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

在年轻人中，严重抑郁障碍(MDD)和双相情感障碍(BD)是十大病因中的两个 残疾的风险，并增加自杀的风险。由于BD通常最初表现为MDD发作，年轻人患有 BD经常被误诊，因此接受的治疗无效。情绪障碍的家族史是一种 对早发性MDD和BD以及其他精神疾病的有力预测。先前的研究已经确定 BD或MDD家族风险高的健康青年与低家族风险的健康青年之间的神经生物学差异 一项研究已经确定了BD和MDD家族高危青年之间的神经回路差异。 与之相关的是，有初步证据表明，神经标记物可以预测精神病理学的较晚发病。 BD和MDD的高家族风险青年。这些研究表明，存在易受攻击的标志 可以在症状出现之前在大脑中检测到，这可能会进一步增加精神健康不良的风险 在这些易受影响的青年中的结果。然而，现有的研究一直受到样本量小的限制。 以及缺乏随时间推移的多种纵向症状测量，这阻碍了对 强健的生物标记物，区分有BD和MDD家族史的年轻人的风险特征。这个 在年轻人中识别BD和MDD风险的基于大脑的特征将促进对不同的 脆弱性增加的潜在机制，这最终可能会为更早和更多的 对这些疾病的准确识别。目前的研究旨在揭示独特的神经生物学特征。 健康青年中BD和MDD的高家族性风险，并调查这些生物标志物是否可以预测 青春期精神病理学的后续发病和纵向病程。这项研究将包括 健康青年患有MDD(HR-MDD，n=1,564)或BD(HR-BD，n=407)的低风险(LR，n=3,915)或高风险(HR-MDD，n=1,564) 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将研究情绪中静息状态功能连接(FC)的可分离模式--以及 健康的HR-BD、HR-MDD和LR年轻人之间基线的奖励相关网络，使用全脑种子- 以杏仁核、腹侧纹状体和背侧纹状体为种子感兴趣区的体素方法。目标2 将在3年内确定青春期维度精神症状的纵向轨迹 使用基于群体的轨迹建模的高危青少年。AIM 3将调查是否存在 情绪和奖励相关网络中的基线FC预测以后临床诊断的存在 青春期和/或整个青春期更严重的维度症状的纵向病程。这 研究将揭示导致脆弱人群风险与弹性的关键机制 青年，有可能成为干预措施的主要生物目标。这一知识也可能会让人们 早期发现和干预计划，这将有助于减轻BD和MDD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.