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      DNA methylation patterns associated with oxidative stress in an ageing population

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          Abstract

          Background

          Oxidative stress has been related to type 2 diabetes (T2D) and cardiovascular disease (CVD), the leading global cause of death. Contributions of environmental factors such as oxidative stress on complex traits and disease may be partly mediated through changes in epigenetic marks (e.g. DNA methylation). Studies relating differential methylation with intermediate phenotypes and disease endpoints may be useful in identifying additional candidate genes and mechanisms involved in disease.

          Methods

          To investigate the role of epigenetic variation in oxidative stress marker levels and subsequent development of CVD and T2D, we performed analyses of genome-wide DNA methylation in blood, ten markers of oxidative stress (total glutathione [TGSH], reduced glutathione [GSH], oxidised glutathione [GSSG], GSSG to GSH ratio, homocysteine [HCY], oxidised low-density lipoprotein (oxLDL), antibodies against oxLDL [OLAB], conjugated dienes [CD], baseline conjugated dienes [BCD]-LDL and total antioxidant capacity [TAOC]) and incident disease in up to 966 age-matched individuals.

          Results

          In total, we found 66 cytosine-guanine (CpG) sites associated with one or more oxidative stress markers (false discovery rate [FDR] <0.05). These sites were enriched in regulatory regions of the genome. Genes annotated to CpG sites showed enrichment in annotation clusters relating to phospho-metabolism and proteins with pleckstrin domains. We investigated the contribution of oxidative stress-associated CpGs to development of cardiometabolic disease. Methylation variation at CpGs in the 3'-UTR of HIST1H4D (cg08170869; histone cluster 1, H4d) and in the body of DVL1 (cg03465880; dishevelled-1) were associated with incident T2D events during 10 years of follow-up (all permutation p-values <0.01), indicating a role of epigenetic regulation in oxidative stress processes leading to development or progression of diabetes. Methylation QTL (meQTL) analysis showed significant associations with genetic sequence variants in cis at 28 (42%) of oxidative stress phenotype-associated sites (FDR < 0.05). Integrating cis-meQTLs with genotype-phenotype associations indicated that genetic effects on oxidative stress phenotype at one locus (cg07547695; BCL2L11) may be mediated through DNA methylation.

          Conclusions

          In conclusion, we report novel associations of DNA methylation with oxidative stress, some of which also show evidence of a relation with T2D incidence.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12920-016-0235-0) contains supplementary material, which is available to authorized users.

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          Most cited references40

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          R: A language and environment for statistical computing

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            High density DNA methylation array with single CpG site resolution.

            We have developed a new generation of genome-wide DNA methylation BeadChip which allows high-throughput methylation profiling of the human genome. The new high density BeadChip can assay over 480K CpG sites and analyze twelve samples in parallel. The innovative content includes coverage of 99% of RefSeq genes with multiple probes per gene, 96% of CpG islands from the UCSC database, CpG island shores and additional content selected from whole-genome bisulfite sequencing data and input from DNA methylation experts. The well-characterized Infinium® Assay is used for analysis of CpG methylation using bisulfite-converted genomic DNA. We applied this technology to analyze DNA methylation in normal and tumor DNA samples and compared results with whole-genome bisulfite sequencing (WGBS) data obtained for the same samples. Highly comparable DNA methylation profiles were generated by the array and sequencing methods (average R2 of 0.95). The ability to determine genome-wide methylation patterns will rapidly advance methylation research. Copyright © 2011 Elsevier Inc. All rights reserved.
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              Epigenome-wide association studies for common human diseases.

              Despite the success of genome-wide association studies (GWASs) in identifying loci associated with common diseases, a substantial proportion of the causality remains unexplained. Recent advances in genomic technologies have placed us in a position to initiate large-scale studies of human disease-associated epigenetic variation, specifically variation in DNA methylation. Such epigenome-wide association studies (EWASs) present novel opportunities but also create new challenges that are not encountered in GWASs. We discuss EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies. We also discuss how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.
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                Author and article information

                Contributors
                asa.hedman@medsci.uu.se
                mihkel.zilmer@ut.ee
                johan.sundstrom@medsci.uu.se
                lars.lind@medsci.uu.se
                eriking@stanford.edu
                Journal
                BMC Med Genomics
                BMC Med Genomics
                BMC Medical Genomics
                BioMed Central (London )
                1755-8794
                25 November 2016
                25 November 2016
                2016
                : 9
                : 72
                Affiliations
                [1 ]Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
                [2 ]Institute of Biomedicine and Translational Medicine, Department of Biochemistry, The Centre of Excellence for Genomics and Translational Medicine, University of Tartu, Tartu, Estonia
                [3 ]Department of Medical Sciences, Cardiovascular Epidemiology, Uppsala University Hospital, Uppsala, Sweden
                [4 ]Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA USA
                Article
                235
                10.1186/s12920-016-0235-0
                5123374
                27884142
                2bad8a01-ecaa-426a-b4c4-b2259646f7c5
                © The Author(s). 2016

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                : 6 August 2016
                : 14 November 2016
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100004063, Knut och Alice Wallenbergs Stiftelse;
                Funded by: FundRef http://dx.doi.org/10.13039/501100004359, Vetenskapsrådet;
                Award ID: 2012-1397
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100003793, Hjärt-Lungfonden;
                Award ID: 20120197
                Award Recipient :
                Funded by: Linnestiftelsen
                Funded by: European Regional Development Fund
                Award ID: Project No. 2014-2020.4.01.15-0012
                Award Recipient :
                Funded by: Eesti Teadusagentuur (EE)
                Award ID: IUT 20-42
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100005423, Akademiska Sjukhuset;
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2016

                Genetics
                dna methylation,epigenetics,oxidative stress,type 2 diabetes,cardiovascular disease
                Genetics
                dna methylation, epigenetics, oxidative stress, type 2 diabetes, cardiovascular disease

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