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Figure 1. Atherosclerosis and APOE Genotype
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The relative mean wall thickness of the common carotid and internal carotid arteries according to apolipoprotein APOE ∊4 genotype. The referent is the mean artery wall thickness in APOE 2/2.
Figure 2. Change in Modified Mini-Mental State Examination Scores by Presence ofAPOE ∊4 Alleles and the Quartile of Carotid Atherosclerosis
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Table 1. Number of Subjects Taking Cognitive Tests During Follow-up*
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Table 2. Cognitive Test Scores by Age, Race, and Sex Controlled for Education
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Table 3. Cognitive Test Results by Years of Education and Baseline Stroke, Controlled for Age, Sex, Race, and Stroke or Education
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Table 4. Descriptive Statistics for Digit Symbol Substitution Test (DSS) and the Modified Mini-Mental State Examination (3MSE)
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Table 5. Change in Score Over 7 Years on the Modified Mini-Mental State Examination (3MSE) and the Digit Symbol Substitution Test (DDS)*
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Table 6. Decline in Modified Mini-Mental State Examination (3MSE) Score by Apolipoprotein E4 (APOE ∊4) and Subclinical Cardiovascular Disease*
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Original Contribution
July 7, 1999

The Role of APOE ∊4 in Modulating Effects of Other Risk Factors for Cognitive Decline in Elderly Persons

Author Affiliations

Author Affiliations: Departments of Epidemiology and Preventive Medicine (Dr Haan) and Neurology (Dr Jagust), University of California, School of Medicine, Davis; Department of Biostatistics, School of Public Health, University of Washington, Seattle (Dr Shemanski); Departments of Epidemiology and Biometry, National Heart, Lung, and Blood Institute, Bethesda, Md (Dr Manolio); and Department of Epidemiology, School of Public Health, University of Pittsburgh, Pittsburgh, Pa (Dr Kuller).

JAMA. 1999;282(1):40-46. doi:10.1001/jama.282.1.40
Abstract

Context Cognitive decline in elderly persons is often an early predictor of dementia. Subclinical cardiovascular disease (CVD) and diabetes mellitus may contribute to substantial decline in cognitive function in the elderly. These risks may be modified by gene-environment interactions between apolipoprotein E (APOE) genotype and CVD risk factors or subclinical CVD.

Objectives To examine the association between subclinical CVD and decline in cognitive functioning in the elderly and to examine effect modification by the APOE genotype of the association between subclinical disease and cognitive decline.

Design The Cardiovascular Health Study, a population-based, prospective cohort study.

Setting and Population A total of 5888 randomly selected Medicare-eligible participants from Sacramento County, California; Forsyth County, North Carolina; Washington County, Maryland; and Pittsburgh, Pa, aged 65 years or older, who were recruited in 1989-1990 (n = 5201) and in 1992-1993 (n = 687) and who were followed up for 7 and 5 years, respectively.

Main Outcome Measures Change over time in scores on the Modified Mini-Mental State Examination and the Digit Symbol Substitution Test as a function of APOE genotype, subclinical CVD, and diabetes mellitus.

Results Seventy percent of participants had no significant decline on the Modified Mini-Mental State Examination. Systolic blood pressure, the ankle-arm brachial index, atherosclerosis of the internal carotid artery, diabetes mellitus, and several diagnoses of prevalent CVD were significantly associated with declines in scores on the Modified Mini-Mental State Examination and the Digit Symbol Substitution Test. The rate of cognitive decline associated with peripheral vascular disease, atherosclerosis of the common and internal carotid arteries, or diabetes mellitus was increased by the presence of any APOE ∊4 allele.

Conclusions Most healthy elderly people did not experience cognitive decline. Measures of subclinical CVD were modest predictors of cognitive decline. Those with any APOE ∊4 allele in combination with atherosclerosis, peripheral vascular disease, or diabetes mellitus were at substantially higher risk of cognitive decline than those without the APOE ∊4 allele or subclinical CVD. High levels of atherosclerosis increased cognitive decline independently of APOE genotype.

The influence of cardiovascular diseases (CVDs) and risk factors on cognitive decline in the elderly is of importance in the search for predictors and pathways for prevention of dementia. Previous work has linked cognitive decline and dementia to CVD,1 stroke,2 diabetes mellitus (DM) and glucose metabolism,2-11 hypertension and high and low blood pressure,2,12-17 peripheral vascular disease,18 atherosclerosis,19 genetic factors,20,21 and cerebral blood flow.22,23 Apolipoprotein E ∊4 (APOE ∊4) genotype is associated with an increased risk of dementia and cognitive decline.24 Apolipoprotein E ∊4 alleles may account for 13% to 20% of dementia cases.25,26 Although APOE genotype is not a specific disease locus, it may create host susceptibility that affects the rate of disease progression.27 Gene-environment interactions are important in the progression of cognitive impairment and the development of dementia.28 Recent work by the Rotterdam Study1 has suggested that DM, peripheral vascular disease, and atherosclerosis are associated with an increased risk of vascular dementia and Alzheimer disease (AD). Similar findings for a synergistic role played by the APOE ∊4 genotype in the presence of atherosclerotic diseases have been reported by Kuusisto et al.29

A previous Cardiovascular Health Study (CHS) article30 reported an association between cognitive decline measured using the Modified Mini-Mental State Examination (3MSE) of at least 5 points from year 5 (when magnetic resonance imaging was performed) through year 7 and several magnetic resonance imaging measures (infarct on magnetic resonance imaging, high ventricular volume, increased sulci width, and high white matter grade). Heckbert et al31 also found in CHS that a lower 3MSE score was associated with white matter changes.

The purpose of this study was to examine the influence of subclinical CVD and DM on 7-year changes in the 3MSE and the Digit Symbol Substitution test (DSS) results and to examine effect modification by APOE ∊4 of the associations among cognitive decline and atherosclerosis, peripheral vascular disease, or DM.

Methods
Design

The CHS is a cohort study of 5888 randomly selected persons aged 65 years or older at baseline. Descriptions of the CHS study design and recruitment of the CHS cohort have been published elsewhere.32-35 The original sample of the CHS was composed of 5201 elderly adults who were recruited from a defined sample of the Medicare files in 4 communities in the United States: Forsyth County, North Carolina; Sacramento County, California; Washington County, Maryland; and Pittsburgh, Pa. Eligible participants were not institutionalized and were able to give informed consent. Recruitment occurred between June 1989 and May 1990 (year 2). The sample at that time was 57% women and 95% white. In 1992-1993 (year 5), 687 blacks were recruited from Forsyth County, Sacramento, and Pittsburgh by similar methods as the original recruitment, so 15% of the total sample were blacks. Out of the 5888 total study participants, only those who attended the first annual visit for the original cohort (year 3) and attended baseline (year 5) for the new cohort are included in these analyses (Table 1).

Cognitive Status Measures

Each person took the 3MSE and the DSS at least twice (2 years) during the follow-up period.

Modified Mini-Mental State Examination

The 3MSE is scored from 0 to 100.36 It was administered in all annual examinations, starting with the second annual examination.

Digit Symbol Substitution Test

The DSS, a subtest of the Wechsler Adult Intelligence Scales, measures the ability to link symbols with numbers in a timed test (90 seconds).37 Scores include the total test items completed, the number correctly coded, and the number incorrectly coded. The score ranges from 0 to 90 and is the total number done correctly. A higher score indicates better cognitive status. It was administered in all annual examinations.

Measurement of

Methods of measurement for APOE alleles have been published elsewhere.30APOE alleles were assessed for 4607 whites (93%), 850 blacks (93%), and 37 others (82%). At the baseline for both cohorts, prevalence and extent of clinical CVD were assessed by confirmed history of myocardial infarction, angina, congestive heart failure (CHF), atrial fibrillation, coronary artery bypass graft, the use of a pacemaker, stroke or transient ischemic attack, carotid endarterectomy, intermittent claudication, or peripheral vascular surgery. Subclinical CVD measures included an ankle-arm blood pressure index of less than 0.9 mm Hg, internal or common carotid arterial wall thickness (measured by ultrasonography), major abnormalities on electrocardiogram (ECG),38 and atrial fibrillation (ECG). The details of incident events surveillance have been published elsewhere.39 Incident stroke and DM were both defined by self-report during biannual follow-up visit, which was confirmed by review of medical records or a physician questionnaire. Fasting plasma glucose and insulin levels were measured at each annual clinic visit and analyzed at the CHS central laboratory. Two-hour glucose tolerance was measured at the first annual follow-up visit for the original cohort and the baseline visit for the new cohort.

Statistical Methods

The associations between cardiovascular risk factors measured at baseline and cognitive scores were examined using longitudinal statistical methods. Generalized estimation equations (GEEs), as previously described,40 were used to examine associations of cognitive scores and risk factors, taking into account the lack of independence in a participant's observations across time. In these analyses, the correlation structure between a participant's cognitive scores at different visits was assumed to have compound symmetry, meaning the correlation was assumed constant between any 2 cognitive scores for a participant. This correlation structure was most representative of the data compared with other investigated correlation structures, such as autoregression. The basic GEE model included the covariates of age, sex, education, and race, all at baseline, and incident stroke during follow-up. Stroke was included as a covariate because it is a very strong known predictor of cognitive decline during follow-up.2 To minimize the bias resulting from participants with the greatest decline being lost to follow-up, an indicator variable reflecting missing cognitive score data at the last analyzed visit was also included in each model. Baseline stroke, systolic and diastolic blood pressure, and DM were also added to the model. The effect modification analyses between APOE ∊4 alleles and atherosclerosis, peripheral vascular disease, and DM were included because previous reports of such analyses1,2,6,9 suggested that APOE ∊4 might modify the association between these measures and cognitive status or dementia.

Tests of the associations between cognitive scores and risk factors were performed using 2-way interactions of the risk factor with follow-up years and the dependent variable was the cognitive score at each year. Modification of the association between a prespecified risk factor and cognitive change was examined by including a 3-way interaction term to the model, which was equal to the product of follow-up year and the 2 risk factors of interest. All analyses were performed using SAS statistical software,41 with P<.001 considered significant. The new cohort of blacks was not analyzed separately because race differences were not the focus of the study, nor was there adequate statistical power. Their data and scores were added to years 3 through 7 in the analysis.

Results

Table 2 shows the mean 3MSE and DSS scores by age and sex groups. separately by race. Table 3 shows the mean scores by years of education and for presence of baseline stroke. Women had higher 3MSE and DSS scores than men, and whites had higher scores than blacks. Scores were lower at older ages, and both scores were higher for those with more education. Those with prevalent stroke had lower scores on both tests.

Table 4 shows descriptive statistics by the 3MSE and the DSS scores. The mean 3MSE score declined by 4 points, and the mean DSS score declined by more than 6 points in 7 years. The annual median change in the 3MSE was 0, and −0.67 points for the DSS. The 3MSE score did not change at all for 14% of the people. Assuming a change of at least 5 in either direction due to random variation or learning effects and considered clinically unimportant, 70% of the people exhibited little decline or improvement. Cumulatively over 7 years, 11.9% had a decline of 10 points or more and 4.8% had an improvement of 10 points or more.

Table 5 shows the results from a GEE linear regression model for the association between cognitive change and DM and glycemic status, APOE genotypes, and several circulatory disease measures. Clotting factors (fibrinogen, factors VII and VIII), low-density lipoprotein, high-density lipoprotein, and triglyceride levels (all P values >.05) were not significantly associated with the 3MSE or the DSS (data not shown). For continuous variables, subjects at or above 1 SD higher than the mean were compared with those who were below 1 SD above the mean. Mean (SD) values for the fasting plasma glucose level were 6.17 (2.1) mmol/L (111 [37] mg/dL); 2-hour oral glucose tolerance test, 8.2 (3.2) mmol/L (147 [58] mg/dL); systolic blood pressure, 136.58 (21.84) mm Hg; ankle-arm blood pressure, 1.06 (0.17) mm Hg; common carotid arterial thickness, 1.06 (0.22) mm; and internal carotid arterial thickness, 1.44 (0.57) mm.

Diabetes Mellitus

Self-reported history of DM, a definite (medically confirmed) diagnosis of DM, fasting plasma glucose level, and 2-hour glucose tolerance were all negatively associated with change in the DSS scores. An abnormal 2-hour oral glucose tolerance result was associated with decline in both the DSS and the 3MSE scores. Persons who were 1 SD above the mean on the oral glucose tolerance test declined 0.54 points more on the 3MSE than those below 1 SD above the oral glucose tolerance test mean over the 7 years. Persons with confirmed DM declined by 1.8 points more on the DSS in 7 years compared with those without confirmed DM.

Genotype

The frequency distribution of the APOE genotype was as follows: 2/2 (n=32), 2/3 (n=642), 2/4 (n=124), 3/3 (n=2894), 3/4 (n=940), and 4/4 (n=79). Approximately 25% of the sample had at least 1 APOE ∊4 allele. Table 5 compares the change in the 3MSE score for those with any APOE ∊4 allele to those without any APOE ∊4 alleles. Those with at least one APOE ∊4 allele declined nearly 3 points more in 7 years on the 3MSE compared with those without APOE ∊4 alleles. Those with APOE ∊4 alleles declined 2 points on the DSS vs 0.29 points in those without APOE ∊4 alleles over 7 years.

CVD and Risk Factors

Those with higher systolic blood pressure had greater declines in cognitive functioning for both the 3MSE and the DSS. An increase of 1 SD (21.84 mm Hg) above the mean was associated with a decrease of 0.96 points in the 3MSE over 7 years. Presence of low ankle-arm blood pressure (both the continuous ratio and dichotomized ratio) was associated with greater declines in both measures of cognition. A person with an ankle-arm blood pressure of less than 0.90 mm Hg experienced a 4.62-point decline on his or her 3MSE score over the 7 years and a 2.73-point decline in the DSS score vs −0.66 and −0.39, respectively, for those with an ankle-arm blood pressure of at least 0.90 mm Hg. Atrial fibrillation was associated with a 4.4-point decline in the 3MSE scores over 7 years vs 0.63 for those without atrial fibrillation. Higher maximum wall thickness in both the internal and common carotid arteries was associated with greater declines in DSS and 3MSE scores. Among prevalent CVDs, the greatest declines in the 3MSE scores occurred in those with prevalent stroke, followed by CHF and major ECG abnormal results.

Figure 1 shows the ratios of the mean wall thickness of the internal carotid and common carotid arteries for each allele combination compared with those with 2/2 alleles (P<.001). Those with 4/4 alleles had maximum wall thickness that was 40% greater in the internal carotid artery and 80% greater in the common carotid artery. Maximum wall thickness for those with 3/4 alleles was 30% greater in the internal and 60% greater in the common carotid artery, and they were 20% greater in both arteries for those with 2/4 alleles.

Interactions With

We examined whether the presence of an APOE ∊4 allele increased the rate of cognitive decline associated with several measures of subclinical atherosclerotic disease, peripheral vascular disease, or a confirmed diagnosis of DM (Table 6). Annual rates of change in the 3MSE are presented for combinations of (1) no CVD and no APOE ∊4 allele, (2) either CVD or any APOE ∊4 allele, and (3) CVD and any APOE ∊4 allele. Only measures for which P<.001 are reported.

Among those having any APOE ∊4 allele and low ankle-arm blood pressure, the annual rate of decline in the 3MSE score was 8.3 times greater than subjects with neither. The annual rate of decline in the 3MSE scores in those with only APOE ∊4 allele or only a low ankle-arm blood pressure was 2.94 points and 3.66 points greater than those with neither, respectively. We found that the average annual decline in the 3MSE scores associated with a 1 SD increase above the mean wall thickness of the internal carotid artery was nearly 3.9 times greater in the presence of any APOE ∊4 when compared with those with neither APOE ∊4 alleles nor those at the mean.

Among those with DM, subjects with the APOE ∊4 allele had a 1.67-fold cognitive decline in their 3MSE scores compared with those with neither DM nor the APOE ∊4 allele. The presence of APOE ∊4 alleles in persons who did not have DM actually contributed to a somewhat greater decline in their 3MSE scores than among subjects with DM (3.01-fold increase among those who did not have DM). Those with neither DM nor the APOE ∊4 allele had the least cognitive decline in 3MSE scores.

Figure 2 illustrates the slope of change for each of 7 study years in the 3MSE scores by presence of an APOE ∊4 allele for each quartile of wall thickness of the internal carotid artery. Those with an APOE ∊4 allele who were also in the fourth quartile of internal carotid artery wall thickness had the greatest decline in 3MSE scores. The cognitive change in those in the top 3 quartiles of atherosclerosis was modest despite the presence of an APOE ∊4 allele. The highest risk groups for decline were both groups (those with an APOE ∊4 allele and those without) in the top quartile of atherosclerosis. The final mean 3MSE score for those in the lowest risk group (first quartile of atherosclerosis and without the APOE ∊4 allele) vs the mean score for those in the highest risk group (fourth quartile of atherosclerosis and with the APOE ∊4 allele) were, respectively, 76.4 and 68.4, an 8-point difference.

Comment

At least 2 other studies have reported effect modification of the association between atherosclerosis and cognitive decline or dementia by the APOE ∊4 allele. A cross-sectional study9 has suggested that both peripheral vascular disease and atherosclerosis are associated with a substantially increased risk of vascular dementia and AD. Similar results have been reported by Kuusisto et al.29 Skoog et al42 found that only those with both the APOE ∊4 allele and white matter disease had an increased risk of AD or vascular dementia.

Reports from other research on the association between cognitive impairment and DM have been conflicting.43,44 Neuropsychological case-control studies have reported cognitive impairment in participants with DM.45-47 Although there have been reports of significant relationships between cognitive impairment and poor glucose management as measured by glycosylated hemoglobin,47-50 other studies have reported a lack of such relationships.51,52 Kuusisto et al29 and Skoog et al42 have both reported an increased risk of AD in those with type 1 or type 2 DM. Finch and Cohen53 have argued for a complex but important etiologic role for DM in AD and other research has reported associations between various measures of glycemic status, including hyperglycemia and insulinemia, and cognitive impairment.54,55 Since we adjusted for the incidence of stroke in these analyses, part of the mechanism by which DM may influence cognitive function was controlled for. A recent study by Curb et al56 based on a single measure of the 2-hour oral glucose tolerance tests taken 25 years before dementia assessment and a brief history of DM diagnosis 15 years previous to testing did find an association with vascular dementia but not AD.

Other research on the association between the APOE ∊4 allele and cognitive change57,58 has found that those without the APOE ∊4 allele perform better than those with the APOE ∊4 allele on verbal learning tests,59 visual attention, psychomotor rapidity, and the 3MSE.60 However, research by Small et al61 has suggested that the APOE ∊4 allele may not influence cognitive performance in adults without dementia, and loss of recent verbal memory may be related to impending dementia, not to normal age-related changes in cognition. This may be a reflection of differences in progression to disease or dementia in those with the APOE ∊4 allele.

Although atherosclerosis of the common and internal carotid arteries was associated with decline in both cognitive measures, lipids and clotting factors were not. The absence of this association and the modest but consistent association of most forms of circulatory disease, systolic blood pressure, and peripheral vascular disease on cognitive decline suggest that mechanisms other than lipids or coagulation may be important and should be further examined. Previous work done in CHS supports the notion that such changes underlie the link between circulatory disease and long-term cognitive decline.30,31

This is a randomly selected, population-based cohort study. During the 7-year follow-up period, 15.1% died, and 5.2% did not participate in the study for other reasons. Attrition between baseline and the first annual examination was negligible (<5%). Other studies of the elderly have shown relatively little cognitive decline in the first few years of follow-up in cohort studies. This may be due to the self-selection of healthier volunteers as study participants. Thus, there is little impact on our estimates of using the 3MSE and DSS scores measured at the first annual visit. Since our analytic approach allows the inclusion of all subjects who contributed a cognitive test score for each year they participated in the study, we have reduced, but not eliminated, bias that might have arisen from a differential dropout of more cognitively impaired subjects. We reduced this potential for bias further by including an indicator variable reflecting missing data at the final follow-up visit. Since most of the homebound CHS cohort subjects are assessed by our staff in their homes and relatively few are admitted to nursing homes, we have assessed most study participants who are cognitively impaired. Any selection would probably tend to bias any association toward the null hypothesis. A learning effect may be of concern for repeated administrations of the 3MSE and the DSS. This would improve test scores from repeated exposure to the same test. The CHS neither altered the 3MSE nor specifically changed words for recall. Nevertheless, our results have shown a consistent decline in these measures over time. If there is a learning effect, it is counterbalanced by real decline in cognition and our results would be conservative from this standpoint.

The results of our study may have important implications for the origin of vascular dementia and of AD. This adds to the evidence of a link between atherosclerosis and dementia. The modifying role of the APOE ∊4 allele identifies a high-risk group for cognitive decline. Since the rate of cognitive decline is also much higher among those who have high levels of atherosclerosis but who do not have the APOE ∊4 allele, circulatory disease appears to have a role independent of the APOE ∊4 allele. Based on these results, prevention of atherosclerosis could reduce the risk of dementia.

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