An epigenome-wide association study of sex-specific chronological ageing
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 investigat...
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| Veröffentlicht in: | Genome medicine Jg. 12; H. 1; S. 1 - 11 |
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
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London
BioMed Central
31.12.2019
BioMed Central Ltd Springer Nature B.V BMC |
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| ISSN: | 1756-994X, 1756-994X |
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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. |
|---|---|
| AbstractList | 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.BACKGROUNDAdvanced 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.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.METHODSLinear 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.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.RESULTSUsing 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.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.CONCLUSIONThe 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. 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. Linear regression models were applied, with stringent genome-wide significance thresholds (p < 3.6 × 10 ) 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. 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. 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. 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. 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 x 10.sup.-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. Keywords: DNA methylation, Ageing, Sexual dimorphism, X chromosome, Generation Scotland 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. 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. 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. Linear regression models were applied, with stringent genome-wide significance thresholds (p < 3.6 x 10.sup.-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. 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. 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. |
| ArticleNumber | 1 |
| Audience | Academic |
| Author | Hillary, Robert F. Boutin, Thibaud Chandra, Tamir Whalley, Heather C. Deary, Ian J. Visscher, Peter M. McCartney, Daniel L. Zhang, Qian Campbell, Archie Porteous, David J. Murray, Alison D. Stevenson, Anna J. Morris, Stewart W. Walker, Rosie M. McIntosh, Andrew M. Yang, Jian Bermingham, Mairead L. Evans, Kathryn L. McRae, Allan F. Zhang, Futao Hayward, Caroline Marioni, Riccardo E. |
| Author_xml | – sequence: 1 givenname: Daniel L. surname: McCartney fullname: McCartney, Daniel L. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 2 givenname: Futao surname: Zhang fullname: Zhang, Futao organization: Institute for Molecular Bioscience, University of Queensland – sequence: 3 givenname: Robert F. surname: Hillary fullname: Hillary, Robert F. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 4 givenname: Qian surname: Zhang fullname: Zhang, Qian organization: Institute for Molecular Bioscience, University of Queensland – sequence: 5 givenname: Anna J. surname: Stevenson fullname: Stevenson, Anna J. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 6 givenname: Rosie M. surname: Walker fullname: Walker, Rosie M. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh – sequence: 7 givenname: Mairead L. surname: Bermingham fullname: Bermingham, Mairead L. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 8 givenname: Thibaud surname: Boutin fullname: Boutin, Thibaud organization: MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 9 givenname: Stewart W. surname: Morris fullname: Morris, Stewart W. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 10 givenname: Archie surname: Campbell fullname: Campbell, Archie organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 11 givenname: Alison D. surname: Murray fullname: Murray, Alison D. organization: Aberdeen Biomedical Imaging Centre, University of Aberdeen – sequence: 12 givenname: Heather C. surname: Whalley fullname: Whalley, Heather C. organization: Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh – sequence: 13 givenname: David J. surname: Porteous fullname: Porteous, David J. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh – sequence: 14 givenname: Caroline surname: Hayward fullname: Hayward, Caroline organization: MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 15 givenname: Kathryn L. surname: Evans fullname: Evans, Kathryn L. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh – sequence: 16 givenname: Tamir surname: Chandra fullname: Chandra, Tamir organization: MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh – sequence: 17 givenname: Ian J. surname: Deary fullname: Deary, Ian J. organization: Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Department of Psychology, University of Edinburgh – sequence: 18 givenname: Andrew M. surname: McIntosh fullname: McIntosh, Andrew M. organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh – sequence: 19 givenname: Jian surname: Yang fullname: Yang, Jian organization: Institute for Molecular Bioscience, University of Queensland, Institute for Advanced Research, Wenzhou Medical University – sequence: 20 givenname: Peter M. surname: Visscher fullname: Visscher, Peter M. organization: Institute for Molecular Bioscience, University of Queensland – sequence: 21 givenname: Allan F. surname: McRae fullname: McRae, Allan F. organization: Institute for Molecular Bioscience, University of Queensland – sequence: 22 givenname: Riccardo E. orcidid: 0000-0003-4430-4260 surname: Marioni fullname: Marioni, Riccardo E. email: Riccardo.Marioni@ed.ac.uk organization: Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31892350$$D View this record in MEDLINE/PubMed |
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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... 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... 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... 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... |
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| SubjectTerms | Adult Age Aged Ageing Aging Aging - genetics Analysis Bioinformatics Biomedical and Life Sciences Biomedicine Blood Cancer Research Chromosomes, Human, X - genetics Cognitive ability CpG Islands Deoxyribonucleic acid Disease DNA DNA Methylation Epigenetics Female Gene Expression Regulation Gene mapping Generation Scotland Genes Genome-Wide Association Study Genomes Genomics Health aspects Human Genetics Humans Life expectancy Life span Linear Models Male Medicine/Public Health Metabolomics Methylation Middle Aged Mortality Prostate cancer Quality control Quantitative Trait Loci Regression analysis Replication Risk factors Sex Sex Characteristics Sex differences Sexual dimorphism Software Studies Systems Biology X chromosome |
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| Title | An epigenome-wide association study of sex-specific chronological ageing |
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