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Contribution of heritability and epigenetic factors to skeletal muscle mass variation in UK twins

Contribution of heritability and epigenetic factors to skeletal muscle mass variation in UK twins
Contribution of heritability and epigenetic factors to skeletal muscle mass variation in UK twins
Context: Skeletal muscle mass (SMM) is one of the major components of human body composition, with deviations from normal values often leading to sarcopenia.

Objective: Our major aim was to conduct a genome-wide DNA methylation study in an attempt to identify potential genomic regions associated with SMM.

Design: This was a mixed cross-sectional and longitudinal study.

Setting: Community-based study.

Participants: A total of 1550 middle-aged UK twin (monozygotic and dizygotic) twins, 297 of which were repeatedly measured participated in the study.

Main Outcome Measure: Appendicular lean mass assessed using DXA technology, and MeDIP-seq DNA methylation profiling genome-wide were obtained from each individual.

Results: Heritability estimate of SMM, with simultaneous adjustment for covariates obtained using variance decomposition analysis was h2=0.809±0.050. After quality control and analysis of longitudinal stability, the DNA methylation data comprised of 723,029 genomic sites, with positive correlations between repeated measurements (Rrepeated =0.114–0.905). Correlations between MZ and DZ twins were 0.51 and 0.38 at a genome-wide average, respectively and clearly increased with Rrepeated. Testing for DNA methylation association with SMM in 50 discordant MZ twins revealed 36,081 nominally significant results, of which the top-ranked 134 signals (P<0.01 and Rrepeated>0.40) were subjected to replication in the sample of 1,196 individuals. Seven SMM-methylation association signals replicated at a false discovery rate <0.1, and these were located in or near genes DNAH12, CAND1, CYP4F29P, ZFP64 which have previously been highlighted in muscle-related studies. Adjusting for age, smoking and blood cell heterogeneity did not alter significance of these associations.

Conclusion: This epigenome-wide study, testing longitudinally stable methylation sites discovered and replicated a number of associations between DNA methylation at CpG loci and skeletal muscle mass. Four replicated signals were related to genes with potential muscle functions, suggesting that the methylome of whole blood may be informative of SMM variation
0021-972X
1-10
Livshits, Gregory
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Gao, Fei
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Malkin, Ida
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Needhamsen, Maria
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Xia, Yudong
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Yuan, Wei
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Bell, Christopher G.
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Ward, Kirsten
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Liu, Yuan
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Wang, Jun
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Bell, Jordana T.
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Spector, Tim D.
1e47066c-6620-4f86-af6f-89d9e130ffc2
Livshits, Gregory
48144766-2155-4c02-9dfd-08a049751cd7
Gao, Fei
fa3e4707-8319-49fa-897b-b27f7a534508
Malkin, Ida
5ebf95ce-4f4a-4eb7-8cba-404b7a29f6a2
Needhamsen, Maria
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Xia, Yudong
1a3cbe01-cb90-4144-939f-ab2c72779f12
Yuan, Wei
934197a6-0708-4967-ab09-032f8327e4e5
Bell, Christopher G.
1e513ce3-92de-4d23-92e0-154aec7b9989
Ward, Kirsten
0d581684-6bdd-40a6-9cad-ec46bf82ed47
Liu, Yuan
85638adc-2658-415f-bd1c-2644f0c1cc04
Wang, Jun
dac45864-634f-41ec-ba2a-1e59ad23ae97
Bell, Jordana T.
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Spector, Tim D.
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Livshits, Gregory, Gao, Fei, Malkin, Ida, Needhamsen, Maria, Xia, Yudong, Yuan, Wei, Bell, Christopher G., Ward, Kirsten, Liu, Yuan, Wang, Jun, Bell, Jordana T. and Spector, Tim D. (2016) Contribution of heritability and epigenetic factors to skeletal muscle mass variation in UK twins. Journal of Clinical Endocrinology & Metabolism, 1-10. (doi:10.1210/jc.2016-1219#sthash.K2fxG0cH.dpuf). (PMID:27144936)

Record type: Article

Abstract

Context: Skeletal muscle mass (SMM) is one of the major components of human body composition, with deviations from normal values often leading to sarcopenia.

Objective: Our major aim was to conduct a genome-wide DNA methylation study in an attempt to identify potential genomic regions associated with SMM.

Design: This was a mixed cross-sectional and longitudinal study.

Setting: Community-based study.

Participants: A total of 1550 middle-aged UK twin (monozygotic and dizygotic) twins, 297 of which were repeatedly measured participated in the study.

Main Outcome Measure: Appendicular lean mass assessed using DXA technology, and MeDIP-seq DNA methylation profiling genome-wide were obtained from each individual.

Results: Heritability estimate of SMM, with simultaneous adjustment for covariates obtained using variance decomposition analysis was h2=0.809±0.050. After quality control and analysis of longitudinal stability, the DNA methylation data comprised of 723,029 genomic sites, with positive correlations between repeated measurements (Rrepeated =0.114–0.905). Correlations between MZ and DZ twins were 0.51 and 0.38 at a genome-wide average, respectively and clearly increased with Rrepeated. Testing for DNA methylation association with SMM in 50 discordant MZ twins revealed 36,081 nominally significant results, of which the top-ranked 134 signals (P<0.01 and Rrepeated>0.40) were subjected to replication in the sample of 1,196 individuals. Seven SMM-methylation association signals replicated at a false discovery rate <0.1, and these were located in or near genes DNAH12, CAND1, CYP4F29P, ZFP64 which have previously been highlighted in muscle-related studies. Adjusting for age, smoking and blood cell heterogeneity did not alter significance of these associations.

Conclusion: This epigenome-wide study, testing longitudinally stable methylation sites discovered and replicated a number of associations between DNA methylation at CpG loci and skeletal muscle mass. Four replicated signals were related to genes with potential muscle functions, suggesting that the methylome of whole blood may be informative of SMM variation

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Accepted/In Press date: 21 April 2016
e-pub ahead of print date: 4 May 2016
Organisations: Human Development & Health, Centre for Biological Sciences, MRC Life-Course Epidemiology Unit

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Local EPrints ID: 395188
URI: http://eprints.soton.ac.uk/id/eprint/395188
ISSN: 0021-972X
PURE UUID: a96b99a2-425e-4956-a135-d79a5d9ff03e

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Date deposited: 25 May 2016 15:52
Last modified: 16 Dec 2019 19:54

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Contributors

Author: Gregory Livshits
Author: Fei Gao
Author: Ida Malkin
Author: Maria Needhamsen
Author: Yudong Xia
Author: Wei Yuan
Author: Christopher G. Bell
Author: Kirsten Ward
Author: Yuan Liu
Author: Jun Wang
Author: Jordana T. Bell
Author: Tim D. Spector

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