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Cited by 65Alzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration MechanismsDementia and Cognitive Impairment Research

Amyloid-β plaque formation and reactive gliosis are required for induction of cognitive deficits in App knock-in mouse models of Alzheimer’s disease

Open access
Sakakibara, Yasufumi, Sekiya, Michiko, Saito, Takashi, Saido, Takaomi C., Iijima, Koichi M.·2019·BMC Neuroscience
DOI 10.1186/s12868-019-0496-6PMC PMC6425634
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Abstract

Knock-in (KI) mouse models of Alzheimer’s disease (AD) that endogenously overproduce Aβ without non-physiological overexpression of amyloid precursor protein (APP) provide important insights into the pathogenic mechanisms of AD. Previously, we reported that App NL - G - F mice, which harbor three familial AD mutations (Swedish, Beyreuther/Iberian, and Arctic) exhibited emotional alterations before the onset of definitive cognitive deficits. To determine whether these mice exhibit deficits in learning and memory at more advanced ages, we compared the Morris water maze performance of App NL - G - F and App NL mice, which harbor only the Swedish mutation, with that of wild-type (WT) C57BL/6J mice at the age of 24 months. To correlate cognitive deficits and neuroinflammation, we also examined Aβ plaque formation and reactive gliosis in these mice. In the Morris water maze, a spatial task, 24-month-old App NL - G - F/NL - G - F mice exhibited significantly poorer spatial learning than WT mice during the hidden training sessions, but similarly to WT mice during the visible training sessions. Not surprisingly, App NL - G - F/NL - G - F mice also exhibited spatial memory deficits both 1 and 7 days after the last training session. By contrast, 24-month-old App NL/NL mice had intact spatial learning and memory relative to WT mice. Immunohistochemical analyses revealed that 24-month-old App NL - G - F/NL - G - F mice developed massive Aβ plaques and reactive gliosis (microgliosis and astrocytosis) throughout the brain, including the cortex and hippocampus. By contrast, we observed no detectable brain pathology in App NL/NL mice despite overproduction of human Aβ40 and Aβ42 in their brains. Aβ plaque formation, followed by sustained neuroinflammation, is necessary for the induction of definitive cognitive deficits in App -KI mouse models of AD. Our data also indicate that introduction of the Swedish mutation alone in endogenous APP is not sufficient to produce either AD-related brain pathology or cognitive deficits in mice.

AI snapshot

Written from the paper’s full text.

TL;DR

At 24 months, AppNL-G-F/NL-G-F mice showed spatial learning and memory deficits in the Morris water maze, together with Aβ plaques and reactive gliosis, whereas AppNL/NL mice were cognitively and pathologically comparable to wild-type mice. The authors conclude that Aβ plaque formation followed by sustained neuroinflammation is required for definitive cognitive deficits in App knock-in models of Alzheimer’s disease.

Key findings

  • In 24-month-old AppNL-G-F/NL-G-F mice, hidden-platform Morris water maze performance was impaired relative to WT mice: longer latency (F[2, 41] = 7.88, p = 0.001; post hoc WT vs. AppNL-G-F/NL-G-F, p < 0.001), longer distance (F[2, 41] = 15.50, p < 0.001; post hoc p < 0.001), and lower path efficiency (F[2, 41] = 18.66, p < 0.001; post hoc p < 0.001). Visible training, swimming speed, and motor/visual performance did not differ among genotypes.
  • AppNL-G-F/NL-G-F mice also showed spatial memory deficits: in Probe test 1 they spent less time in the target quadrant than WT mice (F[2, 41] = 4.23, p = 0.021; post hoc p = 0.025) and had longer proximity to the platform (F[2, 41] = 5.61, p = 0.007; post hoc p = 0.005); in Probe test 2 they spent less time in the target quadrant (F[2, 41] = 9.03, p < 0.001; post hoc p < 0.001) and had longer proximity to the platform (F[2, 41] = 8.94, p < 0.001; post hoc p < 0.001).
  • In contrast, 24-month-old AppNL/NL mice had spatial learning and memory equivalent to WT mice, with no significant differences in hidden training or either probe test.
  • Immunohistochemistry showed massive Aβ plaques and reactive gliosis (microgliosis and astrocytosis) in cortex and hippocampus of AppNL-G-F/NL-G-F mice, whereas AppNL/NL mice had no detectable Aβ deposits or reactive gliosis despite overproducing human Aβ40 and Aβ42.

Methods

  • Male AppNL-G-F/NL-G-F, AppNL/NL, and WT C57BL/6J mice were tested at 24 months of age in the Morris water maze: 4 days of visible training (4 trials/day), 7 days of hidden training (4 trials/day), Probe test 1 one day after the sixth hidden session, and Probe test 2 seven days after the seventh hidden session. Behavioral sample sizes were n = 17 WT, n = 11 AppNL/NL, and n = 16 AppNL-G-F/NL-G-F.
  • Brains were immunostained for Aβ (82E1), microglia (Iba1), and astrocytes (GFAP), with n = 4 mice per genotype, and imaged in cortical and hippocampal regions.
  • Statistical analysis used repeated-measures ANOVA with Greenhouse–Geisser correction where needed, Bonferroni post hoc comparisons, one-way ANOVA with Tukey post hoc tests, one-sample t-tests against chance level (25%), and paired t-tests for target vs. non-target quadrant time; alpha was 0.05.

Limitations

  • The paper does not include a dedicated limitations section.
  • Evident from the Methods: only male mice were used, so sex differences were not assessed; immunohistochemistry used n = 4 per genotype; and the study is correlational, so the conclusion that Aβ plaques and neuroinflammation are “required” for cognitive deficits is not directly tested by an intervention.
  • The text notes that App-KI mice do not exhibit tau pathology or severe neuronal loss, which limits their direct correspondence to the full spectrum of Alzheimer’s disease neuropathology.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1186/s12868-019-0496-6

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

12 tests recomputed · 0 with the reported and recomputed p on opposite sides of .05

Claims the paper makes

27 of 43 cited sources checked · 14 supported · 2 flagged · accuracy not yet measured

  • Premisecitation

    AppNL mice harbor only the Swedish mutation.

    “By contrast, AppNL mice that carry only the Swedish mutation produce significantly higher levels of Aβ40 and Aβ42 without overt AD-related brain pathology such as extracellular Aβ plaques or neuroinflammation [10, 11, 13].”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source
    • cites [11] Masuda A, Kobayashi Y, Kogo N, Saito T, Saido TC, Itohara S. Cognitive deficits in single App knock-in mouse models. Neurobiol Learn Mem. 2016;135:73–82. source
    • cites [13] Salas IH, Callaerts-Vegh Z, D’Hooge R, Saido TC, Dotti CG, De Strooper B. Increased insoluble amyloid-beta induces negligible cognitive deficits in old AppNL/NL Knock-In Mice. J Alzheimers Dis. 2018;66(2):801–9. source
  • Premisecitation

    AppNL mice do not undergo overt cognitive decline prior to 8 months of age.

    “By contrast, AppNL mice do not undergo overt cognitive decline prior to 8 months of age [14]”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [14] Sakakibara Y, Sekiya M, Saito T, Saido TC, Iijima KM. Cognitive and emotional alterations in App knock-in mouse models of Abeta amyloidosis. BMC Neurosci. 2018;19:46. source
  • Premisecitation

    AppNL/NL mice overproduce human Aβ40 and Aβ42 in their brains.

    “despite overproducing human Aβ40 and Aβ42 in their brains [10, 13].”
    Quote in the paperSubstantial claim1 of 2 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source
    • cites [13] Salas IH, Callaerts-Vegh Z, D’Hooge R, Saido TC, Dotti CG, De Strooper B. Increased insoluble amyloid-beta induces negligible cognitive deficits in old AppNL/NL Knock-In Mice. J Alzheimers Dis. 2018;66(2):801–9. source
  • Premisecitation

    To date, Aβ pathologies and cognitive deficits were observed only when two or three familial AD mutations were combined.

    “To date, however, Aβ pathologies and cognitive deficits were observed only when two or three familial AD mutations were combined [33–35].”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites [33] Flood DG, Reaume AG, Dorfman KS, Lin YG, Lang DM, Trusko SP, Savage MJ, Annaert WG, De Strooper B, Siman R, et al. FAD mutant PS-1 gene-targeted mice: increased A beta 42 and A beta deposition without APP overproduction. Neurobiol Aging. 2002;23(3):335–48. source
    • cites [34] Kohler C, Ebert U, Baumann K, Schroder H. Alzheimer’s disease-like neuropathology of gene-targeted APP-SLxPS1mut mice expressing the amyloid precursor protein at endogenous levels. Neurobiol Dis. 2005;20(2):528–40. source
    • cites [35] Li H, Guo Q, Inoue T, Polito VA, Tabuchi K, Hammer RE, Pautler RG, Taffet GE, Zheng H. Vascular and parenchymal amyloid pathology in an Alzheimer disease knock-in mouse model: interplay with cerebral blood flow. Mol Neurodegener. 2014;9:28. source

      The Materials and methods (Animals; page unavailable) describe mice carrying Dutch, Swedish and London APP mutations crossed with PS1 M146V mice—four mutations in total. The Discussion (page unavailable) reports amyloid pathology and spatial learning and memory deficits in these mice. This supports the association with combined mutations, but not the claim that the pathologies and deficits were observed only with two or three. (LLM, conf=0.87)

      Experimental — accuracy not yet measured
  • Findingown data

    In Probe test 1, AppNL-G-F/NL-G-F mice spent less time in the target quadrant than WT mice.

    “In Probe test 1 (Fig. 1a), AppNL-G-F/NL-G-F mice spent less time in the target quadrant than WT mice”
    Quote in the paperSubstantial claim
  • Classified as probably not a substantial claim. 12
  • May combine two claims. 11

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Researchers have reached a consensus that the alterations in cognitive abilities of App-KI mice are very mild relative to the phenotypes of other overexpression models.

    “Accordingly, researchers have reached a consensus that the alterations in cognitive abilities of App-KI mice are very mild relative to the phenotypes of other overexpression models [11, 13, 21].”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [11] Masuda A, Kobayashi Y, Kogo N, Saito T, Saido TC, Itohara S. Cognitive deficits in single App knock-in mouse models. Neurobiol Learn Mem. 2016;135:73–82. source

      The Abstract (page unavailable) reports clear cognitive deficits in NL-G-F App-KI mice, although abnormalities in NL-F mice were modest. Section 4.1 (page unavailable) says the App-KI behavioral abnormalities largely overlap with those reported in transgenic AD models and describes severe reversal-learning deficits in NL-G-F mice. This runs counter to the blanket characterization of App-KI cognitive changes as very mild relative to overexpression models; the paper also does not report a researcher consensus on that comparison. (LLM, conf=0.83)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites [13] Salas IH, Callaerts-Vegh Z, D’Hooge R, Saido TC, Dotti CG, De Strooper B. Increased insoluble amyloid-beta induces negligible cognitive deficits in old AppNL/NL Knock-In Mice. J Alzheimers Dis. 2018;66(2):801–9. source
    • cites [21] Latif-Hernandez A, Shah D, Craessaerts K, Saido T, Saito T, De Strooper B, Van der Linden A, D’Hooge R. Subtle behavioral changes and increased prefrontal-hippocampal network synchronicity in APP(NL-G-F) mice before prominent plaque deposition. Behav Brain Res. 2017;. https://doi.org/10.1016/j.bbr.2017.11.017 . source

      The Discussion describes a relatively mild behavioral phenotype in the APP NL-G-F knock-in mice and says other models showed more robust reversal-learning impairments. It does not establish a field-wide consensus about cognitive abilities across App-KI mice; it also cautions that the compared studies used older animals with more advanced pathology. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    The general behavioral phenotypes of App-KI mice described in many published studies are minimal, with the exception of robust alterations in emotional domains.

    “However, the general behavioral phenotypes of App-KI mice described in many published studies are minimal [9], with the exception of robust alterations in emotional domains [14, 21, 22].”
    Quote in the paperSubstantial claim4 of 4 sources checked
    • cites [9] Sasaguri H, Nilsson P, Hashimoto S, Nagata K, Saito T, De Strooper B, Hardy J, Vassar R, Winblad B, Saido TC. APP mouse models for Alzheimer’s disease preclinical studies. EMBO J. 2017;36(17):2473–87. source

      The citation to this paper [9] supports the claim that App-KI mice generally have minimal behavioral phenotypes; the emotional-domain exception is cited to other sources. In “Second-generation mouse models” (page unavailable), the paper instead reports various cognitive dysfunctions in App NL-F mice, including spatial-memory, learning, and attention deficits, and greater cognitive abnormalities in App NL-G-F mice. (LLM, conf=0.76)

      Checked by a reasoning model — may be wrong.

      Experimental — accuracy not yet measured
    • cites [14] Sakakibara Y, Sekiya M, Saito T, Saido TC, Iijima KM. Cognitive and emotional alterations in App knock-in mouse models of Abeta amyloidosis. BMC Neurosci. 2018;19:46. source
    • cites [21] Latif-Hernandez A, Shah D, Craessaerts K, Saido T, Saito T, De Strooper B, Van der Linden A, D’Hooge R. Subtle behavioral changes and increased prefrontal-hippocampal network synchronicity in APP(NL-G-F) mice before prominent plaque deposition. Behav Brain Res. 2017;. https://doi.org/10.1016/j.bbr.2017.11.017 . source

      The Discussion reports subtle cognitive changes in APP NL-G-F mice, and the Discussion and §3.2 report reduced anxiety-related behavior, particularly in the elevated plus maze. This supports the pattern in the studied mice, but the paper does not establish that behavioral phenotypes are minimal across many published App-KI studies or that robust changes extend across emotional domains generally. (LLM, conf=0.82)

      Experimental — accuracy not yet measured
    • cites [22] Pervolaraki E, Hall SP, Foresteire D, Saito T, Saido TC, Whittington MA, Lever C, Dachtler J. Insoluble Abeta overexpression in an App knock-in mouse model alters microstructure and gamma oscillations in the prefrontal cortex, and social and anxiety-related behaviours. bioRxiv. 2018. source

  • May combine two claims.

    Premisecitation

    AppNL mice produce significantly higher levels of Aβ40 and Aβ42 without overt AD-related brain pathology such as extracellular Aβ plaques or neuroinflammation.

    “By contrast, AppNL mice that carry only the Swedish mutation produce significantly higher levels of Aβ40 and Aβ42 without overt AD-related brain pathology such as extracellular Aβ plaques or neuroinflammation [10, 11, 13].”
    Quote in the paperSubstantial claim2 of 3 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source
    • cites [11] Masuda A, Kobayashi Y, Kogo N, Saito T, Saido TC, Itohara S. Cognitive deficits in single App knock-in mouse models. Neurobiol Learn Mem. 2016;135:73–82. source

      The Introduction (page unavailable) identifies AppNL mice as carrying only the Swedish mutation and says their Aβ deposition and neuroinflammatory response are negligible. Section 3.6 (page unavailable) likewise reports that Aβ accumulation was difficult to detect in AppNL mice even at 18 months. The paper does not establish the claimed significant increases in both Aβ40 and Aβ42 in these mice. (LLM, conf=0.87)

      Experimental — accuracy not yet measured
    • cites [13] Salas IH, Callaerts-Vegh Z, D’Hooge R, Saido TC, Dotti CG, De Strooper B. Increased insoluble amyloid-beta induces negligible cognitive deficits in old AppNL/NL Knock-In Mice. J Alzheimers Dis. 2018;66(2):801–9. source

      The Introduction (page unavailable) says the Swedish mutation increases Aβ production and that AppNL/NL mice lack plaques and reactive gliosis. The Results (page unavailable) find significantly higher insoluble Aβ40 and Aβ42 in older versus younger AppNL/NL mice, but soluble levels decrease with age. Thus, the paper supports the pathology claim and a qualified increase in both peptides, not an unqualified significant increase in their levels. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    None of these App-KI mice exhibit tau pathology or severe neuronal loss, suggesting that they are suitable models for preclinical AD.

    “None of these App-KI mice exhibit tau pathology or severe neuronal loss, suggesting that they are suitable models for preclinical AD [9].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [9] Sasaguri H, Nilsson P, Hashimoto S, Nagata K, Saito T, De Strooper B, Hardy J, Vassar R, Winblad B, Saido TC. APP mouse models for Alzheimer’s disease preclinical studies. EMBO J. 2017;36(17):2473–87. source

  • Classified as probably not a substantial claim. May combine two claims.

    Premisecitation

    Previously, the authors reported that AppNL-G-F mice exhibit anxiolytic-like phenotypes in the elevated plus maze at 6 months of age and a subtle decline in spatial learning during Barnes maze acquisition at 8 months.

    “Previously, we reported that AppNL-G-F mice exhibit anxiolytic-like phenotypes in the elevated plus maze task at 6 months of age, as well as a subtle decline in spatial learning ability during the acquisition session of the Barnes maze task at 8 months [14].”
    Quote in the paperSubstantial claim1 of 1 sources checked
    • cites [14] Sakakibara Y, Sekiya M, Saito T, Saido TC, Iijima KM. Cognitive and emotional alterations in App knock-in mouse models of Abeta amyloidosis. BMC Neurosci. 2018;19:46. source

  • May combine two claims.

    Premisecitation

    In AppNL-G-F mice, Aβ amyloidosis is aggressive, and neuroinflammation is observed in subcortical structures as well as cortical regions.

    “In AppNL-G-F mice, which harbor all three mutations, Aβ amyloidosis is aggressive, and neuroinflammation is observed in subcortical structures as well as cortical regions [10–12].”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source
    • cites [11] Masuda A, Kobayashi Y, Kogo N, Saito T, Saido TC, Itohara S. Cognitive deficits in single App knock-in mouse models. Neurobiol Learn Mem. 2016;135:73–82. source
    • cites [12] Mehla J, Lacoursiere SG, Lapointe V, McNaughton BL, Sutherland RJ, McDonald RJ, Mohajerani MH. Age-dependent behavioral and biochemical characterization of single APP knock-in mouse (APP(NL-G-F/NL-G-F)) model of Alzheimer’s disease. Neurobiol Aging. 2019;75:25–37. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    The first successful mouse models reproducing Aβ pathologies overexpressed human APP with either a single Swedish or Indiana mutation.

    “The first successful mouse models reproducing Aβ pathologies overexpressed human APP with either a single Swedish [25, 26] or Indiana [27] mutation.”
    Quote in the paperNot a substantial claim1 of 3 sources checked
    • cites [25] Hsiao K, Chapman P, Nilsen S, Eckman C, Harigaya Y, Younkin S, Yang F, Cole G. Correlative memory deficits, Abeta elevation, and amyloid plaques in transgenic mice. Science. 1996;274(5284):99–102. source
    • cites [26] Sturchler-Pierrat C, Abramowski D, Duke M, Wiederhold KH, Mistl C, Rothacher S, Ledermann B, Burki K, Frey P, Paganetti PA, et al. Two amyloid precursor protein transgenic mouse models with Alzheimer disease-like pathology. Proc Natl Acad Sci USA. 1997;94(24):13287–92. source
    • cites [27] Games D, Adams D, Alessandrini R, Barbour R, Berthelette P, Blackwell C, Carr T, Clemens J, Donaldson T, Gillespie F, et al. Alzheimer-type neuropathology in transgenic mice overexpressing V717F beta-amyloid precursor protein. Nature. 1995;373(6514):523–7. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Familial AD mutations in APP and PSEN1 genes have been utilized to develop mouse models bearing Aβ pathologies including amyloid plaques and cerebral amyloid angiopathy.

    “Familial AD mutations in APP and PSEN1 genes have been utilized to develop mouse models bearing Aβ pathologies including amyloid plaques and cerebral amyloid angiopathy [2].”
    Quote in the paperNot a substantial claim1 of 1 sources checked
    • cites [2] Jankowsky JL, Zheng H. Practical considerations for choosing a mouse model of Alzheimer’s disease. Mol Neurodegener. 2017;12:89. source

  • May combine two claims.

    Premisecitation

    These mouse models suffered from potential off-target effects caused by non-physiological overexpression of APP/PSEN1 genes and/or combinations of familial AD mutations, which are not observed in AD patients.

    “they also suffered from potential off-target effects caused by either non-physiological overexpression of APP/PSEN1 genes and/or combinations of familial AD mutations, which are not observed in AD patients [2, 9].”
    Quote in the paperNot a substantial claim2 of 2 sources checked
    • cites [2] Jankowsky JL, Zheng H. Practical considerations for choosing a mouse model of Alzheimer’s disease. Mol Neurodegener. 2017;12:89. source

      In “Yin and yang of mouse models” (page unavailable), the paper warns that APP overexpression can produce phenotypes unrelated to Alzheimer’s pathology. “Matching your model to your experimental question” (page unavailable) describes mice combining several familial APP and PSEN1 mutations. The cited passages do not establish that those combinations cause off-target effects or that the combinations are absent in AD patients; they also do not establish the same overexpression concern for PSEN1. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [9] Sasaguri H, Nilsson P, Hashimoto S, Nagata K, Saito T, De Strooper B, Hardy J, Vassar R, Winblad B, Saido TC. APP mouse models for Alzheimer’s disease preclinical studies. EMBO J. 2017;36(17):2473–87. source

      The “Limitations of first-generation mouse models” section warns that APP or APP/PS overexpression can produce artifacts and phenotypes outside normal disease pathology. The paper also describes models combining several familial AD mutations, but the cited passages do not establish that those combinations are never observed in AD patients or that the combinations themselves cause the asserted off-target effects. Page numbers were not available in our copy. (LLM, conf=0.83)

      Experimental — accuracy not yet measured

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Premisecitation

    Recent studies reported negligible cognitive deficits and lack of Aβ plaque formation in AppNL/NL mice.

    “These results are consistent with recent studies reporting negligible cognitive deficits and the lack of Aβ plaque formation in AppNL/NL mice (Fig. 6) [10, 11, 13, 14, 24].”
    Quote in the paperNot a substantial claim2 of 3 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source
    • cites [11] Masuda A, Kobayashi Y, Kogo N, Saito T, Saido TC, Itohara S. Cognitive deficits in single App knock-in mouse models. Neurobiol Learn Mem. 2016;135:73–82. source
    • cites [13] Salas IH, Callaerts-Vegh Z, D’Hooge R, Saido TC, Dotti CG, De Strooper B. Increased insoluble amyloid-beta induces negligible cognitive deficits in old AppNL/NL Knock-In Mice. J Alzheimers Dis. 2018;66(2):801–9. source

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    Dozens of mouse lines overexpressing several combinations of APP and PSEN1 mutations have been created to accelerate the onset of Aβ pathologies in brains.

    “dozens of mouse lines overexpressing several combinations of APP and PSEN1 mutations have been created to accelerate the onset of Aβ pathologies in brains [28–30].”
    Quote in the paperNot a substantial claim3 of 3 sources checked
    • cites [28] Jankowsky JL, Fadale DJ, Anderson J, Xu GM, Gonzales V, Jenkins NA, Copeland NG, Lee MK, Younkin LH, Wagner SL, et al. Mutant presenilins specifically elevate the levels of the 42 residue beta-amyloid peptide in vivo: evidence for augmentation of a 42-specific gamma secretase. Hum Mol Genet. 2004;13(2):159–70. source

      The Introduction (p. 2) and Figure 2 (p. 4) describe APP-mutant mice co-expressing different PS1 mutations and show that co-expression accelerates brain amyloid deposition. The Generation of transgenic mice section (p. 8) identifies several lines, but this paper does not establish that dozens of such lines have been created. (LLM, conf=0.86)

      Experimental — accuracy not yet measured
    • cites [29] Oakley H, Cole SL, Logan S, Maus E, Shao P, Craft J, Guillozet-Bongaarts A, Ohno M, Disterhoft J, Van Eldik L, et al. Intraneuronal beta-amyloid aggregates, neurodegeneration, and neuron loss in transgenic mice with five familial Alzheimer’s disease mutations: potential factors in amyloid plaque formation. J Neurosci. 2006;26(40):10129–40. source

      In “Transgenic strategy and generation of 5XFAD mice” (page unavailable), the paper says the authors combined APP and PS1 mutations to accelerate amyloid deposition and selected three coexpressing lines for study. It does not establish that dozens of lines with several different mutation combinations had been created. (LLM, conf=0.85)

      Experimental — accuracy not yet measured
    • cites [30] Radde R, Bolmont T, Kaeser SA, Coomaraswamy J, Lindau D, Stoltze L, Calhoun ME, Jaggi F, Wolburg H, Gengler S, et al. Abeta42-driven cerebral amyloidosis in transgenic mice reveals early and robust pathology. EMBO Rep. 2006;7(9):940–6. source

      The Introduction describes the creation of mice coexpressing mutated APP and PS1, and the Discussion reports earlier amyloid deposition in this model than in other transgenic models. The paper also mentions several APP and APP/PS1 lines, but it does not establish that dozens of lines with several mutation combinations were created. (LLM, conf=0.85)

      Experimental — accuracy not yet measured

  • May combine two claims.

    Premisecitation

    Findings on Morris water maze deficits in AppNL-G-F/NL-G-F mice are inconsistent: two groups reported no obvious deficits up to 12 months of age, whereas another reported robust deficits at 6 months of age.

    “for example, in the MWM task, two groups have reported that AppNL-G-F/NL-G-F mice develop no obvious deficits in spatial learning and memory up to 12 months of age [21, 23], whereas another reported robust learning and memory deficits in AppNL-G-F/NL-G-F mice at 6 months of age [12].”
    Quote in the paperSubstantial claim1 of 3 sources checked
    • cites [21] Latif-Hernandez A, Shah D, Craessaerts K, Saido T, Saito T, De Strooper B, Van der Linden A, D’Hooge R. Subtle behavioral changes and increased prefrontal-hippocampal network synchronicity in APP(NL-G-F) mice before prominent plaque deposition. Behav Brain Res. 2017;. https://doi.org/10.1016/j.bbr.2017.11.017 . source

      Section 3.4 (Spatial learning and memory; page unavailable) reports similar Morris water maze performance at 6–7 and 10–11 months, supporting the no-obvious-deficit part of the claim. The paper did not test mice at 12 months, and Section 3.5 reports a marginal reversal-memory difference at 6–7 months. The robust deficits attributed to [12] are not attributed to this source. (LLM, conf=0.84)

      Experimental — accuracy not yet measured
    • cites [23] Whyte LS, Hemsley KM, Lau AA, Hassiotis S, Saito T, Saido TC, Hopwood JJ, Sargeant TJ. Reduction in open field activity in the absence of memory deficits in the App(NL-G-F) knock-in mouse model of Alzheimer’s disease. Behav Brain Res. 2018;336:177–81. source
    • cites [12] Mehla J, Lacoursiere SG, Lapointe V, McNaughton BL, Sutherland RJ, McDonald RJ, Mohajerani MH. Age-dependent behavioral and biochemical characterization of single APP knock-in mouse (APP(NL-G-F/NL-G-F)) model of Alzheimer’s disease. Neurobiol Aging. 2019;75:25–37. source

  • May combine two claims.

    Findingown data

    AppNL/NL mice did not develop overt brain pathologies, including Aβ deposition and reactive gliosis, in contrast to AppNL-G-F/NL-G-F mice.

    “Moreover, in sharp contrast to AppNL-G-F/NL-G-F mice, AppNL/NL mice did not develop overt brain pathologies, including Aβ deposition and reactive gliosis (Fig. 3)”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Premisecitation

    AppNL-G-F mice harbor three familial AD mutations (Swedish, Beyreuther/Iberian, and Arctic).

    “alternative mouse models have been generated via knock-in (KI) of a humanized Aβ sequences harboring familial AD mutations (Swedish (NL), Beyreuther/Iberian (F), and Arctic (G)) in order to model Aβ amyloidosis without non-physiological overexpression of APP [10].”
    Quote in the paperNot a substantial claim0 of 1 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source

  • May combine two claims.

    Interpretationown data

    Introduction of the Swedish mutation alone in endogenous APP is not sufficient to produce either AD-related brain pathology or cognitive deficits in mice.

    “Our data also indicate that introduction of the Swedish mutation alone in endogenous APP is not sufficient to produce either AD-related brain pathology or cognitive deficits in mice.”
    Quote in the paperSubstantial claim
    • Rests on an assumption: The AppNL-G-F/NL-G-F and AppNL/NL mice differ only in the intended mutations and resulting pathology, so the cognitive differences are attributable to Aβ plaques and gliosis.

  • May combine two claims.

    Interpretationown data

    AppNL-G-F/NL-G-F mice had reduced spatial memory 1 day after the last training session, but still exhibited a spatial bias toward the former platform location.

    “Together, these results suggest that AppNL-G-F/NL-G-F mice had reduced spatial memory 1 day after the last training session, but still exhibited a spatial bias toward the former location of platform.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    Two probe tests were conducted to confirm that the spatial task was acquired based on navigation by distal cues.

    “To confirm that this spatial task was acquired based on navigation by distal cues, two probe tests were conducted as following”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    Visible training was used to exclude mice with motor, visual or motivational impairments.

    “The aim of the visible training was to exclude mice with motor, visual or motivational impairments.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim.

    Study design and conductnone given

    Total distance travelled and swimming speed were measured to rule out motor function and motivation as confounding factors.

    “Total distance travelled (cm) and swimming speed (cm/s) were also measured to rule out the involvement of motor function and motivation to search the platform as confounding factors.”
    Quote in the paperSubstantial claim

  • Classified as probably not a substantial claim.

    Premisecitation

    KI mouse models with familial AD mutations have been generated to overcome these issues.

    “To overcome these issues, KI mouse models with familial AD mutations have been generated [10, 24, 31, 32].”
    Quote in the paperSubstantial claim0 of 3 sources checked
    • cites [10] Saito T, Matsuba Y, Mihira N, Takano J, Nilsson P, Itohara S, Iwata N, Saido TC. Single App knock-in mouse models of Alzheimer’s disease. Nat Neurosci. 2014;17(5):661–3. source
    • cites [24] Reaume AG, Howland DS, Trusko SP, Savage MJ, Lang DM, Greenberg BD, Siman R, Scott RW. Enhanced amyloidogenic processing of the beta-amyloid precursor protein in gene-targeted mice bearing the Swedish familial Alzheimer’s disease mutations and a “humanized” Abeta sequence. J Biol Chem. 1996;271(38):23380–8. source
    • cites [31] Guo Q, Fu W, Sopher BL, Miller MW, Ware CB, Martin GM, Mattson MP. Increased vulnerability of hippocampal neurons to excitotoxic necrosis in presenilin-1 mutant knock-in mice. Nat Med. 1999;5(1):101–6. source
20 of 20

  • The paper relies on this without support.

    Reactive gliosis (microgliosis and astrocytosis) is a marker of sustained neuroinflammation.

    “Aβ plaque formation, followed by sustained neuroinflammation, is necessary for the induction of definitive cognitive deficits in App-KI mouse models of AD.”

  • The paper relies on this without support.

    Aβ plaque formation precedes and causes the reactive gliosis.

    “Aβ plaque formation, followed by sustained neuroinflammation, is necessary for the induction of definitive cognitive deficits in App-KI mouse models of AD.”

  • The paper relies on this without support.

    The AppNL-G-F/NL-G-F and AppNL/NL mice differ only in the intended mutations and resulting pathology, so the cognitive differences are attributable to Aβ plaques and gliosis.

    “By contrast, 24-month-old AppNL/NL mice had intact spatial learning and memory relative to WT mice.”

  • The paper relies on this without support.

    The cognitive deficits in AppNL-G-F/NL-G-F mice are due to Aβ-related pathology and not to other effects of the mutations.

    “These results indicate that introduction of the Swedish mutation in endogenous APP is not sufficient to produce brain pathology or cognitive deficits in mice, and suggest that Aβ-related pathology is required to induce these cognitive deficits.”
4 of 4

Statistics that don’t add up

Each reported p-value recomputed from its test statistic and degrees of freedom.

  • Inconsistent p-value: t(16) = − 3.30, p < .001

    Minor

    The paper reports p < .001 here; recomputing from the test statistic and its degrees of freedom gives p = .005 (two-tailed). The check cannot tell whether the statistic or the p-value is the misprint.

    Reported p < .001 · recomputed p = .005

1 of 1

Statistics recomputed

Every reported test result, recomputed from its test statistic and degrees of freedom. A result shows as not adding up only once an independent check has confirmed it.

  • Doesn’t add upt(16) = -3.3reported p < .001 · recomputed p = .005

    “t(16) = − 3.30, p < .001”

  • Consistentt(16) = -4.45reported p < .001 · recomputed p < .001

    “t(16) = − 4.45, p < .001”

  • Consistentt(15) = -2.14reported p = .049 · recomputed p = .049

    “t(15) = − 2.14, p = .049”

  • Consistentt(32) = 4.45reported p < .001 · recomputed p < .001

    “t(32) = 4.45, p < .001”

  • Consistentt(30) = 2.14reported p = .04 · recomputed p = .041

    “t(30) = 2.14, p = .040”

  • Consistentt(15) = 1.7reported p = .11 · recomputed p = .110

    “t(15) = 1.70, p = .110”

  • Consistentt(32) = 3.3reported p = .002 · recomputed p = .002

    “t(32) = 3.30, p = .002”

  • Consistentt(30) = -1.7reported p = .099 · recomputed p = .099

    “t(30) = − 1.70, p = .099”

  • Consistentt(20) = 2.8reported p = .011 · recomputed p = .011

    “t(20) = 2.80, p = .011”

  • Consistentt(10) = -2.8reported p = .019 · recomputed p = .019

    “t(10) = − 2.80, p = .019”

  • Consistentt(20) = 5.93reported p < .001 · recomputed p < .001

    “t(20) = 5.93, p < .001”

  • Consistentt(10) = -5.94reported p < .001 · recomputed p < .001

    “t(10) = − 5.94, p < .001”

12 of 12

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Path efficiency is defined using opposite ratios

    Minor

    The Results describe path efficiency as actual distance divided by ideal distance, but the Methods define it as the direct distance to the platform divided by total distance travelled. These ratios are reciprocals, so they cannot both describe the reported measure.

1 of 1

Cites

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Cited by

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Related

Authors
Sakakibara, Y., Sekiya, M., Saito, T., Saido, T. C., & Iijima, K. M.
Affiliations
  • National Center for Geriatrics and Gerontology (JP)
  • RIKEN Center for Brain Science (JP)
  • Nagoya City University (JP)
Corresponding author
  • Sakakibara, Yasufumi
  • Iijima, Koichi M.
ORCID
Venue
BMC Neuroscience
Publisher
Springer Science and Business Media LLC
Published
2019-03-20
Volume
20
Issue
1
Pages
13-13
ISSN
1471-2202 (ISSN-L)
DOI
10.1186/s12868-019-0496-6
PMC
PMC6425634
OpenAlex
W2942242922
Semantic Scholar
9333aedf0b2775bdb9f7199b9cda6c7cc42cd882
Cited by
65
References
39
Citations by year
2026: 5 · 2025: 7 · 2024: 10 · 2023: 6 · 2022: 17 · 2021: 10 · 2020: 8 · 2019: 2
FWCI
5.27
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Neuroscience (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • Europe PMC (PubMed Central) (submittedVersion, cc-by)
  • PubMed Central (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Japan Society for the Promotion of Science (JP18K15381)
  • National Center for Geriatrics and Gerontology (28-26)
  • Takeda Science Foundation
  • DAIKO FOUNDATION
Topics
  • Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
  • Life Sciences › Neuroscience › Neurology › Neuroinflammation and Neurodegeneration Mechanisms
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Keywords
Alzheimer's disease, amyloid plaques, reactive gliosis, APP knock-in mice, familial Alzheimer's disease mutations, Swedish mutation, spatial learning and memory deficits, neuroinflammation, microglial activation, astrocyte activation, cognitive impairment
MeSH terms
Alzheimer Disease, Animals, Brain, Disease Models, Animal, Gliosis, Humans, Inflammation, Male, Mice, Inbred C57BL, Mice, Transgenic, Peptide Fragments, Amyloid beta-Peptides, Amyloid beta-Protein Precursor, Maze Learning, Gene Knock-In Techniques, Plaque, Amyloid, Cognitive Dysfunction, Spatial Memory

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-21.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-21.

Cited sources are checked by gpt-6-sol.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

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