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1. Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup

Author

Huggins, Ashley A, Baird, C Lexi, Briggs, Melvin, Laskowitz, Sarah, Hussain, Ahmed, Fouda, Samar, Haswell, Courtney, Sun, Delin, Salminen, Lauren E, Jahanshad, Neda, Thomopoulos, Sophia I, Veltman, Dick J, Frijling, Jessie L, Olff, Miranda, van Zuiden, Mirjam, Koch, Saskia BJ, Nawjin, Laura, Wang, Li, Zhu, Ye, Li, Gen, Stein, Dan J, Ipser, Jonathan, Seedat, Soraya, du Plessis, Stefan, van den Heuvel, Leigh L, Suarez-Jimenez, Benjamin, Zhu, Xi, Kim, Yoojean, He, Xiaofu, Zilcha-Mano, Sigal, Lazarov, Amit, Neria, Yuval, Stevens, Jennifer S, Ressler, Kerry J, Jovanovic, Tanja, van Rooij, Sanne JH, Fani, Negar, Hudson, Anna R, Mueller, Sven C, Sierk, Anika, Manthey, Antje, Walter, Henrik, Daniels, Judith K, Schmahl, Christian, Herzog, Julia I, Říha, Pavel, Rektor, Ivan, Lebois, Lauren AM, Kaufman, Milissa L, Olson, Elizabeth A, Baker, Justin T, Rosso, Isabelle M, King, Anthony P, Liberzon, Isreal, Angstadt, Mike, Davenport, Nicholas D, Sponheim, Scott R, Disner, Seth G, Straube, Thomas, Hofmann, David, Qi, Rongfeng, Lu, Guang Ming, Baugh, Lee A, Forster, Gina L, Simons, Raluca M, Simons, Jeffrey S, Magnotta, Vincent A, Fercho, Kelene A, Maron-Katz, Adi, Etkin, Amit, Cotton, Andrew S, O’Leary, Erin N, Xie, Hong, Wang, Xin, Quidé, Yann, El-Hage, Wissam, Lissek, Shmuel, Berg, Hannah, Bruce, Steven, Cisler, Josh, Ross, Marisa, Herringa, Ryan J, Grupe, Daniel W, Nitschke, Jack B, Davidson, Richard J, Larson, Christine L, deRoon-Cassini, Terri A, Tomas, Carissa W, Fitzgerald, Jacklynn M, Blackford, Jennifer Urbano, Olatunji, Bunmi O, Kremen, William S, Lyons, Michael J, Franz, Carol E, Gordon, Evan M, May, Geoffrey, Nelson, Steven M, Abdallah, Chadi G, Levy, Ifat, and Harpaz-Rotem, Ilan

Subjects
Clinical and Health Psychology, Psychology, Post-Traumatic Stress Disorder (PTSD), Mental Illness, Behavioral and Social Science, Anxiety Disorders, Mental Health, Brain Disorders, Mind and Body, Neurosciences, Mental health, Humans, Stress Disorders, Post-Traumatic, Cerebellum, Female, Male, Adult, Magnetic Resonance Imaging, Middle Aged, White Matter, Gray Matter, Organ Size, Deep Learning, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p-FDR

Published
2024

2. Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

Author

Zhu, Xi, Kim, Yoojean, Ravid, Orren, He, Xiaofu, Suarez-Jimenez, Benjamin, Zilcha-Mano, Sigal, Lazarov, Amit, Lee, Seonjoo, Abdallah, Chadi, Angstadt, Michael, Averill, Christopher, Baird, C, Baugh, Lee, Blackford, Jennifer, Bomyea, Jessica, Bruce, Steven, Bryant, Richard, Cao, Zhihong, Choi, Kyle, Cisler, Josh, Cotton, Andrew, Daniels, Judith, Davenport, Nicholas, Davidson, Richard, DeBellis, Michael, Dennis, Emily, Densmore, Maria, deRoon-Cassini, Terri, Disner, Seth, Hage, Wissam, Etkin, Amit, Fani, Negar, Fercho, Kelene, Fitzgerald, Jacklynn, Forster, Gina, Frijling, Jessie, Geuze, Elbert, Gonenc, Atilla, Gordon, Evan, Gruber, Staci, Grupe, Daniel, Guenette, Jeffrey, Haswell, Courtney, Herringa, Ryan, Herzog, Julia, Hofmann, David, Hosseini, Bobak, Hudson, Anna, Huggins, Ashley, Ipser, Jonathan, Jahanshad, Neda, Jia-Richards, Meilin, Jovanovic, Tanja, Kaufman, Milissa, Kennis, Mitzy, King, Anthony, Kinzel, Philipp, Koch, Saskia, Koerte, Inga, Koopowitz, Sheri, Korgaonkar, Mayuresh, Krystal, John, Lanius, Ruth, Larson, Christine, Lebois, Lauren, Li, Gen, Liberzon, Israel, Lu, Guang, Luo, Yifeng, Magnotta, Vincent, Manthey, Antje, Maron-Katz, Adi, May, Geoffery, McLaughlin, Katie, Mueller, Sven, Nawijn, Laura, Nelson, Steven, Neufeld, Richard, Nitschke, Jack, OLeary, Erin, Olatunji, Bunmi, Olff, Miranda, Peverill, Matthew, Phan, K, Qi, Rongfeng, Quidé, Yann, Rektor, Ivan, Ressler, Kerry, Riha, Pavel, Ross, Marisa, Rosso, Isabelle, Salminen, Lauren, Sambrook, Kelly, Schmahl, Christian, Shenton, Martha, Sheridan, Margaret, Shih, Chiahao, Sicorello, Maurizio, Sierk, Anika, and van Rooij, Sanne

Subjects
Classification, Deep learning, Machine learning, Multimodal MRI, Posttraumatic stress disorder, Humans, Stress Disorders, Post-Traumatic, Reproducibility of Results, Big Data, Neuroimaging, Magnetic Resonance Imaging, Brain
Abstract

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group. METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality. RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance. CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.

Published
2023

4. A comparison of methods to harmonize cortical thickness measurements across scanners and sites

Author

Sun, Delin, Rakesh, Gopalkumar, Haswell, Courtney C, Logue, Mark, Baird, C Lexi, O'Leary, Erin N, Cotton, Andrew S, Xie, Hong, Tamburrino, Marijo, Chen, Tian, Dennis, Emily L, Jahanshad, Neda, Salminen, Lauren E, Thomopoulos, Sophia I, Rashid, Faisal, Ching, Christopher RK, Koch, Saskia BJ, Frijling, Jessie L, Nawijn, Laura, van Zuiden, Mirjam, Zhu, Xi, Suarez-Jimenez, Benjamin, Sierk, Anika, Walter, Henrik, Manthey, Antje, Stevens, Jennifer S, Fani, Negar, van Rooij, Sanne JH, Stein, Murray, Bomyea, Jessica, Koerte, Inga K, Choi, Kyle, van der Werff, Steven JA, Vermeiren, Robert RJM, Herzog, Julia, Lebois, Lauren AM, Baker, Justin T, Olson, Elizabeth A, Straube, Thomas, Korgaonkar, Mayuresh S, Andrew, Elpiniki, Zhu, Ye, Li, Gen, Ipser, Jonathan, Hudson, Anna R, Peverill, Matthew, Sambrook, Kelly, Gordon, Evan, Baugh, Lee, Forster, Gina, Simons, Raluca M, Simons, Jeffrey S, Magnotta, Vincent, Maron-Katz, Adi, du Plessis, Stefan, Disner, Seth G, Davenport, Nicholas, Grupe, Daniel W, Nitschke, Jack B, deRoon-Cassini, Terri A, Fitzgerald, Jacklynn M, Krystal, John H, Levy, Ifat, Olff, Miranda, Veltman, Dick J, Wang, Li, Neria, Yuval, De Bellis, Michael D, Jovanovic, Tanja, Daniels, Judith K, Shenton, Martha, van de Wee, Nic JA, Schmahl, Christian, Kaufman, Milissa L, Rosso, Isabelle M, Sponheim, Scott R, Hofmann, David Bernd, Bryant, Richard A, Fercho, Kelene A, Stein, Dan J, Mueller, Sven C, Hosseini, Bobak, Phan, K Luan, McLaughlin, Katie A, Davidson, Richard J, Larson, Christine L, May, Geoffrey, Nelson, Steven M, Abdallah, Chadi G, Gomaa, Hassaan, Etkin, Amit, Seedat, Soraya, Harpaz-Rotem, Ilan, Liberzon, Israel, van Erp, Theo GM, Quidé, Yann, Wang, Xin, Thompson, Paul M, and Morey, Rajendra A

Subjects
Good Health and Well Being, Adolescent, Adult, Aged, Aged, 80 and over, Case-Control Studies, Child, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Stress Disorders, Post-Traumatic, Young Adult, Data Harmonization, Scanner Effects, Site Effects, Cortical Thickness, ComBat, ComBat-GAM, Linear Mixed-Effects Model, General Additive Model, PTSD, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Results of neuroimaging datasets aggregated from multiple sites may be biased by site-specific profiles in participants' demographic and clinical characteristics, as well as MRI acquisition protocols and scanning platforms. We compared the impact of four different harmonization methods on results obtained from analyses of cortical thickness data: (1) linear mixed-effects model (LME) that models site-specific random intercepts (LMEINT), (2) LME that models both site-specific random intercepts and age-related random slopes (LMEINT+SLP), (3) ComBat, and (4) ComBat with a generalized additive model (ComBat-GAM). Our test case for comparing harmonization methods was cortical thickness data aggregated from 29 sites, which included 1,340 cases with posttraumatic stress disorder (PTSD) (6.2-81.8 years old) and 2,057 trauma-exposed controls without PTSD (6.3-85.2 years old). We found that, compared to the other data harmonization methods, data processed with ComBat-GAM was more sensitive to the detection of significant case-control differences (Χ2(3) = 63.704, p < 0.001) as well as case-control differences in age-related cortical thinning (Χ2(3) = 12.082, p = 0.007). Both ComBat and ComBat-GAM outperformed LME methods in detecting sex differences (Χ2(3) = 9.114, p = 0.028) in regional cortical thickness. ComBat-GAM also led to stronger estimates of age-related declines in cortical thickness (corrected p-values < 0.001), stronger estimates of case-related cortical thickness reduction (corrected p-values < 0.001), weaker estimates of age-related declines in cortical thickness in cases than controls (corrected p-values < 0.001), stronger estimates of cortical thickness reduction in females than males (corrected p-values < 0.001), and stronger estimates of cortical thickness reduction in females relative to males in cases than controls (corrected p-values < 0.001). Our results support the use of ComBat-GAM to minimize confounds and increase statistical power when harmonizing data with non-linear effects, and the use of either ComBat or ComBat-GAM for harmonizing data with linear effects.

Published
2022

5. Neural correlates of anger expression in patients with PTSD

Author

Eshel, Neir, Maron-Katz, Adi, Wu, Wei, Abu-Amara, Duna, Marmar, Charles R, and Etkin, Amit

Subjects
Biological Psychology, Psychology, Basic Behavioral and Social Science, Neurosciences, Brain Disorders, Clinical Research, Post-Traumatic Stress Disorder (PTSD), Anxiety Disorders, Behavioral and Social Science, Mental Health, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Anger, Brain, Humans, Magnetic Resonance Imaging, Stress Disorders, Post-Traumatic, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological psychology
Abstract

Anger is a common and debilitating symptom of post-traumatic stress disorder (PTSD). Although studies have identified brain circuits underlying anger experience and expression in healthy individuals, how these circuits interact with trauma remains unclear. Here, we performed the first study examining the neural correlates of anger in patients with PTSD. Using a data-driven approach with resting-state fMRI, we identified two prefrontal regions whose overall functional connectivity was inversely associated with anger: the left anterior middle frontal gyrus (aMFG) and the right orbitofrontal cortex (OFC). We then used concurrent TMS-EEG to target the left aMFG parcel previously identified through fMRI, measuring its cortical excitability and causal connectivity to downstream areas. We found that low-anger PTSD patients exhibited enhanced excitability in the left aMFG and enhanced causal connectivity between this region and visual areas. Together, our results suggest that left aMFG activity may confer protection against the development of anger, and therefore may be an intriguing target for circuit-based interventions for anger in PTSD.

Published
2021

6. Identification of psychiatric disorder subtypes from functional connectivity patterns in resting-state electroencephalography

Author

Zhang, Yu, Wu, Wei, Toll, Russell T, Naparstek, Sharon, Maron-Katz, Adi, Watts, Mallissa, Gordon, Joseph, Jeong, Jisoo, Astolfi, Laura, Shpigel, Emmanuel, Longwell, Parker, Sarhadi, Kamron, El-Said, Dawlat, Li, Yuanqing, Cooper, Crystal, Chin-Fatt, Cherise, Arns, Martijn, Goodkind, Madeleine S, Trivedi, Madhukar H, Marmar, Charles R, and Etkin, Amit

Subjects
Neurosciences, Brain Disorders, Post-Traumatic Stress Disorder (PTSD), Depression, Mental Health, Serious Mental Illness, Major Depressive Disorder, Anxiety Disorders, Mental health, Good Health and Well Being, Adult, Antidepressive Agents, Brain, Case-Control Studies, Cluster Analysis, Connectome, Databases, Factual, Depressive Disorder, Major, Electroencephalography, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Psychotherapy, Stress Disorders, Post-Traumatic, Transcranial Magnetic Stimulation
Abstract

The understanding and treatment of psychiatric disorders, which are known to be neurobiologically and clinically heterogeneous, could benefit from the data-driven identification of disease subtypes. Here, we report the identification of two clinically relevant subtypes of post-traumatic stress disorder (PTSD) and major depressive disorder (MDD) on the basis of robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the default mode network. We identified the disease subtypes by analysing, via unsupervised and supervised machine learning, the power-envelope-based connectivity of signals reconstructed from high-density resting-state electroencephalography in four datasets of patients with PTSD and MDD, and show that the subtypes are transferable across independent datasets recorded under different conditions. The subtype whose functional connectivity differed most from those of healthy controls was less responsive to psychotherapy treatment for PTSD and failed to respond to an antidepressant medication for MDD. By contrast, both subtypes responded equally well to two different forms of repetitive transcranial magnetic stimulation therapy for MDD. Our data-driven approach may constitute a generalizable solution for connectome-based diagnosis.

Published
2021

7. Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study

Author

Kinreich, Sivan, Meyers, Jacquelyn L, Maron-Katz, Adi, Kamarajan, Chella, Pandey, Ashwini K, Chorlian, David B, Zhang, Jian, Pandey, Gayathri, Subbie-Saenz de Viteri, Stacey, Pitti, Dan, Anokhin, Andrey P, Bauer, Lance, Hesselbrock, Victor, Schuckit, Marc A, Edenberg, Howard J, and Porjesz, Bernice

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical and Health Psychology, Clinical Sciences, Psychology, Brain Disorders, Clinical Research, Alcoholism, Alcohol Use and Health, Genetics, Substance Misuse, Mental health, Good Health and Well Being, Black or African American, Aged, Alcoholism, Biomarkers, Child, Female, Genome-Wide Association Study, Humans, Machine Learning, Male, United States, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Predictive models have succeeded in distinguishing between individuals with Alcohol use Disorder (AUD) and controls. However, predictive models identifying who is prone to develop AUD and the biomarkers indicating a predisposition to AUD are still unclear. Our sample (n = 656) included offspring and non-offspring of European American (EA) and African American (AA) ancestry from the Collaborative Study of the Genetics of Alcoholism (COGA) who were recruited as early as age 12 and were unaffected at first assessment and reassessed years later as AUD (DSM-5) (n = 328) or unaffected (n = 328). Machine learning analysis was performed for 220 EEG measures, 149 alcohol-related single nucleotide polymorphisms (SNPs) from a recent large Genome-wide Association Study (GWAS) of alcohol use/misuse and two family history (mother DSM-5 AUD and father DSM-5 AUD) features using supervised, Linear Support Vector Machine (SVM) classifier to test which features assessed before developing AUD predict those who go on to develop AUD. Age, gender, and ancestry stratified analyses were performed. Results indicate significant and higher accuracy rates for the AA compared with the EA prediction models and a higher model accuracy trend among females compared with males for both ancestries. Combined EEG and SNP features model outperformed models based on only EEG features or only SNP features for both EA and AA samples. This multidimensional superiority was confirmed in a follow-up analysis in the AA age groups (12-15, 16-19, 20-30) and EA age group (16-19). In both ancestry samples, the youngest age group achieved higher accuracy score than the two other older age groups. Maternal AUD increased the model's accuracy in both ancestries' samples. Several discriminative EEG measures and SNPs features were identified, including lower posterior gamma, higher slow wave connectivity (delta, theta, alpha), higher frontal gamma ratio, higher beta correlation in the parietal area, and 5 SNPs: rs4780836, rs2605140, rs11690265, rs692854, and rs13380649. Results highlight the significance of sampling uniformity followed by stratified (e.g., ancestry, gender, developmental period) analysis, and wider selection of features, to generate better prediction scores allowing a more accurate estimation of AUD development.

Published
2021

8. Global connectivity and local excitability changes underlie antidepressant effects of repetitive transcranial magnetic stimulation

Author

Eshel, Neir, Keller, Corey J, Wu, Wei, Jiang, Jing, Mills-Finnerty, Colleen, Huemer, Julia, Wright, Rachael, Fonzo, Gregory A, Ichikawa, Naho, Carreon, David, Wong, Melinda, Yee, Andrew, Shpigel, Emmanuel, Guo, Yi, McTeague, Lisa, Maron-Katz, Adi, and Etkin, Amit

Subjects
Serious Mental Illness, Neurosciences, Rehabilitation, Mental Health, Clinical Trials and Supportive Activities, Major Depressive Disorder, Depression, Clinical Research, Brain Disorders, Bioengineering, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, Antidepressive Agents, Depressive Disorder, Major, Humans, Magnetic Resonance Imaging, Prefrontal Cortex, Transcranial Magnetic Stimulation, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Repetitive transcranial magnetic stimulation (rTMS) is a commonly- used treatment for major depressive disorder (MDD). However, our understanding of the mechanism by which TMS exerts its antidepressant effect is minimal. Furthermore, we lack brain signals that can be used to predict and track clinical outcome. Such signals would allow for treatment stratification and optimization. Here, we performed a randomized, sham-controlled clinical trial and measured electrophysiological, neuroimaging, and clinical changes before and after rTMS. Patients (N = 36) were randomized to receive either active or sham rTMS to the left dorsolateral prefrontal cortex (dlPFC) for 20 consecutive weekdays. To capture the rTMS-driven changes in connectivity and causal excitability, resting fMRI and TMS/EEG were performed before and after the treatment. Baseline causal connectivity differences between depressed patients and healthy controls were also evaluated with concurrent TMS/fMRI. We found that active, but not sham rTMS elicited (1) an increase in dlPFC global connectivity, (2) induction of negative dlPFC-amygdala connectivity, and (3) local and distributed changes in TMS/EEG potentials. Global connectivity changes predicted clinical outcome, while both global connectivity and TMS/EEG changes tracked clinical outcome. In patients but not healthy participants, we observed a perturbed inhibitory effect of the dlPFC on the amygdala. Taken together, rTMS induced lasting connectivity and excitability changes from the site of stimulation, such that after active treatment, the dlPFC appeared better able to engage in top-down control of the amygdala. These measures of network functioning both predicted and tracked clinical outcome, potentially opening the door to treatment optimization.

Published
2020

9. K-shell decomposition reveals hierarchical cortical organization of the human brain

Author

Lahav, Nir, Ksherim, Baruch, Ben-Simon, Eti, Maron-Katz, Adi, Cohen, Reuven, and Havlin, Shlomo

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

In recent years numerous attempts to understand the human brain were undertaken from a network point of view. A network framework takes into account the relationships between the different parts of the system and enables to examine how global and complex functions might emerge from network topology. Previous work revealed that the human brain features 'small world' characteristics and that cortical hubs tend to interconnect among themselves. However, in order to fully understand the topological structure of hubs one needs to go beyond the properties of a specific hub and examine the various structural layers of the network. To address this topic further, we applied an analysis known in statistical physics and network theory as k-shell decomposition analysis. The analysis was applied on a human cortical network, derived from MRI\DSI data of six participants. Such analysis enables us to portray a detailed account of cortical connectivity focusing on different neighborhoods of interconnected layers across the cortex. Our findings reveal that the human cortex is highly connected and efficient, and unlike the internet network contains no isolated nodes. The cortical network is comprised of a nucleus alongside shells of increasing connectivity that formed one connected giant component. All these components were further categorized into three hierarchies in accordance with their connectivity profile, with each hierarchy reflecting different functional roles. Such a model may explain an efficient flow of information from the lowest hierarchy to the highest one, with each step enabling increased data integration. At the top, the highest hierarchy (the nucleus) serves as a global interconnected collective and demonstrates high correlation with consciousness related regions, suggesting that the nucleus might serve as a platform for consciousness to emerge., Comment: New Journal of Physics, Volume 18, August 2016

Published
2018
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10. Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder

Author

Etkin, Amit, Maron-Katz, Adi, Wu, Wei, Fonzo, Gregory A, Huemer, Julia, Vértes, Petra E, Patenaude, Brian, Richiardi, Jonas, Goodkind, Madeleine S, Keller, Corey J, Ramos-Cejudo, Jaime, Zaiko, Yevgeniya V, Peng, Kathy K, Shpigel, Emmanuel, Longwell, Parker, Toll, Russ T, Thompson, Allison, Zack, Sanno, Gonzalez, Bryan, Edelstein, Raleigh, Chen, Jingyun, Akingbade, Irene, Weiss, Elizabeth, Hart, Roland, Mann, Silas, Durkin, Kathleen, Baete, Steven H, Boada, Fernando E, Genfi, Afia, Autea, Jillian, Newman, Jennifer, Oathes, Desmond J, Lindley, Steven E, Abu-Amara, Duna, Arnow, Bruce A, Crossley, Nicolas, Hallmayer, Joachim, Fossati, Silvia, Rothbaum, Barbara O, Marmar, Charles R, Bullmore, Edward T, and O'Hara, Ruth

Subjects
Clinical Research, Basic Behavioral and Social Science, Mental Health, Brain Disorders, Neurosciences, Serious Mental Illness, Behavioral and Social Science, Post-Traumatic Stress Disorder (PTSD), Rehabilitation, Anxiety Disorders, Aetiology, 2.1 Biological and endogenous factors, Mental health, Attention, Behavior, Brain Mapping, Comorbidity, Electroencephalography, Humans, Magnetic Resonance Imaging, Mental Recall, Nerve Net, Rest, Stress Disorders, Post-Traumatic, Transcranial Magnetic Stimulation, Treatment Outcome, Biological Sciences, Medical and Health Sciences
Abstract

A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.

Published
2019

11. Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results From the ENIGMA-PGC Posttraumatic Stress Disorder Consortium

Author

Sun, Delin, Rakesh, Gopalkumar, Clarke-Rubright, Emily K., Haswell, Courtney C., Logue, Mark W., O’Leary, Erin N., Cotton, Andrew S., Xie, Hong, Dennis, Emily L., Jahanshad, Neda, Salminen, Lauren E., Thomopoulos, Sophia I., Rashid, Faisal M., Ching, Christopher R.K., Koch, Saskia B.J., Frijling, Jessie L., Nawijn, Laura, van Zuiden, Mirjam, Zhu, Xi, Suarez-Jimenez, Benjamin, Sierk, Anika, Walter, Henrik, Manthey, Antje, Stevens, Jennifer S., Fani, Negar, van Rooij, Sanne J.H., Stein, Murray B., Bomyea, Jessica, Koerte, Inga, Choi, Kyle, van der Werff, Steven J.A., Vermeiren, Robert R.J.M., Herzog, Julia I., Lebois, Lauren A.M., Baker, Justin T., Ressler, Kerry J., Olson, Elizabeth A., Straube, Thomas, Korgaonkar, Mayuresh S., Andrew, Elpiniki, Zhu, Ye, Li, Gen, Ipser, Jonathan, Hudson, Anna R., Peverill, Matthew, Sambrook, Kelly, Gordon, Evan, Baugh, Lee A., Forster, Gina, Simons, Raluca M., Simons, Jeffrey S., Magnotta, Vincent A., Maron-Katz, Adi, du Plessis, Stefan, Disner, Seth G., Davenport, Nicholas D., Grupe, Dan, Nitschke, Jack B., deRoon-Cassini, Terri A., Fitzgerald, Jacklynn, Krystal, John H., Levy, Ifat, Olff, Miranda, Veltman, Dick J., Wang, Li, Neria, Yuval, De Bellis, Michael D., Jovanovic, Tanja, Daniels, Judith K., Shenton, Martha E., van de Wee, Nic J.A., Schmahl, Christian, Kaufman, Milissa L., Rosso, Isabelle M., Sponheim, Scott R., Hofmann, David Bernd, Bryant, Richard A., Fercho, Kelene A., Stein, Dan J., Mueller, Sven C., Phan, K. Luan, McLaughlin, Katie A., Davidson, Richard J., Larson, Christine, May, Geoffrey, Nelson, Steven M., Abdallah, Chadi G., Gomaa, Hassaan, Etkin, Amit, Seedat, Soraya, Harpaz-Rotem, Ilan, Liberzon, Israel, Wang, Xin, Thompson, Paul M., and Morey, Rajendra A.

Published
2022
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12. Smaller total and subregional cerebellar volumes in posttraumatic stress disorder:a mega-analysis by the ENIGMA-PGC PTSD workgroup

Author

Huggins, Ashley A., Baird, C. Lexi, Briggs, Melvin, Laskowitz, Sarah, Hussain, Ahmed, Fouda, Samar, Haswell, Courtney, Sun, Delin, Salminen, Lauren E., Jahanshad, Neda, Thomopoulos, Sophia I., Veltman, Dick J., Frijling, Jessie L., Olff, Miranda, van Zuiden, Mirjam, Koch, Saskia B.J., Nawjin, Laura, Wang, Li, Zhu, Ye, Li, Gen, Stein, Dan J., Ipser, Jonathan, Seedat, Soraya, du Plessis, Stefan, van den Heuvel, Leigh L., Suarez-Jimenez, Benjamin, Zhu, Xi, Kim, Yoojean, He, Xiaofu, Zilcha-Mano, Sigal, Lazarov, Amit, Neria, Yuval, Stevens, Jennifer S., Ressler, Kerry J., Jovanovic, Tanja, van Rooij, Sanne J.H., Fani, Negar, Hudson, Anna R., Mueller, Sven C., Sierk, Anika, Manthey, Antje, Walter, Henrik, Daniels, Judith K., Schmahl, Christian, Herzog, Julia I., Říha, Pavel, Rektor, Ivan, Lebois, Lauren A.M., Kaufman, Milissa L., Olson, Elizabeth A., Baker, Justin T., Rosso, Isabelle M., King, Anthony P., Liberzon, Isreal, Angstadt, Mike, Davenport, Nicholas D., Sponheim, Scott R., Disner, Seth G., Straube, Thomas, Hofmann, David, Qi, Rongfeng, Lu, Guang Ming, Baugh, Lee A., Forster, Gina L., Simons, Raluca M., Simons, Jeffrey S., Magnotta, Vincent A., Fercho, Kelene A., Maron-Katz, Adi, Etkin, Amit, Cotton, Andrew S., O’Leary, Erin N., Xie, Hong, Wang, Xin, Quidé, Yann, El-Hage, Wissam, Lissek, Shmuel, Berg, Hannah, Bruce, Steven, Cisler, Josh, Ross, Marisa, Herringa, Ryan J., Grupe, Daniel W., Nitschke, Jack B., Davidson, Richard J., Larson, Christine L., deRoon-Cassini, Terri A., Tomas, Carissa W., Fitzgerald, Jacklynn M., Blackford, Jennifer Urbano, Olatunji, Bunmi O., Kremen, William S., Lyons, Michael J., Franz, Carol E., Gordon, Evan M., May, Geoffrey, Nelson, Steven M., Abdallah, Chadi G., Levy, Ifat, Harpaz-Rotem, Ilan, Krystal, John H., Dennis, Emily L., Tate, David F., Cifu, David X., Walker, William C., Wilde, Elizabeth A., Harding, Ian H., Kerestes, Rebecca, Thompson, Paul M., Morey, Rajendra, Huggins, Ashley A., Baird, C. Lexi, Briggs, Melvin, Laskowitz, Sarah, Hussain, Ahmed, Fouda, Samar, Haswell, Courtney, Sun, Delin, Salminen, Lauren E., Jahanshad, Neda, Thomopoulos, Sophia I., Veltman, Dick J., Frijling, Jessie L., Olff, Miranda, van Zuiden, Mirjam, Koch, Saskia B.J., Nawjin, Laura, Wang, Li, Zhu, Ye, Li, Gen, Stein, Dan J., Ipser, Jonathan, Seedat, Soraya, du Plessis, Stefan, van den Heuvel, Leigh L., Suarez-Jimenez, Benjamin, Zhu, Xi, Kim, Yoojean, He, Xiaofu, Zilcha-Mano, Sigal, Lazarov, Amit, Neria, Yuval, Stevens, Jennifer S., Ressler, Kerry J., Jovanovic, Tanja, van Rooij, Sanne J.H., Fani, Negar, Hudson, Anna R., Mueller, Sven C., Sierk, Anika, Manthey, Antje, Walter, Henrik, Daniels, Judith K., Schmahl, Christian, Herzog, Julia I., Říha, Pavel, Rektor, Ivan, Lebois, Lauren A.M., Kaufman, Milissa L., Olson, Elizabeth A., Baker, Justin T., Rosso, Isabelle M., King, Anthony P., Liberzon, Isreal, Angstadt, Mike, Davenport, Nicholas D., Sponheim, Scott R., Disner, Seth G., Straube, Thomas, Hofmann, David, Qi, Rongfeng, Lu, Guang Ming, Baugh, Lee A., Forster, Gina L., Simons, Raluca M., Simons, Jeffrey S., Magnotta, Vincent A., Fercho, Kelene A., Maron-Katz, Adi, Etkin, Amit, Cotton, Andrew S., O’Leary, Erin N., Xie, Hong, Wang, Xin, Quidé, Yann, El-Hage, Wissam, Lissek, Shmuel, Berg, Hannah, Bruce, Steven, Cisler, Josh, Ross, Marisa, Herringa, Ryan J., Grupe, Daniel W., Nitschke, Jack B., Davidson, Richard J., Larson, Christine L., deRoon-Cassini, Terri A., Tomas, Carissa W., Fitzgerald, Jacklynn M., Blackford, Jennifer Urbano, Olatunji, Bunmi O., Kremen, William S., Lyons, Michael J., Franz, Carol E., Gordon, Evan M., May, Geoffrey, Nelson, Steven M., Abdallah, Chadi G., Levy, Ifat, Harpaz-Rotem, Ilan, Krystal, John H., Dennis, Emily L., Tate, David F., Cifu, David X., Walker, William C., Wilde, Elizabeth A., Harding, Ian H., Kerestes, Rebecca, Thompson, Paul M., and Morey, Rajendra

Abstract

Although the cerebellum contributes to higher-order cognitive and emotional functions relevant to posttraumatic stress disorder (PTSD), prior research on cerebellar volume in PTSD is scant, particularly when considering subregions that differentially map on to motor, cognitive, and affective functions. In a sample of 4215 adults (PTSD n = 1642; Control n = 2573) across 40 sites from the ENIGMA-PGC PTSD working group, we employed a new state-of-the-art deep-learning based approach for automatic cerebellar parcellation to obtain volumetric estimates for the total cerebellum and 28 subregions. Linear mixed effects models controlling for age, gender, intracranial volume, and site were used to compare cerebellum volumes in PTSD compared to healthy controls (88% trauma-exposed). PTSD was associated with significant grey and white matter reductions of the cerebellum. Compared to controls, people with PTSD demonstrated smaller total cerebellum volume, as well as reduced volume in subregions primarily within the posterior lobe (lobule VIIB, crus II), vermis (VI, VIII), flocculonodular lobe (lobule X), and corpus medullare (all p -FDR < 0.05). Effects of PTSD on volume were consistent, and generally more robust, when examining symptom severity rather than diagnostic status. These findings implicate regionally specific cerebellar volumetric differences in the pathophysiology of PTSD. The cerebellum appears to play an important role in higher-order cognitive and emotional processes, far beyond its historical association with vestibulomotor function. Further examination of the cerebellum in trauma-related psychopathology will help to clarify how cerebellar structure and function may disrupt cognitive and affective processes at the center of translational models for PTSD.

Published
2024

13. Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches: A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

Author

Zhu, Xi, primary, Kim, Yoojean, additional, Ravid, Orren, additional, He, Xiaofu, additional, Suarez-Jimenez, Benjamin, additional, Zilcha-Mano, Sigal, additional, Lazarov, Amit, additional, Lee, Seonjoo, additional, Abdallah, Chadi G., additional, Angstadt, Michael, additional, Averill, Christopher L., additional, Baird, C. Lexi, additional, Baugh, Lee A., additional, Blackford, Jennifer U., additional, Bomyea, Jessica, additional, Bruce, Steven E., additional, Bryant, Richard A., additional, Cao, Zhihong, additional, Choi, Kyle, additional, Cisler, Josh, additional, Cotton, Andrew S., additional, Daniels, Judith K., additional, Davenport, Nicholas D., additional, Davidson, Richard J., additional, DeBellis, Michael D., additional, Dennis, Emily L., additional, Densmore, Maria, additional, deRoon-Cassini, Terri, additional, Disner, Seth G., additional, Hage, Wissam El, additional, Etkin, Amit, additional, Fani, Negar, additional, Fercho, Kelene A., additional, Fitzgerald, Jacklynn, additional, Forster, Gina L., additional, Frijling, Jessie L., additional, Geuze, Elbert, additional, Gonenc, Atilla, additional, Gordon, Evan M., additional, Gruber, Staci, additional, Grupe, Daniel W, additional, Guenette, Jeffrey P., additional, Haswell, Courtney C., additional, Herringa, Ryan J., additional, Herzog, Julia, additional, Hofmann, David Bernd, additional, Hosseini, Bobak, additional, Hudson, Anna R., additional, Huggins, Ashley A., additional, Ipser, Jonathan C., additional, Jahanshad, Neda, additional, Jia-Richards, Meilin, additional, Jovanovic, Tanja, additional, Kaufman, Milissa L., additional, Kennis, Mitzy, additional, King, Anthony, additional, Kinzel, Philipp, additional, Koch, Saskia B.J., additional, Koerte, Inga K., additional, Koopowitz, Sheri M., additional, Korgaonkar, Mayuresh S., additional, Krystal, John H., additional, Lanius, Ruth, additional, Larson, Christine L., additional, Lebois, Lauren A.M., additional, Li, Gen, additional, Liberzon, Israel, additional, Lu, Guang Ming, additional, Luo, Yifeng, additional, Magnotta, Vincent A., additional, Manthey, Antje, additional, Maron-Katz, Adi, additional, May, Geoffery, additional, McLaughlin, Katie, additional, Mueller, Sven C., additional, Nawijn, Laura, additional, Nelson, Steven M., additional, Neufeld, Richard W.J., additional, Nitschke, Jack B, additional, O'Leary, Erin M., additional, Olatunji, Bunmi O., additional, Olff, Miranda, additional, Peverill, Matthew, additional, Phan, K. Luan, additional, Qi, Rongfeng, additional, Quidé, Yann, additional, Rektor, Ivan, additional, Ressler, Kerry, additional, Riha, Pavel, additional, Ross, Marisa, additional, Rosso, Isabelle M., additional, Salminen, Lauren E., additional, Sambrook, Kelly, additional, Schmahl, Christian, additional, Shenton, Martha E., additional, Sheridan, Margaret, additional, Shih, Chiahao, additional, Sicorello, Maurizio, additional, Sierk, Anika, additional, Simmons, Alan N., additional, Simons, Raluca M., additional, Simons, Jeffrey S., additional, Sponheim, Scott R., additional, Stein, Murray B., additional, Stein, Dan J., additional, Stevens, Jennifer S., additional, Straube, Thomas, additional, Sun, Delin, additional, Théberge, Jean, additional, Thompson, Paul M., additional, Thomopoulos, Sophia I., additional, van der Wee, Nic J.A., additional, van der Werff, Steven J.A., additional, van Erp, Theo G.M., additional, van Rooij, Sanne J.H., additional, van Zuiden, Mirjam, additional, Varkevisser, Tim, additional, Veltman, Dick J., additional, Vermeiren, Robert R.J.M., additional, Walter, Henrik, additional, Wang, Li, additional, Wang, Xin, additional, Weis, Carissa, additional, Winternitz, Sherry, additional, Xie, Hong, additional, Zhu, Ye, additional, Wall, Melanie, additional, Neria, Yuval, additional, and Morey, Rajendra A., additional

Published
2023
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14. Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium

Author

MGGZ, Brain, Zhu, Xi, Kim, Yoojean, Ravid, Orren, He, Xiaofu, Suarez-Jimenez, Benjamin, Zilcha-Mano, Sigal, Lazarov, Amit, Lee, Seonjoo, Abdallah, Chadi G., Angstadt, Michael, Averill, Christopher L., Baird, C. Lexi, Baugh, Lee A., Blackford, Jennifer U., Bomyea, Jessica, Bruce, Steven E., Bryant, Richard A., Cao, Zhihong, Choi, Kyle, Cisler, Josh, Cotton, Andrew S., Daniels, Judith K., Davenport, Nicholas D., Davidson, Richard J., DeBellis, Michael D., Dennis, Emily L., Densmore, Maria, deRoon-Cassini, Terri, Disner, Seth G., Hage, Wissam El, Etkin, Amit, Fani, Negar, Fercho, Kelene A., Fitzgerald, Jacklynn, Forster, Gina L., Frijling, Jessie L., Geuze, Elbert, Gonenc, Atilla, Gordon, Evan M., Gruber, Staci, Grupe, Daniel W., Guenette, Jeffrey P., Haswell, Courtney C., Herringa, Ryan J., Herzog, Julia, Hofmann, David Bernd, Hosseini, Bobak, Hudson, Anna R., Huggins, Ashley A., Ipser, Jonathan C., Jahanshad, Neda, Jia-Richards, Meilin, Jovanovic, Tanja, Kaufman, Milissa L., Kennis, Mitzy, King, Anthony, Kinzel, Philipp, Koch, Saskia B.J., Koerte, Inga K., Koopowitz, Sheri M., Korgaonkar, Mayuresh S., Krystal, John H., Lanius, Ruth, Larson, Christine L., Lebois, Lauren A.M., Li, Gen, Liberzon, Israel, Lu, Guang Ming, Luo, Yifeng, Magnotta, Vincent A., Manthey, Antje, Maron-Katz, Adi, May, Geoffery, McLaughlin, Katie, Mueller, Sven C., Nawijn, Laura, Nelson, Steven M., Neufeld, Richard W.J., Nitschke, Jack B., O'Leary, Erin M., Olatunji, Bunmi O., Olff, Miranda, Peverill, Matthew, Phan, K. Luan, Qi, Rongfeng, Quidé, Yann, Rektor, Ivan, Ressler, Kerry, Riha, Pavel, Ross, Marisa, Rosso, Isabelle M., Salminen, Lauren E., Sambrook, Kelly, Schmahl, Christian, Shenton, Martha E., Sheridan, Margaret, Shih, Chiahao, Sicorello, Maurizio, Sierk, Anika, Simmons, Alan N., Simons, Raluca M., Simons, Jeffrey S., Sponheim, Scott R., Stein, Murray B., Stein, Dan J., Stevens, Jennifer S., Straube, Thomas, Sun, Delin, Théberge, Jean, Thompson, Paul M., Thomopoulos, Sophia I., van der Wee, Nic J.A., van der Werff, Steven J.A., van Erp, Theo G.M., van Rooij, Sanne J.H., van Zuiden, Mirjam, Varkevisser, Tim, Veltman, Dick J., Vermeiren, Robert R.J.M., Walter, Henrik, Wang, Li, Wang, Xin, Weis, Carissa, Winternitz, Sherry, Xie, Hong, Zhu, Ye, Wall, Melanie, Neria, Yuval, Morey, Rajendra A., MGGZ, Brain, Zhu, Xi, Kim, Yoojean, Ravid, Orren, He, Xiaofu, Suarez-Jimenez, Benjamin, Zilcha-Mano, Sigal, Lazarov, Amit, Lee, Seonjoo, Abdallah, Chadi G., Angstadt, Michael, Averill, Christopher L., Baird, C. Lexi, Baugh, Lee A., Blackford, Jennifer U., Bomyea, Jessica, Bruce, Steven E., Bryant, Richard A., Cao, Zhihong, Choi, Kyle, Cisler, Josh, Cotton, Andrew S., Daniels, Judith K., Davenport, Nicholas D., Davidson, Richard J., DeBellis, Michael D., Dennis, Emily L., Densmore, Maria, deRoon-Cassini, Terri, Disner, Seth G., Hage, Wissam El, Etkin, Amit, Fani, Negar, Fercho, Kelene A., Fitzgerald, Jacklynn, Forster, Gina L., Frijling, Jessie L., Geuze, Elbert, Gonenc, Atilla, Gordon, Evan M., Gruber, Staci, Grupe, Daniel W., Guenette, Jeffrey P., Haswell, Courtney C., Herringa, Ryan J., Herzog, Julia, Hofmann, David Bernd, Hosseini, Bobak, Hudson, Anna R., Huggins, Ashley A., Ipser, Jonathan C., Jahanshad, Neda, Jia-Richards, Meilin, Jovanovic, Tanja, Kaufman, Milissa L., Kennis, Mitzy, King, Anthony, Kinzel, Philipp, Koch, Saskia B.J., Koerte, Inga K., Koopowitz, Sheri M., Korgaonkar, Mayuresh S., Krystal, John H., Lanius, Ruth, Larson, Christine L., Lebois, Lauren A.M., Li, Gen, Liberzon, Israel, Lu, Guang Ming, Luo, Yifeng, Magnotta, Vincent A., Manthey, Antje, Maron-Katz, Adi, May, Geoffery, McLaughlin, Katie, Mueller, Sven C., Nawijn, Laura, Nelson, Steven M., Neufeld, Richard W.J., Nitschke, Jack B., O'Leary, Erin M., Olatunji, Bunmi O., Olff, Miranda, Peverill, Matthew, Phan, K. Luan, Qi, Rongfeng, Quidé, Yann, Rektor, Ivan, Ressler, Kerry, Riha, Pavel, Ross, Marisa, Rosso, Isabelle M., Salminen, Lauren E., Sambrook, Kelly, Schmahl, Christian, Shenton, Martha E., Sheridan, Margaret, Shih, Chiahao, Sicorello, Maurizio, Sierk, Anika, Simmons, Alan N., Simons, Raluca M., Simons, Jeffrey S., Sponheim, Scott R., Stein, Murray B., Stein, Dan J., Stevens, Jennifer S., Straube, Thomas, Sun, Delin, Théberge, Jean, Thompson, Paul M., Thomopoulos, Sophia I., van der Wee, Nic J.A., van der Werff, Steven J.A., van Erp, Theo G.M., van Rooij, Sanne J.H., van Zuiden, Mirjam, Varkevisser, Tim, Veltman, Dick J., Vermeiren, Robert R.J.M., Walter, Henrik, Wang, Li, Wang, Xin, Weis, Carissa, Winternitz, Sherry, Xie, Hong, Zhu, Ye, Wall, Melanie, Neria, Yuval, and Morey, Rajendra A.

Published
2023

15. Multimodal Imaging-Based Classification of PTSD Using Data-Driven Computational Approaches: A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

Author

Zhu, Xi, primary, Kim, Yoojean, additional, Ravid, Orren, additional, He, Xiaofu, additional, Suarez-Jimenez, Benjamin, additional, Zilcha-Mano, Sigal, additional, Lazarov, Amit, additional, Lee, Seonjoo, additional, Abdallah, Chadi G., additional, Angstadt, Michael, additional, Averill, Christopher L., additional, Baird, C. Lexi, additional, Baugh, Lee A., additional, Blackford, Jennifer U., additional, Bomyea, Jessica, additional, Bruce, Steven E., additional, Bryant, Richard A., additional, Cao, Zhihong, additional, Choi, Kyle, additional, Cisler, Josh, additional, Cotton, Andrew S., additional, Daniels, Judith K., additional, Davenport, Nicholas D., additional, Davidson, Richard J., additional, DeBellis, Michael D., additional, Dennis, Emily L., additional, Densmore, Maria, additional, deRoon-Cassini, Terri, additional, Disner, Seth G., additional, Hage, Wissam El, additional, Etkin, Amit, additional, Fani, Negar, additional, Fercho, Kelene A., additional, Fitzgerald, Jacklynn, additional, Forster, Gina L., additional, Frijling, Jessie L., additional, Geuze, Elbert, additional, Gonenc, Atilla, additional, Gordon, Evan M., additional, Gruber, Staci, additional, Grupe, Daniel W, additional, Guenette, Jeffrey P., additional, Haswell, Courtney C., additional, Herringa, Ryan J., additional, Herzog, Julia, additional, Hofmann, David Bernd, additional, Hosseini, Bobak, additional, Hudson, Anna R., additional, Huggins, Ashley A., additional, Ipser, Jonathan C., additional, Jahanshad, Neda, additional, Jia-Richards, Meilin, additional, Jovanovic, Tanja, additional, Kaufman, Milissa L., additional, Kennis, Mitzy, additional, King, Anthony, additional, Kinzel, Philipp, additional, Koch, Saskia B. J., additional, Koerte, Inga K., additional, Koopowitz, Sheri M., additional, Korgaonkar, Mayuresh S., additional, Krystal, John H., additional, Lanius, Ruth, additional, Larson, Christine L., additional, Lebois, Lauren A. M., additional, Li, Gen, additional, Liberzon, Israel, additional, Lu, Guang Ming, additional, Luo, Yifeng, additional, Magnotta, Vincent A., additional, Manthey, Antje, additional, Maron-Katz, Adi, additional, May, Geoffery, additional, McLaughlin, Katie, additional, Mueller, Sven C., additional, Nawijn, Laura, additional, Nelson, Steven M., additional, Neufeld, Richard W.J., additional, Nitschke, Jack B, additional, O’Leary, Erin M., additional, Olatunji, Bunmi O., additional, Olff, Miranda, additional, Peverill, Matthew, additional, Phan, K. Luan, additional, Qi, Rongfeng, additional, Quidé, Yann, additional, Rektor, Ivan, additional, Ressler, Kerry, additional, Riha, Pavel, additional, Ross, Marisa, additional, Rosso, Isabelle M., additional, Salminen, Lauren E., additional, Sambrook, Kelly, additional, Schmahl, Christian, additional, Shenton, Martha E., additional, Sheridan, Margaret, additional, Shih, Chiahao, additional, Sicorello, Maurizio, additional, Sierk, Anika, additional, Simmons, Alan N., additional, Simons, Raluca M., additional, Simons, Jeffrey S., additional, Sponheim, Scott R., additional, Stein, Murray B., additional, Stein, Dan J., additional, Stevens, Jennifer S., additional, Straube, Thomas, additional, Sun, Delin, additional, Théberge, Jean, additional, Thompson, Paul M., additional, Thomopoulos, Sophia I., additional, van der Wee, Nic J.A., additional, van der Werff, Steven J.A., additional, van Erp, Theo G. M., additional, van Rooij, Sanne J. H., additional, van Zuiden, Mirjam, additional, Varkevisser, Tim, additional, Veltman, Dick J., additional, Vermeiren, Robert R.J.M., additional, Walter, Henrik, additional, Wang, Li, additional, Wang, Xin, additional, Weis, Carissa, additional, Winternitz, Sherry, additional, Xie, Hong, additional, Zhu, Ye, additional, Wall, Melanie, additional, Neria, Yuval, additional, and Morey, Rajendra A., additional

Published
2022
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16. A comparison of methods to harmonize cortical thickness measurements across scanners and sites

Author

Sun, Delin, primary, Rakesh, Gopalkumar, additional, Haswell, Courtney C., additional, Logue, Mark, additional, Baird, C. Lexi, additional, O'Leary, Erin N., additional, Cotton, Andrew S., additional, Xie, Hong, additional, Tamburrino, Marijo, additional, Chen, Tian, additional, Dennis, Emily L., additional, Jahanshad, Neda, additional, Salminen, Lauren E., additional, Thomopoulos, Sophia I., additional, Rashid, Faisal, additional, Ching, Christopher R.K., additional, Koch, Saskia B.J., additional, Frijling, Jessie L., additional, Nawijn, Laura, additional, van Zuiden, Mirjam, additional, Zhu, Xi, additional, Suarez-Jimenez, Benjamin, additional, Sierk, Anika, additional, Walter, Henrik, additional, Manthey, Antje, additional, Stevens, Jennifer S., additional, Fani, Negar, additional, van Rooij, Sanne J.H., additional, Stein, Murray, additional, Bomyea, Jessica, additional, Koerte, Inga K., additional, Choi, Kyle, additional, van der Werff, Steven J.A., additional, Vermeiren, Robert R.J.M., additional, Herzog, Julia, additional, Lebois, Lauren A.M., additional, Baker, Justin T., additional, Olson, Elizabeth A., additional, Straube, Thomas, additional, Korgaonkar, Mayuresh S., additional, Andrew, Elpiniki, additional, Zhu, Ye, additional, Li, Gen, additional, Ipser, Jonathan, additional, Hudson, Anna R., additional, Peverill, Matthew, additional, Sambrook, Kelly, additional, Gordon, Evan, additional, Baugh, Lee, additional, Forster, Gina, additional, Simons, Raluca M., additional, Simons, Jeffrey S., additional, Magnotta, Vincent, additional, Maron-Katz, Adi, additional, du Plessis, Stefan, additional, Disner, Seth G., additional, Davenport, Nicholas, additional, Grupe, Daniel W., additional, Nitschke, Jack B., additional, deRoon-Cassini, Terri A., additional, Fitzgerald, Jacklynn M., additional, Krystal, John H., additional, Levy, Ifat, additional, Olff, Miranda, additional, Veltman, Dick J., additional, Wang, Li, additional, Neria, Yuval, additional, De Bellis, Michael D., additional, Jovanovic, Tanja, additional, Daniels, Judith K., additional, Shenton, Martha, additional, van de Wee, Nic J.A., additional, Schmahl, Christian, additional, Kaufman, Milissa L., additional, Rosso, Isabelle M., additional, Sponheim, Scott R., additional, Hofmann, David Bernd, additional, Bryant, Richard A., additional, Fercho, Kelene A., additional, Stein, Dan J., additional, Mueller, Sven C., additional, Hosseini, Bobak, additional, Phan, K. Luan, additional, McLaughlin, Katie A., additional, Davidson, Richard J., additional, Larson, Christine L., additional, May, Geoffrey, additional, Nelson, Steven M., additional, Abdallah, Chadi G., additional, Gomaa, Hassaan, additional, Etkin, Amit, additional, Seedat, Soraya, additional, Harpaz-Rotem, Ilan, additional, Liberzon, Israel, additional, van Erp, Theo G.M., additional, Quidé, Yann, additional, Wang, Xin, additional, Thompson, Paul M., additional, and Morey, Rajendra A., additional

Published
2022
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17. Remodeling of the Cortical Structural Connectome in Posttraumatic Stress Disorder: Results from the ENIGMA-PGC PTSD Consortium

Author

Sun, Delin, Rakesh, Gopalkumar, Clarke-Rubright, Emily K, Haswell, Courtney C, Logue, Mark, O'Leary, Erin N, Cotton, Andrew S, Xie, Hong, Dennis, Emily L, Jahanshad, Neda, Salminen, Lauren E, Thomopoulos, Sophia I, Rashid, Faisal, Ching, Christopher R K, Koch, Saskia B J, Frijling, Jessie L, Nawijn, Laura, van Zuiden, Mirjam, Zhu, Xi, Suarez-Jimenez, Benjamin, Sierk, Anika, Walter, Henrik, Manthey, Antje, Stevens, Jennifer S, Fani, Negar, van Rooij, Sanne J H, Stein, Murray, Bomyea, Jessica, Koerte, Inga, Choi, Kyle, van de Werff, Steven J A, Vermeiren, Robert R J M, Herzog, Julia, Lebois, Lauren A M, Baker, Justin T, Ressler, Kerry J, Olson, Elizabeth A, Straube, Thomas, Korgaonkar, Mayuresh S, Andrew, Elpiniki, Zhu, Ye, Li, Gen, Ipser, Jonathan, Hudson, Anna, Peverill, Matthew, Sambrook, Kelly, Gordon, Evan, Baugh, Lee, Forster, Gina, Simons, Raluca, Simons, Jeffrey, Magnotta, Vincent, Maron-Katz, Adi, du Plessis, Stefan, Disner, Seth, Davenport, Nicholas, Grupe, Dan, Nitschke, Jack, deRoon-Cassini, Terri A, Fitzgerald, Jacklynn, Krystal, John H, Levy, Ifat, Olff, Miranda, Veltman, Dick J, Wang, Li, Neria, Yuval, De Bellis, Michael D, Jovanovic, Tanja, Daniels, Judith K, Shenton, Martha, van de Wee, Nic J A, Schmahl, Christian, Kaufman, Milissa L, Rosso, Isabelle M, Sponheim, Scott R, Hofmann, David Bernd, Bryant, Richard A, Fercho, Kelene A, Stein, Dan J, Mueller, Sven C, Phan, Luan, McLaughlin, Katie A, Davidson, Richard J, Larson, Christine, May, Geoffrey, Nelson, Steven M, Abdallah, Chadi G, Gomaa, Hassaan, Etkin, Amit, Seedat, Soraya, Harpaz-Rotem, Ilan, Liberzon, Israel, Wang, Xin, Thompson, Paul M, Morey, Rajendra A, and Clinical Psychology and Experimental Psychopathology

Abstract

BACKGROUND: Posttraumatic stress disorder (PTSD) is accompanied by disrupted cortical neuroanatomy. We investigated alteration in covariance of structural networks associated with PTSD in regions that demonstrate the case-control differences in cortical thickness (CT) and surface area (SA). METHODS: Neuroimaging and clinical data were aggregated from 29 research sites in >1,300 PTSD cases and >2,000 trauma-exposed controls (age 6.2-85.2 years) by the ENIGMA-PGC PTSD working group. Cortical regions in the network were rank-ordered by effect size of PTSD-related cortical differences in CT and SA. The top-n (n = 2 to 148) regions with the largest effect size for PTSD > non-PTSD formed hypertrophic networks, the largest effect size for PTSD < non-PTSD formed atrophic networks, and the smallest effect size of between-group differences formed stable networks. The mean structural covariance (SC) of a given n-region network was the average of all positive pairwise correlations and was compared to the mean SC of 5,000 randomly generated n-region networks. RESULTS: Patients with PTSD, relative to non-PTSD controls, exhibited lower mean SC in CT-based and SA-based atrophic networks. Comorbid depression, sex and age modulated covariance differences of PTSD-related structural networks. CONCLUSIONS: Covariance of structural networks based on CT and cortical SA are affected by PTSD and further modulated by comorbid depression, sex, and age. The structural covariance networks that are perturbed in PTSD comport with converging evidence from resting state functional connectivity networks and networks impacted by inflammatory processes, and stress hormones in PTSD.

Published
2022

18. Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup

Author

Huggins, Ashley A., primary, Baird, C. Lexi, additional, Briggs, Melvin, additional, Laskowitz, Sarah, additional, Foudra, Samar, additional, Haswell, Courtney, additional, Sun, Delin, additional, Salminen, Lauren E., additional, Jahanshad, Neda, additional, Thomopoulos, Sophia I., additional, Veltman, Dick J., additional, Frijling, Jessie L., additional, Olff, Miranda, additional, van Zuiden, Mirjam, additional, Koch, Saskia B.J., additional, Nawjin, Laura, additional, Wang, Li, additional, Zhu, Ye, additional, Li, Gen, additional, Stein, Dan J., additional, Ipser, Johnathan, additional, Seedat, Soraya, additional, du Plessis, Stefan, additional, van den Heuvel, Leigh L., additional, Suarez-Jimenez, Benjamin, additional, Zhu, Xi, additional, Kim, Yoojean, additional, He, Xiaofu, additional, Zilcha-Mano, Sigal, additional, Lazarov, Amit, additional, Neria, Yuval, additional, Stevens, Jennifer S., additional, Ressler, Kerry J., additional, Jovanovic, Tanja, additional, van Rooij, Sanne JH, additional, Fani, Negar, additional, Hudson, Anna R., additional, Mueller, Sven C., additional, Sierk, Anika, additional, Manthey, Antje, additional, Walter, Henrik, additional, Daniels, Judith K., additional, Schmahl, Christian, additional, Herzog, Julia I., additional, Říha, Pavel, additional, Rektor, Ivan, additional, Lebois, Lauren A.M., additional, Kaufman, Milissa L., additional, Olson, Elizabeth A., additional, Baker, Justin T., additional, Rosso, Isabelle M., additional, King, Anthony P., additional, Liberzon, Isreal, additional, Angstadt, Mike, additional, Davenport, Nicholas D., additional, Sponheim, Scott R., additional, Disner, Seth G., additional, Straube, Thomas, additional, Hofmann, David, additional, Qi, Rongfeng, additional, Lu, Guang Ming, additional, Baugh, Lee A., additional, Forster, Gina L., additional, Simons, Raluca M., additional, Simons, Jeffrey S., additional, Magnotta, Vincent A., additional, Fercho, Kelene A., additional, Maron-Katz, Adi, additional, Etkin, Amit, additional, Cotton, Andrew S., additional, O’Leary, Erin N., additional, Xie, Hong, additional, Wang, Xin, additional, Quidé, Yann, additional, El-Hage, Wissam, additional, Lissek, Shmuel, additional, Berg, Hannah, additional, Bruce, Steven, additional, Cisler, Josh, additional, Ross, Marisa, additional, Herringa, Ryan J., additional, Grupe, Daniel W., additional, Nitschke, Jack B., additional, Davidson, Richard J., additional, Larson, Christine, additional, deRoon-Cassini, Terri A., additional, Tomas, Carissa W., additional, Fitzgerald, Jacklynn M., additional, Blackford, Jennifer Urbano, additional, Olatunji, Bunmi O., additional, Kremen, William S., additional, Lyons, Michael J., additional, Franz, Carol E., additional, Gordon, Evan M., additional, May, Geoffrey, additional, Nelson, Steven M., additional, Abdallah, Chadi G., additional, Levy, Ifat, additional, Harpaz-Rotem, Ilan, additional, Krystal, John H., additional, Dennis, Emily L., additional, Tate, David F., additional, Cifu, David X., additional, Walker, William C., additional, Wilde, Elizabeth A., additional, Harding, Ian H., additional, Kerestes, Rebecca, additional, Thompson, Paul M., additional, and Morey, Rajendra, additional

Published
2022
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22. Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups

Author

Clausen, Ashley N., primary, Fercho, Kelene A., additional, Monsour, Molly, additional, Disner, Seth, additional, Salminen, Lauren, additional, Haswell, Courtney C., additional, Rubright, Emily Clarke, additional, Watts, Amanda A., additional, Buckley, M. Nicole, additional, Maron‐Katz, Adi, additional, Sierk, Anika, additional, Manthey, Antje, additional, Suarez‐Jimenez, Benjamin, additional, Olatunji, Bunmi O., additional, Averill, Christopher L., additional, Hofmann, David, additional, Veltman, Dick J., additional, Olson, Elizabeth A., additional, Li, Gen, additional, Forster, Gina L., additional, Walter, Henrik, additional, Fitzgerald, Jacklynn, additional, Théberge, Jean, additional, Simons, Jeffrey S., additional, Bomyea, Jessica A., additional, Frijling, Jessie L., additional, Krystal, John H., additional, Baker, Justin T., additional, Phan, K. Luan, additional, Ressler, Kerry, additional, Han, Laura K. M., additional, Nawijn, Laura, additional, Lebois, Lauren A. M., additional, Schmaal, Lianne, additional, Densmore, Maria, additional, Shenton, Martha E., additional, Zuiden, Mirjam, additional, Stein, Murray, additional, Fani, Negar, additional, Simons, Raluca M., additional, Neufeld, Richard W. J., additional, Lanius, Ruth, additional, Rooij, Sanne, additional, Koch, Saskia B.J., additional, Bonomo, Serena, additional, Jovanovic, Tanja, additional, deRoon‐Cassini, Terri, additional, Ely, Timothy D., additional, Magnotta, Vincent A., additional, He, Xiaofu, additional, Abdallah, Chadi G., additional, Etkin, Amit, additional, Schmahl, Christian, additional, Larson, Christine, additional, Rosso, Isabelle M., additional, Blackford, Jennifer Urbano, additional, Stevens, Jennifer S., additional, Daniels, Judith K., additional, Herzog, Julia, additional, Kaufman, Milissa L., additional, Olff, Miranda, additional, Davidson, Richard J., additional, Sponheim, Scott R., additional, Mueller, Sven C., additional, Straube, Thomas, additional, Zhu, Xi, additional, Neria, Yuval, additional, Baugh, Lee A., additional, Cole, James H., additional, Thompson, Paul M., additional, and Morey, Rajendra A., additional

Published
2021
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23. Altered Neurotransmitter Ratio in the Prefrontal Cortex is Associated with Pain in Fibromyalgia Syndrome

Author

Bishop, James H., primary, Faerman, Afik, additional, Geoly, Andrew, additional, Khan, Naushaba, additional, Tischler, Claudia, additional, Amin, Heer, additional, Maron-Katz, Adi, additional, Azeez, Azeezat, additional, Yeomans, David C., additional, Hurd, Ralph, additional, Gu, Meng, additional, Baltusis, Laima, additional, Spielman, Daniel, additional, Sacchet, Matthew D., additional, Spiegel, David, additional, and Williams, Nolan, additional

Published
2021
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24. A Comparison of Methods to Harmonize Cortical Thickness Measurements Across Scanners and Sites

Author

Sun, Delin, primary, Rakesh, Gopalkumar, additional, Haswell, Courtney C., additional, Logue, Mark, additional, Lexi Baird, C., additional, O’Leary, Brian M., additional, Cotton, Andrew S., additional, Xie, Hong, additional, Tamburrino, Marijo, additional, Chen, Tian, additional, Dennis, Emily L., additional, Jahanshad, Neda, additional, Salminen, Lauren E., additional, Thomopoulos, Sophia I., additional, Rashid, Faisal, additional, Ching, Christopher R. K., additional, Koch, Saskia B. J., additional, Frijling, Jessie L., additional, Nawijn, Laura, additional, van Zuiden, Mirjam, additional, Zhu, Xi, additional, Suarez-Jimenez, Benjamin, additional, Sierk, Anika, additional, Walter, Henrik, additional, Manthey, Antje, additional, Stevens, Jennifer S., additional, Fani, Negar, additional, van Rooij, Sanne J.H., additional, Stein, Murray, additional, Bomyea, Jessica, additional, Koerte, Inga K., additional, Choi, Kyle, additional, van der Werff, Steven J.A., additional, Vermeiren, Robert R. J. M., additional, Herzog, Julia, additional, Lebois, Lauren A. M., additional, Baker, Justin T., additional, Olson, Elizabeth A., additional, Straube, Thomas, additional, Korgaonkar, Mayuresh S., additional, Andrew, Elpiniki, additional, Zhu, Ye, additional, Li, Gen, additional, Ipser, Jonathan, additional, Hudson, Anna R., additional, Peverill, Matthew, additional, Sambrook, Kelly, additional, Gordon, Evan, additional, Baugh, Lee, additional, Forster, Gina, additional, Simons, Raluca M., additional, Simons, Jeffrey S., additional, Magnotta, Vincent, additional, Maron-Katz, Adi, additional, du Plessis, Stefan, additional, Disner, Seth G., additional, Davenport, Nicholas, additional, Grupe, Daniel W., additional, Nitschke, Jack B., additional, deRoon-Cassini, Terri A., additional, Fitzgerald, Jacklynn M., additional, Krystal, John H., additional, Levy, Ifat, additional, Olff, Miranda, additional, Veltman, Dick J., additional, Wang, Li, additional, Neria, Yuval, additional, De Bellis, Michael D., additional, Jovanovic, Tanja, additional, Daniels, Judith K., additional, Shenton, Martha, additional, van de Wee, Nic J.A., additional, Schmahl, Christian, additional, Kaufman, Milissa L., additional, Rosso, Isabelle M., additional, Sponheim, Scott R., additional, Hofmann, David Bernd, additional, Bryant, Richard A., additional, Fercho, Kelene A., additional, Stein, Dan J., additional, Mueller, Sven C., additional, Hosseini, Bobak, additional, Luan Phan, K., additional, McLaughlin, Katie A., additional, Davidson, Richard J., additional, Larson, Christine L., additional, May, Geoffrey, additional, Nelson, Steven M., additional, Abdallah, Chadi G., additional, Gomaa, Hassaan, additional, Etkin, Amit, additional, Seedat, Soraya, additional, Harpaz-Rotem, Ilan, additional, Liberzon, Israel, additional, van Erp, Theo G.M., additional, Wang, Xin, additional, Thompson, Paul M., additional, and Morey, Rajendra A., additional

Published
2021
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25. Resolution limit-free community detection reveals unique patterns of resting-state network connectivity in posttraumatic stress disorder: A PGC-ENIGMA PTSD Consortium investigation

Author

Ross, Marisa C., primary, Cisler, Josh M., additional, Koch, Saskia B.J., additional, Olff, Miranda, additional, Veltman, Dick J., additional, Nawijn, Laura, additional, Frijling, Jessie L., additional, van Zuiden, Mirjam, additional, Zhu, Xi, additional, Neria, Yuval, additional, Suarez-Jimenez, Benjamin, additional, Wager, Tor, additional, Haswell, Courtney, additional, De Bellis, Michael D., additional, Rubright, Emily Clarke, additional, Stevens, Jennifer S., additional, van Rooij, Sanne J.H., additional, Fani, Negar, additional, Jovanovic, Tanja, additional, Ressler, Kerry J., additional, Daniels, Judith K., additional, Walter, Henrik, additional, Manthey, Antje, additional, Sierk, Anika, additional, Riha, Pavel, additional, Rektor, Ivan, additional, Davidson, Richard, additional, Nitschke, Jack B., additional, Grupe, Dan, additional, Larson, Christine, additional, deRoon-Cassini, Terri, additional, Fitzgerald, Jacklynn, additional, Huggins, Ashley, additional, Weis, Carissa, additional, Lanius, Ruth, additional, Densmore, Maria, additional, Lebois, Lauren A. M., additional, Kaufman, Milissa L., additional, Baker, Justin T., additional, Straube, Thomas, additional, Neumeister, Paula, additional, Hofmann, David, additional, Etkin, Amit, additional, Maron-Katz, Adi, additional, King, Anthony, additional, Liberzon, Israel, additional, Angstadt, Michael, additional, Herringa, Ryan, additional, Wang, Xin, additional, Chen, Tian, additional, Cotton, Andrew, additional, O’Leary, Brian, additional, Xie, Hong, additional, Disner, Seth, additional, Davenport, Nicholas, additional, Hage, Wissam El, additional, Quidé, Yann, additional, Geuze, Elbert, additional, Kennis, Mitzy, additional, Gordon, Evan, additional, May, Geoffery, additional, Nelson, Steven, additional, Jia-Richards, Meilin, additional, Bruce, Steven, additional, Veer, Ilya, additional, Waller, Lea, additional, Berg, Hannah, additional, Lissek, Shmuel, additional, Morey, Rajendra A., additional, and Sponheim, Scott, additional

Published
2021
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26. Structural Covariance Networks in Post-Traumatic Stress Disorder: A Multisite ENIGMA-PGC Study

Author

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

Published
2021
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27. Identification of psychiatric disorder subtypes from functional connectivity patterns in resting-state electroencephalography

Author

Zhang, Yu, primary, Wu, Wei, additional, Toll, Russell T., additional, Naparstek, Sharon, additional, Maron-Katz, Adi, additional, Watts, Mallissa, additional, Gordon, Joseph, additional, Jeong, Jisoo, additional, Astolfi, Laura, additional, Shpigel, Emmanuel, additional, Longwell, Parker, additional, Sarhadi, Kamron, additional, El-Said, Dawlat, additional, Li, Yuanqing, additional, Cooper, Crystal, additional, Chin-Fatt, Cherise, additional, Arns, Martijn, additional, Goodkind, Madeleine S., additional, Trivedi, Madhukar H., additional, Marmar, Charles R., additional, and Etkin, Amit, additional

Published
2020
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29. Individual Patterns of Abnormality in Resting-State Functional Connectivity Reveal Two Data-Driven PTSD Subgroups

Author

Maron-Katz, Adi, primary, Zhang, Yu, additional, Narayan, Manjari, additional, Wu, Wei, additional, Toll, Russell T., additional, Naparstek, Sharon, additional, De Los Angeles, Carlo, additional, Longwell, Parker, additional, Shpigel, Emmanuel, additional, Newman, Jennifer, additional, Abu-Amara, Duna, additional, Marmar, Charles, additional, and Etkin, Amit, additional

Published
2020
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30. Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups.

Author

Clausen, Ashley N., Fercho, Kelene A., Monsour, Molly, Disner, Seth, Salminen, Lauren, Haswell, Courtney C., Rubright, Emily Clarke, Watts, Amanda A., Buckley, M. Nicole, Maron‐Katz, Adi, Sierk, Anika, Manthey, Antje, Suarez‐Jimenez, Benjamin, Olatunji, Bunmi O., Averill, Christopher L., Hofmann, David, Veltman, Dick J., Olson, Elizabeth A., Li, Gen, and Forster, Gina L.

Published
2022
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32. Predicting risk for Alcohol Use Disorder using longitudinal data with multimodal biomarkers and family history: a machine learning study

Author

Kinreich, Sivan, primary, Meyers, Jacquelyn L., additional, Maron-Katz, Adi, additional, Kamarajan, Chella, additional, Pandey, Ashwini K., additional, Chorlian, David B., additional, Zhang, Jian, additional, Pandey, Gayathri, additional, Subbie-Saenz de Viteri, Stacey, additional, Pitti, Dan, additional, Anokhin, Andrey P., additional, Bauer, Lance, additional, Hesselbrock, Victor, additional, Schuckit, Marc A., additional, Edenberg, Howard J., additional, and Porjesz, Bernice, additional

Published
2019
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35. EXPANDER – an integrative program suite for microarray data analysis

Author

Shiloh Yosef, Sharan Roded, Steinfeld Israel, Linhart Chaim, Tanay Amos, Maron-Katz Adi, Shamir Ron, and Elkon Ran

Subjects
Computer applications to medicine. Medical informatics, R858-859.7, Biology (General), QH301-705.5
Abstract

Abstract Background Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis. Results Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER) software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO) and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms. Conclusion EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander

Published
2005
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42. 473. Failure to Downregulate Amygdala Activation during Regulation of Emotional Conflict in Post Traumatic Stress Disorder: Results from a Large Veteran Sample

Author

Chick, Christina, primary, de los Angeles, Carlo, additional, Patenaude, Brian, additional, Longwell, Parker, additional, Shpigel, Emmanuel, additional, Gonzalez, Bryan, additional, Durkin, Kathleen, additional, Chen, Jingyun, additional, Abu Amara, Duna, additional, Hart, Roland, additional, Mann, Silas, additional, Maron-Katz, Adi, additional, Marmar, Charles, additional, and Etkin, Amit, additional

Published
2017
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44. The EXPANDER Integrated Platform for Transcriptome Analysis.

Author

Hait, Tom Aharon, Maron-Katz, Adi, Sagir, Dorit, Amar, David, Ulitsky, Igor, Linhart, Chaim, Tanay, Amos, Sharan, Roded, Shiloh, Yosef, Elkon, Ran, and Shamir, Ron

Subjects
*GENE expression profiling, *GENE regulatory networks, *GENE expression, *CELL analysis, *INTEGRATED software
Abstract

Genome-wide analysis of cellular transcriptomes using RNA-seq or expression arrays is a major mainstay of current biological and biomedical research. EXPANDER (EXPression ANalyzer and DisplayER) is a comprehensive software package for analysis of expression data, with built-in support for 18 different organisms. It is designed as a "one-stop shop" platform for transcriptomic analysis, allowing for execution of all analysis steps starting with gene expression data matrix. Analyses offered include low-level preprocessing and normalization, differential expression analysis, clustering, bi-clustering, supervised grouping, high-level functional and pathway enrichment tests, and networks and motif analyses. A variety of options is offered for each step, using established algorithms, including many developed and published by our laboratory. EXPANDER has been continuously developed since 2003, having to date over 18,000 downloads and 540 citations. One of the innovations in the recent version is support for combined analysis of gene expression and ChIP-seq data to enhance the inference of transcriptional networks and their functional interpretation. EXPANDER implements cutting-edge algorithms and makes them accessible to users through user-friendly interface and intuitive visualizations. It is freely available to users at http://acgt.cs.tau.ac.il/expander/. Unlabelled Image • Gene expression profiling is a central omics technique, and functional interpretation of the data is a key challenge. • EXPANDER is a "one-stop-shop" platform for analysis of gene expression, available as RNA-seq or microarray data. • EXPANDER integrates all analysis steps from normalization through differential analysis, clustering, functional enrichment to network, and motif analyses. • EXPANDER combines the analysis of gene expression and ChIP-seq data. • EXPANDER has built-in support for 18 organisms. [ABSTRACT FROM AUTHOR]

Published
2019
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