Multivariate patterns between brain network properties, polygenic scores, phenotypes, and environment in preadolescents

Author:

Seo JungwooORCID,Lee EunjiORCID,Kim Bo-gyeom,Kim GakyungORCID,Joo Yoonjung YoonieORCID,Cha JiookORCID

Abstract

AbstractThe brain network is an infrastructure for cognitive and behavioral processes. Genetic and environmental factors influence the development of the brain network. However, little is known about how specific genetic traits and children’s brain network properties are related. Furthermore, insight into the holistic relationship of brain network properties with genes, environment, and phenotypic outcomes in children is still limited. To fill these knowledge gaps, we investigated the multivariate associations between the brain network properties and three domains using a large youth sample (the ABCD study, N=9,393, 9-10 years old): (i) genetic predisposition of various traits, (ii) phenotypic outcomes, and (iii) environmental factors. We constructed structural brain networks using probabilistic tractography and estimated nodal and global network measures such as degree and network efficiency. We then conducted sparse canonical correlation analysis with brain network measures and polygenic scores of 30 complex traits (e.g., IQ), phenotypic traits (e.g., cognitive ability), and environmental variables. We found multivariate associations of brain network properties with (i) genetic risk for psychiatric disorders, (ii) genetic influence on cognitive ability, and (iii) the phenotype of cognitive ability-psychopathology in preadolescents. Our subsequent mediation analysis using the latent variables from the canonical correlation analysis showed that the influence of genetic factors for cognitive ability on the cognitive outcomes was partially mediated by the brain network properties. Taken together, this study shows the key role of the development of the brain structural network in children in cognitive development with its tight, likely causal, relationship with genetic factors. These findings may shed light on future studies of the longitudinal deviations of those gene-environment-brain network relationships in normal and disease conditions.

Publisher

Cold Spring Harbor Laboratory

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3