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Longitudinal analysis of blood markers reveals progressive loss of resilience and predicts ultimate limit of human lifespan

View ORCID ProfileTimothy V. Pyrkov, Konstantin Avchaciov, View ORCID ProfileAndrei E. Tarkhov, Leonid I. Menshikov, Andrei V. Gudkov, View ORCID ProfilePeter O. Fedichev
doi: https://doi.org/10.1101/618876
Timothy V. Pyrkov
aGero LLC, 105064, Nizhny Susalny per. 5/4, Moscow, Russia
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  • For correspondence: tim.pyrkov@gero.com peter.fedichev@gero.com
Konstantin Avchaciov
aGero LLC, 105064, Nizhny Susalny per. 5/4, Moscow, Russia
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Andrei E. Tarkhov
aGero LLC, 105064, Nizhny Susalny per. 5/4, Moscow, Russia
bSkolkovo Institute of Science and Technology, Bolshoy Boulevard 30, bld. 1, Moscow 121205, Russia
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Leonid I. Menshikov
aGero LLC, 105064, Nizhny Susalny per. 5/4, Moscow, Russia
cNational Research Center “Kurchatov Institute”, 1, Akademika Kurchatova pl., Moscow 123182, Russia
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Andrei V. Gudkov
dRoswell Park Comprehensive Cancer Center, Elm and Carlton streets, Buffalo, NY 14263, USA
eGenome Protection, Inc. 640 Ellicott St #444, Buffalo, NY 14203, USA
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Peter O. Fedichev
aGero LLC, 105064, Nizhny Susalny per. 5/4, Moscow, Russia
fMoscow Institute of Physics and Technology, 141700, Institutskii per. 9, Dolgoprudny, Moscow Region, Russia
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ABSTRACT

We analyzed aging trajectories of complete blood counts (CBC) and their association with the incidence of chronic diseases and death in cohorts of aging individuals registered in the UK Biobank and National Health and Nutrition Examination Survey (NHANES) studies. Application of a proportional hazards model to the CBC data allowed us to identify the log-transformed hazard ratio as a quantitative measure of aging process, which we have named the dynamic morbidity index (DMI). DMI increased with age in the UK Biobank and NHANES cohorts, was associated with multiple morbidity, and predicted the prospective incidence of age-related diseases and death. To better understand the nature of DMI variations along individual aging trajectories, we acquired a large longitudinal database of CBC measurements from a consumer diagnostics laboratory. We observed that population DMI distribution broadening can be explained by a progressive loss of physiological resilience measured by the DMI auto-correlation time. Extrapolation of this data suggested that DMI recovery time and variance would simultaneously diverge at a critical point of 120-150 years of age corresponding to a complete loss of resilience. We conclude that the criticality resulting in the end of life is an intrinsic biological property of an organism that is independent of stress factors and signifies a fundamental or absolute limit of human lifespan.

Footnotes

  • Added discussion of reviews on resilience in physiological data. Figure 3C: added inverse variance of physical activity for reference.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted February 07, 2020.
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Longitudinal analysis of blood markers reveals progressive loss of resilience and predicts ultimate limit of human lifespan
Timothy V. Pyrkov, Konstantin Avchaciov, Andrei E. Tarkhov, Leonid I. Menshikov, Andrei V. Gudkov, Peter O. Fedichev
bioRxiv 618876; doi: https://doi.org/10.1101/618876
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Longitudinal analysis of blood markers reveals progressive loss of resilience and predicts ultimate limit of human lifespan
Timothy V. Pyrkov, Konstantin Avchaciov, Andrei E. Tarkhov, Leonid I. Menshikov, Andrei V. Gudkov, Peter O. Fedichev
bioRxiv 618876; doi: https://doi.org/10.1101/618876

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