Proposal for a Novel Classification of Patients With Enlarged Ventricles and Cognitive Impairment Based on Data‐Driven Analysis of Neuroimaging Results in Patients With Psychiatric Disorders

• Published in: Neuropsychopharmacology reports Vol. 45; no. 1; pp. e70010 - n/a
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.03.2025; John Wiley and Sons Inc; Wiley
• Subjects: Adult; Autism; Biomarkers; Bipolar disorder; Brain - diagnostic imaging; Brain - pathology; Brain research; Cerebral Ventricles - diagnostic imaging; Cerebral Ventricles - pathology; Classification; Cluster Analysis; Cognitive ability; Cognitive Dysfunction - classification; Cognitive Dysfunction - diagnostic imaging; cognitive impairment; copy number variation; data‐driven analysis; Disease; Electroencephalography; enlarged ventricles; Female; Humans; Intelligence; Magnetic Resonance Imaging; Male; Medical imaging; Mental depression; Mental disorders; Mental Disorders - classification; Mental Disorders - complications; Mental Disorders - diagnostic imaging; Mental Disorders - pathology; Middle Aged; Neuroimaging; Neuroimaging - methods; Original; Quality control; Regression analysis; Review boards; Schizophrenia; Young Adult; enlarged ventricles; cognitive impairment; data‐driven analysis; schizophrenia; copy number variation
• ISSN: 2574-173X; 2574-173X
• DOI: 10.1002/npr2.70010

ABSTRACT 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. An enlarged ventricle is a representative feature of brain biotype 1 among the four brain biotypes classified by subcortical regional volume.