Abstract
Background
Vascular risk factors increase the risk of Alzheimer's disease (AD). The mechanisms for these associations are unclear, and may be due to misdiagnosis of a vascular dementia syndrome as AD.
Objective
To examine differences in neuropsychological profile among persons diagnosed clinically with AD with and without vascular risk factors or stroke.
Methods
Community based cohort study. Individual and composite scores of neuropsychological tests at the time of clinical diagnosis of incident AD were compared among 243 persons with and without vascular risk factors or stroke.
Results
Among subjects with incident AD, diabetes was associated with lower performance in Delayed Recall of the Selective Reminding Test (SRT), while persons diagnosed with hypertension scored lower in consistent long term recall (CLTR) of the SRT and current smokers scored lower in Category Fluency. None of the risk factors was associated with differences in composite scores in memory, abstract/visuospatial or language domain, nor was the number of risk factors per person. Persons with stroke had a higher delayed recall score at the time of AD diagnosis.
Conclusion
The presence of vascular risk factors among persons with clinically diagnosed AD was associated with subtle differences in neuropsychological profile at the time of diagnosis. This study needs to be replicated in samples with brain imaging, a comprehensive executive abilities battery, and pathological diagnosis of AD.
Keywords: Vascular risk factors, Stroke, Neuropsychological test performance
1. Introduction
Alzheimer's disease (AD) is among the most common diseases in aging societies, and its prevalence is expected to quadruple by the year 2047. [1] Vascular risk factors and stroke, which are highly prevalent in ageing societies, are clearly associated to a higher risk of vascular dementia (VaD), [2,3] but are also associated with a higher risk of AD. [4,5] We previously reported associations of stroke, [6] hyperinsulinemia, [7] diabetes, [8] current smoking, [9] and hypertension, [10] to a higher risk of cognitive impairment or AD. We sought to explore how the presence of vascular risk factors modifies the neuropsychological profile of clinically diagnosed AD.
The objective of this study was to explore the neuropsychological differences among persons with incident clinically diagnosed AD with and without vascular risk factors and stroke at the time of diagnosis.
2. Methods
2.1. Subjects and setting
Participants were part of a longitudinal study of Medicare recipients 65 years or older residing in northern Manhattan (Washington Heights, Hamilton Heights, Inwood) that has been described elsewhere. [11] Each participant underwent an in-person interview of general health and function at the time of the study entry followed by a standard assessment, including medical history, physical and neurological examination as well as a neuropsychological battery. [12] Baseline data were collected from 1992 through 1994. Follow-up data were collected during evaluations at sequential intervals of approximately 18 months, performed from 1994 to 1996, 1996 to 1997, and 1997 to 1999. In this elderly population, some participants did not complete follow up at all intervals due to refusal to participate further, relocation or death. About one half of participants were evaluated at the third follow-up visit. Data collected at each follow-up interval included medical, neurogical, and neuropsychological evaluations. [12,13]
The sample for this study was the 243 persons who developed incident clinically defined AD during follow-up, and who did not have dementia at study baseline and when vascular risk factors were ascertained.
2.2. Neuropsychological assessment
All participants underwent a standardized neuropsychological test battery in either English or Spanish. [12] Orientation was evaluated using parts of the modified Mini-Mental State Examination. [14] Language was assessed using the Boston Naming Test, [15] the Controlled Word Association Test, [16] category naming, and the Complex Ideational Material and Phrase Repetition subtests from the Boston Diagnostic Aphasia Evaluation. [15] Abstract Reasoning was evaluated using WAIS-R Similarities subtest, [17] and the non-verbal Identities and Oddities subtest of the Mattis Dementia Rating Scale. [18] Visuospatial ability was examined using the Rosen Drawing Test, [19] and a matching version of the Benton Visual Retention Test. [20] Memory was evaluated using the multiple choice version of the Benton Visual Retention Test [20] and the seven subtests of the Selective Reminding Test [21]: total recall, long-term recall, long-term storage, consistent long-term retrieval (CLTR), words recalled on last trial, delayed recall, and delayed recognition. This neuropsychological test battery has established norms for the same community. [22] The scores of neuropsychological tests used in this study were those obtained from the first visit the person was diagnosed with dementia and who did not have dementia in previous visits.
A factor analysis was performed using data with the 15 neuropsychological measures using a principal component analysis with varimax rotation and Kaiser normalization. [23] This analysis resulted in three factors: 1) a memory factor, in which the seven subtests of the Selective Reminding Test were the main contributors; 2) an abstract/visuospatial factor, where visuospatial and tests of reasoning were the main contributors; and 3) a language factor, in which language measures from the Boston Naming Test [15], Controlled Oral Word Association Test, [16] and the WAIS-R Similarities [17] were the main contributors. Each factor score was normally distributed. Each test within a factor was standardized to a scale of 100 and a final composite score was obtained from the mean of the main tests contributing to each factor.
2.3. Definition of dementia, possible and probable AD
Results from the neurological, psychiatric and neuropsychological examinations were reviewed in a consensus conference comprised of physicians, neurologists, neuropsychologists and psychiatrists. Based on this review all participants were assigned to one of three categories: normal cognitive function, cognitive impairment without dementia, or dementia. Cognitive impairment without dementia was defined as the presence of abnormal neuropsychological tests for age, gender, and education group without significant cognitive impairment, and a Clinical Dementia Rating (reference) (CDR) of 0.5. Dementia was defined as the presence of abnormalities in several cognitive domains in neuropsychiatric testing accompanied by significant functional impairment (CDR ≥1). A diagnosis of probable AD was made when the dementia could not be explained by any other disorder. A diagnosis of possible AD was made when the most likely cause of dementia was AD, but there were other disorders that could contribute to the dementia such as stroke or Parkinson disease (PD). A diagnosis of dementia associated with stroke was made when the dementia started within 3 months of the stroke.
The association between vascular risk factors and AD could be explained by misclassification of vascular dementia or dementia associated with stroke as AD. [24] To address this possible misclassification, we conducted analyses among all persons with incident AD (possible or probable AD), and additional analyses only among persons with probable AD. The diagnosis of dementia and its subtypes was based only on clinical criteria and was not based on pathological or neuroimaging information, which was not available.
2.4. Stroke
Stroke was defined according to the WHO criteria. [25] The presence of stroke was ascertained from an interview with participants and their informants. Persons with stroke were confirmed through their medical records, 85% of which included results of brain imaging. The remaining were confirmed by direct examination. This definition of stroke is related to a higher risk of AD in this cohort [6], and thus is included in our analyses.
2.5. Vascular risk factors
Diabetes mellitus and hypertension were defined by self-report at baseline and at each follow-up interval or by the use of disease specific medications. Blood pressure measurements were also considered in the definition of hypertension. Heart disease was defined as a history of atrial fibrillation and other arrhythmias, myocardial infarction, congestive heart failure or angina pectoris. Smoking was also ascertained by self report, and was classified as current smoking or ever smoking. These diagnoses have shown a sensitivity and specificity of over 90% using medical records as the gold standard. We previously reported that only diabetes, hypertension, heart disease, and current smoking have at least marginal associations with a higher risk of AD, [26] while other risk factors, such as homocysteine [27] and dyslipidemia [28,29] are not related to AD risk in this cohort. Thus, the only risk factors that we include in our analyses are diabetes, hypertension, heart disease, and current smoking, in addition to stroke.
2.6. APOE genotyping
APOE genotypes were determined as described by Hixson and Vernier [30] with slight modification. [31] We classified persons as homozygeous or heterozygeous for the APOE ε4 allele or not having any ε4 allele.
3. Statistical methods
Demographics and other potentially relevant factors were compared among individuals with incident clinically defined AD with and without vascular risk factors and with and without stroke. We only included vascular risk factors which have been observed to be associated with clinically defined AD in our previous studies in the same population [26]: diabetes mellitus, heart disease, hypertension, and current smoking. We used χ2 tests for categorical data and analysis of variance for continuous variables. ANCOVA was used to compare the means of each individual test among persons with incident possible and probable AD with and without each risk factor adjusted for age, gender, ethnic group, and years of education. ANCOVA was then repeated comparing the adjusted means of the composite scores in memory, abstract/visuospatial and language domains among persons with clinically defined incident AD (possible or probable) with and without each risk factor. In a third model, adjusted means of individual and composite tests were compared among persons with clinically defined incident AD with and without various clusters of risk factors. To address possible misclassification of vascular dementia or dementia associated with stroke as AD, all analyses were repeated among subjects with clinically defined probable AD only. We also conducted secondary analyses relating vascular risk factors to slope of decline in the memory, abstract/visuospatial, and language scores. These analyses were restricted to individuals with clinically diagnosed AD with at least 3 neuropsychological examinations including that at the time of dementia diagnosis. First, the slope of change in scores was calculated per individual using linear regression. Then the individual scores were used as the dependent variable in linear regression with vascular risk factors as the independent variable adjusting for age, gender, ethnic group, and APOE-ε4, and baseline score. SPPS V10 was used for all analyses.
4. Results
There were 1,138 individuals without dementia at baseline with 6292 person-years of follow-up (mean= 5.5; SD = 3.2) and 270 persons developed incident dementia; 243 persons were clinically diagnosed with incident probable or possible AD (90.0% of all incident dementia), 12 (4.4%) with dementia associated with stroke and 15 (5.6%) with other types of dementia (e.g. Parkinson's disease, Lewy body disease). The sample for this study only included persons with clinically defined AD. For subsequent analyses we reclassified the subtypes of dementia by considering probable cases only as having AD, and the frequencies of dementia subtypes changed as follows: 175 subjects developed AD (62.1% of all dementia), 72 (26.7%) cases had dementia associated with stroke or mixed (vascular and AD) dementia, and 23 (8.2%) had other types of dementia.
Among persons with incident clinically defined possible and probable AD, the mean age was 82.8 ± 6.0, and 70.0% of the sample were women, 54.7% were Hispanic, 8.2% were White, and 35.8% were Black (Table 1). The mean of years of education was 7.1 ± 4.6, and 30.4% were homozygous or heterozygous for the APOE-ε4 allele. Prior to the development of dementia, 33.7% of the subjects reported having diabetes, 83.1% hypertension, 21.0% heart disease, 12.4% had a history of stroke and 14.8% were current smokers. Women reported diabetes, hypertension, heart disease and stroke more often than men, and persons with less years of education were more likely to report hypertension, heart disease, and current smoking compared to persons with more years of education (Table 2).
Table 1.
Demographic characteristics of study population (possible and probable AD)
| Characteristic | Possible and probable AD (n=243) |
|---|---|
| Sex | |
| Men | 73 (30%) |
| Women | 170 (70%) |
| Age at enrollment, mean (SD) | |
| Men | 82.5 (6.0) |
| Women | 83.2 (6.3) |
| Education in years, mean (SD) | 7.1 (4.6) |
| Ethnic groupa | |
| White | 20 (8.2) |
| African-American | 87 (35.8) |
| Hispanic | 133 (54.7) |
| Other | 3 (1.2) |
| APOE genotype 4/4 | 10 (4.1) |
| APOE genotype 4/- | 64 (26.3) |
| APOE genotype -/- | 148 (60.9) |
| Diabetes | 82 (33.7) |
| Hypertension | 202 (83.1) |
| Heart disease | 51 (21.0) |
| Current smoker | 36 (14.8) |
| Stroke | 30 (12.4) |
Values are expressed as number (percentage) unless otherwise indicated. Some percentages are based on an incomplete sample due to small amounts of missing data.
Classified by self-report using the format of the 1990 US census [55].
Table 2.
Comparison of demographics between possible and probable AD participants with and without risk factors
| Demographics | Diabetes |
Hypertension |
Heart disease |
Stroke |
Current smoker |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| No |
Yes |
No |
Yes |
No |
Yes |
No |
Yes |
No |
Yes |
|
| N=161 | N=82 | N=41 | N=202 | N=192 | N=51 | N=213 | N=30 | N=207 | N=36 | |
| Age, mean (SD) | 83.1 (6.0) | 82.7 (6.4) | 83.2 (6.7) | 82.9 (6.1) | 83.0 (6.2) | 82.8 (6.0) | 83.1 (6.3) | 82.3 (5.2) | 83.4 (6.2) | 80.5 (5.1) |
| Sex | ||||||||||
| Men | 53 (32.9) | 20 (24.4) | 16 (39.0) | 57 (28.2) | 59 (30.7) | 14 (27.5) | 65 (30.5) | 8 (26.7) | 55 (26.6) | 18 (50.0) |
| Women | 108 (67.1) | 62 (75.6) | 25 (61.0) | 145 (71.8) | 133 (69.3) | 37 (72.5) | 148 (69.5) | 22 (73.3) | 152 (73.4) | 18 (50.0) |
| Education in years, mean (SD) | 7.1 (4.5) | 7.1 (4.7) | 7.7 (5.4) | 7.0 (4.4) | 7.2 (4.6) | 6.8 (4.4) | 6.9 (4.4) | 8.9 (5.1) | 7.2 (4.6) | 6.6 (4.4) |
| Ethnic groupa | ||||||||||
| White | 13 (8.1) | 7 (8.5) | 4 (9.8) | 16 (7.9) | 15 (7.8) | 5 (9.8) | 14 (6.6) | 6 (20.0) | 17 (8.2) | 3 (8.3) |
| African-American | 59 (36.6) | 28 (34.1) | 16 (39.0) | 71 (35.1) | 67 (34.9) | 20 (39.2) | 75 (35.2) | 12 (40.0) | 72 (34.8) | 15 (41.7) |
| Hispanic | 88 (54.7) | 45 (54.9) | 20 (48.8) | 113 (55.9) | 108 (56.3) | 25 (49.0) | 121 (56.8) | 12 (40.0) | 116 (56.0) | 17 (47.2) |
| Other | 1 (0.6) | 2 (2.4) | 1 (2.4) | 2 (1.0) | 2 (1.0) | 1 (2.0) | 3 (1.4) | - | 2 (1.0) | 1 (2.8) |
| APOE allele | ||||||||||
| 2/4, 3/4, 4/4 | 51 (34.5) | 23 (31.1) | 11 (30.6) | 63 (33.9) | 57 (32.4) | 17 (37.0) | 66 (33.5) | 8 (32.0) | 62 (33.0) | 12 (35.3) |
| 2/2, 2/3 | 24 (16.2) | 4 (5.4) | 4 (11.1) | 24 (12.9) | 23 (13.1) | 5 (10.9) | 25 (12.7) | 3 (12.0) | 23 (12.2) | 5 (14.7) |
| 3/3 | 73 (49.3) | 47 (63.5) | 21 (58.3) | 99 (53.2) | 96 (54.5) | 24 (52.2) | 106 (53.8) | 14 (56.0) | 103 (54.8) | 17 (50.0) |
All models adjusted for age, gender, education, ethnicity and APOEε4 allele. Values are expressed as number (percentage) unless otherwise indicated. Some percentages are based on an incomplete sample due to small amounts of missing data.
Classified by self-report using the format of the 1990 US census [55].
In analyses relating each putative risk factor with scores in individual neuropsychological tests among persons with clinically defined possible and probable AD, persons with diabetes mellitus had significantly lower scores in the Delayed Free Recall Subtest of the Selective Reminding Test (1.1 vs. 1.7; p = 0.006) (Table 3), while persons diagnosed with hypertension scored lower in Category Fluency (8.7 vs. 10.0, p = 0.015). Current smokers showed lower scores on CLTR Raw (2.1 vs. 3.8, p = 0.017), while subjects with a history of stroke or incident stroke performed better in the Delayed Free Recall (2.1 vs. 1.4, p = 0.029 and 1.9 vs. 1.4, p = 0.01) and WAIS-R Similarities Raw subtests (7.3 vs. 4.9, p = 0.025 and 6.5 vs. 4.6, p = 0.048) than persons without stroke. When we related each individual risk factor with composite scores in memory, abstract/visuospatial and language domains, none of the risk factors was associated with lower performance in any of the three cognitive domains (Table 4). In subsequent analyses among subjects with probable AD only, these results remained unchanged.
Table 3.
Comparison of adjusted means (SD) from individual neuropsychological tests among subjects with possible and probable AD with and without each risk factor
| Neuropsychological tests | Diabetes |
Hypertension |
Heart disease |
Stroke |
Current smoker |
|||||
|---|---|---|---|---|---|---|---|---|---|---|
| No | Yes | No | Yes | No | Yes | No | Yes | No | Yes | |
| SRT LTS raw | 10.4 (0.5) | 10.2 (0.8) | 9.4 (1.1) | 10.5 (0.5) | 10.2 (0.5) | 10.8 (1.0) | 10.3 (0.5) | 10.7 (1.4) | 10.4 (0.5) | 10.0 (1.2) |
| SRT total recall | 21.3 (0.5) | 20.0 (0.7) | 20.3 (1.0) | 20.9 (0.5) | 21.0 (0.5) | 20.2 (0.9) | 20.7 (0.4) | 22.1 (1.3) | 21.2 (0.5) | 19.0 (1.1) |
| SRT CLTR raw | 3.7 (0.3) | 3.1 (0.4) | 3.1 (0.6) | 3.6 (0.3) | 3.7 (0.3) | 3.0 (0.5) | 3.5 (0.3) | 3.5 (0.8) | 3.8 (0.3) | 2.1 (0.6)a |
| SRT delayed free recall | 1.7 (0.1) | 1.1 (0.2)a | 1.4 (0.2) | 1.6 (0.1) | 1.6 (0.1) | 1.4 (0.2) | 1.4 (0.1) | 2.1 (0.3)a | 1.6 (0.1) | 1.3 (0.3) |
| SRT delayed recognition | 7.6 (0.2) | 7.5 (0.3) | 7.6 (0.4) | 7.5 (0.2) | 7.6 (0.2) | 7.5 (0.4) | 7.5 (0.2) | 8.2 (0.5) | 7.4 (0.2) | 8.1 (0.4) |
| Benton recognition | 4.3 (0.2) | 4.6 (0.3) | 4.3 (0.3) | 4.4 (0.2) | 4.3 (0.2) | 4.3 (0.3) | 4.4 (0.1) | 4.0 (0.5) | 4.3 (0.1) | 4.7 (0.4) |
| WAIS-R similarities raw | 5.3 (0.4) | 4.6 (0.6) | 4.1 (0.9) | 5.3 (0.4) | 4.9 (0.4) | 5.7 (0.8) | 4.9 (0.4) | 7.3 (1.2)a | 5.0 (0.4) | 5.7 (1.0) |
| Benton matching | 6.6 (0.2) | 6.6 (0.3) | 6.4 (0.5) | 6.6 (0.2) | 6.5 (0.2) | 6.8 (0.4) | 6.6 (0.2) | 6.1 (0.6) | 6.6 (0.2) | 6.6 (0.5) |
| CFL mean (Letter fluency) | 5.6 (0.3) | 5.7 (0.4) | 5.9 (0.5) | 5.6 (0.2) | 5.7 (0.2) | 5.3 (0.5) | 5.7 (0.2) | 5.2 (0.7) | 5.6 (0.2) | 6.2 (0.6) |
| Category fluency mean | 8.8 (0.2) | 9.3 (0.4) | 10.0 (0.5) | 8.7 (0.2)a | 8.9 (0.2) | 9.1 (0.4) | 8.9 (0.2) | 9.1 (0.7) | 8.8 (0.2) | 9.7 (0.6) |
| Identities/similarities total | 12.8 (0.2) | 13.2 (0.3) | 12.3 (0.4) | 13.0 (0.2) | 13.0 (0.2) | 12.4 (0.4) | 12.8 (0.2) | 13.3 (0.6) | 12.8 (0.2) | 13.6 (0.5) |
| BDAE repetition | 7.1 (1.0) | 7.2 (0.1) | 7.0 (0.2) | 7.1 (0.1) | 7.1 (0.1) | 7.3 (0.2) | 7.1 (0.1) | 7.1 (0.2) | 7.0 (0.1) | 7.4 (0.2) |
| BDAE comprehension | 3.9 (0.1) | 4.2 (0.2) | 3.9 (0.2) | 4.0 (0.1) | 4.0 (0.1) | 4.2 (0.2) | 4.0 (0.1) | 4.1 (0.3) | 4.0 (0.1) | 4.2 (0.3) |
All models adjusted for age, gender, education, ethnicity and APOEε4 allele.
Significant at a 0.05 level.
Table 4.
Comparison of adjusted means (SD) from composite scores neuropsychological tests among subjects with possible and probable AD with and without each risk factor
| Diabetes |
Hypertension |
Heart disease |
Stroke |
Incident stroke |
Current smoker |
|||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No | Yes | No | Yes | No | Yes | No | Yes | No | Yes | No | Yes | |
| Memory performance |
25.9 (0.6) | 24.1 (0.8) | 24.6 (1.2) | 25.5 (0.5) | 25.5 (0.5) | 24.8 (1.0) | 25.0 (0.5) | 27.9 (1.4) | 24.9 (0.6) | 26.6 (0.9) | 25.4 (0.5) | 24.9 (1.2) |
| Abstract/ visuospatial performance |
40.9 (0.8) | 41.6 (1.2) | 40.2 (1.6) | 41.3 (0.7) | 41.0 (0.7) | 41.4 (1.4) | 41.1 (0.7) | 41.3 (2.1) | 40.9 (0.7) | 41.9 (1.3) | 40.9 (0.7) | 43.5 (1.8) |
| Language performance |
77.1 (1.2) | 79.4 (1.8) | 76.7 (2.5) | 78.0 (1.1) | 77.0 (1.1) | 80.7 (2.2) | 77.7 (1.1) | 78.9 (2.9) | 78.4 (1.2) | 76.2 (2.0) | 77.1 (1.1) | 81.8 (2.7) |
All models adjusted for age, gender, education, ethnicity and APOEε4 allele.
We previously reported that the risk of clinically diagnosed AD increases with the number of vascular risk factors (diabetes + hypertension + heart disease + current smoking). [26] We constructed a variable counting the number of risk factors: diabetes, hypertension, heart disease, stroke and current smoking; 5.8% of the individuals with possible or probable AD had no risk factors, 30.9% had one risk factor, 44.9% had two risk factors, 15.2% had three risk factors, and 3.3% had four risk factors. We compared the adjusted means from neuropsychological tests among subjects with possible or probable AD with one, two, three, and four vascular risk factors, and there was no association between the number of risk factors and any of the three cognitive domains (Table 5). The results remained unchanged among subjects with probable AD only.
Table 5.
Comparison of adjusted means (SD) from composite scores of neuropsychological tests among subjects with possible and probable AD and with 0 to 5 risk factors
| # of risk factors | Memory performance | Abstract/visuospatial performance | Language performance |
|---|---|---|---|
| 0 | 24.3 (1.9) | 40.3 (2.4) | 70.4 (4.1) |
| 1 | 26.4 (0.9) | 40.0 (1.2) | 78.0 (1.8) |
| 2 | 24.6 (0.7) | 41.1 (0.9) | 77.8 (1.5) |
| 3 | 25.9 (1.2) | 44.0 (1.8) | 79.8 (2.5) |
| 4 | 25.0 (2.7) | 42.2 (4.6) | 82.1 (5.7) |
| p-value | 0.555 | 0.467 | 0.350 |
All models adjusted for age, gender, education, ethnicity and APOEε4 allele.
We conducted secondary analyses relating the vascular risks factors to decline in cognitive scores (memory, abstract visuospatial, language) in 204 persons with clinically diagnosed AD who had at least 3 neuropsychological examinations (Table 6). We found no relation between any of the risk factors and the slopes of the cognitive scores. These results were not different for probable and possible AD.
Table 6.
Coefficients and standard deviations from linear regression relating vascular risk factors and stroke to slopes of change in memory, abstract/visuospatial, and language performance, adjusted for age, gender, education, ethnicity, and APOE-ε4 allele
| Slope of change | Diabetes | Hypertension | Heart disease | stroke | Incident stroke | Current smoking |
|---|---|---|---|---|---|---|
| Memory | 0.1±0.9 | 1.6±1.2 | -0.4±1.25 | -0.1±0.9 | -0.1±0.6 | -0.5±0.7 |
| Abstract /visuospatial | -0.1±0.4 | 0.5±0.6 | -0.7±0.6 | -0.4±0.4 | -0.1±0.3 | -0.6±0.3 |
| Language | 0.0±0.3 | 0.5±0.4 | -0.5±0.4 | 0.0±0.3 | 0.0±0.2 | -0.3±0.2 |
None of the coefficients were statistically significant.
5. Comment
We found subtle differences in neuropsychological profile at the time of clinical diagnosis of AD among persons with and without vascular risk factors. Diabetes was associated with lower performance in Delayed Recall of the SRT among subjects with possible or probable AD. Persons with hypertension scored lower in category fluency and current smokers scored lower in the CLTR subtest of the SRT. Subjects with stroke performed better in the Delayed Recall and WAIS-R Similarities. None of the risk factors was associated with differences in composite scores in memory, abstract/visuospatial or language domain, and increasing number of risk factors was not related to performance in any cognitive domain. The results were the same when comparisons were made only among persons with probable AD. In addition, we found no relation between the risk factors and rate of cognitive decline up to the clinical diagnosis of AD.
The role of vascular risk factors in vascular dementia seems clear. Vascular dementia is related to cerebral small and large vessel disease, [32] which in turn may be caused by diabetes, hypertension, heart disease and smoking. [33] The role of vascular risk factors in AD remains unclear. [5] The main putative mechanism in the pathogenesis of AD is the deposition of amyloid beta (Aβ) in the brain, [34] and it is thought that putative risk factors for AD may act through this pathway. [35,36] However, it is also possible that the relation between vascular risk factors and AD is not causal, but may be explained by coexistence of common disorders in the elderly, or by misclassification of cases of vascular dementia as AD. [24] Vascular risk factors are known to be related to cerebrovascular disease, which in turn has been shown to be associated with AD [6,37] but the mechanisms relating cerebrovascular disease to AD remain to be elucidated. Among the vascular risk factors, diabetes seems to have the strongest biologic plausibility for a direct role in AD, [5,7,26] given its relation not only to cerebrovascular disease, but also to other mechanisms that may impair amyloid beta clearance in the brain such as hyperinsulinemia affecting insulin degrading enzyme. [38-40] The clinical definition of AD has a sensitivity of over 90% but a specificity of approximately 50% using pathological diagnosis as the gold standard, [41] which can result in misclassification of other types of dementia, including vascular dementia, as AD. In addition, some researchers have criticized the emphasis on the clinical diagnosis of AD at the expense of the diagnosis of other types of dementia [42] that may include those related to vascular risk factors and stroke. Thus, we sought to explore whether there was evidence of misclassification of dementia by comparing the neuropsychological profiles of persons with and without vascular risk factors.
Diabetes was associated with lower delayed recall scores at the time of diagnosis of AD, but no other differences in neuropsychological profile. Diabetes has the potential to affect amyloid beta directly and through multiple mechanisms, [5] including cerebrovascular disease, [6] inflammation, [43] and glycosilated end products. [44,45] Given that diabetes has been shown to be a strong risk factor for AD in our cohort [8] as well as in other studies [46,47], and given that memory performance is the strongest predictor of AD, [48,49] it is not surprising that memory performance is worse in persons with AD who have diabetes. However, we found no association between diabetes and more rapid memory decline preceding AD clinical diagnosis.
Persons with hypertension and current smokers had a lower category fluency mean and lower values in the CLTR of the SRT, respectively, but no other differences in neuropsychological profile. This could be explained by the fact that hypertension and current smoking may affect more frontal/executive cognitive abilities, [3] and our results may be showing the juxtaposition of frontal cognitive impairment with AD.
Persons with stroke had a higher delayed recall compared to persons without stroke, but no other differences in neuropsychological profile. Of all the comparisons we made, this finding is the only one that would suggest that these persons had a dementia other than AD, given that an abnormal (low) delayed recall is the neuropsychological hallmark of AD; [49] this result suggests that while these persons had a dementia syndrome very similar to AD, their dementia may have been due to cognitive impairment related to stroke that had an additive effect on the AD process and precipitated functional impairment and the diagnosis of dementia despite higher delayed recall.
There are several alternative explanations for our findings. One is that the few differences in neuropsychological profile that we found are due to chance in the context of multiple comparisons. It is possible that the differences were explained by confounding: vascular risk factors are related to lower socioeconomic status, [50] which can be related to lower raw cognitive scores [12], but we adjusted for education and ethnic group as socioeconomic markers in our analyses. Another possible explanation is bias caused by misclassification of the vascular risk factors and stroke; these were ascertained by self-report, and if underestimated, would have resulted in underestimation of differences between persons with and without risk factors. In particular, we lacked neuroimaging data to ascertain “subclinical” cerebrovascular disease. [51] Another possibility is that the neuropsychological battery in this study may have been biased towards the detection of AD, and thus, we may not be able to find differences because neuropsychological domains more likely to be affected by vascular risk factors were not detected. This last point may indicate that this study is tautological; that is, persons with AD with and without vascular risk factors were going to have the same neuropsychological profile because that profile is what this cohort study sought to detect. In this context, the small differences we found could be interpreted as having clinical significance. We cannot elucidate if this differences are due to mixed additive pathology (vascular and AD), or to differences in the underlying pathophysiologic process because we lacked neuroimaging and pathological data.
This study included a comprehensive neuropsychological battery. However, it may be limited in addressing cognitive domains that are associated with vascular disease. For example, we lacked tests of executive function such as the color trails [52,53] and the stroop color and word tests [54] which may have resulted in underestimation of the differences we sought to find.
It is important to point out that our study only examined differences in neuropsychological profile among persons with the clinical diagnosis, or syndrome, of AD. We did not have neuroimaging or brain pathology data. Thus, we cannot make direct inferences about pathology based on our analyses. We can say that from a neuropsychological standpoint, AD in the presence of vascular risk factors is very similar to that in its absence. The small differences we found may reflect different severity of disease, concomitant pathology, or different pathologic processes. This study needs to be replicated in a sample with a comprehensive battery of tests of executive function, neuroimaging, and ideally, brain pathology.
Acknowledgments
This study was supported by grants PO1 AG07232, AG07702, 1K08AG20856-01, RR00645 from the National Institutes of Health (Bethesda, MD), the Charles S. Robertson Memorial Gift for Research in Alzheimer's disease, the Blanchette Hooker Rockefeller Foundation (New York, NY).
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