Neuroimaging data used to construct viable aging biomarker

U.K. and Aussie researchers have introduced a clinically relevant neuroimaging biomarker of aging-related brain deterioration and, in the process, shown how brain age predicts mortality.  

Dr. James Cole of Imperial College London and colleagues had their work published online April 25 in Molecular Psychiatry.

The team analyzed neuroimaging data from 2,001 healthy reference patients to calculate brain age using machine-learning algorithms. They used 669 cases in the Lothian Birth Cohort of 1936 to determine relationships with age-associated functional measures and mortality.

The researchers found that having a brain-predicted age indicative of an older-appearing brain was associated with weaker grip strength, poorer lung function, slower walking speed, lower fluid intelligence, higher allostatic load and increased mortality risk.

What’s more, while combining brain-predicted age with gray matter and cerebrospinal fluid volumes—themselves strong predictors—not did improve mortality risk prediction, the combination of brain-predicted age and DNA-methylation-predicted age did, the authors write.

“This study provides evidence that neuroimaging data can be used to construct a viable aging biomarker, and potentially provides important prognostic information, particularly in combination with complementary epigenetic aging data,” conclude Cole et al. “A global biomarker of aging has the potential to screen for asymptomatic individuals who are experiencing adverse aging 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-aging therapeutics.”

The journal has posted the study in full for free.