Brain age predicts mortality

TY - JOUR

T1 - Brain age predicts mortality

AU - Cole, J. H.

AU - Ritchie, S J

AU - Bastin, M E

AU - Valdés Hernández, M C

AU - Muñoz Maniega, S

AU - Royle, N

AU - Corley, J

AU - Pattie, A

AU - Harris, S E

AU - Zhang, Q

AU - Wray, N R

AU - Redmond, P

AU - Marioni, R E

AU - Starr, J M

AU - Cox, S R

AU - Wardlaw, J M

AU - Sharp, D J

AU - Deary, I J

PY - 2017/4/25

Y1 - 2017/4/25

N2 - Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. 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. Furthermore, while combining brain-predicted age with grey 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. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.Molecular Psychiatry advance online publication, 25 April 2017; doi:10.1038/mp.2017.62.

AB - Age-associated disease and disability are placing a growing burden on society. However, ageing does not affect people uniformly. Hence, markers of the underlying biological ageing process are needed to help identify people at increased risk of age-associated physical and cognitive impairments and ultimately, death. Here, we present such a biomarker, 'brain-predicted age', derived using structural neuroimaging. Brain-predicted age was calculated using machine-learning analysis, trained on neuroimaging data from a large healthy reference sample (N=2001), then tested in the Lothian Birth Cohort 1936 (N=669), to determine relationships with age-associated functional measures and mortality. 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. Furthermore, while combining brain-predicted age with grey 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. This indicates that neuroimaging and epigenetics measures of ageing can provide complementary data regarding health outcomes. Our study introduces a clinically-relevant neuroimaging ageing biomarker and demonstrates that combining distinct measurements of biological ageing further helps to determine risk of age-related deterioration and death.Molecular Psychiatry advance online publication, 25 April 2017; doi:10.1038/mp.2017.62.

KW - Journal Article

U2 - 10.1038/mp.2017.62

DO - 10.1038/mp.2017.62

M3 - Article

C2 - 28439103

SN - 1359-4184

VL - 23

SP - 1385

EP - 1392

JO - Molecular Psychiatry

JF - Molecular Psychiatry

ER -