Deep Behavioural Phenotyping Reveals Divergent Trajectories of Ageing and Quantifies Health in  C. elegans

Abstract

Neurodegenerative diseases are suggested as a cause or a consequence of the acceleration of physiological ageing processes. Here, we compared the processes of physiological and pathological ageing in Caenorhabditis elegans. A multi-parametric approach precisely described the phenotypic evolution of each individual. Trajectories of ageing within the phenotypic landscape are defined and analysed. Rather than an acceleration of ageing, our model for synucleinopathy showed a divergent and accelerated trajectory of ageing, compared to control. Despite of similar lifespans, the disease-model worms displayed an early onset of decline in their phenotypic range of ability, an index of health. The pathological progression of individual animals can be predicted from early phenotypes with a high accuracy. We demonstrate the power of multi-parametric dataset to describe ageing, to quantify health and to predict specific health risks.