Identification of Neurobiological Intermediate Phenotypes in Major Depressive Dis

描述（由申请人提供）：NIMH的一项主要倡议是早期识别精神疾病的风险中间表型（IPs），以及这些IPs的进展与复发。长期以来对活动性疾病状态的关注，而不是缓解状态，阻碍了对这些IPs及其随时间稳定性的精确研究。本研究旨在通过招募从重度抑郁症缓解的个体，在青春期晚期/成年早期的疾病过程中更好地识别神经生物学IPs。我们将在三周的时间内建立IPs的稳定性，然后对这些个体进行为期一年的跟踪，使用这些IPs来预测抑郁症的复发。我们小组和其他人的研究表明，共病抑郁和焦虑（MDD+A）是MDD的一个强大亚型。这支持了先前的研究，即先前存在的焦虑症会增加患重度抑郁症的风险，治疗效果较差的风险，以及更大的复发机会。因此，更好地了解这些年轻人对健康的好处，有很大的潜力启动更有针对性的治疗策略，并确定那些最需要随访的人。60名年龄在18到22岁之间从重度抑郁症中解脱出来的第一次发作的年轻人将被纳入研究，另外60名年龄和性别匹配的健康对照者将被纳入研究。重度抑郁症患者要么从第一发作缓解，有阳性家族史，要么在第二和第三发作之间，没有家族史。70名重度抑郁症受试者将被平均分为有和没有焦虑症病史的人，并与60名健康对照的年轻人进行比较。神经生物学IP测量包括fMRI与情绪，调节（抑制控制），记忆范式和类似的神经心理学测量（记忆，情绪处理，执行功能）。这些测量将在指标点（缓解状态）和3周后（评估性状稳定性）再次使用。分析将集中在1)定义MDD+A与MDD IPs的特征，2)这些IPs在缓解状态下的稳定性，以及3)这些IPs预测一年内抑郁症复发/复发的能力。我们将在关键阶段研究这些个体，在疾病过程的早期，与年轻青少年的研究相比，发育变异性将被最小化。这将使我们能够在累积疾病效应出现之前评估这些IPs的存在和稳定性。将神经生物学IPs的搜索嵌入到复发预测研究中，可以将研究结果随时转化为临床环境。纵向方法巩固了诊断，解决了IP测量的稳定性，并为临床应用提供了一个简单的进入，如果我们从异质MDD组中获得的初步结果可以在这些更均匀的样本中复制。BRAINS机制允许该PI进行这种创新的、关键的冒险，以改进他对患有MDD+A和MDD的成人的ip的初步工作。

DESCRIPTION (provided by applicant): A major initiative of NIMH is the early identification of risk intermediate phenotypes (IPs) for psychiatric disorders and the progression of these IPs with recurrence of episodes. The longtime focus on active disease states, rather than the remitted state, has thwarted precise study of these IPs and their stability over time. The present study is designed to better identify neurobiological IPs by enrolling individuals remitted from MDD, early in the course of illness in late adolescence/early adulthood. We will establish the stability of IPs over a three week period, and then follow these individuals for 1 year to use these IPs to predict recurrence of depressive illnesses. Research by our group and others suggests that comorbid depression and anxiety (MDD+A) is a robust subtype for MDD. This supports the previous research that pre-existing anxiety disorder increases risk for MDD, risk for poorer treatment response, and greater chance of relapse. As such, the health benefits of better understanding these young adults has great potential to initiate more tailored treatment strategies, and to identify those most in need of follow-up. Sixty first episode young adults between the ages of 18 and 22 remitted from MDD will be enrolled in the study as well as sixty age and sex matched healthy controls. The MDD subjects will be either remitted from a first episode with positive family history, or between the second and third episodes with no family history. The 70 MDD subjects will be evenly divided between those with and without a prior history of anxiety disorder and compared to 60 healthy control young adults. Neurobiological IP measures include fMRI with emotion, regulation (inhibitory control), and memory paradigms and similar neuropsychological measures (memory, emotion processing, executive functioning). These measures will be used at the index point (remitted state) and again 3 weeks later (to assess trait stability). Analyses will focus on 1) defining the trait MDD+A vs trait MDD IPs, 2) stability of these IPs in the remitted state, and 3) ability of these IPs to predict relapse/recurrence of depressive illness at one year. We will study these individuals at the critical nexus, early in the course of illness where developmental variability will be minimized compared to studies of younger adolescents. This will enable us to assess the presence and stability of these IPs before cumulative illness effects are present. Embedding the search for neurobiological IPs into a relapse prediction study can provide for ready translation of findings into clinical settings. A longitudinal approach solidifies diagnoses, and addresses stability of IP measures, and provides a easy entrie into a clinical application, should our preliminary results from a heterogeneous MDD group be replicated in these more homogeneous samples. The BRAINS mechanism allows this PI to take this innovative, critical venture toward refining his initial work on IPs for adults with MDD+A and MDD.