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Reproducible abnormalities of functional gradient reliably predict clinical and cognitive symptoms in schizophrenia

Meng Wang, Ang Li, Yong Liu, Hao Yan, Yuqing Sun, Ming Song, Jun Chen, Yunchun Chen, Huaning Wang, Hua Guo, Ping Wan, Luxian Lv, Yongfeng Yang, Peng Li, Lin Lu, Jun Yan, Huiling Wang, Hongxing Zhang, Dai Zhang, View ORCID ProfileTianzi Jiang, Bing Liu
doi: https://doi.org/10.1101/2020.11.24.395251
Meng Wang
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
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Ang Li
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
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Yong Liu
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
3CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
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Hao Yan
4Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
5Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
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Yuqing Sun
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
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Ming Song
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
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Jun Chen
6Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China
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Yunchun Chen
7Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an 710032, China
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Huaning Wang
7Department of Psychiatry, Xijing Hospital, The Fourth Military Medical University, Xi’an 710032, China
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Hua Guo
8Zhumadian Psychiatric Hospital, Zhumadian 463000, China
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Ping Wan
8Zhumadian Psychiatric Hospital, Zhumadian 463000, China
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Luxian Lv
9Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China
10Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China
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Yongfeng Yang
9Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China
10Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China
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Peng Li
4Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
5Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
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Lin Lu
4Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
5Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
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Jun Yan
4Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
5Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
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Huiling Wang
6Department of Radiology, Renmin Hospital of Wuhan University, Wuhan 430060, China
11Department of Psychiatry, Renmin Hospital of Wuhan University, Wuhan 430060, China
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Hongxing Zhang
9Department of Psychiatry, Henan Mental Hospital, The Second Affiliated Hospital of Xinxiang Medical University, Xinxiang 453002, China
10Henan Key Lab of Biological Psychiatry, Xinxiang Medical University, Xinxiang 453002, China
12Department of Psychology, Xinxiang Medical University, Xinxiang 453002, China
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Dai Zhang
4Peking University Sixth Hospital/Institute of Mental Health, Beijing 100191, China
5Key Laboratory of Mental Health, Ministry of Health (Peking University), Beijing 100191, China
13Center for Life Sciences/PKU-IDG/McGovern Institute for Brain Research, Peking University, Beijing 100871, China
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Tianzi Jiang
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
3CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
14Key Laboratory for NeuroInformation of Ministry of Education, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu 610054, China
15Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
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  • ORCID record for Tianzi Jiang
Bing Liu
1Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China
3CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
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  • For correspondence: bliu@nlpr.ia.ac.cn
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Abstract

Background Schizophrenia (SZ) typically manifests heterogeneous phenotypes involving positive, negative and cognitive symptoms. However, the underlying neural mechanisms of these symptoms keep unclear. Functional gradient is a fascinating measure to characterize continuous, hierarchical organization of brain.

Methods We aimed to investigate whether reproducible disruptions of functional gradient existed in SZ compared to normal controls (NC), and these abnormalities were associated with severity of clinical and cognitive symptoms in SZ. All analyses were implemented in two independent large-sample multi-site datasets (discovery dataset, 400 SZ and 336 NC; replication dataset, 279 SZ and 262 NC). First, functional gradient across cerebral cortex was calculated in each subject. Second, vertex-wise comparisons of cortical gradient between SZ and NC groups were performed to identify abnormalities in SZ. Meanwhile, reproducible and robustness analyses were implemented to validate these abnormalities. Finally, regression analyses were performed using generalized additive models to link these abnormalities to severity of clinical and cognitive symptoms in SZ.

Results We found an abnormal gradient map in SZ in the discovery dataset, which was reproducible in the replication dataset. The abnormal gradient pattern was also robust when performing methodological alternatives and control analyses. Further, these reproducible abnormalities can reliably predict symptoms of clinical and cognitive domains across the two independent datasets.

Conclusion These findings demonstrated that alterations in functional gradient can provide a reliable signature of SZ, characterizing the heterogenous symptoms of clinical or cognitive domains, and may be further investigated to understand the neurobiological mechanisms of these symptoms.

Impact Statement In our study, using functional gradient measure and statistical learning technology and two independent multi-site case-control resting-state fMRI datasets (discovery dataset: 736 subjects; replication dataset: 541 subjects), we comprehensively investigated functional hierarchical organization in the cerebral cortex of SZ and its association with interindividual severity of symptoms. We found reproducible and robust abnormalities of functional gradient existed in SZ, which provided a reliable signature to characterize negative and general psychopathology symptoms, as well as cognitive deficits. Our findings can provide new insights to understand the neurobiological mechanisms of clinical and cognitive symptoms in SZ.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted November 24, 2020.
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Reproducible abnormalities of functional gradient reliably predict clinical and cognitive symptoms in schizophrenia
Meng Wang, Ang Li, Yong Liu, Hao Yan, Yuqing Sun, Ming Song, Jun Chen, Yunchun Chen, Huaning Wang, Hua Guo, Ping Wan, Luxian Lv, Yongfeng Yang, Peng Li, Lin Lu, Jun Yan, Huiling Wang, Hongxing Zhang, Dai Zhang, Tianzi Jiang, Bing Liu
bioRxiv 2020.11.24.395251; doi: https://doi.org/10.1101/2020.11.24.395251
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Reproducible abnormalities of functional gradient reliably predict clinical and cognitive symptoms in schizophrenia
Meng Wang, Ang Li, Yong Liu, Hao Yan, Yuqing Sun, Ming Song, Jun Chen, Yunchun Chen, Huaning Wang, Hua Guo, Ping Wan, Luxian Lv, Yongfeng Yang, Peng Li, Lin Lu, Jun Yan, Huiling Wang, Hongxing Zhang, Dai Zhang, Tianzi Jiang, Bing Liu
bioRxiv 2020.11.24.395251; doi: https://doi.org/10.1101/2020.11.24.395251

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