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

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Preprint
en
2021

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

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0 Files

en
2021
DOI: 10.1101/2021.03.13.432212

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Dan Joseph Stein
Dan Joseph Stein

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Gopalkumar Rakesh
Mark W. Logue
Emily K. Clarke‐Rubright
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Abstract

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 subjects’ data from 29 cohorts in five countries (n=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 (≤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 a node’s 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.

How to cite this publication

Gopalkumar Rakesh, Mark W. Logue, Emily K. Clarke‐Rubright, Erin N. O’Leary, Courtney C. Haswell, Hong Xie, Paul M. Thompson, Emily L. Dennis, Neda Jahanshad, Saskia B.J. Koch, Jessie L. Frijling, Laura Nawijn, Miranda Olff, Mirjam van Zuiden, Faisal Rashid, Xi Zhu, Michael D. De Bellis, Judith K. Daniels, Anika Sierk, Antje Manthey, Jennifer S. Stevens, Tanja Jovanović, Murray B. Stein, Martha E. Shenton, Steven J.A. van de Werff, Nic J.A. van de Wee, Robert Vermeiren, Christian Schmahl, Julia Herzog, Milissa L. Kaufman, Lauren K. O’Connor, Lauren A. M. Lebois, Justin T. Baker, Staci A. Gruber, Jonathan D. Wolff, Erika J. Wolf, Sherry R. Wintemitz, A. Gönenç, Kerry J. Ressler, David Hofmann, Richard A. Bryant, Mayuresh S. Korgaonkar, Elpiniki Andrew, Li Wang, Ye Zhu, Gen Li, Dan Joseph Stein, Jonathan Ipser, Sheri‐Michelle Koopowitz, Sven C. Mueller, Anna R. Hudson, Luan Phan, Bobak Hosseini, Kevin Angstadt, Anthony P. King, Marijo Tamburrino, Brynn C. 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, Scott M. Nelson, Geoffrey May, Lee A. Baugh, Gina L. Forster, Raluca M. Simons, Jeffrey S. Simons, Vincent A. Magnotta, Kelene A. Fercho, Adi Maron‐Katz, Stefan S. du Plessis, Seth G. Disner, Nicholas D. Davenport, Sophia I. Thomopoulos, Benjamin Suarez‐Jimenez, Tor D. Wager, Yuval Neria, Negar Fani, Henrik Walter, Inga K. Koerte, Jessica Bomyea, Kyle Choi, Alan N. Simmons, Elizabeth A. Olson, Isabelle M. Rosso, Thomas Straube, Theo G.M. van Erp, Tian Chen, Andrew S. Cotton, John T. Wall, Richard J. Davidson, Terri A. deRoon‐Cassini, Jacklynn M. Fitzgerald, Christine L. Larson, Evan M. Gordon (2021). Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study. , DOI: https://doi.org/10.1101/2021.03.13.432212.

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Publication Details

Type

Preprint

Year

2021

Authors

100

Datasets

0

Total Files

0

Language

en

DOI

https://doi.org/10.1101/2021.03.13.432212

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