Assessing Variability of Longevity in Stress Response Upregulation Therapies

Most of the interventions demonstrated to slow aging and extend life span to some degree in mice involve upregulation of cellular stress responses. This means increased activity in the repair and maintenance mechanisms, such as autophagy, that keep cells and tissues functional. These approaches are the not the path to radically increased human longevity. As the practice of calorie restriction demonstrates, short-lived mammals have a much greater plasticity of longevity than we long-lived humans when it comes to the effects of stress response mechanisms. Calorie restriction adds 40% to mouse life span, but no more than a few years to human life span. It does, however, improve measures of health in our species, and that should probably set our expectations regarding the benefits that will arise from present efforts to produce calorie restriction mimetics, autophagy enhancers, and similar categories of therapy.

In the research here, scientists report on an effort to calibrate variability in the effects of these stress response upregulation therapies. The ideal life extending treatment is one that (a) extends healthy life, not the period of decline, and (b) does so by a large amount, and (c) is very reliable in achieving that large gain. Stress response upregulation is a failure as a strategy when it comes to the size of the effect, and while we tend to think of calorie restriction as a very reliable intervention, when considering variation in size of effect between individuals, that may not be as much the case as we'd like it to be.

In studies of aging, changes in the length of life are usually analyzed by comparing average (mean) or median longevity. Frequently, some estimate of maximal longevity is also considered. While values of the standard deviations or standard errors of the mean are routinely reported, the distribution of individual age at death is rarely analyzed or discussed. In a recent publication based on analysis of demographic data, it was reported that socio-economic status influences not only the mean longevity but also the variability of human life-span. Using an example of Finnish women, these investigators showed that reduced mean longevity of less educated and less affluent people is associated with greater variability of life-span.

Because of the potential significance of this relationship for the analysis of mortality data and physiological biomarkers in studies of aging as well as for various public health considerations, we thought that it would be of interest to determine whether interventions known to extend the average (or the average and the maximal) longevity of experimental animals have any effect on the variability of life-span. We hypothesized that extension of longevity by genetic, dietary or pharmacological means leads to reduction of life-span variability.

However, inspection of data from the National Institute of Aging Interventions Testing Program (ITP) and from our studies of the interactions of murine longevity genes with calorie restriction (CR) indicated that reciprocal changes of longevity and its variability are not consistently observed. This suggested that our hypothesis would most likely need to be rejected and brought up a new question, namely, what factors influence variability of the lifespan. Here we report results of a study aimed at analyzing the effects of sex, strain, life-extending interventions and their interactions on life-span variation.

The relationship of changes in longevity and in longevity variance was found to depend on sex and treatment and apparently also on strain. Increased longevity of male mice treated with effective anti-aging drugs was accompanied by reduced variance of age at death and apparent reduction of early life mortality. Life extension induced by growth-hormone related mutations and calorie restriction tended to increase longevity variance in females only. We conclude that impact of anti-aging interventions on the variance of age at death and distribution of individual lifespans in laboratory mice is treatment-dependent and sexually dimorphic.

Link: https://doi.org/10.18632/aging.102037

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