Clustering of Pick bodies in patients with Pick's disease

Clustering of Pick bodies (PB) was studied in the frontal and temporal lobe in 10 cases of Pick's disease (PD). Pick bodies exhibited clustering in 47/50 (94%) brain areas analysed. In 20/50 (40%) brain areas, PB were present in a single large cluster ≤ 6400 μm in diameter, in 27/50 (54%) PB occurred in smaller clusters (200-3200 μm in diameter) which exhibited a regular periodicity relative to the tissue boundary, in 1/50 (2%) there was a regular distribution of individual PB and in 2/50 (4%), PB were randomly distributed. Mean cluster size of the PB was greater in the dentate gyrus compared with the inferior temporal gyrus and lateral occipitotemporal gyrus. Mean cluster size of PB in a brain region was positively correlated with the mean density of PB. Hence, PB exhibit essentially the same spatial patterns as senile plaques and neurofibrillary tangles in Alzheimer's disease (AD) and Lewy bodies in Dementia with Lewy bodies (DLB).

Analysis of spatial patterns in histological sections of brain tissue

A method is described which enables the spatial pattern of discrete objects in histological sections of brain tissue to be determined. The method can be applied to cell bodies, sections of blood vessels or the characteristic lesions which develop in the brain of patients with neurodegenerative disorders. The density of the histological feature under study is measured in a series of contiguous sample fields arranged in a grid or transect. Data from adjacent sample fields are added together to provide density data for larger field sizes. A plot of the variance/mean ratio (V/M) of the data versus field size reveals whether the objects are distributed randomly, uniformly or in clusters. If the objects are clustered, the analysis determines whether the clusters are randomly or regularly distributed and the mean size of the clusters. In addition, if two different histological features are clustered, the analysis can determine whether their clusters are in phase, out of phase or unrelated to each other. To illustrate the method, the spatial patterns of senile plaques and neurofibrillary tangles were studied in histological sections of brain tissue from patients with Alzheimer's disease.

Visual field defects in Alzheimer's disease patients may reflect differential pathology in the primary visual cortex

The aim of this study was to test the hypothesis that differences in density of senile plaques (SP) and neurofibrillary tangles (NFT) in the cuneal and lingual gyri of area V1 of the visual cortex could explain the predominantly inferior visual field defects seen in patients with Alzheimer's disease (AD). The density of SP and NFT was measured in the cuneal and lingual gyri of 18 AD patients. In 7/18 (39%) patients, the density of SP and/or NFT was significantly greater in the cuneal compared with the lingual gyri. In 3/18 (17%) patients, densities were greater in the lingual than the cuneal gyri and in 8/18 (44%) patients there were no significant differences among gyri. The data suggest that pathological differences between cuneal and lingual gyri could contribute to the reported visual field defects in some AD patients.

The use of multivariate methods in the identification of subtypes of Alzheimer's disease: a comparison of principal components and cluster analysis

Two contrasting multivariate statistical methods, viz., principal components analysis (PCA) and cluster analysis were applied to the study of neuropathological variations between cases of Alzheimer's disease (AD). To compare the two methods, 78 cases of AD were analyzed, each characterised by measurements of 47 neuropathological variables. Both methods of analysis revealed significant variations between AD cases. These variations were related primarily to differences in the distribution and abundance of senile plaques (SP) and neurofibrillary tangles (NFT) in the brain. Cluster analysis classified the majority of AD cases into five groups which could represent subtypes of AD. However, PCA suggested that variation between cases was more continuous with no distinct subtypes. Hence, PCA may be a more appropriate method than cluster analysis in the study of neuropathological variations between AD cases.

Aluminium and Alzheimer's disease: review of possible pathogenic mechanisms

Chronic exposure to aluminium (Al) remains a controversial possible cause of sporadic forms of Alzheimer's disease (AD). This article reviews the evidence that once Al enters the brain and individual brain cells, it may be involved in three pathological processes: (1) the production of abnormal forms of tau leading to the formation of cellular neurofibrillary tangles and neuropil threads; (2) the processing of the amyloid precursor protein, resulting in the formation of beta-amyloid deposits and senile plaques, and (3) that via the mutual histocompatibility system, Al could be involved in the initiation of the immune response observed in AD patients. Despite recent evidence that Al could be involved in these processes, a conclusive case that exposure to Al initiates the primary pathological process in sporadic AD remains to be established.

Neuropathological differences between areas B17 and B18: implications for visual evoked responses in Alzheimer's disease

The density of senile plaques (SP) and neurofibrillary tangles (NFT) was estimated at post-mortem in areas B17 and B18 of the visual cortex in 18 Alzheimer’s disease (AD) cases which varied in disease onset and duration. The density of SP in B17 and NFT in B17 and B18 declined significantly with age at death of the patient. The density of SP and NFT was greater in B18 than B17 but only in cases of earlier onset and shorter duration. The pathological differences between B17 and B18 could explain the visual evoked responses (VER) that have been reported in AD. However, the differences were small, and changes in the afferent pathways remain the most likely explanation for the VER in AD. © 1994 S. Karger AG, Basel.

Measuring the degree of spatial correlation between pathological lesions in Alzheimer's disease

The pathological lesions characteristic of Alzheimer's disease (AD), viz., senile plaques (SP) and neurofibrillary tangles (NFT) may not be randomly distributed with reference to each other but exhibit a degree of sptial association or correlation, information on the degree of association between SP and NFT or between the lesions and normal histological features, such as neuronal perikarya and blood vessels, may be valuable in elucidating the pathogenesis of AD. This article reviews the statistical methods available for studying the degree of spatial association in histological sections of AD tissue. These include tests of interspecific association between two or more histological features using chi-square contingency tables, measurement of 'complete' and 'absolute' association, and more complex methods that use grids of contiguous samples. In addition, analyses of association using correlation matrices and stepwise multiple regression methods are described. The advantages and limitations of each method are reviewed and possible future developments discussed.

The spatial patterns of Pick bodies, Pick cells and Alzheimer’s disease pathology in Pick’s disease

The spatial patterns of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) were studied in the frontal and temporal lobe in nine cases of Pick’s disease (PD). Pick bodies exhibited clustering in 41/44 (93%) of analyses and clusters of PB were regularly distributed parallel to the tissue boundary in 24/41 (58%) of analyses. Pick cells exhibited clustering with regular periodicity of clusters in 14/16 (88%) analyses, SP in three out of four (75%) analyses and NFT in 21/27 (78%) analyses. The largest clusters of PB were observed in the dentate gyrus and PC in the frontal cortex. In 10/17 (59%) brain areas studied, a positive or negative correlation was observed between the densities of PB and PC. The densities of PB and NFT were not significantly correlated in the majority of brain areas but a negative correlation was observed in 7/29 (24%) brain areas. The data suggest that PB and PC in patients with PD exhibit essentially the same spatial patterns as SP and NFT in Alzheimer’s disease (AD) and Lewy bodies (LB) in dementia with Lewy bodies (DLB). In addition, there was a spatial correlation between the clusters of PB and PC, suggesting a pathogenic relationship between the two lesions. However, in the majority of tissues examined there was no spatial correlation between the clusters of PB and NFT, suggesting that the two lesions develop in association with different populations of neurons.

A comparison of histological and immunohistochemical methods for quantifying the pathological lesions of Pick's disease

Counts of Pick bodies (PB), Pick cells (PC), senile plaques (SP) and neurofibrillary tangles (NFT) were made in the frontal and temporal cortex from patients with Pick's disease (PD). Lesions were stained histologically with hematoxylin and eosin (HE) and the Bielschowsky silver impregnation method and labeled immunohistochemically with antibodies raised to ubiquitin and tau. The greatest numbers of PB were revealed by immunohistochemistry. Counts of PB revealed by ubiquitin and tau were highly positively correlated which suggested that the two antibodies recognized virtually identical populations of PB. The greatest numbers of PC were revealed by HE followed by the anti-ubiquitin antibody. However, the correlation between counts was poor, suggesting that HE and ubiquitin revealed different populations of PC. The greatest numbers of SP and NFT were revealed by the Bielschowsky method indicating the presence of Alzheimer-type lesions not revealed by the immunohistochemistry. In addition, more NFT were revealed by the anti-ubiquitin compared with the anti-tau antibody. The data suggested that in PD: (i) the anti-ubiquitin and anti-tau antibodies were equally effective at labeling PB; (ii) both HE and anti-ubiquitin should be used to quantitate PC; and (iii) the Bielschowsky method should be used to quantitate SP and NFT.

Is neuropathological heterogeneity in Alzheimer’s disease related to apolipoprotein genotype?

The abundance of senile plaques (SP) and neurofibrillary tangles (NFT) was studied in cortical and subcortical regions from 30 patients with Alzheimer’s disease (AD) expressing different apolipoprotein E (apoE) genotypes. Principal components analysis (PCA) was used to identify the most important neuropathological variations between individual patients and to determine whether these variations were related to apoE genotype. The first two principal components (PC) accounted for 60% and 40% of the total variance of the SP and NFT data respectively. The abundance of SP in the frontal and occipital cortex and NFT in the frontal cortex, amygdala and substantia nigra were positively correlated with the first principal component (PC1). Analysis of the SP data revealed that the apoE score of the patient (the sum of the two alleles) was positively correlated with PC1 while analysis of the NFT data revealed no significant correlations between apoE score and the PC. The data suggest that apoE genotype was more closely related to variations in the distribution and abundance of SP than of NFT. In addition, a more rapid spread of SP into the frontal and occipital cortex may occur in patients with a high apoE score.

Lewy body and Alzheimer pathology in temporal lobe in dementia with Lewy bodies

The density of Lewy bodies (LB), senile plaques (SP), and neurofibrillary tangles (NFT) was studied in the temporal lobe in four patients diagnosed with ‘pure’ dementia with Lewy bodies (DLB) and eight patients diagnosed with DLB with associated Alzheimer’s disease (DLB/AD). In both patient groups, the density of LB was greatest in the lateral occipitotemporal gyrus (LOT) and least in areaas CA1 and CA4 of the hippocampus. In DLB/AD, the densities of SP and NFT were greatest in the cortical regions and in area CA1 of the hippocampus respectively. Mean LB densities in the temporal lobe were similar in ‘pure’ DLB and DLB/AD patients but mean SP and NFT densities were greater in DLB/AD. No significant correlations were observed between the densities of LB, SP and NFT in any brain region. The data suggest that in the temporal lobe LB and SP/NFT are distributed differently; SP and NFT in DLB/AD are distributed similarly to ‘pure’ AD and also that LB and AD pathologies appear to develop independently. Hence, the data support the hypothesis that some cases of DLB combine the features of DLB and AD.

Does the neurodegeneration of Alzheimer’s disease spread between visual cortical regions B17 and B18 via the feedforward or feedback short cortico-cortical projections?

The laminar distribution of senile plaques (SP) and neurofibrillary tangles (NFT) was studied in areas B17 and B18 of the visual cortex in 18 cases of Alzheimer’s disease which varied in disease onset and duration. The objective was to test the hypothesis that SP and NFT could spread via either the feedforward or feedback short cortico-cortical projections. In area B17, the mean density of SP and NFT reached a maximum in lamina III and in laminae II and III respectively. In B18, mean SP density was maximal in laminae III and IV and NFT density in laminae II and III. No significant correlations were observed in any cortical lamina between the density of SP and patient age. However, the density of NFT in laminae III, IV and VI in B18 was negatively correlated with patient age. In addition, in B18, the density of SP in lamina II and lamina V was negatively correlated with disease duration and disease onset respectively. Although these results suggest that SP and NFT might spread between B17 and B18 via the feedforward short cortico-cortical projections, it is also possible that the longer cortico-cortical and cortico-subcortical connections may be involved.

Neuropathological changes in the visual cortex in Alzheimer's disease

A survey of 106 cases of Alzheimer's disease (AD) indicated that senile plaques (SP) and neurofibrillary tangles (NFT) were recorded as frequent or abundant in the visual cortex in 72% and 27% of cases respectively. Comparable estimates for other brain regions were 89% for both lesions in temporal cortex and 94% and 95% respectively in the hippocampus. In 18 cases studied in detail, the density of SP and NFT was greater in B19/18 than in B17 in cases with early onset and short duration. The density of SP and NFT in B17, B18/19 and parietal cortex was negatively correlated with age at death of the patient but not with duration of the disease. In about 50% of tissue sections examined SP and NFT were clustered at a particular depth in the cortex. Clustering was more frequent in the upper layers of the cortex and in early onset cases. It was concluded that visual stimuli that evoke activity in different areas of visual cortex might be developed as a diagnostic test for early onset AD.

Distribution of A4 protein and neurofibrillary change in the hippocampus in Alzheimer's disease

The principal components of classical senile plaques (SP) in Alzheimer's disease (AD) appear to be A4/beta protein and paired helical filaments (PHF). A4 deposits may evolve into classical SP in brain regions vulnerable to the formation of PHF. We have investigated the diatribution of A4 deposits using an immunostain and the neurofibrillary change using the Gallyas stain in various regions of the hippocampus. This region is particularly affected in AD and also has relatively restricted inputs and outputs. In 6 patients we found a significant preponderance of A4 deposits in the adjacent parahippocampal gyrus (PHG) compared with all regions of the hippocampus. However, plaque-like clusters of PHF (Gallyas plaques) were more abundant in the subiculum while neurofibrillary tangles (NFT) were more abundant in the subiculum and region CA1 compared with the PHG and other hippocampal regions. Hence, A4 deposits appear to be concentrated in the region providing a major input into the hippocampus while the neurofibrillary changes are characteristic of the major output areas (subiculum and CA1). Hence, the data suggest that A4 formation and the neurofibrillary changes may occur in regions of the hippocampus that are connected anatomically.

Principal components analysis of Alzheimer's disease based on neuropathological data: a study of 79 patients

A principal components analysis was carried out on neuropathological data collected from 79 cases of Alzheimer's disease (AD) diagnosed in a single centre. The purpose of the study was to determine whether on neuropathological criteria there was evidence for clearly defined subtypes of the disease. Two principal components (PC1 and PC2) were extracted from the data. PC1 was considerable more important than PC2 accounting for 72% of the total variance. When plotted in relation to the first two principal components the majority of cases (65/79) were distributed in a single cluster within which subgroupings were not clearly evident. In addition, there were a number of individual, mainly early-onset cases, which were neither related to each other nor to the main cluster. The distribution of each neuropathological feature was examined in relation to PC1 and 2, Disease onset, rhe degree of gross brain atrophy, neuronal loss and the devlopment of senile plaques (SP) and neurofibrillary tangles (NFT) were negatively correlated with PC1. The devlopment of SP and NFT and the degree of brain athersclerosis were positively correlated with PC2. These results suggested: 1) that there were different forms of AD but no clear division of the cases into subclasses could be made based on the neuropathological criteria used; the cases showing a more continuous distribution from one form to another, 2) that disease onset was an important variable and was associated with a greater development of pathological changes, 3) familial cases were not a distinct subclass of AD; the cases being widely distributed in relation to PC1 and PC2 and 4) that there may be two forms of late-onset AD whic grade into each other, one of which was associated with less SP and NFT development but with a greater degree of brain atherosclerosis.