Brazilian-American Initiative on Neuroimaging for Identifying Depression Early in Adolescence (BRAIN-IDEA)

项目总结/摘要 抑郁症是全球青少年残疾的主要原因，也是自杀的主要风险因素。九十 世界上有10%的青少年生活在低收入和中等收入国家（LMIC），但大多数研究表明， 在高收入国家（HIC）进行了一项关于青少年抑郁症的研究。这就造成了一个巨大的差距， 我们对青少年抑郁症的心理社会预测因素和神经发育机制的了解 在低资源环境中。我们的团队，一个成熟的全球跨学科联盟：识别抑郁症 早期的青春期（IDEA），是唯一的定位，成功地进行大规模的纵向研究， LMIC设置来解决这些差距。研究团队的长期目标是开发一种跨文化的 有效的抑郁症风险计算器，可以识别抑郁症高危青少年，以指导研究， 预防和治疗的基础上的知识神经网络驱动抑郁症的风险。年的目标 这个R21是为了测试中等收入国家抑郁症风险计算器的预测效用，并确定 这个风险计算器是否预测了在假设的神经网络中改变的神经发育。此外，本发明还提供了一种方法， 该团队将为LMIC的青少年神经科学研究建立能力。IDEA研究联盟 使用收集的社会人口统计学变量生成了抑郁症发展的综合风险评分 直接来自青少年。使用这个风险评分，研究小组招募了150名青少年作为基线样本 (ages 14至16岁，50%为女性，44%为非洲裔），他们被归类为巴西波尔图阿莱格雷的 基线时分为三组：50名“高风险”参与者，目前或以前没有抑郁症，50名“低风险”参与者 没有当前或先前的抑郁症，和50名参与者与当前未经治疗的抑郁症。在他们的基线期间， 在评估中，参与者完成了fMRI扫描，任务引起了威胁和奖励网络活动， 完成抑郁症状的测量。对于此R21，他们将在基线后3年被邀请回来 评估完成相同的措施。研究团队将完成三个具体目标。一是 研究小组将测试基线风险组分类是否能预测抑郁症状严重程度的变化 三年后，威胁和奖励大脑网络的改变是否可以解释这一点 协会其次，根据研究领域标准（RDoC）框架，该团队将研究 威胁和奖励网络的变化是否可以预测与以下行为相关的行为和抑郁症状： 消极情感和快感缺失。第三，研究小组将在巴西进行能力建设， 通过一系列培训项目进行跨学科神经科学研究。这项研究将推动 NIMH战略目标2通过表征与脑功能相关的脑功能的发展轨迹， 抑郁症的发展，并确定临床上有用的生物标志物和行为指标，预测风险 治疗青春期抑郁症

PROJECT SUMMARY/ABSTRACT Depression is a leading cause of disability in adolescents worldwide and is a major risk factor for suicide. Ninety percent of the world’s adolescents live in low- and middle-income countries (LMIC), yet the majority of research on adolescent depression has been conducted in high-income countries (HIC). This leaves a significant gap in our knowledge of the psychosocial predictors and neurodevelopmental mechanisms of adolescent depression in low resource settings. Our team, an established global interdisciplinary consortium: Identifying Depression Early in Adolescence (IDEA), is uniquely positioned to successfully conduct large scale longitudinal research in LMIC settings to address these gaps. The long-term goal of the research team is to develop a cross-culturally valid risk calculator for depression that could identify adolescents at high risk for depression to guide research, prevention, and treatment based on knowledge of the neural networks driving depression risk. The objective for this R21 is to test the predictive utility of a risk calculator for depression in a middle-income country and determine whether this risk calculator predicts altered neural development within hypothesized neural networks. In addition, the team will build capacity for adolescent neuroscience research in LMIC. The IDEA research consortium has generated a composite risk score for the development of depression using sociodemographic variables collected directly from the adolescent. Using this risk score, the team recruited a baseline sample of 150 adolescents (ages 14 to 16 years, 50% female, 44% African descent) in Porto Alegre, Brazil, who were classified into one of three groups at baseline: 50 “high-risk” participants without current or prior depression, 50 “low-risk” participants without current or prior depression, and 50 participants with current untreated depression. During their baseline assessment, participants completed an fMRI scan with tasks that elicited threat and reward network activity and completed measures of depression symptoms. For this R21, they will be invited back 3 years after the baseline assessment to complete the same measures. The research team will complete three specific aims. First, the team will test whether risk group classification at baseline predicts changes in depression symptom severity three years later, and whether altered development of the threat and reward brain networks explains this association. Second, in line with the Research Domain Criteria (RDoC) framework, the team will examine whether changes in the threat and reward networks predict behaviors and depression symptoms associated with negative affect and anhedonia, respectively. Third, the research team will build capacity in Brazil to conduct interdisciplinary neuroscience research through a constellation of training programs. This research will advance NIMH Strategic Objective 2 by characterizing developmental trajectories of brain function associated with the development of depression and identifying clinically useful biomarkers and behavioral indicators that predict risk for depression during adolescence.