Psychotic Symptom, Mood, and Cognition-associated Multimodal MRI Reveal Shared Links to the Salience Network Within the Psychosis Spectrum Disorders

Author:

Liang Chuang1,Pearlson Godfrey2,Bustillo Juan3,Kochunov Peter4,Turner Jessica A56ORCID,Wen Xuyun1,Jiang Rongtao2ORCID,Fu Zening6,Zhang Xiao7,Li Kaicheng8,Xu Xijia9,Zhang Daoqiang1,Qi Shile1ORCID,Calhoun Vince D5610

Affiliation:

1. Department of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics , Nanjing , China

2. Department of Psychiatry and Neuroscience, Yale School of Medicine , New Haven, CT , USA

3. Departments of Neurosciences and Psychiatry and Behavioral Sciences, University of New Mexico , Albuquerque, NM , USA

4. Department of Psychiatry, University of Maryland School of Medicine , Baltimore, MD , USA

5. Department of Psychology, Georgia State University , Atlanta, GA , USA

6. Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS) Georgia State University, Georgia Institute of Technology, Emory University , Atlanta, GA , USA

7. Department of Psychiatry, Peking University Sixth Hospital/Institute of Mental Health , Beijing , China

8. Department of Radiology, The Second Affiliated Hospital of Zhejiang University School of Medicine , Hangzhou , China

9. Department of Psychiatry, Affiliated Nanjing Brain Hospital, Nanjing Medical University , Nanjing , China

10. Department of Electrical and Computer Engineering, Georgia Tech University , Atlanta, GA , USA

Abstract

Abstract Schizophrenia (SZ), schizoaffective disorder (SAD), and psychotic bipolar disorder share substantial overlap in clinical phenotypes, associated brain abnormalities and risk genes, making reliable diagnosis among the three illness challenging, especially in the absence of distinguishing biomarkers. This investigation aims to identify multimodal brain networks related to psychotic symptom, mood, and cognition through reference-guided fusion to discriminate among SZ, SAD, and BP. Psychotic symptom, mood, and cognition were used as references to supervise functional and structural magnetic resonance imaging (MRI) fusion to identify multimodal brain networks for SZ, SAD, and BP individually. These features were then used to assess the ability in discriminating among SZ, SAD, and BP. We observed shared links to functional and structural covariation in prefrontal, medial temporal, anterior cingulate, and insular cortices among SZ, SAD, and BP, although they were linked with different clinical domains. The salience (SAN), default mode (DMN), and fronto-limbic (FLN) networks were the three identified multimodal MRI features within the psychosis spectrum disorders from psychotic symptom, mood, and cognition associations. In addition, using these networks, we can classify patients and controls and distinguish among SZ, SAD, and BP, including their first-degree relatives. The identified multimodal SAN may be informative regarding neural mechanisms of comorbidity for psychosis spectrum disorders, along with DMN and FLN may serve as potential biomarkers in discriminating among SZ, SAD, and BP, which may help investigators better understand the underlying mechanisms of psychotic comorbidity from three different disorders via a multimodal neuroimaging perspective.

Funder

Natural Science Foundation of Jiangsu Province

National Natural Science Foundation of China

National Key Research and Development Program of China

National Institutes of Health

National Science Foundation

Publisher

Oxford University Press (OUP)

Subject

Psychiatry and Mental health

Reference74 articles.

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