Multidimensional phenotyping predicts lifespan and quantifies health in Caenorhabditis elegans

Abstract

Ageing affects a wide range of phenotypes at all scales, but an objective measure of ageing remains challenging, even in simple model organisms. To measure the ageing process, we characterized the sequence of alterations of multiple phenotypes at organismal scale. Hundreds of morphological, postural, and behavioral features were extracted from high-resolution videos. Out of the 1019 features extracted, 896 are ageing biomarkers, defined as those that show a significant correlation with relative age (age divided by lifespan). We used support vector regression to predict age, remaining life and lifespan of individual C. elegans. The quality of these predictions (age R 2 = 0.79; remaining life R 2 = 0.77; lifespan R 2 = 0.72) increased with the number of features added to the model, supporting the use of multiple features to quantify ageing. We quantified the rate of ageing as how quickly animals moved through a phenotypic space; we quantified health decline as the slope of the declining predicted remaining life. In both ageing dimensions, we found that short lived-animals aged faster than long-lived animals. In our conditions, for isogenic wild-type worms, the health decline of the individuals was scaled to their lifespan without significant deviation from the average for short-or long-lived animals.

A Hierarchical Process Model Links Behavioral Aging and Lifespan inC. elegans

“…Using the lifespan machine, we collected by-hand annotated time-lapse images of 236 wild-type C. elegans nematodes housed on agar plates and fed UV-inactivated E. coli at 20 °C. In agreement with previous findings 11,12,17,18 , we observed variation in the times at which individuals slowed and cease locomotion late in life 18–20 . We confirmed, that contemporaneous to or shortly after their final movements, individuals exhibit a characteristic rapid decrease and then increase in apparent body size immediately after ceasing movement (Fig.…”

“…So, we introduced a frailty term 34,47 into the model, allowing each individual to have its own characteristic drift rate such that some individuals progressed faster on average than others. This frailty mimics the heterogeneity in aging rates observed in populations of C. elegans and humans, where indistinguishable individuals exhibit consistent, life-long differences in the risk of adverse age-associated events and visible aging phenotypes 11,17 . Adding frailty to our model produced a positive correlation between state transition time and subsequent state duration (Fig.…”

“…Here, we focus on two macroscopically observable outcomes of aging: behavioral decline and lifespan. Behavioral aging is a complex and high-dimensional process 11 but we reasoned that the automated microscopy platform "the lifespan machine" 12 could be applied to simultaneously characterize some age-associated changes in behavior and compare them to lifespan across very large populations. In this way, we could quantify the pleiotropic action of lifespan-extending interventions at high statistical and temporal resolution.…”

Maximally predictive ensemble dynamics from data

“…These emergent Markov dynamics offer a promising and powerful demonstration of quantitative connections across the hierarchy of movement behavior generally exhibited by all organisms [88,112]. Particularly interesting future directions include the analysis of even longer dynamics in C. elegans [113][114][115][116], for which no canonical behavioral states have been described.…”

Artificial Intelligence, Brains, and Beyond: Imperial College London Neurotechnology Symposium, 2020

“…To automate the image analysis, Ziwei Li (co-supervised by Prof. Anil Bharath and Dr. Andre Brown) presented a poster reporting the use of Deep (8-layer) Convolutional Neural Networks to tell if a certain number of pixels belongs to the image of the worm whereupon its movements could be tracked. 4 This method could ultimately be used to study worm behavior and screen drugs in 96-well plates.…”