Blood Test-Based age Acceleration Is Inversely Associated with High-Volume Sports Activity.

PURPOSE:We develop blood test-based aging clocks and examine how these clocks reflect high-volume sports activity. METHODS:We use blood tests and body metrics data of 421 Hungarian athletes and 283 age-matched controls (mean age 24.1 and 23.9 years, respectively), the latter selected from a group of healthy Caucasians of the National Health and Nutrition Examination Survey (NHANES) to represent the general population (n = 11,412). We train two age prediction models (i.e., aging clocks) using the NHANES dataset: the first model relies on blood test parameters only, while the second one additionally incorporates body measurements and sex. RESULTS:We find lower age acceleration among athletes compared to the age-matched controls with a median value of -1.7 and 1.4 years, p <  0.0001. BMI is positively associated with age acceleration among the age-matched controls (r = 0.17, p <  0.01) and the unrestricted NHANES population (r = 0.11, p <  0.001). We find no association between BMI and age acceleration within the athlete dataset. Instead, age acceleration is positively associated with body fat percentage (r = 0.21, p <  0.05) and negatively associated with skeletal muscle mass (Pearson r: -0.18, p <  0.05) among athletes. The most important blood test features in age predictions were serum ferritin, mean cell volume, blood urea nitrogen, and albumin levels. CONCLUSIONS:We develop and apply blood test-based aging clocks to adult athletes and healthy controls. The data suggest that high-volume sports activity is associated with slowed biological aging. Here, we propose an alternative, promising application of routine blood tests.