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DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation

DNAmPhenoAge, DNAmGrimAge, and the newly developed DNAmFitAge are DNA methylation (DNAm)-based biomarkers that reflect the individual aging process. Here, we examine the relationship between physical fitness and DNAm-based biomarkers in adults aged 33–88 with a wide range of physical fitness (includ...

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Autores principales: Jokai, Matyas, Torma, Ferenc, McGreevy, Kristen M., Koltai, Erika, Bori, Zoltan, Babszki, Gergely, Bakonyi, Peter, Gombos, Zoltan, Gyorgy, Bernadett, Aczel, Dora, Toth, Laszlo, Osvath, Peter, Fridvalszky, Marcell, Teglas, Timea, Posa, Aniko, Kujach, Sylwester, Olek, Robert, Kawamura, Takuji, Seki, Yasuhiro, Suzuki, Katsuhiko, Tanisawa, Kumpei, Goto, Sataro, Kerepesi, Csaba, Boldogh, Istvan, Ba, Xueqing, Davies, Kelvin J. A., Horvath, Steve, Radak, Zsolt
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643800/
https://www.ncbi.nlm.nih.gov/pubmed/37209203
http://dx.doi.org/10.1007/s11357-023-00826-1
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author Jokai, Matyas
Torma, Ferenc
McGreevy, Kristen M.
Koltai, Erika
Bori, Zoltan
Babszki, Gergely
Bakonyi, Peter
Gombos, Zoltan
Gyorgy, Bernadett
Aczel, Dora
Toth, Laszlo
Osvath, Peter
Fridvalszky, Marcell
Teglas, Timea
Posa, Aniko
Kujach, Sylwester
Olek, Robert
Kawamura, Takuji
Seki, Yasuhiro
Suzuki, Katsuhiko
Tanisawa, Kumpei
Goto, Sataro
Kerepesi, Csaba
Boldogh, Istvan
Ba, Xueqing
Davies, Kelvin J. A.
Horvath, Steve
Radak, Zsolt
author_facet Jokai, Matyas
Torma, Ferenc
McGreevy, Kristen M.
Koltai, Erika
Bori, Zoltan
Babszki, Gergely
Bakonyi, Peter
Gombos, Zoltan
Gyorgy, Bernadett
Aczel, Dora
Toth, Laszlo
Osvath, Peter
Fridvalszky, Marcell
Teglas, Timea
Posa, Aniko
Kujach, Sylwester
Olek, Robert
Kawamura, Takuji
Seki, Yasuhiro
Suzuki, Katsuhiko
Tanisawa, Kumpei
Goto, Sataro
Kerepesi, Csaba
Boldogh, Istvan
Ba, Xueqing
Davies, Kelvin J. A.
Horvath, Steve
Radak, Zsolt
author_sort Jokai, Matyas
collection PubMed
description DNAmPhenoAge, DNAmGrimAge, and the newly developed DNAmFitAge are DNA methylation (DNAm)-based biomarkers that reflect the individual aging process. Here, we examine the relationship between physical fitness and DNAm-based biomarkers in adults aged 33–88 with a wide range of physical fitness (including athletes with long-term training history). Higher levels of VO(2)max (ρ = 0.2, p = 6.4E − 4, r = 0.19, p = 1.2E − 3), Jumpmax (p = 0.11, p = 5.5E − 2, r = 0.13, p = 2.8E − 2), Gripmax (ρ = 0.17, p = 3.5E − 3, r = 0.16, p = 5.6E − 3), and HDL levels (ρ = 0.18, p = 1.95E − 3, r = 0.19, p = 1.1E − 3) are associated with better verbal short-term memory. In addition, verbal short-term memory is associated with decelerated aging assessed with the new DNAm biomarker FitAgeAcceleration (ρ: − 0.18, p = 0.0017). DNAmFitAge can distinguish high-fitness individuals from low/medium-fitness individuals better than existing DNAm biomarkers and estimates a younger biological age in the high-fit males and females (1.5 and 2.0 years younger, respectively). Our research shows that regular physical exercise contributes to observable physiological and methylation differences which are beneficial to the aging process. DNAmFitAge has now emerged as a new biological marker of quality of life.
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spelling pubmed-106438002023-11-15 DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation Jokai, Matyas Torma, Ferenc McGreevy, Kristen M. Koltai, Erika Bori, Zoltan Babszki, Gergely Bakonyi, Peter Gombos, Zoltan Gyorgy, Bernadett Aczel, Dora Toth, Laszlo Osvath, Peter Fridvalszky, Marcell Teglas, Timea Posa, Aniko Kujach, Sylwester Olek, Robert Kawamura, Takuji Seki, Yasuhiro Suzuki, Katsuhiko Tanisawa, Kumpei Goto, Sataro Kerepesi, Csaba Boldogh, Istvan Ba, Xueqing Davies, Kelvin J. A. Horvath, Steve Radak, Zsolt GeroScience Original Article DNAmPhenoAge, DNAmGrimAge, and the newly developed DNAmFitAge are DNA methylation (DNAm)-based biomarkers that reflect the individual aging process. Here, we examine the relationship between physical fitness and DNAm-based biomarkers in adults aged 33–88 with a wide range of physical fitness (including athletes with long-term training history). Higher levels of VO(2)max (ρ = 0.2, p = 6.4E − 4, r = 0.19, p = 1.2E − 3), Jumpmax (p = 0.11, p = 5.5E − 2, r = 0.13, p = 2.8E − 2), Gripmax (ρ = 0.17, p = 3.5E − 3, r = 0.16, p = 5.6E − 3), and HDL levels (ρ = 0.18, p = 1.95E − 3, r = 0.19, p = 1.1E − 3) are associated with better verbal short-term memory. In addition, verbal short-term memory is associated with decelerated aging assessed with the new DNAm biomarker FitAgeAcceleration (ρ: − 0.18, p = 0.0017). DNAmFitAge can distinguish high-fitness individuals from low/medium-fitness individuals better than existing DNAm biomarkers and estimates a younger biological age in the high-fit males and females (1.5 and 2.0 years younger, respectively). Our research shows that regular physical exercise contributes to observable physiological and methylation differences which are beneficial to the aging process. DNAmFitAge has now emerged as a new biological marker of quality of life. Springer International Publishing 2023-05-20 /pmc/articles/PMC10643800/ /pubmed/37209203 http://dx.doi.org/10.1007/s11357-023-00826-1 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Original Article
Jokai, Matyas
Torma, Ferenc
McGreevy, Kristen M.
Koltai, Erika
Bori, Zoltan
Babszki, Gergely
Bakonyi, Peter
Gombos, Zoltan
Gyorgy, Bernadett
Aczel, Dora
Toth, Laszlo
Osvath, Peter
Fridvalszky, Marcell
Teglas, Timea
Posa, Aniko
Kujach, Sylwester
Olek, Robert
Kawamura, Takuji
Seki, Yasuhiro
Suzuki, Katsuhiko
Tanisawa, Kumpei
Goto, Sataro
Kerepesi, Csaba
Boldogh, Istvan
Ba, Xueqing
Davies, Kelvin J. A.
Horvath, Steve
Radak, Zsolt
DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation
title DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation
title_full DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation
title_fullStr DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation
title_full_unstemmed DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation
title_short DNA methylation clock DNAmFitAge shows regular exercise is associated with slower aging and systemic adaptation
title_sort dna methylation clock dnamfitage shows regular exercise is associated with slower aging and systemic adaptation
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10643800/
https://www.ncbi.nlm.nih.gov/pubmed/37209203
http://dx.doi.org/10.1007/s11357-023-00826-1
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