AnAge Longevity Database

The AnAge database includes information on the longevity of thousands of animal species, allowing studies of the factors related to long lifespans.

Motivation

The AnAge Database of Animal Ageing and Longevity is a “curated database of ageing and life history in animals” that was “primarily developed for comparative biology studies.” It contains information, compiled from hundreds of scientific papers, for over 4,200 species. It’s mainly meant for studies of aging, so for each species, it includes variables such as lifespan, age of sexual maturity, adult body mass, typical body temperature, and metabolic rate. We can use this data to learn more about the relationships between each variable and the key outcome variable: lifespan.

Data

Each observation is one animal species. Note that many variables are missing for individual species, so you may need to restrict your analysis to complete observations.

Data preview

anage.csv

Variable descriptions

Variable	Description
HAGRID	A unique ID for each entry (the Human Ageing Genomic Resources ID)
Kingdom	Along with the following variables (phylum, class, order, family, genus, and species), this gives the taxonomic classification of the species. Species names are typically given as genus and species, e.g. Anaxyrus americanus is the species name for the American toad.
Phylum	Phylum of the species
Class	Class of the species
Order	Order of the species
Family	Family of the species
Genus	Genus of the species
Species	Species name
Common.name	Common name (i.e., the name used by ordinary people, not scientists) for the animal
Maximum.longevity.yrs	Maximum longevity (lifespan), in years
Body.mass.g	Typical adult body mass, in grams
Metabolic.rate	Typical resting metabolic rate (i.e., rate of energy use), in Watts
Temperature	Typical body temperature, in Kelvin

Questions

1. Some research has suggested that slowing the metabolic rate—for example, by intermittent fasting—may increase lifespan. Is this supported by the evidence? Develop a model for lifespan using metabolic rate, and interpret what it means.
2. Is the relationship between metabolic rate and lifespan nonlinear, even after transformations? Use a nonparametric model to determine if a nonlinear fit is more appropriate.
3. Build a model to predict longevity using the available data. Evaluate its accuracy and report on any problems with the model.
4. Explain whether your model supports the conclusion that changing an animal’s metabolic rate, such as through medical intervention, would cause its mean lifespan to change.

References

The AnAge Database of Animal Ageing and Longevity, at https://genomics.senescence.info/species/index.html. Data made available under the Creative Commons Attribution 3.0 Unported License.