Dataset Information

Heterogeneous Disease Progression in a Mouse Model of Vascular Cognitive Impairment.

ABSTRACT: Recently, an asymmetric vascular compromise approach that replicates many aspects of human vascular cognitive impairment (VCI) has been reported. The present study aimed to first investigate on the reproducibility in the disease progression of this newly reported VCI model using wild-type C57BL6/J mice. The second aim was to assess how this approach will affect the disease progression of transgenic Alzheimer's disease (AD) 5XFAD mice subjected to VCI. C57BL6/J and 5XFAD mice were subjected to VCI by placing an ameroid constrictor on the right CCA and a microcoil on the left CCA. Infarcts and hippocampal neuronal loss did not appear predominantly in the right (ameroid side) as expected but randomly in both hemispheres. The mortality rate of C57BL6/J mice was unexpectedly high. Inducing VCI reduced amyloid burden in the hippocampi of 5XFAD mice. Since VCI is known to be complex and complicated, the heterogeneous disease progression observed from this current study shares close resemblance to the clinical manifestation of VCI. This heterogeneity, however, makes it challenging to test novel treatment options using this model. Further study is warranted to tackle the heterogeneous nature of VCI.

SUBMITTER: Lee NK

PROVIDER: S-EPMC7215687 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Heterogeneous Disease Progression in a Mouse Model of Vascular Cognitive Impairment.

Lee Na Kyung NK Kim Hunnyun H Yang Jehoon J Kim Jeyun J Son Jeong Pyo JP Jang Hyemin H Na Duk L DL

International journal of molecular sciences 20200417 8

Recently, an asymmetric vascular compromise approach that replicates many aspects of human vascular cognitive impairment (VCI) has been reported. The present study aimed to first investigate on the reproducibility in the disease progression of this newly reported VCI model using wild-type C57BL6/J mice. The second aim was to assess how this approach will affect the disease progression of transgenic Alzheimer's disease (AD) 5XFAD mice subjected to VCI. C57BL6/J and 5XFAD mice were subjected to VC ...[more]

PMID: 32316637

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Project description:Predicting progression of mild cognitive impairment (MCI) to Alzheimer's disease (AD) is clinically important. In this study, we propose a dual-model radiomic analysis with multivariate Cox proportional hazards regression models to investigate promising risk factors associated with MCI conversion to AD. T1 structural magnetic resonance imaging (MRI) and 18F-Fluorodeoxyglucose (FDG) positron emission tomography (PET) data, from the AD Neuroimaging Initiative database, were collected from 131 patients with MCI who converted to AD within 3 years and 132 patients with MCI without conversion within 3 years. These subjects were randomly partition into 70% training dataset and 30% test dataset with multiple times. We fused MRI and PET images by wavelet method. In a subset of subjects, a group comparison was performed using a two-sample t-test to determine regions of interest (ROIs) associated with MCI conversion. 172 radiomic features from ROIs for each individual were established using a published radiomics tool. Finally, L1-penalized Cox model was constructed and Harrell's C index (C-index) was used to evaluate prediction accuracy of the model. To evaluate the efficacy of our proposed method, we used a same analysis framework to evaluate MRI and PET data separately. We constructed prognostic Cox models with: clinical data, MRI images, PET images, fused MRI/PET images, and clinical variables and fused MRI/PET images in combination. The experimental results showed that captured ROIs significantly associated with conversion to AD, such as gray matter atrophy in the bilateral hippocampus and hypometabolism in the temporoparietal cortex. Imaging model (MRI/PET/fused) provided significant enhancement in prediction of conversion compared to clinical models, especially the fused-modality Cox model. Moreover, the combination of fused-modality imaging and clinical variables resulted in the greatest accuracy of prediction. The average C-index for the clinical/MRI/PET/fused/combined model in the test dataset was 0.69, 0.73, 0.73 and 0.75, and 0.78, respectively. These results suggested that a combination of radiomic analysis and Cox model analyses could be used successfully in survival analysis and may be powerful tools for personalized precision medicine patients with potential to undergo conversion from MCI to AD.

Dataset Information

Heterogeneous Disease Progression in a Mouse Model of Vascular Cognitive Impairment.

Publications

Heterogeneous Disease Progression in a Mouse Model of Vascular Cognitive Impairment.

Similar Datasets

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