Abstract

Neurobiological abnormalities associated with psychiatric disorders do not map well to existing diagnostic categories. High co-morbidity suggests dimensional circuit-level abnormalities that cross diagnoses. Here we seek to identify brain-based dimensions of psychopathology using sparse canonical correlation analysis in a sample of 663 youths. This analysis reveals correlated patterns of functional connectivity and psychiatric symptoms. We find that four dimensions of psychopathology – mood, psychosis, fear, and externalizing behavior – are associated (r = 0.68–0.71) with distinct patterns of connectivity. Loss of network segregation between the default mode network and executive networks emerges as a common feature across all dimensions. Connectivity linked to mood and psychosis becomes more prominent with development, and sex differences are present for connectivity related to mood and fear. Critically, findings largely replicate in an independent dataset (n = 336). These results delineate connectivity-guided dimensions of psychopathology that cross clinical diagnostic categories, which could serve as a foundation for developing network-based biomarkers in psychiatry.

Details

Title
Linked dimensions of psychopathology and connectivity in functional brain networks
Author
Xia, Cedric Huchuan 1 ; Ma, Zongming 2 ; Ciric, Rastko 1 ; Gu, Shi 3 ; Betzel, Richard F 4 ; Kaczkurkin, Antonia N 1 ; Calkins, Monica E 1 ; Cook, Philip A 5 ; Angel García de la Garza 1 ; Vandekar, Simon N 6 ; Cui, Zaixu 1 ; Moore, Tyler M 1 ; Roalf, David R 1 ; Ruparel, Kosha 1 ; Wolf, Daniel H 1 ; Davatzikos, Christos 5 ; Gur, Ruben C 7 ; Gur, Raquel E 7 ; Shinohara, Russell T 6 ; Bassett, Danielle S 8   VIAFID ORCID Logo  ; Satterthwaite, Theodore D 1   VIAFID ORCID Logo 

1  Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 
2  Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA 
3  Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA; Department of Computer Science and Engineering, University of Electronic Science and Technology, Chengdu, Sichuan, China 
4  Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA 
5  Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 
6  Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 
7  Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA 
8  Department of Bioengineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA; Department of Electrical and Systems Engineering, School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, USA 
Pages
1-14
Publication year
2018
Publication date
Aug 2018
Publisher
Nature Publishing Group
e-ISSN
20411723
Source type
Scholarly Journal
Language of publication
English
DOI
https://doi.org/10.1038/s41467-018-05317-y
ProQuest document ID
2081521126
Copyright
© 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.