Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan.
Schizophr Bull. 2017 Jul 1;43(4):900-906. doi: 10.1093/schbul/sbw176.
Schizophrenia is an etiologically and clinically heterogeneous disorder. Although neuroimaging studies have revealed brain alterations in schizophrenia, most studies have assumed that the disorder is a single entity, neglecting the diversity of alterations observed in the disorder. The current study sought to explore the distinct patterns of altered cortical thickness in patients with schizophrenia and healthy individuals using a data-driven approach. Unsupervised clustering using self-organizing maps followed by a K-means algorithm was applied to regional cortical thickness data in 108 schizophrenia patients and 121 healthy controls. After clustering, the clinical characteristics and cortical thickness patterns of each cluster were assessed. Unsupervised clustering revealed that a 6-cluster solution was the most appropriate in this sample. There was substantial overlap between the patterns of cortical thickness in schizophrenia patients and healthy controls, although the distributions of the patients and controls differed across the clusters. The patterns of altered cortical thickness in schizophrenia exhibited cluster-specific features; patients within a cluster exhibited the most extensive cortical thinning, particularly in the medial prefrontal and temporal regions, while those in other clusters exhibited reduced cortical thickness in the medial frontal region or temporal lobe. Furthermore, in the schizophrenia group, extensive cortical thinning was correlated with a higher dosage of antipsychotic medication, while preserved cortical thickness appeared to be linked to less negative symptoms. This data-driven neuroimaging approach revealed distinct patterns of cortical thinning in schizophrenia, possibly reflecting the etiological heterogeneity of the disorder.
精神分裂症是一种病因学和临床表现均存在异质性的疾病。尽管神经影像学研究已经揭示了精神分裂症患者的大脑改变，但大多数研究都假设该疾病是单一实体，忽略了该疾病中观察到的多样性改变。本研究旨在使用数据驱动的方法探讨精神分裂症患者和健康个体之间皮质厚度改变的不同模式。使用自组织映射的无监督聚类，然后使用 K-均值算法，对 108 名精神分裂症患者和 121 名健康对照者的局部皮质厚度数据进行了分析。聚类后，评估了每个聚类的临床特征和皮质厚度模式。无监督聚类表明，在该样本中，6 聚类解决方案是最合适的。尽管患者和对照组的分布在聚类之间存在差异，但精神分裂症患者和健康对照组之间的皮质厚度模式存在很大重叠。精神分裂症患者的皮质厚度改变模式具有聚类特异性；一个聚类内的患者表现出最广泛的皮质变薄，特别是在前内侧额和颞叶区域，而其他聚类的患者则表现出内侧额叶或颞叶皮质厚度减少。此外，在精神分裂症组中，广泛的皮质变薄与抗精神病药物剂量的增加相关，而皮质厚度的保持似乎与较少的阴性症状有关。这种基于数据的神经影像学方法揭示了精神分裂症皮质变薄的不同模式，可能反映了该疾病的病因异质性。
