老化
健康老龄化
医学
健康衰老
生物标志物
内科学
线性回归
脑老化
生物年龄
相关性
方差分析
内分泌学
老年学
生物
数学
生物化学
统计
几何学
疾病
作者
Irene Brusini,Eilidh MacNicol,Eugene Kim,Örjan Smedby,Chunliang Wang,Eric Westman,Mattia Veronese,Federico Turkheimer,Diana Cash
标识
DOI:10.1016/j.neurobiolaging.2021.10.004
摘要
The difference between brain age predicted from MRI and chronological age (the so-called BrainAGE) has been proposed as an ageing biomarker. We analyse its cross-species potential by testing it on rats undergoing an ageing modulation intervention. Our rat brain age prediction model combined Gaussian process regression with a classifier and achieved a mean absolute error (MAE) of 4.87 weeks using cross-validation on a longitudinal dataset of 31 normal ageing rats. It was then tested on two groups of 24 rats (MAE = 9.89 weeks, correlation coefficient = 0.86): controls vs. a group under long-term environmental enrichment and dietary restriction (EEDR). Using a linear mixed-effects model, BrainAGE was found to increase more slowly with chronological age in EEDR rats (p=0.015 for the interaction term). Cox regression showed that older BrainAGE at 5 months was associated with higher mortality risk (p=0.03). Our findings suggest that lifestyle-related prevention approaches may help to slow down brain ageing in rodents and the potential of BrainAGE as a predictor of age-related health outcomes.
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