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Network Biomarkers of Alzheimer's Disease Risk Derived from Joint Volume and Texture Covariance Patterns in Mouse Models.

Publication ,  Journal Article
Bridgeford, EW; Chung, J; Anderson, RJ; Mahzarnia, A; Stout, JA; Moon, HS; Han, ZY; Vogelstein, JT; Badea, A
Published in: bioRxiv
February 6, 2025

Alzheimer's disease (AD) lacks effective cures and is typically detected after substantial pathological changes have occurred, making intervention challenging. Early detection and understanding of risk factors and their downstream effects are therefore crucial. Animal models provide valuable tools to study these prodromal stages. We investigated various levels of genetic risk for AD using mice expressing the three major human APOE alleles in place of mouse APOE. We leverage these mouse models utilizing high-resolution magnetic resonance diffusion imaging, due to its ability to provide multiple parameters that can be analysed jointly. We examine how APOE genotype interacts with age, sex, diet, and immunity to yield jointly discernable changes in regional brain volume and fractional anisotropy, a sensitive metric for brain water diffusion. Our results demonstrate that genotype strongly influences the caudate putamen, pons, cingulate cortex, and cerebellum, while sex affects the amygdala and piriform cortex bilaterally. Immune status impacts numerous regions, including the parietal association cortices, thalamus, auditory cortex, V1, and bilateral dentate cerebellar nuclei. Risk factor interactions particularly affect the amygdala, thalamus, and pons. APOE2 mice on a regular diet exhibited the fewest temporal changes, suggesting resilience, while APOE3 mice showed minimal effects from a high-fat diet (HFD). HFD amplified aging effects across multiple brain regions. The interaction of AD risk factors, including diet, revealed significant changes in the periaqueductal gray, pons, amygdala, inferior colliculus, M1, and ventral orbital cortex. Future studies should investigate the mechanisms underlying these coordinated changes in volume and texture, potentially by examining network similarities in gene expression and metabolism, and their relationship to structural pathways involved in neurodegenerative disease progression.

Duke Scholars

Published In

bioRxiv

DOI

EISSN

2692-8205

Publication Date

February 6, 2025

Location

United States
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Bridgeford, E. W., Chung, J., Anderson, R. J., Mahzarnia, A., Stout, J. A., Moon, H. S., … Badea, A. (2025). Network Biomarkers of Alzheimer's Disease Risk Derived from Joint Volume and Texture Covariance Patterns in Mouse Models. BioRxiv. https://doi.org/10.1101/2025.02.05.636582
Bridgeford, Eric W., Jaewon Chung, Robert J. Anderson, Ali Mahzarnia, Jacques A. Stout, Hae Sol Moon, Zay Yar Han, Joshua T. Vogelstein, and Alexandra Badea. “Network Biomarkers of Alzheimer's Disease Risk Derived from Joint Volume and Texture Covariance Patterns in Mouse Models.BioRxiv, February 6, 2025. https://doi.org/10.1101/2025.02.05.636582.
Bridgeford EW, Chung J, Anderson RJ, Mahzarnia A, Stout JA, Moon HS, et al. Network Biomarkers of Alzheimer's Disease Risk Derived from Joint Volume and Texture Covariance Patterns in Mouse Models. bioRxiv. 2025 Feb 6;
Bridgeford, Eric W., et al. “Network Biomarkers of Alzheimer's Disease Risk Derived from Joint Volume and Texture Covariance Patterns in Mouse Models.BioRxiv, Feb. 2025. Pubmed, doi:10.1101/2025.02.05.636582.
Bridgeford EW, Chung J, Anderson RJ, Mahzarnia A, Stout JA, Moon HS, Han ZY, Vogelstein JT, Badea A. Network Biomarkers of Alzheimer's Disease Risk Derived from Joint Volume and Texture Covariance Patterns in Mouse Models. bioRxiv. 2025 Feb 6;

Published In

bioRxiv

DOI

EISSN

2692-8205

Publication Date

February 6, 2025

Location

United States