Related Experiment Video
Updated: May 20, 2026
10:08
Surveying Low-Cost Methods to Measure Lifespan and Healthspan in Caenorhabditis elegans
Published on: May 18, 2022
A comparative cellular and molecular biology of longevity database
Jeffrey A Stuart1, Ping Liang, Xuemei Luo
1Department of Biological Sciences, Brock University, St. Catharines, ON, Canada, L2S 3A1, jstuart@brocku.ca.
Age (Dordrecht, Netherlands)
|July 28, 2012
Summary
A new database compiles cellular and molecular data from long-lived animals to understand longevity. This resource aids researchers in analyzing traits linked to extended lifespans through meta-analysis.
Area of Science:
- Gerontology
- Comparative Biology
- Molecular Biology
Background:
- Understanding the cellular and molecular basis of longevity is crucial in aging research.
- Comparative analysis of long-lived species offers insights into evolved longevity traits.
- Existing data on cell and molecular biology related to longevity is fragmented.
Purpose of the Study:
- To introduce the Comparative Cellular and Molecular Biology of Longevity Database.
- To provide a centralized, open-access compendium of longevity-related data.
- To facilitate meta-analysis of comparative cell and molecular data in the context of maximum lifespan.
Main Methods:
- Compilation of existing datasets on cellular and molecular traits from long-lived animals.
- Standardization of maximum lifespan (MLSP) data using the AnAge database.
- Development of an accessible online database (http://genomics.brocku.ca/ccmbl/).
Main Results:
- The database contains over 800 records of experimental measurements.
- Data includes cellular stress resistance, reactive oxygen species metabolism, membrane composition, protein homeostasis, and genome homeostasis.
- The database links these traits to vertebrate species' maximum lifespan (MLSP).
Conclusions:
- The Comparative Cellular and Molecular Biology of Longevity Database serves as a valuable resource for aging and longevity research.
- The database enables meta-analysis of amalgamated datasets to identify key longevity traits.
- This resource will advance the understanding of the evolutionary basis of longevity.
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