Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts

dc.contributor.authorCong, Shan
dc.contributor.authorYao, Xiaohui
dc.contributor.authorXie, Linhui
dc.contributor.authorYan, Jingwen
dc.contributor.authorShen, Li
dc.contributor.authorAlzheimer’s Disease Neuroimaging Initiative
dc.contributor.departmentBiomedical Engineering and Informatics, Luddy School of Informatics, Computing, and Engineerin
dc.date.accessioned2024-05-01T11:06:55Z
dc.date.available2024-05-01T11:06:55Z
dc.date.issued2022-02-07
dc.description.abstractBackground: 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.
dc.eprint.versionFinal published version
dc.identifier.citationCong S, Yao X, Xie L, Yan J, Shen L; and the Alzheimer’s Disease Neuroimaging Initiative. Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts. Front Genet. 2022;12:782953. Published 2022 Feb 7. doi:10.3389/fgene.2021.782953
dc.identifier.urihttps://hdl.handle.net/1805/40394
dc.language.isoen_US
dc.publisherFrontiers Media
dc.relation.isversionof10.3389/fgene.2021.782953
dc.relation.journalFrontiers in Genetics
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourcePMC
dc.subjectCausal inference
dc.subjectBody mass index
dc.subjectGenome-wide association study
dc.subjectHuman connectomics
dc.subjectNetwork segregation
dc.titleGenetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts
dc.typeArticle
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