Will you live to be 100?
SCIENTISTS are claiming a genetic test can predict whether someone will live to 100 years old.
The study, undertaken by researchers from the Boston University Schools of Public Health and Medicine, Boston Medical Center, IRCCS Multimedica in Milan, Italy, and Yale University claims to be able to predict exceptional longevity with 60 to 85 percent accuracy, depending on the subject's age.
The study said centenarians are a model of healthy aging, as the onset of disability in these individuals is generally delayed until they are well into their mid-90s.
Because exceptional longevity can run strongly in families, and numerous animal studies have suggested a strong genetic influence on life span, the researchers set out to determine which genetic variants play roles in human survival beyond 100 years of age.
The study found subjects who shared the same profile of variations for genetic markers appeared to share similar levels of risk for various traits or diseases associated with exceptional longevity.
People who shared these genetic traits could expect to live longer.
The study could also explain why living beyond the age of 100 appears to run in families.
The findings are the corrected version of work originally published in Science in July last year.
That study was voluntarily retracted, and the latest version includes data from exceptionally old subjects, with an average age of 107.
Thomas Perls, MD, MPH, associate professor of medicine at the Boston University School of Medicine described the findings as a "useful step towards meaningful predictive medicine and personal genomics".
"When people can do this kind of analysis on whole genome sequences for traits that have important genetic components, the predictive value should be even better.
"Further study of these genetic characteristics may yield a better understanding of the genetic and biological bases of delaying or escaping age-related diseases and achieving longer survival," Dr Perls said.
"The novel approach to genetic data that is described here is likely applicable to other complex inherited traits, and we look forward to other research groups applying these methods to their data."