Gillan C M, Fineberg N A, Robbins T W
Department of Psychology,New York University,New York, NY,USA.
National Obsessive Compulsive Disorders Specialist Service,Hertfordshire Partnership NHS University Foundation Trust,UK.
Psychol Med. 2017 Jul;47(9):1528-1548. doi: 10.1017/S0033291716002786. Epub 2017 Mar 27.
Progress in understanding the underlying neurobiology of obsessive-compulsive disorder (OCD) has stalled in part because of the considerable problem of heterogeneity within this diagnostic category, and homogeneity across other putatively discrete, diagnostic categories. As psychiatry begins to recognize the shortcomings of a purely symptom-based psychiatric nosology, new data-driven approaches have begun to be utilized with the goal of solving these problems: specifically, identifying trans-diagnostic aspects of clinical phenomenology based on their association with neurobiological processes. In this review, we describe key methodological approaches to understanding OCD from this perspective and highlight the candidate traits that have already been identified as a result of these early endeavours. We discuss how important inferences can be made from pre-existing case-control studies as well as showcasing newer methods that rely on large general population datasets to refine and validate psychiatric phenotypes. As exemplars, we take 'compulsivity' and 'anxiety', putatively trans-diagnostic symptom dimensions that are linked to well-defined neurobiological mechanisms, goal-directed learning and error-related negativity, respectively. We argue that the identification of biologically valid, more homogeneous, dimensions such as these provides renewed optimism for identifying reliable genetic contributions to OCD and other disorders, improving animal models and critically, provides a path towards a future of more targeted psychiatric treatments.
对强迫症（OCD）潜在神经生物学的理解进展部分受阻，原因在于该诊断类别中存在相当严重的异质性问题，以及其他假定离散的诊断类别之间缺乏同质性。随着精神病学开始认识到纯粹基于症状的精神病学分类法的缺点，新的数据驱动方法已开始被用于解决这些问题：具体而言，基于临床现象学与神经生物学过程的关联来识别跨诊断方面。在本综述中，我们描述了从这个角度理解强迫症的关键方法，并强调了由于这些早期努力已经确定的候选特征。我们讨论了如何从现有的病例对照研究中得出重要推论，以及展示依赖大型普通人群数据集来完善和验证精神疾病表型的更新方法。作为示例，我们选取“强迫性”和“焦虑”，它们分别是与明确的神经生物学机制、目标导向学习和错误相关负波相关的假定跨诊断症状维度。我们认为，识别诸如此类具有生物学有效性、更具同质性的维度，为确定强迫症和其他疾病的可靠遗传贡献、改进动物模型带来了新的希望，至关重要的是，为未来更具针对性的精神科治疗指明了道路。
