Despite recent advances, there is still a major need for prediction of treatment success in schizophrenia, a condition long considered a disorder of dysconnectivity in the brain. Graph theory provides a means to characterize the connectivity in both healthy and abnormal brains. We calculated structural similarity networks in each participant and hypothesized that the "hubness", i.e., the number of edges connecting a node to the rest of the network, would be associated with clinical outcome. This prospective controlled study took place at an academic research center and included 82 early-phase psychosis patients (23 females; mean age [SD] = 21.6 [5.5] years) and 58 healthy controls. Medications were administered in a double-blind randomized manner, and patients were scanned at baseline prior to treatment with second-generation antipsychotics. Symptoms were assessed with the Brief Psychiatric Rating Scale at baseline and over the course of 12 weeks. Nodal degree of structural similarity networks was computed for each subject and entered as a predictor of individual treatment response into a partial least squares (PLS) regression. The model fit was significant in a permutation test with 1000 permutations (P = 0.006), and the first two PLS regression components explained 29% (95% CI: 27; 30) of the variance in treatment response after cross-validation. Nodes loading strongly on the first PLS component were primarily located in the orbito- and prefrontal cortex, whereas nodes loading strongly on the second PLS component were primarily located in the superior temporal, precentral, and middle cingulate cortex. These data suggest a link between brain network morphology and clinical outcome in early-phase psychosis.

中文翻译：

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结构相似性网络预测早期精神病的临床结果。

尽管最近取得了进展，但仍然非常需要预测精神分裂症的治疗成功，这种情况长期以来被认为是大脑中的连接障碍。图论提供了一种表征健康和异常大脑中连接性的方法。我们计算了每个参与者的结构相似性网络，并假设“中心性”，即连接节点与网络其余部分的边数，将与临床结果相关联。这项前瞻性对照研究在一个学术研究中心进行，包括 82 名早期精神病患者（23 名女性；平均年龄 [SD] = 21.6 [5.5] 岁）和 58 名健康对照者。药物以双盲随机方式给药，在使用第二代抗精神病药物治疗之前，对患者进行基线扫描。在基线和 12 周的过程中，使用简明精神病学评定量表评估症状。为每个受试者计算结构相似性网络的节点度，并将其作为个体治疗反应的预测因子输入到偏最小二乘法 (PLS) 回归中。模型拟合在具有 1000 个排列的排列测试中是显着的 (P = 0.006)，前两个 PLS 回归分量解释了交叉验证后治疗反应中 29% (95% CI: 27; 30) 的方差。在第一个 PLS 组件上强烈加载的节点主要位于眼眶和前额叶皮层，而在第二个 PLS 组件上强烈加载的节点主要位于颞上、中央前、和中间扣带皮层。这些数据表明脑网络形态与早期精神病的临床结果之间存在联系。