Cargando…
Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts
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, fu...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8884108/ https://www.ncbi.nlm.nih.gov/pubmed/35237294 http://dx.doi.org/10.3389/fgene.2021.782953 |
_version_ | 1784660090585874432 |
---|---|
author | Cong, Shan Yao, Xiaohui Xie, Linhui Yan, Jingwen Shen, Li |
author_facet | Cong, Shan Yao, Xiaohui Xie, Linhui Yan, Jingwen Shen, Li |
author_sort | Cong, Shan |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8884108 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88841082022-03-01 Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts Cong, Shan Yao, Xiaohui Xie, Linhui Yan, Jingwen Shen, Li Front Genet Genetics 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. Frontiers Media S.A. 2022-02-07 /pmc/articles/PMC8884108/ /pubmed/35237294 http://dx.doi.org/10.3389/fgene.2021.782953 Text en Copyright © 2022 Cong, Yao, Xie, Yan and Shen and the Alzheimer’s Disease Neuroimaging Initiative. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Cong, Shan Yao, Xiaohui Xie, Linhui Yan, Jingwen Shen, Li Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts |
title | Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts |
title_full | Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts |
title_fullStr | Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts |
title_full_unstemmed | Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts |
title_short | Genetic Influence Underlying Brain Connectivity Phenotype: A Study on Two Age-Specific Cohorts |
title_sort | genetic influence underlying brain connectivity phenotype: a study on two age-specific cohorts |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8884108/ https://www.ncbi.nlm.nih.gov/pubmed/35237294 http://dx.doi.org/10.3389/fgene.2021.782953 |
work_keys_str_mv | AT congshan geneticinfluenceunderlyingbrainconnectivityphenotypeastudyontwoagespecificcohorts AT yaoxiaohui geneticinfluenceunderlyingbrainconnectivityphenotypeastudyontwoagespecificcohorts AT xielinhui geneticinfluenceunderlyingbrainconnectivityphenotypeastudyontwoagespecificcohorts AT yanjingwen geneticinfluenceunderlyingbrainconnectivityphenotypeastudyontwoagespecificcohorts AT shenli geneticinfluenceunderlyingbrainconnectivityphenotypeastudyontwoagespecificcohorts AT geneticinfluenceunderlyingbrainconnectivityphenotypeastudyontwoagespecificcohorts |