David Wing , Lisa T. Eyler , Eric J. Lenze , Julie Loebach Wetherell , Jeanne F. Nichols , Romain Meeusen , Job G. Godino , Joshua S. Shimony , Abraham Z. Snyder , Tomoyuki Nishino , Ginger E. Nicol , Guy Nagels , Bart Roelands
{"title":"肥胖、健康和大脑老化:对大脑年龄的生理估计与身体健康、活动、睡眠和身体组成之间关系的横断面研究","authors":"David Wing , Lisa T. Eyler , Eric J. Lenze , Julie Loebach Wetherell , Jeanne F. Nichols , Romain Meeusen , Job G. Godino , Joshua S. Shimony , Abraham Z. Snyder , Tomoyuki Nishino , Ginger E. Nicol , Guy Nagels , Bart Roelands","doi":"10.1016/j.ynirp.2022.100146","DOIUrl":null,"url":null,"abstract":"<div><h3>Introduction</h3><p>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.</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>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.</p></div><div><h3>Discussion</h3><p>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).</p></div>","PeriodicalId":74277,"journal":{"name":"Neuroimage. 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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.</p></div><div><h3>Methods</h3><p>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.</p></div><div><h3>Results</h3><p>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.</p></div><div><h3>Discussion</h3><p>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).</p></div>\",\"PeriodicalId\":74277,\"journal\":{\"name\":\"Neuroimage. Reports\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ftp.ncbi.nlm.nih.gov/pub/pmc/oa_pdf/d4/07/nihms-1855870.PMC9894084.pdf\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Neuroimage. 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引用次数: 2
摘要
随着年龄的增长,大脑结构和功能会发生变化。然而,就这些变化开始的时间和进展的速度而言,存在着实质性的异质性。了解这种异质性背后的机制和/或行为可能使我们能够针对和减缓与衰老相关的负面变化采取行动。方法使用T1加权MRI图像,我们应用一种新的算法来确定大脑的生理年龄(大脑预测年龄)以及基于生理估计的预测年龄与实足年龄(BrainPAD)之间的年龄差异,551名年龄在65至84岁之间的久坐成年人,在基线时测量自我报告的认知疾病,作为一项更大的研究的一部分。我们还用分级运动测试评估了最大有氧能力,用加速度计评估了身体活动和睡眠,用双能x线吸收仪评估了身体成分。使用分类分组对关联进行线性和逻辑探索。结果内脏脂肪组织(VAT)、总睡眠时间(TST)和最大有氧能力均与脑垫有显著相关性。更高的增值税与更高的(即)。较高的TST与较高的BrainPAD相关(r = 0.087 p = 0.042),较高的有氧能力与较低的BrainPAD相关(r = - 0.088 p = 0.040)。通过线性回归,VAT和TST仍然显著(p分别= 0.036和0.008)。每公斤增值税预测BrainPAD增加0.741年,每小时TST增加预测BrainPAD增加0.735年。在完全调整的线性模型中,最大有氧能力没有保持统计学意义。内脏脂肪组织的积累和更长的总睡眠时间,而不是有氧能力、每日总体力活动或睡眠数量和/或质量,与生理上比仅根据实足年龄预期的年龄更大的大脑有关(BrainPAD)。
Fatness, fitness and the aging brain: A cross sectional study of the associations between a physiological estimate of brain age and physical fitness, activity, sleep, and body composition
Introduction
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.
Methods
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.
Results
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.
Discussion
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).