Communicating author:
Dr R. A. Armstrong, Vision Sciences, Aston University, Birmingham B4 7ET, UK, phone 0121-359-3611, fax 0121-333-4220,
e-mail: R.A.Armstrong@aston.ac.uk
Introduction
Alzheimer's disease (AD) is characterised by the presence of two hallmark lesions in the brain, viz., senile plaques (SP) and neurofibrillary tangles (NFT). The most important constituent of the SP is the protein amyloid-β (Aβ) [15]. Aβ is an approximately 4-kDa peptide arising by cleavage of a larger trans-membrane amyloid precursor protein (APP) present in most brain cells. The Aβ peptide exists in alternative spliced forms, the most common being Aβ42/43 found predominantly in SP and the more soluble Aβ40 found in association with blood vessels [23]. Deposition of Aβ in familial [10] and sporadic AD [30] is probably the result of processes that increase the proportion of the highly amyloidogenic peptide Aβ42/43 [16]. By contrast, NFT are intracellular inclusions composed of paired helical filaments (PHF), the most important molecular constituent of which is the microtubule protein tau. There is a single gene for tau and different isoforms result from alternative splicing and post-transcriptional changes [13]. In AD, all six isoforms of tau are abnormally phosphorylated and aggregated into PHF [9].
The 'Amyloid Cascade Hypothesis (ACH) ' [17] is the most important theory to date to explain the pathology of AD. This hypothesis proposes that there is a direct causal relationship between the pathogenesis of the SP and NFT, viz., the deposition of Aβ is the initial pathological event in AD leading to the formation of NFT, neuronal loss, and the development of dementia [17]. Despite attempts to relate the development of abnormal tau to Aβ [31], little evidence has been found that directly connects the two pathologies [6] suggesting that the processes leading to the formation of SP and NFT could be distinct phenomena [11]. Previous studies [6,7] have concluded that in the cerebral cortex in AD, SP and NFT are distributed in clusters that often exhibit a regular distribution parallel to the pia mater. If Aβ deposition leads to tau pathology as proposed by the ACH, then the clusters of SP and NFT should not be randomly distributed with reference to each other but exhibit a degree of spatial association. To test this hypothesis, the degree of spatial correlation between the SP and NFT was measured in various brain regions in cases of sporadic AD using a statistical method based on contingency tables.
Materials and methods
Cases
Six cases of sporadic AD, without evidence of a family history of the disease, were obtained from the Brain Bank, Dept. of Neuropathology, Institute of Psychiatry, King's College, London, UK. Informed consent was given for the removal of all brain tissue and followed the principles embodied in the 1964 Helsinki declaration. Patients (details in Table I) were clinically assessed and all fulfilled the 'National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer Disease and Related Disorders Association' (NINCDS/ADRDA) criteria for probable AD [32]. The histological diagnosis of AD was confirmed by the presence of widespread neocortical SP consistent with the 'Consortium to Establish a Registry of Alzheimer Disease' (CERAD) criteria [24]. All cases also had numerous NFT in the cerebral cortex and hippocampus. Apolipoprotein e (apo e) genotype is a significant risk factor for sporadic AD [28], individuals with allele e4 having an increased risk of developing the disease. In the present study, four of the cases had an apo e genotype of 3/4, one case was 3/3, and the remaining case 2/3.
Histological methods
Tissue blocks of the frontal cortex (B8) at the level of the genu of the corpus callosum, parietal cortex (B7) at the level of the splenium of the corpus callosum, occipital cortex including the calcarine sulcus (B17), superior temporal gyrus (B38), lateral occipitotemporal gyrus (B36), parahippocampal gyrus (B28), and hippocampus were taken from each case. Tissue was fixed in 10% phosphate buffered formal saline, embedded in paraffin wax, and 7 µm coronal sections were cut and stained with the Gallyas silver impregnation method [14] to reveal the SP and NFT.
Morphometric methods
In the cerebral cortex, a sample of between 64 and 128, 500x500 µm microscopic fields were located at random throughout the cortical ribbon in each brain area studied. Sample fields must not be so small that they are incapable of containing at least two individuals of the histological features under study. Conversely, fields should not be too large so that individuals of the two features occur in every field. Consideration of the densities, distribution and range of sizes of lesions suggested that a 500x500 µm field would be optimal for sampling the SP and NFT. The presence or absence of SP and NFT was recorded within each sample field. A lesion was recorded in a sample field when at least 50% of its area was present within the field. In the hippocampus, sample fields were located at random in the pyramidal cell layer and included sectors CA1 to CA4.
Statistical methods
In each brain region, the frequencies of the SP and NFT in all sample fields were first summarised as a 2x2 contingency table (Table II). From these frequencies, a 'coefficient of association' (C7) can be calculated which varies from +1, when the maximum possible co-occurrence is present, to -1 the minimum possible co-occurrence [18]. Values close to zero indicate that the frequencies of the two features are close to those that would be expected to occur by chance. The calculation of C7 depends on the relationships between the numerical values in the contingency table and is dependent on first, whether the product of the joint presences and joint absences (ad) is greater or less than the product of samples which contain one feature alone (cb) and second, on the relative magnitude of 'c' and 'b' and 'a' and 'd' (see Table II) [27]. In addition to C7, a value of chi-square (χ2) can be calculated from the frequencies in the contingency table. Chi-square is a test of the null hypothesis that the two histological features are distributed independently. Since the χ2 distribution is continuous and is being used to approximate a discrete distribution, it is necessary to make a 'correction for continuity' [26] and this statistic is given the symbol χ2. Differences in the degree of association between brain regions were tested using a one-way analysis of variance (ANOVA). Differences between cases with apo e genotype 3/4 and those of genotype 2/3 and 3/3 were tested using Student's 't' test. The relationship between C7 and the density of lesions in a brain region was tested using correlation and regression methods.
Results
The frequencies of SP and NFT in 104 randomly located sample fields in a single brain region (Case A, Superior temporal gyrus) are shown in Table III. In 43/104 fields, either both SP and NFT occur in the same field (35/104) or both lesions were absent (8/104). By contrast, there were 61/104 fields in which either SP or NFT were recorded alone. From these data, a value of C7 of -0.27 was obtained indicating a weak but negative spatial association between the SP and NFT, i.e., there was a greater tendency for the SP and NFT to occur alone rather than together in a sample field. The value of χ2 (χ2=1.51) calculated from these data was not significant suggesting that there was no statistically significant degree of association between the SP and NFT, i.e., essentially the SP and NFT are distributed independently in this region.
The values of C7 and χ2 obtained from all brain regions and cases investigated are summarised in Table IV. The value of C7 varied from -0.31 to +0.32 suggesting weak spatial associations but significant values of χ2 were observed in only 8/39 (21%) of the brain areas studied. In all regions where there was a significant degree of association between the SP and NFT, the two lesions were positively associated. There was no significant difference in the magnitude of C7 between brain regions (F=1.06, P>0.05) or between patients with different apo e genotypes (t=0.54, P>0.05). However, the value of C7 was positively correlated with the overall density of NFT (r=0.36, P<0.05) and with the total density of lesions (SP+NFT) (r=0.44, P<0.01) (Fig. 1) but not with SP alone (r=0.27, P>0.05).
Discussion
A significant spatial association between the SP and NFT was found in approximately 20% of the brain areas studied consistent with previous studies [6,19]. A number of hypotheses could explain the lack of spatial association in the majority of brain areas. First, the degree of association is dependent on field size [26] and the sample field may have been too small to have a significant chance of including both lesions. However, considering the densities, sizes, and distribution of lesions, the field size used was large enough to sample both the SP and NFT adequately. Second, the degree of association between SP and NFT could depend on the stage of the disease. For example, early in the disease process, the SP and NFT may be present in small co-localised clusters [6,7] but later, the correlation may disappear if one of the lesions becomes more abundant and widely distributed than the other. In the present study, however, both lesions become widely distributed and the degree of association between the SP and NFT becomes greater as their density increases. Third, the Gallyas stain may preferentially stain the primitive and classic subtypes of SP but not the diffuse SP [2,3]. Hence, a more significant association between the SP and NFT may be detected using methods that stain all the SP in the tissue [5]. The Gallyas-stained SP, however, contain tau positive PHF and are likely to be the most closely related population of plaques to the cellular NFT [8]. Fourth, SP and NFT may not be spatially associated within the same area of the cortex but there could be a more complex relationship between the two lesions, e.g., SP may develop on the axon terminals of NFT containing neurons [8,12,22,25,29].
The degree of association between SP and NFT (C7) in a region was positively correlated with NFT density and with the total density of both lesions but not with the density of SP alone. These results suggest that the probability of observing a spatial association between the SP and NFT is more likely in areas with larger numbers of lesions. Two histological features may appear to be positively associated if large numbers of lesions are present if there are some areas of the section that are 'unsuitable' for the development of either feature. In such a circumstance, the number of empty plots ('d' in a 2x2 table) may be large leading to a spurious positive association. This could arise in the present study during random sampling across the cerebral cortex as SP and NFT may occur with greater abundance in laminae II/III and V/VI respectively and are not randomly distributed across the section [4]. In addition, a positive association can arise if both histological features studied are common and distributed in patches throughout the entire area. If the patches are large relative to the total area sampled (a 'coarse grained' pattern) [1], then there may be a considerable area of overlap between the two features that is largely due to chance. In such areas, it may be possible to record sufficient sample fields with both SP and NFT to achieve a significant χ2. Consistent with this hypothesis, large scale clustering of SP [6] and NFT [2] is often observed in the cerebral cortex in AD. A similar hypothesis has been proposed to explain the positive spatial associations observed between SP and blood vessels in AD [20,21], viz., when SP are especially abundant, there is a high probability that a sufficient proportion of them will contact a blood vessel profile by chance.
In conclusion, the data suggest that clusters of SP and NFT are not spatially associated in the majority of areas of the cerebral cortex and hippocampus studied in cases of sporadic AD. Where positive associations are present, they are likely to be attributable to the abundance and wide distribution of the lesions in the tissue rather than reflect a causal relationship between them. Hence, it is unlikely that the formation of SP and NFT occurs in relation to either the same or closely related cell bodies as predicted by the 'amyloid cascade hypothesis'. The data therefore support the hypothesis that Aβ and tau pathology are discreet phenomena in AD [6,11].
References
1. Armstrong RA. The usefulness of spatial pattern analysis in understanding the pathogenesis of neurodegenerative disorders, with particular reference to plaque formation in Alzheimer's disease. Neurodegen 1993; 2: 73-80.
2. Armstrong RA. Clustering patterns of neurofibrillary tangles in Alzheimer's disease. Alz Rep 1999; 2: 151-154.
3. Armstrong RA, Myers D. b/A4 deposits and their relationship to senile plaques in Alzheimer's disease. Neuroreport 1992; 3: 262-264.
4. Armstrong RA, Slaven A. Does the neurodegeneration of Alzheimer's disease spread between the visual cortical areas B17 and B18 via the feedforward or feedback short cortico-cortical projections? Neurodegen 1994; 3: 191-196.
5. Armstrong RA, Myers D, Smith CU, Cairns N, Luthert PJ. The spatial pattern of senile plaques, neurofibrillary tangles and A4 deposits in Alzheimer's disease. Neurosci Res Commun 1992; 10: 27-33.
6. Armstrong RA, Myers D, Smith CU. The spatial patterns of plaques and tangles in Alzheimer's disease do not support the 'cascade hypothesis'. Dementia 1993; 4: 16-20.
7. Armstrong RA, Myers D, Smith CUM. The spatial patterns of b/A4 deposit subtypes in Alzheimer's disease. Acta Neuropathol 1993; 86: 36-41.
8. Armstrong RA, Cairns NJ, Lantos PL. Degeneration of cortical neurons associated with diffuse b-amyloid (Aβ) deposits in Alzheimer's disease. Neurosci Res Commun 1999; 24: 89-97.
9. Buee-Scherrer V, Hof PR, Buee L, Leveugle B, Vermersch P, Perl DP, Olanow CW, Delacourte A. Hyperphosphorylated tau proteins differentiate corticobasal degeneration and Pick's disease. Acta Neuropathol 1996; 91: 351-359.
10. Chartier-Harlin MC, Crawford F, Houlden H, Warren A, Hughes D, Fidani L, Goate A, Rossor M, Roques P, Hardy J, Mullan M. Early-onset Alzheimer's disease caused by mutations at codon 717 of the b-amyloid precursor protein gene. Nature 1991; 353: 844-846.
11. Cras P, Kawai M, Lowery D, Gonzalez-DeWhitt P, Greenberg B, Perry G. Senile plaque neurites in Alzheimer's disease accumulate amyloid precursor protein. Proc Nat Acad Sci USA 1991; 88: 7552-7556.
12. De Lacoste MC, White CL 3rd. The role of cortical connectivity in Alzheimer's disease pathogenesis: a review and model system. Neurobiol Aging 1993; 14: 1-16.
13. Dustin P, Brion JP, Flament-Durand J. What's new in the pathology of neuronal cytoskeleton: the significance of neurofibrillary tangles. Pathol Res Pract 1992; 188: 248-253.
14. Gallyas F. Silver staining of Alzheimer neuropathology changes by means of physical development. Acta Morphol Acad Sci Hung 1971; 19: 1-8.
15. Glenner GG, Wong CW. Alzheimer's disease and Down's syndrome: sharing of a unique cerebrovascular amyloid fibril protein. Biochem Biophys Res Commun 1984; 122: 1131-1135.
16. Greenberg BD. The COOH-terminus of the Alzheimer amyloid Aβ peptide: Differences in length influence the process of amyloid deposition in Alzheimer brain, and tell us something about relationships among parenchymal and vessel-associated amyloid deposits. Amyloid 1995; 21: 195-203.
17. Hardy JA, Higgins GA. Alzheimer's disease: The Amyloid Cascade Hypothesis. Science 1992; 256: 184-185.
18. Hurlbert SH. A coefficient of interspecific association. Ecology 1969; 50: 1-9.
19. Hyman BT, Tanzi RE. Amyloid, dementia and Alzheimer's disease. Curr Opin Neurol Neurosurg 1992; 5: 88-93.
20. Kawai M, Kalaria RN, Harik SI, Perry G. The relationship of amyloid plaques to cerebral capillaries in Alzheimer's disease. Amer J Pathol 1990; 137: 1435-1446.
21. Luthert PJ, Williams JA. A quantitative study of the co-incidence of blood vessels and A4 protein deposits in Alzheimer's disease. Neurosci Lett 1991; 126: 110-112.
22. Mann DMA. The neuropathology of Alzheimer's disease: a review with pathogenetic, aetiological and therapeutic considerations. Mech Ageing Dev 1985; 31: 213-255.
23. Miller DL, Papayannopoulos IA, Styles J, Bobin SA, Lin YY, Biemann K, Iqbal K. Peptide compositions of the cerebrovascular and senile plaque core amyloid deposits of Alzheimer's disease. Arch Biochem Biophys 1993; 301: 41-52.
24. Mirra SS, Heyman A, McKeel D, Sumi SM, Crain BJ, Brownlee LM, Vogel FS, Hughes JP, van Belle G, Berg L. The Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Part II. Standardization of the neuropathologic assessment of Alzheimer's disease. Neurology 1991; 41: 479-486.
25. Pearson RCA, Esiri MM, Hiorns RW, Wilcock GK, Powell TPS. Anatomical correlates of the distribution of the pathological changes in the neocortex in Alzheimer's disease. Proc Natl Acad Sci USA 1985; 82: 4531-4534.
26. Pielou EC. An Introduction to Mathematical Ecology. John Wiley, New York 1969; pp. 159-178.
27. Ratliff RD. A correction of Cole's C7 and Hurlbert's C8 coefficients of interspecific association. Ecology 1982; 63: 1605-1606.
28. Saunders AM, Strittmatter PH, Schmechel D, St. George-Hyslop PH, Pericak-Vance MA, Joo SH, Rose BL, Gasella JF, Crapper-MacLachlan, Albersts MJ, Hulette C, Crain B, Goldgaber D, Roses AD. Association of apolipoprotein E allele E4 with late-onset familial and sporadic Alzheimer's disease. Neurology 1993; 43: 1467-1472.
29. Senut MC, Roudier M, Davous P, Fallet-Bianco C, Lamour Y. Senile dementia of the Alzheimer type: is there a correlation between entorhinal cortex and dentate gyrus lesions? Acta Neuropathol 1991; 82: 306-315.
30. Sisodia SS, Koo EH, Beyreuther K, Unterbeck A, Price DL. Evidence that b-amyloid protein in Alzheimer's disease is not derived by normal processing. Science 1990; 248: 492-495
31. Smith MA, Siedlak SL, Richey PL, Mulvihill P, Ghiso J, Frangione B, Tagliavini F, Giaccone G, Bugiani O, Praprotnik D, Kalaria RN, Perry G. Tau protein directly interacts with the amyloid b-protein precursor: implications for Alzheimer's disease. Nat Med 1995;
1: 365-369.
32. Tierney MC, Fisher RH, Lewis AJ, Zorzitto ML, Snow WG, Reid DW, Nieuwstraten P. The NINCDS-ADRDA Work Group criteria for the clinical diagnosis of probable Alzheimer's disease: a clinicopathologic study of 57 cases. Neurology 1988; 38: 359-364.
