If you’ve been following efforts to slow aging in laboratory animals for any great length of time, then you should find the open access paper I’ll point out today to be quite interesting – though note that the full text is PDF only at the time of writing. As a general rule, it is a lot harder to dissect the statistical shape of aging for a population than it is to just put numbers to mean and maximum life span. Measuring health to any useful level of detail is far more labor intensive than counting the study animals who are still alive. This means that there is actually comparatively little information on the numerous methods of slightly slowing aging when it comes to what exactly that means in various species: a longer span of health, a longer span of ill health, slower aging at the outset, slower aging at the end, the development of plateaus in which little aging takes place, and so forth.
For smaller and shorter-lived species such as nematodes, there is the potential to solve this problem with automation, however. In the past few years researchers have made considerable progress in automating lifespan and healthspan studies of nematodes, with one group constructing a Lifespan Machine that enables data mining of the health and longevity across tens of thousands of individuals. The authors of the paper quoted below have built what they call the WorMotel, serving a similar function. This new data is enabling a variety of novel insights.
What does this tell us about slowing aging? Judging from this latest set of results, it looks like yet another illustration to show that everything in the intersection of cellular metabolism and aging is more complex than we’d like it to be. More data is needed, and in gathering that data there continues to be some debate over the sort of outcome that is produced by any specific intervention: extended youth or extended decline. Do these interventions increase resistance to the consequences of damage, which seems the likely cause of an extended period of decline, or postpone damage, which seems the likely cause of extended youth? It would be very interesting to see what an analogous Lifespan Machine or WorMotel would find in flies, or in mice – though the cost would be prohibitive for mouse studies in the current model of automation.
For further consideration, bear in mind that slowing aging is itself a completely different mode of intervention from that of rejuvenation produced by repair of damage – the SENS approach. We don’t yet have much to go on when it comes to how repair therapies differ in outcomes between species, or between individuals, or between approaches. Only one such class of therapy has any life span studies to reference, those for senescent cell clearance. Even there only a couple of studies exist and only a comparatively small number of animal subjects have undergone the therapies. There is every reason to expect that repair therapies will look very different from methods of slowing aging in the results produced, but we won’t know the full details across populations and species for years yet, even for removal of senescent cells. Still, the sort of analysis in the paper below is exactly the sort of thing we’d like to see applied to rejuvenation therapies as they emerge from the laboratory.
Here we describe the WorMotel, a microfabricated device for long-term cultivation and automated longitudinal imaging of large numbers of C. elegans confined to individual wells. Using the WorMotel, we find that short-lived and long-lived strains exhibit patterns of behavioral decline that do not temporally scale between individuals or populations, but rather resemble the shortest and longest lived individuals in a wild type population.
While many factors are known to modulate the mean lifespan of a population, less is known about how these factors alter the aging process on an individual level. It was recently shown that within a wild-type population, long-lived and short-lived animals differed in two ways. First, the rate of physiological decline was slower in long-lived individuals, as might be expected. The second, however, was counter-intuitive: the additional lifespan of longer-lived individuals was primarily due to differences toward the end of the lifespan. That is, long-lived animals exhibited longer periods of low physiological function, or ‘extended twilight’. A different picture was suggested by a study using automated assays of lifespan in the ‘Lifespan machine’. In this study it was reported that various genetic and environmental perturbations do not fundamentally change the shape of the survival curve, but rather only compress or dilate it in time. This result was interpreted as suggesting that the aging process in C. elegans is, at least at some point in its pathway, controlled by a single process describable by a single variable corresponding to the rate of aging.
We sought to determine to what extent, ‘extended twilight’ and/or scaling effects apply at the behavioral level in mutants with altered aging. The concept of a universal scaling parameter in aging would suggest that the short and long-lived individuals within any strain (whether with normal, short, or long mean lifespan) would resemble their short and long-lived counterparts in the reference strain, but with a temporal scaling. If the variations in aging rate among individuals in any isogenic strain are governed by similar factors, we would expect that long and short lived individuals would display similar late-life characteristics as their wild type counterparts. If, on the other hand, short-lived strains as a whole physiologically more closely resemble short-lived individuals of a wild type population, we might expect them to display late-life characteristics similar to these short lived individuals. Similarly, long-lived strains might display a range of late-life decays or alternatively collectively resemble long-lived worms in the reference strain.
Wild-type strain N2 worms exhibited an initial decline followed by a ‘plateau’ period of nearly constant spontaneous and stimulated activity and response duration and latency. When we compared the behavior of the shortest-lived and longest-lived quartile of N2 worms, we found that their behavioral declines were qualitatively different. The longest-lived animals exhibited a “decline and plateau” phenotype, in which an initial rapid decline in behavioral capacity is later replaced by a very gradual decline for the remainder of life. By contrast, the shortest-lived animals showed only the rapid decline in behavior before dying. The result that long-lived animals experience a long period of low behavior are consistent with the ‘extended twlight’ reported by other researchers.
Short-lived daf-16 mutants declined at a similar rate to N2, but did not exhibit any plateau phase; instead, daf-16 worms die after their initial behavioral decline. A similar effect was seen in daf-16 response duration and response latency, which do not level off but decrease or increase, respectively, at a similar rate until the time of death. Comparing the activity history of the shortest-lived N2 worms to that of daf-16 as a whole, we found a striking correspondence between the behavioral decline of the two groups. These results show that the behavioral decline of daf-16 animals is not a scaled version of the wild type distribution of decline, but instead resembles the short-lived individuals in a wild-type population.
Long-lived daf-2 mutants, in which behavioral quiescence has been previously reported, exhibited a decline in stimulated activity akin to that observed in N2 and daf-16 followed by a nearly constant low level of stimulated activity and response behaviors for the remainder of life. Spontaneous activity in daf-2, on the other hand, declined to near zero within 10 days of adulthood, where it remained until death. Long-lived strains age-1, tax-4, and unc-31 also exhibited the “decline and plateau” phenotype. These results show that aging behavior of daf-2 and other long-lived animals, like that of daf-16 animals, does not resemble a scaled version of wild type. Instead, they resemble the longest-lived individuals in a wild-type population, in that they exhibit a long plateau period of low locomotory function during late life.
These results suggest that the sources of variability in lifespan in individuals also impact functional decline in a corresponding manner. For example, the N2 worm that survives 15 days due to stochastic factors will decline in a similar manner to the daf-16 worm that survives 15 days. Furthemore, individuals with a 30-day lifespan will exhibit a different shape of functional decline, but this shape is dictated by the confluence of genetic and stochastic factors that result in the lifespan of 30 days.