                License:

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                Date received : 25 February 2022
                Date accepted : 1 June 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100003970, Isfahan University of Medical Sciences;
                Categories
                Subject: Review
                Custom metadata
                issue-copyright-statement © The Author(s) 2022

                ScienceOpen disciplines: Genetics
                Keywords: epigenetics,dna methylation,metabolic syndrome,air pollution
                Data availability:
                ScienceOpen disciplines: Genetics
                Keywords: epigenetics, dna methylation, metabolic syndrome, air pollution

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