In vivo detection of gray matter neuropathology in the 3xTg mouse model of alzheimer’s disease with diffusion tensor imaging.
Open accessAbstract
A diagnosis of Alzheimer's disease (AD), a neurodegenerative disorder accompanied by severe functional and cognitive decline, is based on clinical findings, with final confirmation of the disease at autopsy by the presence of amyloid-β (Aβ) plaques and neurofibrillary tangles. Given that microstructural brain alterations occur years prior to clinical symptoms, efforts to detect brain changes early could significantly enhance our ability to diagnose AD sooner. Diffusion tensor imaging (DTI), a type of MRI that characterizes the magnitude, orientation, and anisotropy of the diffusion of water in tissues, has been used to infer neuropathological changes in vivo. Its utility in AD, however, is still under investigation. The current study used DTI to examine brain regions susceptible to AD-related pathology; the cerebral cortex, entorhinal cortex, and hippocampus, in 12-14-month-old 3xTg AD mice that possess both Aβ plaques and neurofibrillary tangles. Mean diffusivity did not differ between 3xTg and control mice in any region. Decreased fractional anisotropy (p < 0.01) and axial diffusivity (p < 0.05) were detected only in the hippocampus, in which both congophilic Aβ plaques and hyperphosphorylated tau accumulation, consistent with neurofibrillary tangle formation, were detected. Pathological tau accumulation was seen in the cortex. The entorhinal cortex was largely spared from AD-related neuropathology. This is the first study to demonstrate DTI abnormalities in gray matter in a mouse model of AD in which both pathological hallmarks are present, suggesting the feasibility of DTI as a non-invasive means of detecting brain pathology in vivo in early-stage AD.
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FA in the cortex was reported to increase in 3xTg AD mice, while FA was reduced in APP transgenic mice.
“For instance, FA in the cortex was reported to increase in 3xTg AD mice (Snow et al., 2017; Manno et al., 2019), while the FA was showed reduced in APP transgenic mice (Muller et al., 2013; Qin et al., 2013).”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Snow et al., 2017
Snow et al.’s DTI measures section reports no significant difference in cortical FA between 3xTg and control mice; Table 1 lists 0.31 versus 0.33 (p = 0.8). It reports reduced FA in the hippocampus instead. The APP-mouse clause is cited to other papers, not Snow et al. (LLM, conf=0.90)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredWithin the hippocampus, significant changes of diffusion metrics (FA, MD, AxD, and RD) were observed in 3×Tg-AD mice compared with controls, with decreased FA and AxD at both 2 and 8 months, and increased RD at 12 and 14 months.
“Within the hippocampus, significant changes of diffusion metrics (FA, MD, AxD, and RD) were observed in 3×Tg-AD mice compared with controls, with decreased FA and AxD at both 2 and 8 months (Falangola et al., 2021), and increased RD at 12 and 14 months (Snow et al., 2017).”
From Multimodal MRI combined with RNA sequencing reveals pathological signatures in the 9-month-old 3×Tg-AD mouse brain (2026) · cites this paper as Snow et al., 2017
The Snow citation is attached to the increased-RD finding. In the DTI measures and Discussion sections (pages unavailable), the paper reports a significant RadD increase in the slice containing the hippocampus, but explicitly says there was no difference within the hippocampal region itself. Its results group mice aged 12–14 months rather than reporting separate findings at 12 and 14 months. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe FA increase could represent a rise before the fall; rising in FA prior to AD onset and falling during plaque build-up.
“Here, the FA increase observed is different from previous reports in humans (Sexton et al., 2011) and mouse models (Sun et al., 2005, 2014; Snow et al., 2017), which could represent a rise before the fall; rising in FA prior to AD onset and falling during plaque build-up (Sun et al., 2005, 2014; Snow et al., 2017).”
From Early stage alterations in white matter and decreased functional interhemispheric hippocampal connectivity in the 3xTg mouse model of Alzheimer’s disease. (2019) · cites this paper as Snow et al., 2017
The Discussion reports decreased hippocampal FA in symptomatic 3xTg mice whose hippocampi contained both amyloid plaques and neurofibrillary tangles. It does not report FA rising before AD onset or track a subsequent fall during plaque build-up; those parts of the proposed trajectory remain unsupported. (LLM, conf=0.83)
Experimental — accuracy not yet measuredThe FA increase observed in the 3xTg-AD is different from previous reports in humans and mouse models.
“Here, the FA increase observed is different from previous reports in humans (Sexton et al., 2011) and mouse models (Sun et al., 2005, 2014; Snow et al., 2017), which could represent a rise before the fall; rising in FA prior to AD onset and falling during plaque build-up (Sun et al., 2005, 2014; Snow et al., 2017).”
From Early stage alterations in white matter and decreased functional interhemispheric hippocampal connectivity in the 3xTg mouse model of Alzheimer’s disease. (2019) · cites this paper as Snow et al., 2017
The Discussion reports decreased hippocampal FA in 3xTg mice, supporting the comparison with the citing paper’s observed increase. It also reports plaques in the affected hippocampus, but does not establish that FA rises before AD onset and then falls during plaque build-up; that temporal sequence is not supported by Snow et al. (LLM, conf=0.86)
Experimental — accuracy not yet measuredDecreased FA was detected in the hippocampus in the 12-14-month-old 3xTG AD mice.
“In contrast, decreased FA was detected in the hippocampus in the 12-14-month-old 3xTG AD mice (Snow et al., 2017).”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Snow et al., 2017
DTI studies of AD models with marked neuron loss indicate increased MD, whereas those of a mild neuropathological phenotype without neuron loss tend to report decreased MD.
“It’s also suggested that DTI studies of AD models with marked neuron loss indicate increased MD, whereas those of a mild neuropathological phenotype without neuron loss tend to report decreased MD (Snow et al., 2017).”
From Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging (2022) · cites this paper as Snow et al., 2017
Another study of an overlapping age range (12-14 months) found that the 3xTg-AD developed decreases in FA and axial diffusivity (AD λ//).
“but in another study of an overlapping age range (12–14 months) the 3xTg-AD developed decreases in FA and axial diffusivity (AD λ//; Snow et al., 2017).”
From Early stage alterations in white matter and decreased functional interhemispheric hippocampal connectivity in the 3xTg mouse model of Alzheimer’s disease. (2019) · cites this paper as Snow et al., 2017
In the 3xTg-AD model, at later time points (at least 11 months), FA was decreased.
“Results in the literature using the same model indicate that at later time points (at least 11 months) FA was decreased in the 3xTg-AD (Snow et al., 2017)”
From Early stage alterations in white matter and decreased functional interhemispheric hippocampal connectivity in the 3xTg mouse model of Alzheimer’s disease. (2019) · cites this paper as Snow et al., 2017
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MRI analysis of brain connectivity in a mouse model of Alzheimer’s disease
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- Authors
- Snow, W. M., Dale, R., O’Brien-Moran, Z., Buist, R., Peirson, D., Martin, M., & Albensi, B. C.
- Affiliations
- St. Boniface Hospital (CA)
- The University of Winnipeg (CA)
- University of Manitoba (CA)
- Corresponding author
- Snow, Wanda M.
- Albensi, Benedict C.
- Venue
- Journal of Alzheimer s Disease
- Publisher
- SAGE Publications
- Published
- 2017-06-05
- Volume
- 58
- Issue
- 3
- Pages
- 841-853
- ISSN
- 1387-2877 (ISSN-L)
- 1875-8908
- PMC
- PMC5467717
- OpenAlex
- W2612644294
- Cited by
- 29
- References
- 58
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 1 · 2023: 2 · 2022: 4 · 2021: 3 · 2020: 5 · 2019: 5 · 2018: 3
- FWCI
- 2.73
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Alzheimer s Disease (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- Research Manitoba
- University of Manitoba
- Alzheimer's Society
- University College London
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
- Keywords
- Alzheimer's disease, 3xTg mouse model
- MeSH terms
- Alzheimer Disease, Animals, Cerebral Cortex, Disease Models, Animal, Female, Hippocampus, Magnetic Resonance Imaging, Male, Mice, Inbred C57BL, Mice, Transgenic, Neurofibrillary Tangles, Diffusion Tensor Imaging, Plaque, Amyloid, Gray Matter
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.
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