Effects of Aerobic Training on Cognition and Brain Glucose Metabolism in Subjects with Mild...

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Journal of Alzheimer’s Disease 46 (2015) 747–760DOI 10.3233/JAD-150033IOS Press

747

Effects of Aerobic Training on Cognitionand Brain Glucose Metabolism in Subjectswith Mild Cognitive Impairment

Fabio Henrique de Gobbi Portoa,∗, Artur Martins Novaes Coutinhob, Ana Lucia de Sa Pintoc,Bruno Gualanoc, Fabio Luıs de Souza Durand, Silvana Prandod, Carla Rachel Onob, Lıvia Spındolaa,Maira Okada de Oliveiraa, Patrıcia Helena Figueredo do Valea, Ricardo Nitrinia,Carlos Alberto Buchpiguelb and Sonia Maria Dozzi BruckibaDepartment of Neurology and Cognitive Disorders Reference Center (CEREDIC), Hospital das Clınicas daFaculdade de Medicina da Universidade de Sao Paulo, Sao Paulo, SP, BrazilbDepartment of Radiology, Nuclear Medicine Center (LIM43), Hospital das Clınicas da Faculdade de Medicinada Universidade de Sao Paulo, Sao Paulo, SP, BrazilcLaboratory of Assessment and Conditioning in Rheumatology (LACRE), Hospital das Clınicas da Faculdade deMedicina da Universidade de Sao Paulo, Sao Paulo, SP, BrazildDepartment of Psychiatry and LIM21, Hospital das Clınicas da Faculdade de Medicina da Universidade de SaoPaulo, Sao Paulo, SP, Brazil

Handling Associate Editor: Paulo Caramelli

Accepted 18 March 2015

Abstract.Background: Aerobic training (AT) is a promising intervention for mild cognitive impairment (MCI).Objective: To evaluate the effects of AT on cognition and regional brain glucose metabolism (rBGM) in MCI patients.Methods: Subjects performed a twice-a-week, moderate intensity, AT program for 24 weeks. Assessment with ADAS-cog, a com-prehensive neuropsychological battery, and evaluation of rBGM with positron emission tomography with 18F-fluorodeoxyglucose([18F]FDG-PET) were performed before and after the intervention. Aerobic capacity was compared using the maximal oxygenconsumption VO2max (mL/Kg/min). [18F]FDG-PET data were analyzed on a voxel-by-voxel basis with SPM8 software.Results: Forty subjects were included, with a mean (M) age of 70.3 (5.4) years and an initial Mini-Mental State Exam scoreof 27.4 (1.7). Comparisons using paired t-tests revealed improvements in the ADAS-cog (M difference: −2.7 (3.7), p < 0.001)and VO2max scores (M difference: 1.8 (2.0) mL/kg/min, p < 0.001). Brain metabolic analysis revealed a bilateral decrease in therBGM of the dorsal anterior cingulate cortex, pFWE = 0.04. This rBGM decrease was negatively correlated with improvementin a visuospatial function/attentional test (rho = −0.31, p = 0.04). Several other brain areas also showed increases or decreasesin rBGM. Of note, there was an increase in the retrosplenial cortex, an important node of the default mode network, that wasnegatively correlated with the metabolic decrease in the dorsal anterior cingulate cortex (r = −0.51, p = 0.001).Conclusion: AT improved cognition and changed rBGM in areas related to cognition in subjects with MCI.

Keywords: Aerobic physical exercise, aerobic training, anterior cingulate cortex, cognition, mild cognitive impairment, non-pharmacological interventions, positron emission tomography with 18F-fluorodeoxyglucose

∗Correspondence to: Fabio Henrique de Gobbi Porto, CognitiveDisorders Reference Center (CEREDIC - Centro de Referenciaem Disturbios Cognitivos), 206 Arruda Alvim st, Cerqueira Cesar,

Sao Paulo, SP 05419-020, Brazil. Tel./Fax: +55 11 30861326;E-mail: [email protected].

ISSN 1387-2877/15/$35.00 © 2015 – IOS Press and the authors. All rights reserved

mailto:[email protected]

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748 F.H. de Gobbi Porto et al. / Effects of AT on Brain Glucose Metabolism

INTRODUCTION

Mild cognitive impairment (MCI) is a heteroge-neous condition characterized by cognitive declinethat is not severe enough to cause functional impair-ment and meet the threshold of dementia [1]. MCI iscommonly caused by Alzheimer’s disease (AD) andrepresents a transitional state between normal agingand mild dementia, both in cognition and neuropathol-ogy [2, 3]. It is a major risk factor for dementia, with anannual conversion rate to dementia of 5–15% (as com-pared to a 1% rate in cognitively normal older adults)[2]. Consequently, MCI has been considered as a tar-get for interventions aimed at decreasing the risk ofdementia [4]. Even small decreases in the conversionrate of MCI to dementia may significantly impact theprevalence of dementia [5]. Therefore, there has beenan extensive search for interventions that reduce theprogression of cognitive decline in subjects with MCI.

Physical exercise (PE) is associated with a decreasedrisk of dementia in normal older adults [6, 7]. In arecent meta-analysis of the risk factors for AD, phys-ical inactivity was one of the greatest modifiable riskfactors, accounting for 12.7% (95% CI 3.3–24) ofthe population-attributable risk worldwide [8]. Sev-eral biological mechanisms have been implicated in theprotective effects of PE, including improved neuroge-nesis, angiogenesis, and synaptic plasticity as well as adecrease in vascular risk factors, insulin resistance, andnormal aging-related brain atrophy [9]. PE may alsodecrease brain deposition of amyloid-� (A�) protein,although the data regarding this effect are conflict-ing [10, 11]. However, data about the cognitive effectsof PE in subjects with established dementia are moreheterogeneous, with somewhat divergent results. [12,13]. Because MCI is believed to be an intermediatestate between normal aging and dementia, an impor-tant question is whether PE is useful for improvingcognition or for slowing the rate of cognitive declinein this specific group of subjects.

Recent evidence has demonstrated that PE mayimprove cognition in MCI. Data from randomized con-trolled trials with PE have indicated improvements inglobal cognitive function, memory, and executive func-tion [14–18]. A recent meta-analysis showed strongevidence of benefits for global cognitive function [19].Furthermore, somestudies revealedchanges in imagingbiomarkers in subjects with MCI who performed PE.One study used volumetric magnetic resonance imag-ing (MRI) and revealed a lower brain atrophy rate in theamnestic MCI group [20]. However, in the MCI popula-tion,thebrainvolumechangesassociatedwithPEarenot

always correlated with better cognitive function [21].Another study used functional MRI (fMRI) to demon-strate decreases in hippocampal activation during asemantic memory retrieval test, indicating improvedneural efficiency after the PE intervention [22]. Nev-ertheless, more data are required to better understandthe effects of PE on AD biomarkers in MCI subjects.

Positron emission tomography with 18F-fluoro-deoxyglucose ([18F]FDG-PET) measures regionalbrain glucose metabolism (rBGM), a surrogate markerof synaptic function. Hypometabolism on [18F]FDG-PET is considered a measurement of neuronaldysfunction or neurodegeneration and has been shownto be an earlier marker of neuronal injury [23, 24].A reduction in rBGM in the posterior cingulate andtemporoparietal regions is related to a faster cognitivedecline in MCI patients [25, 26]. Brain metabolismmeasured by [18F]FDG-PET has a good correlationwith cognition and function across all stages of cog-nitive decline [23]. This method is promising as anoutcome measure in interventional studies because itprovides objective data, high test-retest reliability, anda good correlation with cognitive performance and mayenable the use of a smaller sample size [26, 27]. More-over, the use of [18F]FDG-PET to measure rBGM isrelatively independent of language as well as culturaland educational variables, and unlike neuropsycholog-ical measures, it is not associated with learning effectsin test-retest situations.

In the present study, we investigated the effects ofa 24-week, supervised Aerobic training (AT) programon cognition and rBGM (measured by [18F]FDG-PET)in subjects with MCI. The objective of this studywas to evaluate the effects of AT on cognition andbrain metabolism in subjects with MCI. Our previoushypothesis was that AT would not only improve cogni-tion but would also change rBGM in the brain regionsmediating cognition.

MATERIALS AND METHODS

Community-dwelling older adults (60 years orolder) with cognitive complaints were evaluated by aneurologist. Screening cognitive tests and assessmentsof depressive and anxiety symptoms were performedin all participants. The subjects were invited to undergoa complete neuropsychological evaluation. A finaldiagnosis was then established by a consensus of neu-rologists with expertise in cognitive and behavioralneurology. The revised Petersen et al. criteria (2009)were used to diagnose subjects with MCI [2]. As such,

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F.H. de Gobbi Porto et al. / Effects of AT on Brain Glucose Metabolism 749

subjects with MCI were classified as amnestic MCI(aMCI) or non-amnestic MCI (naMCI) according tothe presence or absence of impairment in memorytasks during the neuropsychological assessment. Thescreening cognitive battery included the Mini-MentalState Exam (MMSE) [28, 29] and Brief Cognitive Bat-tery (BCB) [30, 31]. The BCB is a visual learningtest in which subjects have 3 trials to learn 10 simpleline drawings (shoe, house, comb, key, airplane, turtle,book, spoon, tree, and bucket). Initially, the 10 fig-ures are shown, and the subjects are instructed to namethem. Afterward, the pictures are withdrawn, and thesubjects are asked to spontaneously retrieve the namesof the pictures (without a clear instruction to try toremember them during the encoding phase). The pic-tures remembered are scored as “incidental memory”.Then, the pictures are shown again for 30 s, and thesubjects are instructed to try to memorize the figures.The pictures are removed, and the subjects have 1 minto retrieve the names of the objects. This procedure isrepeated once (total of 2 trials of 30 s to learn the 10pictures). The number of learned pictures after the sec-ond trial is scored as “learning memory”. Thereafter,the subjects perform a categorical fluency test (gener-ating animal names in 1 min) and the clock drawingtest (CDT) [32], both of which also served as a dis-tracter activity. The next step involved a delayed recallof drawings, in which subjects have 1 min to try toremember the pictures (called “delayed recall”) and arecognition test of previously learned drawings mergedwith ten other drawings on the same sheet. This batteryhad good accuracy for the diagnosis of early demen-tia [33]. We also included a phonemic verbal fluencytest (number of words in 1 min beginning with theletter “P”) in the BCB after the animal fluency test(which also increased the distraction time of the test).The neuropsychological (NP) battery was composedof the following: 1) memory tests: visual reproductionand logical memory subtests of the Wechsler MemoryScale – revised (WMS-R) [34], delayed recall of theRey-Osterrieth Complex Figure (drROCF) [35], andthe Rey Auditory Verbal Learning Test (RAVLT) [36];2) constructive abilities: Block Design subtest of theWechsler Adult Intelligence Scale (WAIS) [37, 38] andcopy of the Rey-Osterrieth Complex Figure (cROCF)[35]; 3) visual perception: matrix reasoning [39]; and4) attention and executive functions: Trail Making Test(Parts A and B) and Stroop test [35]. The application,scoring, and interpretation of the results obtained fromall tests were performed according to each referenceguide, and the scores were adjusted according to ageand educational levels [37, 38].

Subjects with a diagnosis of MCI were then selectedto participate in the study. All subjects agreed to partic-ipate in the study and underwent an informed consentprocess approved by our local Human ResearchEthics Committee (Nº 0064/11). The study was reg-istered under the Universal Trial Number (UTN)U1111-1149-2365, and Brazilian Clinical Trials Reg-istry (ReBec) number RBR-5tv5vt. All participantsunderwent a cognitive evaluation followed by a car-diopulmonary exercise test (CET). After approval bya cardiologist (based on the CET results), the subjectsunderwent a neuroimaging evaluation (brain MRI andresting state [18F]FDG-PET). After the neuroimag-ing procedures, a lumbar puncture was performed,which was used to determine the levels of A�, tau, andphosphorylated-tau (p-tau) in the cerebrospinal fluid(CSF). All procedures were performed on differentdays, ideally with no more than a 4-week difference.Finally, the subjects participated in an exercise pro-gram that consisted of 24 weeks of supervised ATperformed twice a week. After completion of theexercise program, the CET, cognitive evaluation, and[18F]FDG-PET imaging were repeated, ideally withintwo weeks after the last training.

Inclusion and exclusion criteria

Subjects met the inclusion criteria for cognitiveimpairment when the score on one cognitive func-tion test was 1.5 standard deviations (SD) below theage- and education-appropriate scores, or if the scoreswere between 1.0 and 1.5 SD on more than one testof the same cognitive domain. The exclusion criteriaincluded the following: 1) clinically relevant psychi-atric symptoms meeting the DSM-IV criteria (the shortversion of the Geriatric Depression Scale [40, 41], wasapplied to evaluate the severity of depressive symp-toms, and a cut-off of more than 5/15 was used toexclude subjects); 2) any uncontrolled uncompensatedclinical comorbidity; 3) history or signs of neuro-logic diseases (such as Parkinson’s disease, epilepsy,inflammatory diseases, or stroke), with the exceptionof migraines; 4) presence of any drug abuse (especiallyalcoholism); 5) orthopedic problems that preventedwalking on a treadmill (e.g., knee osteoarthritis); 6) thepresence of cardiovascular disease (even if compen-sated, e.g., coronary artery disease, congestive heartfailure, or atrial fibrillation); and 7) a functional declinesufficiently intense to meet the dementia criteria (theFunctional Activities Questionnaire [42] was also usedas a measure of functional status, and the participantswith scores of 5 or higher were not included). None of

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the participants were using cholinesterase inhibitors ormemantine. Antidepressants (for remitted depression)were allowed only if they were administered at stabledoses for at least three months in the absence of activepsychiatric disease. Of note, participants were notrequired to be sedentary. Subjects were not includedonly if they were doing supervised physical activitybefore the beginning of the study.

Cardiopulmonary exercise test

The CET was performed on a treadmill (Centurion200, Micromed, Brazil) with increases in velocity andinclination at 1-min increments until perceived voli-tional exhaustion or the observation of some specificclinical symptom, as previously described in Pradoet al. [43]. Oxygen consumption (VO2) and carbondioxide output were obtained through breath-by-breathsampling and expressed as 30-s averages using an indi-rect calorimetric system (Cortex - model MetalyzerIIIB, Germany). The heart rate (HR) was continu-ously recorded at rest, during exercise, and at recoveryusing a 12-lead electrocardiogram (Ergo PC Elite,Inc. Micromed, Brazil). CET was considered maximalwhen one of the following criteria was met: 1) VO2plateau (increases smaller than 150 mL/min betweentwo consecutive stages of difficulty); 2) respiratoryexchange ratio value above 1.10; or 3) HR greater than10 beats below the age-predicted maximal HR. TheVO2 peak was defined as the 30-s average of the lasttesting stage. The ventilatory thresholds were identi-fied following standard procedures [44]. The volumeof O2 expired (VE) was used in these measurements.The ventilatory anaerobic threshold was identifiedwhen the ventilatory equivalent for VO2 (VE/VO2)increased without a concomitant increase in the venti-latory equivalent for carbon dioxide (VE/VCO2). Therespiratory compensation point was defined as thetime in which the VE/VO2 and VE/VCO2 increasedsimultaneously. The ventilatory anaerobic thresholdand respiratory compensation point are measured inminutes (min). Patients with cardiac or orthopedicabnormalities (identified during the CET) that pre-vented them from participating in the PE program wereexcluded from the study in this phase. The main param-eter studied as an outcome was the maximal oxygenconsumption (VO2 max). The VO2 max is the max-imum capacity of an individual to transport and useoxygen during incremental exercise. This test is basedon measurements of the oxygen and carbon dioxideconcentrations of the inhaled and exhaled air duringprogressively intense PE. The VO2 max is reached

when the oxygen consumption remains at a steadystate despite an increase in workload. The VO2 maxis expressed in milliliters of oxygen per kilogram ofbody weight per min (mL/kg/min).

CSF analysis

Lumbar punctures were performed after an 8-h fast,always between 8 and 10 AM. A 22-gauge spinalneedle was inserted between the 4th and 5th lumbarvertebral body by a trained neurologist. Approxi-mately 10 mL of CSF was collected. CSF sampleswere collected in polypropylene tubes and analyzed todetermine cell count, total protein, lactate, glucose, A�protein, tau, and p-tau proteins. All CSF samples werebriefly centrifuged and then stored at a temperatureof −80◦C for subsequent analysis. CSF total tau andp-tau were determined quantitatively using a commer-cial sandwich enzyme-linked immunosorbent assay(ELISA) (Innotest hTAUAg, Innogenetics, Belgium).CSF A� was determined using a sandwich ELISA(Innotest amyloid 1–42, Innogenetics, Belgium).

Image procedures

Magnetic resonance imaging acquisitionAfter the initial work-up, all patients underwent a

3.0 Tesla MRI scan to exclude structural diseases thatmay contribute to the cognitive impairment (e.g., vas-cular or neoplastic) and also for co-registration with[18F]FDG-PET images. The following MRI sequenceswere acquired: sagittal 3D T1, axial T2 FSE, axialFLAIR, coronal T2 SPIR and diffusion SENSE.

[18F]FDG-PET imaging acquisition

To ensure that their blood glucose levels were lowerthan 180 mg/mL, the subjects fasted for at least 4 hprior to the intravenous injection of 370 MBq of[18F]FDG into a peripheral vein. After the tracerinjection, the patients rested with eyes open and earsunplugged for 60 min in a calm, silent, and slightlydarkened room. Acquisition of the [18F]FDG-PETdata was performed for 15 min (matrix = 256 × 256,zoom = 2.5, pixel size = 1.04 mm) using a Siemens Bio-graph PET-CT scanner (CTI/Siemens, Knoxville, TN,USA). Images were reconstructed with the orderedsubset expectation maximization method (OSEM)with 6 iterations and 16 subsets. The images were thensmoothened with a 5 mm Gaussian filter. The data werealso corrected for scattering, attenuation, and decay.Attenuation correction was performed using a singlehelical computed tomography.

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Cognitive evaluation

The ADAS-cog (Alzheimer’s Disease AssessmentScale-cognitive subscale) [47, 48] was selected as the“global cognitive” outcome in the study. Parallel ver-sions were used to decrease “learning effects” betweenassessments. The same NP battery (described in the“methods” session) used for diagnostic classificationwas repeated after the PE. The NP battery results wereused to measure differences in “specific” cognitivedomains as a secondary cognitive outcome.

Aerobic exercise training program

The training consisted of 24 weeks of a supervisedAT program performed twice a week. The sessions con-sisted of a 5-min warm-up followed by 30 to 50 minof treadmill aerobic training and a 5-min cool-downperiod. Participants were instructed not to talk or readduring the exercise sessions. All sessions were moni-tored by at least one certified professional. The durationof aerobic training was increased every eight weeks,from 30 to 50 min. The intensity was increased fromthe ventilatory anaerobic threshold to 10% below therespiratory compensation point. Training load (i.e.,treadmill speed) was adjusted throughout the trainingperiod at every training session in order to maintain thecorresponding HR between the ventilatory anaerobicthreshold and 10% below the respiratory compensa-tion point. The exercise program was performed in anexercise laboratory inside our hospital (Laboratory ofAssessment and Conditioning in Rheumatology).

Revaluation

After the program was completed, CET, ADAS-cog,NP battery, and brain [18F]FDG-PET were repeated,ideally within two weeks after the end of the trainingsessions.

Statistical analysis

Clinical data analyses were performed using SPSSversion 17.0 (SPSS, Inc., Chicago, IL). The Shapiro-Wilk and Levine tests were used to test the assumptionsof normality and homoscedasticity in distributions. Avoxel-based analysis of the [18F]FDG-PET data wasperformed using SPM8 software (Wellcome Depart-ment of Cognitive Neurology, Functional ImagingLaboratory, London, UK). A paired t-test was usedto compare the rBGM before and after the AT pro-gram. As an additional comparison, we performed anon-paired t-test of the [18F]FDG-PET images of the

subjects at these two time points (before and after theAT) with a group of normal cognitive elderly (singletime point) patients from the database of our Institution(n = 30) as an indirect way to measure rBGM changes.Detailed demographic data for this control group (CG)are available as Supplementary Material. Additionaldetails regarding [18F]FDG-PET image processing areprovided below.

[18F]FDG-PET voxel-based processing andanalysis with SPM8

Anatomic normalization and statistical processingfor [18F]FDG-PET were performed using SPM8 inconjunction with MATLAB R2009a (The MathworksInc., USA). All PET images were co-registered withthe MRI images (volumetric T1 sequence) of theparticipants and spatially normalized in SPM8 to astandard stereotactic space based on the Talairach andTournoux atlas [47, 48] using a 12-parameter linearaffine normalization and a further nonlinear iterationalgorithm. This analysis was performed using an SPM8template for [18F]FDG. Each of the scans was also indi-vidually smoothed with a Gaussian kernel to reducethe impact of misregistration into the template spaceand improve the signal to noise ratio. The smoothingwas performed with an 8-mm FWHM filter. To ensurethat the analysis only included voxels mapping cere-bral tissue, a default threshold of 80% of the meanuptake inside the brain was selected. Global uptake dif-ferences between the brain scans were adjusted usingthe “proportional scaling” SPM option. As previouslydescribed, a paired t-test analysis was used to examinethe metabolic differences between pre- and post-ATscans, and a non-paired t-test was used to compareimages before and after AT to those of cognitivelynormal older adults. Each pairwise analysis was per-formed by searching for increases or decreases ofrBGM after AT. Whole-brain differences with a sig-nificance level threshold (p) below 0.001 (uncorrectedfor multiple comparisons) for the peak voxel (with aminimum number of 10 voxels within the cluster) wereaccepted (Z score above 3.09). The anatomic localiza-tions of the relevant peak voxels were determined interms of their coordinates according to Talairach andTournoux with the aid of the Talairach Client softwareafter conversion from the SPM8 space [47, 48].

Volumetric region of interest (VOI) analysis withSPM

After the initial explorative analyses with SPM,the maps generated a t statistic for each voxel, thus

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constituting statistical parametric maps. The highestt-value within each map was thus identified, and avolume of interest in the corresponding cluster ofvoxels was generated. Subsequently, numeric valuesrepresenting the [18F]FDG uptake measures in thatcluster for each individual (after the entire normaliza-tion process) were obtained with the toolbox MarsBarfor SPM (http://marsbar.sourceforge.net/) under theoption “explore design/files and factors.” With thisapproach, regions of particular interest (i.e., voxelswith significant changes in rBGM after the AT inter-vention) could be better explored and correlated withclinical and CSF data.

RESULTS

Forty subjects who completed the 24-week AT pro-gram were included. A flow diagram according to theCONSORT guideline is shown as supplementary mate-rial (Supplementary Figure 1) [49]. The demographicsand neuropsychological and CSF biomarker baselineresults are shown in Table 1. The mean (M) and stan-dard deviation (SD) in years (Y) were 70.3 (5.4) forage and 10 (4.4) for education. There was a predomi-nance of women in this sample (male/female ratio of9/31, χ2 = 0.01). The baseline MMSE was 27.4 (1.7).The CSF results for A�, tau, and p-tau were 772.9(332.6) ng/L, 251.5 (116.7) ng/L, and 45.1 (15.2) ng/L,respectively. According to the manufacturer, the cut-off values for AD are as follows: A� <540 ng/L; tau<450 ng/L; p-tau <61 ng/L.

Table 1Demographic, cognitive screening, and CSF data of the sample

Variable Mean (SD) Variable Mean (SD)

Age (Y) 70.3 (5.4) CVF 15.3 (3.1)Gender (F) 31 (77.5%)∗† PVF 10.2 (3.5)School (Y) 10 (4.4) GDS 1.5 (1.4)HTN 14 (35%)∗ FAQ 1(1.9)DM 21 (52.5%)∗ A��,‡ 772 (332)DLP 9 (22.5%)∗† Tau�,‡ 251 (116)MMSE 27.4 (1.7) p-tau�,‡ 45 (15)drBCB 8.0 (1.3)

A�, amyloid-�; CVF, categorical verbal fluency (animals/ 1 minute);DLP, dyslipidemia, DM, diabetes; drBCB, delayed recall of BriefCognitive Battery; F, female; FAQ, Functional Activities Ques-tionnaire; GDS, Geriatric Depression Scale (15 items); HTN,hypertension; MMSE, Mini-Mental State Examination; PVF, phone-mic verbal fluency (words with the letter “P”/ 1 minute); p-tau,phosphorylated-tau; SD, standard deviation; Y, years. ∗number ofcases and percentage of total; †p = 0.001 (Chi-Square); �cut-off val-ues for AD are: A� protein <540 ng/L, tau <450 ng/L, p-tau <61ng/L; ‡n = 39 (1 participant’s CSF biomarkers were not availablebecause of technical difficulties).

Table 2ADAS-cog, CET, and neuropsychological scores before and after

the AT intervention

n = 40 Before After Dif

Mean (SD) Mean (SD) Mean (SD) Sig (p=)∗

ADAS-cog 11.8 (3.4) 9.1 (3.8) −2.7 (3.7) <0.001ADAS-mem 9.5 (3.0) 7.2 (3.1) −2.2 (3.1) <0.001VAT† 13.5 (2.4) 13.5 (2.4) 0 (2.7) 1.0RCP† 19.9 (2.8) 20.8 (3.4) 0.9 (2.1) 0.01VO2 max† 22.0 (3.5) 23.8 (4.0) 1.8 (2.0) <0.001TM (B-A) 114.5 (66.9) 125.0 (72.7) −10.4 (85) 0.4Stroop 37.9 (13) 37.0 (9.3) −0.92 (12.5) 0.6cROCF 29.3 (5.0) 31.3 (5.4) 2.0 (5.2) 0.01MR 11.4 (2.7) 11.6 (3.3) 0.18 (3.3) 0.7Logic Mem 15.0 (7.0) 14.0 (6.0) −1 (6.0) 0.3Visual Mem 11.4 (8.2) 17.9 (11.8) 6.4 (12.6) 0.003RAVLTs 38.9 (6.9) 39.6 (6.9) 0.6 (3.7) 0.2RAVLTdr 6.8 (2.5) 7.4 (3.9) 0.5 (4.0) 0.3drROCF 10.8 (6.6) 10.3 (5.7) −0.4 (6.8) 0.6

ADAS-cog, Alzheimer’s disease Assessment Scale-cognitive sub-scale; ADAS-mem, memory subtests of the ADAS-cog (sum); AT,aerobic training; cROCP, copy of Rey-Osterrieth complex figure;Dif, difference; Mem, memory; drROCF, delayed recall of Rey-Osterrieth complex figure; MR, matrices reasoning; RAVLTdr, ReyAuditory Verbal Learning Test (delayed recall); RAVLTs, Rey Audi-tory Verbal Learning Test (sum of the 5 learning trials); RCP,respiratory compensation point; SD, standard deviation; TM (A-B), difference between trial making B and A; VAT, ventilatoryanaerobic threshold; VO2 max, maximal oxygen consumption;*Two-tailed; †n = 38 (two participants were unable to complete thepost-training CET); VAT and RCP are measured in minutes, VO2maxin mL/Kg/min.

The CET results before and after the intervention,along with the mean differences, are shown in Table 2.The mean number of training sessions performed bythe participants was 39.2 (5.5), with a maximum of48 sessions (approximately 80% of the training ses-sions were completed). Text and tables are providedas Supplementary Material, showing the results foronly participants who completed more than 75% ofthe AT sessions (n = 35). For two participants, thepost-training CET results were not obtained (1 subjectexperienced atrial fibrillation during the post-trainingCET, and the other had orthopedic problems that con-traindicated the test). There was an increase in therespiratory compensation point and VO2 max scoresafter the training (Post - Pre; M and SD differences:0.9 (2.1) min, p = 0.01; 1.8 (2) mL/(kg·min), p < 0.001,respectively). This result indicates that there was anincrease in aerobic capacity after the PE intervention.

The ADAS-cog and NP battery scores are alsoreported in Table 2. There was a decrease in the ADAS-cog scores of −2.7 (3.7) points (p < 0.001), whichrepresents a better performance after the AT (higherscores indicate greater impairment). As mentioned

http://marsbar.sourceforge.net/

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Table 3Regions of rBGM reduction and increase after AT. The results were obtained at the peak voxel level

(global analysis, paired t test, p uncorrected for multiple comparisons)

Metabolism reduction Z score p value CS Peak voxel coordinates‡

Anterior Cingulate Gyrus, BA 24 L 4.20 0.00001 109 −2 −10 32Inferior Frontal Gyrus, BA 47 L 4.01 0.00003 79 −42 26 −18Anterior Cingulate Gyrus, BA 32† R 3.90 0.00008 470 4 16 40Anterior Cingulate Gyrus, BA 24† R 3.90 0.00005 470 4 28 23Anterior Cingulate Gyrus, BA 24† R 3.52 0.0002 470 2 7 31Precentral Gyrus, BA 13 L 3.66 0.0001 37 −48 −9 13Anterior Entorhinal Cortex, BA 34 L 3.62 0.0002 37 −10 1 −14Posterior Cingulate Cortex, BA 23 R 3.62 0.0001 22 10 −28 29Substantia Nigra L 3.35 0.0004 20 −4 −18 −14Metabolism increaseGyrus Rectus, BA 11 R 3.70 0.0003 87 10 42 −19Retrosplenial Cortex, BA 30 R 3.41 0.0003 22 18 −50 8Cerebellum, Posterior Lobe R 3.39 0.0003 28 18 −52 −24Medial Frontal Gyrus, BA 25 L 3.35 0.0004 25 −12 22 −18

BA: Brodmann area; CS: cluster size (number of voxels); L, left; PE, physical exercise; R, right, rBGM,regional brain glucose metabolism. †These are contiguous areas in the same cluster of voxels andreached statistical significance at the cluster level with p corrected for multiple comparisons with thefamilywise error method (FWE) (pFWE = 0.04). ‡Talairach.

Fig. 1. Illustrative view of the main changes in resting state rBGM after the AT program plotted in an MRI template. The left panel shows themost significant rBGM reduction (yellow area, red arrow), encompassing a large area in the ACC. In the right panel, two regions of increasein rBGM are noted (blue arrow) in the PCC and posterior left cerebellum. The rBGM decrease in the ACC was inversely correlated with therBGM increase in these two areas, and also with cognitive scales such as the cROCF. (Colours are visible in the online version of the article;http://dx.doi.org/10.3233/JAD-150033).

previously, the words to be learned, recalled, andrecognized were not the same in parallel versionsof the ADAS-cog, which minimizes learning effects.The scores on the ADAS-cog memory subtests werecompared. There was an improvement in memory per-formance, as determined by a decrease of −2.2 (3.1)(p < 0.001). A comparison of NP results showed dif-ferences in the delayed visual memory recall (dVMR)subtest of the WMS-R and in the cROCF (M andSD differences of 6.4 (12.6) (p = 0.003) and 2 (5.2)(p = 0.02), respectively). To identify an interactionbetween the effects of PE, the type of MCI (aMCIand naMCI), and gender effects, a factorial compar-

ison was performed. There was no interaction betweenthe difference in the ADAS-cog scores (Post - Pre)after AT and the type of MCI (F(1,36) = 2.1 (p = 0.152);gender, F (1,36) = 0.01 (p = 0.96)) or in the combina-tion “type of MCI/gender” (F(1,36) = 0.19, p = 0.662).There were no correlations between changes in the cog-nitive tasks and changes in the CET scores or initialCSF biomarkers.

The results of the first global exploratory analy-sis are shown in Table 3 and Fig. 1. Increases in therBGM were seen in several areas, labeled by Brodmannareas (BA), which included the right retrosplenial cor-tex (RSC) (p = 0.0003, BA = 30), right gyrus rectus

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Table 4Pearson product-moment correlation coefficient (Pearson’s r) between changes in the mean radioactive counts (mRC) in brain areas that reached

statistical significance (p < 0.001)

Decreases in mRC Increases in mRCn = 40 ACC† ETC ACC‡ SBN IFG PCG PCC MFG CRBL RSC GR

ACC† – 0.29 0.47∗∗ 0.35∗ 0.26 0.25 0.24 0.21 −0.42∗∗ −0.51∗∗ 0.26ET – 0.27 0.6∗∗ 0.56∗∗ 0.16 0,15 −0.21 −0.14 −0.31∗ 0.03ACC‡ – 0.34∗ 0.06 0.34 0,48∗∗ 0.00 −0.03 −0.11 −0.05SBN – 0.56∗∗ 0.26 0.28 −0.11 −0.03 −0.26 −0.06IFG – 0.22 0,17 −0.09 −0.84 −0.36∗ 0.11PCG – 0,26 −0.10 −0.09 −0.28 −0.19PCC‡ – −0.15 −0.29 −0.04 −0.08MFG – −0.17 0.01 0.68∗∗CRBL – 0.43∗∗ −0.24RSC – −0.09GR –

ACC†, right anterior cingulate cortex (cluster of 3 voxels comprising BA 24 and 32); BA, Brodmann area; ACC‡, left anterior cingulate cortex(BA 24); CRBL, cerebellum; ETC, entorhinal cortex; GR, gyrus rectus; IFG, inferior frontal gyrus; L, left; MFG, middle frontal gyrus; mRC,mean radioactive counts; PCC, posterior cingulate cortex, dorsal division; PCG, precentral gyrus; RSC, retrosplenial cortex, ventral division ofposterior cingulate region; SBN, substantia nigra. ∗p < 0.05; ∗∗p < 0.01.

(GR) (p = 0.0003, BA = 11), left medial frontal gyrus(MFG) (p = 0.0004, BA = 25), and right posterior lobeof the cerebellum (CRBL) (p = 0.0003). In contrast,there was a decrease in the rBGM of the anteriorcingulate cortex (ACC), including three peak voxels inthe right—one in BA 32 and two in BA 24 (p = 0.00008,p = 0.00005, and p = 0.0002, respectively)—and onepeak voxel in the left ACC, BA 24 (p = 0.00001). Whentaken together as a single cluster, the group of vox-els in the right ACC reached statistical significanceafter controlling for multiple comparisons (family-wise error method - FWE) (pFWE = 0.04). Other areasof decreased rBGM were the right posterior cingu-late cortex (PCC) (BA = 23, p = 0.0001), left anteriorentorhinal cortex (ETC) (BA = 34, p = 0.0002), left pre-central gyrus (PCG) (BA = 13, p = 0.0001), left inferiorfrontal gyrus (IFG) (BA = 47, p = 0.00003), and leftsubstantia nigra (p = 0.0004).

Numeric values of the mean radioactive countsfor brain areas with statistically significant changesin the rBGM after AT were extracted in SPM8 (asdetailed in the Materials and Methods section). Cor-relations between mRC values (differences: Post -Pre) with cognitive tests (differences: Post - Pre) andCSF biomarkers (pre-exercise values) were obtained.As the cROCF scores were not normally distributed(Shapiro-Wilk test, p < 0.001), the Spearman correla-tion coefficient was used for this correlation. For othervariables, the assumption of a normal distribution wasmet, and the Pearson correlation coefficient was cal-culated. There was a negative correlation between thecROCF and the mean radioactive counts in the left ACC(rho = −0.38, p = 0.016) and in the three congruent

areas of the right ACC (rho = −0.31, p = 0.04). Theseresults demonstrated that decreases in the radioactivecounts in these areas after the AT were correlated withimproved performance on the cROCF. The delayedvisual memory scores from the WMS-R correlatedwith the right posterior CRBL (r = 0.38, p = 0.01),indicating that increases in the cerebellar rBGM areassociated with better visual memory. There were nocorrelations among differences in the rBGM, CSFbiomarkers, ADAS-cog, and CET changes. We founda correlation between age and changes in the rBGMof the right cerebellar cortex (r = 0.41, p = 0.008). Noother correlation with the differences in the meanradioactive counts was found, including education andinitial MMSE (p > 0.05).

To further investigate the relationship among themetabolic changes in different brain areas, the meanradioactive count differences of the 3 voxels in the rightACC (the most significant finding) were correlatedwith the mean radioactive count differences of othervoxels that reached statistical significance (increasesor decreases). The results are shown in Table 4. Therewas a negative correlation between the rBGM decreasein the right ACC and the rBGM increase in theright RSC and posterior CRBL (r = −0.51, p = 0.001;r = −0.42, p = 0.006). Decrements in ACC metabolismwere linked to increments of rBGM in RSC and CRBL.There was also a positive correlation between the meanradioactive counts in the left ACC and substantia nigra(r = 0.47, p = 0.002; r = 0.35, p = 0.02; respectively),both with decreases in the rBGM. All correlations per-sisted after controlling for age, education, and baselineMMSE.

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Table 5rBGM comparison of MCI and normal cognitive elderly patients (CG - n = 30) before and after AT.

The results were obtained at the peak voxel level (global analysis, non paired t test)

Z score pFWE pUnc Value CS Peak voxel coordinates‡

MCI x CG before ATPrecuneus, BA 7∗ L 4.63 0.032 0.000002 1907 −2 −50 43Precuneus, BA 7∗ L 4.41 0.073 0.000005 1907 −2 −63 60Precuneus, BA 7∗ L 4.18 0.169 <0.00001 1907 2 −64 40MCI x CG after ATPrecuneus, BA 7† L 4.16 0.182 0.00002 1622 −2 −63 60Precuneus, BA 7† L 4.05 0.252 0.00002 1622 0 −50 45Precuneus, BA 7† L 4.03 0.274 0.00003 1622 2 −64 40

AT, Aerobic training; BA, Brodmann area; CG, control groups (cognitively normal older adults); CS,cluster size (number of voxels); MCI, mild cognitive impairment; L, left; PE, pFWE: p value correctedfor multiple comparisons with the familywise error method; pUnc: p value uncorrected for multiplecomparisons; R, right.*These are contiguous areas in the same cluster of voxels and reached statisticalsignificance at the cluster level (pFWE <0.05; punc <0.001). †These are contiguous areas in the samecluster of voxels and did not reach statistical significance at the cluster level (pFWE >0.05; punc <0.000).‡Talairach.

Fig. 2. Illustrative view of the regions with reduction in rBGM in the MCI patients in relation to normal cognitive older adults before (upperrow) and after the AT program (lower row). Note the reduction in the area of rBGM impairment and also in the impairment intensity in theprecuneus (arrows).

In a post-hoc analysis, an additional comparisonwas performed between participants (before and afterthe AT program) and a CG of cognitively normalolder adults from our institution (Pre-PE versus CGand Post-PE versus CG). The results of this compar-ison are shown in Table 5 and Fig. 2 (demographicdata of CG are reported as Supplementary Material).A left precuneus (PCun) (BA = 7) reduction in therBGM was present in both comparisons, a classicalfinding in MCI populations [50]. The magnitude ofthis metabolic reduction, however, was larger in thecomparison with participants before the AT program.Before the intervention, there was significance after

correction for multiple comparisons at the voxel level(pFWE = 0.033), comprising 1907 voxels in the area ofrBGM reduction. After the AT program, although stillsignificant, the comparison did not reach significanceafter multiple comparisons, and the area with rBGMreduction was smaller (1622 voxels), as seen in Table 5.

DISCUSSION

The results showed that a program of 24 weeks ofsupervised AT was associated with an improvement incognitive functions and with changes in rBGM. Thesefindings indicate that PE may improve cognition and

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cause modifications in resting state brain metabolism,even in an MCI phase.

We observed a mean difference of −2.7 points inthe ADAS-cog scores after the PE intervention. Thisdifference was larger than in a previous trial usingthe ADAS-cog as the main global outcome. Laut-enschlager et al. found that a 24-week home-basedprogram of AT improved the ADAS-cog scores bya mean of −0.87 points when analyzing only MCIsubjects [17]. Part of the difference noted by Laut-enschlager et al. was due to worse scores in the CG(change of 1.29 points, 95% CI 0.2–2.39) rather thanto an improvement of the PE group (change of 0.87points, 95% CI 1.83–0.04). Of note, a large random-ized controlled trial of the cholinesterase inhibitordonepezil in MCI revealed a mean difference of −0.61points in the donepezil group and −0.09 points in theplacebo group after 6 months [51]. Compared withthese two studies, the impact of the current interventionon ADAS-cog score was larger.

Other interventional studies with approximately6-month durations of AT have also shown cogni-tive benefits in MCI subjects. Suzuki et al. reportedimprovements in MMSE and immediate recall inWMS-R logical memory scores after 6 months of amulticomponent exercise-training program includingaerobic exercises, muscle strength training, and pos-tural balance retraining [20]. Baker et al. conducted arandomized trial of high-intensity and high frequency(4 sessions per week) AT in aMCI subjects. They foundimprovements in executive functions and category ver-bal fluency after the intervention. The magnitude of theresults was greater in women [14]. Our data showedsimilar cognitive improvements for amnestic and non-amnestic MCI, and for both gender.Differences in theresults between these studies and ours may be due thetype of PE (supervised versus home-based; aerobiconly versus multicomponent), frequency, type of MCIstudied (amnestic only versus all types) and method-ological heterogeneity.

A decrease in the rBGM of the bilateral dorsal ACC(BA 24 and 32) was the most robust finding in ourstudy. Although this finding could be counter-intuitive,this decrease was negatively correlated with improve-ments in visuospatial and attentional function (cROCF)and with increments in RSC metabolism, which is acomponent of the posterior cingulate region (PCR).The PCR (PCC plus RSC) and PCun have been clas-sically shown to be hypometabolic in MCI due to AD[25, 26, 50], as was confirmed in our sample.

Interestingly,whilestudyingtheacuteeffectsofaero-bic PE in rBGM in normal young adults, Kemppainen et

al. found a generalized metabolic decrease in all inves-tigated areas, particularly in the dorsal ACC [52]. Thephenomenon of glucolytic metabolism reduction washypothesized to be due to a switch from glucose to lac-tate as the preferred neuronal fuel to compensate forthe increased metabolic needs during aerobic PE. Inline with this hypothesis, these authors found that brainmetabolism was negatively correlated with plasma lac-tate. When participants were divided in two groups(“trained” versus “less trained”) based on the cut-offVO2 max of 51 mL/kg/min, the trained group had aprominent reduction in the dorsal ACC as compared tothe less trained group, suggesting some type of adaptivemetabolic change in the region. Additionally, lactatelevels could not explain this selective rBGM decrementin the ACC. It is possible that this “acute effect” maypersist after long-term training, a form of AT-inducedneuroplasticity in the rostral ACC. However, as wemeasured the rBGM at rest and at least 1 week afterthe last training session, it is highly unlikely that this“fuel-change” effect is responsible for the ACC rBGMreductions,sincelactate isclearedfromthebloodstreama few hours after the end of the exercise [53].

These results are anatomically concordant withprevious studies using functional neuroimaging thatshowed ACC functional changes after AT. In a task-related fMRI study using a flanker task paradigm,Colcombe et al. showed decreases in ACC activation innormal older adults with higher levels of aerobic fitnessand after a training intervention, both of which wereassociated with better cognitive performances [54].An increase in task-related activation in frontoparietalassociative areas was also noted. As the ACC is knownto be activated in conflict monitoring situations and bepart of the adaptive attention network, better use offrontoparietal networks and consequently less behav-ioral conflict was the explanation given by the authors,for these results.

Recently, Chapman et al. showed that 12 weeksof supervised aerobic training with three sessions perweek increased cerebral blood flow in the ACC inhealthy sedentary older adults [55]. Additionally, Bur-dette et al. found increased connectivity between theACC and hippocampus in older adults after 4 monthsof aerobic training [56]. These studies provide someevidence that the ACC may be of crucial importancein the link between physical fitness and the augmen-tation of cognitive performance. Our results provideadditional evidence that even in an “MCI stage”, ATcan modify resting state rBGM in brain regions impor-tant for cognition and that the ACC is an importantregion linking brain responses to PE.

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To understand the cognitive effects of the metabolicchanges induced by PE in the ACC, it is importantto review the role of ACC in cognition. The ACC isa specialized neocortical area involved in cognitiveand emotional control as well as intelligent behavior(emotional self-control, focused problem solving, errorrecognition, and adaptive responses to changing con-ditions) [57, 58]. Despite being an interface betweenemotional and cognitive processing [58], there is someanatomical separation between the more dorsal “cogni-tive” and ventral “emotional” regions of the ACC. BA24 and 32 have been labeled the “cognitive division ofthe ACC” [59]. Consistent with this idea, the dorsalACC has been demonstrated to be an important nodeof the cingulo-opercular or “salience network”, a sub-component of the fronto-parietal control network. Thesalience network is involved in cognitive control andis parallel and complementary to the dorsal attentionalfrontoparietal network [60, 61]. Also, the dorsal ACChas been shown to have both structural and functionalhemispheric asymmetries. Structural data have indi-cated that the gray matter volume on the right sideis larger than that on the left side [62, 63]. A restingstate fMRI study also reported asymmetries in connec-tivity strength, with a strong connection of the righthemisphere with strategic cognitive areas, such as thedorsolateral prefrontal cortex and the dorsal posteriorcingulate cortex [64]. Decreases in resting state rBGMin these right dorsal areas of the ACC after the exerciseintervention were the more prominent finding in thisstudy.

We found an increase in the rBGM of the ventraldivision of the PCR (RSP, BA 30) and a decrease inthe dorsal PCC (BA 23). The PCR is composed ofRSC (BA 29 and 30) and PCC (BA 23 and 31) [65].The PCR is not functionally homogeneous [66]. It canbe divided into dorsal and ventral sub-regions, the for-mer composed of the anterior PCC (BA 23 and 31)and the latter composed of the posterior parts of thePCC (BA 23 and 31) and the RSC [66]. Along withPCun (BA 7), both ventral and dorsal components ofthe PCR are highly connected with other componentsof the default mode network (DMN) [66]. However,the ventral PCR is also connected with the medialtemporal lobes, while the dorsal PCC is connectedwith the ventromedial prefrontal cortex through thecingulum bundle [67]. As such, within the DMN func-tions, the ventral PCR is believed to support moreinternally directed processes, including the retrievalof episodic and semantic memories, while the dorsalPCR, which is connected with frontal “task-positivenetworks”, is more involved in cognitive control by

coordinating switches between “task-positive” and“task-negative” brain networks [66, 68, 69]. Our datasupport the idea that at rest, a decreased rBGM inthe dorsal ACC, an important node of the saliencenetwork that is associated with an increased rBGMin RSC (component of the ventral PCR), indicatesbetter functioning of these opposing brain networks.This idea is also supported by the cognitive improve-ment and the negative correlation between decreases inACC and MFG metabolism and increases in cROCFscores, which involve executive and visuospatial atten-tional functions. The decreased rBGM in the dorsalPCR may be related to its connections with the leftACC, as noted by a correlation between the changesin these areas (r = 0.48, p < 0.01). Additionally, a largecluster in the PCun showed significant rBGM reduc-tion when compared with a CG, but this reductiondecreased in intensity after AT. Both findings indi-cate increased metabolism in the central nodes (RSCand PCun) of the DMN after AT. Hypometabolismin the DMN nodes is a widely explored [18F]FDG-PET prognostic marker for the progression of MCIpatients to dementia and has been considered the“metabolic signature” of AD [23, 25, 26, 50]. Ourresults show that AT attenuated the metabolic dys-functions in some nodes of the DMN. When takentogether, our results indicate that after aerobic training,a simultaneous decrease in rBGM in a large area of theACC and other areas acted in opposition to an increasein the ventral PCR and an improvement in cognitiveperformance.

Other cerebral areas presented statistically signifi-cant changes in rBGM after the intervention, includingfrontal areas (increases and decreases), the substan-tia nigra (decrease), and the cerebellum (increase). Ofnote, the posterior CRBL rBGM changes were cor-related with increments in RSC and decrements inACC rBGM (r = 0.46, p = 0.006; r = −0.42, p = 0.006).These changes were also correlated with better visualmemory function (r = 0.38, p = 0.01). The CRBL defi-nitely plays a role in cognition, especially its posteriordivisions [70]. A link between the posterior lobe of theCRBL and visuospatial learning has been shown [71].The metabolic change in the “cognitive CRBL” may belinked to the other metabolic changes and the cognitiveimprovement shown here.

Thepresent studyhas some limitations.First, anMCICG without intervention was not included. The authorsrecognize that this situation makes it difficult to con-clude whether the results were due to the interventionandnot toother factors, suchas learningeffectsor socialinteraction. Some of these questions were addressed by

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studies using data from the Alzheimer’s Disease Neu-roimagingInitiativeandshed lighton thenaturalhistoryof cognition and [18F]FDG-PET in subjects with MCI[24]. When subjects were followed without interven-tions, their ADAS-cog scores did not improve over time(baseline mean: 10.6 (4); after 6 months: 11.5 (4.6)).Other randomized controlled trials with MCI subjectsalso did not reveal significant improvements in theplacebo or control arm [17, 51]. PET data have shownthat in the absence of an intervention, there is a progres-sive decrease in metabolism in specific regions (e.g.,posterior cingulate cortex, temporoparietal cortex, andprefrontal association cortex) [24], but not changesin the ACC. Additionally, recent evidence related toprospective cognitive trajectories in aging showed thatlearning effects are minimal after the conversion fromnormal cognition to MCI or early dementia [72]. Thus,our results may be considered valid. Second, therewas a predominance of female subjects in our study.This was a selection bias due to convenience sampling.Because some evidence exists indicating that womenmay achieve greater cognitive benefits from PE thanmen[14], thegeneralizabilityofourresultsmaybecom-promised. However, it is noteworthy that no interactionbetween cognitive changes and gender was observed.Third, there was no group division according to previ-ousaerobiccapacity (sedentaryversus trained).Finally,there were some demographic differences between theMCI group and the CG of cognitively normal olderadults, such as in education.

In sum, these results must be replicated in a furtherrandomized controlled trial. Nevertheless, our investi-gation provides a model for future studies that focuson changes in resting state rBGM induced by AT.We agree with others that “proof of concept” stud-ies with biomarkers are necessary as a first step toinvestigate promising interventions such as PE beforeexpensive randomized controlled clinical trials are per-formed [73].

CONCLUSION

In conclusion, a 24-week supervised AT programimproved cognition and led to rBGM decreases in thedorsal ACC in subjects with MCI. The decrease in ACCmetabolism was negatively correlated with increasesin the metabolism of the ventral PCR (an importantnode of the DMN) and cognitive improvements. Ourresults are consistent with previous studies indicatingthat, even after the onset of cognitive decline, AT canstill improve cognition. Additionally, ACC appeared

to be an important region mediating the associationbetween PE and cognitive improvements.

ACKNOWLEDGMENTS

The authors thank Prof. Dr. Kirk R. Daffner forhis critical comments and review of the manuscriptand Dr. Igor Yakushev for his providential help withthe MarsBar toolbox for SPM. Also, the authors areindebted to all assistants of the LACRE for their hardwork with the aerobic training. This study was fundedby grants from Fundacao de Amparo a Pesquisa doEstado de Sao Paulo (FAPESP) (numbers 2011/18245-4). The first author (FHGP) was also sponsored by theCoordination for the Improvement of Higher Educa-tion Personnel (CAPES) / Brazil as part of his PhDresearch in the program Science without Borders (num-ber 99999.003029/2014-00).

Authors’ disclosures available online (http://j-alz.com/manuscript-disclosures/15-0033r1).

SUPPLEMENTARY MATERIAL

The supplementary material is available in theelectronic version of this article: http://dx.doi.org/10.3233/JAD-150033.

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