Linked dimensions of psychopathology and connectivity in functional brain networks

Cedric Huchuan Xia; Zongming Ma; Rastko Ciric; Shi Gu; Richard F. Betzel; Antonia N. Kaczkurkin; Monica E. Calkins; Philip A. Cook; Angel García de la Garza; Simon N. Vandekar; Zaixu Cui; Tyler M. Moore; David R. Roalf; Kosha Ruparel; Daniel H. Wolf; Christos Davatzikos; Ruben C. Gur; Raquel E. Gur; Russell T. Shinohara; Danielle S. Bassett; Theodore D. Satterthwaite

doi:10.1038/s41467-018-05317-y

Linked dimensions of psychopathology and connectivity in functional brain networks

Cedric Huchuan Xia, Zongming Ma, Rastko Ciric, Shi Gu, Richard F. Betzel, Antonia N. Kaczkurkin, Monica E. Calkins, Philip A. Cook, Angel García de la Garza, Simon N. Vandekar, Zaixu Cui, Tyler M. Moore, David R. Roalf, Kosha Ruparel, Daniel H. Wolf, Christos Davatzikos, Ruben C. Gur, Raquel E. Gur, Russell T. Shinohara, Danielle S. BassettTheodore D. Satterthwaite

Research output: Contribution to journal › Article › peer-review

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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.

Original language	English (US)
Article number	3003
Journal	Nature communications
Volume	9
Issue number	1
DOIs	https://doi.org/10.1038/s41467-018-05317-y
State	Published - Dec 1 2018
Externally published	Yes

ASJC Scopus subject areas

General
Physics and Astronomy(all)
Chemistry(all)
Biochemistry, Genetics and Molecular Biology(all)

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Xia, C. H., Ma, Z., Ciric, R., Gu, S., Betzel, R. F., Kaczkurkin, A. N., Calkins, M. E., Cook, P. A., García de la Garza, A., Vandekar, S. N., Cui, Z., Moore, T. M., Roalf, D. R., Ruparel, K., Wolf, D. H., Davatzikos, C., Gur, R. C., Gur, R. E., Shinohara, R. T., ... Satterthwaite, T. D. (2018). Linked dimensions of psychopathology and connectivity in functional brain networks. Nature communications, 9(1), Article 3003. https://doi.org/10.1038/s41467-018-05317-y

Xia, CH, Ma, Z, Ciric, R, Gu, S, Betzel, RF, Kaczkurkin, AN, Calkins, ME, Cook, PA, García de la Garza, A, Vandekar, SN, Cui, Z, Moore, TM, Roalf, DR, Ruparel, K, Wolf, DH, Davatzikos, C, Gur, RC, Gur, RE, Shinohara, RT, Bassett, DS & Satterthwaite, TD 2018, 'Linked dimensions of psychopathology and connectivity in functional brain networks', Nature communications, vol. 9, no. 1, 3003. https://doi.org/10.1038/s41467-018-05317-y

@article{4154733d78af4aeca4b820c849006f94,

title = "Linked dimensions of psychopathology and connectivity in functional brain networks",

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.",

author = "Xia, {Cedric Huchuan} and Zongming Ma and Rastko Ciric and Shi Gu and Betzel, {Richard F.} and Kaczkurkin, {Antonia N.} and Calkins, {Monica E.} and Cook, {Philip A.} and {Garc{\'i}a de la Garza}, Angel and Vandekar, {Simon N.} and Zaixu Cui and Moore, {Tyler M.} and Roalf, {David R.} and Kosha Ruparel and Wolf, {Daniel H.} and Christos Davatzikos and Gur, {Ruben C.} and Gur, {Raquel E.} and Shinohara, {Russell T.} and Bassett, {Danielle S.} and Satterthwaite, {Theodore D.}",

note = "Funding Information: Thanks to Chad Jackson for data management and systems support. This study was supported by grants from National Institute of Mental Health: R01MH107703 (T.D.S.), R01MH112847 (R.T.S. & T.D.S.), R21MH106799 (D.S.B. & T.D.S.), R01MH107235 (R.C. G.), R01MH113550 (T.D.S. & D.S.B.), and R01EB022573 (C.D.). The PNC was supported by MH089983 and MH089924. Additional support was provided by P50MH096891 to R.E.G., R01MH101111 to D.H.W., K01MH102609 to D.R.R., K08MH079364 to M.E.C., R01NS085211 to R.T.S., and the Dowshen Program for Neuroscience. Additionally, D.S.B. acknowledges support from the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the ISI Foundation, the Paul Allen Foundation, the Army Research Laboratory (W911NF-10-2-0022), the Army Research Office (Bassett-W911NF-14-1-0679, Grafton-W911NF-16-1-0474, DCIST-W911NF-17-2-0181), the Office of Naval Research, the National Institute of Mental Health (2-R01-DC-009209-11, R01 – MH112847, R01-MH107235, R21-M MH-106799), the National Institute of Child Health and Human Development (1R01HD086888-01), National Institute of Neurological Disorders and Stroke (R01 NS099348), and the National Science Foundation (BCS-1441502, BCS-1430087, NSF PHY-1554488 and BCS-1631550). The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. Publisher Copyright: {\textcopyright} 2018, The Author(s).",

year = "2018",

month = dec,

day = "1",

doi = "10.1038/s41467-018-05317-y",

language = "English (US)",

volume = "9",

journal = "Nature communications",

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TY - JOUR

T1 - Linked dimensions of psychopathology and connectivity in functional brain networks

AU - Xia, Cedric Huchuan

AU - Ma, Zongming

AU - Ciric, Rastko

AU - Gu, Shi

AU - Betzel, Richard F.

AU - Kaczkurkin, Antonia N.

AU - Calkins, Monica E.

AU - Cook, Philip A.

AU - García de la Garza, Angel

AU - Vandekar, Simon N.

AU - Cui, Zaixu

AU - Moore, Tyler M.

AU - Roalf, David R.

AU - Ruparel, Kosha

AU - Wolf, Daniel H.

AU - Davatzikos, Christos

AU - Gur, Ruben C.

AU - Gur, Raquel E.

AU - Shinohara, Russell T.

AU - Bassett, Danielle S.

AU - Satterthwaite, Theodore D.

N1 - Funding Information: Thanks to Chad Jackson for data management and systems support. This study was supported by grants from National Institute of Mental Health: R01MH107703 (T.D.S.), R01MH112847 (R.T.S. & T.D.S.), R21MH106799 (D.S.B. & T.D.S.), R01MH107235 (R.C. G.), R01MH113550 (T.D.S. & D.S.B.), and R01EB022573 (C.D.). The PNC was supported by MH089983 and MH089924. Additional support was provided by P50MH096891 to R.E.G., R01MH101111 to D.H.W., K01MH102609 to D.R.R., K08MH079364 to M.E.C., R01NS085211 to R.T.S., and the Dowshen Program for Neuroscience. Additionally, D.S.B. acknowledges support from the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the ISI Foundation, the Paul Allen Foundation, the Army Research Laboratory (W911NF-10-2-0022), the Army Research Office (Bassett-W911NF-14-1-0679, Grafton-W911NF-16-1-0474, DCIST-W911NF-17-2-0181), the Office of Naval Research, the National Institute of Mental Health (2-R01-DC-009209-11, R01 – MH112847, R01-MH107235, R21-M MH-106799), the National Institute of Child Health and Human Development (1R01HD086888-01), National Institute of Neurological Disorders and Stroke (R01 NS099348), and the National Science Foundation (BCS-1441502, BCS-1430087, NSF PHY-1554488 and BCS-1631550). The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies. Publisher Copyright: © 2018, The Author(s).

PY - 2018/12/1

Y1 - 2018/12/1

N2 - 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.

AB - 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.

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ER -

Linked dimensions of psychopathology and connectivity in functional brain networks

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