The original Pace of Aging that emerged from analysis of Dunedin Study data was a form of epigenetic clock. Here, what the researchers are calling Pace of Aging is instead a form of aging clock derived from clinical chemistry and other simple measures of function such as grip strength. Further, it was generated from data obtained from different study populations. It is not the same at all! There is nothing in common between these assessments. It seems unhelpful to keep the same name. That said, at the present time the use of clinical data as a basis for an aging clock seems more helpful than use of omics data, as one can at least make some attempt to hypothesize regarding the underlying causes for changes in the aging clock output following interventions.
Originally developed using data from the Dunedin Study - a longitudinal study of individuals born in 1972-73 - the initial Pace of Aging tool focused on changes from young adulthood through midlife. A newly refined method for measuring the Pace of Aging in population-based studies provides a powerful tool for predicting risks associated with aging. The team analyzed data from two large-scale, nationally representative studies: the U.S. Health and Retirement Study (HRS) and the English Longitudinal Study of Aging (ELSA). These long-term studies follow adults aged 50 and older - along with their spouses - and collect detailed information on health, cognition, socioeconomic status, and family dynamics. The studies have been ongoing for decades and periodically enroll new participants.
The new approach makes use of data from dried blood spots, physical exams, and performance tests given to participants in their homes at up to three timepoints over eight-year follow-up intervals. Pace of Aging was examined in 19,045 participants who contributed data over 2006-2016, with additional follow-up to determine disease, disability, and mortality through 2022. In the US study, Pace of Aging was measured from C-reactive protein (CRP), Cystatin-C, glycated hemoglobin (HbA1C), diastolic blood pressure, waist circumference, lung capacity (peak flow), balance, grip strength, and gait speed.
"Our findings establish that we can measure important variability in the pace of aging in older people with a relatively limited set of measurements. These metrics consistently predict future health outcomes, including disease onset, disability, and death. And they reveal important differences in aging trajectories across population subgroups. For example, the study reported signs of accelerated aging in people with lower levels of education."
View the full article at FightAging
