Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium

• Authors: Hengyi Cao, Yale University; Yoohuo Chung, Yale University; Sarah C McEwen, University of California, Los Angeles; Carrie E Bearden, University of California, Los Angeles; Jean Addington, University of Calgary; Bradley Goodyear, University of Calgary; Kristin S Cadenhead, Department of Psychiatry; Heline Mirzakhanian, Department of Psychiatry; Barbara A Cornblatt, Zucker Hillside Hospital; Ricardo Carrión, Zucker Hillside Hospital; Daniel H Mathalon, University of California, San Francisco; Thomas H McGlashan, Yale School of Medicine; Diana O Perkins, The University of North Carolina at Chapel Hill; Aysenil Belger, The University of North Carolina at Chapel Hill; Larry J Seidman, Harvard Medical School; Heidi Thermenos, Harvard Medical School; Ming T Tsuang, Department of Psychiatry; Theo GM van Erp, UCI School of Medicine; Elaine Walker, Emory University; Stephan Hamann, Emory University; Alan Anticevic, Yale School of Medicine; Scott W Woods, Yale School of Medicine; Tyrone D Cannon, Yale University
• Journal Title: Schizophrenia Research
• Volume: Volume 226
• Publisher: Elsevier Inc | 2020-12-01, Pages 30-37
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1016/j.schres.2019.01.017
• Subjects: Health Sciences, Radiology; Health Sciences, Mental Health
• Keywords: Brain network; Clinical high risk; Graph theory; Psychosis; Resting state; Brain; Humans; Longitudinal Studies; Magnetic Resonance Imaging; Psychotic Disorders; United States

Abstract

Mounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, may be implicated in the progression to full psychosis.