Neuropsychological Markers of Cognitive Decline in Persons With ...

J Neuropathol Exp Neurol Copyright © 2015 by the American Association of Neuropathologists, Inc.

Vol. 74, No. 11 November 2015 pp. 1086–1092

ORIGINAL ARTICLE

Neuropsychological Markers of Cognitive Decline in Persons With Alzheimer Disease Neuropathology Jason Hassenstab, PhD, Sarah E. Monsell, MS, Charles Mock, MD, PhD, Catherine M. Roe, PhD, Nigel J. Cairns, PhD, FRCPath, John C. Morris, MD, and Walter Kukull, PhD Abstract To evaluate cognitive performance among persons who did and did not develop clinical Alzheimer disease (AD) but had AD neuropathology at autopsy, we examined neuropsychological performance in cognitively healthy (Clinical Dementia Rating [CDR] = 0) participants who returned for at least 1 follow-up and died within 2 years of their last assessment. Nonprogressors remained at CDR = 0 until death; progressors developed symptomatic AD during life (CDR > 0). Cognitive performance at baseline was compared between progressors and nonprogressors on a global cognitive composite and 4 domainspecific composites (episodic memory, language, attention/working From the Knight Alzheimer’s Disease Research Center, Department of Neurology (JH, CMR, NJC, JCM), Washington University School of Medicine, St. Louis, Missouri; and National Alzheimer’s Coordinating Center (SEM, CM, WK), University of Washington, Seattle, Washington. Send correspondence and reprint requests to: Jason Hassenstab, PhD, Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, 4488 Forest Park Ave, Suite 130, St. Louis, MO 63108; E-mail: [email protected] Funding: The NACC database is supported by NIA grant U01 AG016976. Disclosures: J. Hassenstab, S.E. Monsell, C. Mock, C.M. Roe, N.J. Cairns, and W. Kukull report no disclosures. JC Morris: Neither Dr. Morris nor his family owns stock or has equity interest (outside of mutual funds or other externally directed accounts) in any pharmaceutical or biotechnology company. Dr. Morris has participated or is currently participating in clinical trials of antidementia drugs sponsored by the following companies: Janssen Immunotherapy and Pfizer. Dr. Morris has served as a consultant for Lilly USA. He receives research support from Eli Lilly/Avid Radiopharmaceuticals and is funded by NIH grants P50AG005681, P01AG003991, P01AG026276, and U19AG032438. The NACC database is funded by NIA/NIH Grant U01 AG016976. NACC data are contributed by the NIA-funded ADCs: P30 AG019610 (PI Eric Reiman, MD), P30 AG013846 (PI Neil Kowall, MD), P50 AG008702 (PI Scott Small, MD), P50 AG025688 (PI Allan Levey, MD, PhD), P30 AG010133 (PI Andrew Saykin, PsyD), P50 AG005146 (PI Marilyn Albert, PhD), P50 AG005134 (PI Bradley Hyman, MD, PhD), P50 AG016574 (PI Ronald Petersen, MD, PhD), P50 AG005138 (PI Mary Sano, PhD), P30 AG008051 (PI Steven Ferris, PhD), P30 AG013854 (PI M. Marsel Mesulam, MD), P30 AG008017 (PI Jeffrey Kaye, MD), P30 AG010161 (PI David Bennett, MD), P30 AG010129 (PI Charles DeCarli, MD), P50 AG016573 (PI Frank LaFerla, PhD), P50 AG016570 (PI David Teplow, PhD), P50 AG005131 (PI Douglas Galasko, MD), P50 AG023501 (PI Bruce Miller, MD), P30 AG035982 (PI Russell Swerdlow, MD), P30 AG028383 (PI Linda Van Eldik, PhD), P30 AG010124 (PI John Trojanowski, MD, PhD), P50 AG005133 (PI Oscar Lopez, MD), P50 AG005142 (PI Helena Chui, MD), P30 AG012300 (PI Roger Rosenberg, MD), P50 AG005136 (PI Thomas Montine, MD, PhD), P50 AG033514 (PI Sanjay Asthana, MD, FRCP), and P50 AG005681 (PI John Morris, MD). Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal’s Web site (www.jneuropath.com).

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memory, and executive function). Models adjusted for age, education, sex, and non-AD neuropathology. Progressors (n = 173) had worse performance than nonprogressors (n = 141) in nearly all cognitive domains. Progressors scored lower on composites of global cognition (P < 0.001), executive function (P = 0.0006), language (P < 0.0001), and episodic memory (P = 0.0006) but not on attention/working memory (P = 0.91). These data indicate that individuals with underlying AD neuropathology who are clinically healthy but who later develop symptomatic AD have worse performance in a wide range of domains versus individuals with underlying AD neuropathology who are clinically healthy but do not become symptomatic during life. Therefore, subtle cognitive decline at baseline may indicate an increased risk of progression to symptomatic AD. Key Words: Alzheimer disease, Braak staging, Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) plaque, Clinical diagnosis, Memory, Mild cognitive impairment, Neuropathology.

INTRODUCTION The pathological hallmarks of Alzheimer disease (AD) are known to be present well before the onset of symptoms sufficient to trigger a clinical diagnosis of mild cognitive impairment (MCI) or dementia. β-Amyloidosis may begin as early as 2 decades before diagnosis, followed by tau proliferation resulting in neuronal injury (1–3). The final stage of “preclinical” AD may be characterized by subtle cognitive decline, although this has yet to be fully defined (3). Studies that have modeled cognitive trajectories in the preclinical stage of AD have shown cognitive declines beginning within approximately 7 years of clinical diagnosis (4, 5), with a pronounced acceleration 3 to 5 years before diagnosis (6, 7). However, most of these studies rely on clinical and biomarker evidence of AD in living participants, and the correspondence between clinical diagnosis, in vivo biomarkers, and the “gold standard” of neuropathological diagnosis of AD remains unclear (8, 9). Thus, without autopsy confirmation, the time course and cognitive domains that characterize early cognitive decline in preclinical AD may be biased by diagnostic inaccuracies. Until recently, a diagnosis of AD required autopsy evidence of AD-related neuropathologic change in addition to the presence of symptoms (10). The most recent standards for neuropathologic diagnosis of AD are the NIA-Alzheimer’s Association (AA) guidelines, which require only the presence of AD-related neuropathologic change and do not require evidence of clinical symptoms during life (11). This change effectively acknowledges the presence of a preclinical stage of AD in which subtle cognitive changes may be present that are insufficient to

J Neuropathol Exp Neurol • Volume 74, Number 11, November 2015

Copyright © 2015 by the American Association of Neuropathologists, Inc. Unauthorized reproduction of this article is prohibited.


warrant a clinical diagnosis. Using autopsy-confirmed AD as a standard, we previously examined longitudinal cognitive performance in participants with neuropathologic AD who were clinically asymptomatic during life and found subtle declines in attention over time (12). This suggested that the very earliest changes in the AD continuum may be in areas other than episodic memory. In the current study, we extend these findings by examining whether there are baseline differences in cognitive performance between participants with autopsy-confirmed AD who did and who did not develop symptomatic AD, as defined by a clinical diagnosis of MCI or dementia during life.

MATERIALS AND METHODS Study Sample Data for this study were obtained from the National Alzheimer's Coordinating Center Uniform Data Set (UDS) (13) and Neuropathology Data Set (NPDS). Data were collected between September 2005 and December 2014 at 34 current and past National Institute on Aging Alzheimer's Disease Centers (NIA ADCs). Written informed consent was obtained from all participants. Research using the NACC database was approved by the University of Washington institutional review board. As described previously, UDS forms are used to obtain information on subject demographics, health history, and current clinical characteristics. Subjects with cognitive impairment, and cognitively healthy subjects, are enrolled in the UDS (14). Data, including a neuropsychological test battery, are collected approximately annually. Neuropathologic data are available for UDS subjects who consent to autopsy and die. These data are recorded in the NPDS and can be linked to UDS data. Subjects included in this study were required to have the following: 1) neuropathology data available, 2) died within 2 years of their last clinical assessment, 3) 2 or more UDS visits, and 4) healthy cognition at the first UDS visit. Healthy cognition was defined as a global score of zero on the Clinical Dementia Rating (CDR), an instrument that summarizes an individual's cognitive and functional abilities (15). Subjects who had a CDR score of zero at every follow-up visit were considered “nonprogressors” because they did not develop clinical AD during follow-up, whereas subjects who had a CDR score of 0.5 or higher (clinical characteristics consistent with symptomatic dementia) from at least 1 follow-up visit were considered “progressors.” Subjects who received a CDR score higher than 0 but who reverted back to CDR = 0 on or before their last visit were considered nonprogressors.

AD Neuropathology The definition of AD neuropathologic change (AD-NP) was based on a modification of the NIA-AA criteria for neuropathologic AD “ABC score” (11, 16), as previously described (17). Briefly, Braak stage (B score) for neurofibrillary tangles (18) and Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) neuritic plaque frequency (19) (C score) were recorded in the NPDS. At the time of data analysis, however, a Thal phase for amyloidβ (Aβ) plaques (20) (A score) was not recorded in the NPDS. To capture the most frequent

Cognitive Decline in AD Neuropathology

plaque type, we included “diffuse plaque,” which is most likely an early form of Aβ plaque formation and is defined as plaques with no apparent dystrophic neurites, as detected by silver impregnation methods, ubiquitin, or tau immunohistochemistry. All types of Aβ plaques, including diffuse plaques, are also readily identified using Aβ immunohistochemistry. Subjects with sparse, moderate, or frequent diffuse plaques were considered to have a Thal Aβ plaque phase of 1 or higher and thus met AD-NP inclusion criteria for this study. Likewise, subjects with sparse, moderate, or frequent neuritic plaques had a neuritic plaque C score of 1 or higher and also met study inclusion criteria. Limiting the sample to subjects with diffuse and/or neuritic plaques is similar to including all subjects meeting NIA-AA criteria for low to high AD neuropathologic change. The resulting study sample included only those subjects with Aβ plaques, excluding those without, regardless of Braak stage.

Non-AD Neuropathologic Features Neuropathology unrelated to AD was defined with variables from the NPDS that were coded to indicate the presence or absence of each condition. Lacunes and infarcts included data on the presence or absence of large cerebral artery infarcts, lacunes (small artery infarcts and/or hemorrhages), and gross infarcts. Data on hemorrhages and microbleeds were indicated with one variable that included the presence or absence of microbleeds and both old and acute hemorrhages. Hippocampal and medial temporal lobe sclerosis was identified with one summary variable indicating presence or absence of unilateral or bilateral sclerosis. Mild, moderate, or severe cerebral amyloid angiopathy was coded as present or absent. Similarly, mild, moderate, or severe arteriosclerosis was coded as present or absent. Lewy body pathology in the brainstem, limbic regions, neocortex, or any brain region was coded as present or absent. Data regarding other non-AD pathologies, including frontotemporal lobar degeneration and other tauopathies, were not available in the majority of cases and, therefore, were not included in analyses.

Measures of Decline Neuropsychological test performance was assessed using the UDS neuropsychological battery (21). The tests were grouped into cognitive domains based on a previous factor analysis of the UDS battery (22). The episodic memory domain was measured by the 2 Logical Memory Tests, the language domain by the Boston Naming Test and the object naming tests, attention/working memory by the Digit Span tests, and executive function domain by the Trail Making tests and Digit Symbol test. At each visit, an individual test score was converted to a z-score by subtracting the mean and dividing by the standard deviation of all UDS initial-visit scores among cognitively healthy subjects defined as having a CDR global score of 0. The z-scores for the tests within each domain were then averaged to obtain a standardized domain-specific composite score. Averaging all of the domain-specific scores created a global cognitive composite score. Domains missing data on at least 1 test were considered missing for that subject.

© 2015 the American Association of Neuropathologists, Inc.

Copyright © 2015 by the American Association of Neuropathologists, Inc. Unauthorized reproduction of this article is prohibited.

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Statistical Analysis Mean cognitive performance at the initial visit was estimated using linear regression with generalized estimating equations, which allowed us to account for clustering of subjects within an ADC. Each of the 4 cognitive domains, and the global composite, was an outcome measure (dependent variable) in a separate regression model, resulting in 5 separate models. The average score for progressors was compared with the average for nonprogressors using a Wald test. Two adjusted models were run for each outcome measure. The first model was adjusted for age at initial visit, education, and sex. We were unable to adjust for race in the model because of the infrequency of nonwhite race in both groups. The second model was adjusted for the same characteristics as the first and the non-AD neuropathologic features. Adding non-AD neuropathologic features did not change results or conclusions. Several sensitivity analyses were run using different methods of adjustment for time of follow-up. All regression models were fit with an independent correlation structure and robust standard errors in R 2.14.2 using the “geeglm” package.

RESULTS Neuropathologic data were available for 3345 UDS subjects. Restricting the sample to those who received a diagnosis of low to high AD neuropathologic change and who died within 2 years of their last available assessment reduced the sample to 2381 subjects. The data were further limited to subjects who enrolled with a CDR global score of 0 and had at least 2 UDS visits. Of the resulting analytic sample of 314 subjects, 173 (55%) had progressed to symptomatic AD, and 141 (45%) remained with CDR 0 through their final clinical assessment. Demographic characteristics and neuropathology findings are described in Tables 1 and 2. As shown in Table 1, subjects completed 2 to 7 annual visits, with most subjects completing more than 2 visits (82%). Progressors and nonprogressors were similar in terms of age at first UDS visit, education, race, and sex distribution, but a higher percent of progressors had 1 or 2 APOE ε4 alleles. Progressors more often made 3 or more visits and had a longer period between first and last visit, (mean of 1515 days vs. 1243 days for nonprogressors). Correspondence between clinical diagnoses and CDR global score at the last available visit was high. Of the nonprogressors, only 6% (9/141) were given a clinical diagnosis of MCI or dementia. Alternatively, only 9% (15/173) of progressors were given a clinical diagnosis of healthy cognition. Progressors had slightly more ischemic lesions (infarcts and lacunes) and hemorrhagic pathology (hemorrhages or microbleeds) and more arteriosclerosis and cerebral amyloid angiopathy. Progressors also had more pronounced AD neuropathologic change (neuritic plaques, diffuse plaques, and Braak stage I or higher). The presence of Lewy body pathology was similar between progressors and nonprogressors. Differences in mean scores (β) between progressors and nonprogressors are presented, adjusted for age, education, and sex in Table 3. The average progressor performed 0.33 SDs worse than the average nonprogressor on the global composite. Progressors also performed significantly worse than

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TABLE 1. Frequency of Clinical and Demographic Characteristics Characteristic No. visits made 2 3 4 5 6 7 8 9 Age at first UDS visit