Introduction

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with no effective treatments or biomarkers for definitive diagnosis. Observable changes in brain pathology can appear decades prior to clinical symptoms, substantiating the need for early detection and intervention.1,2 To this end, magnetic resonance imaging (MRI) and spectroscopy (MRS) offer a unique window into the brain; these neuroimaging techniques enable non-invasive, longitudinal assays of brain structure and tissue chemistry and are highly translatable from animal models to human subjects.3–5 To deconstruct the processes underlying disease progression and identify potential biomarkers, we performed longitudinal MRI, MRS, and behavioural testing in the TgF344-AD rat model, which recapitulates the full spectrum of Alzheimer’s neuropathology.6 Impaired spatial reference memory was present prior to the appearance of altered neurochemistry, both of which preceded major structural abnormalities.

Methods

TgF344-AD rats (n=26, 14M/12F) and wildtype littermates (n=24, 12M/12F) underwent MRI, MRS, and behavioural testing at 4-, 10-, 16-, and 18-months of age.MRI acquisition and volume estimation: High-resolution 3D anatomical MR images were acquired using Rapid Acquisition with Relaxation Enhancement (TR/TE=325/10.8ms, 114µm isotropic resolution) on a 7 Tesla Bruker Biospec 70/30 scanner. As described previously,7 pre-processing was performed using minc-toolkit-v2.8 The Pydpiper toolkit9 co-registered pre-processed images into a common space, generating voxelwise Jacobian deformation fields. The local volume of 120 brain regions was estimated using the Fischer 344 rat atlas.101H-MRS acquisition and analyses: Automated localized shimming was performed using the FASTMAP method11 prior to acquisition using Point RESolved Spectroscopy (TR/TE=3000/11ms) in the left dorsal hippocampus. Spectral preprocessing was performed in MATLAB using the FID-A toolkit.12 Processed spectra were analyzed using LCModel13 with a neurochemical basis set consisting of 18 metabolites and 9 macromolecules14 (Fig2.inset). Concentrations are reported referenced to water (mM). Barnes Maze: Spatial reference memory was assessed using a five-trial training protocol with a one-session probe test.15,16 Percent (%) time spent in the target quadrant and target holes, % success, number of holes searched, and speed were recorded during the probe trial. Statistics: Volumes were predicted using a linear mixed effects (LME) model with an interaction between quadratic age and genotype, a fixed effect of sex, and a random intercept per subject. Concentrations were predicted using an LME with an interaction between linear age and genotype with sex and water linewidth covaried, a random intercept per subject, and a weighting factor of the inverse absolute CRLB for each metabolite. Four age-centered models were also used to examine the main effect of genotype at each time point. For all LMEs, the False Discovery Rate (FDR) method17 applied at 5% was used to account for multiple comparisons. % time in target quadrant and target holes were analyzed using one-sample t-tests against a mean of 25%. % success, number of holes searched, and speed (cm/s) were analyzed using a linear model with genotype as a fixed effect and sex covaried. Bonferroni correction was applied across all tests (P-value<0.05/7) at each time point.

Results and Discussion

Volume changes are illustrated as t-statistic maps in Fig. 1A for voxel-wise (left) and regional (right) analyses. The strongest interactions were atrophy in the basal forebrain, caudoputamen, fimbria, hippocampus, and nucleus accumbens, unilateral atrophy in the right fornix, and hypertrophy in the dentate gyrus, as seen in Fig. 1B. Age-centered models indicated initial hypertrophy followed by significant atrophy at 16 and 18 months in several regions. Select linear model results are shown in Table 1. Models of human disease progression indicate tissue pathology and atrophy in many of these regions18,19 with additional reports of earlier volume increases,20,21 possibly as an initial compensatory response. As shown in Fig. 2, total choline and myo-inositol demonstrated positive age-by-genotype interactions but did not survive FDR correction. Age-centered models revealed decreased total creatine, taurine, and the ratio of N-acetylaspartate to myo-inositol, and increased Lactate and total choline in Tg rats at 10, 16, and 18 months. myo-inositol was higher in TgF344-AD rats at 16 and 18 months only. Select linear model results are shown in Table 2. These changes suggest dysfunction in mitochondrial bioenergetics, cell membrane turnover, gliosis, antioxidant capacity, and synaptic transmission, all of which are affected in human AD.22–24 TgF344-AD rats did not spend significantly more than a chance amount of time in the target quadrant or target holes at any time point (Fig. 3A,B), suggesting impaired long-term spatial reference memory by 4-months of age. TgF344-AD rats also demonstrated a lower % success rate and slower speed, and searched fewer holes overall (Fig. 3C-E). Deficits in hippocampus-dependent spatial memory are among the earliest complaints in AD subjects25 but typically appear later into disease progression than identified here.1 This may be due to inconsistencies in how cognitive dysfunction is tested or presents in humans versus rodents.

Conclusion

These findings support the use of MRI and MRS for the development of non-invasive biomarkers of disease progression, clarify the timing of pathological feature presentation in this model, and contribute to the validation of the TgF344-AD rat as a highly relevant model for preclinical research.

Acknowledgements

No acknowledgement found.

References

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