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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 56:B294-B301 (2001)
© 2001 The Gerontological Society of America

Predictors of Healthy Brain Aging

Melissa Gonzales McNeala, Sepideh Zareparsib, Richard Camiciolib, Alison Dameb, Diane Howiesonb, Joseph Quinnb,d, Melvyn Ballb,c, Jeffrey Kayeb,d and Haydeh Payamib

a Departments of Molecular and Medical Genetics, Oregon Health Sciences University, Portland
b Departments of Neurology, Oregon Health Sciences University, Portland
c Departments of Pathology, Oregon Health Sciences University, Portland
d Portland Veteran's Affairs Medical Center, Oregon

Haydeh Payami, Department of Neurology, CR131, Oregon Health Sciences University, 3181 S.W. Sam Jackson Park Road, Portland, OR 97201 E-mail: payamih{at}ohsu.edu.

Decision Editor: John Faulkner, PhD


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
To determine if superior health at old age protects against cognitive impairment (CI) and Alzheimer's disease (AD), we prospectively studied 100 optimally healthy oldest-old (>=85 years) individuals. Initially, subjects represented the top 3% of the oldest old for health. During 5.6 ± 0.3 years of follow-up, 34 subjects developed CI, and 23 progressed to AD. By age 100, probability of CI and AD were .65 ± .09 and .49 ± .10. Median onset age was 97 years for CI and 100 for AD. Clearly, superior health at old age does not guarantee protection against cognitive decline. Lifetime risks were similar to the general population but onset ages were later, suggesting factors that delay onset are key to improving cognitive health in the elderly. In this population, absence of apolipoprotein E-{epsilon}4 and male gender were associated with delayed onset, whereas estrogen use and education had no detectable effect on cognitive outcome.

WITH the rapidly growing number of elderly individuals at risk for cognitive impairment (CI), greater emphasis is warranted on finding ways to improve health and quality of life for this population. Longevity, which science has managed to enhance considerably, is not always accompanied by health and independence. Normal cognitive function is essential for maintaining independence. Loss of cognitive function is one of the most prevalent and most feared end-of-life tragedies. The risk of CI rises sharply with increasing ages (1)(2). Alzheimer's disease (AD) alone, one of the most severe forms of CI, affects half of all North Americans over the age of 85 (3)(4)(5)(6). More suffer with mild or moderate CI.

Our growing knowledge of the pathogenesis of dementia has come primarily from studies of AD and related disorders, which typically occur in the seventh to ninth decades of life. What appears to be AD in the tenth decade, however, may not be the same disease as late-onset (60–90 years) AD. The standard clinical diagnosis of AD, by the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer's Disease and Related Disorders Association (NINCDS–ADRDA) criteria (7), excludes those individuals whose onset is at >=90 years of age. Consequently, little is known about the cause of CI at higher ages, or the factors that modulate its onset and severity.

The oldest-old (age >=85 years) group is the fastest growing segment of the population (8) and has the highest risk for dementia. It is not known if dementia in the oldest old is a disease affecting only those who are susceptible or a condition that is an inevitable consequence of aging. Recent meta-analyses have shown that the incidence of dementia rises with age and does not level off (1)(2), which suggests that we may all become impaired if we live long enough. In contrast, another large study concluded that only half of the elderly population develops AD, whereas the other half is immune (9). There were important differences in the study designs and definitions of impairment, making it difficult to draw parallel comparisons. Whether we are all at risk, or a subset is innately immune, remains an issue of controversy.

Assuming that some people are "immune" to CI, we set out to identify and study individuals who seemed least likely to be at risk, hoping that they would hold the key to prevention. In 1989, we launched the Oregon Brain Aging Study (OBAS), a prospective study of the effect of aging on the central nervous system. The two primary goals were to define healthy brain aging and to identify factors associated with protection against age-related neurodegenerative disorders. To that effect, we enrolled the healthiest of the oldest individuals in the community and followed them with frequent and detailed examinations until death (10)(11). Representing the top 1–3% of the elderly for cognitive and physical health, individuals who entered this study exemplified successful aging. We have followed them for up to 11 years (mean 5.6 years).

Although clinically and pathologically indistinguishable, it is not known if what appears to be AD in the oldest-old group is the same disease as late-onset AD or a different condition. The major risk factors for late-onset AD are increasing age (1)(2), allele {epsilon}4 of the apolipoprotein E (APOE) gene (12)(13), and female gender (2)(13)(14). We questioned if these factors exert a similar effect on cognitive health throughout the most advanced ages. Here we report the cognitive and neuropathological outcomes, estimate risk, and assess the effects of age, APOE genotype, and gender on the cognitive well being of "successful agers."


   Methods
Top
 Abstract
 Methods
Results
 Discussion
 References
 
At entry to the OBAS, subjects were community dwelling, functionally independent, healthy individuals who met the strict inclusion and exclusion criteria listed in Table 1 . They were cognitively healthy and free of any condition that could affect cognition (e.g., no stroke, heart disease, hypertension, cancer, or diabetes).


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  		Table 1. Subject Selection Criteria

 
Ascertainment
Two methods were used to identify and recruit subjects. The first method was the use of community volunteers. The majority of subjects were recruited from the community by advertisement (print and electronic media) and direct appeals during presentations to local senior citizens groups, seeking elderly volunteers who considered themselves cognitively and physically healthy. Through this method, 1207 individuals entered the initial screening process. The screening process included a telephone interview followed by a review of medical records to assess inclusion and exclusion criteria. Of the 1207 volunteers, 1008 were excluded at the screening stage. The remaining 199 were seen at the medical center or visited at home to obtain vital signs, perform visual and hearing screenings, and administer the Mini-Mental State Examination (MMSE) (15), Cornell Depression Scale (16), Geriatric Depression Scale (17), and Clinical Dementia Rating (CDR) Scale (18). If all assessments were normal, subjects were seen at the medical center for a completeC physical and neurological evaluation and laboratory studies as outlined in Table 2 (10). Thirty-six subjects were excluded at this exam. The 163 subjects still meeting all eligibility criteria were asked to return for a neuropsychological evaluation (11) and a magnetic resonance imaging (MRI) examination. Seven subjects were excluded based on the neuropsychological evaluation or MRI results. The 156 subjects who met all eligibility criteria were enrolled in the OBAS.


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  		Table 2. Assessments Performed at Entry and Annual Follow-Up*

 
The second method used health care organizations. A database search, approved by the Institutional Review Board of Kaiser Permanante in Portland, identified 4494 health maintenance organization (HMO) members as being >=85 years old. A computer survey of their medication records identified 3669 of the 4494 as being on exclusionary medications. Full medical record reviews for the remaining 825 members excluded an additional 698 individuals. The 127 potentially eligible individuals were invited to participate in the study. Ninety-four (74%) declined interview, 12 were found ineligible at interview, and 21 underwent physical, neurological, neuropsychiatric and MRI evaluations as described above. Fourteen subjects were eligible and enrolled in the OBAS. Given that 4494 oldest old were surveyed, 127 were potentially eligible, and 74% refused participation, we estimated that the 14 who were enrolled represented the top 1–3% of the oldest old for health. Similar computerized surveys were performed in 1997 and 1998 at the Family Practice Clinic and the Internal Medicine Clinic of Oregon Health Sciences University (OHSU). A total of 289 individuals aged >=85 years were identified. After the survey for exclusionary medications and a review of medical records, 25 subjects were potentially eligible and invited to participate in the study. Sixteen individuals (64%) did not respond or refused to participate, five were found ineligible, the remaining four underwent the full battery of examinations, met all entry criteria, and were enrolled.

There was no significant difference between the community volunteers and those ascertained from health care organizations with regard to baseline MMSE, gender ratio, or education level. The two groups, therefore, were pooled. One hundred, seventy-four subjects have been enrolled in the OBAS. For the present study, we used only those who met all entry criteria at age >=85 years (N = 100). Two were Hispanic (both female), one was Native American (female), and 97 were Caucasian (60 females, 37 males). All subjects signed informed consents approved by the OHSU Institutional Review Board. Separate consent forms were obtained for longitudinal clinical studies, genetic studies, and brain autopsy.

Genotyping
Subjects were asked to donate blood samples for extraction and storage of DNA, genetic studies, and establishment of immortalized cell lines. DNA was extracted by the salting out method, using the commercial kit PureGene (Gentra Systems Inc., Minneapolis, MN). APOE genotypes were determined by using a standard method (19).

Follow-Up Assessments
Once enrolled, subjects received a home visit every 6 months for a medical history review, and for Older Americans Resource Scale (20), MMSE, and CDR assessments. In addition, every year the subjects underwent full physical, neurological, neuropsychological, and MRI examinations. The biannual assessments and annual examinations continued until death. Upon death, with prior consent, brain autopsies for neuropathological analysis were performed (21). New medical conditions (e.g., stroke, heart disease, hypertension, and cancer) were diagnosed either by the personal physician, which we verified by reviewing the medical records, or by us at the annual examinations.

Definitions of CI and AD
We defined CI as repeated abnormal scores on MMSE or CDR on consecutive assessments without reversion to the normal range. CI as defined here is an irreversible phenotype. All subjects entered the study cognitively intact with MMSE >= 24 and CDR = 0. Subjects who maintained MMSE >= 24 and CDR = 0 on all follow-up assessments up to the time of this analysis were considered cognitively intact. Subjects who scored MMSE < 24 or CDR >= 0.5 on repeated assessments were categorized with CI. Subjects who received one abnormal score (MMSE < 24 or CDR >= 0.5) but recovered to the normal range on subsequent visits were classified as cognitively intact. Subjects who either had one abnormal score immediately prior to this analysis (pending follow-up) or died before their next assessment and had no autopsy were classified as indeterminate. AD was diagnosed clinically by using the NINCDS–ADRDA criteria (7), and pathologically by the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) criteria (22).

Age at onset was defined as the age when the subject first scored MMSE < 24 or CDR >= 0.5. Age at onset was assigned only to individuals who met the criteria for CI; that is, those who received abnormal scores on consecutive assessments and did not revert. The same definition (age at the first of consecutive abnormal scores) was used for those who progressed to AD.

Statistics
Standard statistical methods were used to calculate means ± standard error (SE). Differences in means (for age, MMSE scores, and years of education) were tested by using t tests. Age-specific cumulative incidence rates were estimated by using actuarial and Kaplan Meier survival analyses. Because risk was thought to be a function of age rather than years of follow-up, age was specified for time in all survival models. For subjects who developed CI or AD, age at onset was specified as the time of event. For subjects who remained cognitively intact, current age or age at death was used. Subjects with indeterminate cognitive status were censored at the last age when they were known to be cognitively intact. Age at onset distributions were plotted by the Kaplan Meier survival analysis method (23) and were compared by log-rank statistics. Proportions (differences in allele frequencies, and gender ratios) were tested by using Z statistics. Hazard ratio (HR) was calculated by using the Cox proportional hazards model with 95% confidence intervals (24). Correlation (years of education with onset age) was tested by using Pearson's correlation coefficient (r) method. SPSS software (release 10.0.5; 27 November 1999; SPSS Inc; Chicago, IL) was used for statistical analyses.


   Results
Top
 Abstract
 Methods
 Results
Discussion
 References
 
We screened 5990 elderly individuals in the Portland, Oregon area and enrolled 174 subjects who met all entry criteria, including 100 oldest-old (age >=85 years) and 74 young-old (65–84 years) individuals. In keeping with the focus on the oldest old, the present study was limited to the 100 subjects who met all entry criteria at age >=85 years. Table 3 lists the characteristics of these subjects.


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  		Table 3. Characteristics of Oldest-Old OBAS Subjects

 
Major Health Outcomes
At entry to study, subjects were free of cognitive impairment, stroke, heart disease, hypertension, cancer, diabetes and neurological disorders. During 5.6 ± 0.3 years of follow-up, 38% developed hypertension, 37% developed CI, 33% developed heart disease (arrhythmia, myocardial infarction), 30% developed cancer (all cancers combined), 23% developed AD, 23% had a stroke or transient ischemic attack, 6% developed diabetes, and 2% became blind. These groups are not mutually exclusive.

Cognitive Outcomes
Table 4 outlines the subjects' cognitive outcomes and their classification. At the time of this analysis, 58 of 100 subjects were classified as cognitively intact. They included 54 subjects who had normal scores (CDR = 0 and MMSE >= 24) at all follow-up assessments, and four who had one or two abnormal scores but reverted and maintained normal scores at all subsequent assessments. Thirty-four of the 100 subjects were classified with CI. Eight subjects were classified as indeterminate because they had been fluctuating between the normal and the abnormal range (n = 3), or had their first abnormal score at their last visit and were awaiting follow-up (n = 3), or died after their first abnormal score without follow-up or autopsy (n = 2).


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  		Table 4. Clinical Outcomes and Classification

 
Among the 34 subjects classified with CI, 19 had the clinical diagnosis of possible or probable AD; one was diagnosed as possible vascular dementia and one as mixed dementia. The remaining 13 were CI with questionable or incipient dementia. In addition, of the 13 subjects classified with CI, four did not meet the clinical criteria for AD but were diagnosed with definite AD at autopsy. If AD is defined as meeting clinical or neuropathological diagnosis of AD, there were 23 cases.

Neuropathological data were reviewed to confirm the clinical findings. Twenty-seven subjects had died; 20 had brain autopsy. Mean age at death was 95.6 ± 0.8 years. Of the 20 subjects with brain autopsy, only one had no AD pathology. All other 19 brains had Alzheimer's pathology to varying degrees (25). Table 5 shows the neuropathological findings with their corresponding clinical phenotypes. Details of neuropathological findings are reported elsewhere (21).


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  		Table 5. Clinical Phenotypes of the Autopsied Cases (n = 20) and Their Corresponding Neuropathological Diagnoses

 
Incidence of CI and AD: Age, Genotype, and Gender
The cumulative probabilities of CI and AD rose with increasing ages of the subjects (Table 6 ). The probability that a subject would live to age 95 was .84 ± .05. The probability that a subject would live to age 95 cognitively intact was .59 ± .06. The median age at onset, estimated by the Kaplan Meier analysis, was 97.2 ± 2.0 years for CI and 99.8 ± 1.7 years for AD.


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  		Table 6. Age-Specific Cumulative Probability of Survival Outcomes

 
At baseline (Table 3 ), the APOE genotype and allele frequencies were similar to other published frequencies for this age group (26). The incident cases of CI had a higher frequency of {epsilon}4 (0.13 versus 0.07) and a lower frequency of {epsilon}2 (0.04 versus 0.11) than those who remained intact. When it was analyzed with the Cox method and when age was taken into account, the effect of {epsilon}4 on the risk of CI was significant (HR = 2.5, p = .03). Similarly, the age at onset distribution for CI, shown by Kaplan Meier curves (Fig. 1), was significantly earlier for {epsilon}4 carriers (p = .03). Cox and Kaplan Meier analyses for {epsilon}2 showed statistically insignificant trends, suggesting reduced risk and delayed onset of CI in the presence of {epsilon}2. Similar trends were seen for AD (Table 7 and Fig. 1), although none reached statistical significance possibly as a result of the smaller numbers of AD.



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  		Figure 1. Age at onset distributions, determined by Kaplan Meier survival analysis. A, {epsilon}4 vs no {epsilon}4 (—, {epsilon}4 heterozygotes or homozygotes; ---, no {epsilon}4 allele). B, {epsilon}2 vs no {epsilon}2 (—, {epsilon}2 heterozygotes or homozygotes; ---, no {epsilon}2 allele). C, Women vs men (—, women; ---, men). AD = Alzheimer's disease; CI = cognitive impairment.

 

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  		Table 7. Hazard Ratios for Gender and APOE

 
The study included 37 men and 63 women, which reflects the gender distribution after age 85 in the United States (27). As shown in Table 3 , 41% of women developed CI as compared with 22% of men. Women had a significantly higher age-specific risk of developing CI than men (HR = 3.0; p = .01; Table 7 ). Women also had significantly earlier age at onset than men (p = .007; see Kaplan Meier curves in Fig. 1). Similar trends were seen for AD but they were not significant (Table 7 and Fig. 1), possibly because sample size and power were smaller for AD than CI.

We wondered if the gender difference in risk was linked to age and longer survival in women, differences in baseline MMSE scores, estrogen use in women, or higher education in men. Men and women were similar in age. At entry, the mean ages were 87.6 ± 0.7 for men and 87.4 ± 0.5 for women. Currently, men are 93.4 ± 0.7 and women are 92.9 ± 0.5 years old. Identical proportions (76%) of men and women lived to age 90 or higher. Thirty-five percent of men and 27% of women lived to age 95 or higher. There was no evidence for increased life span in women, measured either by the Cox method (HR = 1.0; p = .9) or by the Kaplan Meier and log-rank statistics (p = .9). There was no significant difference in the baseline mean MMSE scores between men and women (28.0 ± 0.3 vs 27.9 ± 0.2; p = .7). Twenty-three women reported having used estrogen; 40 reported they had never used estrogen. A comparison of ever users versus never users showed no difference in the risk or the age at onset distribution for CI (p = .9) or AD (p = .9). Education level was marginally higher for men than for women (15.0 ± 0.5 vs 14.0 ± 0.3 years; p = .08), but there was no correlation between years of education and age at onset of CI (r = .07; p = .5).


   Discussion
Top
 Abstract
 Methods
 Results
 Discussion
References
 
We have described a population of elderly individuals who at age 85 represented the healthiest of the oldest old, exemplifying successful aging. They were highly selected at entry to represent those who at the time were thought to be least likely to develop CI. Yet, they proceeded to develop CI and AD at a high rate. The incidence of CI and AD was not lower in this group than others (2)(9), but the age at onset was considerably later. These data suggest that for cognitive health of the oldest old to be improved, emphasis should be placed on finding factors that modify age at onset of CI.

Subjects who did not become affected were younger than those who developed CI, which begs the question: If they live long enough, will they all become affected? Similarly, subjects who had CI but did not develop AD were younger than those who progressed to AD, which raises another question: Given enough time, will all the cognitively impaired elderly individuals progress to AD? We will continue to learn more as the subjects are followed longer and reach higher ages. Seventy-three of the oldest-old subjects are still living and being followed. Brain autopsy is critical because neuropathology may ultimately distinguish, or unify, age-related CI and AD.

A limitation of this study was sample size. Despite an extensive search since 1989, we identified only 100 individuals in the Portland Metropolitan area who were aged 85 years or older, met the OBAS criteria for health, and were willing to participate in a lifelong study that entailed biannual assessments and detailed annual examinations. Larger studies are needed to examine the present findings in more detail and to search for protective factors. Given the scarcity of optimally healthy elderly individuals, such studies will be possible only through multicenter collaborations. Another caveat relates to the assessment instruments. We chose MMSE and CDR because they are used widely in research, but they are not precise and on occasion may miss mild impairment. Repeated testing and the "practice effect" may also lead to artificially high scores and misclassification of mildly impaired individuals as unaffected. If these confounders existed in our data, the true incidence of CI may be higher than the estimates reported here.

It is not known if age-related cognitive impairment leading to what appears to be AD in the oldest-old population is the same as the classical late-onset AD or a different pathophysiological process. The major risk factors for late-onset AD, that is, age, APOE genotype, and gender, had a similar effect upon CI and AD in this population of oldest old. The {epsilon}4 allele had a significant effect on risk and age onset of cognitive impairment in this group of elderly individuals, but not on AD. The lack of a significant effect on AD may be partly due to smaller numbers of AD cases, and partly due to a weakening effect of {epsilon}4 on cognitive decline at higher ages (28). In a subset of subjects that were used in a previous study (29), we witnessed a reduction in the effect of {epsilon}4 with longer follow-up and increasing ages. Over a 3.3-year period, the relative risk of AD as a function of {epsilon}4 dropped from 19.9 (p = .01) to 1.9 (p = .3).

Some studies suggest that the {epsilon}2 allele protects against late-onset AD (28)(30)(31), although the association of {epsilon}2 with AD is not well established (32). We observed a nonsignificant trend that was consistent with reduced risk and later onset in {epsilon}2 carriers. The protective effect of {epsilon}2 is difficult to assess because {epsilon}2 is the rarest of the three APOE alleles, and to have sufficient power, a sample size four times larger than the present study would be needed.

We detected a significant gender effect, which could not be explained by differences in age, survival, baseline MMSE scores, or estrogen use. Men had on average 1 more year of education than women. It is difficult to tell if only 1 added year of education can result in a significant improvement in cognitive health as seen here. There was no correlation between years of education and age at onset of CI. Furthermore, the 1-year difference between men and women was statistically insignificant. Thus, it is unlikely that the gender difference in cognitive outcome was solely due to education. Further studies are needed to determine if the results reflect a biological sex difference in the pathogenesis of CI, or a social or environmental gender difference that gives men an advantage. Several lines of evidence suggest that sex is a factor in the pathogenesis of CI and AD. Epidemiological studies including two large meta-analyses of incidence of AD suggest that, age for age, women have a higher risk than men do (1)(2). Genetic studies have shown in familial late-onset AD, age at onset is earlier in women (33). Furthermore, the APOE-associated risk for AD is sex specific, suggesting a gene–gender interaction in the etiology of AD (13)(34).

An alternative explanation for the gender effect seen here is related to natural selection. In midlife, the selection pressure is higher on men than women. Men are generally more vulnerable to disease and mortality than women (35)(36). This differential selection is reflected in the skewed sex ratio at extreme ages. Starting at approximately equal numbers at birth, by age 85 years, women outnumber men two to one (27). It is therefore possible that having gone through more stringent natural selection, men who reach extreme ages in optimal health have a stronger constitution overall than their age-matched female counterparts, and represent those most resistant to disease and mortality.

For research to promote cognitive health in the elderly population, it is important to find the explanation to the putative male advantage. From a public health point of view, the results are alarming. Whatever the cause may be—a sex difference in disease pathogenesis, stronger selection on men, or social differences—women over the age of 85 are more likely to experience cognitive loss than men (1)(2)(13)(33)(34)(35)(36)(37). These data predict a major concern for the aging population, because two-thirds of all people over the age of 85 are women.


   Acknowledgments
 
This study was supported by grants from the National Alzheimer Association (RG1-96-042), the National Institute on Aging (AG08017), the National Institutes of Health (PHS 5 MO1 RR00334), and the Department of Veteran's Affairs. We thank the subjects and staff of the Oregon Brain Aging Study.

Received October 8, 2000

Accepted February 7, 2001


   References
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 Methods
 Results
 Discussion
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