9 research outputs found
H3K4me1 marks DNA regions hypomethylated during aging in human stem and differentiated cells
In differentiated cells, aging is associated with hypermethylation of DNA regions enriched in repressive histone post-translational modifications. However, the chromatin marks associated with changes in DNA methylation in adult stem cells during lifetime are still largely unknown. Here, DNA methylation profiling of mesenchymal stem cells (MSCs) obtained from individuals aged 2 to 92 yr identified 18,735 hypermethylated and 45,407 hypomethylated CpG sites associated with aging. As in differentiated cells, hypermethylated sequences were enriched in chromatin repressive marks. Most importantly, hypomethylated CpG sites were strongly enriched in the active chromatin mark H3K4me1 in stem and differentiated cells, suggesting this is a cell type–independent chromatin signature of DNA hypomethylation during aging. Analysis of scedasticity showed that interindividual variability of DNA methylation increased during aging in MSCs and differentiated cells, providing a new avenue for the identification of DNA methylation changes over time. DNA methylation profiling of genetically identical individuals showed that both the tendency of DNA methylation changes and scedasticity depended on nongenetic as well as genetic factors. Our results indicate that the dynamics of DNA methylation during aging depend on a complex mixture of factors that include the DNA sequence, cell type, and chromatin context involved and that, depending on the locus, the changes can be modulated by genetic and/or external factors
Kaplan Meier survival function for the probability of first fall from a raised surface overall during the first two years of life.
FERF = First Event of Raised surface Fall.</p
Leading cause of unintentional injuries during the first and second year of life.
Leading cause of unintentional injuries during the first and second year of life.</p
Potential risk factors of the 2,886 mother‐child pairs.
Potential risk factors of the 2,886 mother‐child pairs.</p
Associations (expressed by regression coefficients with 95% CIs, BMI units (kg/m<sup>2</sup>)) of former smoking with BMI compared to current smokers (reference) in twin individuals (n = 156,593) and same-sex twin pairs (DZ or MZ pairs) discordant for their smoking status (m = 10,551 pairwise measurements) by sex and time period from the CODATwins database, 1960–2012.
<p>BMI = body mass index; CI = confidence interval; DZ = dizygotic; MZ = monozygotic.</p
Associations (expressed by regression coefficients with 95% CIs, BMI units (kg/m<sup>2</sup>)) of current smoking with BMI compared to never smokers (reference) in twin individuals (n = 156,593) and same-sex twin pairs (DZ or MZ pairs) discordant for their smoking status (m = 10,128 pairwise measurements) by sex and time period from the CODATwins database, 1960–2012.
<p>BMI = body mass index; CI = confidence interval; DZ = dizygotic; MZ = monozygotic.</p
Flow chart of the CODATwins dataset (n = 156,593 twin individuals and 30,014 pairwise comparisons in smoking discordant same-sexed twin pairs) included in the study.
<p>BMI = body mass index; MZ = monozygotic.</p
Associations (expressed by regression coefficients with 95% CIs, BMI units (kg/m<sup>2</sup>)) of former smoking with BMI compared to never smokers (reference) in twin individuals (n = 156,593) and same-sex twin pairs (DZ or MZ pairs) discordant for their smoking status (m = 9,336 pairwise measurements) by sex and time period from the CODATwins database, 1960–2012.
<p>BMI = body mass index; CI = confidence interval; DZ = dizygotic; MZ = monozygotic.</p