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

Autor:	Juhász V; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Ország A; Institute for Computer Science and Control (SZTAKI), Hungarian Research Network (HUN-REN), Budapest, HUNGARY., Balla D; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Szabó L; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Sydó N, Kiss O, Csulak E; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Babity M; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Dohy Z; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Skoda R; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Becker D; Heart and Vascular Centre, Semmelweis University, Budapest, HUNGARY., Merkely B, Benczúr A; Institute for Computer Science and Control (SZTAKI), Hungarian Research Network (HUN-REN), Budapest, HUNGARY., Vágó H, Kerepesi C; Institute for Computer Science and Control (SZTAKI), Hungarian Research Network (HUN-REN), Budapest, HUNGARY.
Jazyk:	angličtina
Zdroj:	Medicine and science in sports and exercise [Med Sci Sports Exerc] 2024 May 01; Vol. 56 (5), pp. 868-875. Date of Electronic Publication: 2024 Feb 29.
DOI:	10.1249/MSS.0000000000003380
Abstrakt:	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 yr, 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, whereas the second one additionally incorporates body measurements and sex. Results: We find lower age acceleration among athletes compared with the age-matched controls with a median value of -1.7 and 1.4 yr, 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. (Copyright © 2024 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American College of Sports Medicine.)
Databáze:	MEDLINE
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