A Molecular Map of Aging
A new genetic database could help reveal why animals age so differently.
Even closely related animals can have drastically different life spans, a fact that scientists have been puzzling over for years. Mice, which live about two years, got the short end of the longevity stick: their rodent cousin, the Southern flying squirrel, can live nearly 20 years. Chimps are 99 percent genetically identical to humans but live only half as long. Now a new resource could help pinpoint the genetic changes that underlie those differences.
In a study of mice, researchers at Stanford University and the National Institute on Aging (NIA) have generated a database that catalogues how gene expression–a measure of how active a gene is–changes in different parts of the body as the animals age. The researchers’ findings suggest that different tissues age very differently, and this could help pinpoint when it is appropriate to use mice as a model of human aging–and when it’s not.
Previous studies in both mice and humans have examined how gene expression changes with age in specific parts of the body, such as the brain or the kidneys. But the new study, commissioned by the NIA, analyzed simultaneously the activity of thousands of genes in 16 different tissues at different points during the animals’ lives. That allowed researchers to compare age-related patterns of gene expression between different organs.
“One of the key lessons of this work is that to understand aging, we need to be thinking not in terms of individual genes, but of networks of genes and systems of different organs,” says Daniel Promislow, a biologist at the University of Georgia in Athens, who was not involved in the project.
The results, published this week in the journal PLoS Genetics, confirm the role of two processes believed to be major contributors to aging: slowed metabolism and increased inflammation. The expression of genes linked to both processes changed globally in aging mice. But the researchers also found large disparities in different tissues: expression profiles in the liver, brain, and muscle changed very little with age, while those in the lungs, the eyes, and the thymus (an immune organ) underwent the most radical transformation.
The researchers also found distinct patterns of aging in different tissues: neural, vascular, and endocrine tissue each had a characteristic expression profile. “It appears that the mouse has a mosaic of different things going on which may or may not be in synchrony with each other,” says Stuart Kim, a biologist at Stanford who led the work. These patterns of gene-expression changes aren’t clearly linked to oxidative stress–an excess of free radicals that damage cells–or other biochemical factors hypothesized to trigger aging, says Kim, so it’s not yet clear how they influence aging.
The researchers also compared their findings with previous studies analyzing gene-expression changes in aging brain, muscle, and kidney tissue in humans, as well as in the tissues of flies and worms. The researchers found one theme universal to gene expression and aging: the slowing of a cell’s energy factory. In each of these species, expression of genes related to energy production dropped twofold by the end of an animal’s life span–about 2 years in mice and 80 years in humans. “This is the only common property of growing old between the four different animals,” says Kim. “Maybe that should alert us to say there is something unavoidable to getting old.”
However, researchers found few other similarities, raising the issue of how good of a model mice–or any of the other standard lab animals–provide for studying human aging. For example, studies in humans and other animals suggest that length of telomeres–repetitive strips of DNA at the end of each chromosome–is linked to aging. But researchers didn’t find changes in expression of telomere-related genes in mice as they aged. “I wouldn’t say that this means that model organisms can’t be used to study aging in humans,” says Promislow. “It does suggest there is a lot more going on.”
Kim’s analysis is likely the first of many analyses that will take advantage of the new database, dubbed AGEMAP. Scientists still need to figure out the function of the genetic networks implicated in aging.
“The scale of this study is phenomenal,” says Promislow. “In some ways, this shows us where things are likely to be headed in coming years in terms of the kinds of experiments people will do to understand the genetic basis of complex traits.”