Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You and Your Team.

Learn More →

Association of Life Activities With Cerebral Blood Flow in Alzheimer Disease

Association of Life Activities With Cerebral Blood Flow in Alzheimer Disease BackgroundRegional cerebral blood flow (CBF), a good indirect index of cerebral pathologic changes in Alzheimer disease (AD), is more severely reduced in patients with higher educational attainment and IQ when controlling for clinical severity. This has been interpreted as suggesting that cognitive reserve allows these patients to cope better with the pathologic changes in AD.ObjectiveTo evaluate whether premorbid engagement in various activities may also provide cognitive reserve.DesignWe evaluated intellectual, social, and physical activities in 9 patients with early AD and 16 healthy elderly controls who underwent brain H215O positron emission tomography. In voxelwise multiple regression analyses that controlled for age and clinical severity, we investigated the association between education, estimated premorbid IQ, and activities, and CBF.ResultsIn accordance with previous findings, we replicated an inverse association between education and CBF and IQ and CBF in patients with AD. In addition, there was a negative correlation between previous reported activity score and CBF in patients with AD. When both education and IQ were added as covariates in the same model, a higher activity score was still associated with more prominent CBF deficits. No significant associations were detected in the controls.ConclusionsAt any given level of clinical disease severity, there is a greater degree of brain pathologic involvement in patients with AD who have more engagement in activities, even when education and IQ are taken into account. This may suggest that interindividual differences in lifestyle may affect cognitive reserve by partially mediating the relationship between brain damage and the clinical manifestation of AD.THE COGNITIVE reserve (CR) hypothesis suggests that there are individual differences in the ability to cope with the pathologic changes in Alzheimer disease (AD).Innate intelligence or aspects of life experience may supply reserve in the form of a set of skills or repertoires that allow some people to cope with the pathologic changes better than others. Educational and occupational attainments are considered such aspects of life experience.Epidemiologic data supporting the CR hypothesis include observations that higher educational and occupational attainment is associated with decreased risk for incident dementia.Functional imaging studies have also provided support for the concept of CR. Considering cerebral blood flow (CBF) as an indirect index of pathologic changes in disease(lower blood flow indicating more advanced pathologic changes in AD) studies have shown that patients with higher educationalor occupationalattainment as well as those with a higher premorbid IQhave more prominent flow deficits when controlling for clinical severity. These flow deficits were located in the brain regions typically associated with reduced CBF in AD. Again, these observations support the prediction that individuals with more CR can tolerate more pathologic changes. Factors other than education and occupation might also provide reserve against pathologic changes in AD. Both cross-sectional and prospective longitudinal studies have suggested that engaging in various social, intellectual, and leisure activities is associated with reduced risk of prevalent or incident AD.The present study was designed to use the functional imaging approach just described to clarify the role of reported activities in CR. We evaluated intellectual, social, and physical activities in patients with AD who underwent brain H215O positron emission tomography (PET). A role for such activities in CR would predict that, when controlling for disease severity, patients with higher activity scores would have more advanced pathologic changes in AD. Thus, using CBF as an indirect indicator of pathologic changes in disease would show a negative correlation between activity scores and CBF in areas of the brain that typically show reduced CBF in AD.METHODSSUBJECTSNine patients who met Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition(DSM-III-R) criteria for dementiaand the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer's Disease and Related Disorders Association for probable ADand 16 healthy elderly controls participated in this study. The patients underwent extensive neuropsychologic evaluation, including the Wechsler Adult Intelligence Scale–Revised,the American version of the Nelson Adult Reading Test (NART) estimated IQ,the modified Mini-Mental State examination (mMMS),and tests of memory (short- and long-term verbaland nonverbal), orientation, abstract reasoning (verbaland nonverbal), language (naming,verbal fluency,comprehension,and repetition), and construction (copyingand matching). In addition, the Blessed Dementia Rating Scale (part I, sections A and B)was administered. Magnetic resonance imaging (MRI) was used to rule out patients with vascular diseases or tumors. Other causes of dementia were excluded with appropriate laboratory tests. The diagnosis of AD was reached at a consensus diagnostic conference of physicians and neuropsychologists. Positron emission tomography results did not play any role in the diagnostic process.ACTIVITIESBefore the PET scan, an interview with the patient and the informant or the healthy subject assessed activities engaged in during the last 6 months. The questionnaire was an expanded version of a scale administered to a community of 1772 elderly subjects in a prospective incidence dementia study.Participation in 18 activities was recorded (Table 1). The sum of the points over the 18 activities was calculated for each patient and this leisure score was used as a predictor in subsequent analyses. It was also recorded whether the amount of time patients had spent doing each activity had decreased, remained the same, or increased during the previous 10 years.Table 1. Items Included in the Activities ScaleDuring the Last 6 Months Did You . . . (Never = 1, Sometimes = 2, Often = 3)Watched television or listen to the radioPlay cards or other gamesRead books, magazines, or newspapersGo to lectures or concertsGo to theater or moviesTravel or go on toursGo for walks or ridesTake part in sports, dancing, or exerciseDo gardeningSpend time being aloneDo arts and crafts or hobbiesCook or prepare food as a hobbyCollect things as a hobbySing or play a musical instrumentVisit or were visited by friends or relative or neighborsParticipate as a member of a club or organizationParticipate in church or religious activitiesDo other volunteer work and have time to be alonePET SCAN ACQUISITION AND PROCESSINGScans were collected while the subject was at rest with eyes closed. For each scan, a bolus of 30 mCi (1110 MBq) of intravenous H215O was injected. Using an EXACT 47 PET camera (Siemens, Knoxville, Tenn), three 30-second scan frames were acquired in 2-dimensional mode beginning 20 seconds after tracer administration. After measured attenuation correction (15-minute transmission scan) and reconstruction by filtered back-projection, image resolution was 10 mm full width at half-maximum (FWHM). Arterial blood sampling was not conducted; thus, nonquantitative count images (and not absolute CBF measures) were obtained.Using modules from the statistical parametric mapping program (SPM99; Wellcome Department of Cognitive Neurology, London, England), the following steps were performed in turn for each subject: (1) The 3 PET frames were realigned to each other and summed. (2) A T1-weighted MRI was coregistered to this summed PET image. Magnetic resonance images were acquired using a 1.5-Tesla MR scanner. A T1 3-dimensional spoiled-gradient-recalled echo sequence (repetition time [TR] = 34 ms; echo time [TE] = 5 ms; flip angle = 45°) was used to acquire T1-weighted images with an in-plane resolution of 0.859 mm × 0.859 mm (256 × 256 matrix; 22 cm2field of view). One hundred twenty four –1.5-mm transaxial slices were acquired. The z-dimension was down-sampled to a final dimension of 6 mm per slice. (3) The coregistered MRI was spatially transformed to the coordinates defined by the Montreal Neurological Institute template brain provided by SPM99. (4) The spatial normalization parameters were applied to the summed PET image, which was resliced using sinc interpolation to a final voxel size of 2 mm × 2 mm × 2 mm. (5) The spatially normalized PET image was intensity normalized by its average perirolandic count value (given that both pathologic and quantitative PET CBF imaging data suggest that the perirolandic cortex is typically spared by pathologic changes in disease). (6) The spatially and intensity normalized PET image was spatially smoothed with an isotropic Gaussian kernel (FWHM = 8 mm).STATISTICAL ANALYSESVarious voxelwise multiple regression analyseswere performed on the intensity normalized images (subsequently referred to as "CBF" with the understanding that they are not in physiologic units). Values of the CBF were used as the dependent variable in all of the multiple regression models.Several regression models were separately estimated. Putative CR variables in these various models included education, estimates of premorbid IQ, and the activity score. Word-reading ability as assessed by NART was used to estimate premorbid IQ. Performance on this task remains relatively preserved in mild AD and is considered a good estimate of premorbid abilities.The score on the mMMS was used as an index of the clinical severity of dementia.Our strategy for the regression analyses was to first assess the association between CBF and each putative CR variable individually. We controlled for ageand mMMS score (ie, clinical severity) in all of the models. We first introduced years of education and NART score (in 2 separate models) as independent variables to replicate previous findings. We then used the activity score as an independent variable in a separate model. We finally sought to explore whether there was a relationship between CBF and activity score while accounting for the other variables (education and NART score).For each regression model, voxelwise relationships between the scaled count values and the independent variables of interest were calculated and statistically assessed with tvalues.The false-positive rate was controlled at α = .05 per map via Bonferroni correction for the number of statistically independent resolution elements (resels) across which regressions were calculated (number of resels = total volume of map / product of FWHM across x, y, and z dimensions).We used the tissue density values from subjects' MRI results (in voxels where significant associations were noted in the previous analyses) as covariates in the regression analyses to explore the possibility that any associations between the CR variables and CBF are mediated by atrophy. The atrophy analyses did not change the results.RESULTSDEMOGRAPHICS, LEISURE SCORES, AND CR SUMMARY MEASURESDemographic, clinical, and neuropsychologic variables for each of the AD subjects are presented in Table 2. The same data are presented for both patients with AD and controls in Table 3. There were 5 men and 4 women in the AD group and 6 men and 10 women in the control group.Table 2. Demographic, Clinical, and Neuropsychologic Data for 9 Patients With Alzheimer DiseasePatient No.123456789Age, y677663865255854985Duration of disease, y1257334310Education, y12819141816161814NART score92105.4122115122.599.4114.9121.6121.2Activity score283239393736373639mMMS score424651413437434953SRT total recall303644261030253032SRT delayed recall144201426Phonological fluency, percentile381034563910129990Categorical fluency, percentile1956152021319Blessed Dementia Rating Scale1.521.5220.51.521Abbreviations: mMMS, Mini-Mental State examination; NART, Nelson Adult Reading Test; SRT, Selective Reminding Test.Table 3. Demographic, Cognitive, and Functional Characteristics of the Subjects*CharacteristicAlzheimer Disease (n = 9)Control (n = 16)P ValueAge, y68.8 (14.9)76.6 (6.3).16Duration of disease, y4.2 (2.8)NANAEducation, y15 (3.5)15.3 (2.0).82NART score112.6 (11.2)119.8 (6.1).11Activity score35.9 (3.7)37.9 (2.4).12mMMS score43.9 (6.3)51.9 (3.4).006SRT total recall29.2 (9.2)48.8 (8.7).001SRT delayed recall2.7 (1.9)7.7 (3.0).001Phonological fluency, percentile43.1 (33.1)75.7 (22.4).009Categorical fluency, percentile14 (17.5)54.1 (24.7).001Blessed Dementia Rating Scale1.6 (0.5)0.15 (2.4).001Abbreviations: mMMS, Mini-Mental State examination; NA, not applicable; NART, Nelson Adult Reading Test; SRT, Selective Reminding Test.*Data are given as mean (SD) unless otherwise indicated.Although all of the test subjects had only mild AD, it could be argued that current activities do not accurately reflect premorbid lifestyle. We therefore examined the reported change in the amount of time spent doing each activity during the last 10 years. For 5 patients, the time spent on each activity was reported to have either increased or remained stable over the last 10 years. Four patients reported decreased time devoted to 2 of 18, 3 of 18, 4 of 18, and 6 of 18 activities, respectively. Since these activities represented only a small fraction of the overall score, with most of the activities exercised at a stable rate or more frequently, we considered the activity score to be a reasonable estimate of activities, at least during the decade preceding the study.Correlations between education and NART score were r= 0.59, P<.002 (AD: r= 0.60, P<.09; control: r= 0.67, P<.004); between education and activities, r= 0.29, P<.15 (AD: r= 0.60, P<.08; control: r= −0.15, P<.59); and between NART score and activities, r= 0.53, P<.007 (AD: r= 0.81, P<.008; control: r= −0.05, P<.85). The nonsignificant correlations may indicate that the variables are not truly associated. Nevertheless, it is hard to draw many conclusions from this given the very small number of subjects (9 patients with AD and 16 controls), which may have resulted in low power to detect existing significant correlations.REGRESSION ANALYSESIn accordance with previous findings,education was inversely associated with CBF (Table 4). Similarly, in line with previous reports,there was a negative association between premorbid IQ (as measured by the NART) and CBF (Table 4).Table 4. Local Maxima With Statistically Significant Inverse Association Between Cerebral Blood Flow (CBF) and Education and Between CBF and Nelson Adult Reading Test Score*Talairach Coordinatest ValuesLocations (Brodmann Area)xyzEducationAlzheimer disease−10−58455.2†Precuneus (7)2616454.8†Middle frontal gyrus (8)50−69224.5‡Middle temporal gyrus (39)Control. . .. . .. . .. . .. . .Nelson Adult Reading Test scoreAlzheimer disease141176.0‡Caudate20−7245.3‡Cingulate20−13125.1†Thalamus−34−34505.6‡Parietal-postcentral gyrus (3)−32−24−95.4‡Hippocampus−12−41395.4‡Cingulate (31)8455.2†Caudate8−204.9†Lentiform nucleus18−68295.1†Precuneus (7)12−12−134.8†Brainstem36−20−164.7†Parahippocampal gyrus−142924.7†Cingulate-corpus callosum−2435414.6†Middle frontal gyrus (8)Control. . .. . .. . .. . .. . .*The analyses were controlled for age and Mini-Mental State examination score. Ellipses indicate that significant inverse associations were detected for the controls. No positive associations were detected for either group.†P<.05.‡P<.01.The activity score was also inversely correlated with CBF when controlling for age and mMMS score (Table 5and Figure 1). Significant associations were localized mainly to the temporal lobe but also in temporal-parietal-occipital association areas. When simultaneously controlling for age, mMMS score, education, and NART score, activity score was still negatively correlated with CBF (Table 6).Table 5. Local Maxima With a Statistically Significant Inverse Association Between Cerebral Blood Flow and Activity Scores*Talairach Coordinatest ValuesLocations (Brodmann Area)xyzActivity scoreAlzheimer disease10−63316.7†Precuneus (7)−4−45355.7‡Precuneus (31)0−60345.5‡Precuneus (7)−24−52526.2‡Precuneus (7)2216455.7‡Superior frontal gyrus (8)−12−60445.6‡Precuneus (7)−57−19−15.4‡Superior temporal gyrus (21)22−50395.3§Precuneus (7)32−56425.0§Inferior parietal lobule (7)−53−49−95.3§Inferior temporal gyrus (20)−32−22−115.3§Parahippocampal gyrus−26−30−95.0§Parahippocampal gyrus−38−35485.3§Inferior parietal lobule (40)2−14−145.2§Brainstem-mamillary body−50−58145.2§Superior temporal gyrus (22)48−67245.1§Middle temporal gyrus (39)51−47235.1§Supramarginal gyrus (40)−46−7195.0§Middle occipital gyrus (19)−30−55215.0§Middle temporal gyrus (39)−38−78−64.9§Inferior occipital gyrus (19)−57−3724.8§Middle temporal gyrus (22)−32−77194.8§Middle occipital gyrus (19)38−24−114.8§Hippocampus−57−38134.8§Superior temporal gyrus (22)46−3774.7§Superior temporal gyrus (41)−2455194.7§Middle frontal gyrus (10)55−20−124.6§Middle temporal gyrus (21)−6−63254.6§Precuneus (31)53−43−54.6§Middle temporal gyrus (37)Control8−47−84.7§Cerebellum*The analyses were controlled for age and Mini-Mental State examination score. No positive associations were detected for either group.†P<.001.‡P<.01.§P<.05.Statistical parametric map and its 3-dimensional brain rendering representation depicting areas of significant (some P<.001, some P<.01, and some P<.05, as presented in Table 4) inverse correlations between cerebral blood flow and activities score in the Alzheimer group, controlling for age and Mini-Mental State Examination score.Table 6. Local Maxima With a Statistically Significant Inverse Association Between Cerebral Blood Flow and Activity Scores*Talairach Coordinatest ValuesLocations (Brodmann Area)xyzActivity scoreAlzheimer disease−42−76−16.9†Inferior occipital gyrus (19)−46−7076.4†Middle occipital gyrus (19)−50−48216.7†Supramarginal gyrus (40)−50−52146.1†Superior temporal gyrus (39)−59−22−45.1‡Middle temporal gyrus (21)−38−1365.0‡InsulaControl32−1365.3‡Lentiform nucleus*The analyses were controlled for age, Mini-Mental State Examination score, education, and Nelson Adult Reading Test score. No positive associations were detected for either group.†P<.01.‡P<.05.With the exception of 2 voxels (1 in the cerebellum [Table 5], and 1 in the lentiform nucleus [Table 6]), no significant associations were detected for the controls. We did not detect positive associations in any of the analyses, neither in the AD nor in the control group.COMMENTConsistent with the prediction of the CR hypothesis, we found that activities had a negative correlation with CBF in patients with AD when controlling for disease severity. This relationship was seen primarily in voxels located in the temporal but also in temporal-occipital-parietal association cortices, the areas in which CBF changes are typically noted in AD. This inverse association was still present when both education and IQ were included in the model. This indicates that there is a unique relationship between activities and CBF over and above the relationship of CBF to education and IQ.A previous study noted an inverse association between educational attainment and CBF (controlling for disease severity) in parietal areas.In our study, we observed a similar negative correlation between education and CBF, localizing to parietal, frontal, and temporal regions.Another study found an inverse association between premorbid IQ and CBF in prefrontal, premotor, orbitofrontal, superior parietal, thalamic, and anterior cingulate areas.In our study, similar results (in terms of directionality of the relationship between IQ and CBF) were obtained. Significant correlations included thalamic, temporal, parietal, frontal, and cingulate areas in our study.The observed differences in localization between previous studies and the present one could derive from the different types of functional imaging modalities used (xenon and fluorodeoxyglucose in previous studies vs oxygen 15 here), different covariates reflecting disease severity used in the analysis, different denominators used for intensity normalization, or different measures of IQ. Most notable, however, is the different methods of analysis: both previous studies used a region-of-interest analysis when they examined the associations between education and CBF and IQ and CBF,while we elected to use a voxelwise analysis. Because we were able to replicate the directionality and, to a certain extent, the localization of these earlier findings with a voxelwise analysis, the validity of these previous observations is strengthened.We detected significant associations in different areas of the brain depending on whether education or IQ or activities were used in the analyses. At first approximation, this may suggest that different aspects of CR mediate clinical protection in an anatomically specific way: ie, patients with high educational attainment can be maintained at similar clinical severity status when the pathologic changes AD affect certain areas of the brain, while patients with high IQ or leisure activity scores can be maintained when other brain regions are affected. Nevertheless, it is also possible that different aspects of CR are not region-specific and that the locations reported in our analyses generally co-localize to the same extended association areas usually affected by AD. The combination of the limited number of subjects included in our analyses and our conservative approach for controlling for type I error might have limited our power to detect significant associations in the whole spectrum of affected areas of the brain. In addition, the locations reported in our analyses represent only local maxima of more extended areas of the brain (Figure 1). Maintaining intellectual and social engagement through participation in everyday activities seems to buffer healthy individuals against cognitive decline in later life.We recently reported the results of a longitudinal epidemiologic study in northern Manhattan, NY.Thirteen leisure activities (intellectual, social, and physical in character) were assessed in 1772 healthy elderly subjects who were prospectively followed for up to 7 years. Even when multiple potentially confounding factors were controlled for, subjects with high leisure activity scores had 38% less risk of developing dementia. There are at least 2 other large prospective cohorts that have reported a protective effect for leisureand cognitive activitiesin relationship to incident dementia.A limitation of the present study is that activities were assessed in patients with mild dementia and that the extent to which they participated in these activities might have been affected by the disease. Optimally, activities should have been recorded during presymptomatic periods. However, as described in the "Results" section, our patients were at early stages of AD and the reported changes in their activities over the last 10 years were ostensibly negligible. We therefore used the recorded activity score as an estimate of lifestyle during the 10 years before study enrollment.To further explore this potential bias, we repeated the analyses using reconstructed scores for the subjects who reported decreased time devoted to activities, adding in points for the activities they reported to exercise less over the last 10 years. The results for all models were essentially unchanged. We elected to use the contemporaneous activity score for the analyses because it is less prone to recollection bias. The fact that the activities information was corroborated by the informant also added to the face validity of the scores.The activity scale items collected in this study reflected not only intellectual and social activities but also physical ones. Epidemiologic evidence that physical exercise may delay cognitive impairment is equivocal. While high levels of physical activity were associated with reduced risk of dementia in at least 4 prospective studies,no effect of exercise on dementia and cognitive impairment risk was reported from other cohorts.Additionally, there is basic research evidence that environmental enrichment in the form of voluntary wheel running is associated with enhanced neurogenesis in the adult mouse dentate gyrus.It has also been shown that physical activity sustains cerebral blood flowand may improve aerobic capacity and cerebral nutrient supply.Therefore, although it is conceivable that physical activity may merely be a nonspecific marker of good health indirectly related to dementia (or not related to dementia at all), it is also possible that it has a direct physiologic association with brain disease.Recent evidence indicates that certain areas of the brain retain the capability to generate new neurons into adulthood, not only in rodentsand primatesbut also in humans.Thus, it is possible that the stimulation provided by everyday intellectual and social activities facilitates the maintenance of general cognitive skills in a manner that is analogous to physical exercise for musculoskeletal and cardiovascular functions.This reserve could be the result of a physiologic process involving increased synaptic density in the neocortical association cortex acquired by stimulation.This study does not indicate that more engagement in activities affords some kind of immunity to the neuropathologic aspect of the AD process. On the contrary, we assume that the pathologic changes in AD progress independently of life activities. The concept of CR was developed in an attempt to explain interindividual differences in the degree of pathologic changes in the brain necessary for the clinical expression of disease.This has been confirmed in multiple studies, which have found that a significant proportion of clinically nondemented individuals manifest neuropathologic changes consistent with AD at autopsy.More engagement in activities may supply a reserve that allows an individual to cope longer before AD is clinically expressed. Aspects of life experience, such as social, intellectual, and physical activities, could modify the paradigms used by the brain to mediate a task by making individuals more efficient or resilient in the face of pathologic changes in the brain or by recruitment of alternate networks.The activity score may simply represent innate rather than acquired abilities. However, activities, education, and IQ seem to have a unique association to CBF, which supports the concept that aspects of life experience may modulate reserve. The hypothesized contribution of life experiences, styles, and activities to the ability to cope with the pathologic changes in AD suggests the possibility of interventions that might delay the onset of the clinical symptoms of the disease.YSternWhat is cognitive reserve? theory and research application of the reserve concept.J Int Neuropsychol Soc.2002;8:448-460.YSternBGurlandTKTatemichiMXTangDWilderRMayeuxInfluence of education and occupation on the incidence of Alzheimer's disease.JAMA.1994;271:1004-1010.PLMcGeerHKamoRHarropPositron emission tomography in patients with clinically diagnosed Alzheimer's disease.CMAJ.1986;134:597-607.PLMcGeerHKamoRHarropComparison of PET, MRI, and CT with pathology in a proven case of Alzheimer's disease.Neurology.1986;36:1569-1574.EGMcGeerPLMcGeerRHarropHAkiyamaHKamoCorrelations of regional postmortem enzyme activities with premortem local glucose metabolic rates in Alzheimer's disease.J Neurosci Res.1990;27:612-619.EGMcGeerRPPeppardPLMcGeer18Fluorodeoxyglucose positron emission tomography studies in presumed Alzheimer cases, including 13 serial scans.Can J Neurol Sci.1990;17:1-11.RMielkeRSchroderGRFinkJKesslerKHerholzWDHeissRegional cerebral glucose metabolism and postmortem pathology in Alzheimer's disease.Acta Neuropathol.1996;91:174-179.JMHoffmanKAWelsh-BohmerMHansonFDG PET imaging in patients with pathologically verified dementia.J Nucl Med.2000;41:1920-1928.RPFriedlandABrunTFBudingerPathological and positron emission tomographic correlations in Alzheimer's disease [letter].Lancet.1985;1:228.CDeCarliJRAtackMJBallPost-mortem regional neurofibrillary tangle densities but not senile plaque densities are related to regional cerebral metabolic rates for glucose during life in Alzheimer's disease patients.Neurodegeneration.1992;1:113-121.YSternGEAlexanderIProhovnikRMayeuxInverse relationship between education and parietotemporal perfusion deficit in Alzheimer's disease.Ann Neurol.1992;32:371-375.YSternGEAlexanderIProhovnikRelationship between lifetime occupation and parietal flow: implications for a reserve against Alzheimer's disease pathology.Neurology.1995;45:55-60.GEAlexanderMLFureyCLGradyAssociation of premorbid intellectual function with cerebral metabolism in Alzheimer's disease: implications for the cognitive reserve hypothesis.Am J Psychiatry.1997;154:165-172.KKondoMNiinoKShidoA case-control study of Alzheimer's disease in Japan: significance of life-styles.Dementia.1994;5:314-326.RPFriedlandTFritschKASmythPatients with Alzheimer's disease have reduced activities in midlife compared with healthy control-group members.Proc Natl Acad Sci U S A.2001;98:3440-3445.CFabrigouleLLetenneurJFDartiguesMZarroukDCommengesPBarberger-GateauSocial and leisure activities and risk of dementia: a prospective longitudinal study.J Am Geriatr Soc.1995;43:485-490.RSWilsonCFMendes de LeonLBarnesParticipation in cognitively stimulating activities and risk of incident Alzheimer disease.JAMA.2002;287:742-748.NScarmeasGLevyMTangJManlyYSternInfluence of leisure activity on the incidence of Alzheimer's disease.Neurology.2001;57:2236-2242.American Psychiatric AssociationDiagnostic and Statistical Manual of Mental Disorders, Revised Third Edition.Washington, DC: American Psychiatric Association; 1987.GMcKhannDDrachmanMFolsteinRKatzmanDPriceEMStadlanClinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease.Neurology.1984;34:939-944.DWechslerWechler Adult Intelligence Scale Revised.New York, NY: The Psychological Corp; 1981.EGroberMSliwinskiDevelopment and validation of a model for estimating premorbid verbal intelligence in the elderly.J Clin Exp Neuropsychol.1991;13:933-949.HENelsonAO'ConnellDementia: the estimation of premorbid intelligence levels using the New Adult Reading Test.Cortex.1978;14:234-244.HENelsonThe National Adult Reading Test (NART): Test Manual.Windsor, England: NFER-Nelson; 1982.MFFolsteinSEFolsteinPRMcHughMini-mental state: a practical method for grading the cognitive state of patients for the clinician.J Psychiatr Res.1975;12:189-198.RMayeuxYSternJRosenJLeventhalDepression, intellectual impairment, and Parkinson disease.Neurology.1981;31:645-650.YSternMSanoJPaulsonRMayeuxModified mini-mental state examination: validity and reliability.Neurology.1987;37(suppl 1):179.HBuschkePAFuldEvaluating storage, retention, and retrieval in disordered memory and learning.Neurology.1974;24:1019-1025.ABentonThe Visual Retention Test.New York, NY: The Psychological Corp; 1955.SMattisMental Status ecamination for organic mental syndrome inthe elderly patient.In: Bellak L Karasu TB, eds. Geriatric Psychiatry.New York, NY: Grune & Stratton; 1976.EKaplanHGoodglassSWeintraubBoston Naming Test.Philadelphia, Pa: Lea & Febiger; 1983.ABentonAHamsherMultiligual Aphasia Examination.Iowa City: University of Iowa; 1976.HGoodglassDKaplanThe Assessment of Aphasia and Related Disorders.2nd ed. Philadelphia, Pa: Lea & Febiger; 1983.Not AvailableThe Rosen Drawing Test.Bronx NY: Veterans Administration Medical Center; 1981.GBlessedBETomlinsonMRothThe association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects.Br J Psychiatry.1968;114:797-811.SEArnoldBTHymanJFloryARDamasioGWVan HoesenThe topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer's disease.Cereb Cortex.1991;1:103-116.GSSmithMJde LeonAEGeorgeTopography of cross-sectional and longitudinal glucose metabolic deficits in Alzheimer's disease: pathophysiologic implications.Arch Neurol.1992;49:1142-1150.KJFristonAPHolmesKJWorsleyJPPolineRSJFrackowiakStatistical parametric maps in functional imaging: a general linear approach.Hum Brain Mapp.1995;2:189-210.MLezakNeuropsychological Assessment.New York, NY: Oxford University Press; 1995.YSternMSanoJPaulsonRMayeuxModified mini-mental state examination: validity and reliability.Neurology.1987;37(suppl 1):179.RCabezaFunctional neuroimaging of cognitive aging.In: Cabeza R, Kingstone A, eds. Handbook of Functional Neuroimaging of Cognition. Cambridge, Mass: Massachusetts Institute of Technology Press; 2001:331-377.KJWorsleySMarrettPNeelinACVandalKJFristonACEvansA unified statistical approach for determining significant signals in images of cerebral activation.Hum Brain Mapp.1996;4:58-73.DFHultschCHertzogBJSmallRADixonUse it or lose it: engaged lifestyle as a buffer of cognitive decline in aging?Psychol Aging.1999;14:245-263.DPGoldDAndresJEtezadiTArbuckleASchwartzmanJChaikelsonStructural equation model of intellectual change and continuity and predictors of intelligence in older men.Psychol Aging.1995;10:294-303. [published erratum appears in Psychol Aging.1998;13:434].KSchaieMidlife influences upon intellectual functioning in old age.Int J Behav Dev.1984;7:463-478.GLiYCShenCHChenYWZhauSRLiMLuA three-year follow-up study of age-related dementia in an urban area of Beijing.Acta Psychiatr Scand.1991;83:99-104.TYoshitakeYKiyoharaIKatoIncidence and risk factors of vascular dementia and Alzheimer's disease in a defined elderly Japanese population: the Hisayama Study.Neurology.1995;45:1161-1168.DLaurinRVerreaultJLindsayKMacPhersonKRockwoodPhysical activity and risk of cognitive impairment and dementia in elderly persons.Arch Neurol.2001;58:498-504.GABroeHCreaseyAFJormHealth habits and risk of cognitive impairment and dementia in old age: a prospective study on the effects of exercise, smoking and alcohol consumption.Aust N Z J Public Health.1998;22:621-623.Hvan PraagGKempermannFHGageRunning increases cell proliferation and neurogenesis in the adult mouse dentate gyrus.Nat Neurosci.1999;2:266-270.RLRogersJSMeyerKFMortelAfter reaching retirement age physical activity sustains cerebral perfusion and cognition.J Am Geriatr Soc.1990;38:123-128.REDustmanRORuhlingEMRussellAerobic exercise training and improved neuropsychological function of older individuals.Neurobiol Aging.1984;5:35-42.WWSpirdusoPhysical fitness, aging, and psychomotor speed: a review.J Gerontol.1980;35:850-865.GKempermannHGKuhnFHGageMore hippocampal neurons in adult mice living in an enriched environment.Nature.1997;386:493-495.EGouldAJReevesMSGrazianoCGGrossNeurogenesis in the neocortex of adult primates.Science.1999;286:548-552.PSErikssonEPerfilievaTBjork-ErikssonNeurogenesis in the adult human hippocampus.Nat Med.1998;4:1313-1317.CBJohanssonMSvenssonLWallstedtAMJansonJFrisenNeural stem cells in the adult human brain.Exp Cell Res.1999;253:733-736.RKatzmanEducation and the prevalence of dementia and Alzheimer's disease.Neurology.1993;43:13-20.RKatzmanMAronsonPFuldDevelopment of dementing illnesses in an 80-year-old volunteer cohort.Ann Neurol.1989;25:317-324.PIncePathological correlates of late-onset dementia in a multicenter community-based population in England and Wales.Lancet.2001;357:169-175.WGoldmanJLPriceMStorandtAbsence of cognitive impairement or decline in preclinical Alzheimer's disease.Neurology.2001;56:361-367.Corresponding author and reprints: Nikolaos Scarmeas, MD, Columbia Presbyterian Medical Center, P&S Mailbox 16, PH 19th Floor, 630 W 168th St, New York, NY 10032 (e-mail: ns257@columbia.edu).Accepted for publication October 23, 2002.Author contributions:Study concept and design (Drs Scarmeas, Anderson, Sackeim, Van Heertum, and Stern);acquisition of data (Drs Scarmeas, Anderson, Hilton, Marder, Bell, Van Heertum, and Stern, and Mr Flynn);analysis and interpretation of data (Drs Scarmeas, Zarahn, Habeck, Hilton, Sackeim, Van Heertum, Moeller, and Stern, and Mr Flynn);drafting of the manuscript (Drs Scarmeas and Van Heertum);critical revision of the manuscript for important intellectual content (Drs Zarahn, Anderson, Habeck, Hilton, Marder, Bell, Sackeim, Van Heertum, Moeller, and Stern, and Mr Flynn);statistical expertise (Drs Scarmeas, Zarahn, Habeck, Hilton, Sackeim, Moeller, and Stern, and Mr Flynn);obtained funding (Drs Sackeim and Stern);administrative, technical, and material support (Drs Sackeim, Van Heertum, and Stern);study supervision (Drs Scarmeas, Anderson, Van Heertum, and Stern).This research was supported by federal grants AG 14671 and RR 00645. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png JAMA Neurology American Medical Association

Loading next page...
 
/lp/american-medical-association/association-of-life-activities-with-cerebral-blood-flow-in-alzheimer-PA0AUiEUYd
Publisher
American Medical Association
Copyright
Copyright 2003 American Medical Association. All Rights Reserved. Applicable FARS/DFARS Restrictions Apply to Government Use.
ISSN
2168-6149
eISSN
2168-6157
DOI
10.1001/archneur.60.3.359
Publisher site
See Article on Publisher Site

Abstract

BackgroundRegional cerebral blood flow (CBF), a good indirect index of cerebral pathologic changes in Alzheimer disease (AD), is more severely reduced in patients with higher educational attainment and IQ when controlling for clinical severity. This has been interpreted as suggesting that cognitive reserve allows these patients to cope better with the pathologic changes in AD.ObjectiveTo evaluate whether premorbid engagement in various activities may also provide cognitive reserve.DesignWe evaluated intellectual, social, and physical activities in 9 patients with early AD and 16 healthy elderly controls who underwent brain H215O positron emission tomography. In voxelwise multiple regression analyses that controlled for age and clinical severity, we investigated the association between education, estimated premorbid IQ, and activities, and CBF.ResultsIn accordance with previous findings, we replicated an inverse association between education and CBF and IQ and CBF in patients with AD. In addition, there was a negative correlation between previous reported activity score and CBF in patients with AD. When both education and IQ were added as covariates in the same model, a higher activity score was still associated with more prominent CBF deficits. No significant associations were detected in the controls.ConclusionsAt any given level of clinical disease severity, there is a greater degree of brain pathologic involvement in patients with AD who have more engagement in activities, even when education and IQ are taken into account. This may suggest that interindividual differences in lifestyle may affect cognitive reserve by partially mediating the relationship between brain damage and the clinical manifestation of AD.THE COGNITIVE reserve (CR) hypothesis suggests that there are individual differences in the ability to cope with the pathologic changes in Alzheimer disease (AD).Innate intelligence or aspects of life experience may supply reserve in the form of a set of skills or repertoires that allow some people to cope with the pathologic changes better than others. Educational and occupational attainments are considered such aspects of life experience.Epidemiologic data supporting the CR hypothesis include observations that higher educational and occupational attainment is associated with decreased risk for incident dementia.Functional imaging studies have also provided support for the concept of CR. Considering cerebral blood flow (CBF) as an indirect index of pathologic changes in disease(lower blood flow indicating more advanced pathologic changes in AD) studies have shown that patients with higher educationalor occupationalattainment as well as those with a higher premorbid IQhave more prominent flow deficits when controlling for clinical severity. These flow deficits were located in the brain regions typically associated with reduced CBF in AD. Again, these observations support the prediction that individuals with more CR can tolerate more pathologic changes. Factors other than education and occupation might also provide reserve against pathologic changes in AD. Both cross-sectional and prospective longitudinal studies have suggested that engaging in various social, intellectual, and leisure activities is associated with reduced risk of prevalent or incident AD.The present study was designed to use the functional imaging approach just described to clarify the role of reported activities in CR. We evaluated intellectual, social, and physical activities in patients with AD who underwent brain H215O positron emission tomography (PET). A role for such activities in CR would predict that, when controlling for disease severity, patients with higher activity scores would have more advanced pathologic changes in AD. Thus, using CBF as an indirect indicator of pathologic changes in disease would show a negative correlation between activity scores and CBF in areas of the brain that typically show reduced CBF in AD.METHODSSUBJECTSNine patients who met Diagnostic and Statistical Manual of Mental Disorders, Revised Third Edition(DSM-III-R) criteria for dementiaand the criteria of the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer's Disease and Related Disorders Association for probable ADand 16 healthy elderly controls participated in this study. The patients underwent extensive neuropsychologic evaluation, including the Wechsler Adult Intelligence Scale–Revised,the American version of the Nelson Adult Reading Test (NART) estimated IQ,the modified Mini-Mental State examination (mMMS),and tests of memory (short- and long-term verbaland nonverbal), orientation, abstract reasoning (verbaland nonverbal), language (naming,verbal fluency,comprehension,and repetition), and construction (copyingand matching). In addition, the Blessed Dementia Rating Scale (part I, sections A and B)was administered. Magnetic resonance imaging (MRI) was used to rule out patients with vascular diseases or tumors. Other causes of dementia were excluded with appropriate laboratory tests. The diagnosis of AD was reached at a consensus diagnostic conference of physicians and neuropsychologists. Positron emission tomography results did not play any role in the diagnostic process.ACTIVITIESBefore the PET scan, an interview with the patient and the informant or the healthy subject assessed activities engaged in during the last 6 months. The questionnaire was an expanded version of a scale administered to a community of 1772 elderly subjects in a prospective incidence dementia study.Participation in 18 activities was recorded (Table 1). The sum of the points over the 18 activities was calculated for each patient and this leisure score was used as a predictor in subsequent analyses. It was also recorded whether the amount of time patients had spent doing each activity had decreased, remained the same, or increased during the previous 10 years.Table 1. Items Included in the Activities ScaleDuring the Last 6 Months Did You . . . (Never = 1, Sometimes = 2, Often = 3)Watched television or listen to the radioPlay cards or other gamesRead books, magazines, or newspapersGo to lectures or concertsGo to theater or moviesTravel or go on toursGo for walks or ridesTake part in sports, dancing, or exerciseDo gardeningSpend time being aloneDo arts and crafts or hobbiesCook or prepare food as a hobbyCollect things as a hobbySing or play a musical instrumentVisit or were visited by friends or relative or neighborsParticipate as a member of a club or organizationParticipate in church or religious activitiesDo other volunteer work and have time to be alonePET SCAN ACQUISITION AND PROCESSINGScans were collected while the subject was at rest with eyes closed. For each scan, a bolus of 30 mCi (1110 MBq) of intravenous H215O was injected. Using an EXACT 47 PET camera (Siemens, Knoxville, Tenn), three 30-second scan frames were acquired in 2-dimensional mode beginning 20 seconds after tracer administration. After measured attenuation correction (15-minute transmission scan) and reconstruction by filtered back-projection, image resolution was 10 mm full width at half-maximum (FWHM). Arterial blood sampling was not conducted; thus, nonquantitative count images (and not absolute CBF measures) were obtained.Using modules from the statistical parametric mapping program (SPM99; Wellcome Department of Cognitive Neurology, London, England), the following steps were performed in turn for each subject: (1) The 3 PET frames were realigned to each other and summed. (2) A T1-weighted MRI was coregistered to this summed PET image. Magnetic resonance images were acquired using a 1.5-Tesla MR scanner. A T1 3-dimensional spoiled-gradient-recalled echo sequence (repetition time [TR] = 34 ms; echo time [TE] = 5 ms; flip angle = 45°) was used to acquire T1-weighted images with an in-plane resolution of 0.859 mm × 0.859 mm (256 × 256 matrix; 22 cm2field of view). One hundred twenty four –1.5-mm transaxial slices were acquired. The z-dimension was down-sampled to a final dimension of 6 mm per slice. (3) The coregistered MRI was spatially transformed to the coordinates defined by the Montreal Neurological Institute template brain provided by SPM99. (4) The spatial normalization parameters were applied to the summed PET image, which was resliced using sinc interpolation to a final voxel size of 2 mm × 2 mm × 2 mm. (5) The spatially normalized PET image was intensity normalized by its average perirolandic count value (given that both pathologic and quantitative PET CBF imaging data suggest that the perirolandic cortex is typically spared by pathologic changes in disease). (6) The spatially and intensity normalized PET image was spatially smoothed with an isotropic Gaussian kernel (FWHM = 8 mm).STATISTICAL ANALYSESVarious voxelwise multiple regression analyseswere performed on the intensity normalized images (subsequently referred to as "CBF" with the understanding that they are not in physiologic units). Values of the CBF were used as the dependent variable in all of the multiple regression models.Several regression models were separately estimated. Putative CR variables in these various models included education, estimates of premorbid IQ, and the activity score. Word-reading ability as assessed by NART was used to estimate premorbid IQ. Performance on this task remains relatively preserved in mild AD and is considered a good estimate of premorbid abilities.The score on the mMMS was used as an index of the clinical severity of dementia.Our strategy for the regression analyses was to first assess the association between CBF and each putative CR variable individually. We controlled for ageand mMMS score (ie, clinical severity) in all of the models. We first introduced years of education and NART score (in 2 separate models) as independent variables to replicate previous findings. We then used the activity score as an independent variable in a separate model. We finally sought to explore whether there was a relationship between CBF and activity score while accounting for the other variables (education and NART score).For each regression model, voxelwise relationships between the scaled count values and the independent variables of interest were calculated and statistically assessed with tvalues.The false-positive rate was controlled at α = .05 per map via Bonferroni correction for the number of statistically independent resolution elements (resels) across which regressions were calculated (number of resels = total volume of map / product of FWHM across x, y, and z dimensions).We used the tissue density values from subjects' MRI results (in voxels where significant associations were noted in the previous analyses) as covariates in the regression analyses to explore the possibility that any associations between the CR variables and CBF are mediated by atrophy. The atrophy analyses did not change the results.RESULTSDEMOGRAPHICS, LEISURE SCORES, AND CR SUMMARY MEASURESDemographic, clinical, and neuropsychologic variables for each of the AD subjects are presented in Table 2. The same data are presented for both patients with AD and controls in Table 3. There were 5 men and 4 women in the AD group and 6 men and 10 women in the control group.Table 2. Demographic, Clinical, and Neuropsychologic Data for 9 Patients With Alzheimer DiseasePatient No.123456789Age, y677663865255854985Duration of disease, y1257334310Education, y12819141816161814NART score92105.4122115122.599.4114.9121.6121.2Activity score283239393736373639mMMS score424651413437434953SRT total recall303644261030253032SRT delayed recall144201426Phonological fluency, percentile381034563910129990Categorical fluency, percentile1956152021319Blessed Dementia Rating Scale1.521.5220.51.521Abbreviations: mMMS, Mini-Mental State examination; NART, Nelson Adult Reading Test; SRT, Selective Reminding Test.Table 3. Demographic, Cognitive, and Functional Characteristics of the Subjects*CharacteristicAlzheimer Disease (n = 9)Control (n = 16)P ValueAge, y68.8 (14.9)76.6 (6.3).16Duration of disease, y4.2 (2.8)NANAEducation, y15 (3.5)15.3 (2.0).82NART score112.6 (11.2)119.8 (6.1).11Activity score35.9 (3.7)37.9 (2.4).12mMMS score43.9 (6.3)51.9 (3.4).006SRT total recall29.2 (9.2)48.8 (8.7).001SRT delayed recall2.7 (1.9)7.7 (3.0).001Phonological fluency, percentile43.1 (33.1)75.7 (22.4).009Categorical fluency, percentile14 (17.5)54.1 (24.7).001Blessed Dementia Rating Scale1.6 (0.5)0.15 (2.4).001Abbreviations: mMMS, Mini-Mental State examination; NA, not applicable; NART, Nelson Adult Reading Test; SRT, Selective Reminding Test.*Data are given as mean (SD) unless otherwise indicated.Although all of the test subjects had only mild AD, it could be argued that current activities do not accurately reflect premorbid lifestyle. We therefore examined the reported change in the amount of time spent doing each activity during the last 10 years. For 5 patients, the time spent on each activity was reported to have either increased or remained stable over the last 10 years. Four patients reported decreased time devoted to 2 of 18, 3 of 18, 4 of 18, and 6 of 18 activities, respectively. Since these activities represented only a small fraction of the overall score, with most of the activities exercised at a stable rate or more frequently, we considered the activity score to be a reasonable estimate of activities, at least during the decade preceding the study.Correlations between education and NART score were r= 0.59, P<.002 (AD: r= 0.60, P<.09; control: r= 0.67, P<.004); between education and activities, r= 0.29, P<.15 (AD: r= 0.60, P<.08; control: r= −0.15, P<.59); and between NART score and activities, r= 0.53, P<.007 (AD: r= 0.81, P<.008; control: r= −0.05, P<.85). The nonsignificant correlations may indicate that the variables are not truly associated. Nevertheless, it is hard to draw many conclusions from this given the very small number of subjects (9 patients with AD and 16 controls), which may have resulted in low power to detect existing significant correlations.REGRESSION ANALYSESIn accordance with previous findings,education was inversely associated with CBF (Table 4). Similarly, in line with previous reports,there was a negative association between premorbid IQ (as measured by the NART) and CBF (Table 4).Table 4. Local Maxima With Statistically Significant Inverse Association Between Cerebral Blood Flow (CBF) and Education and Between CBF and Nelson Adult Reading Test Score*Talairach Coordinatest ValuesLocations (Brodmann Area)xyzEducationAlzheimer disease−10−58455.2†Precuneus (7)2616454.8†Middle frontal gyrus (8)50−69224.5‡Middle temporal gyrus (39)Control. . .. . .. . .. . .. . .Nelson Adult Reading Test scoreAlzheimer disease141176.0‡Caudate20−7245.3‡Cingulate20−13125.1†Thalamus−34−34505.6‡Parietal-postcentral gyrus (3)−32−24−95.4‡Hippocampus−12−41395.4‡Cingulate (31)8455.2†Caudate8−204.9†Lentiform nucleus18−68295.1†Precuneus (7)12−12−134.8†Brainstem36−20−164.7†Parahippocampal gyrus−142924.7†Cingulate-corpus callosum−2435414.6†Middle frontal gyrus (8)Control. . .. . .. . .. . .. . .*The analyses were controlled for age and Mini-Mental State examination score. Ellipses indicate that significant inverse associations were detected for the controls. No positive associations were detected for either group.†P<.05.‡P<.01.The activity score was also inversely correlated with CBF when controlling for age and mMMS score (Table 5and Figure 1). Significant associations were localized mainly to the temporal lobe but also in temporal-parietal-occipital association areas. When simultaneously controlling for age, mMMS score, education, and NART score, activity score was still negatively correlated with CBF (Table 6).Table 5. Local Maxima With a Statistically Significant Inverse Association Between Cerebral Blood Flow and Activity Scores*Talairach Coordinatest ValuesLocations (Brodmann Area)xyzActivity scoreAlzheimer disease10−63316.7†Precuneus (7)−4−45355.7‡Precuneus (31)0−60345.5‡Precuneus (7)−24−52526.2‡Precuneus (7)2216455.7‡Superior frontal gyrus (8)−12−60445.6‡Precuneus (7)−57−19−15.4‡Superior temporal gyrus (21)22−50395.3§Precuneus (7)32−56425.0§Inferior parietal lobule (7)−53−49−95.3§Inferior temporal gyrus (20)−32−22−115.3§Parahippocampal gyrus−26−30−95.0§Parahippocampal gyrus−38−35485.3§Inferior parietal lobule (40)2−14−145.2§Brainstem-mamillary body−50−58145.2§Superior temporal gyrus (22)48−67245.1§Middle temporal gyrus (39)51−47235.1§Supramarginal gyrus (40)−46−7195.0§Middle occipital gyrus (19)−30−55215.0§Middle temporal gyrus (39)−38−78−64.9§Inferior occipital gyrus (19)−57−3724.8§Middle temporal gyrus (22)−32−77194.8§Middle occipital gyrus (19)38−24−114.8§Hippocampus−57−38134.8§Superior temporal gyrus (22)46−3774.7§Superior temporal gyrus (41)−2455194.7§Middle frontal gyrus (10)55−20−124.6§Middle temporal gyrus (21)−6−63254.6§Precuneus (31)53−43−54.6§Middle temporal gyrus (37)Control8−47−84.7§Cerebellum*The analyses were controlled for age and Mini-Mental State examination score. No positive associations were detected for either group.†P<.001.‡P<.01.§P<.05.Statistical parametric map and its 3-dimensional brain rendering representation depicting areas of significant (some P<.001, some P<.01, and some P<.05, as presented in Table 4) inverse correlations between cerebral blood flow and activities score in the Alzheimer group, controlling for age and Mini-Mental State Examination score.Table 6. Local Maxima With a Statistically Significant Inverse Association Between Cerebral Blood Flow and Activity Scores*Talairach Coordinatest ValuesLocations (Brodmann Area)xyzActivity scoreAlzheimer disease−42−76−16.9†Inferior occipital gyrus (19)−46−7076.4†Middle occipital gyrus (19)−50−48216.7†Supramarginal gyrus (40)−50−52146.1†Superior temporal gyrus (39)−59−22−45.1‡Middle temporal gyrus (21)−38−1365.0‡InsulaControl32−1365.3‡Lentiform nucleus*The analyses were controlled for age, Mini-Mental State Examination score, education, and Nelson Adult Reading Test score. No positive associations were detected for either group.†P<.01.‡P<.05.With the exception of 2 voxels (1 in the cerebellum [Table 5], and 1 in the lentiform nucleus [Table 6]), no significant associations were detected for the controls. We did not detect positive associations in any of the analyses, neither in the AD nor in the control group.COMMENTConsistent with the prediction of the CR hypothesis, we found that activities had a negative correlation with CBF in patients with AD when controlling for disease severity. This relationship was seen primarily in voxels located in the temporal but also in temporal-occipital-parietal association cortices, the areas in which CBF changes are typically noted in AD. This inverse association was still present when both education and IQ were included in the model. This indicates that there is a unique relationship between activities and CBF over and above the relationship of CBF to education and IQ.A previous study noted an inverse association between educational attainment and CBF (controlling for disease severity) in parietal areas.In our study, we observed a similar negative correlation between education and CBF, localizing to parietal, frontal, and temporal regions.Another study found an inverse association between premorbid IQ and CBF in prefrontal, premotor, orbitofrontal, superior parietal, thalamic, and anterior cingulate areas.In our study, similar results (in terms of directionality of the relationship between IQ and CBF) were obtained. Significant correlations included thalamic, temporal, parietal, frontal, and cingulate areas in our study.The observed differences in localization between previous studies and the present one could derive from the different types of functional imaging modalities used (xenon and fluorodeoxyglucose in previous studies vs oxygen 15 here), different covariates reflecting disease severity used in the analysis, different denominators used for intensity normalization, or different measures of IQ. Most notable, however, is the different methods of analysis: both previous studies used a region-of-interest analysis when they examined the associations between education and CBF and IQ and CBF,while we elected to use a voxelwise analysis. Because we were able to replicate the directionality and, to a certain extent, the localization of these earlier findings with a voxelwise analysis, the validity of these previous observations is strengthened.We detected significant associations in different areas of the brain depending on whether education or IQ or activities were used in the analyses. At first approximation, this may suggest that different aspects of CR mediate clinical protection in an anatomically specific way: ie, patients with high educational attainment can be maintained at similar clinical severity status when the pathologic changes AD affect certain areas of the brain, while patients with high IQ or leisure activity scores can be maintained when other brain regions are affected. Nevertheless, it is also possible that different aspects of CR are not region-specific and that the locations reported in our analyses generally co-localize to the same extended association areas usually affected by AD. The combination of the limited number of subjects included in our analyses and our conservative approach for controlling for type I error might have limited our power to detect significant associations in the whole spectrum of affected areas of the brain. In addition, the locations reported in our analyses represent only local maxima of more extended areas of the brain (Figure 1). Maintaining intellectual and social engagement through participation in everyday activities seems to buffer healthy individuals against cognitive decline in later life.We recently reported the results of a longitudinal epidemiologic study in northern Manhattan, NY.Thirteen leisure activities (intellectual, social, and physical in character) were assessed in 1772 healthy elderly subjects who were prospectively followed for up to 7 years. Even when multiple potentially confounding factors were controlled for, subjects with high leisure activity scores had 38% less risk of developing dementia. There are at least 2 other large prospective cohorts that have reported a protective effect for leisureand cognitive activitiesin relationship to incident dementia.A limitation of the present study is that activities were assessed in patients with mild dementia and that the extent to which they participated in these activities might have been affected by the disease. Optimally, activities should have been recorded during presymptomatic periods. However, as described in the "Results" section, our patients were at early stages of AD and the reported changes in their activities over the last 10 years were ostensibly negligible. We therefore used the recorded activity score as an estimate of lifestyle during the 10 years before study enrollment.To further explore this potential bias, we repeated the analyses using reconstructed scores for the subjects who reported decreased time devoted to activities, adding in points for the activities they reported to exercise less over the last 10 years. The results for all models were essentially unchanged. We elected to use the contemporaneous activity score for the analyses because it is less prone to recollection bias. The fact that the activities information was corroborated by the informant also added to the face validity of the scores.The activity scale items collected in this study reflected not only intellectual and social activities but also physical ones. Epidemiologic evidence that physical exercise may delay cognitive impairment is equivocal. While high levels of physical activity were associated with reduced risk of dementia in at least 4 prospective studies,no effect of exercise on dementia and cognitive impairment risk was reported from other cohorts.Additionally, there is basic research evidence that environmental enrichment in the form of voluntary wheel running is associated with enhanced neurogenesis in the adult mouse dentate gyrus.It has also been shown that physical activity sustains cerebral blood flowand may improve aerobic capacity and cerebral nutrient supply.Therefore, although it is conceivable that physical activity may merely be a nonspecific marker of good health indirectly related to dementia (or not related to dementia at all), it is also possible that it has a direct physiologic association with brain disease.Recent evidence indicates that certain areas of the brain retain the capability to generate new neurons into adulthood, not only in rodentsand primatesbut also in humans.Thus, it is possible that the stimulation provided by everyday intellectual and social activities facilitates the maintenance of general cognitive skills in a manner that is analogous to physical exercise for musculoskeletal and cardiovascular functions.This reserve could be the result of a physiologic process involving increased synaptic density in the neocortical association cortex acquired by stimulation.This study does not indicate that more engagement in activities affords some kind of immunity to the neuropathologic aspect of the AD process. On the contrary, we assume that the pathologic changes in AD progress independently of life activities. The concept of CR was developed in an attempt to explain interindividual differences in the degree of pathologic changes in the brain necessary for the clinical expression of disease.This has been confirmed in multiple studies, which have found that a significant proportion of clinically nondemented individuals manifest neuropathologic changes consistent with AD at autopsy.More engagement in activities may supply a reserve that allows an individual to cope longer before AD is clinically expressed. Aspects of life experience, such as social, intellectual, and physical activities, could modify the paradigms used by the brain to mediate a task by making individuals more efficient or resilient in the face of pathologic changes in the brain or by recruitment of alternate networks.The activity score may simply represent innate rather than acquired abilities. However, activities, education, and IQ seem to have a unique association to CBF, which supports the concept that aspects of life experience may modulate reserve. The hypothesized contribution of life experiences, styles, and activities to the ability to cope with the pathologic changes in AD suggests the possibility of interventions that might delay the onset of the clinical symptoms of the disease.YSternWhat is cognitive reserve? theory and research application of the reserve concept.J Int Neuropsychol Soc.2002;8:448-460.YSternBGurlandTKTatemichiMXTangDWilderRMayeuxInfluence of education and occupation on the incidence of Alzheimer's disease.JAMA.1994;271:1004-1010.PLMcGeerHKamoRHarropPositron emission tomography in patients with clinically diagnosed Alzheimer's disease.CMAJ.1986;134:597-607.PLMcGeerHKamoRHarropComparison of PET, MRI, and CT with pathology in a proven case of Alzheimer's disease.Neurology.1986;36:1569-1574.EGMcGeerPLMcGeerRHarropHAkiyamaHKamoCorrelations of regional postmortem enzyme activities with premortem local glucose metabolic rates in Alzheimer's disease.J Neurosci Res.1990;27:612-619.EGMcGeerRPPeppardPLMcGeer18Fluorodeoxyglucose positron emission tomography studies in presumed Alzheimer cases, including 13 serial scans.Can J Neurol Sci.1990;17:1-11.RMielkeRSchroderGRFinkJKesslerKHerholzWDHeissRegional cerebral glucose metabolism and postmortem pathology in Alzheimer's disease.Acta Neuropathol.1996;91:174-179.JMHoffmanKAWelsh-BohmerMHansonFDG PET imaging in patients with pathologically verified dementia.J Nucl Med.2000;41:1920-1928.RPFriedlandABrunTFBudingerPathological and positron emission tomographic correlations in Alzheimer's disease [letter].Lancet.1985;1:228.CDeCarliJRAtackMJBallPost-mortem regional neurofibrillary tangle densities but not senile plaque densities are related to regional cerebral metabolic rates for glucose during life in Alzheimer's disease patients.Neurodegeneration.1992;1:113-121.YSternGEAlexanderIProhovnikRMayeuxInverse relationship between education and parietotemporal perfusion deficit in Alzheimer's disease.Ann Neurol.1992;32:371-375.YSternGEAlexanderIProhovnikRelationship between lifetime occupation and parietal flow: implications for a reserve against Alzheimer's disease pathology.Neurology.1995;45:55-60.GEAlexanderMLFureyCLGradyAssociation of premorbid intellectual function with cerebral metabolism in Alzheimer's disease: implications for the cognitive reserve hypothesis.Am J Psychiatry.1997;154:165-172.KKondoMNiinoKShidoA case-control study of Alzheimer's disease in Japan: significance of life-styles.Dementia.1994;5:314-326.RPFriedlandTFritschKASmythPatients with Alzheimer's disease have reduced activities in midlife compared with healthy control-group members.Proc Natl Acad Sci U S A.2001;98:3440-3445.CFabrigouleLLetenneurJFDartiguesMZarroukDCommengesPBarberger-GateauSocial and leisure activities and risk of dementia: a prospective longitudinal study.J Am Geriatr Soc.1995;43:485-490.RSWilsonCFMendes de LeonLBarnesParticipation in cognitively stimulating activities and risk of incident Alzheimer disease.JAMA.2002;287:742-748.NScarmeasGLevyMTangJManlyYSternInfluence of leisure activity on the incidence of Alzheimer's disease.Neurology.2001;57:2236-2242.American Psychiatric AssociationDiagnostic and Statistical Manual of Mental Disorders, Revised Third Edition.Washington, DC: American Psychiatric Association; 1987.GMcKhannDDrachmanMFolsteinRKatzmanDPriceEMStadlanClinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease.Neurology.1984;34:939-944.DWechslerWechler Adult Intelligence Scale Revised.New York, NY: The Psychological Corp; 1981.EGroberMSliwinskiDevelopment and validation of a model for estimating premorbid verbal intelligence in the elderly.J Clin Exp Neuropsychol.1991;13:933-949.HENelsonAO'ConnellDementia: the estimation of premorbid intelligence levels using the New Adult Reading Test.Cortex.1978;14:234-244.HENelsonThe National Adult Reading Test (NART): Test Manual.Windsor, England: NFER-Nelson; 1982.MFFolsteinSEFolsteinPRMcHughMini-mental state: a practical method for grading the cognitive state of patients for the clinician.J Psychiatr Res.1975;12:189-198.RMayeuxYSternJRosenJLeventhalDepression, intellectual impairment, and Parkinson disease.Neurology.1981;31:645-650.YSternMSanoJPaulsonRMayeuxModified mini-mental state examination: validity and reliability.Neurology.1987;37(suppl 1):179.HBuschkePAFuldEvaluating storage, retention, and retrieval in disordered memory and learning.Neurology.1974;24:1019-1025.ABentonThe Visual Retention Test.New York, NY: The Psychological Corp; 1955.SMattisMental Status ecamination for organic mental syndrome inthe elderly patient.In: Bellak L Karasu TB, eds. Geriatric Psychiatry.New York, NY: Grune & Stratton; 1976.EKaplanHGoodglassSWeintraubBoston Naming Test.Philadelphia, Pa: Lea & Febiger; 1983.ABentonAHamsherMultiligual Aphasia Examination.Iowa City: University of Iowa; 1976.HGoodglassDKaplanThe Assessment of Aphasia and Related Disorders.2nd ed. Philadelphia, Pa: Lea & Febiger; 1983.Not AvailableThe Rosen Drawing Test.Bronx NY: Veterans Administration Medical Center; 1981.GBlessedBETomlinsonMRothThe association between quantitative measures of dementia and of senile change in the cerebral grey matter of elderly subjects.Br J Psychiatry.1968;114:797-811.SEArnoldBTHymanJFloryARDamasioGWVan HoesenThe topographical and neuroanatomical distribution of neurofibrillary tangles and neuritic plaques in the cerebral cortex of patients with Alzheimer's disease.Cereb Cortex.1991;1:103-116.GSSmithMJde LeonAEGeorgeTopography of cross-sectional and longitudinal glucose metabolic deficits in Alzheimer's disease: pathophysiologic implications.Arch Neurol.1992;49:1142-1150.KJFristonAPHolmesKJWorsleyJPPolineRSJFrackowiakStatistical parametric maps in functional imaging: a general linear approach.Hum Brain Mapp.1995;2:189-210.MLezakNeuropsychological Assessment.New York, NY: Oxford University Press; 1995.YSternMSanoJPaulsonRMayeuxModified mini-mental state examination: validity and reliability.Neurology.1987;37(suppl 1):179.RCabezaFunctional neuroimaging of cognitive aging.In: Cabeza R, Kingstone A, eds. Handbook of Functional Neuroimaging of Cognition. Cambridge, Mass: Massachusetts Institute of Technology Press; 2001:331-377.KJWorsleySMarrettPNeelinACVandalKJFristonACEvansA unified statistical approach for determining significant signals in images of cerebral activation.Hum Brain Mapp.1996;4:58-73.DFHultschCHertzogBJSmallRADixonUse it or lose it: engaged lifestyle as a buffer of cognitive decline in aging?Psychol Aging.1999;14:245-263.DPGoldDAndresJEtezadiTArbuckleASchwartzmanJChaikelsonStructural equation model of intellectual change and continuity and predictors of intelligence in older men.Psychol Aging.1995;10:294-303. [published erratum appears in Psychol Aging.1998;13:434].KSchaieMidlife influences upon intellectual functioning in old age.Int J Behav Dev.1984;7:463-478.GLiYCShenCHChenYWZhauSRLiMLuA three-year follow-up study of age-related dementia in an urban area of Beijing.Acta Psychiatr Scand.1991;83:99-104.TYoshitakeYKiyoharaIKatoIncidence and risk factors of vascular dementia and Alzheimer's disease in a defined elderly Japanese population: the Hisayama Study.Neurology.1995;45:1161-1168.DLaurinRVerreaultJLindsayKMacPhersonKRockwoodPhysical activity and risk of cognitive impairment and dementia in elderly persons.Arch Neurol.2001;58:498-504.GABroeHCreaseyAFJormHealth habits and risk of cognitive impairment and dementia in old age: a prospective study on the effects of exercise, smoking and alcohol consumption.Aust N Z J Public Health.1998;22:621-623.Hvan PraagGKempermannFHGageRunning increases cell proliferation and neurogenesis in the adult mouse dentate gyrus.Nat Neurosci.1999;2:266-270.RLRogersJSMeyerKFMortelAfter reaching retirement age physical activity sustains cerebral perfusion and cognition.J Am Geriatr Soc.1990;38:123-128.REDustmanRORuhlingEMRussellAerobic exercise training and improved neuropsychological function of older individuals.Neurobiol Aging.1984;5:35-42.WWSpirdusoPhysical fitness, aging, and psychomotor speed: a review.J Gerontol.1980;35:850-865.GKempermannHGKuhnFHGageMore hippocampal neurons in adult mice living in an enriched environment.Nature.1997;386:493-495.EGouldAJReevesMSGrazianoCGGrossNeurogenesis in the neocortex of adult primates.Science.1999;286:548-552.PSErikssonEPerfilievaTBjork-ErikssonNeurogenesis in the adult human hippocampus.Nat Med.1998;4:1313-1317.CBJohanssonMSvenssonLWallstedtAMJansonJFrisenNeural stem cells in the adult human brain.Exp Cell Res.1999;253:733-736.RKatzmanEducation and the prevalence of dementia and Alzheimer's disease.Neurology.1993;43:13-20.RKatzmanMAronsonPFuldDevelopment of dementing illnesses in an 80-year-old volunteer cohort.Ann Neurol.1989;25:317-324.PIncePathological correlates of late-onset dementia in a multicenter community-based population in England and Wales.Lancet.2001;357:169-175.WGoldmanJLPriceMStorandtAbsence of cognitive impairement or decline in preclinical Alzheimer's disease.Neurology.2001;56:361-367.Corresponding author and reprints: Nikolaos Scarmeas, MD, Columbia Presbyterian Medical Center, P&S Mailbox 16, PH 19th Floor, 630 W 168th St, New York, NY 10032 (e-mail: ns257@columbia.edu).Accepted for publication October 23, 2002.Author contributions:Study concept and design (Drs Scarmeas, Anderson, Sackeim, Van Heertum, and Stern);acquisition of data (Drs Scarmeas, Anderson, Hilton, Marder, Bell, Van Heertum, and Stern, and Mr Flynn);analysis and interpretation of data (Drs Scarmeas, Zarahn, Habeck, Hilton, Sackeim, Van Heertum, Moeller, and Stern, and Mr Flynn);drafting of the manuscript (Drs Scarmeas and Van Heertum);critical revision of the manuscript for important intellectual content (Drs Zarahn, Anderson, Habeck, Hilton, Marder, Bell, Sackeim, Van Heertum, Moeller, and Stern, and Mr Flynn);statistical expertise (Drs Scarmeas, Zarahn, Habeck, Hilton, Sackeim, Moeller, and Stern, and Mr Flynn);obtained funding (Drs Sackeim and Stern);administrative, technical, and material support (Drs Sackeim, Van Heertum, and Stern);study supervision (Drs Scarmeas, Anderson, Van Heertum, and Stern).This research was supported by federal grants AG 14671 and RR 00645.

Journal

JAMA NeurologyAmerican Medical Association

Published: Mar 1, 2003

References