Towards multicenter ß-amyloid PET imaging in mouse models: A triple scanner head-to-head comparison.

AIM: ß-amyloid (Aß) small animal PET facilitates quantification of fibrillar amyloidosis in Alzheimer's disease (AD) mouse models. Thus, the methodology is receiving growing interest as a monitoring tool in preclinical drug trials. In this regard, harmonization of data from different scanners at multiple sites would allow the establishment large collaborative cohorts and may facilitate efficacy comparison of different treatments. Therefore, we objected to determine the level of agreement of Aß-PET quantification by a head-to-head comparison of three different state-of-the-art small animal PET scanners, which could help pave the way for future multicenter studies. METHODS: Within a timeframe of 5 ± 2 weeks, transgenic APPPS1 (n = 9) and wild-type (WT) (n = 8) mice (age range: 13-16 months) were examined three times by Aß-PET ([18F]florbetaben) using a Siemens Inveon DPET, a MedisonanoScan PET/MR, and a MedisonanoScan PET/CT with harmonized reconstruction protocols. Cortex-to-white-matter 30-60 min p.i. standardized uptake value ratios (SUVRCTX/WM) were calculated to compare binding differences, effect sizes (Cohen's d) and z-score values of APPPS1 relative to WT mice. Correlation coefficients (Pearson's r) were calculated for the agreement of individual SUVR between different scanners. Voxel-wise analysis was used to determine the agreement of spatial pathology patterns. For validation of PET imaging against the histological gold standard, individual SUVR values were subject to a correlation analysis with area occupancy of methoxy­X04 staining. RESULTS: All three small animal PET scanners yielded comparable group differences between APPPS1 and WT mice (∆PET=20.4 % ± 2.9 %, ∆PET/MR=18.4 % ± 4.5 %, ∆PET/CT=18.1 % ± 3.3 %). Voxel-wise analysis confirmed a high degree of congruency of the spatial pattern (Dice coefficient (DC)PETvs.PET/MR=83.0 %, DCPETvs.PET/CT=69.3 %, DCPET/MRvs.PET/CT=81.9 %). Differences in the group level variance of the three scanners resulted in divergent z-scores (zPET=11.5 ± 1.6; zPET/MR=5.3 ± 1.3; zPET/CT=3.4 ± 0.6) and effect sizes (dPET=8.5, dPET/MR=4.5, dPET/CT=4.1). However, correlations at the individual mouse level were still strong between scanners (rPETvs.PET/MR=0.96, rPETvs.PET/CT=0.91, rPET/MRvs.PET/CT=0.87; all p ≤ 0.0001). Methoxy-X04 staining exhibited a significant correlation across all three PET machines combined (r = 0.76, p < 0.0001) but also at individual level (PET: r = 0.81, p = 0.026; PET/MR: r = 0.89, p = 0.0074; PET/CT: r = 0.93, p = 0.0028). CONCLUSIONS: Our comparison of standardized small animal Aß-PET acquired by three different scanners substantiates the possibility of moving towards a multicentric approach in preclinical AD research. The alignment of image acquisition and analysis methods achieved good overall comparability between data sets. Nevertheless, differences in variance of sensitivity and specificity of different scanners may limit data interpretation at the individual mouse level and deserves methodological optimization.

Validity and value of metabolic connectivity in mouse models of ß-amyloid and tauopathy.

Among functional imaging methods, metabolic connectivity (MC) is increasingly used for investigation of regional network changes to examine the pathophysiology of neurodegenerative diseases such as Alzheimer's disease (AD) or movement disorders. Hitherto, MC was mostly used in clinical studies, but only a few studies demonstrated the usefulness of MC in the rodent brain. The goal of the current work was to analyze and validate metabolic regional network alterations in three different mouse models of neurodegenerative diseases (ß-amyloid and tau) by use of 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography (FDG-PET) imaging. We compared the results of FDG-µPET MC with conventional VOI-based analysis and behavioral assessment in the Morris water maze (MWM). The impact of awake versus anesthesia conditions on MC read-outs was studied and the robustness of MC data deriving from different scanners was tested. MC proved to be an accurate and robust indicator of functional connectivity loss when sample sizes ≥12 were considered. MC readouts were robust across scanners and in awake/ anesthesia conditions. MC loss was observed throughout all brain regions in tauopathy mice, whereas ß-amyloid indicated MC loss mainly in spatial learning areas and subcortical networks. This study established a methodological basis for the utilization of MC in different ß-amyloid and tau mouse models. MC has the potential to serve as a read-out of pathological changes within neuronal networks in these models.

Distinct molecular profiles of skull bone marrow in health and neurological disorders.

The bone marrow in the skull is important for shaping immune responses in the brain and meninges, but its molecular makeup among bones and relevance in human diseases remain unclear. Here, we show that the mouse skull has the most distinct transcriptomic profile compared with other bones in states of health and injury, characterized by a late-stage neutrophil phenotype. In humans, proteome analysis reveals that the skull marrow is the most distinct, with differentially expressed neutrophil-related pathways and a unique synaptic protein signature. 3D imaging demonstrates the structural and cellular details of human skull-meninges connections (SMCs) compared with veins. Last, using translocator protein positron emission tomography (TSPO-PET) imaging, we show that the skull bone marrow reflects inflammatory brain responses with a disease-specific spatial distribution in patients with various neurological disorders. The unique molecular profile and anatomical and functional connections of the skull show its potential as a site for diagnosing, monitoring, and treating brain diseases.

Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia.

BACKGROUND: Genetic mutations underlying familial Alzheimer's disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain. METHODS: We engineered a novel App knock-in mouse model (AppSAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene. Amyloid-ß pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous AppSAA mice at different ages in brain and/ or biofluids. Wild type littermate mice were used as experimental controls. We used in situ imaging technologies to define the whole-brain distribution of amyloid plaques and compare it to other AD mouse models and human brain pathology. To further explore the microglial response to AD relevant pathology, we isolated microglia with fibrillar Aß content from the brain and performed transcriptomics and metabolomics analyses and in vivo brain imaging to measure energy metabolism and microglial response. Finally, we also characterized the mice in various behavioral assays. RESULTS: Leveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aß content. The AppSAA knock-in mouse model recapitulates key pathological features of AD such as a progressive accumulation of parenchymal amyloid plaques and vascular amyloid deposits, altered astroglial and microglial responses and elevation of CSF markers of neurodegeneration. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged. DISCUSSION: Our findings demonstrate that fibrillar Aß in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology.