Histochemistry of young 5xFAD mice
In this study, we present the first quantification of amyloidosis, astrocytosis, and microgliosis in the lower cortex and the corpus callosum of young 5xFAD mice. The 5xFAD transgenic mouse was developed by Oakley et al. [
22] to co-express five familial forms of Alzheimer’s disease [APP K670 N/M671L (Swedish) + I716 V (Florida) + V717I (London) and PS1 M146L + L286 V]. 5xFAD mice are characterised by the early development of Aβ plaques, neuroinflammation, neuronal loss, and memory impairment [
22‐
24,
30,
31], all hallmarks of human Alzheimer’s disease. Therefore, these 5xFAD transgenic mice have been acknowledged as a useful model for better understanding the pathogenesis of human Alzheimer’s disease. In agreement with previous reports [
22,
24], we found that first signs of amyloidosis and gliosis were detectable in the lower cortex and the corpus callosum of 2.5-month-old 5xFAD mice, although area fractions of GFAP staining and Iba-1 staining did not differ significantly from those of age-matched controls. However, significant increases in both astrocytosis and microgliosis, which occurred in parallel to significant increases in the Aβ area fraction, were found in the lower cortex, as well as in the corpus callosum of 5xFAD mice at the age of 5 months. This is the same age at which first behavioural changes, namely hippocampus-dependent memory impairments, have been observed in 5xFAD mice [
22,
31]. Intriguingly, quantification of Aβ plaque load in 5-month-old 5xFAD mice compared with levels in 2.5-month-old 5xFAD mice revealed only minor increases when compared with the changes between 11- and 5-month-old 5xFAD mice. Taken together, this suggests that subtle changes in brain Aβ load and/or early development of gliosis are sufficient to cause memory deficits in an Alzheimer’s disease mouse model. Our data further point to the importance of Aβ in provoking an inflammatory response, since increases in gliosis appear to follow after the deposition of Aβ.
MRI T1 relaxation times in young 5xFAD mice
As there is currently urgent need for diagnostic tools capable of identifying early changes in the brain of patients with Alzheimer’s disease, we asked whether MRI T
1 relaxation time can be used (1) to distinguish wild-type and 5xFAD mice at an age characterised by early stages of Aβ plaque deposition and neuroinflammation and (2) to monitor disease progression in young 5xFAD mice. In a previous study, we have found that MRI T
1 of the lower cortex and the corpus callosum were significantly different between 11-month-old 5xFAD mice and age-matched wild-type controls [
25]. Brain tissue T
1 is dependent on tissue water content [
32] and is influenced by a variety of factors, which can include myelin density, axonal damage, oedema, or widening of extracellular space [
33]. However, the observed early development of amyloidosis and gliosis in young 5xFAD mice was not accompanied by significant changes in MRI T
1 relaxation time. The T
1 differences are small between 5-month-old WT and 5xFAD mice, representing a 6–7% change in the lower cortex and corpus callosum; and there was not a significant difference between T
1 relaxation times of 2.5- and 5-month-old 5xFAD. In a previous study [
25] we found T
1 reductions confined to specific brain regions, for example, the deep layers of the cortex; therefore, ROIs must be sized and placed appropriately to be able to capture these changes. Despite focusing our attention on the lower cortex and corpus callosum, T
1 values were not significantly different between 5-month-old 5xFAD and WT mice. Other studies have found no T
1 differences between AD and WT mice, for example, in PS/APP mice 16–23 months old [
34], and in ArcAβ mice, which have similar T
1 values to WT mice irrespective of age [
35]. It is not known, however, if the lack of T
1 change in those studies is due to the size and placement of ROIs or the use of different AD transgenic models.
We have suggested previously that the presence of Aβ plaques may explain differences in MRI T
1 between 11-month-old wild-type and 5xFAD mice [
25]. However, since the beginning of Aβ plaque deposition cannot be reliably detected by MRI T
1, this suggests that only substantial Aβ load causes significant changes in MRI T
1 (e.g., in the corpus callosum of 11-month-old mice, WT T
1 = 1.85 s versus 5xFAD T
1 = 1.72 s). This hypothesis is supported by our finding that the Aβ area fractions in lower cortex and corpus callosum of 11-month-old 5xFAD mice were more than 20–30 times larger than those determined for the corresponding brain regions in 5-month-old mice. In general, reports from other research laboratories of significant T
1 differences between AD and wild-type mice were in old mice when Aβ deposition is fully established [
36,
37]. Thus, an insufficient amount of Aβ in young 5xFAD mice could explain the lack of large differences in MRI T
1 relaxation times between young wild-type and 5xFAD mice. We cannot exclude that there might have been T
1 differences in other brain regions of the AD mouse, for example, the subiculum [
36]; in this work, analysis was restricted to the lower cortex and corpus callosum, where there are easily identifiable anatomical boundaries that help to minimise the subjective nature of ROI placement, and where T
1 changes in old mice were previously identified [
25]. Nevertheless, it should be noted that there is still the possibility that differences will be found in MRI studies at high magnetic field strengths (7.0 T and above) that provide higher signal-to-noise ratio and improved spatial resolution), with T
2 or T
2*-weighted imaging, which enables the detection of individual Aβ plaques in the mouse [
38‐
42], ex vivo human [
43], and plaque-like pathology in vivo human brain [
44], and, given the slow rate of Aβ deposition decades prior to the onset of clinical symptoms in AD [
2], direct visualisation of plaques as opposed to measuring indirect effects related to Aβ deposition may provide a better early diagnostic tool. However, there are unresolved questions over the specificity of this technique, and to date, most clinical studies use the lower field strength 3
T MRI. Further work is needed to develop diagnostic tools capable of detecting early changes in the brain of AD patients. Previous investigations have found magnetisation transfer ratio measurements a useful means of assessing changes in tissue integrity that may involve gliosis [
45‐
47] (an early event in AD); it would be of interest to assess other MRI methods such as MTR to give quantitative information on the AD mouse brain.
In providing in vivo evaluation of Aβ deposition, PET is closer to clinical application than MRI. PET tracers that allow direct, in vivo visualisation of Aβ are advancing in their development and may allow early detection and monitoring of treatment response. Increased Pittsburgh Compound B retention is found in AD patients compared with controls [
48,
49], and florbetaben, the third amyloid imaging agent to be approved for clinical use (Amyvid [Florbetapir F 18] was approved by the FDA in 2012 [
50], and Vizamyl [Flutemetamol F 18] was approved by the FDA in 2013 [
51]), demonstrated high sensitivity and specificity for detecting Aβ deposits, and high negative predictive value [
52]. That said, large-scale controlled trials are needed to assess further the usefulness of these techniques in people with early stage AD, who are more likely to benefit from treatment intervention targeting amyloid pathology. Furthermore, it is still important to assess other potential imaging modalities that may have use within the AD diagnostic framework as Aβ-targeted PET is not yet capable of diagnosing AD on its own.
The strength of this study is in the quantitative analysis of histological markers Aβ, GFAP, and Iba-1 in young 5xFAD mice, which takes into account all samples and allows a more objective analysis compared with simply describing changes seen by the eye. The limitations of this study relate to the relatively low MR imaging resolution (0.23 × 0.23 × 1 mm). Despite there being no compelling evidence to suggest the mean T
1 values differ between young 5xFAD and WT mice, we cannot reach a strong conclusion; repeated experiments with larger samples would be needed; however, given the very small differences in T
1 between 5-month-old 5xFAD and WT mice this would not be recommended based on the results of this study. The small size of the mouse brain poses challenges for high-resolution MR imaging. The use of high field MRI systems can deliver higher signal-to-noise ratio than what was achievable on the 4.7 T system used in this study; we cannot neglect the impact improved image quality and higher imaging resolution would have on improving detection. Another important limitation is the discrepancy between mouse models and AD brains, which may arise from differences in tissue composition and structure, for example, Aβ load, tissue-water content, iron accumulation, and loss of fibre tracts; therefore, the mouse model does not fully recapitulate all the features of AD. For example, important differences in the characteristics of plaques in human AD and APP/PS1 mice may provide different mechanisms of MR contrast changes: plaques in APP/PS1 mice contain less iron, but are more densely packed compared with human AD samples [
53]. Using voxel-based quantification, Su et al. found that AD was characterised by reduced T
1 values in certain brain regions, including bilateral temporal and parietal lobes in cross-sectional comparison, and an increase in T
1 in the right caudate, bilateral hippocampus, parahippocampus, and thalamus in longitudinal comparison [
20]. Increased T
1 values in white matter of AD patients has been reported [
54], and taken together this demonstrates the complex nature of T
1 changes in the human AD brain. Caution is needed when translating results from animal to human, and it would be important for future studies to assess more than one transgenic mouse model. The difference between changes in T
1 values in mouse models and human AD may also arise from the relatively low specificity of the measurement. Since brain tissue T
1 is dependent on a variety of factors, the effect of ongoing disease on tissue composition may confound using a simple T
1 relaxation time as a measure of treatment response or disease progression.