Literature DB >> 35118376

The relationship between ageing and changes in the human blood and brain methylomes.

Patrick Bryant1, Arne Elofsson1.   

Abstract

Changes in DNA methylation have been found to be strongly correlated with age, enabling the creation of 'epigenetic clocks'. Previously, studies on the relationship between ageing and DNA methylation have assumed a linear relationship. Here, we show that several markers show a non-linear behaviour. In particular, we observe a tendency for saturation with age, especially in the cerebellum. Further, we show that the relationships between significant methylation changes and ageing are different in different tissues. We suggest a straightforward method of assessing all methylation-age relationships and cluster them according to their relative fold change. Our fold change selection outperforms the most common epigenetic clocks in predicting age for the cerebellum, but not for Blood or the Frontal Cortex. Further, we find that the saturation of methylation observed at older ages for the cerebellum explains why epigenetic clocks consistently underestimate the age there. The findings imply that assuming linear correlations might cause biologically important markers to be missed.
© The Author(s) 2022. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics.

Entities:  

Year:  2022        PMID: 35118376      PMCID: PMC8808541          DOI: 10.1093/nargab/lqac001

Source DB:  PubMed          Journal:  NAR Genom Bioinform        ISSN: 2631-9268


  19 in total

1.  Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain.

Authors:  J Raphael Gibbs; Marcel P van der Brug; Dena G Hernandez; Bryan J Traynor; Michael A Nalls; Shiao-Lin Lai; Sampath Arepalli; Allissa Dillman; Ian P Rafferty; Juan Troncoso; Robert Johnson; H Ronald Zielke; Luigi Ferrucci; Dan L Longo; Mark R Cookson; Andrew B Singleton
Journal:  PLoS Genet       Date:  2010-05-13       Impact factor: 5.917

2.  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

3.  Age-related variations in the methylome associated with gene expression in human monocytes and T cells.

Authors:  Lindsay M Reynolds; Jackson R Taylor; Jingzhong Ding; Kurt Lohman; Craig Johnson; David Siscovick; Gregory Burke; Wendy Post; Steven Shea; David R Jacobs; Hendrik Stunnenberg; Stephen B Kritchevsky; Ina Hoeschele; Charles E McCall; David Herrington; Russell P Tracy; Yongmei Liu
Journal:  Nat Commun       Date:  2014-11-18       Impact factor: 14.919

4.  Consistent inverse correlation between DNA methylation of the first intron and gene expression across tissues and species.

Authors:  Dafni Anastasiadi; Anna Esteve-Codina; Francesc Piferrer
Journal:  Epigenetics Chromatin       Date:  2018-06-29       Impact factor: 4.954

5.  Human Age Prediction Based on DNA Methylation Using a Gradient Boosting Regressor.

Authors:  Xingyan Li; Weidong Li; Yan Xu
Journal:  Genes (Basel)       Date:  2018-08-21       Impact factor: 4.096

6.  PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools.

Authors:  Huaiyu Mi; Anushya Muruganujan; Dustin Ebert; Xiaosong Huang; Paul D Thomas
Journal:  Nucleic Acids Res       Date:  2019-01-08       Impact factor: 16.971

7.  Systematic underestimation of the epigenetic clock and age acceleration in older subjects.

Authors:  Louis Y El Khoury; Tyler Gorrie-Stone; Melissa Smart; Amanda Hughes; Yanchun Bao; Alexandria Andrayas; Joe Burrage; Eilis Hannon; Meena Kumari; Jonathan Mill; Leonard C Schalkwyk
Journal:  Genome Biol       Date:  2019-12-17       Impact factor: 13.583

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

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

9.  Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up.

Authors:  Xia Li; Alexander Ploner; Yunzhang Wang; Patrik Ke Magnusson; Chandra Reynolds; Deborah Finkel; Nancy L Pedersen; Juulia Jylhävä; Sara Hägg
Journal:  Elife       Date:  2020-02-11       Impact factor: 8.140

10.  Blood DNA methylation sites predict death risk in a longitudinal study of 12, 300 individuals.

Authors:  Elena Colicino; Riccardo Marioni; Cavin Ward-Caviness; Rahul Gondalia; Weihua Guan; Brian Chen; Pei-Chien Tsai; Tianxiao Huan; Gao Xu; Agha Golareh; Joel Schwartz; Pantel Vokonas; Allan Just; John M Starr; Allan F McRae; Naomi R Wray; Peter M Visscher; Jan Bressler; Wen Zhang; Toshiko Tanaka; Ann Zenobia Moore; Luke C Pilling; Guosheng Zhang; James D Stewart; Yun Li; Lifang Hou; Juan Castillo-Fernandez; Tim Spector; Douglas P Kiel; Joanne M Murabito; Chunyu Liu; Mike Mendelson; Tim Assimes; Devin Absher; Phil S Tsaho; Ake T Lu; Luigi Ferrucci; Rory Wilson; Melanie Waldenberger; Holger Prokisch; Stefania Bandinelli; Jordana T Bell; Daniel Levy; Ian J Deary; Steve Horvath; Jim Pankow; Annette Peters; Eric A Whitsel; Andrea Baccarelli
Journal:  Aging (Albany NY)       Date:  2020-07-22       Impact factor: 5.682

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