期刊
PLOS ONE
卷 16, 期 3, 页码 -出版社
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0247592
关键词
-
资金
- Ministry of Education
- National Research Foundation of Korea [NRF-2019S1A5A2A03052192]
- Brain Research Program through the National Research Foundation of Korea from the Ministry of Science, ICT & Future Planning [NRF-2015M3C7A1028252]
- Korea Medical Device Development Fund grant - Korean government (Ministry of Science and ICT) [202013B10]
- Korea Medical Device Development Fund grant - Korean government (Ministry of Trade, Industry and Energy) [202013B10]
- Korea Medical Device Development Fund grant - Korean government (Ministry of Health & Welfare, Republic of Korea) [202013B10]
- Korea Medical Device Development Fund grant - Korean government (Ministry of Food and Drug Safety) [202013B10]
- National Research Foundation of Korea [2019S1A5A2A03052192] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)
This study introduces a statistical method called IG-GSCA for investigating the associations between genes, brain, and behavior/cognition. The research considers biological characteristics and methodological complexities, and examines the effects of multiple genes interacting with environmental variables on brain region thickness variations and their impact on depression severity. The results suggest that specific genetic variations and gene-environment interactions have significant effects on brain regions that influence depression severity, which is consistent with previous studies.
With advances in neuroimaging and genetics, imaging genetics is a naturally emerging field that combines genetic and neuroimaging data with behavioral or cognitive outcomes to examine genetic influence on altered brain functions associated with behavioral or cognitive variation. We propose a statistical approach, termed imaging genetics generalized structured component analysis (IG-GSCA), which allows researchers to investigate such gene-brain-behavior/cognitive associations, taking into account well-documented biological characteristics (e.g., genetic pathways, gene-environment interactions, etc.) and methodological complexities (e.g., multicollinearity) in imaging genetic studies. We begin by describing the conceptual and technical underpinnings of IG-GSCA. We then apply the approach for investigating how nine depression-related genes and their interactions with an environmental variable (experience of potentially traumatic events) influence the thickness variations of 53 brain regions, which in turn affect depression severity in a sample of Korean participants. Our analysis shows that a dopamine receptor gene and an interaction between a serotonin transporter gene and the environment variable have statistically significant effects on a few brain regions' variations that have statistically significant negative impacts on depression severity. These relationships are largely supported by previous studies. We also conduct a simulation study to safeguard whether IG-GSCA can recover parameters as expected in a similar situation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据