Deep behavioural phenotyping reveals divergent trajectories of ageing and quantifies health state in C. elegans

Abstract

Neurodegenerative diseases may be the cause or the consequence of an acceleration of physiological ageing. Evidence for this concept is lacking due to practical limitations of human studies. Here, we compared the processes of physiological and pathological ageing of individual C. elegans over their lifespan. Using multi-parametric phenotyping, trajectories of ageing can be defined within a phenotypic landscape made of a large set of phenotypical features. Rather than an acceleration of ageing, a model for synucleinopathy showed a divergent trajectory of ageing. The pathological progression in individual animals can be predicted from early phenotypes with high accuracy. Despite of similar lifespans, disease-model worms display an early onset of decline in their phenotypic range of ability. This loss of flexibility provides an index of health valid for physiological and pathological contexts. Finally, we demonstrate the power of multi-parametric dataset to describe ageing, to quantify health and to predict specific health risks.