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      An epigenome-wide association study of sex-specific chronological ageing

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          Abstract

          Background

          Advanced age is associated with cognitive and physical decline and is a major risk factor for a multitude of disorders. There is also a gap in life expectancy between males and females. DNA methylation differences have been shown to be associated with both age and sex. Here, we investigate age-by-sex differences in blood-based DNA methylation in an unrelated cohort of 2586 individuals between the ages of 18 and 87 years, with replication in a further 4450 individuals between the ages of 18 and 93 years.

          Methods

          Linear regression models were applied, with stringent genome-wide significance thresholds ( p < 3.6 × 10 −8) used in both the discovery and replication data. A second, highly conservative mixed linear model method that better controls the false-positive rate was also applied, using the same genome-wide significance thresholds.

          Results

          Using the linear regression method, 52 autosomal and 597 X-linked CpG sites, mapping to 251 unique genes, replicated with concordant effect size directions in the age-by-sex interaction analysis. The site with the greatest difference mapped to GAGE10, an X-linked gene. Here, DNA methylation levels remained stable across the male adult age range (DNA methylation by age r = 0.02) but decreased across female adult age range (DNA methylation by age r = − 0.61). One site (cg23722529) with a significant age-by-sex interaction also had a quantitative trait locus (rs17321482) that is a genome-wide significant variant for prostate cancer. The mixed linear model method identified 11 CpG sites associated with the age-by-sex interaction.

          Conclusion

          The majority of differences in age-associated DNA methylation trajectories between sexes are present on the X chromosome. Several of these differences occur within genes that have been implicated in sexually dimorphic traits.

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          Most cited references18

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          An epigenetic biomarker of aging for lifespan and healthspan

          Identifying reliable biomarkers of aging is a major goal in geroscience. While the first generation of epigenetic biomarkers of aging were developed using chronological age as a surrogate for biological age, we hypothesized that incorporation of composite clinical measures of phenotypic age that capture differences in lifespan and healthspan may identify novel CpGs and facilitate the development of a more powerful epigenetic biomarker of aging. Using an innovative two-step process, we develop a new epigenetic biomarker of aging, DNAm PhenoAge, that strongly outperforms previous measures in regards to predictions for a variety of aging outcomes, including all-cause mortality, cancers, healthspan, physical functioning, and Alzheimer's disease. While this biomarker was developed using data from whole blood, it correlates strongly with age in every tissue and cell tested. Based on an in-depth transcriptional analysis in sorted cells, we find that increased epigenetic, relative to chronological age, is associated with increased activation of pro-inflammatory and interferon pathways, and decreased activation of transcriptional/translational machinery, DNA damage response, and mitochondrial signatures. Overall, this single epigenetic biomarker of aging is able to capture risks for an array of diverse outcomes across multiple tissues and cells, and provide insight into important pathways in aging.
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            The Relationship of DNA Methylation with Age, Gender and Genotype in Twins and Healthy Controls

            Cytosine-5 methylation within CpG dinucleotides is a potentially important mechanism of epigenetic influence on human traits and disease. In addition to influences of age and gender, genetic control of DNA methylation levels has recently been described. We used whole blood genomic DNA in a twin set (23 MZ twin-pairs and 23 DZ twin-pairs, N = 92) as well as healthy controls (N = 96) to investigate heritability and relationship with age and gender of selected DNA methylation profiles using readily commercially available GoldenGate bead array technology. Despite the inability to detect meaningful methylation differences in the majority of CpG loci due to tissue type and locus selection issues, we found replicable significant associations of DNA methylation with age and gender. We identified associations of genetically heritable single nucleotide polymorphisms with large differences in DNA methylation levels near the polymorphism (cis effects) as well as associations with much smaller differences in DNA methylation levels elsewhere in the human genome (trans effects). Our results demonstrate the feasibility of array-based approaches in studies of DNA methylation and highlight the vast differences between individual loci. The identification of CpG loci of which DNA methylation levels are under genetic control or are related to age or gender will facilitate further studies into the role of DNA methylation and disease.
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              Genome instability and aging.

              Genome instability has long been implicated as the main causal factor in aging. Somatic cells are continuously exposed to various sources of DNA damage, from reactive oxygen species to UV radiation to environmental mutagens. To cope with the tens of thousands of chemical lesions introduced into the genome of a typical cell each day, a complex network of genome maintenance systems acts to remove damage and restore the correct base pair sequence. Occasionally, however, repair is erroneous, and such errors, as well as the occasional failure to correctly replicate the genome during cell division, are the basis for mutations and epimutations. There is now ample evidence that mutations accumulate in various organs and tissues of higher animals, including humans, mice, and flies. What is not known, however, is whether the frequency of these random changes is sufficient to cause the phenotypic effects generally associated with aging. The exception is cancer, an age-related disease caused by the accumulation of mutations and epimutations. Here, we first review current concepts regarding the relationship between DNA damage, repair, and mutation, as well as the data regarding genome alterations as a function of age. We then describe a model for how randomly induced DNA sequence and epigenomic variants in the somatic genomes of animals can result in functional decline and disease in old age. Finally, we discuss the genetics of genome instability in relation to longevity to address the importance of alterations in the somatic genome as a causal factor in aging and to underscore the opportunities provided by genetic approaches to develop interventions that attenuate genome instability, reduce disease risk, and increase life span.
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                Author and article information

                Contributors
                Riccardo.Marioni@ed.ac.uk
                Journal
                Genome Med
                Genome Med
                Genome Medicine
                BioMed Central (London )
                1756-994X
                31 December 2019
                31 December 2019
                2020
                : 12
                : 1
                Affiliations
                [1 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, , University of Edinburgh, ; Edinburgh, Scotland, UK
                [2 ]ISNI 0000 0000 9320 7537, GRID grid.1003.2, Institute for Molecular Bioscience, , University of Queensland, ; Brisbane, QLD Australia
                [3 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Centre for Cognitive Ageing and Cognitive Epidemiology, , University of Edinburgh, ; Edinburgh, Scotland, UK
                [4 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, , University of Edinburgh, ; Edinburgh, Scotland, UK
                [5 ]ISNI 0000 0004 1936 7291, GRID grid.7107.1, Aberdeen Biomedical Imaging Centre, , University of Aberdeen, ; Aberdeen, Scotland, UK
                [6 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Division of Psychiatry, Royal Edinburgh Hospital, , University of Edinburgh, ; Edinburgh, Scotland, UK
                [7 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, Department of Psychology, , University of Edinburgh, ; Edinburgh, Scotland, UK
                [8 ]ISNI 0000 0001 0348 3990, GRID grid.268099.c, Institute for Advanced Research, , Wenzhou Medical University, ; Wenzhou, Zhejiang, 325027 China
                Author information
                http://orcid.org/0000-0003-4430-4260
                Article
                693
                10.1186/s13073-019-0693-z
                6938636
                31892350
                4fadbea2-1531-4ad3-9fde-e2515a3f5e08
                © The Author(s). 2019

                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
                : 1 October 2019
                : 15 November 2019
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;
                Award ID: 104036/Z/14/Z
                Award ID: 104036/Z/14/Z
                Award ID: 104036/Z/14/Z
                Award ID: 104036/Z/14/Z
                Award ID: 108890/Z/15/Z
                Award ID: 108890/Z/15/Z
                Award Recipient :
                Funded by: Wellcome Trust (GB)
                Award ID: 104036/Z/14/Z
                Award Recipient :
                Funded by: Alzheimer’s Research UK (GB)
                Award ID: ARUK-PG2017B-10
                Funded by: FundRef http://dx.doi.org/10.13039/501100000925, National Health and Medical Research Council;
                Award ID: 1078037
                Award ID: 1083656
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002283, Alzheimer’s Research UK;
                Award ID: ARUK-PG2017B-10
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Molecular medicine
                dna methylation,ageing,sexual dimorphism,x chromosome,generation scotland
                Molecular medicine
                dna methylation, ageing, sexual dimorphism, x chromosome, generation scotland

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