Thursday, November 21, 2024
11/21/2024
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.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
