Wing David, Eyler Lisa T, Lenze Eric J, Wetherell Julie Loebach, Nichols Jeanne F, Meeusen Romain, Godino Job G, Shimony Joshua S, Snyder Abraham Z, Nishino Tomoyuki, Nicol Ginger E, Nagels Guy, Roelands Bart
Herbert Wertheim School of Public Health and Human Longevity, University of California, San Diego, United States.
Exercise and Physical Activity Resource Center (EPARC), University of California, San Diego, United States.
Neuroimage Rep. 2022 Dec;2(4). doi: 10.1016/j.ynirp.2022.100146. Epub 2022 Nov 18.
Changes in brain structure and function occur with aging. However, there is substantial heterogeneity both in terms of when these changes begin, and the rate at which they progress. Understanding the mechanisms and/or behaviors underlying this heterogeneity may allow us to act to target and slow negative changes associated with aging.
Using T1 weighted MRI images, we applied a novel algorithm to determine the physiological age of the brain (brain-predicted age) and the predicted age difference between this physiologically based estimate and chronological age (BrainPAD) to 551 sedentary adults aged 65 to 84 with self-reported cognitive complaint measured at baseline as part of a larger study. We also assessed maximal aerobic capacity with a graded exercise test, physical activity and sleep with accelerometers, and body composition with dual energy x-ray absorptiometry. Associations were explored both linearly and logistically using categorical groupings.
Visceral Adipose Tissue (VAT), Total Sleep Time (TST) and maximal aerobic capacity all showed significant associations with BrainPAD. Greater VAT was associated with higher (i.e,. older than chronological) BrainPAD (r = 0.149 p = 0.001)Greater TST was associated with higher BrainPAD (r = 0.087 p = 0.042) and greater aerobic capacity was associated with lower BrainPAD (r = - 0.088 p = 0.040). With linear regression, both VAT and TST remained significant (p = 0.036 and 0.008 respectively). Each kg of VAT predicted a 0.741 year increase in BrainPAD, and each hour of increased TST predicted a 0.735 year increase in BrainPAD. Maximal aerobic capacity did not retain statistical significance in fully adjusted linear models.
Accumulation of visceral adipose tissue and greater total sleep time, but not aerobic capacity, total daily physical activity, or sleep quantity and/or quality are associated with brains that are physiologically older than would be expected based upon chronological age alone (BrainPAD).
大脑结构和功能会随着衰老而发生变化。然而,这些变化开始的时间以及进展速度存在很大的异质性。了解这种异质性背后的机制和/或行为,可能使我们能够采取行动,针对并减缓与衰老相关的负面变化。
利用T1加权磁共振成像(MRI)图像,我们应用一种新算法来确定大脑的生理年龄(脑预测年龄)以及基于生理的估计值与实际年龄之间的预测年龄差(脑年龄预测差异,BrainPAD),该算法应用于551名年龄在65至84岁的久坐不动的成年人,这些成年人在基线时自我报告有认知问题,这是一项更大规模研究的一部分。我们还通过分级运动测试评估最大有氧能力,用加速度计评估身体活动和睡眠情况,并用双能X线吸收法评估身体成分。使用分类分组对线性和逻辑关联进行了探究。
内脏脂肪组织(VAT)、总睡眠时间(TST)和最大有氧能力均与BrainPAD显示出显著关联。更多的内脏脂肪组织与更高的(即,比实际年龄更大的)BrainPAD相关(r = 0.149,p = 0.001);更多的总睡眠时间与更高的BrainPAD相关(r = 0.087,p = 0.042),而更大的有氧能力与更低的BrainPAD相关(r = - 0.088,p = 0.040)。通过线性回归分析,内脏脂肪组织和总睡眠时间仍然具有显著性(分别为p = 0.036和0.008)。每千克内脏脂肪组织预测BrainPAD增加0.741岁,总睡眠时间每增加一小时预测BrainPAD增加0.735岁。在完全调整的线性模型中,最大有氧能力没有保留统计学显著性。
内脏脂肪组织的积累和更长的总睡眠时间,但不是有氧能力、每日总身体活动量或睡眠数量和/或质量,与生理年龄比仅根据实际年龄预期的更大的大脑(BrainPAD)相关。