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A hierarchical process model links behavioral aging and lifespan in C. elegans

Oswal, Natasha, Martin, Olivier M. F., Stroustrup, Sofia, Bruckner, Monika Anna Matusiak, Stroustrup, Nicholas·2022·PLOS Computational Biology
DOI 10.1371/journal.pcbi.1010415PMC PMC9524676

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Abstract

Aging involves a transition from youthful vigor to geriatric infirmity and death. Individuals who remain vigorous longer tend to live longer, and within isogenic populations of C . elegan s the timing of age-associated vigorous movement cessation (VMC) is highly correlated with lifespan. Yet, many mutations and interventions in aging alter the proportion of lifespan spent moving vigorously, appearing to “uncouple” youthful vigor from lifespan. To clarify the relationship between vigorous movement cessation, death, and the physical declines that determine their timing, we developed a new version of the imaging platform called “The Lifespan Machine”. This technology allows us to compare behavioral aging and lifespan at an unprecedented scale. We find that behavioral aging involves a time-dependent increase in the risk of VMC, reminiscent of the risk of death. Furthermore, we find that VMC times are inversely correlated with remaining lifespan across a wide range of genotypes and environmental conditions. Measuring and modelling a variety of lifespan-altering interventions including a new RNA-polymerase II auxin-inducible degron system, we find that vigorous movement and lifespan are best described as emerging from the interplay between at least two distinct physical declines whose rates co-vary between individuals. In this way, we highlight a crucial limitation of predictors of lifespan like VMC—in organisms experiencing multiple, distinct, age-associated physical declines, correlations between mid-life biomarkers and late-life outcomes can arise from the contextual influence of confounding factors rather than a reporting by the biomarker of a robustly predictive biological age.

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Metadata

Authors
Oswal, N., Martin, O. M. F., Stroustrup, S., Bruckner, M. A. M., & Stroustrup, N.
ORCID
Venue
PLOS Computational Biology
Publisher
Public Library of Science (PLoS)
Published
2022-09-30
Volume
18
Issue
9
Pages
e1010415
ISSN
1553-7358
DOI
10.1371/journal.pcbi.1010415
PMC
PMC9524676
Cited by
27
References
6
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • H2020 European Research Council (852201)
  • Spanish Ministry of Economy, Industry and Competitiveness
  • Centro de Excelencia Severo Ochoa (CEX2020-001049-S, MCIN/AEI /10.13039/501100011033)
  • CERCA Programme/Generalitat de Catalunya
  • MEIC Excelencia (BFU2017-88615-P)
  • Glenn Foundation for Medical Research

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