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Updated: Jun 5, 2025

Surveying Low-Cost Methods to Measure Lifespan and Healthspan in Caenorhabditis elegans
Published on: May 18, 2022
Similarities and differences in the gene expression signatures of physiological age versus future lifespan
Matthew C Mosley1, Holly E Kinser2, Olivier M F Martin3,4
1Department of Developmental Biology, Washington University in St. Louis, St. Louis, Missouri, USA.
Abstract:
Across all taxa of life, individuals within a species exhibit variable lifespans. Differences in genotype or environment are not sufficient to explain this variance, as even isogenic Caenorhabditis elegans nematodes reared under uniform conditions show significant variability in lifespan. To investigate this phenomenon, we used lifespan-predictive biomarkers to isolate, at mid-adulthood, prospectively long- and short-lived individuals from an otherwise identical population. We selected two biomarkers which correlated positively with lifespan, lin-4p::GFP and mir-243p::GFP, and two which correlated negatively, mir-240/786p::GFP and autofluorescence. The gene-expression signature of long versus short future lifespan was strikingly similar across all four biomarkers tested. Since these biomarkers are expressed in different tissues, these results suggest a shared connection to a global health state correlated with future lifespan. To further investigate this underlying state, we compared the transcriptional signature of long versus short future lifespan to that of chronologically young versus old individuals. By comparison to a high-resolution time series of the average aging transcriptome, we determined that subpopulations predicted to be long- or short-lived by biomarker expression had significantly different transcriptional ages despite their shared chronological age. We found that this difference in apparent transcriptional age accounted for the majority of differentially expressed genes associated with future lifespan. Interestingly, we also identified several genes whose expression consistently separated samples by biomarker expression independent of apparent transcriptional age. These results suggest that the commonalities in the long-lived versus short-lived state reported across different biomarkers of aging extends beyond simply transcriptionally young versus transcriptionally old.
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