In the realm of epigenetics, DNA methylation clocks have emerged as significant biomarkers for assessing biological age. However, the biological mechanisms underlying these clocks remain largely unclear. This study, published in Genome Medicine, investigates the relationship between blood cell composition and DNA methylation age, particularly focusing on how variations in blood cell types can influence age estimation.
What this study does not show
While the study identifies associations between blood cell composition and DNA methylation age, it does not establish a direct causal relationship or definitively link these findings to specific health outcomes.
The researchers conducted a comprehensive analysis involving 4,058 samples to quantify the impact of blood cell composition on DNA methylation age and age acceleration, utilizing six different epigenetic clocks. Their findings indicate that up to 53% of the variation in DNA methylation age can be attributed to the proportions of various blood cell types, particularly the balance between naïve and memory T cells. In contrast, the contribution of cell composition to age acceleration was found to be weaker, explaining up to 21% of the variance, with neutrophils playing a significant role in 2nd-generation clocks.
Furthermore, the study explored the influence of blood cell composition on the association between age acceleration and 176 incident health outcomes in a larger cohort of 18,859 individuals. The results revealed that while cell composition significantly attenuates the association of age acceleration with these health outcomes, the effect remains modest.
These findings suggest that DNA methylation age (DNAmAge) and age acceleration (AgeAccel) reflect different biological processes, as evidenced by their distinct associations with blood cell composition. The study concludes that while blood cell composition does play a role in age estimation, its contribution to the association with mortality and disease outcomes is relatively minor.
Evidence scorecard
- Analytic validity: Established
- Clinical validity: Not established
- Clinical utility: Not established
The evidence is based on primary research involving human samples.