Cited by 157Alzheimer's disease research and treatmentsNeuroinflammation and Neurodegeneration MechanismsDementia and Cognitive Impairment Research

Recent advances in the modeling of Alzheimer’s disease

Open access
Sasaguri, Hiroki, Hashimoto, Shoko, Watamura, Naoto, Sato, Kaori, Takamura, Risa, Nagata, Kenichi, Tsubuki, Satoshi, Ohshima, Toshio +10 more·2022·Frontiers in Neuroscience

Abstract

Since 1995, more than 100 transgenic (Tg) mouse models of Alzheimer’s disease (AD) have been generated in which mutant amyloid precursor protein (APP) or APP/presenilin 1 (PS1) cDNA is overexpressed (1st generation models). Although many of these models successfully recapitulate major pathological hallmarks of the disease such as amyloid β peptide (Aβ) deposition and neuroinflammation, they have suffered from artificial phenotypes in the form of overproduced or mislocalized APP/PS1 and their functional fragments, as well as calpastatin deficiency-induced early lethality, calpain activation, neuronal cell death without tau pathology, endoplasmic reticulum stresses, and inflammasome involvement. Such artifacts bring two important uncertainties into play, these being (1) why the artifacts arise, and (2) how they affect the interpretation of experimental results. In addition, destruction of endogenous gene loci in some Tg lines by transgenes has been reported. To overcome these concerns, single App knock-in mouse models harboring the Swedish and Beyreuther/Iberian mutations with or without the Arctic mutation (App NL–G–F and App NL–F mice) were developed (2nd generation models). While these models are interesting given that they exhibit Aβ pathology, neuroinflammation, and cognitive impairment in an age-dependent manner, the model with the Artic mutation, which exhibits an extensive pathology as early as 6 months of age, is not suitable for investigating Aβ metabolism and clearance because the Aβ in this model is resistant to proteolytic degradation and is therefore prone to aggregation. Moreover, it cannot be used for preclinical immunotherapy studies owing to the discrete affinity it shows for anti-Aβ antibodies. The weakness of the latter model (without the Arctic mutation) is that the pathology may require up to 18 months before it becomes sufficiently apparent for experimental investigation. Nevertheless, this model was successfully applied to modulating Aβ pathology by genome editing, to revealing the differential roles of neprilysin and insulin-degrading enzyme in Aβ metabolism, and to identifying somatostatin receptor subtypes involved in Aβ degradation by neprilysin. In addition to discussing these issues, we also provide here a technical guide for the application of App knock-in mice to AD research. Subsequently, a new double knock-in line carrying the App NL–F and Psen1P 117 L/WT mutations was generated, the pathogenic effect of which was found to be synergistic. A characteristic of this 3rd generation model is that it exhibits more cored plaque pathology and neuroinflammation than the App NL–G–F line, and thus is more suitable for preclinical studies of disease-modifying medications targeting Aβ. Furthermore, a derivative App G–F line devoid of Swedish mutations which can be utilized for preclinical studies of β-secretase modifier(s) was recently created. In addition, we introduce a new model of cerebral amyloid angiopathy that may be useful for analyzing amyloid-related imaging abnormalities that can be caused by anti-Aβ immunotherapy. Use of the App knock-in mice also led to identification of the α-endosulfine-KATP channel pathway as components of the somatostatin-evoked physiological mechanisms that reduce Aβ deposition via the activation of neprilysin. Such advances have provided new insights for the prevention and treatment of preclinical AD. Because tau pathology plays an essential role in AD pathogenesis, knock-in mice with human tau wherein the entire murine Mapt gene has been humanized were generated. Using these mice, the carboxy-terminal PDZ ligand of neuronal nitric oxide synthase (CAPON) was discovered as a mediator linking tau pathology to neurodegeneration and showed that tau humanization promoted pathological tau propagation. Finally, we describe and discuss the current status of mutant human tau knock-in mice and a non-human primate model of AD that we have successfully created.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.3389/fnins.2022.807473

Cites

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Human MAPT knock-in models produce tau pathology, but only very late in the murine life span (~15 months).

    “Human MAPT knock-in models have also been developed, and these models produce tau pathology, but only very late in the murine life span (~15 months) (Saito et al., 2014; Sakakibara et al., 2018; Sasaguri et al., 2022).”

    From β-amyloid accumulation enhances microtubule associated protein tau pathology in an APPNL-G-F/MAPTP301S mouse model of Alzheimer’s disease (2024) · cites this paper as Sasaguri et al., 2022

    The section “Humanization of the Entire Murine Mapt Gene to Generate hMAPT Knock-In Mice” (page unavailable) says that mice carrying human MAPT together with an App knock-in lacked evidence of tau pathology even at 24 months, contrary to the claimed onset at about 15 months. It separately reports aging-dependent tau aggregation in mutant MAPT knock-in mice, but gives no 15-month onset for those models. (LLM, conf=0.88)

    Checked by a reasoning model — may be wrong.

    Experimental — accuracy not yet measured
  • Models relying only on genetic modification of APP develop abundant Aβ plaques but produce little MAPT pathology beyond modest increases in phosphorylation.

    “Models relying only on genetic modification of amyloid precursor protein (APP) develop abundant Aβ plaques but produce little MAPT pathology beyond modest increases in phosphorylation (Sasaguri et al., 2022).”

    From β-amyloid accumulation enhances microtubule associated protein tau pathology in an APPNL-G-F/MAPTP301S mouse model of Alzheimer’s disease (2024) · cites this paper as Sasaguri et al., 2022

    Table 3 in “1st, 2nd, and 3rd Generation Mouse Models” records Aβ plaques but no tangles in two single-App knock-in lines; it also shows that another single-App line has no plaques. “Preclinical Nature of Behaviors” says App knock-in mice do not recapitulate tau pathology alone. The paper discusses increased tau phosphorylation in App/MAPT double knock-in mice, not specifically modest increases in APP-only models, so that detail is not established. (LLM, conf=0.83)

    Experimental — accuracy not yet measured

Self-check

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

The self-check needs the paper’s full text.

No citation lists for this paper

No citation lists for this paper yet — checked again daily.

References 130 · Cited by 157

Authors
Sasaguri, H., Hashimoto, S., Watamura, N., Sato, K., Takamura, R., Nagata, K., Tsubuki, S., Ohshima, T., Yoshiki, A., Sato, K., Kumita, W., Sasaki, E., Kitazume, S., Nilsson, P., Winblad, B., Saito, T., Iwata, N., & Saido, T. C.
Affiliations
  • RIKEN Center for Brain Science (JP)
  • Waseda University (JP)
  • Nagoya University (JP)
  • RIKEN BioResource Research Center (JP)
  • Central Institute for Experimental Animals (JP)
  • Fukushima Medical University (JP)
  • Karolinska Institutet (SE)
  • Nagoya City University (JP)
  • Nagasaki University (JP)
Corresponding author
  • Saito, Takashi
  • Iwata, Nobuhisa
  • Saido, Takaomi C.
Venue
Frontiers in Neuroscience
Published
2022-03-31
Volume
16
Pages
807473-807473
ISSN
1662-453X (ISSN-L)
OpenAlex
W4220790273
Cited by
157
References
130
Citations by year
2026: 23 · 2025: 38 · 2024: 50 · 2023: 37 · 2022: 9
FWCI
4.78
Type
journal article
Language
en
Open access
Locations
  • Frontiers in Neuroscience (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders
  • Japan Agency for Medical Research and Development (JP15dm0207001, JPMJMS2024, JP21gm1210010s0102, JP19dm0207065, JP18am0101036, JP21dk0207050h001)
  • Vetenskapsrådet (2018-02843, 2018-)
  • Hori Sciences and Arts Foundation
  • Bertil Hållstens Forskningsstiftelse
  • Nagoya City University (2021101)
  • Japan Society for the Promotion of Science (21H02831, 19K16271, 20H03564, JPMJMS2024, JP15dm0207001, 15K19036, 18K07402, 21K15378)
  • RIKEN
  • Moonshot Research and Development Program (JPMJMS2024)
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, transgenic mouse model, amyloid precursor protein, presenilin 1, APP knock-in mice, Arctic mutation, amyloid-beta pathology, amyloid-beta metabolism, neprilysin, insulin-degrading enzyme, somatostatin receptors, calpain, endoplasmic reticulum stress

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.

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.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review