Diffusion‐Weighted MRI Brain Connectivity Assessment of Healthy Aging Trajectories in Marmosets

Abstract Background The common marmoset (Callithrix jacchus) is an important animal model in neuroscience and neurological diseases (e.g., Alzheimer’s disease ‐ AD), as they present primate‐specific evolutionary features such as an expanded frontal cortex. We established a new consortium with funding support from the National Institute on Aging to generate, characterize, and validate MArmosets as Research MOdels of AD (MARMO‐AD). This consortium develops and studies gene‐edited marmoset models carrying genetic risk for AD, comparing them against wild‐type aging marmosets from birth throughout their lifespan, using non‐invasive longitudinal assessments. Here, we aimed to characterize the structural cortical connectivity (white matter fibers) in a population of marmosets across the lifespan to establish healthy aging trajectories against which we will compare our genetically engineered marmoset models of AD. Method We performed high‐resolution (500 µm isotropic) diffusion‐weighted MRI (dMRI) in a cohort of 19 marmosets (13 males, 6 females) aged 8 to 89 months using a dedicated 9.4T 30cm bore MRI scanner (Bruker BioSpin Corp, Billerica). The animals were anesthetized under isoflurane and maintained at normal physiological conditions. The brain images were aligned and registered to the Marmoset Brain Mapping (MBM) V2 template. The brain was segmented using the MBM white matter atlas, and voxel‐based morphology (VBM) was used to quantify regional white matter volume in the left and right hemispheres. Furthermore, we used DSI STUDIO to perform the whole‐brain tractogram, calculate network‐based statistics (NBS), and correlate them with age. Result We measured decreases in the NBS properties of Assortativity, Small Worldliness, and Hierarchy with age but an increase in Efficiency, showing the maturation processes of white matter across development. We are actively working on increasing our sample size to identify the entire marmoset age trajectory and its impact on white matter connectivity. Conclusion Our work is the first to thoroughly describe the healthy aging trajectories of the marmoset brain, a valuable model for age‐related neuropathologies (e.g., AD). This research will establish normative baselines for changes in marmoset brain connectivity with aging that will be used to evaluate our genetically engineered marmoset models of AD, which is the goal of the MARMO‐AD consortium.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.090909
Primary Topic
Advanced Neuroimaging Techniques and Applications
Type
article
Field-Weighted Citation Impact
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article

Diffusion‐Weighted MRI Brain Connectivity Assessment of Healthy Aging Trajectories in Marmosets

Diego Szczupak, Gregory W. Carter, Afonso C. Silva, Daniel Papoti et al.
Alzheimer s & Dementia
Advanced Neuroimaging Techniques and Applications
article

Diffusion‐Weighted MRI Brain Connectivity Assessment of Healthy Aging Trajectories in Marmosets

Diego Szczupak, Gregory W. Carter, Afonso C. Silva, Daniel Papoti, Stacey J. Sukoff Rizzo, T. Kevin Hitchens, Fang‐Cheng Yeh, Vinícius Farias Campos, Lauren R Dubberley, Bei Zhang, David J. Schaeffer, Lauren K Hayrynen Schaeffer, Rebecca Bhik‐Ghanie
article en

Abstract

Abstract Background The common marmoset (Callithrix jacchus) is an important animal model in neuroscience and neurological diseases (e.g., Alzheimer’s disease ‐ AD), as they present primate‐specific evolutionary features such as an expanded frontal cortex. We established a new consortium with funding support from the National Institute on Aging to generate, characterize, and validate MArmosets as Research MOdels of AD (MARMO‐AD). This consortium develops and studies gene‐edited marmoset models carrying genetic risk for AD, comparing them against wild‐type aging marmosets from birth throughout their lifespan, using non‐invasive longitudinal assessments. Here, we aimed to characterize the structural cortical connectivity (white matter fibers) in a population of marmosets across the lifespan to establish healthy aging trajectories against which we will compare our genetically engineered marmoset models of AD. Method We performed high‐resolution (500 µm isotropic) diffusion‐weighted MRI (dMRI) in a cohort of 19 marmosets (13 males, 6 females) aged 8 to 89 months using a dedicated 9.4T 30cm bore MRI scanner (Bruker BioSpin Corp, Billerica). The animals were anesthetized under isoflurane and maintained at normal physiological conditions. The brain images were aligned and registered to the Marmoset Brain Mapping (MBM) V2 template. The brain was segmented using the MBM white matter atlas, and voxel‐based morphology (VBM) was used to quantify regional white matter volume in the left and right hemispheres. Furthermore, we used DSI STUDIO to perform the whole‐brain tractogram, calculate network‐based statistics (NBS), and correlate them with age. Result We measured decreases in the NBS properties of Assortativity, Small Worldliness, and Hierarchy with age but an increase in Efficiency, showing the maturation processes of white matter across development. We are actively working on increasing our sample size to identify the entire marmoset age trajectory and its impact on white matter connectivity. Conclusion Our work is the first to thoroughly describe the healthy aging trajectories of the marmoset brain, a valuable model for age‐related neuropathologies (e.g., AD). This research will establish normative baselines for changes in marmoset brain connectivity with aging that will be used to evaluate our genetically engineered marmoset models of AD, which is the goal of the MARMO‐AD consortium.

Alzheimer s & DementiaVol. 20(S2)
University of Pittsburgh (US), Universidade de São Paulo (BR), Jackson Laboratory (US), Universidade Federal do ABC (BR)
Openalex Percentile: Top 58%
Advanced Neuroimaging Techniques and Applications
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