DNA clock can predict lifespan

Scientists have identified a biological clock that provides vital clues about how long a person is likely to live.
Researchers from the University of Edinburgh, in collaboration with scientists in Australia and the US, studied chemical changes to DNA that take place over a lifetime.
When researchers compared individuals' actual ages with their predicted biological clock age, a pattern emerged.
People whose biological age was greater than their true age were more likely to die sooner than those whose biological and actual ages were the same.
Four independent studies tracked the lives of almost 5,000 older people for up to 14 years. Each person's biological age was measured from a blood sample at the outset, and participants were followed up throughout the study.

Researchers found that the link between having a faster-running biological clock and early death held true even after accounting for other factors such as smoking, diabetes and cardiovascular disease.

"The same results in four studies indicated a link between the biological clock and deaths from all causes," said Dr Riccardo Marioni, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh.
"At present, it is not clear what lifestyle or genetic factors influence a person's biological age. We have several follow-up projects planned to investigate this in detail," Marioni said.
The study measured each person's biological age by studying a chemical modification to DNA, known as methylation.

The modification does not alter the DNA sequence, but plays an important role in biological processes and can influence how genes are turned off and on.
Methylation changes can affect many genes and occur throughout a person's life.
"This new research increases our understanding of longevity and healthy ageing. It is exciting as it has identified a novel indicator of ageing, which improves the prediction of lifespan over and above the contribution of factors such as smoking, diabetes, and cardiovascular disease," said Professor Ian Deary Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh.
The study is published in the journal Genome Biology.