Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

Gopalkumar Rakesh; Delin Sun; Mark W Logue; Emily Clarke-Rubright; Brian M. O'Leary; Courtney Haswell; Hong Xie; Paul Thompson; Emily Dennis; Neda Jahanshad; Saskia Koch; Jessie Frijling; Laura Nawijn; Miranda Olff; Mirjam van Zuiden; Faisal Rashid; Xi Zhu; Michael De Bellis; Judith K Daniels; Anika Sierk; Antje Manthey; Jennifer S Stevens; Tanja Jovanovic; Murray B Stein; Martha Shenton; Steven JA van der Werff; Nic JA van der Wee; Robert RJM Vermeiren; Christian Schmahl; Julia Herzog; Milissa L Kaufman; Lauren O'Connor; Lauren A.M Lebois; Justin T Baker; Staci A Gruber; Jonathan D Wolff; Erika J Wolf; Sherry Winternitz; Atilla Gonenc; Kerry J Ressler; David Hofmann; Richard A Bryant; Mayuresh Korgaonkar; Elpiniki Andrew; Li Wang; Ye Zhu; LI Gen; Dan J. Stein; Jonathan Ipser; Sheri Koopowitz; Sven Mueller; Anna Hudson; Luan Phan; Bobak Hosseini; K. Mike Angstadt; Anthony King; Marijo Tamburrino; Brynn P. Skilliter; Elbert Geuze; Sanne J.H. van Rooij; Tim Varkevisser; Katie A. McLaughlin; Margaret A. Sheridan; Matthew Peverill; Kelly Sambrook; Dick J. Veltman; Kathleen Thomaes; Steven Nelson; Geoffrey May; Lee Baugh; Gina Forster; Raluca Simons; Jeffrey Simons; Vincent Magnotta; Kelene A. Fercho; Adi Maron-Katz; Stefan du Plessis; Seth Disner; Nicholas Davenport; Sophia I Thomopoulos; Benjamin Suarez-Jimenez; Tor D. Wager; Yuval Neria; Negar Fani; Henrik Walter; Inga Koerte; Jessica Bomyea; Kyle Choi; Alan N. Simmons; Elizabeth Olson; Isabelle Rosso; Thomas Straube; Theo GM Van Erp; Tian Chen; Andrew S. Cotton; John Wall; Richard J Davidson; Terri deRoon-Cassini; Jacklynn Fitzgerald; Christine Larson; Evan Gordon; Dan Grupe; Scott R. Sponheim; Amit Etkin; Soraya Seedat; Ilan Harpaz-Rotem; Kristen Wrocklage; Chadi Abdallah; John H Krystal; Ifat Levy; Hassaan Gomaa; Mary Agnes B. McMahon; Israel Liberzon; Xin Wang; Rajendra A. Morey

doi:10.1101/2021.03.13.432212

Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

Gopalkumar Rakesh, Delin Sun, Mark W Logue, Emily Clarke-Rubright, Brian M. O'Leary, Courtney Haswell, Hong Xie, Paul Thompson, Emily Dennis, Neda Jahanshad, Saskia Koch, Jessie Frijling, Laura Nawijn, Miranda Olff, Mirjam van Zuiden, Faisal Rashid, Xi Zhu, Michael De Bellis, Judith K Daniels, Anika SierkAntje Manthey, Jennifer S Stevens, Tanja Jovanovic, Murray B Stein, Martha Shenton, Steven JA van der Werff, Nic JA van der Wee, Robert RJM Vermeiren, Christian Schmahl, Julia Herzog, Milissa L Kaufman, Lauren O'Connor, Lauren A.M Lebois, Justin T Baker, Staci A Gruber, Jonathan D Wolff, Erika J Wolf, Sherry Winternitz, Atilla Gonenc, Kerry J Ressler, David Hofmann, Richard A Bryant, Mayuresh Korgaonkar, Elpiniki Andrew, Li Wang, Ye Zhu, LI Gen, Dan J. Stein, Jonathan Ipser, Sheri Koopowitz, Sven Mueller, Anna Hudson, Luan Phan, Bobak Hosseini, K. Mike Angstadt, Anthony King, Marijo Tamburrino, Brynn P. Skilliter, Elbert Geuze, Sanne J.H. van Rooij, Tim Varkevisser, Katie A. McLaughlin, Margaret A. Sheridan, Matthew Peverill, Kelly Sambrook, Dick J. Veltman, Kathleen Thomaes, Steven Nelson, Geoffrey May, Lee Baugh, Gina Forster, Raluca Simons, Jeffrey Simons, Vincent Magnotta, Kelene A. Fercho, Adi Maron-Katz, Stefan du Plessis, Seth Disner, Nicholas Davenport, Sophia I Thomopoulos, Benjamin Suarez-Jimenez, Tor D. Wager, Yuval Neria, Negar Fani, Henrik Walter, Inga Koerte, Jessica Bomyea, Kyle Choi, Alan N. Simmons, Elizabeth Olson, Isabelle Rosso, Thomas Straube, Theo GM Van Erp, Tian Chen, Andrew S. Cotton, John Wall, Richard J Davidson, Terri deRoon-Cassini, Jacklynn Fitzgerald, Christine Larson, Evan Gordon, Dan Grupe, Scott R. Sponheim, Amit Etkin, Soraya Seedat, Ilan Harpaz-Rotem, Kristen Wrocklage, Chadi Abdallah, John H Krystal, Ifat Levy, Hassaan Gomaa, Mary Agnes B. McMahon, Israel Liberzon, Xin Wang, Rajendra A. Morey

Research output: Working paper › Preprint

Abstract

Introduction - Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subject data from 29 cohorts in five countries (3439). Methods - Using Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. Results - Notable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. Conclusion - Unlike previous studies with smaller sample sizes (less than 318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into nodal relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

Original language	English
DOIs	https://doi.org/10.1101/2021.03.13.432212
State	Published - Mar 16 2021

Bibliographical note

Authors retain copyright and choose from several distribution/reuse options under which to make the article available (CC BY, CC BY-NC, CC BY-ND, CC BY-NC-ND, CC0, or no reuse).

Keywords

neuroscience

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10.1101/2021.03.13.432212

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Rakesh, G., Sun, D., Logue, M. W., Clarke-Rubright, E., O'Leary, B. M., Haswell, C., Xie, H., Thompson, P., Dennis, E., Jahanshad, N., Koch, S., Frijling, J., Nawijn, L., Olff, M., Zuiden, M. V., Rashid, F., Zhu, X., Bellis, M. D., Daniels, J. K., ... Morey, R. A. (2021). Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study. https://doi.org/10.1101/2021.03.13.432212

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title = "Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study",

abstract = "Introduction - Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subject data from 29 cohorts in five countries (3439). Methods - Using Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. Results - Notable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. Conclusion - Unlike previous studies with smaller sample sizes (less than 318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into nodal relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.",

keywords = "neuroscience",

author = "Gopalkumar Rakesh and Delin Sun and Logue, {Mark W} and Emily Clarke-Rubright and O'Leary, {Brian M.} and Courtney Haswell and Hong Xie and Paul Thompson and Emily Dennis and Neda Jahanshad and Saskia Koch and Jessie Frijling and Laura Nawijn and Miranda Olff and Zuiden, {Mirjam van} and Faisal Rashid and Xi Zhu and Bellis, {Michael De} and Daniels, {Judith K} and Anika Sierk and Antje Manthey and Stevens, {Jennifer S} and Tanja Jovanovic and Stein, {Murray B} and Martha Shenton and Werff, {Steven JA van der} and Wee, {Nic JA van der} and Vermeiren, {Robert RJM} and Christian Schmahl and Julia Herzog and Kaufman, {Milissa L} and Lauren O'Connor and Lebois, {Lauren A.M} and Baker, {Justin T} and Gruber, {Staci A} and Wolff, {Jonathan D} and Wolf, {Erika J} and Sherry Winternitz and Atilla Gonenc and Ressler, {Kerry J} and David Hofmann and Bryant, {Richard A} and Mayuresh Korgaonkar and Elpiniki Andrew and Li Wang and Ye Zhu and LI Gen and Stein, {Dan J.} and Jonathan Ipser and Sheri Koopowitz and Sven Mueller and Anna Hudson and Luan Phan and Bobak Hosseini and Angstadt, {K. Mike} and Anthony King and Marijo Tamburrino and Skilliter, {Brynn P.} and Elbert Geuze and Rooij, {Sanne J.H. van} and Tim Varkevisser and McLaughlin, {Katie A.} and Sheridan, {Margaret A.} and Matthew Peverill and Kelly Sambrook and Veltman, {Dick J.} and Kathleen Thomaes and Steven Nelson and Geoffrey May and Lee Baugh and Gina Forster and Raluca Simons and Jeffrey Simons and Vincent Magnotta and Fercho, {Kelene A.} and Adi Maron-Katz and Plessis, {Stefan du} and Seth Disner and Nicholas Davenport and Thomopoulos, {Sophia I} and Benjamin Suarez-Jimenez and Wager, {Tor D.} and Yuval Neria and Negar Fani and Henrik Walter and Inga Koerte and Jessica Bomyea and Kyle Choi and Simmons, {Alan N.} and Elizabeth Olson and Isabelle Rosso and Thomas Straube and Erp, {Theo GM Van} and Tian Chen and Cotton, {Andrew S.} and John Wall and Davidson, {Richard J} and Terri deRoon-Cassini and Jacklynn Fitzgerald and Christine Larson and Evan Gordon and Dan Grupe and Sponheim, {Scott R.} and Amit Etkin and Soraya Seedat and Ilan Harpaz-Rotem and Kristen Wrocklage and Chadi Abdallah and Krystal, {John H} and Ifat Levy and Hassaan Gomaa and McMahon, {Mary Agnes B.} and Israel Liberzon and Xin Wang and Morey, {Rajendra A.}",

note = "Authors retain copyright and choose from several distribution/reuse options under which to make the article available (CC BY, CC BY-NC, CC BY-ND, CC BY-NC-ND, CC0, or no reuse).",

year = "2021",

month = mar,

day = "16",

doi = "10.1101/2021.03.13.432212",

language = "English",

type = "WorkingPaper",

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Rakesh, G, Sun, D, Logue, MW, Clarke-Rubright, E, O'Leary, BM, Haswell, C, Xie, H, Thompson, P, Dennis, E, Jahanshad, N, Koch, S, Frijling, J, Nawijn, L, Olff, M, Zuiden, MV, Rashid, F, Zhu, X, Bellis, MD, Daniels, JK, Sierk, A, Manthey, A, Stevens, JS, Jovanovic, T, Stein, MB, Shenton, M, Werff, SJAVD, Wee, NJAVD, Vermeiren, RRJM, Schmahl, C, Herzog, J, Kaufman, ML, O'Connor, L, Lebois, LAM, Baker, JT, Gruber, SA, Wolff, JD, Wolf, EJ, Winternitz, S, Gonenc, A, Ressler, KJ, Hofmann, D, Bryant, RA, Korgaonkar, M, Andrew, E, Wang, L, Zhu, Y, Gen, LI, Stein, DJ, Ipser, J, Koopowitz, S, Mueller, S, Hudson, A, Phan, L, Hosseini, B, Angstadt, KM, King, A, Tamburrino, M, Skilliter, BP, Geuze, E, Rooij, SJHV, Varkevisser, T, McLaughlin, KA, Sheridan, MA, Peverill, M, Sambrook, K, Veltman, DJ, Thomaes, K, Nelson, S, May, G, Baugh, L, Forster, G, Simons, R, Simons, J, Magnotta, V, Fercho, KA, Maron-Katz, A, Plessis, SD, Disner, S, Davenport, N, Thomopoulos, SI, Suarez-Jimenez, B, Wager, TD, Neria, Y, Fani, N, Walter, H, Koerte, I, Bomyea, J, Choi, K, Simmons, AN, Olson, E, Rosso, I, Straube, T, Erp, TGMV, Chen, T, Cotton, AS, Wall, J, Davidson, RJ, deRoon-Cassini, T, Fitzgerald, J, Larson, C, Gordon, E, Grupe, D, Sponheim, SR, Etkin, A, Seedat, S, Harpaz-Rotem, I, Wrocklage, K, Abdallah, C, Krystal, JH, Levy, I, Gomaa, H, McMahon, MAB, Liberzon, I, Wang, X & Morey, RA 2021 'Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study'. https://doi.org/10.1101/2021.03.13.432212

TY - UNPB

T1 - Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

AU - Rakesh, Gopalkumar

AU - Sun, Delin

AU - Logue, Mark W

AU - Clarke-Rubright, Emily

AU - O'Leary, Brian M.

AU - Haswell, Courtney

AU - Xie, Hong

AU - Thompson, Paul

AU - Dennis, Emily

AU - Jahanshad, Neda

AU - Koch, Saskia

AU - Frijling, Jessie

AU - Nawijn, Laura

AU - Olff, Miranda

AU - Zuiden, Mirjam van

AU - Rashid, Faisal

AU - Zhu, Xi

AU - Bellis, Michael De

AU - Daniels, Judith K

AU - Sierk, Anika

AU - Manthey, Antje

AU - Stevens, Jennifer S

AU - Jovanovic, Tanja

AU - Stein, Murray B

AU - Shenton, Martha

AU - Werff, Steven JA van der

AU - Wee, Nic JA van der

AU - Vermeiren, Robert RJM

AU - Schmahl, Christian

AU - Herzog, Julia

AU - Kaufman, Milissa L

AU - O'Connor, Lauren

AU - Lebois, Lauren A.M

AU - Baker, Justin T

AU - Gruber, Staci A

AU - Wolff, Jonathan D

AU - Wolf, Erika J

AU - Winternitz, Sherry

AU - Gonenc, Atilla

AU - Ressler, Kerry J

AU - Hofmann, David

AU - Bryant, Richard A

AU - Korgaonkar, Mayuresh

AU - Andrew, Elpiniki

AU - Wang, Li

AU - Zhu, Ye

AU - Gen, LI

AU - Stein, Dan J.

AU - Ipser, Jonathan

AU - Koopowitz, Sheri

AU - Mueller, Sven

AU - Hudson, Anna

AU - Phan, Luan

AU - Hosseini, Bobak

AU - Angstadt, K. Mike

AU - King, Anthony

AU - Tamburrino, Marijo

AU - Skilliter, Brynn P.

AU - Geuze, Elbert

AU - Rooij, Sanne J.H. van

AU - Varkevisser, Tim

AU - McLaughlin, Katie A.

AU - Sheridan, Margaret A.

AU - Peverill, Matthew

AU - Sambrook, Kelly

AU - Veltman, Dick J.

AU - Thomaes, Kathleen

AU - Nelson, Steven

AU - May, Geoffrey

AU - Baugh, Lee

AU - Forster, Gina

AU - Simons, Raluca

AU - Simons, Jeffrey

AU - Magnotta, Vincent

AU - Fercho, Kelene A.

AU - Maron-Katz, Adi

AU - Plessis, Stefan du

AU - Disner, Seth

AU - Davenport, Nicholas

AU - Thomopoulos, Sophia I

AU - Suarez-Jimenez, Benjamin

AU - Wager, Tor D.

AU - Neria, Yuval

AU - Fani, Negar

AU - Walter, Henrik

AU - Koerte, Inga

AU - Bomyea, Jessica

AU - Choi, Kyle

AU - Simmons, Alan N.

AU - Olson, Elizabeth

AU - Rosso, Isabelle

AU - Straube, Thomas

AU - Erp, Theo GM Van

AU - Chen, Tian

AU - Cotton, Andrew S.

AU - Wall, John

AU - Davidson, Richard J

AU - deRoon-Cassini, Terri

AU - Fitzgerald, Jacklynn

AU - Larson, Christine

AU - Gordon, Evan

AU - Grupe, Dan

AU - Sponheim, Scott R.

AU - Etkin, Amit

AU - Seedat, Soraya

AU - Harpaz-Rotem, Ilan

AU - Wrocklage, Kristen

AU - Abdallah, Chadi

AU - Krystal, John H

AU - Levy, Ifat

AU - Gomaa, Hassaan

AU - McMahon, Mary Agnes B.

AU - Liberzon, Israel

AU - Wang, Xin

AU - Morey, Rajendra A.

N1 - Authors retain copyright and choose from several distribution/reuse options under which to make the article available (CC BY, CC BY-NC, CC BY-ND, CC BY-NC-ND, CC0, or no reuse).

PY - 2021/3/16

Y1 - 2021/3/16

N2 - Introduction - Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subject data from 29 cohorts in five countries (3439). Methods - Using Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. Results - Notable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. Conclusion - Unlike previous studies with smaller sample sizes (less than 318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into nodal relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

AB - Introduction - Cortical thickness (CT) and surface area (SA) are established biomarkers of brain pathology in posttraumatic stress disorder (PTSD). Structural covariance networks (SCN) constructed from CT and SA may represent developmental associations, or unique interactions between brain regions, possibly influenced by a common causal antecedent. The ENIGMA-PGC PTSD Working Group aggregated PTSD and control subject data from 29 cohorts in five countries (3439). Methods - Using Destrieux Atlas, we built SCNs and compared centrality measures between PTSD subjects and controls. Centrality is a graph theory measure derived using SCN. Results - Notable nodes with higher CT-based centrality in PTSD compared to controls were left fusiform gyrus, left superior temporal gyrus, and right inferior temporal gyrus. We found sex-based centrality differences in bilateral frontal lobe regions, left anterior cingulate, left superior occipital cortex and right ventromedial prefrontal cortex (vmPFC). Comorbid PTSD and MDD showed higher CT-based centrality in the right anterior cingulate gyrus, right parahippocampal gyrus and lower SA-based centrality in left insular gyrus. Conclusion - Unlike previous studies with smaller sample sizes (less than 318), our study found differences in centrality measures using a sample size of 3439 subjects. This is the first cross-sectional study to examine SCN interactions with age, sex, and comorbid MDD. Although limited to group level inferences, centrality measures offer insights into nodal relationship to the entire functional connectome unlike approaches like seed-based connectivity or independent component analysis. Nodes having higher centrality have greater structural or functional connections, lending them invaluable for translational treatments like neuromodulation.

KW - neuroscience

U2 - 10.1101/2021.03.13.432212

DO - 10.1101/2021.03.13.432212

M3 - Preprint

BT - Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

ER -

Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

Abstract

Bibliographical note

Keywords

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