Neurobiological markers of risk and resilience for psychopathology in youth at familial risk for mood disorders

在青少年中，重度抑郁症 (MDD) 和双相情感障碍 (BD) 是十大病因中的两个 残疾并增加自杀风险。由于 BD 通常最初表现为 MDD 发作，因此青少年 双相情感障碍经常被误诊，从而得不到有效的治疗。情绪障碍家族史是 早发性 MDD 和 BD 以及其他精神疾病的有力预测因子。先前的研究已经确定 BD 或 MDD 高家族风险的健康青少年相对于低家族风险的健康青少年之间的神经生物学差异， 一项研究发现，BD 和 MDD 家族高风险青少年之间的神经回路存在差异。 相关地，有初步证据表明神经标记可以预测精神病理学的后期发作 BD 和 MDD 家族风险较高的青少年。这些研究表明存在脆弱性标记 在症状出现之前可以在大脑中检测到，这可能会进一步增加心理健康状况不佳的风险 这些易受影响的年轻人的结果。然而，现有研究受到样本量较小的限制 随着时间的推移，缺乏多种纵向症状测量，这阻碍了识别 强大的生物标志物，可区分有 BD 家族史和 MDD 家族史的青少年的风险状况。的 识别青少年 BD 和 MDD 风险的大脑特征将促进对不同疾病的理解 脆弱性加剧背后的机制，最终可能会为更早和更多的方法提供信息 准确识别这些疾病。本研究旨在揭示独特的神经生物学特征 健康青少年中 BD 和 MDD 的高家族风险，并调查这些生物标志物是否可以预测 整个青春期精神病理学的后续发作和纵向过程。这项研究将包括 MDD（HR-MDD，n=1,564）或 BD（HR-BD，n=407）家族风险低（LR，n=3,915）或高的健康青年 长达 3 年的纵向数据，源自具有里程碑意义的青少年大脑认知发展 (ABCD) 学习。目标 1 将检查情绪和情绪中静息态功能连接 (FC) 的可分离模式 使用全脑种子在健康 HR-BD、HR-MDD 和 LR 青少年之间建立基线奖励相关网络 以杏仁核、腹侧纹状体和背侧纹状体作为感兴趣的种子区域的体素方法。目标2 将确定 3 年内青春期维度精神症状的纵向轨迹 使用基于群体的轨迹模型对高家庭风险青少年进行研究。目标 3 将调查是否发生了改变 情感和奖励相关网络中的基线 FC 预测稍后临床诊断的存在 青春期和/或整个青春期维度症状的更严重的纵向过程。这个 研究将揭示对弱势群体风险与复原力的影响机制的重要见解 青年，有可能成为干预措施的关键生物目标。这些知识也可能会告知 早期发现和干预计划，这将有助于减轻双相情感障碍和重度抑郁症的巨大负担。

Among youth, major depressive disorder (MDD) and bipolar disorder (BD) represent two of the top ten causes of disability and confer heightened risk of suicide. Since BD often initially presents as a MDD episode, youth with BD are frequently misdiagnosed and thus receive ineffective treatment. Family history of mood disorders is a robust predictor of early-onset MDD and BD as well as other psychiatric disorders. Prior studies have identified neurobiological differences between healthy youth at high familial risk for BD or MDD relative to low familial risk, and one study has identified neural circuit differences between youth at high familial risk for BD versus MDD. Relatedly, there is preliminary evidence for neural markers that predict later onset of psychopathology among youth at high familial risk for BD and MDD. These studies suggest that there are markers of vulnerability that can be detected in the brain, prior to symptom onset, which may further increase risk for poor mental health outcomes among these susceptible youth. However, extant research has been limited by small sample sizes and a lack of multiple longitudinal symptom measurements over time, which have hindered the identification of robust biomarkers that distinguish risk profiles among youth with a family history of BD versus MDD. The identification of brain-based signatures of BD and MDD risk in youth would advance understanding of distinct mechanisms underlying heightened vulnerability, which may ultimately inform approaches for earlier and more accurate identification of these disorders. The present study aims to uncover unique neurobiological profiles of high familial risk for BD and MDD among healthy youth, and to investigate whether these biomarkers predict the subsequent onset and longitudinal course of psychopathology across adolescence. This study will include healthy youth at low (LR, n=3,915) or high familial risk for MDD (HR-MDD, n=1,564) or BD (HR-BD, n=407) with longitudinal data up to 3 years, derived from the landmark Adolescent Brain Cognitive Development (ABCD) Study. Aim 1 will examine dissociable patterns of resting-state functional connectivity (FC) in emotion- and reward-related networks at baseline between healthy HR-BD, HR-MDD, and LR youth, using a whole-brain seed- to-voxel approach with the amygdala, ventral striatum, and dorsal striatum as seed regions of interest. Aim 2 will ascertain longitudinal trajectories of dimensional psychiatric symptoms across adolescence over 3 years in high familial risk youth using group-based trajectory modeling. Aim 3 will investigate whether alterations in baseline FC within emotion- and reward-related networks predicts the presence of a clinical diagnosis in later adolescence and/or a more severe longitudinal course of dimensional symptoms across adolescence. This research will reveal critical insight into the mechanisms that contribute to risk versus resilience in vulnerable youth, potentially serving as key biological targets for interventions. This knowledge may also potentially inform early detection and intervention programs, which will help to alleviate the immense burden of BD and MDD.