title: A computational approach to studying ageing at the individual level.
abstract: The ageing process is actively regulated throughout an organism's life, but studying the rate of ageing in individuals is difficult with conventional methods. Consequently, ageing studies typically make biological inference based on population mortality rates, which often do not accurately reflect the probabilities of death at the individual level. To study the relationship between individual and population mortality rates, we integrated in vivo switch experiments with in silico stochastic simulations to elucidate how carefully designed experiments allow key aspects of individual ageing to be deduced from group mortality measurements. As our case study, we used the recent report demonstrating that pheromones of the opposite sex decrease lifespan in Drosophila melanogaster by reversibly increasing population mortality rates. We showed that the population mortality reversal following pheromone removal was almost surely occurring in individuals, albeit more slowly than suggested by population measures. Furthermore, heterogeneity among individuals due to the inherent stochasticity of behavioural interactions skewed population mortality rates in middle-age away from the individual-level trajectories of which they are comprised. This article exemplifies how computational models function as important predictive tools for designing wet-laboratory experiments to use population mortality rates to understand how genetic and environmental manipulations affect ageing in the individual.
authors: Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI 48109, USA Medical Scientist Training Program, University of Michigan, Ann Arbor, MI 48109, USA.
authors: Zachary M
authors: http://orcid.org/0000-0003-3702-1051
authors: ZM
authors: Harvanek
authors: Mathematical Biosciences Institute, The Ohio State University, Columbus, OH 43210, USA.
authors: Márcio A
authors: MA
authors: Mourão
authors: Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI 48109, USA Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, MI 48109, USA schnells@umich.edu.
authors: Santiago
authors: S
authors: Schnell
authors: Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI 48109, USA Geriatrics Center, University of Michigan, Ann Arbor, MI 48109, USA spletch@umich.edu.
authors: Scott D
authors: SD
authors: Pletcher
mesh_terms: D000375:Aging; D000818:Animals; D004331:Drosophila melanogaster / Q000502:physiology*; D005260:Female; D008136:Longevity; D008297:Male; D008954:Models, Biological; D010675:Pheromones / Q000378:metabolism*
chemical_list: D010675:Pheromones
keywords: ageing; heterogeneity; mortality; reproduction; stochastic models