The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Age-associated DNA methylation in pediatric populations
Open accessAbstract
DNA methylation (DNAm) plays diverse roles in human biology, but this dynamic epigenetic mark remains far from fully characterized. Although earlier studies uncovered loci that undergo age-associated DNAm changes in adults, little is known about such changes during childhood. Despite profound DNAm plasticity during embryogenesis, monozygotic twins show indistinguishable childhood methylation, suggesting that DNAm is highly coordinated throughout early development. Here we examine the methylation of 27,578 CpG dinucleotides in peripheral blood DNA from a cross-sectional study of 398 boys, aged 3–17 yr, and find significant age-associated changes in DNAm at 2078 loci. These findings correspond well with pyrosequencing data and replicate in a second pediatric population (N = 78). Moreover, we report a deficit of age-related loci on the X chromosome, a preference for specific nucleotides immediately surrounding the interrogated CpG dinucleotide, and a primary association with developmental and immune ontological functions. Meta-analysis (N = 1158) with two adult populations reveals that despite a significant overlap of age-associated loci, most methylation changes do not follow a lifelong linear pattern due to a threefold to fourfold higher rate of change in children compared with adults; consequently, the vast majority of changes are more accurately modeled as a function of logarithmic age. We therefore conclude that age-related DNAm changes in peripheral blood occur more rapidly during childhood and are imperfectly accounted for by statistical corrections that are linear in age, further suggesting that future DNAm studies should be matched closely for age.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Jaenisch, R., & Bird, A. (2003) · Nature Genetics · doi:10.1038/ng1089 · Cited by 6,325
Conversion of 5-Methylcytosine to 5-Hydroxymethylcytosine in Mammalian DNA by MLL Partner TET1
Tahiliani, M., Koh, K. P., Shen, Y., Pastor, W. A., Bandukwala, H., Brudno, Y., Agarwal, S., Iyer, L. M., Liu, D. R., Aravind, L., et al. (2009) · Science · doi:10.1126/science.1170116 · Cited by 5,836
Epigenetic differences arise during the lifetime of monozygotic twins
Fraga, M. F., Ballestar, E., Paz, M. F., Ropero, S., Setien, F., Ballestar, M. L., Heine-Suñer, D., Cigudosa, J. C., Urioste, M., Benitez, J., et al. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0500398102 · Cited by 3,602
Du, P., Zhang, X., Huang, C.-C., Jafari, N., Kibbe, W. A., Hou, L., & Lin, S. M. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-587 · Cited by 2,136
Stability and flexibility of epigenetic gene regulation in mammalian development
Reik, W. (2007) · Nature · doi:10.1038/nature05918 · Cited by 1,963
Promoter Hypermethylation and BRCA1 Inactivation in Sporadic Breast and Ovarian Tumors
Esteller, M. (2000) · Journal of the National Cancer Institute · doi:10.1093/jnci/92.7.564 · Cited by 1,233
Methylation of the oestrogen receptor CpG island links ageing and neoplasia in human colon
Issa, J.-P. J., Ottaviano, Y. L., Celano, P., Hamilton, S. R., Davidson, N. E., & Baylin, S. B. (1994) · Nature Genetics · doi:10.1038/ng0894-536 · Cited by 1,191
Epigenetics and aging: the targets and the marks
Fraga, M. F., & Esteller, M. (2007) · Trends in Genetics · doi:10.1016/j.tig.2007.05.008 · Cited by 690
Dual functions of Tet1 in transcriptional regulation in mouse embryonic stem cells
Wu, H., D’Alessio, A. C., Ito, S., Xia, K., Wang, Z., Cui, K., Zhao, K., Eve Sun, Y., & Zhang, Y. (2011) · Nature · doi:10.1038/nature09934 · Cited by 646
Dnmt3a-Dependent Nonpromoter DNA Methylation Facilitates Transcription of Neurogenic Genes
Wu, H., Coskun, V., Tao, J., Xie, W., Ge, W., Yoshikawa, K., Li, E., Zhang, Y., & Sun, Y. E. (2010) · Science · doi:10.1126/science.1190485 · Cited by 604
Cited by
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
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
Accounting for cellular heterogeneity is critical in epigenome-wide association studies
Jaffe, A. E., & Irizarry, R. A. (2014) · Genome Biology · doi:10.1186/gb-2014-15-2-r31 · Cited by 1,067
DNA methylation aging clocks: challenges and recommendations
Bell, C. G., Lowe, R., Adams, P. D., Baccarelli, A. A., Beck, S., Bell, J. T., Christensen, B. C., Gladyshev, V. N., Heijmans, B. T., Horvath, S., et al. (2019) · Genome Biology · doi:10.1186/s13059-019-1824-y · Cited by 1,025
DNA methylation and healthy human aging
Jones, M. J., Goodman, S. J., & Kobor, M. S. (2015) · Aging Cell · doi:10.1111/acel.12349 · Cited by 928
Metadata
- Authors
- Alisch, R. S., Barwick, B. G., Chopra, P., Myrick, L. K., Satten, G. A., Conneely, K. N., & Warren, S. T.
- Venue
- Genome Research
- Publisher
- Cold Spring Harbor Laboratory
- Published
- 2012-02-01
- Volume
- 22
- Issue
- 4
- Pages
- 623-632
- ISSN
- 1088-9051 (ISSN-L)
- OpenAlex
- W2014945558
- Cited by
- 389
- References
- 11
- Type
- posted content
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Age-associated DNA methylation in pediatric populations. https://app.cochat.ai/papers/10.1101/gr.125187.111
- The paper
- Alisch, R. S., Barwick, B. G., Chopra, P., Myrick, L. K., Satten, G. A., Conneely, K. N., & Warren, S. T. (2012). Age-associated DNA methylation in pediatric populations. Genome Research. https://doi.org/10.1101/gr.125187.111
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.