DNA may predict potential lifespan, study finds

Scientists say they can predict whether a person can expect to live longer or die sooner than average, by looking at their DNA.

The team has analysed the combined effect of genetic variations that influence lifespan to produce a scoring system.

Longevity score

People who score in the top ten per cent of the population might expect to live up to five years longer than those who score in the lowest ten per cent, they say.

The findings also revealed fresh insights into diseases and the biological mechanisms involved in ageing, the researchers say.

If we take 100 people at birth, or later, and use our lifespan score to divide them into ten groups, the top group will live five years longer than the bottom on average.

Dr Peter Joshi
AXA Fellow, The Usher Institute

DNA data

Experts at the University of Edinburgh’s Usher Institute looked at genetic data from more than half a million people alongside records of their parents’ lifespan.

Some 12 areas of the human genome were pinpointed as having a significant impact on lifespan, including five sites that have not been reported before.

Lifespan

The DNA sites with the greatest impact on overall lifespan were those that have previously been linked to fatal illnesses, including heart disease and smoking-related conditions.

We found genes that affect the brain and the heart are responsible for most of the variation in lifespan.

Paul Timmers
PhD student, The Usher Institute

Genetic differences

Genes that have been linked to other cancers, not directly associated with smoking, did not show up in this study, however.

This suggests that susceptibility to death caused by these cancers is either a result of rarer genetic differences in affected people, or social and environmental factors.

Ageing

The researchers had hoped to discover genes that directly influence how quickly people age. They say that if such genes exist, their effects were too small to be detected in this study.

The research, published in the journal eLife, was funded by the UK Medical Research Council and the AXA Research Fund. The study was carried out using data from UK Biobank, a research resource containing health and genetic information for half a million people.

Related links

Journal article