Physiological Resilience and the Impact on Health

We investigated the dynamic properties of the organism state fluctuations along individual aging trajectories in a large longitudinal database of CBC measurements from a consumer diagnostics laboratory. To simplify the analysis, we used a log-linear mortality estimate from the CBC variables as a single quantitative measure of the aging process, henceforth referred to as dynamic organism state indicator (DOSI). We observed, that the age-dependent population DOSI distribution broadening could be explained by a progressive loss of physiological resilience measured by the DOSI auto-correlation time. Extrapolation of this trend suggested that DOSI recovery time and variance would simultaneously diverge at a critical point of 120 − 150 years of age corresponding to a complete loss of resilience. The observation was immediately confirmed by the independent analysis of correlation properties of intraday physical activity levels fluctuations collected by wearable devices. 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.

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

Pyrkov

Avchaciov

Tarkhov

et al. 2019

Preprint

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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 quantification 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 frailty, 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 sufficiently 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.

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Physiological Resilience and the Impact on Health

Cited by 3 publications

References 150 publications

Proposal for Physiological-Resilience Usability Model in Security-Enhanced Mobile Application for Secure Travel

Proposal for Physiological-Resilience Usability Model in Security-Enhanced Mobile Application for Secure Travel

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

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

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