Brain Function and Neurogenomic influences on AUD risk and resilience.

脑功能和神经基因组对 AUD 风险和恢复力的影响。

• 批准号: 10298736
• 负责人: Chella Kamarajan
• 金额: $ 52.51万
• 依托单位: SUNY DOWNSTATE MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-09-20 至 2026-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10298736
• 关键词: Address; Adolescent and Young Adult; Adult Children; Affect; Affective; Age; Alcohol consumption; Anatomy; Anisotropy; Behavior; Brain; COVID-19; COVID-19 pandemic; Cannabis; Clinical Data; Cognitive; Complement; Corpus striatum structure; DSM-V; Data; Data Collection; Development; Diagnosis; Diffusion; Diffusion Magnetic Resonance Imaging; Disease; Electroencephalography; Electrophysiology (science); Emotional; Epidemic; Ethnic Origin; Event-Related Potentials; Exhibits; Family; Family history of; Fiber; Fibrinogen; Functional Magnetic Resonance Imaging; Gambling; Genetic; Genomics; Hippocampus (Brain); Impairment; Individual; Inferior frontal gyrus; Insula of Reil; Joints; Literature; Longevity; Machine Learning; Measures; Mental Depression; Mental disorders; Methods; Modeling; Neurocognitive; Neuropsychology; Nicotine; Nucleus Accumbens; Pattern; Prevention; Prospective Studies; Protocols documentation; Race; Recording of previous events; Recovery; Rest; Rewards; Risk; Risk Factors; Role; Sampling; Sampling Studies; Sex Differences; Social Environment; Specificity; Stress; Structure; Thick; Time; Work; age effect; alcohol risk; alcohol use disorder; alcohol use initiation; analytical method; base; behavioral study; binge drinking; brain volume; career; cingulate cortex; cognitive task; comorbidity; coronavirus disease; density; developmental disease; disorder risk; drinking; drinking behavior; emerging adult; emerging adulthood; executive function; genetics of alcoholism; genome wide association study; high risk; high risk drinking; machine learning method; middle age; multimodal data; multimodality; neural circuit; neural network; neuroadaptation; neurogenomics; novel; offspring; polygenic risk score; prospective; protective factors; relating to nervous system; resilience; response; reward processing; sex; substance use; temporal measurement; trait; traumatic stress; white matter; young adult

This COGA (Collaborative Study on the Genetics of Alcoholism) spinoff application aims to understand structural/functional features in key brain networks (Default Mode Network (DMN), Executive Control Network (ECN), Reward/Salience Network (RSN)) underlying the critical transition from regular drinking to DSM-5 Alcohol Use Disorder (AUD) in young adult offspring from enriched COGA families, by combining newly ascertained structural, diffusion and functional (s/d/fMRI), Neuropsychological (NPsych) and Electrophysiological (EPhys) data together with existing multimodal longitudinal data (85% with 3+ assessments). The well- characterized, genetically informative COGA sample with many offspring from families densely affected with AUD at higher risk to develop AUD will be moving through the understudied age of young adulthood/early midlife (20's, 30's), when most longitudinal AUD development studies end and when our data predicts that a substantial portion from high density families will transition from regular alcohol use to AUD. This proposal will target 150 young adults (mean age 26) from the COGA study who are current regular drinkers (1/month+ for >6 months, but do not currently meet criteria for DSM-5 AUD), and will follow them longitudinally with a multimodal approach to compare those who transition to DSM-5 AUD and those who do not. We will add s/d/fMRI measures that are not part of the COGA protocol, to provide anatomical specificity to complement current and existing NPsych and EPhys longitudinal data during resting state, and three analogous cognitive/affective tasks [response inhibition (Go/NoGo), reward processing (monetary gambling task), and affect modulation (cognitive/affective Stroop)]. Combining machine learning methods, advanced nonparametric, linear mixed methods, survival model, and joint models of longitudinal data and survival data, we will: (Aim 1) identify features in specific neural circuits (DMN, ECN, RSN) during resting state and during cognitive/affective tasks in young adults who transition from regular drinking to AUD diagnosis from those who do not; (Aim 2) study the effects of drinking behaviors (e.g. age, pattern, duration of alcohol use) on the s/d/fMRI, EPhys, and NPsych features in specific neural circuits associated with the transition to AUD identified in Aim 1; and (Aim 3) determine the role of polygenic risk as measured by polygenic risk score (PRS) derived from alcohol use- and brain-related GWAS, other risk/protective factors [i.e., sex, race/ethnicity, family history, comorbid substance use (nicotine, cannabis), and psychiatric disorders (depression), COVID-related traumatic stress] on neural circuits and their developmental trajectories associated with transitions to AUD identified in Aims 1 and 2. The strength of our diverse, genetically informative, enriched high-risk sample of young adults, longitudinal multimodal measures, and novel integrative analyses will elucidate vulnerabilities and reciprocal relationships among neural circuits, genomic and other risk/protectives factors in the transition to AUD during the 20s and 30s, with utility in prevention and treatment initiatives.

这个COGA（酒精中毒遗传学合作研究）衍生应用程序旨在了解 关键脑网络的结构/功能特征（默认模式网络（DMN），执行控制网络 (ECN)奖励/显着性网络（RSN））的关键转变，从定期饮酒到DSM-5 酒精使用障碍（AUD）在年轻的成年后代丰富的COGA家庭，通过结合新的 确定的结构，扩散和功能（s/d/fMRI），神经心理（NPsych）和电生理 （EPHys）数据与现有的多模态纵向数据（85%，3+评估）。井- 特征性的、遗传信息丰富的COGA样本，其中许多后代来自严重受AUD影响的家族 发展AUD的风险较高的人将经历未充分研究的青年期/中年早期（20多岁， 30年代），当大多数纵向澳元发展研究结束时，当我们的数据预测， 从高密度家庭将从常规酒精使用过渡到AUD。该提案将针对150名年轻人 来自COGA研究的成年人（平均年龄26岁），目前经常饮酒（1/月+>6个月，但 目前不符合DSM-5 AUD的标准），并将采用多模式方法纵向跟踪这些标准， 比较那些过渡到DSM-5 AUD和那些没有过渡到DSM-5 AUD的人。我们将增加s/d/fMRI测量， COGA协议的一部分，提供解剖特异性，以补充当前和现有的NPsych， 在静息状态下的EPys纵向数据，以及三个类似的认知/情感任务[反应抑制 (Go/NoGo）、奖励处理（货币赌博任务）和情感调节（认知/情感Stroop）]。 结合机器学习方法，先进的非参数，线性混合方法，生存模型，联合 模型的纵向数据和生存数据，我们将：（目的1）识别特定的神经回路（DMN， ECN，RSN）在静息状态和认知/情感任务期间， 从不饮酒的人到AUD诊断;（目的2）研究饮酒行为的影响（例如年龄， 模式、饮酒持续时间）对特定神经回路中s/d/fMRI、EPYS和NPsych特征的影响 与目标1中确定的向AUD过渡相关;以及（目标3）确定多基因风险的作用， 通过来自酒精使用和脑相关GWAS的多基因风险评分（PRS）测量，其他风险/保护 因素[即，性别、种族/民族、家族史、共病药物使用（尼古丁、大麻）和精神疾病 疾病（抑郁症），COVID相关的创伤性应激]对神经回路及其发展轨迹的影响 与目标1和2中确定的向澳元过渡有关。我们多样化的，基因信息丰富的， 丰富的年轻人高风险样本，纵向多模式测量和新的综合分析 将阐明神经回路，基因组和其他之间的脆弱性和相互关系 在20多岁和30多岁期间向AUD过渡的风险/保护因素，在预防和治疗方面具有实用性 举措