Abstract #1841

Gray Matter Network Organization in Psychotic Disorders

Wenjing Zhang¹, Du Lei¹, Brett Clementz², Carol Tamminga³, Matcheri Keshavan⁴, Sarah Keedy⁵, Godfrey Pearlson⁶, Elliot Gershon⁵, Jeffrey Bishop⁷, Jieke Liu¹, Qiyong Gong¹, John Sweeney⁸, and Su Lui¹

¹Huaxi MR Research Center (HMRRC), Department of Radiology, West China Hospital of Sichuan University, Chengdu, China, ²Department of Psychology, University of Georgia, Athens, GA, United States, ³Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States, ⁴Department of Psychiatry, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, United States, ⁵Department of Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, United States, ⁶Department of Psychiatry, School of Medicine, Yale University, New Haven, CT, United States, ⁷Department of Experimental and Clinical Pharmacology, College of Pharmacy, University of Minnesota, Minneapolis, MN, United States, ⁸Department of Psychiatry, University of Cincinnati, Cincinnati, OH, United States

Recently, new approaches have been developed using graph theory to identify deficits in gray matter networks at individual level. In the current study, by investigating single-subject graphs based on gray matter morphology to define neuroanatomic networks in a large group of individuals across psychotic disorders (n=330), we observed disrupted network organizations associated with superior temporal and prefrontal regions within the gray matter networks in patients, which were also negatively associated with severity of psychotic symptoms. These findings showed the utility of graph theory based measures of neuroanatomic network organization to extend our understanding of the neurobiology underlying psychotic disorders.

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