An Approach to the Analysis of Differences Between Species in the Matter of Aging and Longevity-Enhancing Interventions

Most research into the mechanisms of aging starts with cells and then moves to short-lived species such as flies or nematode worms - easier to manage than mice, and the short life spans mean that more work can be carried out for a given amount of funding and time. Only later do more promising projects move to the use of mice. At each stage of the process, from cells to worms, from worms to mice, from mice to people, many research results fail to prove relevant. Worms are not mice, and mice are not people. There are significant differences, for all that many of the most fundamental aspects of aging and cellular biochemistry are remarkable similar in all of these species. The paper here, the full text in PDF format only I'm afraid, is an interesting attempt to put some numbers to the degree to which nematodes and mice are different in the matter of aging and interventions that slow aging.

Given the existence of subtle but important differences that can produce the results outlined here, then it may well be the case that the development of reliable biomarkers of aging should be prioritized to a greater degree and work in nematodes and the like largely abandoned in favor of short mouse studies that assess effects on aging through the use of biomarker tests. The discussion below should be considered in the context of the comparatively small changes in life span achieved by most interventions, where it is reasonable to ask how that change came about and whether it was due to an influence on aging or some other factor. The future of the field, assuming that SENS rejuvenation research prospers, is to create increases in life span and health span so large that there is no room for debate as to what is taking place.

It has been argued that an extension of lifespan may not necessarily be concrete evidence of a retardation of the aging process. In this view, a lifespan-extending intervention may simply remedy deficiencies in the environment or in the genetic make-up of one particular strain. The intervention would therefore extend lifespan by correcting specific flaws rather than altering the aging process. These considerations create a conundrum: if lifespan is not a reliable measure of aging, how can we confirm that a particular manipulation truly affects the aging process? One approach is to assess physiological phenotypes which are known to deteriorate with age, such as cognition or the functioning of the cardiovascular or immune systems, in order to detect similarities or discrepancies with the patterns observed in control strains. An alternative criterion is to consider whether a particular manipulation changes how mortality rates increase with age. This is based on the hypothesis that the increased incidence of the age-related pathological changes that characterizes the aging process is reflected in changing mortality rates.

In the Gompertz model of mortality, 'G' describes the rate at which mortality rates accelerate with age and 'A' represents the initial mortality rate at time 0. 'A' is strictly theoretical as a mortality rate, since there can be no actual mortality at time 0. Instead, it can be determined by extrapolation from mortality rates at greater ages, and does not necessarily correspond to true mortality rates at birth or during youth. Decreasing 'A' extends lifespan by shifting the inflection point of the curve rightwards, such that it occurs proportionally later in age, relative to maximum lifespan. There is no change in the apparent "slope" of the curve. In contrast, decreasing 'G' extends lifespan by decreasing the slope. 'A' has been described as measuring the vulnerability to disease unrelated to the onset of aging, or the effect of the environment on mortality. Changes to 'A' will alter mortality rates evenly across the lifespan of the population. In contrast, since the parameter 'G' can be considered a rate constant for the age-related increase of mortality of a sample or population, it is often given a pre-eminent role as an indicator of the "rate of aging". This is a logical hypothesis, since an increased or decreased 'G' would likely reflect the rate at which physiological conditions are declining with age. Therefore it is often assumed that interventions that extend lifespan by slowing aging, rather than by alleviating some age-independent pathology, will be associated with a decreased 'G'.

Since a substantial number of studies reporting changes in mouse lifespan resulting from genetic manipulations have now been published, we hypothesized that a correlation-based approach may be a more powerful technique to search for patterns in Gompertz parameter shifts. For example, a negative correlation between lifespan and 'G' across long-lived lines of mice would suggest that their extended longevity was due to a decreased rate of aging. By the straightforward method of plotting Gompertz parameters against lifespan we found that most of the genetically-driven variability in lifespan between normal- or long-lived groups of mice was due to changes in 'A', not in 'G'. In fact, 'G' remained remarkably invariant for different groups of wild-type mice as well as for mice with genetic variations that extend lifespan. The only exceptions to this trend were some interventions which acutely shortened lifespan. We also found this to be true for a collection of inbred mice strains studied under uniform conditions as part of the Mouse Phenome Database. Thus, with the exception of some severe lifespan-shortening interventions, lifespan in laboratory mice is largely determined by factors that affect initial vulnerability, rather than age-dependent mortality rate acceleration. In contrast to mice, we found lifespan to be associated with changes in 'G', not 'A', among long-lived C. elegans mutants. This was true as a trend across long-lived mutants, and was also observed by analysing changes to Gompertz parameters among numerous replicate studies of the well-characterized daf-2, isp-1, and eat-2 mutants.

Link: http://dx.doi.org/10.1534/genetics.116.192369