NCANDA: Data Analysis Resource

NCANDA：数据分析资源

• 批准号: 10678681
• 负责人: Adolf Pfefferbaum
• 金额: $ 110.3万
• 依托单位: STANFORD UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-15 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10678681
• 关键词: 21 year old; Abstinence; Acceleration; Adolescence; Adolescent; Adult; Adverse effects; Affective; Age; Alcohol abuse; Alcohol consumption; Alcohols; Behavioral; Biological; Brain; COVID-19 pandemic; COVID-19 pandemic effects; Clinical; Clinical assessments; Cognition; Cognitive; Collection; Communities; Complement; Computers; Data; Data Analyses; Data Collection; Development; Distress; Dose; Economics; Emotional; Emotions; Ensure; Event; Family; Female; Frequencies; Functional Magnetic Resonance Imaging; Goals; Growth; Health; Heavy Drinking; Home; Independent Living; Individual; Life; Life Stress; Link; Machine Learning; Magnetic Resonance Imaging; Measures; Mediating; Mission; Modeling; Monitor; Neuropsychology; Outcome; Outcome Measure; Participant; Pattern; Personal Satisfaction; Persons; Physical activity; Positioning Attribute; Procedures; Process; Protocols documentation; Psychopathology; Psychosocial Factor; Quality Control; Recording of previous events; Recovery; Resources; Rest; Risk; Sampling; Schools; Sex Differences; Sex Differentiation; Site; Sleep; Standardization; Stress; Structure; Symptoms; System; Technology; Testing; Work; Youth; adolescent binge drinking; alcohol cue; alcohol effect; alcohol expectancy; alcohol use disorder; alcohol use initiation; binge drinking; career; cognitive control; cognitive performance; cohort; cue reactivity; data integration; data sharing; data standards; design; drinking; drinking onset; early onset; emerging adult; emerging adulthood; experience; externalizing behavior; follow-up; hazardous drinking; informatics infrastructure; information processing; machine learning framework; male; medical specialties; mobile application; multimodal neuroimaging; neural; neurodevelopment; neuroimaging; neuropsychiatry; novel; novel strategies; pandemic disease; post-pandemic; pre-pandemic; predictive marker; recruit; response; retention rate; social; success; underage drinking; young man; young woman

PROJECT SUMMARY Excessive alcohol drinking Initiated during adolescence is known to disturb typical neurodevelopmental patterns, increase the risk of developing alcohol use disorder (AUD), and accelerate involutional processes in adulthood. In response to RFA-AA-21-009, the Data Analysis Resource (DAR) proposes to support the next 5 years' data collection and analysis across a diverse community sample of male and female participants that were recruited in 3 age bands between 12 and 21 years old, were mostly no-to-low drinkers, and tracked over the last 8 years across 5 sites (N=831; 93% retention rate). Monitoring has involved annually-acquired multimodal neuroimaging (MRI, DTI, resting state fMRI, task fMRI) and cognitive, clinical, behavioral, and biological data, collected in person or remotely by computer and our mobile app. These measures will now be complemented with new advanced neuroimaging and sleep and physical activity tracking. This cohort sequential design uniquely positions NCANDA-A to quantify transient or enduring alcohol-related disturbances in specific adolescent and early adult neural system growth trajectories and functional concomitants. NCANDA-A proposes four consortium-wide specific aims and two specialty project aims. In Aim 1, NCANDA-A will investigate the impact of excessive alcohol drinking during adolescence and emerging adulthood on subsequent developmental trajectories of cognitive performance, brain structure and function, and psychopathology. Aim 2 analyses will identify neurodevelopment patterns describing the extent to which alcohol’s effects on brain structure and function resolve or persist during desistance after binge drinking. Aim 3 will deploy data-driven analysis to identify adolescent biological, environmental, and behavioral factors (e.g., age of drinking onset) that forecast excessive drinking during early adulthood. In Aim 4, NCANDA-A will quantify the impact of the COVID pandemic on life stress and social, emotional, and economic wellbeing and their relations with alcohol use patterns. For each aim, sex differences in development, alcohol use patterns and history, impact of alcohol use on the brain, and sex-differentiating psychosocial factors will be tested. The goal of the DAR is to support hypothesis testing based on five aims. Aim D1 will ensure that procedures for collection and quality control of neuroimaging, neuropsychological, and clinical assessment data are standardized. In Aim D2, the DAR will advance the existing informatics infrastructure for integrating data collected across all sites. Aim D3 will enhance macrostructural, microstructural, and functional neuroimage processing and analysis. In Aim D4, the DAR will create machine (deep) learning frameworks identifying predictive markers of early adulthood drinking. Aim D5 will maintain data sharing and distribution systems for consortium PIs and the scientific public at large. With the longitudinal data collected into early adulthood during this renewal, NCANDA-A will provide novel information to the public on the enduring and transient effects of adolescent drinking on adult functioning.

项目概要 众所周知，青春期期间开始的过量饮酒会扰乱典型的神经发育 模式，增加患酒精使用障碍（AUD）的风险，并加速退化过程 为了回应 RFA-AA-21-009，数据分析资源 (DAR) 建议支持接下来的 5 个阶段。 多年来对男性和女性参与者的不同社区样本进行的数据收集和分析 被招募者分为 12 岁至 21 岁之间的 3 个年龄段，大部分是从不饮酒到低度饮酒者，并进行了超过 过去 8 年跨 5 个站点的监测（N=831；93% 的保留率）涉及每年获得的数据。 多模态神经影像（MRI、DTI、静息态 fMRI、任务 fMRI）以及认知、临床、行为和 亲自或通过计算机和我们的移动应用程序远程收集的生物数据现在将是。 该队列补充了新的先进神经影像学以及睡眠和身体活动跟踪。 序贯设计独特地定位 NCANDA-A 来量化短暂或持久的酒精相关干扰 在特定的青少年和早期成人神经系统生长轨迹和功能伴随物中。 NCANDA-A 在目标 1 中提出了四个联盟范围内的具体目标和两个专业项目目标。 将调查青春期和成年初期过度饮酒对健康的影响 随后的认知表现、大脑结构和功能的发展轨迹，以及 目标 2 分析将识别神经发育模式，描述其程度。 酒精对大脑结构和功能的影响在目标 3 戒酒后消失或持续。 将部署数据驱动的分析来识别青少年的生物、环境和行为因素（例如， 在目标 4 中，NCANDA-A 将预测成年早期的过度饮酒。 量化新冠疫情大流行对生活压力以及社会、情感和经济福祉的影响， 它们与饮酒模式的关系 对于每个目标、发展中的性别差异、饮酒模式。 病史、饮酒对大脑的影响以及性别差异心理社会因素将得到测试。 DAR 的目标是支持基于五个目标的假设检验，以确保程序得以实现。 用于神经影像、神经心理学和临床评估数据的收集和质量控制 在目标 D2 中，DAR 将推进现有的信息学基础设施以集成数据。 Aim D3 将增强宏观结构、微观结构和功能神经图像。 在 Aim D4 中，DAR 将创建机器（深度）学习框架来识别。 Aim D5 将维护成年早期饮酒的预测标记。 PI 联盟和广大科学公众。 通过在更新期间收集到成年早期的纵向数据，NCANDA-A 将提供新颖的 向公众提供有关青少年饮酒对成人功能的持久和短暂影响的信息。