We investigated 20-week old APP/PS1 transgenic mice developing early cerebral plaque-like β-amyloidosis using high-field MRI at 7T prior to the onset of neurodegeneration (after age 34–36 weeks). We found a significant reduction of T2 relaxation times in the transgenic animals compared to wildtype controls in deeper neocortical layers, hippocampus and caudate-putamen using both manual ROI measurements in native space as well as automated voxel-based analysis in a group-specific common space. Moreover, this effect was independent of local atrophy, as grey matter maps did not differ in wildtype and APP/PS1-transgenic animals at this timepoint. We focussed with our investigation on the detection of early changes at the beginning of the cerebral amyloidosis prior to the onset of marked neurodegeneration. The rapid onset of amyloidosis as compared to APP-only models (e.g. Tg2576) does not replicate the development of AD, but it helps to investigate in vivo changes due to cerebral amyloidosis within a shorter time frame. The localization of the T2 relaxation time effects mapped the spatial distribution of Aβ-plaques and activated microglia in histological sections of the brain ().
To our knowledge, this is the first description of the high-field MRI features of the Thy1-promoter-driven APP/PS1 double mutant mouse model in vivo
. In this model, cerebral β-amyloidosis has been shown to start by 6 to 8 weeks of age, and to lead to significant plaque load in neocortex, hippocampus, thalamus and striatum by the age of 5 months [26
]. At age 8 months, the entire forebrain is laden with Aβ-positive plaques and loss of neurons becomes detectable.
Consistent with the early onset and spatial distribution of plaques in the transgenic mice, our animals showed significantly reduced T2 relaxation times at age 4.4 to 5 months in neocortex, hippocampus, CPu, and thalamus. Several studies have demonstrated an association of iron with plaques in humans and in mouse models of AD pathology [12
]. The iron has been localized to senile plaques and adjacent microglia, where it leads to paramagnetic susceptibility and consequent reductions of T2 relaxation times [17
]. Consistently, we identified iron accumulation in the center of the amyloid plaques in our transgenic mice ().
In agreement with the report that significant neuron loss does not begin until 8 months of age in this double transgenic model [26
], we did not find significant reductions of grey matter density in the transgenic mice when compared to the wildtype mice, and histological analysis with cell stains further indicates that neuronal loss is minimal or absent at age 5 months (). Moreover, there was no evidence of myelin changes or gross changes in the corpus callosum () that would also indicate significant neuronal loss in the cortex. It should be noted, however, that other mechanisms could compensate volumetrically for minor neuronal loss, for example, the volume effect of β-amyloid plaques and accompanying astrogliosis () or microgliosis (). Neuronal loss in this model has been reported at age 8 months and later [26
]. For comparison, APP/PS1 models resulting from intercrosses of two independent APP- and PS1-transgene strains exhibit atrophy at age 24 months and later that was detected by in vivo
MRI and histological evaluation [48
]. A PDAPP mouse model by [49
] showed significant reductions of commissural fibers already at 3.6 months of age that became more pronounced at 17 months of age, as detected by MRI. It has been suggested that the very early changes of commissural connections in this PDAPP model represent a neurodevelopmental abnormality induced by the PDAPP transgene construct rather than an effect of neurodegeneration induced by amyloid pathology.
Unexpectedly, we found reduced T2 relaxation times in the ventricular CSF spaces of the transgenic animals. Though the explanation for this outcome remains uncertain, one study in transgenic mice overexpressing the London mutant form of APP at age 24 months found high levels of Aβ in CSF [50
]. Therefore, high levels of Aβ, or possibly other substances related to cerebral Aβ deposition, in CSF may lead to reduced T2 relaxation times in CSF spaces, in agreement with the observation that higher viscosity of fluids decreases T2 relaxation times [51
]. This issue clearly merits further study.
In addition, we found significantly reduced T2 relaxation times in the cerebellum in the voxel-based analysis. The spatial distribution of the effects matched the extension of the cerebellar folia. In the histological analysis, these areas were devoid of amyloid plaques and amyloid-related microgliosis (). Astrogliosis occurred in cerebellar structures, but was localized to the cerebellar peduncles, sparing the cerebellar folia (). The close association between CSF spaces and grey matter folia in the cerebellum suggests that the observed signal reductions in the cerebellum are most likely due to partial volume effects from CSF spaces that have decreased T2 relaxation times, as seen in the forebrain regions. This interpretation is supported by the finding that after correcting the T2 relaxation time maps for the content of grey matter within each voxel as assessed from the TSE data, cortical areas showed reduced T2 relaxation times, but the cerebellum was devoid of almost any signal reductions. Segmentation of TSE scans into different tissue compartments is less accurate than for human structural MRI data and therefore induces additional variability into the voxel-based analysis, which can also bee seen by the reduced T-values compared to the uncorrected analysis. However, the lack of effects in the cerebellum is not only due to the reduced sensitivity of the analysis, since the effects in the cortex, although with reduced effect sizes, remained preserved.
In our histological analysis, we found iron accumulation in the center of the plaques (), supporting the association between T2 relaxation time reductions and plaque-related iron accumulation in forebrain regions. One study challenged the specificity of T2 relaxation time changes [24
]. In this longitudinal study, T2 relaxation times declined significantly over a one-year follow-up in the hippocampus and cortex of an APP/PS1 model that shows slightly later onset of cerebral β-amyloidosis than does the model used in our study [26
]. However, PS1 single-transgenic mice, which do not develop Aβ plaques, showed a significant, age-associated decline of T2 relaxation times as well. At the same time, however, these mice were reported not to differ from wildtype controls at baseline, as well as at both follow-up time points in cross-sectional analyses. As the wildtype mice showed no significant longitudinal decline in T2 relaxation times, it remained unclear why the PS single-transgenic mice had progressive decline of T2 relaxation times but never differed from wildtype mice at any time point in the cross-sectional analyses. A likely reason is the severe attrition of animal numbers over time, since the study began with 23 PS1 single-transgenic mice at baseline and ended with only four animals at the second follow-up. This attrition renders the estimates of rates of change unreliable. In contrast, cross-sectional analyses were performed with reasonable group sizes after data from single time-point acquisitions had been added.
The transgenic mice employed in our study represent a valuable model to investigate early onset cerebral β-amyloidosis. However, the morphology and composition of amyloid plaques differs across different mouse models and between transgenic models and AD patients [53
]. These differences may limit the translation of imaging findings in transgenic mouse models to human studies. The first attempts to undertake ultra-high-field MRI in human studies in AD at 7T suggest that plaque-related susceptibility alterations can be detected in vivo
in cortical areas [55
]. T2 relaxation time reductions were found to be associated with senile plaques, both in human brain tissue as well as in post mortem
APP/PS1 transgenic mouse brains [16
]. T2* contrast reductions were well-matched with iron deposits within and close to senile plaques in post mortem
samples of AD patients’ brains. In contrast, there were reductions of the T2* signal that corresponded to the location of plaques in APP/PS1 mice that develop cerebral β-amyloidosis after 1 year of age, but in the absence of significant iron deposits. The authors suggested that the detection of the murine plaques via the T2 effect was related to their higher fibrillar organization and density compared to human plaques. So different morphological changes may lead to similar signal changes in MRI, limiting the inference from MRI signal changes on the underlying plaque morphology. In our transgenic model, we consistently found a significant amount of iron within and in proximity to senile plaques, suggesting that iron is a significant contributor to T2 relaxation time reduction in this context.
The absolute T2 values we measured in our study were higher than those reported in other animal studies [17
], but are comparable to those observed in a human investigation [56
]. These differences may partly be due to the pulse sequence parameters used. Additionally, the processing of the data likely had an influence. In previous experiments, multiecho data were fitted to an exponential function, but no details were given as to whether the data were processed to exclude overall noise levels [17
]. The human study did not employ noise level corrections [56
]. We used the raw data without correcting for the effects of noise as well. However, we also estimated noise levels through the signal intensity in an ROI that was placed at the maximum distance from the measured object. Signal intensity in this ROI was nearly identical across the different echo times. Therefore, when considering noise levels, the signal was relatively more reduced with higher echo times, yielding a steeper decay function of the T2 signal. After correcting for noise levels, our T2 values were close to those in the previous animal studies [17
]. However, since the between-group effects were not affected by the noise level correction of the data, we decided to use the T2 time measurements derived from the raw data.
There is a wide range of MRI based diagnostic markers in AD, from visual rating of hippocampus atrophy [57
] through manual [58
] and automated [59
] hippocampus volumetry, and cortical thickness measurement [60
] to automated detection of high resolution differences in brain morphology using deformation based morphology and multivariate analysis such as principal component analysis [61
] or machine learning algorithms such as support vector machines [62
]. These approaches yield an accuracy of about 80% in the prediction of AD in at risk subjects such as patients with the clinical syndrome of amnestic mild cognitive impairment [63
]. In vivo amyloid imaging techniques will help in future to shift the diagnosis of AD into presymptomatic stages. A recent model on the dynamic use of biomarkers in AD [64
] suggests that amyloid pathology precedes the loss of cortical neurons, as detected by structural MRI. However, the specificity of amyloid load findings in the brain for predicting AD in cognitively normal subjects remains to be shown. Additionally, amyloid imaging in combination with functional and structural markers of brain changes based on MRI will help us to better understand the dynamic sequence of molecular changes, such as amyloid accumulation, synaptic dysfunction and neuronal loss. In future, the combined use of these markers will help to improve our models on the development of AD pathology in the brain.
In summary, we found significant reductions of T2 relaxation times in cortical and subcortical brain areas that corresponded to the pattern of Aβ accumulation and reactive gliosis shown in subsequent histological analyses (). The APP/PS1-related effects on T2 relaxation times occurred in the absence of obvious morphological brain changes (besides the occurrence of senile plaques), as shown both in vivo in the grey matter density maps and post mortem in histological sections. Our findings suggest that the APP/PS1 transgenic model can serve as a useful model for the high-field MRI analysis of brain changes related to cerebral β-amyloidosis. Due to the earlyonset and rapid progression of Aβ pathology, the APP/PS1 mouse also could be employed for the efficient testing of therapeutic interventions that would be expected to influence Aβ load and associated MR signal. Moreover, our data suggest that voxel-based analysis can readily be employed as an observer-independent and automated approach to detecting in vivo surrogate markers of β-amyloid load and related tissue changes throughout the brain.