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Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females

In this study we applied a new analytical strategy to investigate the relations between stochastic epigenetic mutations (SEMs) and aging. We analysed methylation levels through the Infinium HumanMethylation27 and HumanMethylation450 BeadChips in a population of 178 subjects ranging from 3 to 106 yea...

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Autores principales: Gentilini, Davide, Garagnani, Paolo, Pisoni, Serena, Bacalini, Maria Giulia, Calzari, Luciano, Mari, Daniela, Vitale, Giovanni, Franceschi, Claudio, Di Blasio, Anna Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals LLC 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586102/
https://www.ncbi.nlm.nih.gov/pubmed/26342808
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author Gentilini, Davide
Garagnani, Paolo
Pisoni, Serena
Bacalini, Maria Giulia
Calzari, Luciano
Mari, Daniela
Vitale, Giovanni
Franceschi, Claudio
Di Blasio, Anna Maria
author_facet Gentilini, Davide
Garagnani, Paolo
Pisoni, Serena
Bacalini, Maria Giulia
Calzari, Luciano
Mari, Daniela
Vitale, Giovanni
Franceschi, Claudio
Di Blasio, Anna Maria
author_sort Gentilini, Davide
collection PubMed
description In this study we applied a new analytical strategy to investigate the relations between stochastic epigenetic mutations (SEMs) and aging. We analysed methylation levels through the Infinium HumanMethylation27 and HumanMethylation450 BeadChips in a population of 178 subjects ranging from 3 to 106 years. For each CpG probe, epimutated subjects were identified as the extreme outliers with methylation level exceeding three times interquartile ranges the first quartile (Q1-(3 × IQR)) or the third quartile (Q3+(3 × IQR)). We demonstrated that the number of SEMs was low in childhood and increased exponentially during aging. Using the HUMARA method, skewing of X chromosome inactivation (XCI) was evaluated in heterozygotes women. Multivariate analysis indicated a significant correlation between log(SEMs) and degree of XCI skewing after adjustment for age (β = 0.41; confidence interval: 0.14, 0.68; p-value = 0.0053). The PATH analysis tested the complete model containing the variables: skewing of XCI, age, log(SEMs) and overall CpG methylation. After adjusting for the number of epimutations we failed to confirm the well reported correlation between skewing of XCI and aging. This evidence might suggest that the known correlation between XCI skewing and aging could not be a direct association but mediated by the number of SEMs.
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spelling pubmed-45861022015-09-30 Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females Gentilini, Davide Garagnani, Paolo Pisoni, Serena Bacalini, Maria Giulia Calzari, Luciano Mari, Daniela Vitale, Giovanni Franceschi, Claudio Di Blasio, Anna Maria Aging (Albany NY) Research Paper In this study we applied a new analytical strategy to investigate the relations between stochastic epigenetic mutations (SEMs) and aging. We analysed methylation levels through the Infinium HumanMethylation27 and HumanMethylation450 BeadChips in a population of 178 subjects ranging from 3 to 106 years. For each CpG probe, epimutated subjects were identified as the extreme outliers with methylation level exceeding three times interquartile ranges the first quartile (Q1-(3 × IQR)) or the third quartile (Q3+(3 × IQR)). We demonstrated that the number of SEMs was low in childhood and increased exponentially during aging. Using the HUMARA method, skewing of X chromosome inactivation (XCI) was evaluated in heterozygotes women. Multivariate analysis indicated a significant correlation between log(SEMs) and degree of XCI skewing after adjustment for age (β = 0.41; confidence interval: 0.14, 0.68; p-value = 0.0053). The PATH analysis tested the complete model containing the variables: skewing of XCI, age, log(SEMs) and overall CpG methylation. After adjusting for the number of epimutations we failed to confirm the well reported correlation between skewing of XCI and aging. This evidence might suggest that the known correlation between XCI skewing and aging could not be a direct association but mediated by the number of SEMs. Impact Journals LLC 2015-08-23 /pmc/articles/PMC4586102/ /pubmed/26342808 Text en Copyright: © 2015 Gentilini et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Paper
Gentilini, Davide
Garagnani, Paolo
Pisoni, Serena
Bacalini, Maria Giulia
Calzari, Luciano
Mari, Daniela
Vitale, Giovanni
Franceschi, Claudio
Di Blasio, Anna Maria
Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females
title Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females
title_full Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females
title_fullStr Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females
title_full_unstemmed Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females
title_short Stochastic epigenetic mutations (DNA methylation) increase exponentially in human aging and correlate with X chromosome inactivation skewing in females
title_sort stochastic epigenetic mutations (dna methylation) increase exponentially in human aging and correlate with x chromosome inactivation skewing in females
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4586102/
https://www.ncbi.nlm.nih.gov/pubmed/26342808
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