Chronic antigenic stress, immunosenescence and human survivorship over the 3 last centuries: heuristic value of a mathematical model

Mech Ageing Dev. 2003 Apr;124(4):453-8. doi: 10.1016/s0047-6374(03)00022-8.

Abstract

In previous investigations we pursued the hypothesis that lifelong, chronic antigenic load (CAL) is the major driving force of immunosenescence, which impacts on human lifespan by reducing the number of virgin antigen-non experienced (ANE) T cells, and filling the immunological space with expanded clones of memory and effector, antigen-experienced (AE) T cells. A model has been proposed to relate CAL with the conversion rate from ANE to AE CD8+ T cells. In addition, in order to account for individual variations of immunosenescence and lifespan, a noise term has been introduced to describe the individual fluctuations of CAL. This model was able to follow with a reasonable approximation the age-related decrease of ANE CD8+ T cells, as well as human survival curves. In this paper we extend this approach to historical survival curves, starting from 1750 until present days, and show that the quality of the fit of historical demographic data improves as we approach the recent, quantitative and qualitative decrease of CAL. Indeed, the almost linearity in the increase of lifespan and in the decrease of the noise fluctuation amplitude within this historical period suggests that the improvement of life conditions has steadily lowered the intensity of CAL and restricted the variability which results from the interaction between the individuals and their immunological environment. On the whole, this approach allows to appreciate when and how immunosenescence has started to impact on survivorship, and predicts its increasing, crucial role in explaining human mortality in hygienized, economically developed societies.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Aging / immunology*
  • Antigens / immunology*
  • CD8-Positive T-Lymphocytes / immunology
  • Chronic Disease
  • Humans
  • Models, Immunological*
  • Mortality
  • Stochastic Processes
  • Stress, Physiological / immunology*
  • Survival Analysis

Substances

  • Antigens