Yasuda Yuka, Ito Satsuki, Matsumoto Junya, Okada Naohiro, Onitsuka Toshiaki, Ikeda Masashi, Kushima Itaru, Sumiyoshi Chika, Fukunaga Masaki, Nemoto Kiyotaka, Miura Kenichiro, Hashimoto Naoki, Ohi Kazutaka, Takahashi Tsutomu, Sasabayashi Daiki, Koeda Michihiko, Yamamori Hidenaga, Fujimoto Michiko, Takano Harumasa, Hasegawa Naomi, Narita Hisashi, Yamamoto Maeri, Tha Khin Khin, Kikuchi Masataka, Kamishikiryo Toshiharu, Itai Eri, Okubo Yoshiro, Tateno Amane, Nakamura Motoaki, Kubota Manabu, Igarashi Hiroyuki, Hirano Yoji, Okada Go, Miyata Jun, Numata Shusuke, Abe Osamu, Yoshimura Reiji, Nakagawa Shin, Yamasue Hidenori, Ozaki Norio, Kasai Kiyoto, Hashimoto Ryota
Life Grow Brilliant Mental Clinic, Medical Corporation Foster, Osaka, Osaka, Japan.
Department of Pathology of Mental Diseases, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
Neuropsychopharmacol Rep. 2025 Mar;45(1):e70010. doi: 10.1002/npr2.70010.
One of the challenges in diagnosing psychiatric disorders is that the results of biological and neuroscience research are not reflected in the diagnostic criteria. Thus, data-driven analyses incorporating biological and cross-disease perspectives, regardless of the diagnostic category, have recently been proposed. A data-driven clustering study based on subcortical volumes in 5604 subjects classified into four brain biotypes associated with cognitive/social functioning. Among the four brain biotypes identified in controls and patients with schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, and other psychiatric disorders, we further analyzed the brain biotype 1 subjects, those with an extremely small limbic region, for clinical utility. We found that the representative feature of brain biotype 1 is enlarged lateral ventricles. An enlarged ventricle, defined by an average z-score of left and right lateral ventricle volumes > 3, had a sensitivity of 99.1% and a specificity of 98.1% for discriminating brain biotype 1. However, the presence of an enlarged ventricle was not sufficient to classify patient subgroups, as 1% of the controls also had enlarged ventricles. Reclassification of patients with enlarged ventricles according to cognitive impairment resulted in a stratified subgroup that included patients with a high proportion of schizophrenia diagnoses, electroencephalography abnormalities, and rare pathological genetic copy number variations. Data-driven clustering analysis of neuroimaging data revealed subgroups with enlarged ventricles and cognitive impairment. This subgroup could be a new diagnostic candidate for psychiatric disorders. This concept and strategy may be useful for identifying biologically defined psychiatric disorders in the future.
诊断精神疾病的挑战之一在于生物和神经科学研究的结果并未反映在诊断标准中。因此,最近有人提出了结合生物和跨疾病视角的数据驱动分析方法,而不考虑诊断类别。一项基于5604名受试者皮质下体积的数据驱动聚类研究将其分为与认知/社会功能相关的四种脑生物型。在对照组以及患有精神分裂症、双相情感障碍、重度抑郁症、自闭症谱系障碍和其他精神疾病的患者中所确定的四种脑生物型中,我们进一步分析了脑生物型1的受试者,即边缘区域极小的那些受试者,以探讨其临床实用性。我们发现脑生物型1的典型特征是侧脑室扩大。通过左右侧脑室体积的平均z分数>3来定义的扩大脑室,在区分脑生物型1方面的敏感性为99.1%,特异性为98.1%。然而,脑室扩大并不足以对患者亚组进行分类,因为1%的对照组也有脑室扩大的情况。根据认知障碍对脑室扩大的患者进行重新分类,产生了一个分层亚组,其中精神分裂症诊断比例高、脑电图异常以及罕见病理性基因拷贝数变异的患者占比很大。对神经影像数据进行数据驱动聚类分析揭示了脑室扩大和认知障碍的亚组。这个亚组可能是精神疾病的一个新的诊断候选类型。这一概念和策略可能有助于未来识别生物学定义的精神疾病。