Wang Jicai, Cao Hongbao, Liao Yanhui, Liu Weiqing, Tan Liwen, Tang Yanqing, Chen Jindong, Xu Xiufeng, Li Haijun, Luo Chunrong, Liu Chunyu, Ries Merikangas Kathleen, Calhoun Vince, Tang Jinsong, Shugart Yin Yao, Chen Xiaogang
Institute of Mental Health, The Second Xiangya Hospital of Central South University, 139 Renmin Road, Changsha, Hunan 410011, China ; Department of Psychiatry, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan Province 650032, China.
Unit on Statistical Genomics, National Institute of Mental Health, NIH, Bethesda 20892, USA.
Neuroimage Clin. 2015 Mar 24;8:95-103. doi: 10.1016/j.nicl.2015.03.017. eCollection 2015.
Among individuals diagnosed with schizophrenia, approximately 20%-33% are recognized as treatment-resistant schizophrenia (TRS) patients. These TRS patients suffer more severely from the disease but struggle to benefit from existing antipsychotic treatments. A few recent studies suggested that schizophrenia may be caused by impaired synaptic plasticity that manifests as functional dysconnectivity in the brain, however, few of those studies focused on the functional connectivity changes in the brains of TRS groups. In this study, we compared the whole brain connectivity variations in TRS patients, their unaffected siblings, and healthy controls. Connectivity network features between and within the 116 automated anatomical labeling (AAL) brain regions were calculated and compared using maps created with three contrasts: patient vs. control, patient vs. sibling, and sibling vs.
To evaluate the predictive power of the selected features, we performed a multivariate classification approach. We also evaluated the influence of six important clinical measures (e.g. age, education level) on the connectivity features. This study identified abnormal significant connectivity changes of three patterns in TRS patients and their unaffected siblings: 1) 69 patient-specific connectivity (PCN); 2) 102 shared connectivity (SCN); and 3) 457 unshared connectivity (UCN). While the first two patterns were widely reported by previous non-TRS specific studies, we were among the first to report widespread significant connectivity differences between TRS patient groups and their healthy sibling groups. Observations of this study may provide new insights for the understanding of the neurophysiological mechanisms of TRS.
在被诊断为精神分裂症的个体中，约20%-33%被认为是难治性精神分裂症（TRS）患者。这些TRS患者病情更严重，但难以从现有的抗精神病治疗中获益。最近的一些研究表明，精神分裂症可能由突触可塑性受损引起，表现为大脑中的功能连接障碍，然而，这些研究中很少有关注TRS组大脑功能连接变化的。在本研究中，我们比较了TRS患者、其未患病的兄弟姐妹以及健康对照者的全脑连接变化。使用通过三种对比创建的图谱计算并比较了116个自动解剖标记（AAL）脑区之间和内部的连接网络特征：患者与对照、患者与兄弟姐妹、兄弟姐妹与对照。
为了评估所选特征的预测能力，我们采用了多变量分类方法。我们还评估了六项重要临床指标（如年龄、教育水平）对连接特征的影响。本研究确定了TRS患者及其未患病兄弟姐妹中三种模式的异常显著连接变化：1）69个患者特异性连接（PCN）；2）102个共享连接（SCN）；3）457个非共享连接（UCN）。虽然前两种模式在先前的非TRS特异性研究中已有广泛报道，但我们是首批报道TRS患者组与其健康兄弟姐妹组之间存在广泛显著连接差异的研究之一。本研究的观察结果可能为理解TRS的神经生理机制提供新的见解。
