NCANDA: Data Analysis Resource

NCANDA：数据分析资源

• 批准号: 10471131
• 负责人: Adolf Pfefferbaum
• 金额: $ 112.01万
• 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/10471131
• 关键词: 21 year old; Abstinence; 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; Magnetic Resonance Imaging; Measures; Mediating; Mission; Modeling; Monitor; Neuropsychology; Outcome; Outcome Measure; Parietal; 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; base; binge drinking; career; cognitive control; cognitive performance; cohort; cue reactivity; data sharing; data standards; deep learning; design; drinking; drinking onset; early onset; emerging adult; emerging adulthood; experience; externalizing behavior; follow-up; hazardous drinking; informatics infrastructure; information processing; male; medical specialties; mobile application; multimodal neuroimaging; neurodevelopment; neuroimaging; neuropsychiatry; novel; novel strategies; pandemic disease; predictive marker; recruit; relating to nervous system; 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.

项目摘要 众所周知，在青春期开始的过度饮酒会扰乱典型的神经发育 模式，增加发展酒精使用障碍（AUD）的风险，并加速退化过程， 成年作为对RFA-AA-21-009的响应，数据分析资源（DAR）建议支持下一个5 多年的数据收集和分析，在不同的社区样本的男性和女性参与者， 在12至21岁之间的3个年龄段招募，大多数是无饮酒者， 5个研究中心的过去8年（N=831; 93%留存率）。监测涉及每年获得的 多模态神经成像（MRI，DTI，静息状态fMRI，任务fMRI）和认知，临床，行为， 生物数据，亲自或通过计算机和我们的移动的应用程序远程收集。这些措施现在将 辅以新的先进神经成像和睡眠和身体活动跟踪。该队列 序贯设计使NCANDA-A能够量化短暂或持续的酒精相关紊乱 在特定的青少年和早期成人神经系统的生长轨迹和功能伴随。 NCANDA-A提出了四个联盟范围的具体目标和两个专业项目目标。目标1：NCANDA-A 将调查青春期和成年期过度饮酒对 认知表现、大脑结构和功能的后续发展轨迹，以及 精神病理学目标2分析将确定神经发育模式，描述在何种程度上， 酒精对大脑结构和功能的影响在酗酒后停止饮酒期间消退或持续。目标3 将部署数据驱动的分析，以确定青少年的生物，环境和行为因素（例如， 饮酒开始的年龄），预测成年早期过度饮酒。在目标4中，NCANDA-A将 量化COVID大流行对生活压力以及社会、情感和经济福祉的影响， 与酒精使用模式的关系对于每一个目标，发展中的性别差异，酒精使用模式 和历史，酒精使用对大脑的影响，以及性别差异的心理社会因素将被测试。 DAR的目标是支持基于五个目标的假设检验。目标D1将确保程序 用于神经影像学、神经心理学和临床评估数据的收集和质量控制， 规范在Aim D2中，DAR将推进现有的信息学基础设施，以整合数据 在所有网站上收集。目的D3可增强神经元的宏观、微观和功能影像 处理和分析。在Aim D4中，DAR将创建机器（深度）学习框架， 成年早期饮酒的预测指标Aim D5将维护数据共享和分发系统， 财团PI和广大科学公众。 随着在更新期间收集到成年早期的纵向数据，NCANDA-A将提供新的 向公众提供关于青少年饮酒对成年人功能的持久和短暂影响的信息。