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Examining the association between posttraumatic stress disorder and disruptions in cortical networks identified using data-driven methods.

Authors :
Yang J
Huggins AA
Sun D
Baird CL
Haswell CC
Frijling JL
Olff M
van Zuiden M
Koch SBJ
Nawijn L
Veltman DJ
Suarez-Jimenez B
Zhu X
Neria Y
Hudson AR
Mueller SC
Baker JT
Lebois LAM
Kaufman ML
Qi R
Lu GM
Říha P
Rektor I
Dennis EL
Ching CRK
Thomopoulos SI
Salminen LE
Jahanshad N
Thompson PM
Stein DJ
Koopowitz SM
Ipser JC
Seedat S
du Plessis S
van den Heuvel LL
Wang L
Zhu Y
Li G
Sierk A
Manthey A
Walter H
Daniels JK
Schmahl C
Herzog JI
Liberzon I
King A
Angstadt M
Davenport ND
Sponheim SR
Disner SG
Straube T
Hofmann D
Grupe DW
Nitschke JB
Davidson RJ
Larson CL
deRoon-Cassini TA
Blackford JU
Olatunji BO
Gordon EM
May G
Nelson SM
Abdallah CG
Levy I
Harpaz-Rotem I
Krystal JH
Morey RA
Sotiras A
Source :
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology [Neuropsychopharmacology] 2024 Feb; Vol. 49 (3), pp. 609-619. Date of Electronic Publication: 2023 Nov 28.
Publication Year :
2024

Abstract

Posttraumatic stress disorder (PTSD) is associated with lower cortical thickness (CT) in prefrontal, cingulate, and insular cortices in diverse trauma-affected samples. However, some studies have failed to detect differences between PTSD patients and healthy controls or reported that PTSD is associated with greater CT. Using data-driven dimensionality reduction, we sought to conduct a well-powered study to identify vulnerable networks without regard to neuroanatomic boundaries. Moreover, this approach enabled us to avoid the excessive burden of multiple comparison correction that plagues vertex-wise methods. We derived structural covariance networks (SCNs) by applying non-negative matrix factorization (NMF) to CT data from 961 PTSD patients and 1124 trauma-exposed controls without PTSD. We used regression analyses to investigate associations between CT within SCNs and PTSD diagnosis (with and without accounting for the potential confounding effect of trauma type) and symptom severity in the full sample. We performed additional regression analyses in subsets of the data to examine associations between SCNs and comorbid depression, childhood trauma severity, and alcohol abuse. NMF identified 20 unbiased SCNs, which aligned closely with functionally defined brain networks. PTSD diagnosis was most strongly associated with diminished CT in SCNs that encompassed the bilateral superior frontal cortex, motor cortex, insular cortex, orbitofrontal cortex, medial occipital cortex, anterior cingulate cortex, and posterior cingulate cortex. CT in these networks was significantly negatively correlated with PTSD symptom severity. Collectively, these findings suggest that PTSD diagnosis is associated with widespread reductions in CT, particularly within prefrontal regulatory regions and broader emotion and sensory processing cortical regions.<br /> (© 2023. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Details

Language :
English
ISSN :
1740-634X
Volume :
49
Issue :
3
Database :
MEDLINE
Journal :
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
Publication Type :
Academic Journal
Accession number :
38017161
Full Text :
https://doi.org/10.1038/s41386-023-01763-5