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Research Paper|Volume 7, Issue 8|pp 568—578

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

Davide Gentilini1, Paolo Garagnani2,3, Serena Pisoni1, Maria Giulia Bacalini2,3, Luciano Calzari1, Daniela Mari4, Giovanni Vitale1,5, Claudio Franceschi2,3, Anna Maria Di Blasio1
  • 1Istituto Auxologico Italiano IRCCS, Cusano Milanino, 20095 Milan, Italy
  • 2Department of Experimental, Diagnostic and Specialty Medicine, Alma Mater Studiorum- University of Bologna, Bologna 40138, Italy
  • 3Interdepartmental Center “L. Galvani”, University of Bologna, Bologna 40126, Italy
  • 4Geriatric Unit, IRCCS Ca' Granda Foundation Maggiore Policlinico Hospital, Milan, Italy
  • 5Department of Clinical Sciences and Community Health, University of Milan, Milan, Italy
Received: June 23, 2015Accepted: August 16, 2015Published: August 23, 2015
https://doi.org/10.18632/aging.100792

Copyright: © 2015 Gentilini et al. 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.

Abstract

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