Department of Brain and Cognitive Sciences, Seoul National University College of Natural Sciences, Seoul, Republic of Korea.
Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea.
Transl Psychiatry. 2020 Oct 26;10(1):359. doi: 10.1038/s41398-020-01045-4.
Characterization of obsessive-compulsive disorder (OCD), like other psychiatric disorders, suffers from heterogeneities in its symptoms and therapeutic responses, and identification of more homogeneous subgroups may help to resolve the heterogeneity. We aimed to identify the OCD subgroups based on resting-state functional connectivity (rsFC) and to explore their differences in treatment responses via a multivariate approach. From the resting-state functional MRI data of 107 medication-free OCD patients and 110 healthy controls (HCs), we selected rsFC features, which discriminated OCD patients from HCs via support vector machine (SVM) analyses. With the selected brain features, we subdivided OCD patients into subgroups using hierarchical clustering analyses. We identified 35 rsFC features that achieved a high sensitivity (82.74%) and specificity (76.29%) in SVM analyses. The OCD patients were subdivided into two subgroups, which did not show significant differences in their demographic and clinical backgrounds. However, one of the OCD subgroups demonstrated more impaired rsFC that was involved either within the default mode network (DMN) or between DMN brain regions and other network regions. This subgroup also showed both lower improvements in symptom severity in the 16-week follow-up visit and lower responder percentage than the other subgroup. Our results highlight that not only abnormalities within the DMN but also aberrant rsFC between the DMN and other networks may contribute to the treatment response and support the importance of these neurobiological alterations in OCD patients. We suggest that abnormalities in these connectivity may play predictive biomarkers of treatment response, and aid to build more optimal treatment strategies.
强迫症（OCD）的特征，与其他精神障碍一样，其症状和治疗反应存在异质性，识别更同质的亚组可能有助于解决这种异质性。我们旨在基于静息态功能连接（rsFC）识别 OCD 亚组，并通过多变量方法探索它们在治疗反应方面的差异。我们从 107 名未服用药物的 OCD 患者和 110 名健康对照者（HCs）的静息态功能磁共振成像（rsfMRI）数据中，通过支持向量机（SVM）分析选择了能够区分 OCD 患者和 HCs 的 rsFC 特征。利用所选的脑特征，我们使用层次聚类分析将 OCD 患者分为亚组。我们确定了 35 个 rsFC 特征，在 SVM 分析中具有较高的灵敏度（82.74%）和特异性（76.29%）。OCD 患者分为两个亚组，在人口统计学和临床背景方面没有显著差异。然而，其中一个 OCD 亚组表现出更多的 rsFC 受损，这些 rsFC 既涉及默认模式网络（DMN）内，也涉及 DMN 脑区与其他网络区域之间。这个亚组在 16 周的随访中也表现出症状严重程度的改善较低，以及应答者比例低于另一个亚组。我们的研究结果表明，不仅 DMN 内的异常，而且 DMN 与其他网络之间的异常 rsFC，可能与治疗反应有关，并支持这些神经生物学改变在 OCD 患者中的重要性。我们建议，这些连接中的异常可能成为治疗反应的预测生物标志物，并有助于构建更优化的治疗策略。
