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Research Paper|Volume 10, Issue 10|pp 2973—2990

Quantitative characterization of biological age and frailty based on locomotor activity records

Timothy V. Pyrkov1, Evgeny Getmantsev1, Boris Zhurov1, Konstantin Avchaciov1, Mikhail Pyatnitskiy1, Leonid Menshikov1, Kristina Khodova1, Andrei V. Gudkov2, Peter O. Fedichev1,3
  • 1Gero LLC, Moscow, 1015064, Russia
  • 2Roswell Park Cancer Institute, Buffalo, NY 14263, USA
  • 3Moscow Institute of Physics and Technology, Dolgoprudny 141700, Moscow Region, Russia
Received: September 10, 2018Accepted: October 15, 2018Published: October 26, 2018

Copyright: © 2018 Pyrkov et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

We performed a systematic evaluation of the relationships between locomotor activity and signatures of frailty, morbidity, and mortality risks using physical activity records from the 2003-2006 National Health and Nutrition Examination Survey (NHANES) and UK BioBank (UKB). We proposed a statistical description of the locomotor activity tracks and transformed the provided time series into vectors representing physiological states for each participant. The Principal Component Analysis of the transformed data revealed a winding trajectory with distinct segments corresponding to subsequent human development stages. The extended linear phase starts from 35−40 years old and is associated with the exponential increase of mortality risks according to the Gompertz mortality law. We characterized the distance traveled along the aging trajectory as a natural measure of biological age and demonstrated its significant association with frailty and hazardous lifestyles, along with the remaining lifespan and healthspan of an individual. The biological age explained most of the variance of the log-hazard ratio that was obtained by fitting directly to mortality and the incidence of chronic diseases. Our findings highlight the intimate relationship between the supervised and unsupervised signatures of the biological age and frailty, a consequence of the low intrinsic dimensionality of the aging dynamics.