Aerobic training modulates salience network and default mode network metabolism in subjects with mild cognitive impairment

Show simple item record

dc.contributor Sistema FMUSP-HC: Faculdade de Medicina da Universidade de São Paulo (FMUSP) e Hospital das Clínicas da FMUSP
dc.contributor.author PORTO, F. H. G. FMUSP-HC
COUTINHO, Artur Martins FMUSP-HC
DURAN, Fabio Luis de Souza FMUSP-HC
PINTO, Ana Lucia de Sa FMUSP-HC
GUALANO, Bruno FMUSP-HC
BUCHPIGUEL, Carlos Alberto FMUSP-HC
BUSATTO, Geraldo FMUSP-HC
NITRINI, Ricardo FMUSP-HC
BRUCKI, Sonia Maria Dozzi FMUSP-HC
dc.date.issued 2018
dc.identifier.citation NEUROIMAGE-CLINICAL, v.19, p.616-624, 2018
dc.identifier.issn 2213-1582
dc.identifier.uri http://observatorio.fm.usp.br/handle/OPI/29366
dc.description.abstract Aerobic training (AT) is a promising intervention to improve cognitive functioning. However, its modulatory effects on brain networks are not yet entirely understood. Sixty-five subjects with mild cognitive impairment performed a moderate intensity, 24-week AT program. Differences in resting regional brain glucose metabolism (rBGM) with FDG-PET were assessed before and after AT on a voxel-by-voxel basis. Structural equation modeling was used to create latent variables based on regions with significant rBGM changes and to test a hypothetical model about the inter-relationships between these changes. There were significant rBGM reductions in both anterior temporal lobes (ATL), left inferior frontal gyrus, left anterior cingulate cortex, right hippocampus, left meddle frontal gyrus and bilateral caudate nuclei. In contrast, there was an increase in rBGM in the right precuneus and left inferior frontal gyrus. Latent variables reflecting the salience network and ATL were created, while the precuneus represented the default mode network. In the model, salience network rBGM was decreased after AT. In contrast, rBGM in the default mode network increased as a final outcome. This result suggested improved salience network efficacy and increased control over other brain functional networks. The ATL network decreased its rBGM and connected to the salience network and default mode network with positive and negative correlations, respectively. The model fit values reached statistical significance, demonstrating that this model explained the variance in the measured data. In mild cognitive impairment subjects, AT modulated rBGM in salience network and default mode network nodes. Such changes were in the direction of the normally expected resting-state metabolic patterns of these networks.
dc.description.sponsorship · Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [2011/18245-4]
· Coordination for the Improvement of Higher Education Personnel (CAPES)/Brazil [99999.003029/2014-00]
dc.language.iso eng
dc.publisher ELSEVIER SCI LTD
dc.relation.ispartof Neuroimage-Clinical
dc.rights openAccess
dc.subject Mild cognitive impairment; Aerobic training; Salience network; Default mode network; FDG-PET; Non-pharmacological interventions; Structural equation modeling
dc.subject.other cerebral-blood-flow; mini-mental-state; alzheimers-disease; functional connectivity; older-adults; physical-activity; brain networks; glucose-metabolism; clinical-trials; youthful memory
dc.title Aerobic training modulates salience network and default mode network metabolism in subjects with mild cognitive impairment
dc.type article
dc.rights.holder Copyright ELSEVIER SCI LTD
dc.description.group LIM/15
dc.description.group LIM/17
dc.description.group LIM/21
dc.description.group LIM/43
dc.description.group LIM/45
dc.identifier.doi 10.1016/j.nicl.2018.05.002
dc.identifier.pmid 29984169
dc.type.category original article
dc.type.version publishedVersion
hcfmusp.author PORTO, F. H. G.:HC:IPQ
hcfmusp.author COUTINHO, Artur Martins:HC:ICESP
hcfmusp.author DURAN, Fabio Luis de Souza:FM:
hcfmusp.author PINTO, Ana Lucia de Sa:HC:ICHC
hcfmusp.author GUALANO, Bruno:FM:MCM
hcfmusp.author BUCHPIGUEL, Carlos Alberto:FM:MDR
hcfmusp.author BUSATTO, Geraldo:FM:MPS
hcfmusp.author NITRINI, Ricardo:FM:MNE
hcfmusp.author BRUCKI, Sonia Maria Dozzi:HC:ICHC
hcfmusp.origem.id WOS:000441936300063
hcfmusp.origem.id 2-s2.0-85047464029
hcfmusp.publisher.city OXFORD
hcfmusp.publisher.country ENGLAND
hcfmusp.relation.reference · Agrawal A, 2011, NEUROSURGERY, V69, P238, DOI 10.1227/NEU.0b013e318214ab79
· Ahlskog JE, 2011, MAYO CLIN PROC, V86, P876, DOI 10.4065/mcp.2011.0252
· Almeida OP, 1999, ARQ NEURO-PSIQUIAT, V57, P421, DOI 10.1590/S0004-282X1999000300013
· American Psychiatric Association, 2000, AM PSYCH ASS DIAGN S, DOI [10.1176/appi.books.9780890420249.dsm-iv-tr, DOI 10.1176/APPI.BOOKS.9780890420249.DSM-IV-TR]
· Baker LD, 2010, ARCH NEUROL-CHICAGO, V67, P71, DOI 10.1001/archneurol.2009.307
· Blunch N. J., 2008, INTRO STRUCTURAL EQU, DOI [10.4135/79781446249345, DOI 10.4135/79781446249345]
· Boecker H, 2016, NEUROIMAGE, V131, P73, DOI 10.1016/j.neuroimage.2015.10.021
· Brucki SMD, 2003, ARQ NEURO-PSIQUIAT, V61, P777, DOI 10.1590/S0004-282X2003000500014
· Buckner RL, 2012, NEUROIMAGE, V62, P1137, DOI 10.1016/j.neuroimage.2011.10.035
· Burdette JH, 2010, FRONT AGING NEUROSCI, V2, DOI 10.3389/fnagi.2010.00023
· Catani M, 2008, CORTEX, V44, P1105, DOI 10.1016/j.cortex.2008.05.004
· Chapman SB, 2013, FRONT AGING NEUROSCI, V5, DOI 10.3389/fnagi.2013.00075
· Chirles TJ, 2017, J ALZHEIMERS DIS, V57, P845, DOI 10.3233/JAD-161151
· Clark LR, 2013, J INT NEUROPSYCH SOC, V19, P635, DOI 10.1017/S1355617713000313
· Colcombe SJ, 2004, P NATL ACAD SCI USA, V101, P3316, DOI 10.1073/pnas.0400266101
· Porto FHD, 2015, J ALZHEIMERS DIS, V46, P747, DOI 10.3233/JAD-150033
· Dosenbach NUF, 2008, TRENDS COGN SCI, V12, P99, DOI 10.1016/j.tics.2008.01.001
· Doughertya RJ, 2017, J ALZHEIMERS DIS, V58, P1089, DOI 10.3233/JAD-161067
· Drzezga A, 2003, EUR J NUCL MED MOL I, V30, P1104, DOI 10.1007/s00259-003-1194-1
· FOLSTEIN MF, 1975, J PSYCHIAT RES, V12, P189, DOI 10.1016/0022-3956(75)90026-6
· Gajewski PD, 2016, EUR REV AGING PHYS A, V13, DOI 10.1186/s11556-016-0161-3
· Hamer M, 2009, PSYCHOL MED, V39, P3, DOI 10.1017/S0033291708003681
· Herholz K, 2012, BIOMARK MED, V6, P431, DOI [10.2217/BMM.12.51, 10.2217/bmm.12.51]
· Herholz K, 2011, J NUCL MED, V52, P1218, DOI 10.2967/jnumed.111.090902
· Jack CR, 2013, LANCET NEUROL, V12, P207, DOI 10.1016/S1474-4422(12)70291-0
· Jagust W, 2006, ANN NEUROL, V59, P673, DOI 10.1002/ana.20799
· Jilka SR, 2014, J NEUROSCI, V34, P10798, DOI 10.1523/JNEUROSCI.0518-14.2014
· Kemppainen J, 2005, J PHYSIOL-LONDON, V568, P323, DOI 10.1113/jphysiol.2005.091355
· Lacadie CM, 2008, NEUROIMAGE, V42, P717, DOI 10.1016/j.neuroimage.2008.04.240
· Lancaster JL, 1997, HUM BRAIN MAPP, V5, P238, DOI 10.1002/(SICI)1097-0193(1997)5:4<238::AID-HBM6>3.0.CO;2-4
· Lancaster JL, 2000, HUM BRAIN MAPP, V10, P120, DOI 10.1002/1097-0193(200007)10:3<120::AID-HBM30>3.0.CO;2-8
· Lautenschlager NT, 2008, JAMA-J AM MED ASSOC, V300, P1027, DOI 10.1001/jama.300.9.1027
· Leech R, 2014, BRAIN, V137, P12, DOI 10.1093/brain/awt162
· Liang X, 2013, P NATL ACAD SCI USA, V110, P1929, DOI 10.1073/pnas.1214900110
· Lucignani G, 2009, Q J NUCL MED MOL IM, V53, P1
· Lundgaard I, 2015, NAT COMMUN, V6, DOI 10.1038/ncomms7807
· Machulda MM, 2013, CLIN NEUROPSYCHOL, V27, P1247, DOI 10.1080/13854046.2013.836567
· Menon V, 2010, BRAIN STRUCT FUNCT, V214, P655, DOI 10.1007/s00429-010-0262-0
· Mohs RC, 1997, ALZ DIS ASSOC DIS, V11, pS13
· Nagamatsu Lindsay S, 2013, J Aging Res, V2013, P861893, DOI 10.1155/2013/861893
· Ngandu T, 2015, LANCET, V385, P2255, DOI 10.1016/S0140-6736(15)60461-5
· Nitrini R, 2005, ARQ NEURO-PSIQUIAT, V63, P720, DOI 10.1590/S0004-282X2005000400034
· Pascual B, 2015, CEREB CORTEX, V25, P680, DOI 10.1093/cercor/bht260
· Passow S, 2015, HUM BRAIN MAPP, V36, P2027, DOI 10.1002/hbm.22753
· Perneezky R, 2007, J GERIATR PSYCH NEUR, V20, P84, DOI 10.1177/0891988706297093
· Petersen RC, 1999, ARCH NEUROL-CHICAGO, V56, P303, DOI 10.1001/archneur.56.3.303
· PFEFFER RI, 1982, J GERONTOL, V37, P323, DOI 10.1093/geronj/37.3.323
· Pfefferbaum A, 2011, CEREB CORTEX, V21, P233, DOI 10.1093/cercor/bhq090
· Riedl V, 2016, P NATL ACAD SCI USA, V113, P428, DOI 10.1073/pnas.1513752113
· Robinson JL, 2012, NEUROIMAGE, V60, P117, DOI 10.1016/j.neuroimage.2011.12.010
· Rocher AB, 2003, NEUROIMAGE, V20, P1894, DOI 10.1016/j.neuroimaging.2003.07.002
· Rogalski EJ, 2013, J COGNITIVE NEUROSCI, V25, P29, DOI 10.1162/jocn_a_00300
· ROSEN WG, 1984, AM J PSYCHIAT, V141, P1356
· Salmon E, 2008, NEUROBIOL AGING, V29, P1823, DOI 10.1016/j.neurobiolaging.2007.04.016
· Seeley WW, 2007, J NEUROSCI, V27, P2349, DOI 10.1523/JNEUROSCI.5587-06.2007
· Sestieri C, 2014, J COGNITIVE NEUROSCI, V26, P551, DOI 10.1162/jocn_a_00504
· SHEIKH J I, 1986, Clinical Gerontologist, V5, P165
· Signorini M, 1999, NEUROIMAGE, V9, P63, DOI 10.1006/nimg.1998.0381
· Sun FW, 2016, J NEUROSCI, V36, P9659, DOI 10.1523/JNEUROSCI.1492-16.2016
· Suzuki T, 2012, BMC NEUROL, V12, DOI 10.1186/1471-2377-12-128
· van Uffelen JGZ, 2008, BRIT J SPORT MED, V42, DOI 10.1136/bjsm.2007.044735
· Voss MW, 2016, NEUROIMAGE, V131, P113, DOI 10.1016/j.neuroimage.2015.10.044
· Voss MW, 2010, FRONT AGING NEUROSCI, V2, DOI 10.3389/fnagi.2010.00032
· Voss MW, 2010, NEUROPSYCHOLOGIA, V48, P1394, DOI 10.1016/j.neuropsychologia.2010.01.005
· Wang C, 2014, J ALZHEIMERS DIS, V42, P663, DOI 10.3233/JAD-140660
· Winblad B, 2004, J INTERN MED, V256, P240, DOI 10.1111/j.1365-2796.2004.01380.x
· Wu YP, 2016, FRONT NEUROANAT, V10, DOI 10.3389/fnana.2016.00084
· Zou QH, 2009, NEUROIMAGE, V48, P515, DOI 10.1016/j.neuroimage.2009.07.006
dc.description.index MEDLINE
hcfmusp.citation.scopus 0
hcfmusp.citation.wos 0


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search DSpace



Browse

My Account

Statistics