Aberrant accentuation of neurofibrillary degeneration in the hippocampus of Alzheimer's disease with amyloid precursor protein 717 and presenilin-1 gene mutations

Journal of the Neurological Sciences 234 (2005) 55 – 65 www.elsevier.com/locate/jns

Aberrant accentuation of neurofibrillary degeneration in the hippocampus of Alzheimer’s disease with amyloid precursor protein 717 and presenilin-1 gene mutations Satoru Sudoa,*, Masaki Shiozawab, Nigel J. Cairnsc, Yuji Wadaa a

Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, 23 Shimoaizuki, Matsuoka-cho, Fukui 910-1193, Japan b Division of Clinical Research, National Kikuchi Hospital, Kumamoto, Japan c Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, USA Received 17 December 2004; received in revised form 24 February 2005; accepted 8 March 2005 Available online 8 June 2005

Abstract This study reports correlation of the hippocampal neurofibrillary tangles (NFT) density with beta-amyloid (Ah) precursor protein (APP) 717 mutation, presenilin (PS)-1 mutation and apolipoprotein E (Apo-E) e4 alleles (E4), being graded as 3 forms (no-E4, one-E4 and two-E4) in autopsied brains from patients with familial and non-familial Alzheimer’s disease (AD). We studied the density of NFT-free neurons, intracellular NFT (I-NFT), extracellular NFT (E-NFT) and total NFT (I-NFT plus E-NFT) in the six hippocampal subdivisions: cornu ammonis (CA) 1 – CA4, subiculum and entorhinal cortex. The APP mutation cases showed significantly higher total NFT density in the CA1 – CA2 region, and the PS-1 mutation cases also showed higher density of total NFT in the CA1 – CA3 than non-familial cases. Moreover, high densities of the E-NFT contributed to these high total NFT densities. Non-familial AD cases showed a stereotypical NFT distribution with entorhinal accentuation in the hippocampus irrespective of E4 frequency. Thus, APP and PS-1 mutations predominantly affect the CA regions with profound neurodegeneration, which contributes early and severe clinical features of familial AD. D 2005 Elsevier B.V. All rights reserved. Keywords: Alzheimer’s disease; Amyloid precursor protein; Apolipoprotein; Neurofibrillary tangles; Presenilin-1

1. Introduction Alzheimer’s disease (AD) is characterized by progressive cognitive dysfunctions, and beta-amyloid (Ah) peptide deposits forming the senile plaques (SP) and neurofibrillary tangles (NFT) are the key pathological changes of AD. NFT are predominantly distributed in the mesial temporal lobe and consist of hyperphosphorylated microtubule-associated protein tau that forms the paired helical filaments in selected neuronal populations [1– 3]. NFT develop in the neuronal cytoplasm, designated intracellular NFT (I-NFT), and in association with neuronal death they remain in the neuropil as ghost tangles, which are called extracellular NFT (ENFT) [4]. NFT usually spread in a stereotypical pattern in * Corresponding author. Tel.: +81 776 618363; fax: +81 776 618136. E-mail address: [email protected] (S. Sudo). 0022-510X/$ - see front matter D 2005 Elsevier B.V. All rights reserved. doi:10.1016/j.jns.2005.03.043

the brain, classified into six stages [5]. NFT initially occur in the transentorhinal cortex (entorhinal stage: stages I and II), extend to the limbic structure (limbic stage: stages III and IV) and finally spread to the neocortex (stages V and VI), which is believed to correlate more intimately with clinical features of AD than Ah burden [6]. Recent studies have proved that intraneuronal Ah deposits precede tangle formation and are a crucial trigger for NFT development [7,8]. In addition, brains from Ahimmunized patients with AD showed marked decreases in amounts of Ah and abnormal neuritis [9– 11]. Therefore, Ah is considered to play a role in AD-associated abnormal tau phosphorylation. The Ah is generated by amyloid precursor protein (APP) and its gene mutations enhance intraneuronal and extraneuronal Ah secretion, which leads to quantitative and qualitative alteration of Ah deposits and accelerates age at onset [12]. Presenilin (PS) gene mutations elevate the

56

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

plasma level of the aggregated form of Ah [13], and AD patients with PS-1 mutation had much more severe Ah1 – 42 deposits and astrocytosis than non-familial AD patients [14]. Others also reported that brains from patients with mutations on PS-1 and APP717 showed area-specific Ah deposits [15 – 18]. Apolipoprotein E (Apo-E) is involved in non-familial AD. Apo-E epsilon 4 allele (E4) is a well-known risk factor for the development of AD among the allelic variations [19,20]. E4 gene frequency was significantly associated with Ah deposits and associated with an increased NFT density [21 –28], and Apo-E isoforms directly interact with tau protein, alter phosphorylation status and cause phosphorylated tau aggregates that form NFT [29 – 31]. Although direct association of SP and NFT with E4 is otherwise equivocal [21,32 –34], severity of NFT is speculatively influenced by gene mutations of APP and PS and E4 frequency. In this context, we examined the difference in NFT severity in the hippocampal subdivisions between familial AD with APP717 and PS-1 mutation and Apo-E genotype-verified non-familial AD, and described genotype-specific accentuation of NFT in the hippocampal formation.

2. Subjects and methods Forty-three brains from a collection of post mortem brain tissues from the Brain Bank, Department of Neuropatho-

logy, Institute of Psychiatry, London, U.K. and 3 from Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, Fukui, Japan [35,36], were enrolled in this study. All cases were clinically and pathologically assessed and fulfilled the NINDS-ADRDA criteria and the CERAD criteria [37,38]. Six age-matched control cases were derived from a collection of the Brain Bank. Six cases with APP717 mutation (mean age at onset T S.D., 55.3 T 8.7 years old; mean duration T S.D., 10.3 T 5.1 years) and 7 cases with PS-1 mutation (mean age at onset, 43.9 T 8.5 years old; mean duration, 9.1 T 5.1 years) were identified by direct sequence analysis of genome DNA with brain tissue (Table 1). For Apo-E genotyping, genomic DNA was extracted from frozen brain tissue by the standard method [39]. The PCR was carried out on 4 Al of DNA using the following oligonucleotide primers: 5¶-TCCAAGGAGCTGCAGGCGGCGCA-3¶ and 5¶-ACAGAATTCGCCCCGGCCTGGTACACTGCCA-3¶ [40]. Positive and negative controls were used in each experiment. The PCR product (227 bp) was checked by agarose gel electrophoresis using 5 Al of each amplified sample. The Apo-E genotype was determined by digesting 8 Al of the amplified sample at 37 -C for 3 h using the restriction enzyme HhaI. Nondenaturing polyacrylamide gel electrophoresis was used to separate the digested fragments in each sample, which were then visualized by silver staining. Seven cases with no Apo-E epsilon 4 allele

Table 1 Clinical and genotypic data of control cases and familial Alzheimer’s disease cases with APP717 and PS-1 mutation Case number

Sex

Control cases C1469 C1498 C1643 C1650 C1669 C1758 Mean T S.D.

F M F M M F

Onset (years old)

Age at death (years old)

Duration (years)

69 75 69 71 63 79 71.0 T 5.5

Brain weight (g)

E4 allele frequency

1210 1250 1210 1200 1265 1250 1230.8 T 27.2

n.a. n.a. n.a. n.a. n.a. n.a.

Mutation site

Familial AD with APP717 mutation 126/90 F 53 185/93 M 59 211/95 M 40 238/96 F 59 312/96 F 66 51/97 F 55 Mean T S.D. 55.3 T 8.7

59 70 61 69 74 62 65.8 T 6.0

6 11 21 10 8 7 10.3 T 5.1

n.a. n.a. 1170 1160 1084 1070 1121.0 T 51.3

0 0 0 n.a. 0 0

V7171 V7171 V717G V7171 V7171 V7171

Familial AD with PS-1 mutation 236/91 F 283/92 F 114/97 M 29/98 M 148/99 F 93-049 F 96-061 M Mean T S.D.

61 54 58 42 65 47 44 53.0 T 8.9

6 12 19 3 8 9 7 9.1 T 5.1

1020 840 1296 1051 516 775 880 911.1 T 245.0

0 0 n.a. n.a. n.a. 0 0

I143F S290C Delta exon 9 Delta exon 9 E280G Ala260Val Ala260Val

55 42 39 39 57 38 37 43.9 T 8.5

The term ‘‘n.a.’’ indicates ‘‘not available’’ clinical information.

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

(no-E4), 16 cases with heterozygosis for the Apo-E epsilon 4 allele (one-E4) and 10 cases with homozygosis for the Apo-E epsilon 4 allele (two-E4) were enrolled in this study (Table 2). Five of six APP cases were no-E4 and one APP case was not available, and four of seven PS-1 cases were no-E4 and three PS-1 cases were not available. The brain tissues were fixed in 10% buffered formal saline and embedded in paraffin wax. For each case, coronal 20 Amthick and 5 Am-thick sections were taken through the hippocampal formation at the level of the lateral geniculate body. Twenty micrometer-thick sections were stained with Klu¨ ver – Barrera stain for examination of neuronal cytoarchitecture, myelin and tissue changes, and adjacent 5 Am sections were stained with double labeling using the

57

Gallyas silver impregnation technique [41], a highly sensitive method for NFT [42], and hematoxylin –eosin (HE) for counting the number of NFT-free neurons, I-NFT and E-NFT. Since neuronal cellular changes are invisible with the Gallyas silver impregnation technique, we employed Gallyas-HE double staining to distinguish the I-NFT from the E-NFT. The hippocampal cortex was divided into six regions, the cornu ammonis (CA) 1– CA4, subiculum and entorhinal cortex (Fig. 1), based on Lorente de No`’s and Duvernoy’s classification [43,44]. Neurons with visible nucleoli but without NFT were regarded as NFT-free neurons. NFT within the visible neuronal cytoplasm were regarded as I-NFT. The E-NFT were recognized as coarsely fibrillary structures outside of

Table 2 Demographic data of apolipoprotein-E genotypes of the non-familial Alzheimer’s disease cases Case number

Sex

Onset (years old)

Age at death (years old)

Duration (years)

Brain weight (g)

E4 allele frequency

176/89 151/92 5/96 13/96 44/96 225/96 00-312 Mean T S.D.

F F M M F M F

67 73 n.a. 82 76 71 71 73.3 T 5.2

71 81 89 85 84 81 79 81.4 T 5.7

4 8 n.a. 3 8 10 8 6.8 T 2.7

960 942 1406 1180 1132 n.a. 1080 1116.7 T 169.9

0 0 0 0 0 0 0

14/90 135/91 161/92 191/92 12/93 24/94 45/94 130/94 141/94 148/94 348/94 87/95 223/95 308/95 90/96 250/96 Mean T S.D.

F M M F F M F F F M M F M F M F

79 66 70 78 79 70 64 72 67 n.a. 52 66 56 69 n.a. 76 69.7 T 8.5

82 76 81 86 86 78 71 79 78 82 59 73 67 77 75 82 76.4 T 7.0

3 10 11 8 7 8 7 7 11 n.a. 7 7 11 8 n.a. 6 7.9 T 2.2

997 1392 1140 1019 1083 1135 1012 1044 1078 n.a. 1100 1094 922 1044 1092 987 1075 T 105.5

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

197/88 131/89 91/92 302/92 309/92 127/93 329/94 53/95 96/95 240/95 Mean T S.D.

F F F F F M F F M F

75 75 66 77 57 75 68 63 79 n.a. 70.6 T 7.4

81 78 78 80 73 79 82 76 86 75 78.8 T 3.7

6 3 12 3 16 4 14 13 7 n.a. 8.7 T 5.1

1205 1185 1049 982 1054 1313 912 867 1213 1245 1102.5 T 151.2

2 2 2 2 2 2 2 2 2 2

70.7 T 7.5

78.2 T 6.1

7.9 T 4.0

1092.4 T 131.0

Whole cases of non-familial AD Mean T S.D.

The term ‘‘n.a’’ indicates ‘‘not available’’ clinical information.

58

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

cases (mean T S.D., 43.9 T 8.5 years) was lower than that of no-E4 cases (73.3 T 5.2 years, p < 0.0001), one-E4 cases (69.7 T 8.5 years, p < 0.0001) and two-E4 cases (70.6 T 7.4 years, p < 0.0001). Similarly, age at onset of APP mutation cases (55.3 T 8.7 years) was lower than that of no-E4 cases ( p = 0.0003), one-E4 cases ( p = 0.0010) and two-E4 cases ( p = 0.0007). There was no difference in age at onset between APP mutation cases and PS-1 mutation cases ( p = 0.0116) and among the E4 genotypes. Difference in disease duration among these non-familial AD cases, APP and PS-1 mutation cases was insignificant ( F = 0.689, p = 0.6044). 3.1. Difference in NFT density in the hippocampal subdivisions in non-familial AD and APP and PS-1 mutation cases

Fig. 1. Subdivisions of the hippocampal formation at the level of the lateral geniculate body. CA, cornu ammonius (Klu¨ver – Barrera stain).

neurons in the neuropil. In each subdivision, two of the authors (S.S. and M.S.) independently counted NFT-free neurons, I-NFT and E-NFT using a light microscope blind to all aspects of subject identity. Each visual field (10times objective and 10-times eye piece, 0.0625 mm2) was monitored with an Olympus BX 50 on the sectors CA1 – CA4, subiculum and entorhinal cortex. The density of impregnated structures was determined by averaging the densities in 10 non-overlapping visual fields and was expressed as the number per mm2. Density of total NFT was calculated as I-NFT density plus E-NFT density. Statistical analysis was performed by correlation analysis and analysis of variance (ANOVA) followed by Bonferroni’s corrected multiple comparisons with StatView (Abacus Concepts Inc., Berkeley, CA) for Microsoft Windows (Microsoft Corp., Redmond, WA). Statistical significance was set at p < 0.005 for difference in NFT density by genotype and age at onset between familial and non-familial AD cases and p < 0.0033 for difference in NFT density by hippocampal subdivision for Bonferroni’s corrected multiple comparisons and p < 0.05 for correlation analysis.

Table 3 shows average values and standard errors of the mean of I-NFT, E-NFT and total-NFT densities in every hippocampal subdivision among cases of familial AD with APP and PS-1 mutation and non-familial AD. NFT densities were compared in the six hippocampal subdivisions to confirm a gradient of NFT densities according to the NFT staging proposed by Braak and Braak [5]. In non-familial AD cases (Fig. 3A – C), density of INFT, E-NFT and total NFT showed the same distribution pattern in the six hippocampal subdivisions. ANOVA showed regional significant difference in I-NFT ( F = 27.175, p < 0.0001), E-NFT ( F = 26.098, p < 0.0001) and total NFT ( F = 38.485, p < 0.0001). Bonferroni’s multiple comparisons revealed that the entorhinal cortex showed the highest densities of I-NFT, E-NFT and total NFT. The CA1 and subiculum showed the second highest densities of

3. Results I-NFT and E-NFT were visualized clearly enough to perform a quantitative study with Gallyas-HE staining (Fig. 2). NFT were stained dark brown and E-NFT tended to be more lightly stained than I-NFT. Cored and uncored SP and granulovacuolar degeneration were also stained. ANOVA followed by Bonferroni’s corrected multiple comparisons showed that age at onset of the PS-1 mutation

Fig. 2. Neurofibrillary tangles (NFT)-free neurons (*), intracellular NFT (black arrows) and extracellular NFT (white arrow) in CA1 with double staining of Gallyas silver impregnation technique and hematoxylin and eosin stain (400).

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

59

Table 3 Average values and standard errors of the mean of the intracellular NFT (I-NFT), extracelluler NFT (E-NFT) and total NFT densities in every hippocampal subdivisions among cases of familial Alzheimer’s disease with APP and PS-1 mutation and non-familial Alzheimer’s disease cases. (/mm2) CA4

Non-familial AD No-E4 One-E4 Two-E4 APP PS-1

CA3

I-NFT

E-NFT

Total NFT

I-NFT

E-NFT

Total NFT

10.8 T 1.7 6.9 T 2.1 10.3 T 3.0 14.4 T 3.0 22.9 T 3.3 14.1 T 3.0

11.6 T 2.1 5.9 T 2.6 8.70 T 2.2 20.2 T 5.0 18.9 T 5.5 26.3 T 4.7

22.4 T 3.6 12.8 T 4.5 19.0 T 5.1 34.6 T 7.1 41.9 T 8.0 40.5 T 6.8

9.8 T 1.9 4.6 T 1.5 8.6 T 3.0 15.4 T 4.0 18.7 T 3.8 15.5 T 2.7

10.5 T 2.5 4.1 T 2.4 6.8 T 2.3 21.1 T 6.4 24.0 T 6.5 31.1 T 5.3

20.3 T 4.3 8.7 T 3.7 15.3 T 5.1 36.5 T 9.9 42.7 T 7.5 46.6 T 7.7

CA2

Non-familial AD No-E4 One-E4 Two-E4 APP PS-1

CA1

I-NFT

E-NFT

Total NFT

I-NFT

E-NFT

Total NFT

16.6 T 3.1 6.9 T 2.4 20.6 T 5.4 17.1 T 4.7 41.1 T 8.0 21.9 T 6.1

19.0 T 3.3 15.1 T 8.6 13.3 T 2.9 31.0 T 7.2 55.2 T 11 74.5 T 21

35.7 T 5.6 21.9 T 9.7 33.9 T 7.9 48.1 T11 96.3 T 18 96.5 T 23

29.7 T 2.5 20.1 T 7.4 29.6 T 2.9 36.6 T 4.3 45.3 T 4.1 31.7 T 8.6

52.0 T 6.7 29.7 T 9.6 43.1 T 7.2 81.8 T 14 123 T 16 102 T 19

81.7 T 8.2 49.8 T 11 72.7 T 9.8 118 T 15 168 T 15 133 T 21

I-NFT

E-NFT

Total NFT

I-NFT

E-NFT

Total NFT

30.6 T 3.4 23.5 T 12 31.6 T 4.7 35.2 T 2.5 30.4 T 3.4 57.4 T 8.9

55.1 T 9.6 19.9 T 11 52.5 T 11 83.8 T 21 16.8 T 4.3 45.3 T 12

85.7 T 11 43.5 T 20 84.0 T 14 119 T 21 47.2 T 6.4 103 T 15

51.0 T 4.4 38.4 T 14 52.5 T 3.8 57.3 T 8.8 39.3 T 3.8 57.4 T 12

93.2 T 9.1 77.1 T16 88.9 T 12 111 T 20 49.5 T 9.9 42.5 T 6.1

144 T 10 116 T 25 141 T14 169 T 16 88.8 T 11 99.9 T 14

Subculum

Non-familial AD No-E4 One-E4 Two-E4 APP PS-1

Entorhinal

NFT and no difference in NFT density was found in the CA2 –CA4 regions. Therefore, NFT density in the nonfamilial AD cases showed the following grading: entorhinal cortex > subiculum = CA1 > CA2 = CA3 = CA4. In contrast, the NFT densities of APP and PS-1 mutation cases showed bidirectional distribution. In APP mutation cases (Fig. 4A –C), I-NFT density of CA1 was higher than that of CA3 ( p = 0.0004) and CA4 ( p = 0.0021) and I-NFT density of CA2 was higher than that of CA3 ( p = 0.0021). Moreover, E-NFT density of the CA1 was the highest (CA2: p = 0.0002, CA3: p < 0.0001, CA4: p < 0.0001, entorhinal cortex: p < 0.0001, subiculum: p < 0.0001). Similar results were found for the total NFT density (CA2: p < 0.0001, CA3: p < 0.0001, CA4: p < 0.0001, entorhinal cortex: p < 0.0001, subiculum: p < 0.0001). In PS-1 mutation cases (Fig. 5A –C), significant differences in I-NFT ( F = 6.480, p = 0.0002), E-NFT ( F = 4.670, p = 0.0022) and total NFT ( F = 4.915, p = 0.0016) were obtained. I-NFT density in entorhinal cortex was higher than that of CA2 ( p = 0.0028), CA3 ( p = 0.0006) and CA4 ( p = 0.0004). Similarly, I-NFT density in subiculum was higher than that of CA2 ( p = 0.0028), CA3 ( p = 0.0006) and CA4 ( p = 0.0004). In contrast, E-NFT density was relatively high in CA1 where E-NFT density was higher than that of the CA3 ( p = 0.0007) and CA4 ( p = 0.0003). This was also found in the total NFT density; total NFT density of CA1 was higher than that of CA3 ( p = 0.0006) and CA4 ( p = 0.0003).

3.2. Difference in NFT density between non-familial AD and APP and PS-1 mutation cases In the I-NFT (Fig. 6A), significant difference was found in the CA4 ( F = 2.667, p = 0.0457), CA2 ( F = 3.208, p = 0.0222) and subiculum ( F = 3.090, p = 0.0259). Bonferroni’s corrected multiple comparisons showed that the INFT density of APP mutation cases was higher than that of no-E4 cases in the CA4 ( p = 0.0048) and CA2 ( p = 0.0011) and I-NFT density of PS-1 mutation cases was higher than that of no-E4 cases in the subiculum. In the E-NFT (Fig. 6B), significant differences were found in the CA4 ( F = 4.480, p = 0.0043), CA3 ( F = 6.155, p = 0.0006), CA2 ( F = 7.408, p = 0.0001), CA1 ( F = 8.362, p < 0.0001) and entorhinal cortex ( F = 3.112, p = 0.0252). PS-1 mutation cases had higher E-NFT density than no-E4 and one-E4 cases in the CA4 (no-E4: p = 0.0023, one-E4: p = 0.0019) and CA3 (no-E4: p = 0.0006, one-E4: p = 0.0003). In the CA2, APP mutation cases showed higher E-NFT density than one-E4 cases ( p = 0.0034) and PS-1 mutation cases showed higher E-NFT density than no-E4 ( p = 0.0003), one-E4 ( p < 0.0001) and two-E4 cases ( p = 0.0031). In the CA1, APP and PS-1 mutation cases showed higher E-NFT densities than no-E4 (APP: p < 0.0001, PS-1: p = 0.0010) and one-E4 (APP: p < 0.0001, PS-1: p = 0.0015). The subiculum showed no significant difference in E-NFT density among non-familial AD, PS-1 and APP mutation cases, but in the entorhinal

60

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

no-E4 ( p < 0.0001), one-E4 ( p < 0.0001), two-E4 ( p = 0.0002) and APP mutation cases ( p = 0.0028), which indicated that the density of NFT-free neurons of the PS-1 mutation cases was the lowest. PS-1 mutation also showed lower density of NFT-free neurons than one-E4 in the CA2 ( p = 0.0006) and no-E4 ( p = 0.0013) in the CA1. APP mutation cases showed lower NFT-free density than no-E4 in the CA1 ( p = 0.0036) and higher NFT-free neuron density than two-E4 cases in the subiculum ( p = 0.0024). 3.3. Correlation between E-NFT density and NFT-free neuron density Correlation analysis between E-NFT density and NFT-free neuron density was performed in every hippocampal subdivisions. In PS-1 mutation cases, a significant inverse correlation was seen in the CA3 (r = 0.879, p = 0.0070), CA2 (r = 0.887, p = 0.0048) and CA1 (r = 0.952, p = 0.0002). In APP mutation cases, only the subiculum

Fig. 3. Mean density of (A) I-NFT, (B) E-NFT and (C) total NFT in the hippocampal subdivisions in non-familial Alzheimer’s disease. *p < 0.0033 versus CA4, CA3 and CA2, **p < 0.0033 versus all other groups.

cortex PS-1 mutation cases showed lower density of E-NFT than two-E4 cases ( p = 0.0043). In the total NFT (Fig. 6C), significant differences were found in the CA3 ( F = 4.952, p = 0.0024), CA2 ( F = 5.991, p = 0.0007) and CA1 ( F = 9.103, p < 0.0001). PS-1 mutation cases showed higher total NFT density than no-E4 cases and one E4 cases in the CA3 (no-E4: p = 0.0025, one-E4: p = 0.0031), CA2 (no-E4: p = 0.0010, one-E4: p = 0.0011) and CA1 (no-E4: p = 0.0009, one-E4: p = 0.0037). APP mutation cases also showed higher total NFT density in the CA2 (no-E4: p = 0.0016, one-E4: p = 0.0020) and CA1 (noE4: p < 0.0001, one-E4: p < 0.0001). E4 dose effect was only found in the total NFT density in the CA1 (no-E4 and twoE4: p = 0.0026). In the NFT-free neurons (Fig. 6D), the CA3 ( F = 4.952, p = 0.0024), CA2 ( F = 5.991, p = 0.0007), CA1 ( F = 9.103, p < 0.0001) and subiculum ( F = 3.007, p = 0.0289) showed significant differences. In the CA3, the density of NFT-free neurons of the PS-1 mutation cases was lower than those of

Fig. 4. Mean density of (A) I-NFT, (B) E-NFT and (C) total NFT in the hippocampal subdivisions in Alzheimer’s disease with APP mutation. (A) *p < 0.0033 versus CA3, **p < 0.0033 versus CA4 and CA3, (B), (C) **p < 0.0033 versus all other groups.

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

Fig. 5. Mean density of (A) I-NFT, (B) E-NFT and (C) total NFT in the hippocampal subdivisions in Alzheimer’s disease with PS-1 mutation. *p < 0.0033 versus CA4 and CA3, **p < 0.0033 versus CA4, CA3 and CA2.

showed significant inverse correlation (r = 0.880, p = 0.0171). The non-familial AD cases showed significant inverse correlation in the CA4 (r = 0.790, p < 0.0001), CA3 (r = 0.526, p = 0.0014), CA2 (r = 0.837, p < 0.0001), CA1 (r = 0.518, p = 0.0017), subiculum (r = 0.685, p < 0.0001) and entorhinal cortex (r = 0.644, p < 0.0001).

4. Discussion This study provided the contrasting NFT distribution between non-familial AD and familial AD. The gradient of density of NFT, either that of I-NFT or E-NFT, agrees well with the order of NFT development in non-familial AD [5], and findings that the entorhinal cortex is an initial site for NFT was exhaustively examined and established [45]. In contrast, topographical accentuation of NFT within the CA regions is considered to be a characteristic NFT pathology

61

in familial AD, in which PS-1 mutation affected the CA1 – CA3 regions and APP mutation affected the CA1 – CA2 regions with an increase in total NFT density. The I-NFT densities of APP and PS-1 mutation cases predominated only in the CA2 and CA4, respectively, compared with noE4 cases. These findings indicate that high densities of ENFT contributed to high densities of total NFT of the APP and PS-1 mutations. E4 frequency effect on the regional density of NFT was observed only in the total NFT density in CA1 between no-E4 and two-E4. Thus, the effects of PS1 or APP mutation greatly surpassed the E4 frequency effect and can be characterized by an abundance of E-NFT. Neither I-NFT density nor total NFT density in the entorhinal cortex showed a significant difference, and difference in E-NFT density in the entorhinal cortex was discrete between non-familial AD and familial AD. The entorhinal cortex is known as an initial target region for NFT in non-familial AD, but this is not directly applicable to NFT development in familial AD. The direct mechanism of APP and PS-1 mutations in accelerating neurofibrillary degeneration is not fully elucidated, but mutation of APP717 and APP716 has been shown to promote the synthesis of Ah1 – 42 and Ah1 – 40 respectively [46,47], and to accelerate SP formation [12]. An APP mutant transgenic mouse study showed extraordinary numbers of NFT in mouse brains [48], and a pathological study of a familial AD patient with APP717 mutation disclosed severe and unusual accentuation of NFT in the primary visual cortex [49]. PS-1 mutations also cause an increase in production and deposits of Ah. In particular, AD cases with P117L, L235P and P436Q mutations showed markedly elevated Ah1 – 42 and decreased Ah1 – 40 [50,51]. A recent study showed that PS-1 contained the active site of the proteolytic enzyme, gamma-secretase, which generates the Ah peptide by protein cleavage of the APP [52]. Therefore, mutations of APP and PS-1 work differently on Ah overproduction. Intraneuronal Ah deposits have been shown to be deposited prior to NFT formation and to be a crucial trigger for NFT development [7,8]. Therefore, mutations of APP and PS-1 are indirectly and differently linked to NFT development. This may result in unusual accentuation of NFT in the CA in the APP and PS-1 mutation cases. Although we could not find the pathogenesis for regional vulnerability to NFT in the CA, extraentorhinal NFT accentuation has been reported in the CA1subiculum regions in senile dementia of NFT [53] and CA1 –CA2 – subiculum regions in a subset of normal elderly [54]. As in both conditions cognitive ability was not so severely disturbed and NFT density was low compared with familial AD [55], there is a possibility that severe and early intellectual decline in familial AD might be due to the profound neurodegeneration rather than affected regions. In the non-familial AD cases, differences in NFT density were found only in the CA1 between no-E4 and two-E4 cases; E4 genotypes thus had little influence on NFT density. E4 frequency effect on the AD pathology has been

62

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

I-NFT density ( / mm2)

A

*

80

*

60 40

*

20 0

CA4

CA3

CA2

E-NFT density ( / mm2)

B 160 140 120 100 80 60 40 20 0

SUB

* *

ENT

*

* * *

*

CA4

CA3

CA2

C total NFT density ( / mm2)

CA1

CA1

SUB

ENT

SUB

ENT

* *

200

*

* *

160 120

*

80 40 0

CA4

NFT-free neuron density ( / mm2)

D

CA3

CA2

CA1

280 240

*

200

* 160

*

*

CA1

SUB

120 80 40 0

CA4

CA3

CA2

ENT

Fig. 6. Mean density of (A) I-NFT, (B) E-NFT, (C) total NFT and (D) NFT-free neuron in the hippocampal subdivisions in non-familial Alzheimer’s disease in association with the frequency of E4 allele and in familial Alzheimer’s disease with APP mutation and PS-1 mutation. (g); control cases, ( ); no Apo-E E4 allele, ( ); one Apo-E E4 allele, ( ); two Apo-E E4 alleles, ( ); APP mutation, (n); PS-1 mutation. *p < 0.005.

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

considered to cause an increase in SP density [56 – 61], and it is still controversial whether or not the severity of NFT pathology is correlated with E4 frequency [22,62,63]. Data from the present study failed to show a graded severity of NFT pathology according to E4 frequency even in the entorhinal cortex. An Apo-E immunohistochemical study reported down-regulation of Apo-E immunoreactivity in the hippocampus of AD brains and a lack of quantifiable relationship between intensity of Apo-E expression and density of SP and NFT [64]. This down-regulation of Apo-E is interpreted as a reduced ability of the reactive and regenerative mechanisms in AD brains [65], and Apo-E impairs hippocampal plasticity due to impairment of neuronal synaptogenesis [66]. The present study seems to be compatible with these previous studies. The degree of neuronal loss was prominent in the PS-1 mutation cases in CA1 – CA3 and the APP mutation cases in CA1 compared with non-familial AD cases. E-NFT formation is one of the causes of neuronal loss, in addition to apoptosis, and it is expected that E-NFT density is correlated with NFT-free neuron density in every hippocampal subdivision. The non-familial AD cases showed a significant inverse correlation in every hippocampal subdivision, but APP mutation cases showed it only in the subiculum and PS-1 cases in the CA1 –CA3 regions. These regions nearly corresponded to the profound neuronal loss lesions in the PS-1 and APP mutation cases and both mutation cases showed no inverse correlation in the entorhinal cortex. This finding implies that the neuronal loss is independent from E-NFT formation in the entorhinal cortex because other factors such as apoptosis and inflammatory changes play a role in neuronal loss in these regions as well as E-NFT. Indeed APP and PS-1 mutations directly cause neuronal apoptosis [67]. Moreover, mutations in APP gene and PS-1 gene were shown to modify the processing of APP via modulation of secretase activities. These altered APP processing was shown to be one of possibility for neurodegeneration process [68]. E-NFT density does not necessarily reflect the degree of neuronal loss. In conclusion, hippocampal NFT pathology is considerably influenced not by E4 frequency but by APP and PS-1 genotypes. The hippocampal NFT pathology is characterized by prominent E-NFT formation in familial AD.

Acknowledgements Dr. Yuken Fukutani, Fukui Medical University, and Dr. Kiminori Isaki, Department of Nursing and Welfare, Fukui Prefectural University, encouraged this study. Dr. Katsuji Kobayashi, Department of Psychiatry and Neurobiology, Kanazawa University, reviewed the manuscript. We are deeply indebted Miss Eiko Yoshida, National Sanatorium Hokuriku Hospital, Toyama, Japan, and Mr. N. Khan, Institute of Psychiatry, London, for their technical assistance. This research was supported by Grants-in-Aids from

63

the Japanese Ministry of Education, Science, Sports and Culture. (No. 13670995).

References [1] Ball MJ. Topographic distribution of neurofibrillary tangles and granulovacuolar degeneration in hippocampal cortex of aging and demented patients. A quantitative study. Acta Neuropathol (Berl) 1978;42:73 – 80. [2] Grundke-Iqbal I, Iqbal K, Tung YC, Quinlan M, Wisniewski HM, Binder LI. Abnormal phosphorylation of the microtubule-associated protein tau (H ) in Alzheimer cytoskeletal pathology. Proc Natl Acad Sci U S A 1986;83:4913 – 7. [3] Ihara Y, Nukina N, Miura R, Ogawara M. Phosphorylated tau protein is integrated into paired helical filaments in Alzheimer’s disease. J Biochem 1986;99:1807 – 10. [4] Cras P, Smith MA, Richey PL, Siedlak SL, Mulvihill P, Perry G. Extracellular neurofibrillary tangles reflect neuronal loss and provide further evidence of extensive protein cross-linking in Alzheimer disease. Acta Neuropathol (Berl) 1995;89:291 – 5. [5] Braak H, Braak E. Neuropathological staging of Alzheimer-related changes. Acta Neuropathol (Berl) 1991;82:239 – 59. [6] Arriagada PV, Growdon JH, Hedley-Whyte ET, Hyman BT. Neurofibrillary tangles but not senile plaques parallel duration and severity of Alzheimer’s disease. Neurology 1992;42:631 – 9. [7] Oddo S, Caccamo A, Kitazawa M, Tseng BP, LaFerla FM. Amyloid deposition precedes tangle formation in a triple transgenic model of Alzheimer’s disease. Neurobiol Aging 2003;24:1063 – 70. [8] Thaker U, McDonagh AM, Iwatsubo T, Lendon CL, Pickering-Brown SM, Mann DM. Tau load is associated with apolipoprotein E genotype and the amount of amyloid beta protein, Abeta40, in sporadic and familial Alzheimer’s disease. Neuropathol Appl Neurobiol 2003;29: 35 – 44. [9] Nicoll JA, Wilkinson D, Holmes C, Steart P, Markham H, Weller RO. Neuropathology of human Alzheimer disease after immunization with amyloid-beta peptide: a case report. Nat Med 2003;9:448 – 52. [10] Orgogozo JM, Gilman S, Dartigues JF, Laurent B, Puel M, Kirby LC, et al. Subacute meningoencephalitis in a subset of patients with AD after Abeta42 immunization. Neurology 2003;61:46 – 54. [11] Ferrer I, Boada Rovira M, Sanchez Guerra ML, Rey MJ, Costa-Jussa F. Neuropathology and pathogenesis of encephalitis following amyloid-beta immunization in Alzheimer’s disease. Brain Pathol 2004;14:11 – 20. [12] Mann DM, Iwatsubo T, Ihara Y, Cairns NJ, Lantos PL, Bogdanovic N, et al. Predominant deposition of amyloid-beta 42(43) in plaques in cases of Alzheimer’s disease and hereditary cerebral hemorrhage associated with mutations in the amyloid precursor protein gene. Am J Pathol 1996;148:1257 – 66. [13] Scheuner D, Eckman C, Jensen M, Song X, Citron M, Suzuki N, et al. Secreted amyloid beta-protein similar to that in the senile plaques of Alzheimer’s disease is increased in vivo by the presenilin 1 and 2 and APP mutations linked to familial Alzheimer’s disease. Nat Med 1996;2:864 – 70. [14] Lemere CA, Lopera F, Kosik KS, Lendon CL, Ossa J, Saido TC, et al. The E280A presenilin 1 Alzheimer mutation produces increased A beta 42 deposition and severe cerebellar pathology. Nat Med 1996;2:1146 – 50. [15] Cairns NJ, Chadwick A, Lantos PL, Levy R, Rossor MN. Beta A4 protein deposition in familial Alzheimer’s disease with the mutation in codon 717 of the beta A4 amyloid precursor protein gene and sporadic Alzheimer’s disease. Neurosci Lett 1993;149:137 – 40. [16] Citron M, Westaway D, Xia W, Carlson G, Diehl T, Levesque G, et al. Mutant presenilins of Alzheimer’s disease increase production of 42residue amyloid beta-protein in both transfected cells and transgenic mice. Nat Med 1997;3:67 – 72.

64

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

[17] Gomez-Isla T, Wasco W, Pettingell WP, Gurubhagavatula S, Schmidt SD, Jondro PD, et al. A novel presenilin-1 mutation: increased betaamyloid and neurofibrillary changes. Ann Neurol 1997;41:809 – 13. [18] Ishii K, Lippa C, Tomiyama T, Miyatake F, Ozawa K, Tamaoka A, et al. Distinguishable effects of presenilin-1 and APP717 mutations on amyloid plaque deposition. Neurobiol Aging 2001;22:367 – 76. [19] Corder EH, Saunders AM, Strittmatter WJ, Schmechel DE, Gaskell PC, Small GW, et al. Gene dose of apolipoprotein E type 4 allele and the risk of Alzheimer’s disease in late onset families. Science 1993;261:921 – 3. [20] Myers RH, Schaefer EJ, Wilson PW, D’Agostino R, Ordovas JM, Espino A, et al. Apolipoprotein E epsilon4 association with dementia in a population-based study: the Framingham study. Neurology 1996;46:673 – 7. [21] Cairns NJ, Fukutani Y, Chadwick A, Barnes H, Holmes C, Lantos PL, et al. h-Amyloid (Ah), phosphorylated tau and apolipoprotein E genotype in Alzheimer’s disease. Alzheimer’s Res 1997;3:109 – 14. [22] Ohm TG, Scharnagl H, Marz W, Bohl J. Apolipoprotein E isoforms and the development of low and high Braak stages of Alzheimer’s disease-related lesions. Acta Neuropathol (Berl) 1999;98:273 – 80. [23] Bales KR, Verina T, Dodel RC, Du Y, Altstiel L, Bender M, et al. Lack of apolipoprotein E dramatically reduces amyloid beta-peptide deposition. Nat Genet 1997;17:263 – 4. [24] Ohm TG, Kirca M, Bohl J, Scharnagl H, Gross W, Marz W. Apolipoprotein E polymorphism influences not only cerebral senile plaque load but also Alzheimer-type neurofibrillary tangle formation. Neuroscience 1995;66:583 – 7. [25] Polvikoski T, Sulkava R, Haltia M, Kainulainen K, Vuorio A, Verkkoniemi A, et al. Apolipoprotein E, dementia, and cortical deposition of beta-amyloid protein. N Engl J Med 1995;333:1242 – 7. [26] Gomez-Isla T, West HL, Rebeck GW, Harr SD, Growdon JH, Locascio JJ, et al. Clinical and pathological correlates of apolipoprotein E epsilon 4 in Alzheimer’s disease. Ann Neurol 1996;39:62 – 70. [27] Hyman BT, Gomez-Isla T, Rebeck GW, Briggs M, Chung H, West HL, et al. Epidemiological, clinical, and neuropathological study of apolipoprotein E genotype in Alzheimer’s disease. Ann N Y Acad Sci 1996;802:1 – 5. [28] Pirttila T, Soininen H, Mehta PD, Heinonen O, Lehtimaki T, Bogdanovic N, et al. Apolipoprotein E genotype and amyloid load in Alzheimer disease and control brains. Neurobiol Aging 1997;18:121 – 7. [29] Fleming LM, Weisgraber KH, Strittmatter WJ, Troncoso JC, Johnson GV. Differential binding of apolipoprotein E isoforms to tau and other cytoskeletal proteins. Exp Neurol 1996;138:252 – 60. [30] Genis L, Chen Y, Shohami E, Michaelson DM. Tau hyperphosphorylation in apolipoprotein E-deficient and control mice after closed head injury. J Neurosci Res 2000;60:559 – 64. [31] Tesseur I, Van Dorpe J, Spittaels K, Van den Haute C, Moechars D, Van Leuven F. Expression of human apolipoprotein E4 in neurons causes hyperphosphorylation of protein tau in the brains of transgenic mice. Am J Pathol 2000;156:951 – 64. [32] Nagy Z, Esiri MM, Jobst KA, Johnston C, Litchfield S, Sim E, et al. Influence of the apolipoprotein E genotype on amyloid deposition and neurofibrillary tangle formation in Alzheimer’s disease. Neuroscience 1995;69:757 – 61. [33] Gomez-Isla T, Hollister R, West H, Mui S, Growdon JH, Petersen RC, et al. Neuronal loss correlates with but exceeds neurofibrillary tangles in Alzheimer’s disease. Ann Neurol 1997;41:17 – 24. [34] Mukaetova-Ladinska EB, Harrington CR, Roth M, Wischik CM. Presence of the apolipoprotein E type epsilon 4 allele is not associated with neurofibrillary pathology or biochemical changes to tau protein. Dement Geriatr Cogn Disord 1997;8:288 – 95. [35] Fukutani Y, Cairns NJ, Rossor MN, Lantos PL. Purkinje cell loss and astrocytosis in the cerebellum in familial and sporadic Alzheimer’s disease. Neurosci Lett 1996;214:33 – 6. [36] Sasaki K, Fukutani Y, Mukai M, Cairns NJ, Isaki K. Neurons and neurofibrillary tangles in the hippocampal cortex in familial and sporadic Alzheimer’s disease. Neuropathology 1997;17:301 – 6.

[37] Tierney MC, Fisher RH, Lewis AJ, Zorzitto ML, Snow WG, Reid DW, et al. 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 – 64. [38] Mirra SS, Heyman A, McKeel D, Sumi SM, Crain BJ, Brounlee LM, et al. 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 – 86. [39] Ausubel FM, Brent R, Kingston RE, Moore DD, Seidman JG, Smith JA, et al. Current Protocols in Molecular Biology, vol. 1. New York’ Wiley; 1997. p. 2.2.1. [40] Wenham PR, Price WH, Blandell G. Apolipoprotein E genotyping by one-stage PCR. Lancet 1991;337:1158 – 9. [41] Gallyas F. Silver staining of Alzheimer’s neurofibrillary changes by means of physical development. Acta Morphol Acad Sci Hung 1971;19:1 – 8. [42] Braak H, Braak E. On areas of transition between entorhinal allocortex and temporal isocortex in the human brain. Normal morphology and lamina-specific pathology in Alzheimer’s disease. Acta Neuropathol (Berl) 1985;68:325 – 32. [43] Lorente de No R. Studies on the structure of the cerebral cortex. Continuation of the study of ammonic system. J Psychol Neurol 1934;46:113 – 7. [44] Duvernoy HM. An atlas of applied anatomy. Munich’ J. F. BergmannVerlag; 1988. [45] Scho¨nheit B, Zarski R, Ohm TG. Spatial and temporal relationships between plaques and tangles in Alzheimer-pathology. Neurobiol Aging 2000;25:697 – 711. [46] Suzuki N, Cheung TT, Cai XD, Odaka A, Otvos Jr L, Eckman C, et al. An increased percentage of long amyloid beta protein secreted by familial amyloid beta protein precursor (beta APP717) mutants. Science 1994;264:1336 – 40. [47] Eckman CB, Mehta ND, Crook R, Perez-tur J, Prihar G, Pfeiffer E, et al. A new pathogenic mutation in the APP gene (I716V) increases the relative proportion of Ah42(43). Hum Mol Genet 1997;6:2087 – 9. [48] Lewis J, Dickson DW, Lin WL, Chisholm L, Corral A, Jones G, et al. Enhanced neurofibrillary degeneration in transgenic mice expressing mutant tau and APP. Science 2001;24:1487 – 91. [49] Rosenberg CK, Pericak-Vance MA, Saunders AM, Gilbert JR, Gaskell PC, Hulette CM. Lewy body and Alzheimer pathology in a family with the amyloid-beta precursor protein APP717 gene mutation. Acta Neuropathol (Berl) 2000;100:145 – 52. [50] Kwok JB, Taddei K, Hallupp M, Fisher C, Brooks WS, Broe GA, et al. Two novel (M233T and R278T) presenilin-1 mutations in early-onset Alzheimer’s disease pedigrees and preliminary evidence for association of presenilin-1 mutations with a novel phenotype. Neuroreport 1997;8:1537 – 42. [51] Miklossy J, Taddei K, Suva D, Verdile G, Fonte J, Fisher C, et al. Two novel presenilin-1 mutations (Y256S and Q222H) are associated with early-onset Alzheimer’s disease. Neurobiol Aging 2003;24: 655 – 62. [52] Li YM, Xu M, Lai MT, Huang Q, Castro JL, DiMuzio-Mower J, et al. Photoactivated gamma-secretase inhibitors directed to the active site covalently label presenilin 1. Nature 2000;405:689 – 94. [53] Yamada M, Itoh Y, Sodeyama N, Suematsu N, Otomo E, Matsushita M, et al. Senile dementia of the neurofibrillary tangle type: a comparison with Alzheimer’s disease. Dement Geriatr Cogn Disord 2001;12:117 – 26. [54] Takayama N, Iseki E, Yamamoto T, Kosaka K. Regional quantitative study of formation process of neurofibrillary tangles in the hippocampus of non-demented elderly brains: comparison with late-onset Alzheimer’s disease brains. Neuropathology 2002;22:147 – 53. [55] Parihar MS, Hemnari T. Alzheimer’s disease pathogenesis and therapeutic interventions. J Clin Neurosci 2004;11:456 – 67. [56] Zubenko GS, Stiffler S, Stabler S, Kopp U, Hughes HB, Cohen BM, et al. Association of the apolipoprotein E epsilon 4 allele with clinical

S. Sudo et al. / Journal of the Neurological Sciences 234 (2005) 55 – 65

[57]

[58]

[59]

[60]

[61]

[62]

subtypes of autopsy confirmed Alzheimer’s disease. Am J Med Genet 1994;54:199 – 205. Olichney JM, Hansen LA, Galasko D, Saitoh T, Hofstetter CR, Katzman R, et al. The apolipoprotein E epsilon 4 allele is associated with increased neuritic plaques and cerebral amyloid angiopathy in Alzheimer’s disease and Lewy body variant. Neurology 1996;47: 190 – 6. Hyman BT, Gomez-Isla T, Rebeck GW, Briggs M, Chung H, West HL, et al. Epidemiological, clinical, and neuropathological study of apolipoprotein E genotype in Alzheimer’s disease. Ann N Y Acad Sci 1996;802:1 – 5. Mukaetova-Ladinska EB, Harrington CR, Roth M, Wischik CM. Presence of the apolipoprotein E type epsilon 4 allele is not associated with neurofibrillary pathology or biochemical changes to tau protein. Dement Geriatr Cogn Disord 1997;8:288 – 95. Berg L, McKeel Jr DW, Miller JP, Storandt M, Rubin EH, Morris JC, et al. Clinicopathologic studies in cognitively healthy aging and Alzheimer’s disease: relation of histologic markers to dementia severity, age, sex, and apolipoprotein E genotype. Arch Neurol 1998;55:326 – 35. Chen L, Baum L, Ng HK, Chan LY, Pang CP. Apolipoprotein E genotype and its pathological correlation in Chinese Alzheimer’s disease with late onset. Hum Pathol 1999;30:1172 – 7. Ghebremedhin E, Schultz C, Braak E, Braak H. High frequency of apolipoprotein E epsilon4 allele in young individuals with very mild

[63]

[64]

[65] [66]

[67]

[68]

65

Alzheimer’s disease-related neurofibrillary changes. Exp Neurol 1998; 153:152 – 5. Warzok RW, Kessler C, Apel G, Schwarz A, Egensperger R, Schreiber D, et al. Apolipoprotein E4 promotes incipient Alzheimer pathology in the elderly. Alzheimer Dis Assoc Disord 1998;12:33 – 9. Hesse C, Bogdanovic N, Davidsson P, Blennow K. A quantitative and immunohistochemical study on apolipoprotein E in brain tissue in Alzheimer’s disease. Dement Geriatr Cogn Disord 1999;10:452 – 9. Poirier J. Apolipoprotein E in animal models of CNS injury and in Alzheimer’s disease. Trends Neurol Sci 1994;17:525 – 30. Levi O, Jongen-Relo AL, Feldon J, Roses AD, Michaelson DM. ApoE4 impairs hippocampal plasticity isoform-specifically and blocks the environmental stimulation of synaptogenesis and memory. Neurobiol Dis 2003;13:273 – 82. Mattson MP, Gary DS, Chan SL, Duan W. Perturbed endoplasmic reticulum function, synaptic apoptosis and the pathogenesis of Alzheimer’s disease. Biochem Soc Symp 2001;67:151 – 62. Scheuner D, Eckman C, Jensen M, Song X, Citron M, Suzuki N. Secreted amyloid b-protein similar to that in the senile plaques of Alzheimer’s disease is increased in vivo by the presenilin 1 and 2 and APP mutations linked to familial Alzheimer’s disease. Nat Med 1996;2:864 – 8.