Turns Out Your Body Isn’t Always the Same Age as Your Brain

Machine learning is taking computerized medicine to new levels, and thanks to the new technology, we can predict how long we’re going to live. A team of researchers at Imperial College in London has developed a technique that compares brain volume with loss of grey and white matter to determine how fast the brain is aging. They found that the greater the gap between a person’s brain age and their actual age, the higher the risk for early death and deteriorating mental and physical health.

The researchers calculated the brain age using neuroimaging data from an abundant reference sample and machine learning analysis. They first tested the model on the brains of 2,001 healthy adults between the ages of 18 and 90 with a T1-weighted MRI scan. This assessment allowed the researchers to adjust and fine-tune the protocol before they tested the technique on The Lothian Birth Cohort, a group of 669 73-year-olds in Scotland who underwent a mental ability test when they were 11-years-old. The Cohort has been used in over 75 studies on cognitive aging.

The assessment found that individuals with “older brains” were more likely to die before the age of 80. On average, there was an eight-year difference between brain age and chronological age for deceased men and a two-year discrepancy for females. The researchers also discovered that those with brains older than their physical age had a weaker grip strength and lung function, slower walking pace, and “lower fluid general intelligence”. They surmised that those with older brains had also been exposed to a larger allostatic load, or biological ‘wear and tear.’ On the flip side, they learned that those with “younger brains” engaged in regular meditation and/or exercise.

“This study provides evidence that neuroimaging data can be used to construct a viable ageing biomarker, and potentially provides important prognostic information, particularly in combination with complementary epigenetic ageing data,” write the researchers. “A global biomarker of ageing has the potential to screen for asymptomatic individuals who are experiencing adverse ageing and thus are at increased risk of future ill-health and could be used as a surrogate outcome measure in clinical trials of neuroprotective treatments and anti-ageing therapeutics.”