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Prenatal and early life influences on epigenetic age in children: a study of mother–offspring pairs from two cohort studies
Open accessAbstract
DNA methylation-based biomarkers of aging are highly correlated with actual age. Departures of methylation-estimated age from actual age can be used to define epigenetic measures of child development or age acceleration (AA) in adults. Very little is known about genetic or environmental determinants of these epigenetic measures of aging. We obtained DNA methylation profiles using Infinium HumanMethylation450 BeadChips across five time-points in 1018 mother-child pairs from the Avon Longitudinal Study of Parents and Children. Using the Horvath age estimation method, we calculated epigenetic age for these samples. AA was defined as the residuals from regressing epigenetic age on actual age. AA was tested for associations with cross-sectional clinical variables in children. We identified associations between AA and sex, birth weight, birth by caesarean section and several maternal characteristics in pregnancy, namely smoking, weight, BMI, selenium and cholesterol level. Offspring of non-drinkers had higher AA on average but this difference appeared to resolve during childhood. The associations between sex, birth weight and AA found in ARIES were replicated in an independent cohort (GOYA). In children, epigenetic AA measures are associated with several clinically relevant variables, and early life exposures appear to be associated with changes in AA during adolescence. Further research into epigenetic aging, including the use of causal inference methods, is required to better our understanding of aging.
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“Placental and offspring epigenetic signatures, telomere biology and mitochondrial function provide measurable molecular readouts of prenatal exposure at birth or during childhood [116,117,118].”
From Placental Pathophysiology and Developmental Programming of Adult Cardiometabolic Risk: A Narrative Review of Pregnancy Exposures (2026) · cites this paper as [116]
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Random-Effects Models for Longitudinal Data
Laird, N. M., & Ware, J. H. (1982) · Biometrics · doi:10.2307/2529876 · Cited by 8,923
DNA methylation age of human tissues and cell types
Horvath, S. (2013) · Genome Biology · doi:10.1186/gb-2013-14-10-r115 · Cited by 7,075
Self-citationDavey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882
Common SNPs explain a large proportion of the heritability for human height
Yang, J., Benyamin, B., McEvoy, B. P., Gordon, S., Henders, A. K., Nyholt, D. R., Madden, P. A., Heath, A. C., Martin, N. G., Montgomery, G. W., et al. (2010) · Nature Genetics · doi:10.1038/ng.608 · Cited by 4,446
Genome-wide methylation profiles reveal quantitative views of human aging rates
Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J.-B., Gao, Y., et al. (2013) · Molecular Cell · doi:10.1016/j.molcel.2012.10.016 · Cited by 4,270
Boyd, A., Golding, J., Macleod, J., Lawlor, D. A., Fraser, A., Henderson, J., Molloy, L., Ness, A., Ring, S., & Davey Smith, G. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dys064 · Cited by 2,996
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Fraser, A., Macdonald-Wallis, C., Tilling, K., Boyd, A., Golding, J., Davey Smith, G., Henderson, J., Macleod, J., Molloy, L., Ness, A., et al. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dys066 · Cited by 2,494
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Visscher, P. M., Hill, W. G., & Wray, N. R. (2008) · Nature Reviews Genetics · doi:10.1038/nrg2322 · Cited by 1,921
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Marioni, R. E., Shah, S., McRae, A. F., Chen, B. H., Colicino, E., Harris, S. E., Gibson, J., Henders, A. K., Redmond, P., Cox, S. R., et al. (2015) · Genome Biology · doi:10.1186/s13059-015-0584-6 · Cited by 1,261
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Lu, A. T.-H., Xue, L., Salfati, E., Chen, B. H., Ferrucci, L., Levy, D. A., Joehanes, R., Murabito, J. M., Kiel, D. P., Tsai, P.-C., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/157776 · Cited by 1
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Howard, B. H., Hirai, T. H., & RUSSANOVA, V. R. (2018) · PLoS ONE · doi:10.1371/journal.pone.0191033
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Tang, R., Howe, L. D., Suderman, M. J., Relton, C. L., Crawford, A. A., & Houtepen, L. C. (2020) · Yearbook of pediatric endocrinology · doi:10.1530/ey.17.8.13 · Cited by 1
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Strawn, M., Safranski, T. J., & Behura, S. K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.11.28.518197
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Daley, D., Vasileva, D., & Greenwood, C. M. T. (2023) · doi:10.22541/au.167954587.70061237/v1
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Meir, A. Y., Wang, G., Hong, X., Wang, X., & Liang, L. (2023) · medRxiv · doi:10.1101/2023.11.02.23297965
Lux, V. (2024) · SpringerBriefs in psychology · doi:10.1007/978-3-031-55229-8_5
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Tang, R., Howe, L. D., Suderman, M. J., Relton, C. L., Crawford, A. A., & Houtepen, L. C. (2020) · Figshare · doi:10.6084/m9.figshare.12096045
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Maddock, J., Castillo-Fernandez, J., Wong, A., Ploubidis, G. B., Kuh, D. J., Bell, J. T., & Hardy, R. (2021) · Figshare · doi:10.6084/m9.figshare.15139238
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689694
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689706
Ryan, C. P., Rege, R. J., Lee, N. R., Carba, D. B., Kobor, M. S., MacIsaac, J. L., Lin, D. S., Atashzay, P., & Kuzawa, C. W. (2022) · Figshare · doi:10.6084/m9.figshare.20131201
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689700
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25357977
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.25357850
Banszerus, V. L., König, M., Landmesser, U., Vetter, V. M., & Demuth, I. (2023) · Figshare · doi:10.6084/m9.figshare.22616038
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689703
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689691
Peters, T. J., Meyer, B. A., Ryan, L. A., Achinger-Kawecka, J., Song, J. Z., Campbell, E. M., Qu, W., Nair, S. S., Loi-Luu, P., Stricker, P., et al. (2024) · Figshare · doi:10.6084/m9.figshare.26689697
Bozack, A. K., Rifas-Shiman, S. L., Gold, D. R., Laubach, Z. M., Perng, W., Hivert, M., & Cárdenas, A. (2023) · Figshare · doi:10.6084/m9.figshare.22622047
Bergstrom, K., Smith, H., Johnson, R. K., Vanderlinden, L. A., Seifert, J. A., Hohsfield, K. R., Yang, I. V., Slack, S. D., Dong, F., Kechris, K. J., et al. (2026) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2025-005725
Early-life factors and epigenetic precursors of childhood leukemia
Novoloaca, A. (2020) · theses.fr (ABES) · doi:10.70675/4286201fz357fz4b0ez8dbfzdc0b44a46cae
López-Cervantes, J. P., Knudsen, G. T. M., Kitaba, N. T., Lønnebotn, M., Bertelsen, R. J., Accordini, S., Janson, C., Dharmage, S. C., Franklin, K. A., González, F. J. C., et al. (2026) · Environmental Advances · doi:10.1016/j.envadv.2026.100739
Maskey, S., Arzu, J. L., Chen, A., Kelsey, K. T., Langevin, S. M., Cecil, K. M., Yolton, K. A., Braun, J. M., & Sears, C. G. (2026) · SLEEP Advances · doi:10.1093/sleepadvances/zpag090
Everly, C. F., Allen, T. K., Skaar, D. A., Corliss, B. A., Jima, D. D., Maguire, R. L., Jadallah, H., Jirtle, R. L., Murphy, S. K., Tzeng, J., et al. (2026) · medRxiv · doi:10.64898/2026.09.02.26362065
Everly, C. F., Allen, T. K., Skaar, D. A., Corliss, B. A., Jima, D. D., Maguire, R. L., Jadallah, H., Jirtle, R. L., Murphy, S. K., Tzeng, J., et al. (2026) · Epigenetics · doi:10.1080/15592294.2026.2732477
Metal Mixtures and Epigenetic Age Acceleration in Children: Evidence from a Population-Based CohortPreprint
Tung, P. W., Quaid, M., Muldoon, A., Haque, S. E., Islam, T., Sarwar, G., Shahriar, H., Jackson, B. P., Liu, C., Pierce, B., et al. (2026) · SSRN Electronic Journal · doi:10.2139/ssrn.7576811
Harvison, M., & Silveira, P. P. (2026) · Handbook of clinical neurology · doi:10.1016/b978-0-443-19043-8.00004-9
Metadata
- Authors
- Simpkin, A. J., Hemani, G., Suderman, M., Gaunt, T. R., Lyttleton, O., Mcardle, W. L., Ring, S. M., Sharp, G. C., Tilling, K., Horvath, S., Kunze, S., Peters, A., Waldenberger, M., Ward-Caviness, C., Nohr, E. A., Sørensen, T. I. A., Relton, C. L., & Smith, G. D.
- Affiliations
- MRC Integrative Epidemiology Unit (GB)
- University of Bristol (GB)
- University of California, Los Angeles (US)
- Helmholtz Munich (DE)
- University of Southern Denmark (DK)
- University of Copenhagen (DK)
- Corresponding author
- Simpkin, Andrew J.
- ORCID
- Venue
- Human Molecular Genetics
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-11-05
- Volume
- 25
- Issue
- 1
- Pages
- 191-201
- ISSN
- 0964-6906 (ISSN-L)
- 1460-2083
- PMC
- PMC4690495
- OpenAlex
- W2158554646
- Cited by
- 246
- References
- 31
- Citations by year
- 2026: 14 · 2025: 7 · 2024: 24 · 2023: 22 · 2022: 18 · 2021: 30 · 2020: 57 · 2019: 19 · 2018: 22 · 2017: 21 · 2016: 11 · 2015: 1
- FWCI
- 7.96
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by
- Locations
- Human Molecular Genetics (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- University of Southern Denmark Research Portal (University of Southern Denmark) (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Bristol Research (University of Bristol) (publishedVersion, cc-by)
- eScholarship (California Digital Library) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion, cc-by)
- Site cant be reached (submittedVersion, cc-by)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Explore Bristol Research (submittedVersion, cc-by)
- Newcastle University ePrints (Newcastle Univesity) (cc-by)
- Funders
- UK Economic & Social Research Council (RES-060-23-0011)
- UK Medical Research Council (G0601625, G0600705 and MR/L011824/1)
- European Research Council (269874)
- the BBSRC (BBI025751/1 and BB/I025263/1)
- the Medical Research Council (MRC) and the Wellcome Trust (102215/2/13/1)
- NIH
- the auspices of the MRC Integrative Epidemiology Unit at the University of Bristol (MC_UU_12013/2, MC_UU_12013/8, MRC_UU_12013/9)
- German Federal Ministry of Education and Research (01ZX1313A-2014)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Birth, Development, and Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Syndromes and Imprinting
- Keywords
- epigenetic age, accelerated aging, DNA methylation, prenatal exposure, early life exposure, mother-child pairs, birth weight, cesarean section, maternal smoking, maternal cholesterol, sex differences, adolescence, child development, Avon Longitudinal Study of Parents and Children
- MeSH terms
- Aging, Birth Weight, Child, Humans, Longitudinal Studies, Mothers, Cohort Studies, DNA Methylation, Epigenesis, Genetic
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