Brain Function and Neurogenomic influences on AUD risk and resilience.

这个COGA(酒精中毒遗传学合作研究)衍生应用程序旨在理解 关键大脑网络(默认模式网络(DMN)、执行控制网络)的结构/功能特征 (ECN)，奖励/显著网络(RSN)是从经常饮酒到DSM-5关键转变的基础 来自丰富的COGA家庭的年轻成年后代的酒精使用障碍(AUD)，通过结合新的 确定结构、扩散和功能(S/d/fMRI)、神经心理(NPsych)和电生理 (EPHYS)数据和现有的多模式纵向数据(85%使用3+评估)。这口井- 具有特征的、遗传信息丰富的COGA样本，其中有许多来自AUD密集影响家庭的后代 患上澳门氏症的风险更高的人群将会进入未被充分研究的青壮年/中年早期(20‘S， S)，当大多数纵向AUD发展研究结束时，当我们的数据预测很大一部分 来自高密度家庭的人将从经常饮酒过渡到澳元。这项提案将针对150名年轻人 COGA研究中的成年人(平均年龄26岁)，目前经常饮酒(1个月+6个月，但确实如此 目前不符合DSM-5 AUD标准)，并将纵向遵循这些标准，采用多模式方法来 将那些过渡到DSM-5 AUD的人与那些没有过渡到DSM-5的人进行比较。我们将添加S/d/fMRI措施 COGA协议的一部分，为补充当前和现有的NPsych和 静息状态下的EPHY纵向数据和三个类似的认知/情感任务[反应抑制 (Go/NoGo)、奖励处理(金钱赌博任务)和影响调制(认知/情感Stroop)]。 结合机器学习方法、高级非参数方法、线性混合方法、生存模型和关节 纵向数据和生存数据的模型，我们将：(目标1)识别特定神经回路中的特征(DMN， 在静息状态和认知/情感任务中，从正常状态过渡的年轻人 (目标2)研究饮酒行为的影响(例如，年龄， 在特定神经回路的S/d/fMRI、EPHYs和NPsych特征上) 与目标1中确定的向AUD的过渡有关；和(目标3)确定多基因风险的作用如下 由酒精使用和与脑相关的GWA、其他风险/保护措施得出的多基因风险评分(PR)衡量 因素[即性别、种族/族裔、家族史、共患药物使用(尼古丁、大麻)和精神疾病 神经回路中的障碍(抑郁、COVID相关创伤性应激)及其发展轨迹 与目标1和目标2中确定的向AUD的过渡相关。我们多样化的、遗传信息丰富的 丰富的年轻人高危样本、纵向多模式测量和新颖的综合分析 将阐明神经回路、基因组和其他之间的脆弱性和相互关系 20年代和30年代向澳门氏病过渡的风险/保护因素，在预防和治疗中的效用 首创精神。

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.