ArticlePLoS computational biology2020
Multidimensional phenotyping predicts lifespan and quantifies health in Caenorhabditis elegans.
Article in PLoS computational biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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Who cites it
17 citing papers in PubMed.
- Development of a universal imaging "phenome" using shape, appearance and motion (SAM) features and the SAM Phenotype Observation Tool (SPOT).Nature communications · 2026Article
- Lifelong behavioral screen reveals an architecture of vertebrate aging.Science (New York, N.Y.) · 2026Article
- A comprehensive review of artificial intelligence as a catalyst in aging research: insights, gaps and future perspectives.Frontiers in aging · 2026Review
- Life-long behavioral screen reveals an architecture of vertebrate aging.bioRxiv : the preprint server for biology · 2025Article
- HarnessingSensors (Basel, Switzerland) · 2025Review
- Beyond genes and environment: mapping biological stochasticity in aging.GeroScience · 2025Review
- Similarities and differences in the gene expression signatures of physiological age versus future lifespan.Aging cell · 2025Article
- A high precision method of segmenting complex postures in Caenorhabditis elegans and deep phenotyping to analyze lifespan.Scientific reports · 2025Article
- A Markovian dynamics forProceedings of the National Academy of Sciences of the United States of America · 2024Article
- Multisite regulation integrates multimodal context in sensory circuits to control persistent behavioral states in C. elegans.Nature communications · 2023Article
- Analysis of aComputational and structural biotechnology journal · 2023Article
- Article
- Estimation of Caenorhabditis Elegans Lifespan Stages Using a Dual-Path Network Combining Biomarkers and Physiological Changes.Bioengineering (Basel, Switzerland) · 2022Article
- A hierarchical process model links behavioral aging and lifespan in C. elegans.PLoS computational biology · 2022Article
- Automated, high-dimensional evaluation of physiological aging and resilience in outbred mice.eLife · 2022Article
- High temporal resolution measurements of movement reveal novel early-life physiological decline in C. elegans.PloS one · 2022Article
- Artificial Intelligence, Brains, and Beyond: Imperial College London Neurotechnology Symposium, 2020.Bioelectricity · 2020Article
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Authors and funding
3 authors.
Funding
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 R2 = 0.79; remaining life R2 = 0.77; lifespan R2 = 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.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.