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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Neuropathol Exp Neurol. Author manuscript; available in PMC 2010 June 28.
Published in final edited form as:
PMCID: PMC2892786
NIHMSID: NIHMS205348

Thinking outside the box: Alzheimer-type neuropathology that does not map directly onto current consensus recommendations

Abstract

Many cognitively impaired patients’ brains fall into neuropathologic diagnostic categories that cannot be defined explicitly by the National Institute on Aging and Reagan Institute (NIA-RI) guidelines. Two specific case categories are considered: “tangle-intensive” patients with the highest density of neurofibrillary tangles (NFTs, as graded by the Braak staging system) but only moderate density of neuritic amyloid plaques (NPs, as graded by CERAD); and conversely “plaque-intensive” patients with intermediate severity NFTs and high density of NPs. To better understand these technically unclassifiable cases, we analyzed NACC Registry data, which includes both clinical and pathological information from the National Institute on Aging-funded Alzheimer Disease Centers (ADCs). 1,672 cases with antemortem diagnoses of dementia were included. To evaluate the diagnostic tendencies of ADC neuropathologists, we assessed how the plaque-intensive and tangle-intensive cases were diagnosed ultimately. Tangle-intensive cases were more likely to be designated “High likelihood” that the dementia was due to AD, whereas plaque-intensive cases were typically designated “Intermediate likelihood”. Only the Braak stage VI “tangle-intensive” cases had lower final MMSE scores than the “plaque-intensive” cases (P<0.02). We conclude that more explicit diagnostic categories, along with better understanding of pathology in earlier phases of the disease, may be helpful to better guide neuropathologists.

Introduction

The most recent consensus guidelines for neuropathological Alzheimer’s disease (AD) diagnosis were the National Institute on Aging and Reagan Institute (NIA-RI) recommendations, published in 1997 (1). These guidelines indicated that neuropathology is an absolute requirement “to provide an estimate of the likelihood that Alzheimer’s disease pathological changes underlie dementia”(1). The NIA-RI consensus report also concluded that more modifications may be necessary and that it is important to “validate and refine the procedures recommended above.”(1) In the years since the NIA-RI guidelines were published, clinicians’ diagnostic arsenals have expanded dramatically with improved neuroimaging and cerebrospinal fluid tests. However, these encouraging advancements do not diminish the need for validating and refining neuropathological practices, which remain the gold standard for AD and other neurodegenerative disease diagnoses.

Two distinct “pathological hallmarks” of AD are recognized: neurofibrillary tangles (NFTs), and neuritic amyloid plaques (NPs). NFTs develop intracellularly and are composed of filamentous tau protein polymers. The severity of NFT pathology is graded on a 0–6 scale (using Roman numerals 0-VI by convention) according to “Braak stages” (2), which pertain to the spread of NFTs in the brain. In contrast with NFTs, NPs are extracellular amyloid deposits, surrounded by argyrophilic degenerating neurites. The severity of NP pathology is scored according to a distinct metric, which is named after the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) (3). The CERAD scoring system is a four-tiered scale representing neocortical NP density. Neither diffuse amyloid plaques nor cerebral amyloid angiopathy are relevant to current AD pathological diagnoses.

According to Braak staging and the CERAD scale, cases are parsed into “Low”, “Intermediate”, and “High” likelihood that clinical dementia is due to AD. “Low” likelihood corresponds to CERAD “Infrequent”, Braak stages 0–II. “Intermediate likelihood” corresponds to CERAD “Moderate”, Braak stages III or IV. “High likelihood” corresponds to CERAD “Frequent”, Braak stages V or VI. Combinations which have pairings of plaques and tangles off the diagonal are not clearly addressed in the NIA-Reagan criteria.

The majority of human brains can be categorized readily among the NIA-RI diagnostic groups. However, a surprisingly high fraction of cases (in the present study, approximately 18% of persons with antemortem diagnosis of dementia and without strong concomitant pathologies) were observed to fall outside of the NIA-RI rubric. To study these diagnostically problematic cases, we utilized the National Alzheimer’s Coordinating Center (NACC)(4) Registry database. This dataset includes annotated clinical and pathological information about thousands of individuals that had come to autopsy from 30 different Alzheimer Disease Centers (ADCs). The goals of these analyses were to track how neuropathologists are ultimately diagnosing AD, with given CERAD and Braak staging. We also sought to address whether the documented cognitive impairment in patients could give some new information to help guide diagnostic neuropathologic practice.

Methods

The NACC Registry represents data obtained from 30 different ADCs(4); identities of the universities from which cases derived are shown in Supplemental file 1. The data includes 3501 cases for the cohort with dementia, and 3822 cases for the cohort used to assess averaged final MMSE scores. In addition to the previously published NACC original exclusion criteria (5, 6). additional exclusion criteria specific to this study were imposed, specifically: death prior to 1999; no data about education level or neuropathology; or, clinical history of prion disease, synucleinopathies, triplet repeat diseases, brain cancer, or frontotemporal dementia that might explain a dementia syndrome with early death. Using these criteria, included cases from the NACC Registry are shown in Table 2. Neocortical LBs were determined by indication of “diffuse” or “intermediate” cortical LB pathology using the NACC registry “NPLEWY” and “NPLEWYCS” variables, based on consensus diagnostic features (7). Statistical analyses were performed using two-tailed Student’s t-tests.

Table 2
Basic demographics on human cohorts using different inclusion criteria

Results

Basic demographic and other parameters regarding the groups evaluated are shown in Table 2. Many of these subjects have been followed with annual neurologic examinations up to the point of death, with an average interval between the final MMSE scores and death below 1.5 years and a median interval of less than 1 year. The plaque and tangle assessments of cases in the NACC Registry from demented subjects are shown in Table 3. As this table reveals, subjects coming to autopsy are skewed toward high burdens of both plaques and tangles. Nonetheless, these data also show that almost 18% of cases fall outside of the proscribed NIA-RI diagnostic categories (“off-diagonal”).

Table 3
Number of dementia subjects in each neuropathologic diagnostic category

The cases of direct interest for the current study fell into specific categories: Braak stages III/IV and “frequent” NPs as specified by CERAD (“plaque-intensive” cases), and those with Braak stages V/VI and “moderate” NPs by CERAD (“tangle-intensive” cases). In this sample, those case categories comprise 9.4% of the cases overall, a higher percentage than those meeting the “Intermediate likelihood” criteria, which represented only 6.0% of cases in the database (partly due to the restriction to demented patients).

In order to determine the ultimate diagnoses given by neuropathologists at ADCs for these technically unclassifiable cases, separate analyses were performed on cases that had been given the ultimate diagnoses of “High-likelihood” (Table 4), “Intermediate-likelihood” (Table 5), and “Low-likelihood” (Table 6) of AD changes representing the substrate for cognitive impairment in demented subjects. These data show a relatively high concordance between the NIA-Reagan recommendations and neuropathological diagnoses that are indicated in Table 1. Further analyses are presented in Table 7. Note that cases that match with the consensus recommendations are given the appropriate diagnoses with great consistency: 93.1% for “Intermediate likelihood” cases and 97.7% of “High likelihood” cases are appropriate between the Braak, CERAD, and NIA-RI diagnoses.

Table 1
National Institute on Aging/Reagan Institute consensus recommendations to estimate “the likelihood that Alzheimer’s disease pathological changes underlie dementia”
Table 4
Dementia subjects classified in the data as NIA/Reagan “High Likelihood”
Table 5
Dementia subjects classified in the data as NIA/Reagan “Intermediate Likelihood”
Table 6
Dementia subjects classified in the data as NIA/Reagan “Low Likelihood”
Table 7
Summary of numbers and eventual diagnoses, according to the different diagnostic categories among dementia patients

Predictably, for cases outside the NIA-RI rubric, the consistency in terms of diagnostic categories was relatively low. However, there are some notable tendencies. Persons with “tangle-intensive” pathology are far more likely to be ultimately diagnosed as “High likelihood” for AD than “plaque-intensive” pathology (56.2% versus 22.4%). Conversely, 70.6% of “plaque-intensive” cases were designated “Intermediate likelihood” via NIA-RI, as opposed to 32.9% for “tangle-intensive” cases.

Since the cases derived from different research centers, we sought to understand how an individual ADC might affect the overall result. We provide data from individual ADCs as Supplemental Table 1, in which the ADCs are ordered according to the number of cases in the NACC Registry. Since no individual ADC comprised more than 20% of the cases in any particular category, it is unlikely that the diagnostic tendencies of an individual ADC drove the overall result. However, it is notable that in a single ADC (“ADC3” in the Supplemental Table) provided 18.4% (16 out of 87) of the “tangle-intensive” cases, and all 16 of these cases had been designated “High Likelihood”.

To test preliminarily whether “plaque-intensive” or “tangle-intensive” cases have more effect on cognition, we evaluated average final MMSE scores. For these analyses, two important differences were made relative to the prior inclusion criteria. Firstly, we could not restrict the analyses to only those individuals with antemortem dementia diagnoses, since we were trying to understand the clinico-pathological correlation of the diagnostic categories. As such, if one category had “undemented” patients that would be quite relevant and we do not wish to bias the results by excluding them a priori.

Secondly, for this group we were interested in understanding the associative impact of AD-type pathology. Thus, we had more rigorous exclusion criteria for “mixed” pathology and only included individuals with no known stroke history and with neuropathological designation of “No Lewy bodies” to exclude the possibility of bias of synucleinopathies that could be over-represented in some diagnostic categories. The results of the averaged final MMSE scores are shown in Table 8. Results of 2-tailed Student’s t-tests to examine differences among mean final MMSE scores are shown in Table 9. Further tests were performed to evaluate final MMSE score distributions (rather than means), and these did not provide additional information and thus are not shown.

Table 8
Final MMSE scores (range: 0–30) according to the diagnostic categories, including demented and non-demented patients, but excluding patients with stroke history or “any Lewy bodies” (N=1350, categories with <10 cases left ...
Table 9
P Values for 2-tailed Student’s t-tests comparing mean final MMSE scores across selected diagnostic groups

Discussion

Using NACC Registry data, we addressed some of the issues pertinent to cases that fall outside of the explicit recommendations of the NIA-RI Working Group. We found that approximately 18% of patients with antemortem dementia diagnoses fall outside of NIA-RI explicit categories, and almost 10% were either “plaque-intensive” or “tangle-intensive” high-pathology cases as described above. ADC neuropathologists tend to ultimately diagnose “plaque-intensive” cases as being “Intermediate likelihood” for AD, whereas “tangle-intensive” cases tend to be placed in the “High likelihood” category. These diagnostic tendencies are partially supported by an analysis of averaged final MMSE scores.

The current study has some limitations. NACC Registry data derives from 30 different ADCs with differing demographics and recruitment criteria, (5). As with all large databases, there is presumably some error rate in the classification schemes due to human and/or technical errors, which may explain some of the results. It has been demonstrated that there is some variability in the standards of AD severity scoring (e.g., Braak staging) between different pathologists (8, 9). We also had to exclude as dementia confounders many of the cases in the NACC Registry dataset, due to concomitant pathologies including synucleinopathies, frontotemporal dementias/tauopathies, large strokes, triplet repeat diseases, and neoplasms. Only individuals who died after 1999 were included to ensure that current practices were being tested. It would be optimal to be able to understand how these case categories are valid even in cases with “mixed” pathologies. These data in the NACC registry derive (as a rule) from samples of convenience, which involve some bias in case selection (10, 11). This is at least partly reflected by the large skew in the data towards advanced AD pathologically and clinically. Naturally, these data are also somewhat skewed by the fact that autopsy series tend to identify the latest stages in disease development. Finally, there are inevitably difference in the neuropathological methods and practices between ADCs, because there is no current consensus recommendations on exactly how one should process tissue for NPs and NFTs (12, 13). Despite these caveats, the number of individuals that were included was still quite large and post-hoc studies that included less stringent inclusion criteria had essentially similar results.

There were two main aims of the current study. The first was to query how ADC neuropathologists cope with diagnosing dementia cases in which CERAD and Braak stage parameters fall outside the current consensus guidelines in terms of ultimate diagnoses. The data show unequivocally that “tangle-intensive” cases tend to be more likely than “plaque-intensive” cases to be ultimately designed “High-likelihood” for AD. Data about the inter-rater comparisons in terms of detailed diagnostic results at individual ADCs is provided as supplemental file 1. The cumulative tendencies of ADC neuropatholgoists may reflect the fact that prior clinico-pathological studies have provided stronger support for the pathological impact of NFTs than amyloid plaques including NPs (1416). However, there are compelling data in the literature to support the hypothesis that NPs also contribute (albeit to a lesser extent) to cognitive impairment in aged individuals (11, 17, 18). Addressing these contentious issues is outside the scope of the current work. In contrast to the case categories outside the NIA-RI recommendations, the cases where the Braak stage and CERAD score are inside the guidelines the ADC neuropathologists were well over 90% consistent in their final diagnoses. These data seem to emphasize the importance of consensus guidelines such as NIA-RI among neuropathologists.

A second goal of the current study was to see if clinical-pathological correlation could provide insights into the global cognitive impairment (quantified with final MMSE scores) that is seen in association with the various pathological diagnostic categories. Presumably, this could be used to provide some guidance about the diagnostic implications related to those categories. To address this question, inclusion criteria were adjusted to more rigorously exclude mixed pathologies but to not limit the evaluation to clinically demented individuals. These results offer incomplete support for the prevalent practice of designating “tangle-intensive” cases as “High likelihood” for AD. More specifically, the average final MMSE scores for the “tangle-intensive” cases as a group are not lower than those of the “plaque-intensive” cases (although there is a trend in that direction that is not statistically significant). However, the final MMSE scores for the “tangle-intensive” cases are indeed lower than the final MMSE scores for the “Intermediate likelihood” group. Further, the “tangle-intensive” cases that are Braak stage VI, and which comprise 1.3 % of the demented patient cohort, seem to have final MMSE scores that approximate severe AD. This result is not unexpected since there is a large difference in the cognitive status in individuals without concomitant pathologies comparing Braak stage V and VI patients (15, 19).

There have been prior descriptions of cases that fall outside the NIA-RI recommendations. For example, it was suggested that cases we designated as “plaque-intensive” and “tangle-intensive” cases all belong in the category of “Intermediate likelihood” for AD (20). Cases have been described with moderate NFT pathology but very minimal plaque pathology and these may not belong on the AD continuum(21). Nonetheless many unanswered questions persist. Current neuropathological methods are oriented toward making a fixed diagnosis in subjects at various stages of a disease. It will be a challenge to integrate future neuropathologic rubrics with the neuropsychological testing, neuroimaging, and cerebrospinal fluid tests for earlier diagnosis of the disease. Diagnostic modalities are also challenged to account for the very substantial numbers of “mixed pathology” cases which were mostly ignored in the current study. Definitive recommendations that surmount these challenges, or that at least represent a diagnostic standard for the field, await future consensus guidelines. These guidelines may help to integrate the growing literature about the manifestations of AD in the earlier stages of the disease.

Supplementary Material

Supplemental Table

Acknowledgments

We give sincere thanks to the patients and their families that participated in the studies. This study grew out of a discussion, chaired by Dr. Frosch at the ADC NP Core meeting, and the stimulating input by our colleagues was appreciated. This study was supported by NIH grants R01 NS061933, K08 NS050110, P30 AG028383, P50 AG005134, and U01 AG016976 and NIRG (89917) grant from Alzheimer’s Association. We thank Ms Erin L Abner MPH for advice in statistics.

Bibliography

1. Consensus recommendations for the postmortem diagnosis of Alzheimer’s disease. The National Institute on Aging, and Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer’s Disease. Neurobiology of aging. 1997e;18:S1–2. [PubMed]
2. Braak H, Braak E. Staging of Alzheimer’s disease-related neurofibrillary changes. Neurobiology of aging. 1995e;16:271–8. discussion 8–84. [PubMed]
3. Mirra SS. The CERAD neuropathology protocol and consensus recommendations for the postmortem diagnosis of Alzheimer’s disease: a commentary. Neurobiology of aging. 1997e;18:S91–4. [PubMed]
4. Beekly DL, Ramos EM, van Belle G, Deitrich W, Clark AD, Jacka ME, Kukull WA. The National Alzheimer’s Coordinating Center (NACC) Database: an Alzheimer disease database. Alzheimer disease and associated disorders. 2004e;18:270–7. [PubMed]
5. Nelson PT, Jicha GA, Kryscio RJ, Abner EL, Schmitt FA, Cooper G, Xu LO, Smith CD, Markesbery WR. Low sensitivity in clinical diagnoses of dementia with Lewy bodies. J Neurol. 2009e [PMC free article] [PubMed]
6. Nelson PT, Kryscio RJ, Jicha GA, Abner EL, Schmitt FA, Xu LO, Cooper G, Smith CD, Markesbery WR. Relative preservation of MMSE scores in autopsy-proven dementia with Lewy bodies. Neurology. 2009e;73:1127–33. [PMC free article] [PubMed]
7. McKeith IG, Dickson DW, Lowe J, Emre M, O’Brien JT, Feldman H, Cummings J, Duda JE, Lippa C, Perry EK, Aarsland D, Arai H, Ballard CG, Boeve B, Burn DJ, Costa D, Del Ser T, Dubois B, Galasko D, Gauthier S, Goetz CG, Gomez-Tortosa E, Halliday G, Hansen LA, Hardy J, Iwatsubo T, Kalaria RN, Kaufer D, Kenny RA, Korczyn A, Kosaka K, Lee VM, Lees A, Litvan I, Londos E, Lopez OL, Minoshima S, Mizuno Y, Molina JA, Mukaetova-Ladinska EB, Pasquier F, Perry RH, Schulz JB, Trojanowski JQ, Yamada M. Diagnosis and management of dementia with Lewy bodies: third report of the DLB Consortium. Neurology. 2005e;65:1863–72. [PubMed]
8. Halliday G, Ng T, Rodriguez M, Harding A, Blumbergs P, Evans W, Fabian V, Fryer J, Gonzales M, Harper C, Kalnins R, Masters CL, McLean C, Milder DG, Pamphlett R, Scott G, Tannenberg A, Kril J. Consensus neuropathological diagnosis of common dementia syndromes: testing and standardising the use of multiple diagnostic criteria. Acta neuropathologica. 2002e;104:72–8. [PubMed]
9. Alafuzoff I, Arzberger T, Al-Sarraj S, Bodi I, Bogdanovic N, Braak H, Bugiani O, Del-Tredici K, Ferrer I, Gelpi E, Giaccone G, Graeber MB, Ince P, Kamphorst W, King A, Korkolopoulou P, Kovacs GG, Larionov S, Meyronet D, Monoranu C, Parchi P, Patsouris E, Roggendorf W, Seilhean D, Tagliavini F, Stadelmann C, Streichenberger N, Thal DR, Wharton SB, Kretzschmar H. Staging of neurofibrillary pathology in Alzheimer’s disease: a study of the BrainNet Europe Consortium. Brain Pathol. 2008e;18:484–96. [PMC free article] [PubMed]
10. Schneider JA, Aggarwal NT, Barnes L, Boyle P, Bennett DA. The Neuropathology of Older Persons with and Without Dementia from Community versus Clinic Cohorts. J Alzheimers Dis. 2009e [PMC free article] [PubMed]
11. Nelson PT, Abner EL, Schmitt FA, Kryscio RJ, Jicha GA, Smith CD, Davis DG, Poduska JW, Patel E, Mendiondo MS, Markesbery WR. Modeling the Association between 43 Different Clinical and Pathological Variables and the Severity of Cognitive Impairment in a Large Autopsy Cohort of Elderly Persons. Brain Pathol. 2008e [PMC free article] [PubMed]
12. Alafuzoff I, Pikkarainen M, Al-Sarraj S, Arzberger T, Bell J, Bodi I, Bogdanovic N, Budka H, Bugiani O, Ferrer I, Gelpi E, Giaccone G, Graeber MB, Hauw JJ, Kamphorst W, King A, Kopp N, Korkolopoulou P, Kovacs GG, Meyronet D, Parchi P, Patsouris E, Preusser M, Ravid R, Roggendorf W, Seilhean D, Streichenberger N, Thal DR, Kretzschmar H. Interlaboratory comparison of assessments of Alzheimer disease-related lesions: a study of the BrainNet Europe Consortium. Journal of neuropathology and experimental neurology. 2006e;65:740–57. [PubMed]
13. Alafuzoff I, Thal DR, Arzberger T, Bogdanovic N, Al-Sarraj S, Bodi I, Boluda S, Bugiani O, Duyckaerts C, Gelpi E, Gentleman S, Giaccone G, Graeber M, Hortobagyi T, Hoftberger R, Ince P, Ironside JW, Kavantzas N, King A, Korkolopoulou P, Kovacs GG, Meyronet D, Monoranu C, Nilsson T, Parchi P, Patsouris E, Pikkarainen M, Revesz T, Rozemuller A, Seilhean D, Schulz-Schaeffer W, Streichenberger N, Wharton SB, Kretzschmar H. Assessment of beta-amyloid deposits in human brain: a study of the BrainNet Europe Consortium. Acta Neuropathol. 2009e;117:309–20. [PMC free article] [PubMed]
14. Arriagada PV, Growdon JH, Hedley-Whyte ET, Hyman BT. Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology. 1992e;42:631–9. [PubMed]
15. Nelson PT, Braak H, Markesbery WR. Neuropathology and cognitive impairment in Alzheimer disease: a complex but coherent relationship. Journal of neuropathology and experimental neurology. 2009e;68:1–14. [PMC free article] [PubMed]
16. Ingelsson M, Fukumoto H, Newell KL, Growdon JH, Hedley-Whyte ET, Frosch MP, Albert MS, Hyman BT, Irizarry MC. Early Abeta accumulation and progressive synaptic loss, gliosis, and tangle formation in AD brain. Neurology. 2004e;62:925–31. [PubMed]
17. Nagy Z, Esiri MM, Jobst KA, Morris JH, King EM, McDonald B, Litchfield S, Smith A, Barnetson L, Smith AD. Relative roles of plaques and tangles in the dementia of Alzheimer’s disease: correlations using three sets of neuropathological criteria. Dementia (Basel, Switzerland) 1995e;6:21–31. [PubMed]
18. Tiraboschi P, Hansen LA, Thal LJ, Corey-Bloom J. The importance of neuritic plaques and tangles to the development and evolution of AD. Neurology. 2004e;62:1984–9. [PubMed]
19. Whitwell JL, Josephs KA, Murray ME, Kantarci K, Przybelski SA, Weigand SD, Vemuri P, Senjem ML, Parisi JE, Knopman DS, Boeve BF, Petersen RC, Dickson DW, Jack CR., Jr MRI correlates of neurofibrillary tangle pathology at autopsy: a voxel-based morphometry study. Neurology. 2008e;71:743–9. [PMC free article] [PubMed]
20. Jellinger KA. Criteria for the neuropathological diagnosis of dementing disorders: routes out of the swamp? Acta Neuropathol. 2009e;117:101–10. [PubMed]
21. Nelson PT, Abner EL, Schmitt FA, Kryscio RJ, Jicha GA, Santacruz K, Smith CD, Patel E, Markesbery WR. Brains with medial temporal lobe neurofibrillary tangles but no neuritic amyloid plaques are a diagnostic dilemma but may have pathogenetic aspects distinct from Alzheimer disease. Journal of neuropathology and experimental neurology. 2009e;68:774–84. [PMC free article] [PubMed]