Browsing by Subject "Network segregation"

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    Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts
    (Frontiers Media, 2022-02-07) Cong, Shan; Yao, Xiaohui; Xie, Linhui; Yan, Jingwen; Shen, Li; Alzheimer’s Disease Neuroimaging Initiative; Biomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineerin
    Background: Human brain structural connectivity is an important imaging quantitative trait for brain development and aging. Mapping the network connectivity to the phenotypic variation provides fundamental insights in understanding the relationship between detailed brain topological architecture, function, and dysfunction. However, the underlying neurobiological mechanism from gene to brain connectome, and to phenotypic outcomes, and whether this mechanism changes over time, remain unclear. Methods: This study analyzes diffusion-weighted imaging data from two age-specific neuroimaging cohorts, extracts structural connectome topological network measures, performs genome-wide association studies of the measures, and examines the causality of genetic influences on phenotypic outcomes mediated via connectivity measures. Results: Our empirical study has yielded several significant findings: 1) It identified genetic makeup underlying structural connectivity changes in the human brain connectome for both age groups. Specifically, it revealed a novel association between the minor allele (G) of rs7937515 and the decreased network segregation measures of the left middle temporal gyrus across young and elderly adults, indicating a consistent genetic effect on brain connectivity across the lifespan. 2) It revealed rs7937515 as a genetic marker for body mass index in young adults but not in elderly adults. 3) It discovered brain network segregation alterations as a potential neuroimaging biomarker for obesity. 4) It demonstrated the hemispheric asymmetry of structural network organization in genetic association analyses and outcome-relevant studies. Discussion: These imaging genetic findings underlying brain connectome warrant further investigation for exploring their potential influences on brain-related complex diseases, given the significant involvement of altered connectivity in neurological, psychiatric and physical disorders.
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    Sex-specific topological structure associated with dementia via latent space estimation
    (Wiley, 2024) Wang, Selena; Wang, Yiting; Xu, Frederick H.; Tian, Xinyuan; Fredericks, Carolyn A.; Shen, Li; Zhao, Yize; Alzheimer’s Disease Neuroimaging Initiative; Biostatistics and Health Data Science, Richard M. Fairbanks School of Public Health
    Introduction: We investigate sex-specific topological structures associated with typical Alzheimer's disease (AD) dementia using a novel state-of-the-art latent space estimation technique. Methods: This study applies a probabilistic approach for latent space estimation that extends current multiplex network modeling approaches and captures the higher-order dependence in functional connectomes by preserving transitivity and modularity structures. Results: We find sex differences in network topology with females showing more default mode network (DMN)-centered hyperactivity and males showing more limbic system (LS)-centered hyperactivity, while both show DMN-centered hypoactivity. We find that centrality plays an important role in dementia-related dysfunction with stronger association between connectivity changes and regional centrality in females than in males. Discussion: The study contributes to the current literature by providing a more comprehensive picture of dementia-related neurodegeneration linking centrality, network segregation, and DMN-centered changes in functional connectomes, and how these components of neurodegeneration differ between the sexes. Highlights: We find evidence supporting the active role network topology plays in neurodegeneration with an imbalance between the excitatory and inhibitory mechanisms that can lead to whole-brain destabilization in dementia patients. We find sex-based differences in network topology with females showing more default mode network (DMN)-centered hyperactivity, males showing more limbic system (LS)-centered hyperactivity, while both show DMN-centered hypoactivity. We find that brain region centrality plays an important role in dementia-related dysfunction with a stronger association between connectivity changes and regional centrality in females than in males. Females, compared to males, tend to exhibit stronger dementia-related changes in regions that are the central actors of the brain networks. Taken together, this research uniquely contributes to the current literature by providing a more comprehensive picture of dementia-related neurodegeneration linking centrality, network segregation, and DMN-centered changes in functional connectomes, and how these components of neurodegeneration differ between the sexes.