Average telomere length, as presently assessed in immune cells taken from a blood sample, is a truly terrible basis for measuring the pace of aging. Only in large studies is a statistical decline with aging seen, and even then not in all studies. For any given individual this measure is very dynamic, reflecting short term immune system changes that have little to do with aging - and thus a specific measure or set of measures isn't all that actionable.

The study here, in which no correlation was found between telomere length and an epigenetic clock, should be taken as a reinforcement of this point. Despite the challenges remaining in the development of epigenetic clocks, such as the question of what exactly it is that they do measure about aging, they do reliably correlate with risk of age-related disease in individuals and small study groups, which is more than can be said for telomere length. The epigenetic clock is a far, far better foundation for a useful biomarker of aging, one that can be used to quickly assess the results of alleged rejuvenation therapies, than is the case for telomere length.

Aging is accompanied by a range of DNA modifications. Telomere length, which shortens as a consequence of DNA replication, has been widely accepted as a biomarker of aging. While being inversely correlated with chronological age, telomere length is also associated with a range of age-associated phenotypes and clinical diseases. Recently, a novel candidate epigenetic biomarker of aging has been shown to predict an individual's chronological age with high accuracy: the epigenetic clock is based on the weighted DNA methylation fraction of a number of DNA methylation (DNAm) age correlates with cell passage number in vitro and can be predicted across different tissues, including non-proliferating ones in vivo, suggesting that DNA methylation is not exclusively reflecting mitotic age. This is in line with the finding that DNAm age and relative leukocyte telomere length (rLTL) were independently associated with chronological age and mortality. The few existing studies found no supporting evidence of a significant association between rLTL and DNAm age or reported a weak association. Moreover, rLTL was reported to have a lower predictive power in estimating chronological age in comparison to the epigenetic clock. While the number of studies reporting a positive correlation between DNAm and chronological age in a range of different study populations rises, there is accumulating evidence suggesting that DNAm age somewhat reflects biological age. Under the assumption that DNA methylation age reflects biological age, calculating the deviation of the epigenetic age estimate and the chronological age gives rise to a second potentially clinically relevant measure: DNAm age acceleration. Here we aim to explore the association of rLTL and the epigenetic clock variables, DNAm age and DNAm age acceleration, in the context of cardiovascular disease in the LipidCardio cohort. Both rLTL (0.79 ± 0.14) and DNAm age (69.67 ± 7.27 years) were available for 773 subjects (31.6% female; mean chronological age 69.68 ± 11.01 years). While we detected a significant correlation between chronological age and DNAm age, we found neither evidence of an association between rLTL and the DNAm age nor rLTL and the DNAm age acceleration in the studied cohort, suggesting that DNAm age and rLTL measure different aspects of biological age.

Link: https://doi.org/10.3390/ijms20123032