Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

Jing Sui; Shile Qi; Theo G M van Erp; Juan Bustillo; Rongtao Jiang; Dongdong Lin; Jessica A Turner; Eswar Damaraju; Andrew R Mayer; Yue Cui; Zening Fu; Yuhui Du; Jiayu Chen; Steven G Potkin; Adrian Preda; Daniel H Mathalon; Judith M Ford; James Voyvodic; Bryon A Mueller; Aysenil Belger; Sarah C McEwen; Daniel S O'Leary; Agnes McMahon; Tianzi Jiang; Vince D Calhoun

doi:10.1038/s41467-018-05432-w

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Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

Journal article

Open access

Peer reviewed

Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion

Jing Sui, Shile Qi, Theo G M van Erp, Juan Bustillo, Rongtao Jiang, Dongdong Lin, Jessica A Turner, Eswar Damaraju, Andrew R Mayer, Yue Cui, …

Nature communications, Vol.9(1), 3028

08/02/2018

DOI: 10.1038/s41467-018-05432-w

PMCID: PMC6072778

PMID: 30072715

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Abstract

Cognitive impairment is a feature of many psychiatric diseases, including schizophrenia. Here we aim to identify multimodal biomarkers for quantifying and predicting cognitive performance in individuals with schizophrenia and healthy controls. A supervised learning strategy is used to guide three-way multimodal magnetic resonance imaging (MRI) fusion in two independent cohorts including both healthy individuals and individuals with schizophrenia using multiple cognitive domain scores. Results highlight the salience network (gray matter, GM), corpus callosum (fractional anisotropy, FA), central executive and default-mode networks (fractional amplitude of low-frequency fluctuation, fALFF) as modality-specific biomarkers of generalized cognition. FALFF features are found to be more sensitive to cognitive domain differences, while the salience network in GM and corpus callosum in FA are highly consistent and predictive of multiple cognitive domains. These modality-specific brain regions define-in three separate cohorts-promising co-varying multimodal signatures that can be used as predictors of multi-domain cognition.

Magnetic Resonance Imaging

Biomarkers - metabolism

Schizophrenia - physiopathology

Humans

Brain Mapping

Adult

Female

Male

Cognition

Schizophrenia - diagnostic imaging

Nerve Net - physiopathology

Cohort Studies

Details

Title: Subtitle: Multimodal neuromarkers in schizophrenia via cognition-guided MRI fusion
Creators: Jing Sui - CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China. jing.sui@nlpr.ia.ac.cn
Shile Qi - University of Chinese Academy of Sciences, 100049, Beijing, China
Theo G M van Erp - Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, 92697, USA
Juan Bustillo - Department of Psychiatry, University of New Mexico, Albuquerque, NM, 87131, USA
Rongtao Jiang - University of Chinese Academy of Sciences, 100049, Beijing, China
Dongdong Lin - The Mind Research Network, Albuquerque, NM, 87106, USA
Jessica A Turner - Department of Psychology and Neuroscience, Georgia State University, Atlanta, GA, 30302, USA
Eswar Damaraju - The Mind Research Network, Albuquerque, NM, 87106, USA
Andrew R Mayer - Department of Psychiatry, University of New Mexico, Albuquerque, NM, 87131, USA
Yue Cui - Brainnetome Center and National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
Zening Fu - The Mind Research Network, Albuquerque, NM, 87106, USA
Yuhui Du - The Mind Research Network, Albuquerque, NM, 87106, USA
Jiayu Chen - The Mind Research Network, Albuquerque, NM, 87106, USA
Steven G Potkin - Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, 92697, USA
Adrian Preda - Department of Psychiatry and Human Behavior, University of California, Irvine, Irvine, CA, 92697, USA
Daniel H Mathalon - San Francisco VA Medical Center, San Francisco, CA, 94143, USA
Judith M Ford - San Francisco VA Medical Center, San Francisco, CA, 94143, USA
James Voyvodic - Department of Radiology, Brain Imaging and Analysis Center, Duke University, Durham, NC, 27710, USA
Bryon A Mueller - Department of Psychiatry, University of Minnesota, Minneapolis, MN, 55454, USA
Aysenil Belger - Department of Psychiatry, University of North Carolina School of Medicine, Chapel Hill, NC, 27599, USA
Sarah C McEwen - Department of Psychiatry, University of California, San Diego, CA, 92093, USA
Daniel S O'Leary - Department of Psychiatry, University of Iowa Carver College of Medicine, Iowa, IA, 52242, USA
Agnes McMahon - USC Stevens Neuroimaging and Informatics Institute, University of Southern California, San Diego, CA, 90033, USA
Tianzi Jiang - CAS Center for Excellence in Brain Science and Intelligence Technology, Institute of Automation, Chinese Academy of Sciences, 100190, Beijing, China
Vince D Calhoun - Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, 87131, USA. vcalhoun@mrn.org
Resource Type: Journal article
Publication Details: Nature communications, Vol.9(1), 3028
DOI: 10.1038/s41467-018-05432-w
PMID: 30072715
PMCID: PMC6072778
NLM abbreviation: Nat Commun
ISSN: 2041-1723
eISSN: 2041-1723
Publisher: England
Grant note: K01 MH099431 / NIMH NIH HHS R01 EB006841 / NIBIB NIH HHS
Language: English
Date published: 08/02/2018
Academic Unit: Psychiatry
Record Identifier: 9984004076202771

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