Figure 1. Kaplan-Meier curves illustrating the 3-factor interactions among education, normalized whole-brain volume (nWBV), and the cerebrospinal biomarkers of tau and phosphorylated tau (ptau) in subsamples with tau values below (A) and above (B) the median (263.0 pg/mL) and in subsamples with ptau values below (C) and above (D) the median (48.9 pg/mL). CDR indicates Clinical Dementia Rating.
Figure 2. Mean slopes of global Clinical Dementia Rating (CDR) scores for combinations of higher and lower values of the biomarker, education, and normalized whole-brain volume (nWBV) variables for significant mixed-model analyses in subsamples with β-amyloid42 values below (A) and above (B) the median (581.0 pg/mL), in subsamples with tau values below (C) and above (D) the median (263.0 pg/mL), in subsamples with phosphorylated tau values below (E) and above (F) the median (48.9 pg/mL), and in subsamples with tau values below (G) and above (H) the median (263.0 pg/mL).
Roe CM, Fagan AM, Grant EA, Marcus DS, Benzinger TLS, Mintun MA, Holtzman DM, Morris JC. Cerebrospinal Fluid Biomarkers, Education, Brain Volume, and Future Cognition. Arch Neurol. 2011;68(9):1145-1151. doi:10.1001/archneurol.2011.192
Author Affiliations: Knight Alzheimer's Disease Research Center (Drs Roe, Fagan, Grant, Marcus, Benzinger, Mintun, Holtzman, and Morris), Departments of Neurology (Drs Roe, Fagan, Holtzman, and Morris), Radiology (Drs Marcus, Benzinger, and Mintun), Pathology and Immunology (Dr Morris), Physical Therapy (Dr Morris), and Occupational Therapy (Dr Morris), Hope Center for Neurological Disorders (Dr Fagan), and Division of Biostatistics (Dr Grant), Washington University School of Medicine, St Louis, Missouri. Dr Mintun is now with Avid Radiopharmaceuticals, Philadelphia, Pennsylvania.
Background Cross-sectional studies suggest that the cognitive impact of Alzheimer disease pathology varies depending on education and brain size.
Objective To evaluate the combination of cerebrospinal fluid biomarkers of β-amyloid42 (Aβ42), tau, and phosphorylated tau (ptau181) with education and normalized whole-brain volume (nWBV) to predict incident cognitive impairment.
Design Longitudinal cohort study.
Setting Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University, St Louis, Missouri.
Participants A convenience sample of 197 individuals 50 years and older with normal cognition (Clinical Dementia Rating of 0) at baseline observed for a mean of 3.3 years.
Main Outcome Measure Time to Clinical Dementia Rating ≥ 0.5.
Results Three-factor interactions among the baseline biomarker values, education, and nWBV were found for Cox proportional hazards regression models testing tau (P = .02) and ptau (P = .008). In those with lower tau values, nWBV (hazard ratio [HR], 0.54; 95% confidence interval [CI], 0.31-0.91; P = .02), but not education, was related to time to cognitive impairment. For participants with higher tau values, education interacted with nWBV to predict incident impairment (P = .01). For individuals with lower ptau values, there was no effect of education or nWBV. Education interacted with nWBV to predict incident cognitive impairment in those with higher ptau values (P = .02).
Conclusion In individuals with normal cognition and higher levels of cerebrospinal fluid tau and ptau at baseline, time to incident cognitive impairment is moderated by education and brain volume as predicted by the cognitive/brain reserve hypothesis.
Lower educational attainment and smaller brain or head size have been frequently studied as risk factors for Alzheimer disease (AD).1- 4 Educational attainment is a proxy measure of cognitive reserve: the efficient use of brain networks or the ability to recruit alternative brain networks or cognitive strategies.1,5 Brain size is thought to reflect brain reserve: the number and health of neurons.5- 8 Greater amounts of both types of reserve are thought to provide resistance to brain damage caused by AD, delaying the time to cognitive impairment.1,5- 8
Cross-sectional studies suggest that educational attainment4,7,9- 11 and brain size4,6,7 interact with AD abnormalities to determine current cognitive functioning such that the impact of a given amount of AD pathology on cognition varies depending on one's education and brain size. However, until the recent advent of biomarkers of AD pathology, it was impossible to test whether education and brain size modify the association between AD pathology in cognitively normal individuals with the later development of cognitive impairment. The cerebrospinal fluid (CSF) biomarkers of β-amyloid42 (Aβ42), the primary component of amyloid plaques, are decreased in individuals with AD, whereas levels of tau and phosphorylated tau (ptau181), the primary components of neurofibrillary tangles, are increased in AD.12 Abnormal levels of these biomarkers have also been found in cognitively normal individuals and are predictive of later cognitive impairment.13- 15 We tested how the CSF biomarkers of Aβ42, tau, and ptau combine with education and brain volume to predict incident cognitive impairment in individuals with normal cognition at baseline.
Data were collected prospectively from participants enrolled in longitudinal studies at the Charles F. and Joanne Knight Alzheimer’s Disease Research Center, Washington University, St Louis, Missouri. Study protocols were approved by the Washington University Medical Center Human Subjects Committee, and written informed consent was obtained from all the participants. Detailed information on recruitment and assessment procedures are available.16 In brief, participants in these studies are recruited through word of mouth, advertisements, and community events from the greater St Louis area for yearly assessment sessions. Individuals with health conditions, such as metastatic cancer, that may interfere with longitudinal follow-up are excluded from participation.
At the initial and each annual assessment thereafter, participants underwent neurologic and physical examinations and were accompanied by a collateral source who knows the participant well. Experienced clinicians obtain health and medication histories and conduct semistructured interviews with the participant and collateral source separately. The clinicians use the information obtained from these interviews to generate a Clinical Dementia Rating (CDR)17- 19 reflecting the presence or absence of dementia. The global CDR is based on a standard scoring algorithm that integrates functioning in 6 individual domains: memory, orientation, judgment and problem solving, community affairs, home and hobbies, and personal care. The CDR Sum of Boxes (CDR-SB) score is obtained by summing the scores from the 6 domains.18 The CDR has established reliability.20,21 Global CDR scores indicate the following: 0, normal cognition; 1, mild dementia; 2, moderate dementia; and 3, severe dementia. A CDR score of 0.5 designates “uncertain dementia” if the etiology of the cognitive impairment cannot be determined or very mild dementia if on clinical grounds an etiologic diagnosis can be made.
Participants with cognitive impairment at the CDR 0.5 stage can be diagnosed as having very mild dementia of the Alzheimer type (DAT) when there is a history of gradual onset and progression of cognitive problems that represent a decline from that individual's previous level of cognitive function and interfere to at least some degree with usual activities at home and in the community. We demonstrated that the CDR 0.5/DAT participants have progressive cognitive deterioration typical of DAT and, of those coming to autopsy, AD is confirmed in 92%.22 Moreover, it is well recognized that some individuals rated as having a CDR score of 0.5 can merit a DAT diagnosis.23
To obtain CSF from participants, trained neurologists use a 22-gauge Sprotte spinal needle to collect 20 to 30 mL of CSF at 8 AM, after an overnight fast. The CSF samples are gently inverted and centrifuged at low speed to avoid possible gradient effects and then are frozen at −84°C24 after aliquoting into polypropylene tubes. The CSF samples for Aβ42, tau, and ptau are analyzed using enzyme-linked immunosorbent assay (INNOTEST; Innogenetics, Ghent, Belgium).
Normalized whole-brain volume (nWBV), reflecting the percentage of the intracranial cavity occupied by brain, was obtained using previously established methods.25 Briefly, the magnetization-prepared, rapid-acquisition gradient-echo data were intensity normalized.26 A validated segmentation tool was then used to classify brain tissue as CSF, gray matter, or white matter.27,28 Correction of intensity inhomogeneity was accomplished by an automated procedure to minimize intensity variation in contiguous regions. Based on intensity limits and contour (intensity gradient) detection, contiguous region boundaries were identified (without brain masking). The bias field was modeled as a general second-order polynomial in 3 dimensions (10 free variables).26 Segmentation began with an initial estimation step to obtain and classify tissue variables. Using a 3-step expectation-maximization algorithm, class labels and tissue variables were then updated to iterate toward the maximum likelihood estimates of a hidden Markov random field model. This model used spatial proximity to constrain the probability with which voxels of a given intensity are assigned to each tissue class. Finally, the brain volume estimate was taken as the sum of white and gray matter voxels in the atlas-based brain mask and expressed as a percentage of the mask.
Archival data were used from participants who (1) donated CSF between June 18, 1998, and May 18, 2009; (2) were 50 years or older at the time of donation; (3) had normal cognition (CDR = 0) at the closest clinical assessment within 1 year before or 1 month after donation; (4) underwent magnetic resonance imaging with measurement of brain volume within 1 year of donation; and (5) had at least 1 subsequent clinical assessment.
Cox proportional hazards regression models were used to test the 3-factor interaction of each of the biomarker variables (Aβ42, tau, and ptau) with education in years and nWBV in determining time from baseline assessment to cognitive impairment (ie, CDR > 0). All the predictor variables were treated as continuous.
For models in which the 3-factor interaction was significant, Cox proportional hazards regression models were conducted separately for individuals with biomarker values above and below the median; the 2-factor interaction between education and nWBV was tested in these models. For models in which the 3-factor interaction was not significant, the models were repeated testing 2-factor interactions among the biomarker, education, and nWBV variables. If no 2-factor interactions were significant, the final model comprised the main effects of each variable. All the models included terms adjusting for and simultaneously testing the effects of sex, age, race, the presence of an apolipoprotein E ε4 (APOE ε4) allele, and the magnetic resonance imaging scanner used.
To graphically display significant interaction effects, the biomarker, education, and nWBV variables were each dichotomized, reflecting lower and higher values on the variable, using a median split, and Kaplan-Meier survival curves were generated for each combination of these variables.
We also explored whether there were differences in the slope of scores across follow-up as a function of these 8 possible combinations of higher and lower values of the biomarker, education, and nWBV variables. In these analyses, mixed-effects linear models tested whether the slope of scores on the CDR-SB, Mini-Mental State Examination (MMSE),29 and Short Blessed Test30 differed as a function of the combination variable while adjusting for sex, age, race, and the presence of an APOE ε4 allele.
One hundred ninety-seven participants observed for a mean (SD) of 3.3 (2.0) years met the inclusion criteria (Table 1). Of these participants, 26 developed cognitive impairment a mean (SD) of 3.01 (1.93) years after baseline. Table 2 gives the clinical diagnoses assigned at the time of first CDR > 0. We consider individuals who received a DAT diagnosis to meet the “formal” criteria for very mild dementia, although we acknowledge that because the boundaries for mild cognitive impairment and dementia overlap, others may classify these individuals as having mild cognitive impairment. At the time of first CDR = 0.5, individuals with a DAT diagnosis had greater impairment than did those with an uncertain diagnosis, as reflected in worse mean performance on an autobiographical memory test31 (1.25 vs 1.68, P = .04) and in higher mean CDR-SB scores (1.94 vs 0.85, P = .02).
In the survival models testing Aβ42, there were no interactions with education or nWBV. The final model indicated that a larger nWBV was associated with a slower time to cognitive impairment (hazard ratio [HR], 0.81; 95% confidence interval [CI], 0.68-0.97; P = .02), but there was no effect of Aβ42 (P = .24) or education (P = .07).
Three-factor interactions among the biomarker values, education, and nWBV were found for models testing tau (P = .02) and ptau (P = .008). In participants with baseline tau values below the median, nWBV (HR, 0.54; 95% CI, 0.31-0.91; P = .02), but not education (P > .99), was related to time to cognitive impairment, and there was no interaction between these variables (P = .39) (Figure 1A). Of the 8 individuals with lower tau values who developed cognitive impairment (all of whom had nWBV values below the median nWBV), only 2 (25%) received a subsequent diagnosis of DAT at some time during follow-up. The remaining 6 participants had diagnoses of uncertain dementia (n = 5; 3 of these with a secondary diagnosis of mood disorder) or vascular dementia with a secondary diagnosis of Parkinson disease (n = 1). In contrast, 8 of 15 participants (53%) with smaller nWBVs but higher tau values received DAT diagnoses at some point during follow-up. For those with tau values above the median, education interacted with nWBV to predict incident impairment (P = .01) (Figure 1B).
For individuals with lower ptau values, there was no effect of education (P = .89) or nWBV (P = .14) and no interaction between them (P = .94) (Figure 1C). However, education and nWBV interacted to predict incident cognitive impairment in those with higher ptau values (P = .02) (Figure 1D).
Other variables that independently predicted time to impaired cognition were minority race (P < .007), which was associated with a faster time to impairment in each of the biomarker models, and male sex (P = .04), which was associated with more rapid cognitive impairment in the model including tau. There was no relationship between age, APOE ε4 level, or scanner type and incident impairment after adjustment for other variables in the model.
In the mixed-model analyses testing the 8 possible combinations of higher and lower values of the biomarker, education, and nWBV variables, the slope of scores on the CDR-SB differed as a function of the “combination” variable for analyses testing Aβ42, tau, and ptau (P < .001 for all) and on the Short Blessed Test for the analysis testing tau (P = .02). As shown in Figure 2, the significant results generally confirm those found using CDR > 0 as the end point. The slopes of scores on the MMSE did not differ across the combination variable levels.
Accumulating evidence suggests that the presence of AD biomarkers in cognitively normal persons is a harbinger of eventual cognitive impairment,13- 15 and much current effort is devoted to developing therapies that can halt the disease process. When these therapies are ready for use, it is thought that they may be most effective if administered at the time that biomarkers show abnormal values but before dementia symptoms occur.15 However, because biomarker levels may become abnormal a decade or more before clinical symptoms appear,32 it is vital to understand the time course between abnormal biomarker values, the onset of cognitive impairment, and characteristics that affect that time course to avoid exposing healthy individuals to medications and their potential adverse effects many years before they are needed.
The present results indicate that in individuals with higher levels of CSF tau and ptau but normal cognition at baseline, the time to incident cognitive impairment is moderated by education and brain volume. More education and larger nWBV seem to slow the rate of impairment onset in the presence of tau-related abnormalities, whereas individuals with lower levels of education and smaller nWBV values have the most rapid onset. As theorized by other researchers, more education may provide resistance to dementia in the presence of brain damage because more education may be associated with the use of particular cognitive processing approaches or enlistment of compensatory processes or may serve as a proxy for another factor, such as innate intelligence.5 Individuals with larger nWBVs may have sufficient neuronal resources to continue normal functioning in the presence of AD pathology for a longer time,33 or these individuals may have experienced less neuronal neurodegeneration despite having similar abnormal biomarker levels as other individuals. Education and nWBV do not interact to predict future cognitive impairment when lower levels of brain tau and ptau are present.
Previously, cross-sectional autopsy studies34,35 that include individuals with dementia and those with normal cognition before death have suggested that education and brain volume interact with AD pathology to predict concurrent cognitive performance. In these studies,34,35 education was found to interact with amyloid plaque, but not tangle, pathology. In the present study, conducted only with individuals who were cognitively normal at baseline, we found a modifying effect of education and nWBV on incident cognitive impairment for tau-based but not amyloid-based pathology. In fact, the main effect of Aβ42 itself was not significant in the primary multivariate analyses. This is consistent with the previous finding, using a smaller subsample of these individuals, of only a marginally significant effect of Aβ42 on incident AD when education and nWBV were included in the same model (P = .09).36 However, Aβ42 combined with education and nWBV to predict the slope of CDR-SB scores across follow-up, suggesting that Aβ42 interacts with education and nWBV in a manner similar to that exhibited by tau and ptau, although, as shown in Figure 2, the effect is less dramatic. With longer follow-up or a larger sample size, it is possible that a significant 3-way interaction effect among Aβ42, education, and nWBV would be found using the end point of CDR > 0. The categorical variable reflecting combined levels of the biomarkers, education, and nWBV was unrelated to the slope of scores on the MMSE. As pointed out by others,37 the MMSE may be less sensitive to cognitive decline compared with global dementia severity measures, such as the CDR-SB and the Short Blessed Test.
The nWBV was found to be associated with incident cognitive impairment even in individuals with tau levels below the baseline median. Brain volume decline, in addition to occurring as a consequence of neuron loss in AD, also occurs as a function of normal aging.38 Although based on a small sample, individuals with smaller nWBVs and lower tau levels who developed cognitive impairment were less likely to receive DAT diagnoses as an explanation for their cognitive problems compared with individuals with smaller nWBVs and higher tau values. This suggests that individuals with smaller nWBV values may be more vulnerable to cognitive impairment due to reasons other than underlying AD. However, this interpretation should be viewed with caution because the effect of nWBV was not significant when examined in the presence of low ptau levels.
Relatedly, we found no effect of age on incident impairment in the multivariate models. As previously noted, age and nWBV are tightly correlated in the participants.36 Thus, when one variable is present in the model, the other adds little additional predictive power.
No significant effects of APOE ε4 status were noted when considered together with the CSF biomarkers in predicting incident cognitive impairment. This result is similar to the previous finding that APOE4 did not increase the predictive accuracy of CSF biomarker models for the development of incident AD.36 That study also demonstrated that APOE ε4 was helpful in distinguishing prevalent AD from normal cognition.36 It is possible that the APOE genotype, when tested together with CSF biomarkers, might show independent effects on incident cognitive impairment in studies using a larger sample size or longer follow-up.
Limitations of this study include the use of a convenience sample and a relatively short mean follow-up of 3.3 years. Given these limitations, these results provide strong support for the brain and cognitive reserve hypotheses1,5- 8 and suggest that education and nWBV are influential in mediating the time to cognitive impairment when tau-based pathology is present.
Correspondence: Catherine M. Roe, PhD, Washington University School of Medicine, 660 S Euclid Ave, Campus Box 8111, St Louis, MO 63110 (firstname.lastname@example.org).
Accepted for Publication: February 16, 2011.
Author Contributions: All authors had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Roe. Acquisition of data: Fagan, Grant, Benzinger, Mintun, and Morris. Analysis and interpretation of data: Roe, Marcus, and Holtzman. Drafting of the manuscript: Roe and Marcus. Critical revision of the manuscript for important intellectual content: Roe, Fagan, Grant, Benzinger, Mintun, Holtzman, and Morris. Statistical analysis: Roe. Obtained funding: Holtzman and Morris. Administrative, technical, and material support: Fagan, Grant, Marcus, Benzinger, Mintun, Holtzman, and Morris. Study supervision: Benzinger and Morris.
Financial Disclosure: Dr Benzinger has served as a consultant to Biomedical Systems Inc and for ICON Medical Imaging and has received research funding from Avid Radiopharmaceuticals. Dr Holtzman is on the scientific advisory boards of Satori, En Vivo, and C2N Diagnostics and has consulted for Pfizer, Bristol-Myers Squibb, and Innogenetics. Dr Morris has participated or is currently participating in clinical trials of antidementia drugs sponsored by Elan, Eli Lilly & Co, and Wyeth and has served as a consultant for or has received speaking honoraria from AstraZeneca, Bristol-Myers Squibb, Eisai, Elan/Janssen Alzheimer Immunotherapy Program, Genentech, Eli Lilly & Co, Merck, Novartis, Otsuka Pharmaceuticals, Pfizer/Wyeth, and Schering-Plough.
Funding/Support: This work was supported by grant P30 NS057105 from the National Institute of Neurological Disorders and Stroke; grants P50 AG005681, P01 AG003991, and P01 AG026276 from the National Institute on Aging; grants 1UL1RR024992 from the National Center for Research Resources; and the Charles F. and Joanne Knight Alzheimer’s Research Initiative of the Washington University Alzheimer Disease Research Center.
Additional Contributions: We thank the participants, investigators, and staff of the Alzheimer Disease Research Center Clinical (participant assessments) and Genetics (genotyping) Cores and the investigators and staff of the Biomarker Core for the Adult Children Study (P01 AG026276) for CSF analytes.