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Original Contribution |

Neuropsychological Measures in Normal Individuals That Predict Subsequent Cognitive Decline FREE

Deborah Blacker, MD, ScD; Hang Lee, PhD; Alona Muzikansky, MS; Emily C. Martin, PhD; Rudolph Tanzi, PhD; John J. McArdle, PhD; Mark Moss, PhD; Marilyn Albert, PhD
[+] Author Affiliations

Author Affiliations: Departments of Psychiatry (Dr Blacker), Medicine (Dr Lee and Ms Muzikansky), and Neurology (Dr Tanzi), Massachusetts General Hospital, Harvard Medical School, Boston; Department of Biostatistics, Harvard School of Public Health, Boston, Mass (Dr Martin); Department of Psychology, University of Southern California, Los Angeles (Dr McArdle); Department of Anatomy and Neurobiology, Boston University, Boston, Mass (Dr Moss); Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Md (Dr Albert). Dr Martin is currently with Wyeth Research, Cambridge, Mass.


Arch Neurol. 2007;64(6):862-871. doi:10.1001/archneur.64.6.862.
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Objective  To examine neuropsychological measures among normal individuals that predict time to subsequent cognitive decline.

Design  Cognitive performance, as measured by 6 neuropsychological tests, was examined at baseline. Participants were followed up for approximately 5 years. Cox proportional hazards models were used to evaluate the neuropsychological measures at baseline that predicted time to progression from normal cognition to mild impairment. Comparable data also examined time to progression from mild impairment to a diagnosis of Alzheimer disease.

Setting  Community volunteer-based sample examined at a medical institution.

Participants  One hundred and seven individuals who were cognitively normal and 235 individuals with mild cognitive impairment at baseline.

Main Outcome Measures  Time to progression from normal cognition to mild impairment and time to progression from mild impairment to a diagnosis of Alzheimer disease.

Results  The risk of progressing from normal to mild impairment was considerably greater among those with lower scores on tests of episodic memory (eg, hazard ratio for a 1-SD decrease in the California Verbal Learning Test, 0.55; P<.001). Normal individuals who carried at least 1 copy of the apolipoprotein E ε2 allele were less likely to develop cognitive impairments over time than individuals with no ε2 allele (hazard ratio for presence of allele, 0.13; P = .006). Measures of both episodic memory and executive function were significant predictors of time to progression from mild impairment to a clinical diagnosis of Alzheimer disease (eg, hazard ratio for a 1-SD decrease in California Verbal Learning Test score, 0.67; P = .005; hazard ratio for a 1-SD increase in the time to complete part B of the Trail Making test, 1.40; P = .007). Among individuals with mild impairments, the apolipoprotein E ε4 allele increased risk for Alzheimer disease in a dose-dependent manner; however, this effect was not significant within the context of multivariable models.

Conclusions  Episodic memory performance among normal individuals predicts time to progression to mild impairment while apolipoprotein E ε2 status is associated with lower risk of cognitive decline among normal individuals. Tests of both episodic memory and executive function are predictors of time to progression from mild impairment to a clinical diagnosis of Alzheimer disease.

Figures in this Article

There is increasing evidence that the pathology of Alzheimer disease (AD) can take many years, if not decades, to evolve. This suggests that some individuals who appear normal (ie, functionally asymptomatic) have gradually accumulating pathology. Recent reports based on autopsies of well-characterized normal individuals corroborate this hypothesis.13 For example, in one study of 60 normal individuals who had come to autopsy, approximately 60% had a low “likelihood” of AD based on criteria from the National Institute on Aging–Reagan Institute while 40% had an intermediate or high likelihood of AD.3

These findings suggest that it may be possible to identify characteristic changes using existing methodologies among normal individuals with a high likelihood of substantial underlying AD pathology during life. One potential approach is to determine whether neuropsychological performance among normal individuals can predict the time to develop mild degrees of cognitive impairment that are suggestive of the incipient stages of AD.

There are numerous studies of neuropsychological performance among individuals in the prodromal phase of AD, commonly referred to as mild cognitive impairment (MCI).4 Most have focused on which cognitive tests or domains are predictive of subsequent diagnosis of AD and have found that the cognitive alterations are selective. There is widespread consensus that performance on tests of episodic memory are significantly lower among mildly impaired but nondemented individuals who are destined to meet criteria for AD over time.519 There is also consensus that at least 1 other domain may be altered among such individuals. Many studies have reported that executive function performance is altered during this prodromal phase of AD,15,16,20 but other neuropsychological alterations have been reported as well.21 If cognitive changes exist among normal individuals that predict time to develop mild impairment, it seems reasonable to hypothesize that they would be in the area of episodic memory because changes in this domain are clearly evident by the time individuals show mild deficits in daily life.

We therefore chose to examine neuropsychological performance among a group of 107 normal individuals who were followed up annually for an average of 4.7 years. Approximately half of them (n = 54) developed mild impairments in daily life while the rest (n = 53) remained normal. To determine whether the cognitive deficits observed among normal controls who subsequently develop mild impairment are likely to be part of the evolution of AD, we examined a second group of individuals who had been followed up for a comparable period of time. This group consisted of 235 mildly impaired but nondemented individuals who had been followed up for an average of 5.6 years using similar procedures. Of these, 69 subsequently progressed to a diagnosis of AD.

Cox proportional hazards models were used to evaluate time to progress from one level of severity to another as a function of neuropsychological test performance. The impact of the apolipoprotein E (APOE) gene on time to progression was also examined.

SELECTION OF PARTICIPANTS

A total of 342 individuals were included in the analyses. All of them were participants in an ongoing longitudinal study of the evolution of AD. They had been recruited through the print media (rather than from a clinic or other medical referral source) with advertisements indicating that a research study was seeking individuals both with and without memory difficulty.

Volunteers underwent a multistage screening procedure. The details of the screening procedures have been described elsewhere.16 Briefly, to be included in the study, participants had to be aged 65 years and older (with the exception of 17 individuals aged 57-64 y); have an informant who could provide information about their daily function; be free of significant underlying medical, neurologic, or psychiatric illness; and be willing to participate in the study procedures. In addition, individuals with evidence of major vascular risk factors (eg, atrial fibrillation, insulin-dependent diabetes mellitus, cerebral infarcts, etc) were excluded. All subjects were required to be either cognitively normal or mildly impaired but nondemented, ie, to have a Clinical Dementia Rating (CDR)22 of either CDR 0 or CDR 0.5.

At baseline, the study procedures included a medical evaluation (consisting of a physical examination and medical history, electrocardiogram, and standard laboratory tests), a semistructured interview, neuropsychological testing, a magnetic resonance imaging scan, a single-photon emission computed tomography scan, and blood withdrawn for genetic analysis. Only the semistructured interview was repeated annually; the remaining study procedures were repeated in subsets of participants. All subjects provided informed consent prior to the initiation of the study in accordance with the guidelines of Massachusetts General Hospital, Boston.

ASSESSMENT OF CLINICAL SEVERITY

The degree of clinical severity of the subjects was evaluated by the annual semistructured interview. This interview generates both an overall CDR rating and a measure known as the CDR Sum of Boxes (CDR-SB).23 The interview is based on the initial subject protocol that was used in the development of the CDR scale.22 It includes a set of questions regarding cognitive and functional status asked of the subject and an informant (eg, family member, friend) and a standardized neurologic, psychiatric, and mental status evaluation of the subject. The mental status evaluation included the Blessed Memory and Orientation Test,24 which assesses episodic memory, working memory, and orientation; a set of similarities and differences, which assessed executive function; calculations that assessed arithmetic skill and general knowledge; and a standardized language evaluation, including naming, repetition, and comprehension. To be sensitive to clinical impairments at the mildest end of the spectrum, a special set of questions were added to the interview, and the reliability and validity of the revised interview was examined.25 The mean interrater reliability of the overall CDR rating was high (r = 0.99, P<.001) as was the interrater reliability of the 6 CDR subcategories (r = 0.90) that are used to generate the overall CDR rating. The CDR-SB represents the sum of the ratings in each of the 6 CDR subcategories.

In the current study, each interview was administered annually by a masters' or doctoral-level clinician (eg, psychiatrist, neuropsychologist, or physician's assistant) and took approximately 1 to 2 hours to complete. The interviews were performed without knowledge of the other study procedures, including the neuropsychological testing. A consensus review of each case was conducted annually by 2 or more members of the research group (which included the interviewers mentioned here).

GROUP CHARACTERISTICS AT BASELINE AND AT FOLLOW-UP
Baseline

Based on their initial CDR interview, subjects were divided into 2 groups (Table 1). The normal group consisted of 107 subjects with normal cognition (CDR 0); their mean (SD) CDR-SB score was 0.014 (0.08). (The nonzero mean CDR-SB reflects a handful of individuals with slight difficulties in a domain other than memory; a score of 0.5 in the memory domain is required for an overall rating of 0.5.) The MCI group consisted of 235 nondemented individuals with a CDR rating of 0.5; their mean (SD) CDR-SB was 1.34 (0.77). The 2 groups were similar in age at study entry, although the normal group was somewhat younger (71.4 vs 72.9 years in the MCI group; P = .009). Other demographic variables were not significantly different across the 2 groups, as follows: the educational level (means of 15.6 years vs 15.4 years), the sex distribution (59.8% vs 56.6% female), and the racial distribution (4.7% vs 8.1% nonwhite). The mean Mini-Mental State Exam26 scores at baseline were similar (29.5 vs 29.1; range, 27-30 vs 24-30, respectively) but were nevertheless significantly different from one another (P<.04). Thus, both groups were largely white and well educated and had high scores on the Mini-Mental State Exam.

Table Graphic Jump LocationTable 1. Demographic, Clinical, and Genetic Characteristics of Study Groups

The distribution of CDR-SB scores among the mildly impaired subjects was broad (Table 1). At the mild end of the spectrum (ie, CDR-SB 0.5-1.5), many subjects would not meet psychometric cut-offs commonly used to select MCI subjects in epidemiological studies and clinical trials.27,28 The subjects at the more impaired end of the spectrum (ie, CDR-SB≥2) are comparable with MCI subjects recruited from these settings, based on likelihood of progression to a diagnosis of AD.25 We use MCI here to refer to the entire group of mildly impaired subjects. A retrospective review of the cases indicated that approximately two thirds would fall into the category of amnestic MCI while approximately one third would be considered nonamnestic MCI cases, based on the revised criteria for MCI.29

Current Status of Normal Group

Of the 107 individuals who were normal at baseline, a total of 54 were categorized as impaired over time. Of these 54 individuals, 46 were diagnosed as MCI at the time data were analyzed for the present article. Approximately 74% of these had a CDR-SB of 0.5 to 1.5, and approximately 26% (n = 12) had a CDR-SB of 2 or higher. Eight of the normal subjects who progressed now carry a diagnosis of dementia (7 of the 8 have a clinical diagnosis of AD); the mean time to progress from normal to AD was 8 years (a rate of approximately 1% per year). The mean (SD) time to progress from normal to MCI was 4 (2.9) years.

Current Status of MCI Group

Of the 235 individuals who were mildly impaired at baseline, 87 individuals were no longer categorized as mildly impaired at the time data were analyzed for the present article. Of these, 69 received a clinical diagnosis of AD, 11 received a clinical diagnosis of a non-AD dementia, and 7 had a high CDR-SB (ie, 4), but the clinical diagnosis was incomplete because of pending medical procedures. Approximately 60% of the remaining subjects (n = 84) had a CDR-SB of 2 or higher, and approximately 40% (n = 59) had a score of 0.5 to 1.5. Five of the subjects originally categorized as mildly impaired are now categorized as normal (CDR 0). The mean (SD) time to progress from MCI to AD was 4.1 (3.2) years.

Diagnosis of Dementia on Follow-up

As part of the annual review of each case, the consensus diagnostic process determined whether the individual had sufficient impairment for a diagnosis of dementia and, if so, whether the dementia was consistent with research criteria for AD30 or another known diagnostic entity (eg, frontotemporal dementia, vascular dementia).31,32 Diagnoses were based on findings from a combination of clinical history, medical records, laboratory evaluation, and neuroimaging studies.

Autopsy Findings

Over the course of the longitudinal study, 15 subjects have come to autopsy of whom 9 had a clinical diagnosis of probable AD; this diagnosis was confirmed in 6 of the cases based on the criteria for AD from the National Institute on Aging–Reagan Institute. An additional 3 cases showed AD changes insufficient for an autopsy diagnosis of definite AD. These 3 individuals were not considered to have AD in the analyses that follows.

Neuropsychological Measures

All subjects were administered a neuropsychological battery that consisted of 22 tests yielding 23 test scores. The composition of the entire battery has been previously described.16 In the present analyses, we examined 6 of 23 neuropsychological tests measures. These 6 tests included (1) 2 tests of episodic memory: the total recall score of the first 5 trials of the California Verbal Learning Test (CVLT)33 and the free recall score that follows the first 4 trials of the Selective Reminding Test (SRT)34; (2) 3 executive function tests: the time to complete part B of the Trail Making test (Trails B)35 (part A of the Trail Making test was administered as part of the larger battery), the total score on the Self Ordering test,36 and the total score on the Alpha Span test37; and (3) a language test: the total score on the Controlled Word Association test for letter fluency (ie, F, A, S).38

All neuropsychological measures were standardized to have zero mean and unit variance, averaged over the combined study sample, to facilitate interpretable coefficients in the Cox proportional hazards models and facilitate comparisons of effect sizes across tests. Prior to standardization, the raw time to complete Trails B was log-transformed to reduce skewness. Table 2 outlines the distribution of raw test scores and neuropsychological factors for the 2 groups. Mean scores were consistently higher in the normal than in the MCI group. These differences were statistically significant for 5 of 7 test scores (all but letter fluency and the Alpha Span score).

Table Graphic Jump LocationTable 2. Descriptive Statistics for Neuropsychological Tests in Study Groups
Genetic Assessment

The APOE gene was also examined in the participants because the ε4 allele of this gene is overrepresented in patients with AD compared with the general population39 and is now widely recognized as a risk factor for AD. In addition, APOE ε2 has been associated with decreased risk of AD.40APOE genotypes were determined according to previously described methods.41APOE genotypes are available on all but 5 subjects in the study sample (98.5%); missing genetic information reduced the effective sample sizes to 106 for those normal at baseline and 231 for those with MCI at baseline (Table 1). Allele frequencies for the normal group (APOE ε2 = 0.08, APOE ε3 = 0.79, and APOE ε4 = 0.13) were similar to the frequencies for the MCI group (APOE ε2 = 0.08, APOE ε3 = 0.76, and APOE ε4 = 0.16). The APOE ε4 carrier frequency was somewhat lower in the normal group (24.5% vs 30.7%), but this difference was not statistically significant. There was no difference in the percentage of APOE ε2 carriers (15.6% vs 15.1%).

Statistical Methods

The time-to-progression data were analyzed using a Cox proportional hazards model as implemented in the PHREG procedure in SAS version 8 (SAS Institute, Cary, NC). These models tested whether specific predictors (ie, neuropsychological test scores and factor scores and, secondarily, demographic factors and APOE genotype) affect the time to develop a specific outcome (ie, increased clinical severity). The hazard ratio indicates the change in risk per 1-unit change in the predictor. For instance, if the hazard ratio for age (measured in years) is 1.06, each year older increases risk by 6%, or if the hazard ratio for the California Verbal Learning Test is 0.55, each 1-SD increase in this test score decreases risk by 45%.

The primary focus of the analyses was time from study entry to the end point of interest. For the subjects normal at baseline, the end point was progression to mild impairment (ie, CDR 0.5). For subjects categorized as MCI at baseline, the end point was progression to a diagnosis of AD. Subjects were considered censored at the time that they died, were lost to follow-up, or developed a dementia other than AD. Subjects were not observed between annual visits, so models with interval censoring were considered, but preliminary analyses revealed that they made little difference, consistent with the very gradual onset of the disease.

Two sets of Cox models were completed. The first set was for the normal subjects who progressed to mild impairment, and the second set was for the subjects with mild impairment who progressed to a clinical diagnosis of AD. A total of 3 models were completed for each of the 2 groups: 2 univariate models and 1 multivariable model. The 2 univariate models first included a univariate model for each of the 6 standardized neuropsychological test scores, as well as APOE ε2 and APOE ε4 carrier status, unadjusted or “crude.” A second univariate model for each of the same 6 neuropsychological test scores, as well as APOE ε2 and APOE ε4 carrier status, was adjusted for age, sex, and educational attainment. The multivariable model was designed to be the “best” multivariable Cox model (given the set of variables). To accomplish this, first age, sex, and education were “forced” into the model (ie, these variables were retained even if they were not significant); then each of the 6 neuropsychological test scores and APOE ε2 and APOE ε4 carrier status were entered in the model but were only retained if they were significant at the .05 level. Both age at entry and educational level were controlled for linearly because there was no evidence of a nonmonotonic relationship between these variables and the log hazard of progression or conversion.

As noted earlier, the Cox models included 2 ways of examining the APOE effect on risk of cognitive decline, one pertaining to APOE ε4 and one pertaining to APOE ε2. APOE ε2 was coded as to whether or not the subject was an APOE ε2 carrier. We did not examine APOE ε2 “dose” because there were no ε2ε2 subjects. APOE ε4 was coded as to whether or not the subject was an APOE ε4 carrier and also as the linear effect of dose of APOE ε4 allele (ie, 0 vs 1 vs 2 alleles).

The proportional hazards assumption was evaluated descriptively by checking whether the negative log of survival probabilities associated with higher level of each covariate were constant multiples of those of the lower levels across the entire range of event time. This approach was extended to the multivariate Cox models by examining such patterns across the levels of each linear predictor. Model fit was also examined descriptively by checking the distribution of the martingale residuals as well as deviance residuals.42Figure 1 and Figure 2, depicting predicted survival curves as a function of variation in the neuropsychological tests and factors (shown at the mean and 1 SD above and below the mean), are based on the adjusted univariate models. They include a single neuropsychological test and the following covariates for adjustment purpose: age (fixed at the mean), sex (for women), and education (fixed at the mean).

Place holder to copy figure label and caption
Figure 1.

Survival curves for prediction of time to progression to mild impairment among normal controls (based on the adjusted univariate model [shown at the mean and 1 SD above and below the mean]) as a function of variation in (A) the California Verbal Learning Test (total score from trials 1 through 5) and (B) time to complete Trails B (in seconds).

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Place holder to copy figure label and caption
Figure 2.

Survival curves for prediction of time to progression to a diagnosis of Alzheimer disease among subjects with mild cognitive impairment (MCI) (based on the adjusted univariate model [shown at the mean and 1 SD above and below the mean]) as a function of variation in (A) the total score on the California Verbal Learning Test (total score from trials 1 through 5), the Selective Reminding Test (free recall) (B), and time to complete Trails B (C) (in seconds).

Graphic Jump Location
RELATIONSHIP OF DEMOGRAPHIC VARIABLES AND CDR-SB TO TIME TO COGNITIVE DECLINE

In univariate Cox models predicting progression in subjects normal at baseline, no demographic variable was statistically significant either alone (crude hazard ratios [HRs]) or adjusted for the remaining demographic factors. Hazard ratios reported in the text are from the adjusted models (Table 3).

Table Graphic Jump LocationTable 3. Analysis of Demographic Factors and Risk of Cognitive Decline

In univariate Cox models predicting progression to a diagnosis of AD in subjects categorized with mild impairment at baseline, age was significant in both crude and adjusted models (HR = 1.06 [1.02-1.11], P = .003). The remaining demographic variables were not significant (Table 3). However, they were included in the adjusted models and forced into the multivariable model to minimize the risk of residual confounding.

RELATIONSHIP OF NEUROPSYCHOLOGICAL VARIABLES TO TIME TO COGNITIVE DECLINE

In the analyses of time to progression among subjects normal at baseline, virtually all of the neuropsychological tests except the Alpha Span were statistically significant in both the crude and adjusted univariate analyses (Table 4). The CVLT total score showed the largest effect per standard deviation across the full sample (HR = 0.55 [0.39-0.79], P = .001). The 2 most significant predictor variables (the CVLT and Trails B) are shown in Figure 1.

Table Graphic Jump LocationTable 4. Univariate Analyses of Neuropsychological Tests and Risk of Cognitive Decline

In the analyses of time to diagnosis of AD among subjects with mild impairment at baseline, all tests but the Alpha Span and Self Ordering test were significant in univariate analyses (Table 4). There were large effects for the CVLT (HR = 0.53 [0.41-0.68], P<.001), the SRT (HR = 0.48 [0.38-0.60], P<.001), and the time to complete Trails B (HR = 1.76 [1.42-2.18], P<.001); these 3 tests are shown in Figure 2.

EFFECT OF APOE ON TIME TO COGNITIVE DECLINE

Table 5 outlines the results of the univariate analyses of the APOE variables on time to cognitive decline. In the analysis of time to progression to mild impairment among subjects normal at baseline, APOE ε2 was protective (HR = 0.13 [0.03-0.56], P = .006) in the adjusted analyses. There was no APOE ε4 effect.

Table Graphic Jump LocationTable 5. Analysis of APOE and Risk of Cognitive Decline

In the analysis of time to a diagnosis of AD, when modeled as binary APOE ε4 carrier status, there was no significant increase in risk in the adjusted model (HR = 1.50 [0.91-2.43], P = .11), but when modeled as APOE ε4 dose, there was a statistically significant effect of each APOE ε4 allele (HR = 1.64 [1.04-2.57], P = .03).

TIME TO COGNITIVE DECLINE USING MULTIVARIABLE MODELS

In the multivariable model of predictors of time to progression to mild impairment among subjects normal at baseline, only CVLT total score (HR = 0.58 [0.41-0.83], P = .003) and APOE ε2 carrier status (HR = 0.14 [0.03-0.57], P = .006) remained in the model (Table 6).

Table Graphic Jump LocationTable 6. Multivariable Model of Demographic Tests, Neuropsychological Tests, and APOE and Risk of Cognitive Decline

In the multivariable model of progression to a diagnosis of AD among those with mild impairments at baseline, SRT free recall score (HR = 0.63 [0.46-87], P = .005) and time to complete Trails B (HR = 1.38 [1.07-1.78], P = .01) remained in the model (Table 6).

Thus, APOE ε4 status did not exhibit an independent effect in the multivariable model, even though it was a predictor of time to diagnosis of AD in the univariate adjusted models. To understand this phenomenon better, we performed linear regressions that included APOE ε4 dose and the neuropsychological tests that were significant in the multivariable model. These regressions exhibited an APOE ε4 dose (modeled as a linear or quadratic term) in the expected direction; that is, there were statistically significant, larger effects for 2 vs 1 ε4 allele for the SRT total score (P = .02) (all P values are from the model with the quadratic term for ε4 dose). We used a quadratic term for APOE ε4 dose, which gives extra weight to those with 2 copies of the ε4 allele (ie, 0 for no ε4 alleles, 1 for 1 copy, and 4 for 2 copies) because a much larger ε4 effect has previously observed in homozygotes.43

EVALUATION OF STATISTICAL MODELS

We assessed the Cox models to determine whether they met assumptions for proportional hazards. No covariates violated the proportional hazards assumption. In addition, the overall fit was good, and none of the models showed extreme residuals.

PREDICTIVE VALUE OF NEUROPSYCHOLOGICAL PERFORMANCE

These findings suggest that, among normal individuals, poorer cognitive performance on specific neuropsychological tests predicts the time to develop mild degrees of impairment. In the current analyses, the risk of progressing from normal to MCI was considerably greater among those with lower scores on tests of episodic memory, ie, the CVLT and the SRT. The importance of episodic memory performance as a predictor of time to progression was reflected in the fact that variables representing this cognitive domain were highly significant in both the univariate and multivariable models.

These results also indicated that performance on an executive function test, the Trail Making test, predicts time to progress from normal to MCI. However, statistical significance was only seen in the univariate, but not the multivariable models, making it less convincing that impairment in this type of task is a marker of likelihood of progression from normal to MCI. It may be possible that more sensitive tests of executive function would serve as better markers of incipient impairment.

The neuropsychological variables that predict time to progression from mild impairment to a clinical diagnosis of AD are quite comparable with those that predict progression from normal to MCI. Once again, it was evident that lower performance on tests of episodic memory confers considerably increased risk of cognitive decline as shown by all the statistical models evaluated. In these analyses, poorer performance on an executive function test, the Trail Making test, was also shown to be a predictor of time to progression from mild impairment to a clinical diagnosis of AD (as shown by both the univariate and multivariable model). Thus, the primary difference between the neuropsychological predictors for time to progression among normal subjects and time to a diagnosis of AD among MCI cases was the strength of the finding regarding the Trail Making test. These analyses were repeated using factor scores that represented the domains of episodic memory, executive function, spatial skill, and general knowledge. The findings with respect to the episodic memory factor and the executive function factor confirm the results of the individual test scores presented here (data not shown).

We hypothesize that the episodic memory tasks that were particularly useful for prediction of course in the present study (ie, the CVLT and the SRT) were predictive because not only are they difficult verbal memory tests, but they have the added feature that they can be performed more effectively if the subject takes advantage of organizational cues inherent in the task itself, thus using both episodic memory and executive function skills. The executive function test that was particularly useful for prediction, Trails B, requires the individual to switch back and forth from one well-learned series to another (ie, numbers and letters). This requires the individual to inhibit the tendency to complete the series in order, thus making switching between these 2 mental sets particularly challenging.

Taken together, these findings are consistent with the recent revision of the MCI criteria29 and a recent meta-analysis18 indicating that individuals with MCI can have impairments in cognitive domains above and beyond that of memory. Although we did not conduct analyses that specifically address the order in which cognitive impairments emerge during the evolution of AD, these results suggest that during prodromal AD, most individuals first develop difficulty with episodic memory followed by impairments in executive function. These findings indicate that subtle cognitive changes, particularly in the area of episodic memory, are in fact occurring among normal individuals destined to develop mild impairments, even though such changes were not reported during the annual clinical interview by either the subject or informant.

These results are consistent with the known neurobiology of AD. Synaptic dysfunction, neuronal loss, and AD pathology first occurs in medial temporal lobe regions critical for normal memory (eg, the entorhinal cortex and hippocampus).44,45 They are also consistent with previous reports of an association between degree of AD pathology in cognitively normal individuals and performance on tests of episodic memory.46,47 The brain abnormalities responsible for the executive function deficits seen among individuals destined to develop AD are less clear. At least 2 potential neurobiological explanations have been suggested. Findings from functional imaging indicate that during prodromal AD, there is dysfunction within a brain network that involves the dorsolateral prefrontal cortex and the anterior cingulate.48 Alterations in these brain regions have been associated with impairments in executive function.49 An alternative possibility is that the disruption of the corticocortical connections that are seen in AD50 may be responsible for executive dysfunction during prodromal AD.

Our findings agree with 2 previous reports concerning normal subjects who received detailed neuropathological examinations.46,47 Some of the normal individuals were found to have AD pathology on autopsy, and the investigators reported that episodic memory performance differed between subjects with and without pathological findings. Our results differ, however, from another study that also performed autopsies on a small number of normal subjects who had been carefully examined during life. These investigators51 reported that there was no decline in cognitive performance for normal individuals with pathology (n = 3) on autopsy as compared with those lacking pathological findings (n = 5), based on either individual test scores or a factor score derived from the test battery as a whole. The explanation for this discrepancy may relate to the impact of the small sample size (making it difficult to identify differences between groups) as well as the individual tests examined and the fact that neuropsychological testing was administered annually. Although the investigators administered 2 tests of episodic memory, only one (the paired associate test from the Wechsler Memory Scale) examined delayed recall; moreover, a substantial proportion of the paired associates were considered “easy.” Thus, the memory tests may have been insufficiently sensitive to subtle early changes in cognition. In addition, it is likely that annual administration of the tests produced a practice effect that made it difficult to observe subtle changes in performance.52

ROLE OF APOE IN PREDICTION OF TIME TO COGNITIVE DECLINE

In the present analyses, the role of APOE status in prediction of cognitive decline varied depending on whether an individual was normal or had already developed mild impairments in daily life. Normal individuals who carried one or more copy of the APOE ε2 allele were less likely to develop cognitive impairments over time than individuals with no copies of the ε2 allele. This protective effect of APOE ε2 has been previously reported.53 The fact that APOE ε2 status was significant in both the multivariable and univariate models indicates that its impact on risk for cognitive decline is not fully accounted for by its influence on memory performance and suggests the possibility that the benefit of ε2 carrier status might be greatest at the very earliest stages of disease.

Among individuals with mild impairments, the APOE ε4 allele increased risk for AD in a dose-dependent manner. The linear regression models showed that presence of an APOE ε4 allele was associated with lower memory performance, as our group and others have previously reported.53APOE ε4 carrier status was not, however, significant in the multivariable models, suggesting that its influence on cognition is largely accounted for by memory test scores.

STUDY LIMITATIONS

The study must be interpreted in light of its limitations. The subjects are well educated and primarily white, so the results may not generalize to the US population at large. We must also acknowledge that differences in the sample size between the controls and the MCI subjects may have had an impact on the findings. We compared the hazard ratios and confidence intervals for the tests that were significant predictors for the MCI cases who progressed but not for the normal controls and did not see patterns suggesting that limitations in power were responsible for the results. Nevertheless, there is the possibility that larger sample sizes might show additional relationships not found here. In addition, the results may depend on the specific neuropsychological tests involved. While many of the individual tests were significant in the univariate models, only selected ones remained significant in the multivariable model, suggesting that the specific tests identified here may be particularly useful in capturing cognitive impairments predictive of progression.

These findings indicate that neuropsychological testing may be useful in identifying normal individuals who are likely to progress to mild impairment. One potential application of these findings relates to the design of primary intervention trials seeking to delay the onset of memory problems among individuals who are normal. It might be possible to use the type of episodic memory tests shown to be sensitive in the current analyses to select individuals at high risk for progression, thus increasing the power of such studies to show an effect of the intervention.

Correspondence: Marilyn Albert, PhD, 1620 McElderry St, Reed Hall East 2, Baltimore, MD 21205 (malbert9@jhmi.edu)

Accepted for Publication: November 3, 2006.

Author Contributions: Study concept and design: Blacker, Tanzi, Moss, and Albert. Acquisition of data: Blacker, Tanzi, and Albert. Analysis and interpretation of data: Blacker, Lee, Muzikansky, Martin, McArdle, and Albert. Drafting of the manuscript: Blacker, Martin, and Albert. Critical revision of the manuscript for important intellectual content: Blacker, Lee, Muzikansky, Tanzi, McArdle, Moss, and Albert. Statistical analysis: Blacker, Lee, Muzikansky, Martin, and McArdle. Obtained funding: Albert. Administrative, technical, and material support: Blacker, Tanzi, Moss, and Albert. Study supervision: Blacker and Albert.

Financial Disclosure: None reported.

Funding/Support: The study was supported by grants P01 AG04953 and P50 AG05146 from the National Institute on Aging.

Acknowledgment: We thank Drs Li-Jen Wei, Lu Tian, Larry Leon, and Rebecca Betensky for contributions to the biostatistical methods; Jeanette Gunther and numerous research assistants for careful attention to our subjects and their data; Dr Mary Hyde for invaluable assistance with data management; and our participants for their generous ongoing involvement in the study.

Hulette  CWelsh-Bohmer  KMurray  MSaunders  AMash  DMcIntyre  L Neuropathological and neuropsychological changes in “normal” aging: evidence for preclinical Alzheimer disease in cognitively normal individuals. J Neuropathol Exp Neurol 1998;571168- 1174
PubMed Link to Article
Knopman  DParisi  JSalvati  A  et al.  Neuropathology of cognitively normal elderly. J Neuropathol Exp Neurol 2003;621087- 1095
PubMed
Bennett  DSchneider  JBienias  J  et al.  Mild cognitive impairment is related to Alzheimer pathology and cerebral infarctions. Neurology 2005;64834- 841
PubMed Link to Article
Petersen  RSmith  GWaring  SIvnik  RTangalos  EKokmen  E Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 1999;56303- 308
PubMed Link to Article
Tuokko  HVernon-Wilkinson  JWeir  JBeattie  W Cued recall and early identification of dementia. J Clin Exp Neuropsychol 1991;13871- 879
PubMed Link to Article
Bondi  MMonsch  AGalasko  DButters  NSalmon  DDelis  D Preclinical cognitive markers of dementia of the Alzheimer type. Neuropsychology 1994;8374- 384
Link to Article
Petersen  RSmith  GIvnik  RKokmen  ETangalos  E Memory function in very early Alzheimer's disease. Neurology 1994;44867- 872
PubMed Link to Article
Newman  SWarrington  EKennedy  ARossor  M The earliest cognitive change in a person with familial Alzheimer's disease: presymptomatic neuropsychological features in a pedigree with familial Alzheimer's disease confirmed at necropsy. J Neurol Neurosurg Psychiatry 1994;57967- 972
PubMed Link to Article
Small  GLaRue  AKomo  SKaplan  AMandelkern  M Predictors of cognitive change in middle-aged and older adults with memory loss. Am J Psychiatry 1995;1521757- 1764
PubMed
Jacobs  DSano  MDooneief  GMarder  KBell  KStern  Y Neuropsychological detection and characterization of preclinical Alzheimer's disease. Neurology 1995;45957- 962
PubMed Link to Article
Tierney  MSzalai  JSnow  W  et al.  Prediction of probable Alzheimer's disease in memory-impaired patients: a prospective longitudinal study. Neurology 1996;46661- 665
PubMed Link to Article
Howieson  DDame  ACamicioli  RSexton  GPayami  HKaye  J Cognitive markers preceding Alzheimer's dementia in the healthy oldest old. J Am Geriatr Soc 1997;44584- 589
Rubin  EStorandt  MMiller  JP  et al.  A prospective study of cognitive function and onset of dementia in cognitively healthy elders. Arch Neurol 1998;55395- 401
PubMed Link to Article
Kluger  AFerris  SGolomb  JMittelman  MReisberg  B Neuropsychological performance of decline in dementia in non-demented elderly. J Geriatr Psychiatry Neurol 1999;12168- 179
PubMed Link to Article
Chen  PRatcliff  GBelle  SCauley  JDeKosky  SGanguli  M Cognitive tests that best discriminate between presymptomatic AD and those who remain nondemented. Neurology 2000;551847- 1853
PubMed Link to Article
Albert  MMoss  MTanzi  RJones  K Preclinical predictions of AD using neuropsychological tests. J Int Neuropsychol Soc 2001;7631- 639
PubMed Link to Article
Bennett  DWilson  RSchneider  J  et al.  Natural history of mild cognitive impairment in older persons. Neurology 2002;59198- 205
PubMed Link to Article
Backman  LJones  SBerger  ALaukka  ESmall  B Cognitive impairment in preclinical Alzheimer's disease: a meta-analysis. Neuropsychology 2005;19520- 531
PubMed Link to Article
McArdle  JSmall  BBackman  LFratiglioni  L Longitudinal models of growth and survival applied to the early detection of Alzheimer's disease. J Geriatr Psychiatry Neurol 2005;18234- 241
PubMed Link to Article
Chen  PRatcliff  GBelle  SCauley  JDeKosky  SGanguli  M Patterns of cognitive decline in presymptomatic Alzheimer disease: a prospective community study. Arch Gen Psychiatry 2001;58853- 858
PubMed Link to Article
Masur  DSliwinski  MLipton  RBlau  ACrystal  H Neuropsychological prediction of dementia in the absence of dementia in healthy older persons. Neurology 1994;441427- 1432
PubMed Link to Article
Hughes  CPBerg  LDanziger  WLCoben  LAMartin  RL A new clinical scale for the staging of dementia. Br J Psychiatry 1982;140566- 572
PubMed Link to Article
Morris  JC The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993;432412- 2414
PubMed Link to Article
Blessed  GTomlinson  BRoth  M The association between quantitative measures of dementia and of senile change in cerebral grey matter of elderly subjects. Br J Psychiatry 1968;114797- 811
PubMed Link to Article
Daly  EZaitchik  DCopeland  MSchmahmann  JGunther  JAlbert  M Predicting ‘conversion’ to AD using standardized clinical information. Arch Neurol 2000;57675- 680
PubMed Link to Article
Folstein  MFolstein  SMcHugh  P “Mini-Mental State”: practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12189- 198
PubMed Link to Article
Davis  HRockwood  K Conceptualization of mild cognitive impairment: a review. Int J Geriatr Psychiatry 2004;19313- 319
PubMed Link to Article
Petersen  RThomas  RGrundman  M  et al.  Vitamin E and donepezil for the treatment of mild cognitive impairment. N Engl J Med 2005;3522379- 2388
PubMed Link to Article
Petersen  R Mild cognitive impairment. J Intern Med 2004;256183- 194
PubMed Link to Article
McKhann  GDrachman  DFolstein  MFKatzman  RPrice  DStadlan  E Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services Task Force. Neurology 1984;34939- 944
PubMed Link to Article
McKhann  GAlbert  MGrossman  MMiller  BDickson  DTrojanowski  J Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick's Disease. Arch Neurol 2001;581803- 1809
PubMed Link to Article
Roman  GCTatemichi  TKErkinjuntti  T  et al.  Vascular dementia: diagnostic criteria for research studies: report of the NINDS-AIREN International Workshop. Neurology 1993;43250- 260
PubMed Link to Article
Delis  DKramer  JKaplan  EOber  B The California Verbal Learning Test.  New York, NY: Psychological Corp; 1987
Grober  EBuschke  H Genuine memory deficits in dementia. Dev Neuropsychol 1987;313- 36
Link to Article
Reitan  RM Validity of the Trail Making Test as an indicator of organic brain damage. Percept Mot Skills 1958;8271- 276
Link to Article
Petrides  MMilner  B Deficits in subject-ordered tasks after frontal and temporal lobe lesions in man. Neuropsychologia 1982;20249- 262
PubMed Link to Article
Craik  FIM A functional account of age differences in memory.  In: Klix  F, Hagendorf  H, eds. Human Memory and Cognitive Capabilities. New York, NY: Elsevier Press; 1986:409-422
Benton  ALHamsher  K Multilingual Aphasia Examination.  Iowa City: University of Iowa Press; 1976
Saunders  AMStrittmatter  WJSchmechel  D  et al.  Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer's disease. Neurology 1993;431467- 1472
PubMed Link to Article
Corder  ESaunders  EWilson  P  et al.  Protective effect of apolipoprotein E type 2 allele for late onset Alzheimer's disease. Nat Genet 1994;7180- 184
PubMed Link to Article
Hixson  JVernier  D Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res 1990;31545- 548
PubMed
Lin  DYWei  LJYing  Z Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika 1993;80557- 572
Link to Article
Farrer  LACupples  LAHaines  JL  et al.  Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease: a meta-analysis. JAMA 1997;2781349- 1356
PubMed Link to Article
Hyman  BTVanHoesen  GDamasio  ABarnes  C Alzheimer's disease: cell specific pathology isolates the hippocampal formation. Science 1984;2251168- 1170
PubMed Link to Article
Selkoe  D Defining molecular targets to prevent Alzheimer's disease. Arch Neurol 2005;62192- 195
PubMed Link to Article
Schmitt  FDavis  DWekstein  DSmith  CAshford  JMarkesbery  W “Preclinical” AD revisited: neuropathology of cognitively normal older adults. Neurology 2000;55370- 376
PubMed Link to Article
Bennett  DSchneider  JArvanitakis  Z  et al.  Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology 2006;661837- 1844
PubMed Link to Article
Milham  MPErickson  KBanich  MT  et al.  Attentional control in the aging brain: insights from an fMRI study of the Stroop task. Brain Cogn 2002;49277- 296
PubMed Link to Article
Bush  GVogt  BAHolmes  J  et al.  Dorsal anterior cingulate cortex: a role in reward-based decision making. Proc Natl Acad Sci U S A 2002;99523- 528
PubMed Link to Article
Morrison  JHof  P Selective vulnerability of corticocortical and hippocampal circuits in aging and Alzheimer's disease. Prog Brain Res 2002;136467- 486
PubMed
Goldman  WPrice  JStorandt  M  et al.  Absence of cognitive impairment or decline in preclinical Alzheimer's disease. Neurology 2001;56361- 367
PubMed Link to Article
Lamar  MResnick  SZonderman  A Longitudinal changes in verbal memory in older adults: distinguishing the effects of age from repeat testing. Neurology 2003;6082- 86
PubMed Link to Article
Wilson  RSBienias  JLBerry-Kravis  EEvans  DABennett  DA The apolipoprotein E epsilon 2 allele and decline in episodic memory. J Neurol Neurosurg Psychiatry 2002;73672- 677
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure 1.

Survival curves for prediction of time to progression to mild impairment among normal controls (based on the adjusted univariate model [shown at the mean and 1 SD above and below the mean]) as a function of variation in (A) the California Verbal Learning Test (total score from trials 1 through 5) and (B) time to complete Trails B (in seconds).

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2.

Survival curves for prediction of time to progression to a diagnosis of Alzheimer disease among subjects with mild cognitive impairment (MCI) (based on the adjusted univariate model [shown at the mean and 1 SD above and below the mean]) as a function of variation in (A) the total score on the California Verbal Learning Test (total score from trials 1 through 5), the Selective Reminding Test (free recall) (B), and time to complete Trails B (C) (in seconds).

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1. Demographic, Clinical, and Genetic Characteristics of Study Groups
Table Graphic Jump LocationTable 2. Descriptive Statistics for Neuropsychological Tests in Study Groups
Table Graphic Jump LocationTable 3. Analysis of Demographic Factors and Risk of Cognitive Decline
Table Graphic Jump LocationTable 4. Univariate Analyses of Neuropsychological Tests and Risk of Cognitive Decline
Table Graphic Jump LocationTable 5. Analysis of APOE and Risk of Cognitive Decline
Table Graphic Jump LocationTable 6. Multivariable Model of Demographic Tests, Neuropsychological Tests, and APOE and Risk of Cognitive Decline

References

Hulette  CWelsh-Bohmer  KMurray  MSaunders  AMash  DMcIntyre  L Neuropathological and neuropsychological changes in “normal” aging: evidence for preclinical Alzheimer disease in cognitively normal individuals. J Neuropathol Exp Neurol 1998;571168- 1174
PubMed Link to Article
Knopman  DParisi  JSalvati  A  et al.  Neuropathology of cognitively normal elderly. J Neuropathol Exp Neurol 2003;621087- 1095
PubMed
Bennett  DSchneider  JBienias  J  et al.  Mild cognitive impairment is related to Alzheimer pathology and cerebral infarctions. Neurology 2005;64834- 841
PubMed Link to Article
Petersen  RSmith  GWaring  SIvnik  RTangalos  EKokmen  E Mild cognitive impairment: clinical characterization and outcome. Arch Neurol 1999;56303- 308
PubMed Link to Article
Tuokko  HVernon-Wilkinson  JWeir  JBeattie  W Cued recall and early identification of dementia. J Clin Exp Neuropsychol 1991;13871- 879
PubMed Link to Article
Bondi  MMonsch  AGalasko  DButters  NSalmon  DDelis  D Preclinical cognitive markers of dementia of the Alzheimer type. Neuropsychology 1994;8374- 384
Link to Article
Petersen  RSmith  GIvnik  RKokmen  ETangalos  E Memory function in very early Alzheimer's disease. Neurology 1994;44867- 872
PubMed Link to Article
Newman  SWarrington  EKennedy  ARossor  M The earliest cognitive change in a person with familial Alzheimer's disease: presymptomatic neuropsychological features in a pedigree with familial Alzheimer's disease confirmed at necropsy. J Neurol Neurosurg Psychiatry 1994;57967- 972
PubMed Link to Article
Small  GLaRue  AKomo  SKaplan  AMandelkern  M Predictors of cognitive change in middle-aged and older adults with memory loss. Am J Psychiatry 1995;1521757- 1764
PubMed
Jacobs  DSano  MDooneief  GMarder  KBell  KStern  Y Neuropsychological detection and characterization of preclinical Alzheimer's disease. Neurology 1995;45957- 962
PubMed Link to Article
Tierney  MSzalai  JSnow  W  et al.  Prediction of probable Alzheimer's disease in memory-impaired patients: a prospective longitudinal study. Neurology 1996;46661- 665
PubMed Link to Article
Howieson  DDame  ACamicioli  RSexton  GPayami  HKaye  J Cognitive markers preceding Alzheimer's dementia in the healthy oldest old. J Am Geriatr Soc 1997;44584- 589
Rubin  EStorandt  MMiller  JP  et al.  A prospective study of cognitive function and onset of dementia in cognitively healthy elders. Arch Neurol 1998;55395- 401
PubMed Link to Article
Kluger  AFerris  SGolomb  JMittelman  MReisberg  B Neuropsychological performance of decline in dementia in non-demented elderly. J Geriatr Psychiatry Neurol 1999;12168- 179
PubMed Link to Article
Chen  PRatcliff  GBelle  SCauley  JDeKosky  SGanguli  M Cognitive tests that best discriminate between presymptomatic AD and those who remain nondemented. Neurology 2000;551847- 1853
PubMed Link to Article
Albert  MMoss  MTanzi  RJones  K Preclinical predictions of AD using neuropsychological tests. J Int Neuropsychol Soc 2001;7631- 639
PubMed Link to Article
Bennett  DWilson  RSchneider  J  et al.  Natural history of mild cognitive impairment in older persons. Neurology 2002;59198- 205
PubMed Link to Article
Backman  LJones  SBerger  ALaukka  ESmall  B Cognitive impairment in preclinical Alzheimer's disease: a meta-analysis. Neuropsychology 2005;19520- 531
PubMed Link to Article
McArdle  JSmall  BBackman  LFratiglioni  L Longitudinal models of growth and survival applied to the early detection of Alzheimer's disease. J Geriatr Psychiatry Neurol 2005;18234- 241
PubMed Link to Article
Chen  PRatcliff  GBelle  SCauley  JDeKosky  SGanguli  M Patterns of cognitive decline in presymptomatic Alzheimer disease: a prospective community study. Arch Gen Psychiatry 2001;58853- 858
PubMed Link to Article
Masur  DSliwinski  MLipton  RBlau  ACrystal  H Neuropsychological prediction of dementia in the absence of dementia in healthy older persons. Neurology 1994;441427- 1432
PubMed Link to Article
Hughes  CPBerg  LDanziger  WLCoben  LAMartin  RL A new clinical scale for the staging of dementia. Br J Psychiatry 1982;140566- 572
PubMed Link to Article
Morris  JC The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993;432412- 2414
PubMed Link to Article
Blessed  GTomlinson  BRoth  M The association between quantitative measures of dementia and of senile change in cerebral grey matter of elderly subjects. Br J Psychiatry 1968;114797- 811
PubMed Link to Article
Daly  EZaitchik  DCopeland  MSchmahmann  JGunther  JAlbert  M Predicting ‘conversion’ to AD using standardized clinical information. Arch Neurol 2000;57675- 680
PubMed Link to Article
Folstein  MFolstein  SMcHugh  P “Mini-Mental State”: practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12189- 198
PubMed Link to Article
Davis  HRockwood  K Conceptualization of mild cognitive impairment: a review. Int J Geriatr Psychiatry 2004;19313- 319
PubMed Link to Article
Petersen  RThomas  RGrundman  M  et al.  Vitamin E and donepezil for the treatment of mild cognitive impairment. N Engl J Med 2005;3522379- 2388
PubMed Link to Article
Petersen  R Mild cognitive impairment. J Intern Med 2004;256183- 194
PubMed Link to Article
McKhann  GDrachman  DFolstein  MFKatzman  RPrice  DStadlan  E Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services Task Force. Neurology 1984;34939- 944
PubMed Link to Article
McKhann  GAlbert  MGrossman  MMiller  BDickson  DTrojanowski  J Clinical and pathological diagnosis of frontotemporal dementia: report of the Work Group on Frontotemporal Dementia and Pick's Disease. Arch Neurol 2001;581803- 1809
PubMed Link to Article
Roman  GCTatemichi  TKErkinjuntti  T  et al.  Vascular dementia: diagnostic criteria for research studies: report of the NINDS-AIREN International Workshop. Neurology 1993;43250- 260
PubMed Link to Article
Delis  DKramer  JKaplan  EOber  B The California Verbal Learning Test.  New York, NY: Psychological Corp; 1987
Grober  EBuschke  H Genuine memory deficits in dementia. Dev Neuropsychol 1987;313- 36
Link to Article
Reitan  RM Validity of the Trail Making Test as an indicator of organic brain damage. Percept Mot Skills 1958;8271- 276
Link to Article
Petrides  MMilner  B Deficits in subject-ordered tasks after frontal and temporal lobe lesions in man. Neuropsychologia 1982;20249- 262
PubMed Link to Article
Craik  FIM A functional account of age differences in memory.  In: Klix  F, Hagendorf  H, eds. Human Memory and Cognitive Capabilities. New York, NY: Elsevier Press; 1986:409-422
Benton  ALHamsher  K Multilingual Aphasia Examination.  Iowa City: University of Iowa Press; 1976
Saunders  AMStrittmatter  WJSchmechel  D  et al.  Association of apolipoprotein E allele epsilon 4 with late-onset familial and sporadic Alzheimer's disease. Neurology 1993;431467- 1472
PubMed Link to Article
Corder  ESaunders  EWilson  P  et al.  Protective effect of apolipoprotein E type 2 allele for late onset Alzheimer's disease. Nat Genet 1994;7180- 184
PubMed Link to Article
Hixson  JVernier  D Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res 1990;31545- 548
PubMed
Lin  DYWei  LJYing  Z Checking the Cox model with cumulative sums of martingale-based residuals. Biometrika 1993;80557- 572
Link to Article
Farrer  LACupples  LAHaines  JL  et al.  Effects of age, sex, and ethnicity on the association between apolipoprotein E genotype and Alzheimer disease: a meta-analysis. JAMA 1997;2781349- 1356
PubMed Link to Article
Hyman  BTVanHoesen  GDamasio  ABarnes  C Alzheimer's disease: cell specific pathology isolates the hippocampal formation. Science 1984;2251168- 1170
PubMed Link to Article
Selkoe  D Defining molecular targets to prevent Alzheimer's disease. Arch Neurol 2005;62192- 195
PubMed Link to Article
Schmitt  FDavis  DWekstein  DSmith  CAshford  JMarkesbery  W “Preclinical” AD revisited: neuropathology of cognitively normal older adults. Neurology 2000;55370- 376
PubMed Link to Article
Bennett  DSchneider  JArvanitakis  Z  et al.  Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology 2006;661837- 1844
PubMed Link to Article
Milham  MPErickson  KBanich  MT  et al.  Attentional control in the aging brain: insights from an fMRI study of the Stroop task. Brain Cogn 2002;49277- 296
PubMed Link to Article
Bush  GVogt  BAHolmes  J  et al.  Dorsal anterior cingulate cortex: a role in reward-based decision making. Proc Natl Acad Sci U S A 2002;99523- 528
PubMed Link to Article
Morrison  JHof  P Selective vulnerability of corticocortical and hippocampal circuits in aging and Alzheimer's disease. Prog Brain Res 2002;136467- 486
PubMed
Goldman  WPrice  JStorandt  M  et al.  Absence of cognitive impairment or decline in preclinical Alzheimer's disease. Neurology 2001;56361- 367
PubMed Link to Article
Lamar  MResnick  SZonderman  A Longitudinal changes in verbal memory in older adults: distinguishing the effects of age from repeat testing. Neurology 2003;6082- 86
PubMed Link to Article
Wilson  RSBienias  JLBerry-Kravis  EEvans  DABennett  DA The apolipoprotein E epsilon 2 allele and decline in episodic memory. J Neurol Neurosurg Psychiatry 2002;73672- 677
PubMed Link to Article

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