Literature DB >> 33384442

Targeted methods for epigenetic age predictions in mice.

Yang Han1,2, Miloš Nikolić1,2, Michael Gobs1,2, Julia Franzen1,2, Gerald de Haan3, Hartmut Geiger4, Wolfgang Wagner5,6.   

Abstract

Age-associated DNA methylation reflects aspect of biological aging-therefore epigenetic clocks for mice can elucidate how the aging process in this model organism is affected by specific treatments or genetic background. Initially, age-predictors for mice were trained for genome-wide DNA methylation profiles and we have recently described a targeted assay based on pyrosequencing of DNA methylation at only three age-associated genomic regions. Here, we established alternative approaches using droplet digital PCR (ddPCR) and barcoded bisulfite amplicon sequencing (BBA-seq). At individual CG dinucleotides (CpGs) the correlation of DNA methylation with chronological age was slightly higher for pyrosequencing and ddPCR as compared to BBA-seq. On the other hand, BBA-seq revealed that neighboring CpGs tend to be stochastically modified at murine age-associated regions. Furthermore, the binary sequel of methylated and non-methylated CpGs in individual reads can be used for single-read predictions, which may reflect heterogeneity in epigenetic aging. In comparison to C57BL/6 mice the single-read age-predictions using BBA-seq were also accelerated in the shorter-lived DBA/2 mice, and in C57BL/6 mice with a lifespan quantitative trait locus of DBA/2 mice. Taken together, we describe alternative targeted methods for epigenetic age predictions that provide new perspectives for aging-intervention studies in mice.

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Year:  2020        PMID: 33384442      PMCID: PMC7775437          DOI: 10.1038/s41598-020-79509-2

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  37 in total

1.  Detection and measurement of PCR bias in quantitative methylation analysis of bisulphite-treated DNA.

Authors:  P M Warnecke; C Stirzaker; J R Melki; D S Millar; C L Paul; S J Clark
Journal:  Nucleic Acids Res       Date:  1997-11-01       Impact factor: 16.971

2.  Proof of concept study of age-dependent DNA methylation markers across different tissues by massive parallel sequencing.

Authors:  Jana Naue; Timo Sänger; Huub C J Hoefsloot; Sabine Lutz-Bonengel; Ate D Kloosterman; Pernette J Verschure
Journal:  Forensic Sci Int Genet       Date:  2018-07-07       Impact factor: 4.882

Review 3.  Principles of DNA methylation and their implications for biology and medicine.

Authors:  Yuval Dor; Howard Cedar
Journal:  Lancet       Date:  2018-08-09       Impact factor: 79.321

Review 4.  DNA methylation-based biomarkers and the epigenetic clock theory of ageing.

Authors:  Steve Horvath; Kenneth Raj
Journal:  Nat Rev Genet       Date:  2018-06       Impact factor: 53.242

5.  DNA methylation age of blood predicts all-cause mortality in later life.

Authors:  Riccardo E Marioni; Sonia Shah; Allan F McRae; Brian H Chen; Elena Colicino; Sarah E Harris; Jude Gibson; Anjali K Henders; Paul Redmond; Simon R Cox; Alison Pattie; Janie Corley; Lee Murphy; Nicholas G Martin; Grant W Montgomery; Andrew P Feinberg; M Daniele Fallin; Michael L Multhaup; Andrew E Jaffe; Roby Joehanes; Joel Schwartz; Allan C Just; Kathryn L Lunetta; Joanne M Murabito; John M Starr; Steve Horvath; Andrea A Baccarelli; Daniel Levy; Peter M Visscher; Naomi R Wray; Ian J Deary
Journal:  Genome Biol       Date:  2015-01-30       Impact factor: 13.583

6.  Accelerated epigenetic aging in Down syndrome.

Authors:  Steve Horvath; Paolo Garagnani; Maria Giulia Bacalini; Chiara Pirazzini; Stefano Salvioli; Davide Gentilini; Anna Maria Di Blasio; Cristina Giuliani; Spencer Tung; Harry V Vinters; Claudio Franceschi
Journal:  Aging Cell       Date:  2015-02-09       Impact factor: 9.304

7.  Mapping DNA methylation with high-throughput nanopore sequencing.

Authors:  Arthur C Rand; Miten Jain; Jordan M Eizenga; Audrey Musselman-Brown; Hugh E Olsen; Mark Akeson; Benedict Paten
Journal:  Nat Methods       Date:  2017-02-20       Impact factor: 28.547

8.  Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm.

Authors:  Daniel W Belsky; Avshalom Caspi; Louise Arseneault; Andrea Baccarelli; David L Corcoran; Xu Gao; Eiliss Hannon; Hona Lee Harrington; Line Jh Rasmussen; Renate Houts; Kim Huffman; William E Kraus; Dayoon Kwon; Jonathan Mill; Carl F Pieper; Joseph A Prinz; Richie Poulton; Joel Schwartz; Karen Sugden; Pantel Vokonas; Benjamin S Williams; Terrie E Moffitt
Journal:  Elife       Date:  2020-05-05       Impact factor: 8.140

9.  Non-invasive detection of human cardiomyocyte death using methylation patterns of circulating DNA.

Authors:  Hai Zemmour; David Planer; Judith Magenheim; Joshua Moss; Daniel Neiman; Dan Gilon; Amit Korach; Benjamin Glaser; Ruth Shemer; Giora Landesberg; Yuval Dor
Journal:  Nat Commun       Date:  2018-04-24       Impact factor: 14.919

10.  Inhibition of Cdc42 activity extends lifespan and decreases circulating inflammatory cytokines in aged female C57BL/6 mice.

Authors:  Maria Carolina Florian; Hanna Leins; Michael Gobs; Yang Han; Gina Marka; Karin Soller; Angelika Vollmer; Vadim Sakk; Kalpana J Nattamai; Ahmad Rayes; Xueheng Zhao; Kenneth Setchell; Medhanie Mulaw; Wolfgang Wagner; Yi Zheng; Hartmut Geiger
Journal:  Aging Cell       Date:  2020-08-04       Impact factor: 9.304

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  3 in total

1.  Profiling epigenetic age in single cells.

Authors:  Alexandre Trapp; Csaba Kerepesi; Vadim N Gladyshev
Journal:  Nat Aging       Date:  2021-12-09

2.  Epigenetic Clocks for Mice Based on Age-Associated Regions That are Conserved Between Mouse Strains and Human.

Authors:  Juan-Felipe Perez-Correa; Vithurithra Tharmapalan; Hartmut Geiger; Wolfgang Wagner
Journal:  Front Cell Dev Biol       Date:  2022-06-03

Review 3.  How to Translate DNA Methylation Biomarkers Into Clinical Practice.

Authors:  Wolfgang Wagner
Journal:  Front Cell Dev Biol       Date:  2022-02-23
  3 in total

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