Epigenetic clocks based on the measurement of changing patterns of DNA methylation are perhaps the most promising approach to the production of a biomarker of aging - a way to quickly assess an individual's biological age, allowing assessment of the effectiveness of potential rejuvenation therapies in a rapid, low-cost manner. They are certainly far more accurate and useful on an individual basis than is the case for telomere length measured in the immune cells called leukocytes taken from a blood sample. The latter metric is really only reliable over large populations of individuals, and even then there are studies that find a poor or absent correlation with health outcomes. That these two measures should correlate with one another is to be expected, but in practice that isn't the case; I'd tend to blame that on the poor quality of telomere length as a metric. Here, researchers manage to generate a correlation by using a measure that mixes DNA methylation with immune system values known to change with aging, but I think that on balance all this says is that certain aspects of immune aging are related to one another.
Aging eludes precise definition at the systemic level and denotes a multitude of processes at the cellular level. Two of these processes - age-dependent telomere shortening and DNA methylation (DNAm) profiles of cytosine phosphate guanines (CpGs) have been used as indices of biological age. The age estimates resulting from multivariable regression models of DNAm profiles are referred to as "DNAm age" or "epigenetic age". The discrepancy between DNAm age and chronological age is an estimate of the "epigenetic age acceleration", which has been found to increase in Down syndrome, obesity, HIV and early menopause. Notably, measures of epigenetic age in blood have been reported to be predictive of all-cause mortality after adjusting for chronological age and traditional risk factors.
A recent meta-analysis showed that among several estimates of epigenetic age acceleration, one particular measure, i.e., extrinsic epigenetic age acceleration (EEAA), was superior in predicting all-cause mortality, but the reason for this has remained unclear. EEAA is defined as the weighted average of DNAm age and imputed proportions of naïve CD8+ T cells, memory CD8+ T cells and plasmablasts. Here we show a novel correlation between leukocyte telomere length (LTL) and EEAA. We infer that this correlation reflects the aging of the immune system, as expressed in the age-dependent change of the proportions of naive CD8+ T cells and memory CD8+ T cells.
The two key observations of this study are: (a) LTL is inversely correlated with EEAA; and (b) the LTL-EEAA correlation largely reflects the proportions of imputed naïve and memory CD8+ T cell populations in the leukocytes from which DNA was extracted. These correlations were independently replicated in two well-characterized cohorts, providing confidence in their validity. To our knowledge, this is the first study showing association between LTL and a specific formulation of the epigenetic age, but only when it was weighted by the proportions of T naïve cells, T memory cells and plasmoblasts (i.e., the EEAA). A previous study, using the Hannum formulation for DNAm age, showed no significant association between LTL and epigenetic age. Overall, these findings might explain the ability of EEAA to predict all-cause mortality, given that EEAA captures not only leukocyte DNAm age but also a key aspect of immune senescence (principally naïve and memory T cells), which increases risks of a host of age-related diseases and of death.