Guerrero Daniel, Dzemidzic Mario, Moghaddam Mahdi, Liu Mintao, Avena-Koenigsberger Andrea, Harezlak Jaroslaw, Kareken David A, Plawecki Martin H, Cyders Melissa A, Goñi Joaquín
Edwardson School of Industrial Engineering, Purdue University, West-Lafayette, IN, USA.
Purdue Institute of Integrative Neuroscience, Purdue University, West-Lafayette, IN, USA.
ArXiv. 2025 Apr 8:arXiv:2504.06199v1.
Prolonged alcohol use results in neuroadaptations that mark more severe and treatment-resistant alcohol use. The goal of this study was to identify functional connectivity brain patterns underlying Alcohol Use Disorder (AUD)-related characteristics in fifty-five adults (31 female) who endorsed heavy alcohol use. We hypothesized that resting-state functional connectivity (rsFC) of the Salience (SN), Frontoparietal (FPN), and Default Mode (DMN) networks would reflect self-reported recent and lifetime alcohol use, laboratory-based alcohol seeking, urgency, and sociodemographic characteristics related to AUD. To test our hypothesis, we combined the triple network model (TNM) of psychopathology with a multivariate data-driven approach, regularized partial least squares (rPLS), to unfold concurrent functional connectivity (FC) patterns and their association with AUD characteristics. We observed three concurrent associations of interest: i) drinking and age-related cross communication between the SN and both the FPN and DMN; ii) family history density of AUD and urgency anticorrelations between the SN and FPN; and iii) alcohol seeking and sex-associated SN and DMN interactions. These findings demonstrate the utility of combining theory- and data-driven approaches to uncover associations between resting-state functional substrates and AUD-related characteristics that could aid in the identification, development, and testing of novel treatment targets across preclinical and clinical models.
长期饮酒会导致神经适应性变化,这些变化标志着更严重且难治的酒精使用问题。本研究的目的是在55名认可大量饮酒的成年人(31名女性)中,确定酒精使用障碍(AUD)相关特征背后的功能连接脑模式。我们假设,突显网络(SN)、额顶叶网络(FPN)和默认模式网络(DMN)的静息态功能连接(rsFC)将反映自我报告的近期和终生饮酒情况、基于实验室的觅酒行为、冲动性以及与AUD相关的社会人口学特征。为了验证我们的假设,我们将精神病理学的三重网络模型(TNM)与多变量数据驱动方法——正则化偏最小二乘法(rPLS)相结合,以揭示并发功能连接(FC)模式及其与AUD特征的关联。我们观察到三个感兴趣的并发关联:i)饮酒与年龄相关的SN与FPN和DMN之间的交叉通信;ii)AUD家族史密度与SN和FPN之间的冲动性负相关;iii)觅酒行为与性别相关的SN和DMN相互作用。这些发现证明了结合理论驱动和数据驱动方法来揭示静息态功能基质与AUD相关特征之间关联的实用性,这有助于在临床前和临床模型中识别、开发和测试新的治疗靶点。