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    • The method used in our study for measuring epigenetic age

    2018-10-23

    The method used in our study for measuring epigenetic age was based on a model trained on genome-wide DNA methylation extracted from WBC (Hannum et al., 2013). As our measurements were taken from extracted WBC, epigenetic age measured in our study could be a proxy measure for the immune response to cancer initiation and progression, potentially explaining the complex, nonlinear, and time-dependent relationships between Δage, cancer incidence, and cancer mortality we observed. It is well-known that thymic involution with aging can result in diminishing numbers of naïve T AEG 3482 (Taub and Longo, 2005). Our data also suggested that increasing epigenetic age was associated with loss of naïve CD8+ T cells (r=−0.24, P<0.001, Supplementary material, Fig. S7). After removing the confounding effects of chronological age and immunosenescence using Δage, our spline plots showed that the risk of developing cancer over time is minimized at Δage=0, with a more linear risk profile emerging 3–5years prior to diagnosis (Fig. 2). This may reflect the initial anti-inflammatory and pro-apoptotic response by the body to early carcinogenesis, which triggers increased WBC production that successfully (albeit temporarily) represses cancer. As the cancer eventually adapts to such immune responses they become less effective, resulting in the J-shaped curve evident in our spline plot. Thus, epigenetic age substantially ‘younger’ than chronological age (negative Δage) may be a biomarker of the initial response to a developing cancer before it is detectable through standard diagnostic means. The findings of our Kaplan–Meier curve relating any disruption in the normal epigenetic aging observed in healthy subjects (i.e. either higher Δage or accelerated epigenetic aging over time) to cancer incidence and mortality are also consistent with this hypothesis (Fig. 3, Supplementary material, Fig. S6). As we continue to accrue follow-up data for this cohort, we can assess whether this suggestion is accurate by comparing health outcomes for epigenetically ‘young’ to epigenetically ‘old’ subjects over time. These findings should also be verified in other, larger datasets. The observed dynamics are also reflected in the straightforward Δage–mortality relationship. Delays between cancer diagnosis and death may allow time for normal thymic involution and other age-related immune deterioration processes to reassert themselves, after the initial response to cancer. This would effectively allow epigenetic age to ‘catch up’ to chronological age and produce the observed linear relationship with mortality. Alternatively, our findings related to cancer mortality could also be reflective of metastasis-induced changes in WBC epigenetic profiles. Longer follow-up in larger groups will be necessary to confirm these hypotheses, but if confirmed, they suggest that Δage would be best utilized as a biomarker of early immune response to carcinogenic processes, with any perturbations of epigenetic age relative to chronological age serving as a potentially useful indicator for use in mass screenings for cancer. The longitudinal nature of our study enabled us to establish temporal associations between Δage and cancer risk. Our sample size limited our ability to conduct meaningful analyses of cancer subtypes, thus caution should be exercised in interpreting our results. However, while different cancers are biologically distinct from one another blood-based Δage may not be cancer-type-specific. As carcinogenesis usually alters methylation of WBC through inflammation and immune senescence pathways common to most cancer types (Ponnappan and Ponnappan, 2011; Li et al., 2012), epigenetic age acceleration in blood DNA may be a useful biomarker for many (if not all) types of cancer. Therefore, pooling multiple different cancers is biologically plausible for purposes of examining Δage in blood. Additional studies with longer follow-up are needed to confirm this, and to verify the dynamic, nonlinear, and time-dependent relationship between Δage and cancer.