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
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":"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","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. 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. Reports","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666956022000708","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Neuroscience","Score":null,"Total":0}
引用次数: 2
Abstract
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).