New Insight into The Biology of Aging
Researchers from Harvard Medical School have found patterns that may provide clues into the biological basis of aging.
The research team, led by Novartis Fellow Nicholas Stroustrup, found a surprising statistical regularity in how a variety of genetic and environmental factors affect the life span of the Caenorhabditis elegans worm. Their findings suggest that aging does not have a single discrete molecular cause but is rather a systemic process involving many components within a complex biological network. Perturb any node in the system, and you affect the whole thing.
The study, published in Nature, offers an alternative to research that seeks to identify a specific master aging mechanism, such as protein homeostasis or DNA damage.
“There are many important molecular changes that occur with age, but it might not make sense to call all of them ‘causes of aging,’ per se,” said Stroustrup, first author on the paper.
In order to study life span dynamics at the population level, Stroustrup constructed the Lifespan Machine, a device comprising 50 off-the-shelf flatbed scanners purchased from an office supplies store. Each scanner has been retooled to record 16 petri dishes every hour, totaling 800 dishes and 30,000 worms. The scanners capture images at 3,200 dots per inch, which is a resolution high enough to detect movements of eight micrometers, or about 12 percent of the width of an average worm.
Stroustrup subjected the worms to interventions as diverse as temperature changes, oxidative stress, changes in diet and genetic manipulations that altered, for example, insulin growth factor signaling. The Lifespan Machine recorded how long it took the worms to die under each condition. Stroustrup then aggregated the data, generated life span distribution curves for each intervention and compared results.
The life span distributions provided considerably more information than just changes in average life span. The research team measured variations arising in ostensibly identical individuals, looking at how many worms died young versus how many made it to old age under each condition. This comprehensive view was important for capturing the dynamics and randomness in the aging process.
In one sense, the findings were not surprising: different circumstances produced different life spans. Turning up the heat caused the worms to die quickly, and turning it up higher only increased that rate. Pictured as bell-shaped distributions, certain interventions produced a thinner, high-peaked bell, while others resulted in a more drawn-out and protracted bell.
Despite these obvious differences, the researchers found an unexpected uniformity among the curves, observing what statisticians call “temporal scaling.” Stated for the rest of us, if you were to take all of the bell-shaped curves and expand or contract them along the X-axes (which in this study represented time), they would become statistically indistinguishable.