Altered γ‐secretase activity in mild cognitive impairment and Alzheimer's disease
2012; Springer Nature; Volume: 4; Issue: 4 Linguagem: Inglês
10.1002/emmm.201200214
ISSN1757-4684
AutoresNobuto Kakuda, Mikio Shoji, Hiroyuki Arai, Katsutoshi Furukawa, Takeshi Ikeuchi, Kohei Akazawa, Mako Takami, Hiroyuki Hatsuta, Shigeo Murayama, Yasuhiro Hashimoto, Masakazu Miyajima, Hajime Arai, Yu Nagashima, Haruyasu Yamaguchi, Ryozo Kuwano, Kazuhiro Nagaike, Yasuo Ihara,
Tópico(s)Neuroinflammation and Neurodegeneration Mechanisms
ResumoResearch Article21 February 2012Open Access Altered γ-secretase activity in mild cognitive impairment and Alzheimer's disease Nobuto Kakuda Nobuto Kakuda Immuno-Biological Laboratories Co., Fujioka, Japan Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan Search for more papers by this author Mikio Shoji Mikio Shoji Department of Neurology, Institute of Brain Science, Hirosaki University Graduate School of Medicine, Hirosaki, Japan Search for more papers by this author Hiroyuki Arai Hiroyuki Arai Division of Brain Sciences, Department of Geriatrics and Gerontology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan Search for more papers by this author Katsutoshi Furukawa Katsutoshi Furukawa Division of Brain Sciences, Department of Geriatrics and Gerontology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan Search for more papers by this author Takeshi Ikeuchi Takeshi Ikeuchi Department of Neurology, Brain Research Institute, Niigata University, Niigata, Japan Search for more papers by this author Kohei Akazawa Kohei Akazawa Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan Search for more papers by this author Mako Takami Mako Takami Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan Search for more papers by this author Hiroyuki Hatsuta Hiroyuki Hatsuta Department of Neuropathology, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan Search for more papers by this author Shigeo Murayama Shigeo Murayama Department of Neuropathology, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan Search for more papers by this author Yasuhiro Hashimoto Yasuhiro Hashimoto Department of Biochemistry, Fukushima Medical University, Fukushima, Japan Search for more papers by this author Masakazu Miyajima Masakazu Miyajima Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan Search for more papers by this author Hajime Arai Hajime Arai Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan Search for more papers by this author Yu Nagashima Yu Nagashima Department of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan Search for more papers by this author Haruyasu Yamaguchi Haruyasu Yamaguchi Gunma University School of Health Sciences, Maebashi, Japan Search for more papers by this author Ryozo Kuwano Ryozo Kuwano Department of Molecular Genetics, Bioresource Science Branch, Center for Bioresources, Niigata University, Niigata, Japan Search for more papers by this author Kazuhiro Nagaike Kazuhiro Nagaike Immuno-Biological Laboratories Co., Fujioka, Japan Search for more papers by this author Yasuo Ihara Corresponding Author Yasuo Ihara [email protected] Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Corporation, Tokyo, Japan New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan Search for more papers by this author the Japanese Alzheimer's Disease Neuroimaging Initiative the Japanese Alzheimer's Disease Neuroimaging Initiative Search for more papers by this author Nobuto Kakuda Nobuto Kakuda Immuno-Biological Laboratories Co., Fujioka, Japan Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan Search for more papers by this author Mikio Shoji Mikio Shoji Department of Neurology, Institute of Brain Science, Hirosaki University Graduate School of Medicine, Hirosaki, Japan Search for more papers by this author Hiroyuki Arai Hiroyuki Arai Division of Brain Sciences, Department of Geriatrics and Gerontology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan Search for more papers by this author Katsutoshi Furukawa Katsutoshi Furukawa Division of Brain Sciences, Department of Geriatrics and Gerontology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan Search for more papers by this author Takeshi Ikeuchi Takeshi Ikeuchi Department of Neurology, Brain Research Institute, Niigata University, Niigata, Japan Search for more papers by this author Kohei Akazawa Kohei Akazawa Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan Search for more papers by this author Mako Takami Mako Takami Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan Search for more papers by this author Hiroyuki Hatsuta Hiroyuki Hatsuta Department of Neuropathology, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan Search for more papers by this author Shigeo Murayama Shigeo Murayama Department of Neuropathology, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan Search for more papers by this author Yasuhiro Hashimoto Yasuhiro Hashimoto Department of Biochemistry, Fukushima Medical University, Fukushima, Japan Search for more papers by this author Masakazu Miyajima Masakazu Miyajima Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan Search for more papers by this author Hajime Arai Hajime Arai Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan Search for more papers by this author Yu Nagashima Yu Nagashima Department of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan Search for more papers by this author Haruyasu Yamaguchi Haruyasu Yamaguchi Gunma University School of Health Sciences, Maebashi, Japan Search for more papers by this author Ryozo Kuwano Ryozo Kuwano Department of Molecular Genetics, Bioresource Science Branch, Center for Bioresources, Niigata University, Niigata, Japan Search for more papers by this author Kazuhiro Nagaike Kazuhiro Nagaike Immuno-Biological Laboratories Co., Fujioka, Japan Search for more papers by this author Yasuo Ihara Corresponding Author Yasuo Ihara [email protected] Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Corporation, Tokyo, Japan New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan Search for more papers by this author the Japanese Alzheimer's Disease Neuroimaging Initiative the Japanese Alzheimer's Disease Neuroimaging Initiative Search for more papers by this author Author Information Nobuto Kakuda1,2,3, Mikio Shoji4, Hiroyuki Arai5, Katsutoshi Furukawa5, Takeshi Ikeuchi6, Kohei Akazawa7, Mako Takami2,3, Hiroyuki Hatsuta8, Shigeo Murayama8, Yasuhiro Hashimoto9, Masakazu Miyajima10, Hajime Arai10, Yu Nagashima11, Haruyasu Yamaguchi12, Ryozo Kuwano13, Kazuhiro Nagaike1, Yasuo Ihara *,2,14,3 and 1Immuno-Biological Laboratories Co., Fujioka, Japan 2Faculty of Life and Medical Sciences, Department of Neuropathology, Doshisha University, Kyoto, Japan 3New Energy and Industrial Technology Development Organization (NEDO), Kanagawa, Japan 4Department of Neurology, Institute of Brain Science, Hirosaki University Graduate School of Medicine, Hirosaki, Japan 5Division of Brain Sciences, Department of Geriatrics and Gerontology, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan 6Department of Neurology, Brain Research Institute, Niigata University, Niigata, Japan 7Department of Medical Informatics, Niigata University Medical and Dental Hospital, Niigata, Japan 8Department of Neuropathology, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan 9Department of Biochemistry, Fukushima Medical University, Fukushima, Japan 10Department of Neurosurgery, Juntendo University School of Medicine, Tokyo, Japan 11Department of Neurology, Graduate School of Medicine, University of Tokyo, Tokyo, Japan 12Gunma University School of Health Sciences, Maebashi, Japan 13Department of Molecular Genetics, Bioresource Science Branch, Center for Bioresources, Niigata University, Niigata, Japan 14Core Research for Evolutional Science and Technology (CREST), Japan Science and Technology Corporation, Tokyo, Japan *Tel: +81 774 656058; Fax: +81 774 731922 EMBO Mol Med (2012)4:344-352https://doi.org/10.1002/emmm.201200214 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions Figures & Info Abstract We investigated why the cerebrospinal fluid (CSF) concentrations of Aβ42 are lower in mild cognitive impairment (MCI) and Alzheimer's disease (AD) patients. Because Aβ38/42 and Aβ40/43 are distinct product/precursor pairs, these four species in the CSF together should faithfully reflect the status of brain γ-secretase activity, and were quantified by specific enzyme-linked immunosorbent assays in the CSF from controls and MCI/AD patients. Decreases in the levels of the precursors, Aβ42 and 43, in MCI/AD CSF tended to accompany increases in the levels of the products, Aβ38 and 40, respectively. The ratios Aβ40/43 versus Aβ38/42 in CSF (each representing cleavage efficiency of Aβ43 or Aβ42) were largely proportional to each other but generally higher in MCI/AD patients compared to control subjects. These data suggest that γ-secretase activity in MCI/AD patients is enhanced at the conversion of Aβ43 and 42 to Aβ40 and 38, respectively. Consequently, we measured the in vitro activity of raft-associated γ-secretase isolated from control as well as MCI/AD brains and found the same, significant alterations in the γ-secretase activity in MCI/AD brains. The paper explained PROBLEM: Alzheimer's disease is a devastating form of progressive dementia, in which senile plaques composed of Aβ form in the brain. Different species of Aβ are derived from APP through sequential cleavage by β- and γ-secretases and can be detected in the CSF of patients. These can serve as markers for the disease. RESULTS: We investigated why CSF concentrations of Aβ42 are lower in MCI and AD patients. We suggest that this is not because Aβ42/43 is selectively deposited in the brain, but because γ-secretase activity is altered in AD brain: more Aβ42 and Aβ43 are converted to Aβ40 and Aβ38, respectively, resulting in lower Aβ42 and Aβ43 in CSF. IMPACT: Our results predict that γ-secretase modulators would have only limited efficacy in treatment of AD patients, because Aβ42/43 production by γ-secretase is already shifted towards reduced levels in AD brain. INTRODUCTION Senile plaques, the neuropathological hallmark of Alzheimer's disease (AD), are composed of amyloid β-protein (Aβ). Aβ is derived from β-amyloid precursor protein (APP) through sequential cleavage by β- and γ-secretases. β-Secretase cleaves at the luminal portion (β-site) of APP to generate a β-carboxyl terminal fragment of APP (βCTF), an immediate substrate of γ-secretase, to produce different Aβ species (for a review see Selkoe, 2001). The most abundant secreted Aβ species is Aβ40, whereas the species that has two extra residues (Aβ42) is a minor one ( Aβ38 > Aβ42 Aβ43 in all CSF samples examined (Table 1 and Supporting Information Fig S2A). The relative amounts of Aβs were constant across the samples: Aβ38:40 ratio in CSF was ∼1:3, and Aβ42:43 ratio was ∼10:1. The CSF concentrations of Aβ40 were significantly increased in AD compared to control (Table 1; p < 0.05, Dunnett's t-test). Additionally, the CSF concentrations of Aβ38 tended to be increased in AD patients compared to controls. In contrast, those of Aβ42 and 43 were significantly decreased in MCI/AD compared to controls (p < 0.05, Dunnett's t-test). Interestingly, as reported previously (Schoonenboom et al, 2005), the CSF concentrations of Aβ40 and Aβ38 were proportional to each other in all subjects [Fig 2A; ln(Aβ40) = 0.910 × ln(Aβ38) + 1.642, R = 0.913, where ln(Aβ40) is the logarithm of Aβ40], even in MCI/AD cases. This was despite the fact that these species are derived from and the final products of the two different product lines of γ-secretase activity (Fig 1; Takami et al, 2009). In other words, the amounts of products in the third step of cleavage were strictly proportional to each other across the product lines. Table 1. Subject characteristics and CSF concentrations of Aβs Control MCI AD ANOVA ***p-value Age (years) 74.9 ± 7.5 72.5 ± 6.6 72.3 ± 8.2 N (male/female) 21 (10/11) 19 (7/12) 24 (7/17) MMSE score 28.7 ± 1.9 25.7 ± 2.6 19.6 ± 3.3 ApoE ε4 3 (14.3%) 10 (52.6%) a 14 (58.6%) a Aβ38 (pM) 594.5 ± 286.3 669.4 ± 247.6 760.57 ± 269.4 Ln(Aβ38) 6.28 ± 0.46 6.44 ± 0.38 6.56 ± 0.41 NS Aβ40 (pM) 1607.9 ± 712.9 1939.5 ± 698.0 2292.6 ± 799.6 Ln(Aβ40) 7.28 ± 0.47 7.51 ± 0.38 7.68 ± 0.35 0.007 Aβ42 (pM) 133.1 ± 53.4 83.2 ± 49.4** 90.3 ± 40.1 a Ln(Aβ42) 4.80 ± 0.47 4.25 ± 0.60 4.40 ± 0.47 0.004 Aβ43 (pM) 11.8 ± 5.7 6.8 ± 5.6** 7.0 ± 4.6** Ln(Aβ43) 2.32 ± 0.60 1.59 ± 0.86 1.76 ± 0.62 0.004 a 2 MCI subjects were homozygous for ε4, while 4 AD subjects were homozygous for the allele. ** p < 0.05; Dunnett's t-test after log-transformation for comparing between control and MCI or AD. *** p-value of analysis of variance after log-transformation. Figure 2. Relationships between the levels of Aβ40 and 38, and between those of Aβ43 and 42 in CSF from controls and MCI/AD patients. A.. The levels of ln(Aβ40) were proportional to those of ln(Aβ38) (ln(Aβ40) = 0.910 × ln(Aβ38) + 1.642, R = 0.913). B.. The levels of ln(Aβ43) were proportional to those of ln(Aβ42) (ln(Aβ43) = 1.333 × ln(Aβ42) − 4.09, R = 0.979). It should be noted that the levels of both ln(Aβ42) and ln(Aβ43) in MCI [filled triangle (n = 19)]/AD [filled circle (n = 24)] are lower than those in controls [open circles (n = 21)]. Download figure Download PowerPoint Aβ42 and Aβ43 are produced by the second cleavage step of each product line. Like Aβ40 and Aβ38, the CSF concentrations of Aβ42 and Aβ43 are also proportional to each other in controls and in MCI/AD patients [Fig 2B; ln(Aβ43) = 1.333 × ln(Aβ42) − 4.09, R = 0.979]. On the other hand, the levels of Aβ43 and Aβ40 (a precursor and its product) were correlated in control [Fig 3A; ln(Aβ43) = 0.884 × ln(Aβ40) − 4.118, R = 0.688] and in MCI/AD subjects (R = 0.507/0.736 for MCI/AD, respectively) but the MCI/AD values were located below the regression line for controls and thus provided lower Aβ43 measures compared with controls for a given Aβ40 measure (Fig 3A; p < 0.001, analysis of variance, ANOVA). Conversely, for a given Aβ43 value, the plot provided a higher Aβ40 measure in MCI/AD cases. There was a similar situation for the levels of Aβ42 and Aβ38. The levels of Aβ42 and Aβ38 were correlated each other in control subjects [Fig 3B; ln(Aβ42) = 0.724 × ln(Aβ38) + 0.251, R = 0.723], but barely in MCI/AD (R = 0.500 for MCI; 0.393 for AD), and the MCI/AD plots were situated below the regression line for controls (p < 0.001, ANOVA). For a given Aβ42 value, the plot provided a higher Aβ38 measure in MCI/AD compared with controls. Figure 3. Relationships between the levels of Aβ43 and 40, and between those of Aβ42 and 38 in CSF from controls (open circles) and MCI (closed triangle)/AD patients (closed circle). A.. The levels of ln(Aβ43) correlate with those of ln(Aβ40) within controls (R = 0.688), and barely within MCI/AD subjects (R = 0.507/0.736). The plots for MCI/AD were located below the regression line for control (p < 0.001, ANOVA). B.. The levels of Aβ42 correlate with those of Aβ38 within controls (R = 0.723), and barely within MCI/AD (R = 0.500/0.393). The plots for MCI/AD were situated below the regression line for controls (p < 0.001, ANOVA). Download figure Download PowerPoint These lower concentrations of Aβ42 appeared to be compensated with higher concentrations of Aβ38 as the levels of ln(Aβ38 + Aβ42) did not vary even in MCI/AD (p = 0.293, ANOVA). Thus, this points to the possibility that more Aβ42 and Aβ43 are converted to Aβ38 and Aβ40, respectively, in MCI/AD brains. According to numerical simulation based on the stepwise processing model, as the levels of βCTF decline to null, the levels of Aβ43 and 42 decrease and the ratios of Aβ40/43 and Aβ38/42 increase (unpublished observation). However, this situation can be excluded as the mechanism for lower concentrations of Aβ42 and 43, because the levels of βCTF have never been reported to be reduced in AD brains nor in plaque-forming Tg2576 mice that show lower CSF Aβ42 concentrations (Kawarabayashi et al, 2001). Thus, it is reasonable to suspect that the final cleavage steps from Aβ43 mostly to 40 and from Aβ42 to 38 are significantly enhanced in parallel (increases in released tri- and tetrapeptides) in brains affected by MCI/AD compared with controls (Fig 1). This relationship in γ-secretase cleavage becomes clearer by plotting the product/precursor ratio representing cleavage efficiency at the step from Aβ42 to 38 (Aβ38/42) against that representing the cleavage efficiency at the step from Aβ43 to 40 (Aβ40/43) (Fig 4). The 'apparent' cleavage efficiency of Aβ43 was approximately 40-fold larger than that of Aβ42. The two ratios in CSF samples from MCI/AD and control subjects were largely proportional to each other, indicating that the corresponding cleavage processes in the two lines are tightly coupled (Fig 4). All plots were situated on a distinct line [ln(Aβ38/42) = 0.748 × ln(Aβ40/43) − 2.244, R = 0.936] and its close surroundings. An increase in the cleavage from Aβ43 to 40 (i.e. more Aβ43 is converted to Aβ40) accompanied an increase in the cleavage from Aβ42 to 38 and vice versa, although the mechanism underlying this coupling between the two product lines remains unknown. This reminds us of the 'NSAID effect' in the 3-([3-cholamidopropyl]dimetylammonio)-2-hydroxy-1-propanesulfonate (CHAPSO)-reconstituted γ-secretase system (Takami et al, 2009; Weggen et al, 2001) in which the addition of sulindac sulfide to the γ-secretase reaction mixture, as expected, significantly suppressed Aβ42 production and increased Aβ38 production presumably by increasing the amounts of released tetrapeptide (VVIA) (Takami et al, 2009) and other peptides. Figure 4. Ln(Aβ40/43) versus ln(Aβ38/42) plot. The ratios represent the cleavage efficiency at the final step of each line. Both ratios are largely proportional to each other (y = 0.748 × −2.244, R = 0.936) and plots are located on the line and its close surroundings. This plot clearly distinguishes between control subjects and MCI/AD patients (Aβ40/43 for MCI vs. control, p = 0.000; Aβ38/42 for MCI vs. control, p = 0.000; ANOVA, followed by Dunnett's t-test). Control plots [open circles (n = 21)] are located close to the origin and MCI/AD plots [closed triangles (n = 19) and closed circles (n = 24), respectively] are a little distant from the origin. Download figure Download PowerPoint Most importantly, this graph provides a clear distinction between the control and MCI/AD groups (Fig 4; Aβ40/43 for MCI/AD vs. control, p = 0.000; Aβ38/42 for MCI/AD vs. control, p = 0.000; ANOVA, followed by Dunnett's t-test). The control values plotted close to the origin, whereas those for MCI/AD patients were distant from the origin along the line [ln(Aβ38/42) = 0.748 × ln(Aβ40/43) − 2.244, R = 0.936]. It is also of note that there was no significant difference between MCI and AD patients (Fig 4; Aβ40/43 for AD vs. MCI, p = 1.000; Aβ38/42 for AD vs. MCI, p = 1.000; Bonferroni's t-test). Two control values were a little farther from the origin, which may suggest that these subjects already have latent Aβ deposition or are in the preclinical AD stage. Additionally, we examined quite a small number of CSF samples from presenilin (PS) 1-mutated (symptomatic) familial AD (FAD) patients (T116N, L173F, G209R, L286V and L381V). Out of the three FAD cases near the regression line, two (T116N and L286V) were distant from the origin like sporadic AD cases and one (L381V) was closer to the origin than controls (both Aβ42/43 levels were lower than control; unpublished data). The remaining two (G209R and L173F) were extremely displaced from the line. Thus, a larger number of FAD cases are needed to give an appropriate explanation for their unusual characteristics in the plot, and the alteration of CSF Aβs shown above seems to be applicable only for sporadic AD. Altogether, in MCI/AD, more Aβ42 and 43 are processed to Aβ38 and 40, respectively, than in controls. Even in MCI/AD, strict relationships are maintained between the levels of Aβ42 and Aβ43, and between those of Aβ38 and Aβ40 as seen in controls, which are predicted by the stepwise processing kinetics (unpublished observation). Thus, our observations suggest that lower CSF concentrations of Aβ42 and 43 and presumably higher CSF concentrations of Aβ38 and 40 are the consequence of altered γ-secretase activity in brain rather than the effect of preferential deposition of the two longer Aβ species (Aβ42 and 43) in senile plaques, which would not have maintained such strict relationships between the four Aβ species in CSF. To further test our hypothesis, we directly measured γ-secretase activities associated with lipid rafts isolated from AD, MCI and control cortices (Brodmann areas 9–11). For definite confirmation of the Aβ species, the reaction mixtures were subjected to quantitative Western blotting using specific antibodies rather than ELISA. At time 0, deposited Aβ42/43 species were detected in rafts from MCI/AD brains but not in control specimen (Supporting Information Fig S3). The amounts of ln(Aβ38 + Aβ42), which reflect the total capacity of the Aβ38/42-producing line, did not vary between AD, MCI and controls (Supporting Information Fig S4; p = 0.969, ANOVA). Thus, the gross activities of raft γ-secretase were comparable among the three groups. However, the plotted values for Aβ40/43 versus Aβ38/42 are divided into two groups: MCI/AD and controls (Fig 5; Aβ40/43 for control vs. MCI/AD, p < 0.001; Aβ38/42 for control vs. MCI/AD, p = 0.001; Welch's t-test) in the same way as those derived from CSF (Fig 4). It is notable that Figs. 4 and 5 are based on different methods, ELISA and Western blotting, respectively, but give similar results. There were no significant differences between MCI and AD specimen, although MCI patients (91 ± 4.9-year-old) were older than controls (77 ± 6.5-year-old) or AD patients (80 ± 5.0-year-old) (Aβ40/43 for MCI vs. AD, p = 0.342; Aβ38/42 for MCI vs. AD, p = 0.911). There were similar significant differences between control versus AD in the groups of which the ages were not significantly different (Aβ40/43 for control vs. AD, p < 0.001; Aβ38/42 for control vs. AD, p = 0.03). Figure 5. Ln(Aβ40/43) versus ln(Aβ38/42) plot based on direct quantification of raft-associated γ-secretase activity. The raft-associated γ-secretase prepared from control and MCI/AD brain specimens was incubated with βCTF for 2 h at 37°C (see Materials and Methods Section). Produced Aβs were quantified by Western blotting using specific antibodies. This plot distinguishes between control subjects and MCI/AD patients (Aβ40/43 for control vs. MCI/AD, p < 0.001; Aβ38/42 for control vs. MCI/AD, p = 0.001; Welch's t-test). MCI/AD plots [closed triangles (n = 10) and closed circles (n = 13), respectively] are as a whole a little distant from the origin, whereas control plots [open circles (n = 16)] are close to the origin. Download figure Download PowerPoint DISCUSSION Here, we assume that (i) Aβs in CSF are produced exclusively by γ-secretase in the brain, possibly in neurons; and (ii) Aβs in CSF are in the steady state. With these assumptions, the combined measurement of four Aβ species in CSF should predict the activity of γ-secretase in the brain. Here, the alterations in the γ-secretase activities do not mean the gross activity, i.e. total Aβ production, but the cleavage efficiency of the intermediates, Aβ42 and Aβ43. In the present study, we quantified in CSF the four Aβ species, Aβ38/42 and Aβ40/43, but the Western blotting indicated the presence of additional Aβ species, Aβ37 and 39, in CSF (Supporting Information Fig S2). At present, we cannot exclude the possibility that a certain carboxyl terminus-specific protease(s) in CSF acts on the pre-existing Aβ species and converts them to Aβ37 and 39 (Zou et al, 2007). However, according to our unpublished data (Takami et al, unpublished observations), it is plausible that Aβ37 is derived from Aβ40, whereas Aβ39 is derived from Aβ42. Even if so, these pathways are very minor (∼20–100-fold less) compared to the two major pathways, Aβ42 to Aβ38, and Aβ43 to Aβ40, when assessed by a reconstituted system (Takami et al, 2009). Thus, such strict relationships between four Aβs may have been relatively independent of Aβ37 and 39. The detailed relationship between all Aβs in the CSF awaits further quantification of the additional two Aβ species. Currently, we do not know why the observation that Aβ40 is higher in MCI/AD CSF has so far not been reported except a recent paper (Simonsen et al, 2007). In fact, some of us previously reported no significant differences in CSF Aβ40 between AD and control subjects using a different ELISA (Shoji et al, 1998). It may be notable that we used newly constructed ELISA for Aβ40 based on a different set of monoclonal antibodies and thus, those
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