Literature DB >> 31138013

Human epigenetic ageing is logarithmic with time across the entire lifespan.

Sagi Snir1, Colin Farrell2, Matteo Pellegrini2.   

Abstract

Epigenetic changes during ageing have been characterized by multiple epigenetic clocks that allow the prediction of chronological age based on methylation status. Despite their accuracy and utility, epigenetic age biomarkers leave many questions about epigenetic ageing unanswered. Specifically, they do not permit the unbiased characterization of non-linear epigenetic ageing trends across entire life spans, a critical question underlying this field of research. Here we provide an integrated framework to address this question. Our model, inspired from evolutionary models, is able to account for acceleration/deceleration in epigenetic changes by fitting an individual's model age, the epigenetic age, which is related to chronological age in a non-linear fashion. Application of this model to DNA methylation data measured across broad age ranges, from before birth to old age, and from two tissue types, suggests a universal logarithmic trend characterizes epigenetic ageing across entire lifespans.

Entities:  

Keywords:  Aging; DNA methylation

Mesh:

Year:  2019        PMID: 31138013      PMCID: PMC6691990          DOI: 10.1080/15592294.2019.1623634

Source DB:  PubMed          Journal:  Epigenetics        ISSN: 1559-2294            Impact factor:   4.528


  29 in total

1.  The role of DNA methylation in mammalian epigenetics.

Authors:  P A Jones; D Takai
Journal:  Science       Date:  2001-08-10       Impact factor: 47.728

Review 2.  The mammalian epigenome.

Authors:  Bradley E Bernstein; Alexander Meissner; Eric S Lander
Journal:  Cell       Date:  2007-02-23       Impact factor: 41.582

3.  Tissue-specific dysregulation of DNA methylation in aging.

Authors:  Reid F Thompson; Gil Atzmon; Ciprian Gheorghe; Hong Qian Liang; Christina Lowes; John M Greally; Nir Barzilai
Journal:  Aging Cell       Date:  2010-05-22       Impact factor: 9.304

4.  Genome-wide methylation profiles reveal quantitative views of human aging rates.

Authors:  Gregory Hannum; Justin Guinney; Ling Zhao; Li Zhang; Guy Hughes; SriniVas Sadda; Brandy Klotzle; Marina Bibikova; Jian-Bing Fan; Yuan Gao; Rob Deconde; Menzies Chen; Indika Rajapakse; Stephen Friend; Trey Ideker; Kang Zhang
Journal:  Mol Cell       Date:  2012-11-21       Impact factor: 17.970

Review 5.  Epigenetic reprogramming in plant and animal development.

Authors:  Suhua Feng; Steven E Jacobsen; Wolf Reik
Journal:  Science       Date:  2010-10-29       Impact factor: 47.728

6.  Stability along with extreme variability in core genome evolution.

Authors:  Yuri I Wolf; Sagi Snir; Eugene V Koonin
Journal:  Genome Biol Evol       Date:  2013       Impact factor: 3.416

7.  Epigenetic memory at embryonic enhancers identified in DNA methylation maps from adult mouse tissues.

Authors:  Gary C Hon; Nisha Rajagopal; Yin Shen; David F McCleary; Feng Yue; My D Dang; Bing Ren
Journal:  Nat Genet       Date:  2013-09-01       Impact factor: 38.330

8.  Universal pacemaker of genome evolution.

Authors:  Sagi Snir; Yuri I Wolf; Eugene V Koonin
Journal:  PLoS Comput Biol       Date:  2012-11-29       Impact factor: 4.475

9.  Differential methylation of the TRPA1 promoter in pain sensitivity.

Authors:  J T Bell; A K Loomis; L M Butcher; F Gao; B Zhang; C L Hyde; J Sun; H Wu; K Ward; J Harris; S Scollen; M N Davies; L C Schalkwyk; J Mill; F M K Williams; N Li; P Deloukas; S Beck; S B McMahon; J Wang; S L John; T D Spector
Journal:  Nat Commun       Date:  2014       Impact factor: 14.919

10.  DNA methylation age of human tissues and cell types.

Authors:  Steve Horvath
Journal:  Genome Biol       Date:  2013       Impact factor: 13.583

View more
  16 in total

1.  The Epigenetic Pacemaker: modeling epigenetic states under an evolutionary framework.

Authors:  Colin Farrell; Sagi Snir; Matteo Pellegrini
Journal:  Bioinformatics       Date:  2020-11-01       Impact factor: 6.937

2.  The effects of age, sex, weight, and breed on canid methylomes.

Authors:  Liudmilla Rubbi; Haoxuan Zhang; Junxi Feng; Christopher He; Patrick Kurnia; Prashansa Ratan; Aakash Tammana; Sabina House; Michael Thompson; Colin Farrell; Sagi Snir; Daniel Stahler; Elaine A Ostrander; Bridgett M vonHoldt; Matteo Pellegrini
Journal:  Epigenetics       Date:  2022-05-03       Impact factor: 4.861

3.  Age-associated epigenetic change in chimpanzees and humans.

Authors:  Elaine E Guevara; Richard R Lawler; Nicky Staes; Cassandra M White; Chet C Sherwood; John J Ely; William D Hopkins; Brenda J Bradley
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2020-09-21       Impact factor: 6.237

Review 4.  No Time to Age: Uncoupling Aging from Chronological Time.

Authors:  Dana Larocca; Jieun Lee; Michael D West; Ivan Labat; Hal Sternberg
Journal:  Genes (Basel)       Date:  2021-04-21       Impact factor: 4.096

5.  New targeted approaches for epigenetic age predictions.

Authors:  Yang Han; Julia Franzen; Thomas Stiehl; Michael Gobs; Chao-Chung Kuo; Miloš Nikolić; Jan Hapala; Barbara Elisabeth Koop; Klaus Strathmann; Stefanie Ritz-Timme; Wolfgang Wagner
Journal:  BMC Biol       Date:  2020-06-24       Impact factor: 7.431

6.  Disentangling age-dependent DNA methylation: deterministic, stochastic, and nonlinear.

Authors:  O Vershinina; M G Bacalini; A Zaikin; C Franceschi; M Ivanchenko
Journal:  Sci Rep       Date:  2021-04-28       Impact factor: 4.379

7.  Epigenome-wide change and variation in DNA methylation in childhood: trajectories from birth to late adolescence.

Authors:  Rosa H Mulder; Alexander Neumann; Charlotte A M Cecil; Esther Walton; Lotte C Houtepen; Andrew J Simpkin; Jolien Rijlaarsdam; Bastiaan T Heijmans; Tom R Gaunt; Janine F Felix; Vincent W V Jaddoe; Marian J Bakermans-Kranenburg; Henning Tiemeier; Caroline L Relton; Marinus H van IJzendoorn; Matthew Suderman
Journal:  Hum Mol Genet       Date:  2021-03-25       Impact factor: 6.150

8.  Sleep and ageing: from human studies to rodent models.

Authors:  Laura E McKillop; Vladyslav V Vyazovskiy
Journal:  Curr Opin Physiol       Date:  2020-03-16

9.  Epigenetic pacemaker: closed form algebraic solutions.

Authors:  Sagi Snir
Journal:  BMC Genomics       Date:  2020-04-16       Impact factor: 3.969

10.  Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter.

Authors:  Imene Garali; Mourad Sahbatou; Antoine Daunay; Laura G Baudrin; Victor Renault; Yosra Bouyacoub; Jean-François Deleuze; Alexandre How-Kit
Journal:  Sci Rep       Date:  2020-09-24       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.