A decentralized macro and micro gene-by-environment interaction analysis of substance use behavior and its brain biomarkers

物质使用行为及其大脑生物标志物的分散宏观和微观基因与环境相互作用分析

• 批准号: 10645089
• 负责人: VINCE D CALHOUN
• 金额: $ 54.27万
• 依托单位: GEORGIA STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-15 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10645089
• 关键词: Address; Adolescence; Adolescent; Age; Anxiety; Behavior; Behavioral; Biological Markers; Brain; Brain imaging; Brain scan; China; Climate; Communities; Complex; Computer software; Consumption; Country; Data; Data Analyses; Data Protection; Decentralization; Development; Disease; Dropout; Economic Burden; Environment; Environmental Risk Factor; Epidemiology; Ethnic Population; Europe; Family Study; Genes; Genetic; Genomics; Genotype; Heritability; Household; Image; Income; India; Individual; Informatics; International; Intervention; Learning; Legal; Magnetic Resonance Imaging; Measures; Mental Depression; Modeling; Movement; Neurobiology; Neurons; Neurosciences; Outcome; Participant; Physiological; Population; Population Density; Privacy; Quality Control; Race; Regulation; Risk; Scanning; Site; Smoking; Smoking Behavior; Source Code; Structure; System; Time; Twin Studies; Update; Urbanization; Visualization; Work; adolescent substance use; cloud based; cognitive development; cohort; computerized tools; contextual factors; cost; data access; data exchange; drinking; drinking behavior; early life stress; epidemiologic data; gene environment interaction; genetic epidemiology; genomic data; human subject protection; imaging genetics; insight; neural; neuroimaging; open data; open source; peer; prevent; psychiatric symptom; rural area; sex; statistics; substance use; tool; tool development; urban area; virtual

Project Summary/Abstract Substance use behavior (smoking/drinking) is well known to be the result of a complex interplay between genetics and environmental components. However macro- and micro-environmental effects on smoking and drinking behavior are still poorly understood and there is little work evaluating the relationship of such factors to neurobiological changes measured via brain imaging. The data are available though. There is a great amount of internationally collected imaging and genomics data, however much of this data is not being analyzed due to privacy issues or other factors which prevent sharing of the raw data. To address this barrier, we propose to leverage and extend a software platform which enables decentralized analysis of data (e.g. sharing without sharing). We will use this platform to perform an analysis which pools together data from the 10,000 participant longitudinal US-based adolescent brain cognitive development (ABCD) study with an international cohort of more than 20,000 participants from Europe, China, and India called the global imaging genetics of adolescents (GIGA). Our focus will be on assessing macro- and micro-environmental and heritability factors associated with sub- stance use behavior as well as their neuronal biomarkers in the context of factors such as cultural acceptance, urbanization, annual household income, and climate. Results will provide new insights into the factors contrib- uting to substance use behavior. We also propose to develop a persistent decentralized analysis nodes for the GIGA sites using our Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation (COINSTAC) to allow for re-analyses of these large cohorts as well as pooling with one’s local data without requiring collocation of the data at the same site. 3

项目概要/摘要 众所周知，物质使用行为（吸烟/饮酒）是各种因素之间复杂相互作用的结果。 然而，宏观和微观环境对吸烟和吸烟的影响。 人们对饮酒行为的了解仍然知之甚少，而且很少有工作评估这些因素与饮酒行为之间的关系。 通过大脑成像测量的神经生物学变化有大量数据可供使用。 国际上收集的成像和基因组学数据，但由于以下原因，其中大部分数据并未得到分析 隐私问题或其他阻碍原始数据共享的因素，我们建议解决这一障碍。 利用和扩展软件平台，实现数据的去中心化分析（例如，无需共享数据） 我们将使用该平台进行分析，汇集 10,000 名参与者的数据。 美国纵向青少年大脑认知发展（ABCD）研究，涉及更多国际队列 来自欧洲、中国和印度的 20,000 多名参与者被称为全球青少年影像遗传学 (GIGA)。 我们的重点将是评估与亚健康相关的宏观和微观环境以及遗传因素。 在文化接受等因素的背景下，立场使用行为及其神经生物标志物， 城市化、家庭年收入和气候的结果将为影响因素提供新的见解。 我们还建议为物质使用行为开发持久的去中心化分析节点。 GIGA 网站使用我们的协作信息学和神经影像套件工具包进行匿名计算 （COINSTAC）允许重新分析这些大型队列，并与本地数据进行汇总，而无需 要求在同一地点并置数据。 3

项目成果

Associations of DNA Methylation With Behavioral Problems, Gray Matter Volumes, and Negative Life Events Across Adolescence: Evidence From the Longitudinal IMAGEN Study.

DNA 甲基化与青春期行为问题、灰质体积和消极生活事件的关联：来自纵向 IMAGEN 研究的证据。

• 发表时间: 2023-02-15
• 影响因子: 10.6
• 作者: Sun, Yan;Jia, Tianye;Barker, Edward D;Chen, Di;Zhang, Zuo;Xu, Jiayuan;Chang, Suhua;Zhou, Guangdong;Liu, Yun;Tay, Nicole;Luo, Qiang;Chang, Xiao;Banaschewski, Tobias;Bokde, Arun L W;Flor, Herta;Grigis, Antoine;Garavan, Hugh;Heinz, Andreas
• 通讯作者: Heinz, Andreas

Multimodal Brain Age Prediction with Feature Selection and Comparison.

通过特征选择和比较进行多模式脑年龄预测。

• 发表时间: 2021-11
• 作者: Ray, Bhaskar;Duan, Kuaikuai;Chen, Jiayu;Fu, Zening;Suresh, Pranav;Johnson, Sarah;Calhoun, Vince D;Liu, Jingyu
• 通讯作者: Liu, Jingyu

Neurocognitive Analysis of Low-level Arsenic Exposure and Executive Function Mediated by Brain Anomalies Among Children, Adolescents, and Young Adults in India.

印度儿童、青少年和年轻人脑异常介导的低水平砷暴露和执行功能的神经认知分析。

• 发表时间: 2023-05-01
• 影响因子: 13.8
• 作者: Vaidya, Nilakshi;Holla, Bharath;Heron, Jon;Sharma, Eesha;Zhang, Yuning;Fernandes, Gwen;Iyengar, Udita;Spiers, Ale;Yadav, Anupa;Das, Surajit;Roy, Sanjit;Ahuja, Chirag K;Barker, Gareth J;Basu, Debasish;Bharath, Rose Dawn;Hickman, Matthew;Ja
• 通讯作者: Ja

Replication and Refinement of Brain Age Model for adolescent development.

青少年发展脑年龄模型的复制和完善。

• 发表时间: 2023-08-18
• 作者: Ray, Bhaskar;Chen, Jiayu;Fu, Zening;Suresh, Pranav;Thapaliya, Bishal;Farahdel, Britny;Calhoun, Vince D;Liu, Jingyu
• 通讯作者: Liu, Jingyu

Brain age prediction: A comparison between machine learning models using region- and voxel-based morphometric data.

脑年龄预测：使用基于区域和基于体素的形态测量数据的机器学习模型之间的比较。

• 发表时间: 2021-06-01
• 影响因子: 4.8
• 作者: Baecker, Lea;Dafflon, Jessica;da Costa, Pedro F;Garcia;Vieira, Sandra;Scarpazza, Cristina;Calhoun, Vince D;Sato, João R;Mechelli, Andrea;Pinaya, Walter H L
• 通讯作者: Pinaya, Walter H L