Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach

• Published in: Frontiers in human neuroscience 2022, Vol.16, p.1001692-1001692
• Main Authors: Rootes-Murdy, Kelly, Edmond, Jesse T, Jiang, Wenhao, Rahaman, Md A, Chen, Jiayu, Perrone-Bizzozero, Nora I, Calhoun, Vince D, van Erp, Theo G M, Ehrlich, Stefan, Agartz, Ingrid, Jönsson, Erik G, Andreassen, Ole A, Westlye, Lars T, Wang, Lei, Pearlson, Godfrey D, Glahn, David C, Hong, Elliot, Buchanan, Robert W, Kochunov, Peter, Voineskos, Aristotle, Malhotra, Anil, Tamminga, Carol A, Liu, Jingyu, Turner, Jessica A
• Format: Article
• Language: English
• Subjects: bipolar disorder; ICA; Medicin och hälsovetenskap; multivariate analysis; Neuroscience; PANSS; schizophrenia
• ISSN: 1662-5161; 1662-5161
• DOI: 10.3389/fnhum.2022.1001692

Structural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles. We analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large ( ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP. Component A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences. These multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.