The DOI matches its Crossref record; 17 of the 17 references it cites were found in a registry or an index.
Longitudinal, genome-scale analysis of DNA methylation in twins from birth to 18 months of age reveals rapid epigenetic change in early life and pair-specific effects of discordance
Open accessAbstract
Background: The extent to which development- and age-associated epigenetic changes are influenced by genetic, environmental and stochastic factors remains to be discovered. Twins provide an ideal model with which to investigate these influences but previous cross-sectional twin studies provide contradictory evidence of within-pair epigenetic drift over time. Longitudinal twin studies can potentially address this discrepancy. Results: In a pilot, genome-scale study of DNA from buccal epithelium, a relatively homogeneous tissue, we show that one-third of the CpGs assayed show dynamic methylation between birth and 18 months. Although all classes of annotated genomic regions assessed show an increase in DNA methylation over time, probes located in intragenic regions, enhancers and low-density CpG promoters are significantly over-represented, while CpG islands and high-CpG density promoters are depleted among the most dynamic probes. Comparison of co-twins demonstrated that within-pair drift in DNA methylation in our cohort is specific to a subset of pairs, who show more differences at 18 months. The rest of the pairs show either minimal change in methylation discordance, or more similar, converging methylation profiles at 18 months. As with age-associated regions, sites that change in their level of within-pair discordance between birth and 18 months are enriched in genes involved in development, but the average magnitude of change is smaller than for longitudinal change. Conclusions: Our findings suggest that DNA methylation in buccal epithelium is influenced by non-shared stochastic and environmental factors that could reflect a degree of epigenetic plasticity within an otherwise constrained developmental program.
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
Smyth, G. K. (2004) · Statistical Applications in Genetics and Molecular Biology · doi:10.2202/1544-6115.1027 · Cited by 11,829
limma: Linear Models for Microarray Data
Smyth, G. K. (2005) · Statistics for Biology and Health · doi:10.1007/0-387-29362-0_23 · Cited by 5,796
GREAT improves functional interpretation of cis-regulatory regions
McLean, C. Y., Bristor, D., Hiller, M., Clarke, S. L., Schaar, B. T., Lowe, C. B., Wenger, A. M., & Bejerano, G. (2010) · Nature Biotechnology · doi:10.1038/nbt.1630 · Cited by 4,502
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
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
GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists
Eden, E., Navon, R., Steinfeld, I., Lipson, D., & Yakhini, Z. (2009) · BMC Bioinformatics · doi:10.1186/1471-2105-10-48 · Cited by 3,356
Genome-scale DNA methylation maps of pluripotent and differentiated cells
Meissner, A., Mikkelsen, T. S., Gu, H., Wernig, M., Hanna, J., Sivachenko, A., Zhang, X., Bernstein, B. E., Nusbaum, C., Jaffe, D. B., et al. (2008) · Nature · doi:10.1038/nature07107 · Cited by 2,536
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
High density DNA methylation array with single CpG site resolution
Bibikova, M., Barnes, B., Tsan, C., Ho, V., Klotzle, B., Le, J. M., Delano, D., Zhang, L., Schroth, G. P., Gunderson, K. L., et al. (2011) · Genomics · doi:10.1016/j.ygeno.2011.07.007 · Cited by 1,727 · cited 1×
“We have used the Infinium HumanMethylation450 BeadChip (HM450) platform, which interrogates >485,000 CpG dinucleotides and contains probes from CpG islands, shores (2 kb regions flanking CpG islands), shelves (2 kb regions flanking shores), sites from 1,500 bp upstream of transcription start sites through to gene bodi…”
MethodPhenotypic plasticity and the epigenetics of human disease
Feinberg, A. P. (2007) · Nature · doi:10.1038/nature05919 · Cited by 1,613
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
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
Correlation of an epigenetic mitotic clock with cancer risk
Yang, Z., Wong, A., Kuh, D., Paul, D. S., Rakyan, V. K., Leslie, R. D., Zheng, S. C., Widschwendter, M., Beck, S., & Teschendorff, A. E. (2016) · Genome Biology · doi:10.1186/s13059-016-1064-3 · Cited by 325
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: A Comprehensive Review
Cortes Rivera, M., Mastronardi, C., Silva-Aldana, C., Arcos-Burgos, M., & Lidbury, B. (2019) · Diagnostics · doi:10.3390/diagnostics9030091 · Cited by 313
Metadata
- Authors
- Martino, D., Loke, Y. J., Gordon, L., Ollikainen, M., Cruickshank, M. N., Saffery, R., & Craig, J. M.
- Venue
- Genome Biology
- Published
- 2013-05-22
- Volume
- 14
- Issue
- 5
- Pages
- R42-R42
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- OpenAlex
- W2097743364
- Cited by
- 187
- References
- 17
- FWCI
- 10.76
- Type
- journal article
- Language
- en
- Open access
- gold
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: Longitudinal, genome-scale analysis of DNA methylation in twins from birth to 18 months of age reveals rapid epigenetic change in early life and pair-specific effects of discordance. https://app.cochat.ai/papers/10.1186/gb-2013-14-5-r42
- The paper
- Martino, D., Loke, Y. J., Gordon, L., Ollikainen, M., Cruickshank, M. N., Saffery, R., & Craig, J. M. (2013). Longitudinal, genome-scale analysis of DNA methylation in twins from birth to 18 months of age reveals rapid epigenetic change in early life and pair-specific effects of discordance. Genome Biology. https://doi.org/10.1186/gb-2013-14-5-r42
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.