Sixteen Weeks of Aerobic Exercise does not Alter Resting-state Connectivity of the Precuneus in Patients with Alzheimer’s Disease

Page: [171 - 177] Pages: 7

  • * (Excluding Mailing and Handling)

Abstract

Introduction: In healthy elderly persons and patients with mild cognitive impairment, physical exercise can increase functional brain connectivity in the default mode network (DMN) measured by restingstate functional magnetic resonance imaging (rs-fMRI). However, no studies have so far investigated the effect of physical exercise on functional resting-state connectivity in the DMN in patients with Alzheimer’s disease (AD).

Objective: In a single-blinded randomized controlled trial, we assessed the effects of an aerobic exercise intervention of 16 weeks of physical exercise on DMN connectivity using rs-fMRI in patients with AD.

Methods: Forty-five patients were randomly assigned to either a control or exercise group. The exercise group performed 60-min of aerobic exercise three times per week for 16 weeks. All the patients underwent whole-brain rs-fMRI at 3 T, at baseline, and after 16 weeks. Since the posterior cingulate cortex (PCC) and adjacent precuneus constitute a central hub of the DMN, this parietal region was defined as region-ofinterest and used as the seed region for functional connectivity analysis of the rs-fMRI data treating age and gender as covariates.

Results: Neither seed-based analysis, seeded in the PCC/precuneus region nor ICA-based analyses, focusing on components of the DMN network, showed any exercise-induced changes in functional resting-state connectivity from baseline to follow-up.

Conclusion: 16 weeks of aerobic exercise does not modify functional connectivity of the PCC/precuneus region in patients with AD. A longer intervention may be needed to show the effect of exercise on brain connectivity.

Keywords: Physical exercise, exercise, Alzheimer’s disease, default mode network, resting-state, fMRI.

[1]
Baker LD, Frank LL, Foster-Schubert K, et al. Aerobic exercise improves cognition for older adults with glucose intolerance, a risk factor for Alzheimer’s disease. J Alzheimers Dis 2010; 22(2): 569-79.
[http://dx.doi.org/10.3233/JAD-2010-100768] [PMID: 20847403]
[2]
Suzuki T, Shimada H, Makizako H, et al. A randomized controlled trial of multicomponent exercise in older adults with mild cognitive impairment. PLoS One 2013; 8(4): e61483.
[http://dx.doi.org/10.1371/journal.pone.0061483] [PMID: 23585901]
[3]
Venturelli M, Scarsini R, Schena F. Six-month walking program changes cognitive and ADL performance in patients with Alzheimer. Am J Alzheimers Dis Other Demen 2011; 26(5): 381-8.
[http://dx.doi.org/10.1177/1533317511418956] [PMID: 21852281]
[4]
Vreugdenhil A, Cannell J, Davies A, Razay G. A community-based exercise programme to improve functional ability in people with Alzheimer’s disease: A randomized controlled trial. Scand J Caring Sci 2012; 26(1): 12-9.
[http://dx.doi.org/10.1111/j.1471-6712.2011.00895.x] [PMID: 21564154]
[5]
Hoffmann K, Sobol NA, Frederiksen KS, et al. Moderate-to-high intensity physical exercise in patients with Alzheimer’s Disease: A randomized controlled trial. J Alzheimers Dis 2016; 50(2): 443-53.
[http://dx.doi.org/10.3233/JAD-150817] [PMID: 26682695]
[6]
Sobol NA, Hoffmann K, Frederiksen KS, et al. Effect of aerobic exercise on physical performance in patients with Alzheimer’s disease. Alzheimers Dement 2016; 12(12): 1207-15.
[http://dx.doi.org/10.1016/j.jalz.2016.05.004] [PMID: 27344641]
[7]
Frederiksen KS, Madsen K, Andersen BB, Beyer N, Garde E, Høgh P. Moderate- to high-intensity exercise does not modify cortical β-amyloid in Alzheimer's disease. Alzheimer's & dementia (New York, N Y) 2019; 5: 208-15.
[8]
Moore KM, Girens RE, Larson SK, et al. A spectrum of exercise training reduces soluble Aβ in a dose-dependent manner in a mouse model of Alzheimer’s disease. Neurobiol Dis 2016; 85: 218-24.
[http://dx.doi.org/10.1016/j.nbd.2015.11.004] [PMID: 26563933]
[9]
Erickson KI, Voss MW, Prakash RS, et al. Exercise training increases size of hippocampus and improves memory. Proc Natl Acad Sci USA 2011; 108(7): 3017-22.
[http://dx.doi.org/10.1073/pnas.1015950108] [PMID: 21282661]
[10]
Walsh JJ, Tschakovsky ME. Exercise and circulating BDNF: Mechanisms of release and implications for the design of exercise interventions. Appl Physiol Nutr Metab 2018; 43(11): 1095-104.
[11]
van Praag H. Exercise and the brain: Something to chew on. Trends Neurosci 2009; 32(5): 283-90.
[http://dx.doi.org/10.1016/j.tins.2008.12.007] [PMID: 19349082]
[12]
Buckner RL, Andrews-Hanna JR, Schacter DL. The brain’s default network: Anatomy, function, and relevance to disease. Ann N Y Acad Sci 2008; 1124: 1-38.
[http://dx.doi.org/10.1196/annals.1440.011] [PMID: 18400922]
[13]
Jovicich J, Minati L, Marizzoni M, Marchitelli R, Sala-Llonch R, Bartrés-Faz D. Longitudinal reproducibility of default-mode network connectivity in healthy elderly participants: A multicentric resting-state fMRI study. Neuroimage 2016; 124(Pt A): 442-54.
[http://dx.doi.org/10.1016/j.neuroimage.2015.07.010]
[14]
Fox MD, Raichle ME. Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging. Nat Rev Neurosci 2007; 8(9): 700-11.
[http://dx.doi.org/10.1038/nrn2201] [PMID: 17704812]
[15]
Greicius MD, Srivastava G, Reiss AL, Menon V. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proc Natl Acad Sci USA 2004; 101(13): 4637-42.
[http://dx.doi.org/10.1073/pnas.0308627101] [PMID: 15070770]
[16]
Buckner RL, Snyder AZ, Shannon BJ, et al. Molecular, structural, and functional characterization of Alzheimer’s disease: Evidence for a relationship between default activity, amyloid, and memory. J Neurosci 2005; 25(34): 7709-17.
[http://dx.doi.org/10.1523/JNEUROSCI.2177-05.2005] [PMID: 16120771]
[17]
Badhwar A, Tam A, Dansereau C, Orban P, Hoffstaedter F, Bellec P. Resting-state network dysfunction in Alzheimer’s disease: A systematic review and meta-analysis. Alzheimer’s(Amsterdam, Netherlands) 2017; 8: 73-85.
[http://dx.doi.org/10.1016/j.dadm.2017.03.007]
[18]
Sheline YI, Raichle ME, Snyder AZ, et al. Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biol Psychiatry 2010; 67(6): 584-7.
[http://dx.doi.org/10.1016/j.biopsych.2009.08.024] [PMID: 19833321]
[19]
Voss MW, Prakash RS, Erickson KI, Basak C, Chaddock L, Kim JS. Plasticity of brain networks in a randomized intervention trial of exercise training in older adults. Frontiers Aging Neurosci : 2010.2: 32.
[http://dx.doi.org/10.3389/fnagi.2010.00032]
[20]
Burdette JH, Laurienti PJ, Espeland MA, et al. Using network science to evaluate exercise-associated brain changes in older adults. Front Aging Neurosci 2010; 2: 23.
[http://dx.doi.org/10.3389/fnagi.2010.00023] [PMID: 20589103]
[21]
Smith JC, Nielson KA, Antuono P, et al. Semantic memory functional MRI and cognitive function after exercise intervention in mild cognitive impairment. J Alzheimers Dis 2013; 37(1): 197-215.
[http://dx.doi.org/10.3233/JAD-130467] [PMID: 23803298]
[22]
Chirles TJ, Reiter K, Weiss LR, Alfini AJ, Nielson KA, Smith JC. Exercise training and functional connectivity changes in mild cognitive impairment and healthy elders. J Alzheimers Dis 2017; 57(3): 845-56.
[http://dx.doi.org/10.3233/JAD-161151] [PMID: 28304298]
[23]
Gramkow MH, Hasselbalch SG, Waldemar G, Frederiksen KS. Resting state EEG in exercise intervention studies: A systematic review of effects and methods. Front Hum Neurosci 2020; 14(155)
[24]
Folstein MF, Folstein SE, McHugh PR. “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12(3): 189-98.
[http://dx.doi.org/10.1016/0022-3956(75)90026-6] [PMID: 1202204]
[25]
Washburn RA, Smith KW, Jette AM, Janney CA. The Physical Activity Scale for the Elderly (PASE): Development and evaluation. J Clin Epidemiol 1993; 46(2): 153-62.
[http://dx.doi.org/10.1016/0895-4356(93)90053-4] [PMID: 8437031]
[26]
Cink RE, Thomas TR. Validity of the Astrand-Ryhming nomogram for predicting maximal oxygen intake. Br J Sports Med 1981; 15(3): 182-5.
[http://dx.doi.org/10.1136/bjsm.15.3.182] [PMID: 7272663]
[27]
Power JD, Mitra A, Laumann TO, Snyder AZ, Schlaggar BL, Petersen SE. Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 2014; 84: 320-41.
[http://dx.doi.org/10.1016/j.neuroimage.2013.08.048] [PMID: 23994314]
[28]
Andersson JL, Hutton C, Ashburner J, Turner R, Friston K. Modeling geometric deformations in EPI time series. Neuroimage 2001; 13(5): 903-19.
[http://dx.doi.org/10.1006/nimg.2001.0746] [PMID: 11304086]
[29]
Jovicich J, Czanner S, Greve D, et al. Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data. Neuroimage 2006; 30(2): 436-43.
[http://dx.doi.org/10.1016/j.neuroimage.2005.09.046] [PMID: 16300968]
[30]
Buckner RL, Sepulcre J, Talukdar T, et al. Cortical hubs revealed by intrinsic functional connectivity: Mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci 2009; 29(6): 1860-73.
[http://dx.doi.org/10.1523/JNEUROSCI.5062-08.2009] [PMID: 19211893]
[31]
Nickerson LD, Smith SM, Öngür D, Beckmann CF. Using dual regression to investigate network shape and amplitude in functional connectivity analyses. Front Neurosci 2017; 11: 115.
[http://dx.doi.org/10.3389/fnins.2017.00115] [PMID: 28348512]
[32]
Chen G, Saad ZS, Britton JC, Pine DS, Cox RW. Linear mixed-effects modeling approach to FMRI group analysis. Neuroimage 2013; 73: 176-90.
[http://dx.doi.org/10.1016/j.neuroimage.2013.01.047] [PMID: 23376789]
[33]
Eklund A, Nichols TE, Knutsson H. Cluster failure: Why fMRI inferences for spatial extent have inflated false-positive rates. Proc Natl Acad Sci USA 2016; 113(28): 7900-5.
[34]
Calhoun VD, Adali T, Pearlson GD, Pekar JJ. A method for making group inferences from functional MRI data using independent component analysis. Hum Brain Mapp 2001; 14(3): 140-51.
[http://dx.doi.org/10.1002/hbm.1048] [PMID: 11559959]
[35]
Parlatini V, Radua J, Dell’Acqua F, et al. Functional segregation and integration within fronto-parietal networks. Neuroimage 2017; 146: 367-75.
[http://dx.doi.org/10.1016/j.neuroimage.2016.08.031] [PMID: 27639357]
[36]
Winkler AM, Ridgway GR, Webster MA, Smith SM, Nichols TE. Permutation inference for the general linear model. Neuroimage 2014; 92: 381-97.
[http://dx.doi.org/10.1016/j.neuroimage.2014.01.060] [PMID: 24530839]
[37]
Boraxbekk CJ, Salami A, Wåhlin A, Nyberg L. Physical activity over a decade modifies age-related decline in perfusion, gray matter volume, and functional connectivity of the posterior default-mode network-A multimodal approach. Neuroimage 2016; 131: 133-41.
[http://dx.doi.org/10.1016/j.neuroimage.2015.12.010] [PMID: 26702778]
[38]
Greicius MD, Supekar K, Menon V, Dougherty RF. Resting-state functional connectivity reflects structural connectivity in the default mode network. Cereb Cortex 2009; 19(1): 72-8.
[http://dx.doi.org/10.1093/cercor/bhn059] [PMID: 18403396]
[39]
Frederiksen KS, Larsen CT, Hasselbalch SG, et al. A 16-week aerobic exercise intervention does not affect hippocampal volume and cortical thickness in mild to moderate Alzheimer’s disease. Front Aging Neurosci 2018; 10: 293.
[http://dx.doi.org/10.3389/fnagi.2018.00293] [PMID: 30319397]
[40]
van der Kleij LA, Petersen ET, Siebner HR, et al. The effect of physical exercise on cerebral blood flow in Alzheimer’s disease. Neuroimage Clin 2018; 20: 650-4.
[http://dx.doi.org/10.1016/j.nicl.2018.09.003] [PMID: 30211001]
[41]
Dennis A, Thomas AG, Rawlings NB, et al. An ultra-high field magnetic resonance spectroscopy study of post exercise lactate, glutamate and glutamine change in the human brain. Front Physiol 2015; 6: 351.
[http://dx.doi.org/10.3389/fphys.2015.00351] [PMID: 26732236]
[42]
Palmqvist S, Schöll M, Strandberg O, et al. Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity. Nat Commun 2017; 8(1): 1214.
[http://dx.doi.org/10.1038/s41467-017-01150-x] [PMID: 29089479]
[43]
Wolk DA, Price JC, Saxton JA, et al. Amyloid imaging in mild cognitive impairment subtypes. Ann Neurol 2009; 65(5): 557-68.
[http://dx.doi.org/10.1002/ana.21598] [PMID: 19475670]
[44]
Jung R, Moser M, Baucsek S, Dern S, Schneider S. Activation patterns of different brain areas during incremental exercise measured by near-infrared spectroscopy. Exp Brain Res 2015; 233(4): 1175-80.
[http://dx.doi.org/10.1007/s00221-015-4201-4] [PMID: 25579663]