PreprintCited by 22

The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.

PRC2 clock: a universal epigenetic biomarker of aging and rejuvenation

Moqri, Mahdi, Cipriano, Andrea, Nachun, Daniel, Murty, Tara, de Sena Brandine, Guilherme, Rasouli, Sajede, Tarkhov, Andrei, Aberg, Karolina A., van den Oord, Edwin, Zhou, Wanding, Smith, Andrew, Mackall, Crystal, Gladyshev, Vadim, Horvath, Steve, Snyder, Michael P., Sebastiano, Vittorio·2022

Abstract

DNA methylation (DNAm) is one of the most reliable biomarkers for aging across many mammalian tissues. While the age-dependent global loss of DNAm has been well characterized, age-dependent DNAm gain is less specified. Multiple studies have demonstrated that polycomb repressive complex 2 (PRC2) targets are enriched among the CpG sites which gain methylation with age. However, a systematic whole-genome examination of all PRC2 targets in the context of aging methylome as well as whether these associations are pan-tissue or tissue-specific is lacking. Here, by analyzing DNAm data from different assays and from multiple young and old human and mouse tissues, we found that low-methylated regions (LMRs) which are highly bound by PRC2 in embryonic stem cells gain methylation with age in all examined somatic mitotic cells. We also estimated that this epigenetic change represents around 90% of the age-dependent DNAm gain genome-wide. Therefore, we propose the “PRC2 clock,” defined as the average DNAm in PRC2 LMRs, as a universal biomarker of cellular aging in somatic cells. In addition, we demonstrate the application of this biomarker in the evaluation of different anti-aging interventions, including dietary restriction and partial epigenetic reprogramming.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1101/2022.06.03.494609

Cites

10 of 10 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

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

Flagged first, then by citations

Show all 10 references

Research works printed but not linked: 36

  1. 2017, Biological Age Predictors, EBioMedicine, 21, 29, 10.1016/j.ebiom.2017.03.046 · DOI · Paper page
  2. 10.1038/s41576-018-0004-3 · DOI · Paper page
  3. 10.1016/j.molcel.2012.10.016 · DOI · Paper page
  4. Sziráki, A. , Tyshkovskiy, A. & Gladyshev, V. N. Global remodeling of the mouse DNA methylome during aging and in response to calorie restriction. Aging Cell 17, (2018). · DOI
  5. Johansson, Å. , Enroth, S. & Gyllensten, U. Continuous Aging of the Human DNA Methylome Throughout the Human Lifespan. PLoS ONE 8, (2013). · DOI
  6. Tanay, A. , O’donnell, A. H. , Damelin, M. & Bestor, T. H. Hyperconserved CpG domains underlie Polycomb-binding sites. www.pnas.org/cgi/content/full/ (2007). · DOI
  7. Long, H. K. et al. Epigenetic conservation at gene regulatory elements revealed by non-methylated DNA profiling in seven vertebrates. Elife 2013, (2013). · DOI
  8. 10.1016/j.cell.2013.04.022 · DOI
  9. 10.1038/ng.2836 · DOI · Paper page
  10. 10.1016/j.molcel.2020.04.018 · DOI
  11. 10.1016/j.molcel.2012.01.017 · DOI
  12. 10.1038/embor.2011.233 · DOI
  13. Lindroth, A. M. et al. Antagonism between DNA and H3K27 methylation at the imprinted Rasgrf1 locus. PLoS Genetics 4, (2008). · DOI
  14. 10.1016/j.cell.2010.10.012 · DOI · Paper page
  15. Wu, H. et al. Dnmt3a-Dependent Nonpromoter DNA Methylation Facilitates Transcription of Neurogenic Genes. https://www.science.org.
  16. Hagarman, J. A. , Motley, M. P. , Kristjansdottir, K. & Soloway, P. D. Coordinate Regulation of DNA Methylation and H3K27me3 in Mouse Embryonic Stem Cells. PLoS ONE 8, (2013). · DOI
  17. 10.1101/gr.103606.109 · DOI · Paper page
  18. 10.2217/epi-2015-0017 · DOI
  19. Horvath, H. & Horvath, S. DNA methylation age of human tissues and cell types. Genome Biology vol. 14 http://genomebiology.com//14/10/R115 (2013). · DOI · Paper page
  20. 10.1186/gb-2012-13-10-r97 · DOI
  21. 10.1080/15592294.2015.1040619 · DOI
  22. 10.1016/j.mad.2017.02.006 · DOI · Paper page
  23. 2021, Multi-omic profiling of primary mouse neutrophils predicts a pattern of sex-and age-related functional regulation, Nature Aging, 1, 715, 10.1038/s43587-021-00086-8 · DOI
  24. Rozenblit, M. et al. Evidence of accelerated epigenetic aging of breast tissues in patients with breast cancer is driven by CpGs associated with polycomb-related genes. Clinical Epigenetics 14, (2022). · DOI
  25. 10.1038/308274a0 · DOI
  26. 10.1038/ng.3811 · DOI
  27. 10.1038/s41576-022-00477-6 · DOI · Paper page
  28. Steinhardt, I. , Duncan, B. K. & Miller, J. H. Mutagenic deamination of cytosine residues in DNA. Biochem. biophys. Res. Commun vol. 60 (1974).
  29. 10.1038/nature12477 · DOI · Paper page
  30. Li, Y. et al. Genome-wide analyses reveal a role of Polycomb in promoting hypomethylation of DNA methylation valleys. Genome Biology 19, (2018). · DOI
  31. Jung, M. & Pfeifer, G. P. Aging and DNA methylation. BMC Biology 13, (2015). · DOI
  32. 10.1038/s41588-022-01063-6 · DOI
  33. de Sena Brandine, G. & Smith, A. D. Fast and memory-efficient mapping of short bisulfite sequencing reads using a two-letter alphabet. NAR Genomics and Bioinformatics 3, (2021). · DOI
  34. Song, Q. et al. A reference methylome database and analysis pipeline to facilitate integrative and comparative epigenomics. PLoS ONE 8, (2013). · DOI
  35. 10.1093/bioinformatics/btp352 · DOI · Paper page
  36. 10.1101/gr.136184.111 · DOI · Paper page

Cited by

Sorted by citations

See all 22

Metadata

Authors
Moqri, M., Cipriano, A., Nachun, D., Murty, T., de Sena Brandine, G., Rasouli, S., Tarkhov, A., Aberg, K. A., van den Oord, E., Zhou, W., Smith, A., Mackall, C., Gladyshev, V., Horvath, S., Snyder, M. P., & Sebastiano, V.
Publisher
openRxiv
Published
2022-06-05
Cited by
22
References
10
Type
Preprint

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