Lifestyle impacts on the aging-associated expression of biomarkers of DNA damage and telomere dysfunction in human blood

Aging Cell. 2010 Aug;9(4):607-15. doi: 10.1111/j.1474-9726.2010.00583.x. Epub 2010 Jun 17.

Abstract

Cellular aging is characterized by telomere shortening, which can lead to uncapping of chromosome ends (telomere dysfunction) and activation of DNA damage responses. There is some evidence that DNA damage accumulates during human aging and that lifestyle factors contribute to the accumulation of DNA damage. Recent studies have identified a set of serum markers that are induced by telomere dysfunction and DNA damage, and these markers showed an increased expression in blood during human aging. Here, we investigated the influence of lifestyle factors (such as exercise, smoking, body mass) on the aging-associated expression of serum markers of DNA damage (CRAMP, EF-1alpha, stathmin, n-acetyl-glucosaminidase and chitinase) in comparison with other described markers of cellular aging (p16(INK4a) upregulation and telomere shortening) in human peripheral blood. The study shows that lifestyle factors have an age-independent impact on the expression level of biomarkers of DNA damage. Smoking and increased body mass indices were associated with elevated levels of biomarkers of DNA damage independent of the age of the individuals. In contrast, exercise was associated with an age-independent reduction in the expression of biomarkers of DNA damage in human blood. The expression of biomarkers of DNA damage correlated positively with p16(INK4a) expression and negatively with telomere length in peripheral blood T-lymphocytes. Together, these data provide experimental evidence that both aging and lifestyle impact on the accumulation of DNA damage during human aging.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aging / blood*
  • Biomarkers / blood*
  • Body Mass Index
  • Cellular Senescence
  • DNA Damage*
  • Exercise
  • Humans
  • Life Style*
  • Regression Analysis
  • Smoking / blood
  • T-Lymphocytes / metabolism
  • Telomere / metabolism*

Substances

  • Biomarkers