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Genetic and environmental causes of variation in epigenetic aging across the lifespan

DC Field Value Language
dc.contributor.authorLi, Shuai-
dc.contributor.authorNguyen, Tuong L-
dc.contributor.authorWong, Ee M-
dc.contributor.authorDugué, Pierre-Antoine-
dc.contributor.authorDite, Gillian S-
dc.contributor.authorArmstrong, Nicola J-
dc.contributor.authorCraig, Jeffrey M-
dc.contributor.authorMather, Karen A-
dc.contributor.authorSachdev, Perminder S-
dc.contributor.authorSaffery, Richard-
dc.contributor.authorSung, Joohon-
dc.contributor.authorTan, Qihua-
dc.contributor.authorThalamuthu, Anbupalam-
dc.contributor.authorMilne, Roger L-
dc.contributor.authorGiles, Graham G-
dc.contributor.authorSouthey, Melissa C-
dc.contributor.authorHopper, John L-
dc.date.accessioned2021-01-13T00:46:49Z-
dc.date.available2021-01-13T09:48:38Z-
dc.date.issued2020-10-22-
dc.identifier.citationClinical Epigenetics. 2020 Oct 22;12(1):158ko_KR
dc.identifier.issn1868-7083-
dc.identifier.urihttps://hdl.handle.net/10371/171618-
dc.description.abstractBackground
DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan.

Results
In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were −0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI −10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation.

Conclusions
Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.
ko_KR
dc.description.sponsorshipThis work was supported by grants from the Victorian Cancer Agency (Grant No. ECRF19020), Cancer Council Victoria (Grant No. 180626), and National Health and Medical Research Council (NHMRC, Grant No. 057873). SL is a Victorian Cancer Agency Early Career Research Fellow (ECRF19020). SL and TLN were supported by the Cancer Council Victoria Postdoctoral Research
Fellowship and the Picchi Award from the Victorian Comprehensive Cancer Centre. TLN was supported by the Cure Cancer Australia (APP1159399). MCS is a NHMRC Senior Research Fellow (APP1155163). JLH is a NHMRC Senior Principal Research Fellow. The PETS was supported by grants from the NHMRC (Grant No. 1146333 to JC). The AMDTSS was facilitated through access to Twins Research Australia, a national resource supported by a Centre of Research
Excellence Gran (Grant No. 1079102) from the NHMRC. The AMDTSS was supported by NHMRC (Grant Nos. 1050561 and 1079102), Cancer Australia and National Breast Cancer Foundation (Grant No. 509307). The OATS was funded by a NHMRC and Australian Research Council (ARC) Strategic Award Grant of the Ageing Well, Ageing Productively Program (Grant No. 401162) and NHMRC Project Grants (Grant Nos. 1045325 and 1085606). The OATS was facilitated through Twins Research Australia, a national resource in part supported by a Centre for Research Excellence Grant (Grant No. 1079102) from the NHMRC. The MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria. The MCCS was further augmented by NHMRC grants numbers 209057 and 396414 and by infrastructure provided by the Cancer Council Victoria. Additional support was received from NHMRC Project Grant Nos. 1011618, 1026892, 1027505, 1050198, and 1043616. The MCCS research was in part supported by a Program Grant from the NHMRC (Grant No. 1074383) and an award from Victorian Breast Cancer Research Consortium (PI MCS).
ko_KR
dc.language.isoenko_KR
dc.publisherBMCko_KR
dc.subjectAging-
dc.subjectEpigenetic aging-
dc.subjectBiological age-
dc.subjectEpigenetic clock-
dc.subjectDNA methylation-
dc.subjectTwin study-
dc.titleGenetic and environmental causes of variation in epigenetic aging across the lifespanko_KR
dc.typeArticleko_KR
dc.contributor.AlternativeAuthor성주혼-
dc.identifier.doi10.1186/s13148-020-00950-1-
dc.citation.journaltitleClinical Epigeneticsko_KR
dc.language.rfc3066en-
dc.rights.holderThe Author(s)-
dc.date.updated2020-10-25T04:16:34Z-
dc.citation.number1ko_KR
dc.citation.startpage158ko_KR
dc.citation.volume12ko_KR
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