Search

Your search keyword '"Stein, Dan J."' showing total 6,055 results
Start Over Author "Stein, Dan J."
6,055 results on '"Stein, Dan J."'

3. 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, Brain Disorders, Neurosciences, Mental Illness, Mind and Body, Behavioral and Social Science, Mental Health, Anxiety Disorders, Post-Traumatic Stress Disorder (PTSD), 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

7. A Pregnancy and Childhood Epigenetics Consortium (PACE) meta-analysis highlights potential relationships between birth order and neonatal blood DNA methylation

Author

Li, Shaobo, Spitz, Natalia, Ghantous, Akram, Abrishamcar, Sarina, Reimann, Brigitte, Marques, Irene, Silver, Matt J, Aguilar-Lacasaña, Sofía, Kitaba, Negusse, Rezwan, Faisal I, Röder, Stefan, Sirignano, Lea, Tuhkanen, Johanna, Mancano, Giulia, Sharp, Gemma C, Metayer, Catherine, Morimoto, Libby, Stein, Dan J, Zar, Heather J, Alfano, Rossella, Nawrot, Tim, Wang, Congrong, Kajantie, Eero, Keikkala, Elina, Mustaniemi, Sanna, Ronkainen, Justiina, Sebert, Sylvain, Silva, Wnurinham, Vääräsmäki, Marja, Jaddoe, Vincent WV, Bernstein, Robin M, Prentice, Andrew M, Cosin-Tomas, Marta, Dwyer, Terence, Håberg, Siri Eldevik, Herceg, Zdenko, Magnus, Maria C, Munthe-Kaas, Monica Cheng, Page, Christian M, Völker, Maja, Gilles, Maria, Send, Tabea, Witt, Stephanie, Zillich, Lea, Gagliardi, Luigi, Richiardi, Lorenzo, Czamara, Darina, Räikkönen, Katri, Chatzi, Lida, Vafeiadi, Marina, Arshad, S Hasan, Ewart, Susan, Plusquin, Michelle, Felix, Janine F, Moore, Sophie E, Vrijheid, Martine, Holloway, John W, Karmaus, Wilfried, Herberth, Gunda, Zenclussen, Ana, Streit, Fabian, Lahti, Jari, Hüls, Anke, Hoang, Thanh T, London, Stephanie J, and Wiemels, Joseph L

Subjects
Reproductive Medicine, Biomedical and Clinical Sciences, Genetics, Biological Sciences, Human Genome, Contraception/Reproduction, Pediatric, Clinical Research, Perinatal Period - Conditions Originating in Perinatal Period, 2.1 Biological and endogenous factors, Aetiology, Reproductive health and childbirth, Good Health and Well Being, Child, Female, Humans, Infant, Newborn, Pregnancy, Birth Order, DNA Methylation, Epigenesis, Genetic, Epigenomics, Biological sciences, Biomedical and clinical sciences
Abstract

Higher birth order is associated with altered risk of many disease states. Changes in placentation and exposures to in utero growth factors with successive pregnancies may impact later life disease risk via persistent DNA methylation alterations. We investigated birth order with Illumina DNA methylation array data in each of 16 birth cohorts (8164 newborns) with European, African, and Latino ancestries from the Pregnancy and Childhood Epigenetics Consortium. Meta-analyzed data demonstrated systematic DNA methylation variation in 341 CpGs (FDR adjusted P

Published
2024

8. DenseNet and Support Vector Machine classifications of major depressive disorder using vertex-wise cortical features

Author

Belov, Vladimir, Erwin-Grabner, Tracy, Zeng, Ling-Li, Ching, Christopher R. K., Aleman, Andre, Amod, Alyssa R., Basgoze, Zeynep, Benedetti, Francesco, Besteher, Bianca, Brosch, Katharina, Bülow, Robin, Colle, Romain, Connolly, Colm G., Corruble, Emmanuelle, Couvy-Duchesne, Baptiste, Cullen, Kathryn, Dannlowski, Udo, Davey, Christopher G., Dols, Annemiek, Ernsting, Jan, Evans, Jennifer W., Fisch, Lukas, Fuentes-Claramonte, Paola, Gonul, Ali Saffet, Gotlib, Ian H., Grabe, Hans J., Groenewold, Nynke A., Grotegerd, Dominik, Hahn, Tim, Hamilton, J. Paul, Han, Laura K. M., Harrison, Ben J, Ho, Tiffany C., Jahanshad, Neda, Jamieson, Alec J., Karuk, Andriana, Kircher, Tilo, Klimes-Dougan, Bonnie, Koopowitz, Sheri-Michelle, Lancaster, Thomas, Leenings, Ramona, Li, Meng, Linden, David E. J., MacMaster, Frank P., Mehler, David M. A., Meinert, Susanne, Melloni, Elisa, Mueller, Bryon A., Mwangi, Benson, Nenadić, Igor, Ojha, Amar, Okamoto, Yasumasa, Oudega, Mardien L., Penninx, Brenda W. J. H., Poletti, Sara, Pomarol-Clotet, Edith, Portella, Maria J., Pozzi, Elena, Radua, Joaquim, Rodríguez-Cano, Elena, Sacchet, Matthew D., Salvador, Raymond, Schrantee, Anouk, Sim, Kang, Soares, Jair C., Solanes, Aleix, Stein, Dan J., Stein, Frederike, Stolicyn, Aleks, Thomopoulos, Sophia I., Toenders, Yara J., Uyar-Demir, Aslihan, Vieta, Eduard, Vives-Gilabert, Yolanda, Völzke, Henry, Walter, Martin, Whalley, Heather C., Whittle, Sarah, Winter, Nils, Wittfeld, Katharina, Wright, Margaret J., Wu, Mon-Ju, Yang, Tony T., Zarate, Carlos, Veltman, Dick J., Schmaal, Lianne, Thompson, Paul M., and Goya-Maldonado, Roberto

Subjects
Quantitative Biology - Quantitative Methods, Computer Science - Machine Learning, Quantitative Biology - Neurons and Cognition
Abstract

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even today, researchers debate if morphological alterations in the brain are linked to MDD, likely due to the heterogeneity of this disorder. The application of deep learning tools to neuroimaging data, capable of capturing complex non-linear patterns, has the potential to provide diagnostic and predictive biomarkers for MDD. However, previous attempts to demarcate MDD patients and healthy controls (HC) based on segmented cortical features via linear machine learning approaches have reported low accuracies. In this study, we used globally representative data from the ENIGMA-MDD working group containing an extensive sample of people with MDD (N=2,772) and HC (N=4,240), which allows a comprehensive analysis with generalizable results. Based on the hypothesis that integration of vertex-wise cortical features can improve classification performance, we evaluated the classification of a DenseNet and a Support Vector Machine (SVM), with the expectation that the former would outperform the latter. As we analyzed a multi-site sample, we additionally applied the ComBat harmonization tool to remove potential nuisance effects of site. We found that both classifiers exhibited close to chance performance (balanced accuracy DenseNet: 51%; SVM: 53%), when estimated on unseen sites. Slightly higher classification performance (balanced accuracy DenseNet: 58%; SVM: 55%) was found when the cross-validation folds contained subjects from all sites, indicating site effect. In conclusion, the integration of vertex-wise morphometric features and the use of the non-linear classifier did not lead to the differentiability between MDD and HC. Our results support the notion that MDD classification on this combination of features and classifiers is unfeasible.

Published
2023

9. Cognitive Science and Psychiatry: An overview

Author

Stein, Dan J.

Subjects
Psychology: Clinical Psychology, Psychology: Cognitive Psychology, Clinical Psychology, Cognitive Psychology
Abstract

Cognitive science is a multidisciplinary field, comprising cognitive psychology, artificial intelligence, linguistics, neuroscience, and anthropology. In recent years, cognitive science has become a predominant paradigm in studies of the mind. This paper reviews work at the emerging interface between cognitive science and psychiatry. It is argued that cognitive science has significant potential as an integrative framework for theorizing and researching psychiatric disorders and their treatment.

Published
1992

10. Schemas in the Cognitive and Clinical Sciences: An Integrative Construct

Author

Stein, Dan J.

Subjects
Psychology: Clinical Psychology, Psychology: Cognitive Psychology, Clinical Psychology, Cognitive Psychology
Abstract

This paper is concerned in general with the intersection of cognitive and clinical science and in particular with schema theory. The use of schema theory in the various subdisciplines of cognitive science, as well as by cognitive-behavioral clinicians and psychoanalytically oriented clinicians is reviewed. It is argued that schema theory, in both cognitive and clinical sciences, allows a focus on mental structures their biological basis, their development and change, and on the way in which they direct psychological events. Schema theory not only enables important advances in different clinical schools, but it allows central clinical themes to be tackled in convergent ways. It is concluded that the schema construct allows integration within cognitive science, within the clinic, and between the two.

Published
1992

11. Genome-wide association analyses identify 95 risk loci and provide insights into the neurobiology of post-traumatic stress disorder

Author

Nievergelt, Caroline M., Maihofer, Adam X., Atkinson, Elizabeth G., Chen, Chia-Yen, Choi, Karmel W., Coleman, Jonathan R. I., Daskalakis, Nikolaos P., Duncan, Laramie E., Polimanti, Renato, Aaronson, Cindy, Amstadter, Ananda B., Andersen, Soren B., Andreassen, Ole A., Arbisi, Paul A., Ashley-Koch, Allison E., Austin, S. Bryn, Avdibegoviç, Esmina, Babić, Dragan, Bacanu, Silviu-Alin, Baker, Dewleen G., Batzler, Anthony, Beckham, Jean C., Belangero, Sintia, Benjet, Corina, Bergner, Carisa, Bierer, Linda M., Biernacka, Joanna M., Bierut, Laura J., Bisson, Jonathan I., Boks, Marco P., Bolger, Elizabeth A., Brandolino, Amber, Breen, Gerome, Bressan, Rodrigo Affonseca, Bryant, Richard A., Bustamante, Angela C., Bybjerg-Grauholm, Jonas, Bækvad-Hansen, Marie, Børglum, Anders D., Børte, Sigrid, Cahn, Leah, Calabrese, Joseph R., Caldas-de-Almeida, Jose Miguel, Chatzinakos, Chris, Cheema, Sheraz, Clouston, Sean A. P., Colodro-Conde, Lucía, Coombes, Brandon J., Cruz-Fuentes, Carlos S., Dale, Anders M., Dalvie, Shareefa, Davis, Lea K., Deckert, Jürgen, Delahanty, Douglas L., Dennis, Michelle F., Desarnaud, Frank, DiPietro, Christopher P., Disner, Seth G., Docherty, Anna R., Domschke, Katharina, Dyb, Grete, Kulenović, Alma Džubur, Edenberg, Howard J., Evans, Alexandra, Fabbri, Chiara, Fani, Negar, Farrer, Lindsay A., Feder, Adriana, Feeny, Norah C., Flory, Janine D., Forbes, David, Franz, Carol E., Galea, Sandro, Garrett, Melanie E., Gelaye, Bizu, Gelernter, Joel, Geuze, Elbert, Gillespie, Charles F., Goleva, Slavina B., Gordon, Scott D., Goçi, Aferdita, Grasser, Lana Ruvolo, Guindalini, Camila, Haas, Magali, Hagenaars, Saskia, Hauser, Michael A., Heath, Andrew C., Hemmings, Sian M. J., Hesselbrock, Victor, Hickie, Ian B., Hogan, Kelleigh, Hougaard, David Michael, Huang, Hailiang, Huckins, Laura M., Hveem, Kristian, Jakovljević, Miro, Javanbakht, Arash, Jenkins, Gregory D., Johnson, Jessica, Jones, Ian, Jovanovic, Tanja, Karstoft, Karen-Inge, Kaufman, Milissa L., Kennedy, James L., Kessler, Ronald C., Khan, Alaptagin, Kimbrel, Nathan A., King, Anthony P., Koen, Nastassja, Kotov, Roman, Kranzler, Henry R., Krebs, Kristi, Kremen, William S., Kuan, Pei-Fen, Lawford, Bruce R., Lebois, Lauren A. M., Lehto, Kelli, Levey, Daniel F., Lewis, Catrin, Liberzon, Israel, Linnstaedt, Sarah D., Logue, Mark W., Lori, Adriana, Lu, Yi, Luft, Benjamin J., Lupton, Michelle K., Luykx, Jurjen J., Makotkine, Iouri, Maples-Keller, Jessica L., Marchese, Shelby, Marmar, Charles, Martin, Nicholas G., Martínez-Levy, Gabriela A., McAloney, Kerrie, McFarlane, Alexander, McLaughlin, Katie A., McLean, Samuel A., Medland, Sarah E., Mehta, Divya, Meyers, Jacquelyn, Michopoulos, Vasiliki, Mikita, Elizabeth A., Milani, Lili, Milberg, William, Miller, Mark W., Morey, Rajendra A., Morris, Charles Phillip, Mors, Ole, Mortensen, Preben Bo, Mufford, Mary S., Nelson, Elliot C., Nordentoft, Merete, Norman, Sonya B., Nugent, Nicole R., O’Donnell, Meaghan, Orcutt, Holly K., Pan, Pedro M., Panizzon, Matthew S., Pathak, Gita A., Peters, Edward S., Peterson, Alan L., Peverill, Matthew, Pietrzak, Robert H., Polusny, Melissa A., Porjesz, Bernice, Powers, Abigail, Qin, Xue-Jun, Ratanatharathorn, Andrew, Risbrough, Victoria B., Roberts, Andrea L., Rothbaum, Alex O., Rothbaum, Barbara O., Roy-Byrne, Peter, Ruggiero, Kenneth J., Rung, Ariane, Runz, Heiko, Rutten, Bart P. F., de Viteri, Stacey Saenz, Salum, Giovanni Abrahão, Sampson, Laura, Sanchez, Sixto E., Santoro, Marcos, Seah, Carina, Seedat, Soraya, Seng, Julia S., Shabalin, Andrey, Sheerin, Christina M., Silove, Derrick, Smith, Alicia K., Smoller, Jordan W., Sponheim, Scott R., Stein, Dan J., Stensland, Synne, Stevens, Jennifer S., Sumner, Jennifer A., Teicher, Martin H., Thompson, Wesley K., Tiwari, Arun K., Trapido, Edward, Uddin, Monica, Ursano, Robert J., Valdimarsdóttir, Unnur, Van Hooff, Miranda, Vermetten, Eric, Vinkers, Christiaan H., Voisey, Joanne, Wang, Yunpeng, Wang, Zhewu, Waszczuk, Monika, Weber, Heike, Wendt, Frank R., Werge, Thomas, Williams, Michelle A., Williamson, Douglas E., Winsvold, Bendik S., Winternitz, Sherry, Wolf, Christiane, Wolf, Erika J., Xia, Yan, Xiong, Ying, Yehuda, Rachel, Young, Keith A., Young, Ross McD, Zai, Clement C., Zai, Gwyneth C., Zervas, Mark, Zhao, Hongyu, Zoellner, Lori A., Zwart, John-Anker, deRoon-Cassini, Terri, van Rooij, Sanne J. H., van den Heuvel, Leigh L., Stein, Murray B., Ressler, Kerry J., and Koenen, Karestan C.

Published
2024
Full Text
View/download PDF

12. White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

Author

Kim, Bo-Gyeom, Kim, Gakyung, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargalló, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolín, Sara, Beucke, Jan Carl, Bollettini, Irene, Brem, Silvia, Brennan, Brian P., Buitelaar, Jan K., Calvo, Rosa, Castelo-Branco, Miguel, Cheng, Yuqi, Chhatkuli, Ritu Bhusal, Ciullo, Valentina, Coelho, Ana, Couto, Beatriz, Dallaspezia, Sara, Ely, Benjamin A., Ferreira, Sónia, Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael, Gruner, Patricia, Hagen, Kristen, Hansen, Bjarne, Hanna, Gregory L., Hirano, Yoshiyuki, Höxter, Marcelo Q., Hough, Morgan, Hu, Hao, Huyser, Chaim, Ikuta, Toshikazu, Jahanshad, Neda, James, Anthony, Jaspers-Fayer, Fern, Kasprzak, Selina, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Lee, Junhee, Lochner, Christine, Lu, Jin, Manrique, Daniela Rodriguez, Martínez-Zalacaín, Ignacio, Masuda, Yoshitada, Matsumoto, Koji, Maziero, Maria Paula, Menchón, Jose M., Minuzzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Narayanaswamy, Janardhanan C., Narumoto, Jin, Ortiz, Ana E., Ota, Junko, Pariente, Jose C., Perriello, Chris, Picó-Pérez, Maria, Pittenger, Christopher, Poletti, Sara, Real, Eva, Reddy, Y. C. Janardhan, van Rooij, Daan, Sakai, Yuki, Sato, João Ricardo, Segalas, Cinto, Shavitt, Roseli G., Shen, Zonglin, Shimizu, Eiji, Shivakumar, Venkataram, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Sousa, Mafalda Machado, Spalletta, Gianfranco, Stern, Emily R., Stewart, S. Evelyn, Szeszko, Philip R., Thomas, Rajat, Thomopoulos, Sophia I., Vecchio, Daniela, Venkatasubramanian, Ganesan, Vriend, Chris, Walitza, Susanne, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij, Xu, Jian, Yamada, Kei, Yun, Je-Yeon, Zarei, Mojtaba, Zhao, Qing, Zhu, Xi, Thompson, Paul M., Bruin, Willem B., van Wingen, Guido A., Piras, Federica, Piras, Fabrizio, Stein, Dan J., van den Heuvel, Odile A., Simpson, Helen Blair, Marsh, Rachel, and Cha, Jiook

Published
2024
Full Text
View/download PDF

13. Age of onset of obsessive-compulsive disorder differentially affects white matter microstructure

Author

Vriend, Chris, de Joode, Niels T., Pouwels, Petra J. W., Liu, Feng, Otaduy, Maria C. G., Pastorello, Bruno, Robertson, Frances C., Ipser, Jonathan, Lee, Seonjoo, Hezel, Dianne M., van Meter, Page E., Batistuzzo, Marcelo C., Hoexter, Marcelo Q., Sheshachala, Karthik, Narayanaswamy, Janardhanan C., Venkatasubramanian, Ganesan, Lochner, Christine, Miguel, Euripedes C., Reddy, Y. C. Janardhan, Shavitt, Roseli G., Stein, Dan J., Wall, Melanie, Simpson, Helen Blair, and van den Heuvel, Odile A.

Published
2024
Full Text
View/download PDF

20. Multi-ancestry genome-wide association study of major depression aids locus discovery, fine mapping, gene prioritization and causal inference

Author

Meng, Xiangrui, Navoly, Georgina, Giannakopoulou, Olga, Levey, Daniel F., Koller, Dora, Pathak, Gita A., Koen, Nastassja, Lin, Kuang, Adams, Mark J., Rentería, Miguel E., Feng, Yanzhe, Gaziano, J. Michael, Stein, Dan J., Zar, Heather J., Campbell, Megan L., van Heel, David A., Trivedi, Bhavi, Finer, Sarah, McQuillin, Andrew, Bass, Nick, Chundru, V. Kartik, Martin, Hilary C., Huang, Qin Qin, Valkovskaya, Maria, Chu, Chia-Yi, Kanjira, Susan, Kuo, Po-Hsiu, Chen, Hsi-Chung, Tsai, Shih-Jen, Liu, Yu-Li, Kendler, Kenneth S., Peterson, Roseann E., Cai, Na, Fang, Yu, Sen, Srijan, Scott, Laura J., Burmeister, Margit, Loos, Ruth J. F., Preuss, Michael H., Actkins, Ky’Era V., Davis, Lea K., Uddin, Monica, Wani, Agaz H., Wildman, Derek E., Aiello, Allison E., Ursano, Robert J., Kessler, Ronald C., Kanai, Masahiro, Okada, Yukinori, Sakaue, Saori, Rabinowitz, Jill A., Maher, Brion S., Uhl, George, Eaton, William, Cruz-Fuentes, Carlos S., Martinez-Levy, Gabriela A., Campos, Adrian I., Millwood, Iona Y., Chen, Zhengming, Li, Liming, Wassertheil-Smoller, Sylvia, Jiang, Yunxuan, Tian, Chao, Martin, Nicholas G., Mitchell, Brittany L., Byrne, Enda M., Awasthi, Swapnil, Coleman, Jonathan R. I., Ripke, Stephan, Sofer, Tamar, Walters, Robin G., McIntosh, Andrew M., Polimanti, Renato, Dunn, Erin C., Stein, Murray B., Gelernter, Joel, Lewis, Cathryn M., and Kuchenbaecker, Karoline

Published
2024
Full Text
View/download PDF

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

Author

Yang, Jin, Huggins, Ashley A., Sun, Delin, Baird, C. Lexi, Haswell, Courtney C., Frijling, Jessie L., Olff, Miranda, van Zuiden, Mirjam, Koch, Saskia B. J., Nawijn, Laura, Veltman, Dick J., Suarez-Jimenez, Benjamin, Zhu, Xi, Neria, Yuval, Hudson, Anna R., Mueller, Sven C., Baker, Justin T., Lebois, Lauren A. M., Kaufman, Milissa L., Qi, Rongfeng, Lu, Guang Ming, Říha, Pavel, Rektor, Ivan, Dennis, Emily L., Ching, Christopher R. K., Thomopoulos, Sophia I., Salminen, Lauren E., Jahanshad, Neda, Thompson, Paul M., Stein, Dan J., Koopowitz, Sheri M., Ipser, Jonathan C., Seedat, Soraya, du Plessis, Stefan, van den Heuvel, Leigh L., Wang, Li, Zhu, Ye, Li, Gen, Sierk, Anika, Manthey, Antje, Walter, Henrik, Daniels, Judith K., Schmahl, Christian, Herzog, Julia I., Liberzon, Israel, King, Anthony, Angstadt, Mike, Davenport, Nicholas D., Sponheim, Scott R., Disner, Seth G., Straube, Thomas, Hofmann, David, Grupe, Daniel W., Nitschke, Jack B., Davidson, Richard J., Larson, Christine L., deRoon-Cassini, Terri A., Blackford, Jennifer U., Olatunji, Bunmi O., Gordon, Evan M., May, Geoffrey, Nelson, Steven M., Abdallah, Chadi G., Levy, Ifat, Harpaz-Rotem, Ilan, Krystal, John H., Morey, Rajendra A., and Sotiras, Aristeidis

Published
2024
Full Text
View/download PDF

23. Brain-based classification of youth with anxiety disorders: transdiagnostic examinations within the ENIGMA-Anxiety database using machine learning

Author

Bruin, Willem B., Zhutovsky, Paul, van Wingen, Guido A., Bas-Hoogendam, Janna Marie, Groenewold, Nynke A., Hilbert, Kevin, Winkler, Anderson M., Zugman, Andre, Agosta, Federica, Åhs, Fredrik, Andreescu, Carmen, Antonacci, Chase, Asami, Takeshi, Assaf, Michal, Barber, Jacques P., Bauer, Jochen, Bavdekar, Shreya Y., Beesdo-Baum, Katja, Benedetti, Francesco, Bernstein, Rachel, Björkstrand, Johannes, Blair, Robert J., Blair, Karina S., Blanco-Hinojo, Laura, Böhnlein, Joscha, Brambilla, Paolo, Bressan, Rodrigo A., Breuer, Fabian, Cano, Marta, Canu, Elisa, Cardinale, Elise M., Cardoner, Narcís, Cividini, Camilla, Cremers, Henk, Dannlowski, Udo, Diefenbach, Gretchen J., Domschke, Katharina, Doruyter, Alexander G. G., Dresler, Thomas, Erhardt, Angelika, Filippi, Massimo, Fonzo, Gregory A., Freitag, Gabrielle F., Furmark, Tomas, Ge, Tian, Gerber, Andrew J., Gosnell, Savannah N., Grabe, Hans J., Grotegerd, Dominik, Gur, Ruben C., Gur, Raquel E., Hamm, Alfons O., Han, Laura K. M., Harper, Jennifer C., Harrewijn, Anita, Heeren, Alexandre, Hofmann, David, Jackowski, Andrea P., Jahanshad, Neda, Jett, Laura, Kaczkurkin, Antonia N., Khosravi, Parmis, Kingsley, Ellen N., Kircher, Tilo, Kostic, Milutin, Larsen, Bart, Lee, Sang-Hyuk, Leehr, Elisabeth J., Leibenluft, Ellen, Lochner, Christine, Lui, Su, Maggioni, Eleonora, Manfro, Gisele G., Månsson, Kristoffer N. T., Marino, Claire E., Meeten, Frances, Milrod, Barbara, Jovanovic, Ana Munjiza, Mwangi, Benson, Myers, Michael J., Neufang, Susanne, Nielsen, Jared A., Ohrmann, Patricia A., Ottaviani, Cristina, Paulus, Martin P., Perino, Michael T., Phan, K. Luan, Poletti, Sara, Porta-Casteràs, Daniel, Pujol, Jesus, Reinecke, Andrea, Ringlein, Grace V., Rjabtsenkov, Pavel, Roelofs, Karin, Salas, Ramiro, Salum, Giovanni A., Satterthwaite, Theodore D., Schrammen, Elisabeth, Sindermann, Lisa, Smoller, Jordan W., Soares, Jair C., Stark, Rudolf, Stein, Frederike, Straube, Thomas, Straube, Benjamin, Strawn, Jeffrey R., Suarez-Jimenez, Benjamin, Sylvester, Chad M., Talati, Ardesheer, Thomopoulos, Sophia I., Tükel, Raşit, van Nieuwenhuizen, Helena, Werwath, Kathryn, Wittfeld, Katharina, Wright, Barry, Wu, Mon-Ju, Yang, Yunbo, Zilverstand, Anna, Zwanzger, Peter, Blackford, Jennifer U., Avery, Suzanne N., Clauss, Jacqueline A., Lueken, Ulrike, Thompson, Paul M., Pine, Daniel S., Stein, Dan J., van der Wee, Nic J. A., Veltman, Dick J., and Aghajani, Moji

Published
2024
Full Text
View/download PDF

24. A global multicohort study to map subcortical brain development and cognition in infancy and early childhood

Author

Alex, Ann M., Aguate, Fernando, Botteron, Kelly, Buss, Claudia, Chong, Yap-Seng, Dager, Stephen R., Donald, Kirsten A., Entringer, Sonja, Fair, Damien A., Fortier, Marielle V., Gaab, Nadine, Gilmore, John H., Girault, Jessica B., Graham, Alice M., Groenewold, Nynke A., Hazlett, Heather, Lin, Weili, Meaney, Michael J., Piven, Joseph, Qiu, Anqi, Rasmussen, Jerod M., Roos, Annerine, Schultz, Robert T., Skeide, Michael A., Stein, Dan J., Styner, Martin, Thompson, Paul M., Turesky, Ted K., Wadhwa, Pathik D., Zar, Heather J., Zöllei, Lilla, de los Campos, Gustavo, and Knickmeyer, Rebecca C.

Published
2024
Full Text
View/download PDF

25. Epigenome-wide meta-analysis of prenatal maternal stressful life events and newborn DNA methylation

Author

Kotsakis Ruehlmann, Anna, Sammallahti, Sara, Cortés Hidalgo, Andrea P., Bakulski, Kelly M., Binder, Elisabeth B., Campbell, Megan Loraine, Caramaschi, Doretta, Cecil, Charlotte A. M., Colicino, Elena, Cruceanu, Cristiana, Czamara, Darina, Dieckmann, Linda, Dou, John, Felix, Janine F., Frank, Josef, Håberg, Siri E., Herberth, Gunda, Hoang, Thanh T., Houtepen, Lotte C., Hüls, Anke, Koen, Nastassja, London, Stephanie J., Magnus, Maria C., Mancano, Giulia, Mulder, Rosa H., Page, Christian M., Räikkönen, Katri, Röder, Stefan, Schmidt, Rebecca J., Send, Tabea S., Sharp, Gemma, Stein, Dan J., Streit, Fabian, Tuhkanen, Johanna, Witt, Stephanie H., Zar, Heather J., Zenclussen, Ana C., Zhang, Yining, Zillich, Lea, Wright, Rosalind, Lahti, Jari, and Brunst, Kelly J.

Published
2023
Full Text
View/download PDF

26. Genetic Influences on the Developing Young Brain and Risk for Neuropsychiatric Disorders

Author

Alex, Ann M, Buss, Claudia, Davis, Elysia Poggi, de los Campos, Gustavo, Donald, Kirsten A, Fair, Damien A, Gaab, Nadine, Gao, Wei, Gilmore, John H, Girault, Jessica B, Grewen, Karen, Groenewold, Nynke A, Hankin, Benjamin L, Ipser, Jonathan, Kapoor, Shreya, Kim, Pilyoung, Lin, Weili, Luo, Shan, Norton, Elizabeth S, O’Connor, Thomas G, Piven, Joseph, Qiu, Anqi, Rasmussen, Jerod M, Skeide, Michael A, Stein, Dan J, Styner, Martin A, Thompson, Paul M, Wakschlag, Laurie, Knickmeyer, Rebecca, and group, for the ENIGMA ORIGINs

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Biological Psychology, Psychology, Pediatric Research Initiative, Genetic Testing, Brain Disorders, Clinical Research, Mental Health, Neurosciences, Intellectual and Developmental Disabilities (IDD), Pediatric, Prevention, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Female, Pregnancy, Child, Preschool, Humans, Brain, Mental Disorders, Neuroimaging, Phenotype, ENIGMA ORIGINs group, Childhood, Imaging, Infant, Magnetic resonance imaging, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

Imaging genetics provides an opportunity to discern associations between genetic variants and brain imaging phenotypes. Historically, the field has focused on adults and adolescents; very few imaging genetics studies have focused on brain development in infancy and early childhood (from birth to age 6 years). This is an important knowledge gap because developmental changes in the brain during the prenatal and early postnatal period are regulated by dynamic gene expression patterns that likely play an important role in establishing an individual's risk for later psychiatric illness and neurodevelopmental disabilities. In this review, we summarize findings from imaging genetics studies spanning from early infancy to early childhood, with a focus on studies examining genetic risk for neuropsychiatric disorders. We also introduce the Organization for Imaging Genomics in Infancy (ORIGINs), a working group of the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) consortium, which was established to facilitate large-scale imaging genetics studies in infancy and early childhood.

Published
2023

27. Decision-Making Tendencies and Voucher Spending Independently Support Abstinence Within Contingency Management for Methamphetamine Use Disorder

Author

Lake, Marilyn T, Krishnamurti, Tamar, Murtaugh, Kimberly Ling, van Nunen, Lara J, Stein, Dan J, and Shoptaw, Steven

Subjects
Biological Psychology, Psychology, Methamphetamine, Prevention, Clinical Research, Behavioral and Social Science, Good Health and Well Being, Adult, Humans, Male, Behavior Therapy, Gambling, Reinforcement, Psychology, Reward, decision-making, spending, contingency management, methamphetamine use disorder, behavioral economics, Pharmacology and Pharmaceutical Sciences, Substance Abuse, Pharmacology and pharmaceutical sciences, Biological psychology, Clinical and health psychology
Abstract

Decision-making tendencies and spending within cash voucher-based interventions have individually been shown to be related to future abstinence among participants with methamphetamine use disorder (MUD), but less is known of their independent contributions. This study of participants in a contingency management (CM) trial investigated whether decision-making and spending were each associated with future abstinence. Thirty-two outpatients with MUD, predominately male (68%) and mixed ancestry (94%) with a median age of 34 years, participated in an 8-week cash voucher-based CM pilot trial. Prior to commencing the trial, participants completed a computerized Iowa Gambling Task (IGT) to measure decision-making preferences for more frequent rewards and longer term gains of greater magnitude. Spending and abstinence of participants were tracked over the duration of the trial. In a secondary analysis, time-lagged counting process Cox Proportional Hazard models were conducted. Baseline decision-making, characterized by a preference for frequent rewards, was associated with a greater likelihood of future spending, Hazard Ratio; HR = 1.13 [1.06: 1.21]. Avoidance of short-term rewards to realize longer term, higher magnitude rewards, and spending at the prior visit were each associated with abstinence on the trial, HR = 1.12 [1.03: 1.22] and HR = 1.32 [1.08: 1.61], respectively. Controlling for decision-making, spending, and cumulative abstinence, prior abstinence remained the largest predictor of future abstinence, HR = 3.85 [2.88: 5.16]. Decision-making tendencies and spending are correlated yet independently associated with abstinence reinforcement in CM. Findings highlight the opportunity for behavioral treatment programs to tailor program structures to individual-specific characteristics. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Published
2023

29. Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures

Author

Belov, Vladimir, Erwin-Grabner, Tracy, Gonul, Ali Saffet, Amod, Alyssa R., Ojha, Amar, Aleman, Andre, Dols, Annemiek, Scharntee, Anouk, Uyar-Demir, Aslihan, Harrison, Ben J, Irungu, Benson M., Besteher, Bianca, Klimes-Dougan, Bonnie, Penninx, Brenda W. J. H., Mueller, Bryon A., Zarate, Carlos, Davey, Christopher G., Ching, Christopher R. K., Connolly, Colm G., Fu, Cynthia H. Y., Stein, Dan J., Dima, Danai, Linden, David E. J., Mehler, David M. A., Pomarol-Clotet, Edith, Pozzi, Elena, Melloni, Elisa, Benedetti, Francesco, MacMaster, Frank P., Grabe, Hans J., Völzke, Henry, Gotlib, Ian H., Soares, Jair C., Evans, Jennifer W., Sim, Kang, Wittfeld, Katharina, Cullen, Kathryn, Reneman, Liesbeth, Oudega, Mardien L., Wright, Margaret J., Portella, Maria J., Sacchet, Matthew D., Li, Meng, Aghajani, Moji, Wu, Mon-Ju, Jaworska, Natalia, Jahanshad, Neda, van der Wee, Nic J. A., Groenewold, Nynke, Hamilton, Paul J., Saemann, Philipp, Bülow, Robin, Poletti, Sara, Whittle, Sarah, Thomopoulos, Sophia I., van, Steven J. A., Werff, der, Koopowitz, Sheri-Michelle, Lancaster, Thomas, Ho, Tiffany C., Yang, Tony T., Basgoze, Zeynep, Veltman, Dick J., Schmaal, Lianne, Thompson, Paul M., and Goya-Maldonado, Roberto

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (n=5,356) to provide a generalizable ML classification benchmark of major depressive disorder (MDD). Using brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD vs healthy controls (HC) with around 62% balanced accuracy, but when harmonizing the data using ComBat balanced accuracy dropped to approximately 52%. Similar results were observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may achieve more encouraging prospects., Comment: main document 37 pages; supplementary material 24 pages

Published
2022

30. Psychological trauma and the genetic overlap between posttraumatic stress disorder and major depressive disorder

Author

Mundy, Jessica, Hübel, Christopher, Gelernter, Joel, Levey, Daniel, Murray, Robin M, Skelton, Megan, Stein, Murray B, Maihofer, Adam X, Nievergelt, Caroline M, Baker, Dewlen G, Risborough, Victoria B, Calabrese, Joseph R, Galea, Sandro, Stein, Dan J, Koen, Nastassja, Dalvie, Shareefa, Aiello, Allison E, Roberts, Andrea L, Koenen, KC, Solovieff, Nadia, Kranzler, Henry R, Zhao, Hongyu, Farrer, Lindsay A, Johnson, Eric Otto, Rice, John P, Bierut, Laura J, Saccone, Nancy L, McFarlane, Alexander, Forbes, David, Silove, Derrick, O'Donnell, Meaghan, Bryant, Richard A, van Hooff, Miranda, Sponheim, Scott R, Disner, Seth G, Pietrzak, Robert H, Chen, Chia-Yen, Smoller, Jordan W, Ursano, Robert J, Kessler, Ronald C, Junglen, Angela G, Delahanty, Douglas L, Amstadter, Ananda B, Sheerin, Christina M, Ruggiero, Ken, McLaughlin, Katie A, Peverill, Matthew, Caldas-de-Almeida, JM, Austin, S Bryn, Gelaye, Bizu, Williams, Michelle A, Sanchez, Sixto E, Franz, Carol E, Panizzon, Matthew S, Lyons, Michael J, Kremen, William S, Andreassen, Ole A, Dale, Anders M, Rutten, Bart PF, Vinkers, Christiaan, Schijven, Dick, Geuze, Elbert, Vermetten, Eric, Luykx, Jurjen J, Boks, Marco P, Ashley-Koch, Allison E, Beckham, Jean C, Garrett, Melanie E, Hauser, Michael A, Dennis, Michelle F, Kimbrel, Nathan A, Qin, Xue-Jun, Karstoft, Karen-Inge, Andersen, Soren B, Borglum, Anders D, Hougaard, David Michael, Bybjerg-Grauholm, Jonas, Duncan, Laramie E, Bµkvad-Hansen, Marie, Nordentoft, Merete, Mors, Ole, Mortensen, PB, Werge, Thomas, Thompson, Wesley K, Wang, Yunpeng, Heath, Andrew C, Nelson, Elliot C, Martin, Nicholas G, Gordon, Scott D, Wolf, Erika J, Logue, Mark W, Miller, Mark W, McGlinchey, Regina E, Milberg, William, Erbes, Christopher R, Polusny, Melissa A, Arbisi, Paul A, and Peterson, Alan L

Subjects
Prevention, Clinical Research, Genetics, Serious Mental Illness, Depression, Post-Traumatic Stress Disorder (PTSD), Mental Health, Brain Disorders, Anxiety Disorders, Major Depressive Disorder, Human Genome, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Good Health and Well Being, Posttraumatic stress disorder, major depressive disorder, psychological trauma, genetics, genetic correlations, polygenic risk scores, Million Veteran Program, Post Traumatic Stress Disorder Working Group of the Psychiatric Genomics Consortium, Neurosciences, Public Health and Health Services, Psychology, Psychiatry
Abstract

BackgroundPosttraumatic stress disorder (PTSD) and major depressive disorder (MDD) are commonly reported co-occurring mental health consequences of psychological trauma exposure. The disorders have high genetic overlap. Trauma is a complex phenotype but research suggests that trauma sensitivity has a heritable basis. We investigated whether sensitivity to trauma in those with MDD reflects a similar genetic component in those with PTSD.MethodsGenetic correlations between PTSD and MDD in individuals reporting trauma and MDD in individuals not reporting trauma were estimated, as well as with recurrent MDD and single-episode MDD, using genome-wide association study (GWAS) summary statistics. Genetic correlations were replicated using PTSD data from the Psychiatric Genomics Consortium and the Million Veteran Program. Polygenic risk scores were generated in UK Biobank participants who met the criteria for lifetime MDD (N = 29 471). We investigated whether genetic loading for PTSD was associated with reporting trauma in these individuals.ResultsGenetic loading for PTSD was significantly associated with reporting trauma in individuals with MDD [OR 1.04 (95% CI 1.01-1.07), Empirical-p = 0.02]. PTSD was significantly more genetically correlated with recurrent MDD than with MDD in individuals not reporting trauma (rg differences = ~0.2, p < 0.008). Participants who had experienced recurrent MDD reported significantly higher rates of trauma than participants who had experienced single-episode MDD (χ2 > 166, p < 0.001).ConclusionsOur findings point towards the existence of genetic variants associated with trauma sensitivity that might be shared between PTSD and MDD, although replication with better powered GWAS is needed. Our findings corroborate previous research highlighting trauma exposure as a key risk factor for recurrent MDD.

Published
2022

31. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses

Author

Banaj, Nerisa, Vecchio, Daniela, Piras, Fabrizio, De Rossi, Pietro, Bustillo, Juan, Ciufolini, Simone, Dazzan, Paola, Di Forti, Marta, Dickie, Erin W., Ford, Judith M., Fuentes-Claramonte, Paola, Gruber, Oliver, Guerrero-Pedraza, Amalia, Hamilton, Holly K., Howells, Fleur M., Kraemer, Bernd, Lawrie, Stephen M., Mathalon, Daniel H., Murray, Robin, Pomarol-Clotet, Edith, Potkin, Steven G., Preda, Adrian, Radua, Joaquim, Richter, Anja, Salvador, Raymond, Sawa, Akira, Scheffler, Freda, Sim, Kang, Spaniel, Filip, Stein, Dan J., Temmingh, Henk S., Thomopoulos, Sophia I., Tomecek, David, Uhlmann, Anne, Voineskos, Aristotle, Yang, Kun, Jahanshad, Neda, Thompson, Paul M., Van Erp, Theo G. M., Turner, Jessica A., Spalletta, Gianfranco, and Piras, Federica

Published
2023
Full Text
View/download PDF

32. The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Author

Bruin, Willem B., Abe, Yoshinari, Alonso, Pino, Anticevic, Alan, Backhausen, Lea L., Balachander, Srinivas, Bargallo, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolin Triquell, Sara, Brem, Silvia, Calesella, Federico, Couto, Beatriz, Denys, Damiaan A. J. P., Echevarria, Marco A. N., Eng, Goi Khia, Ferreira, Sónia, Feusner, Jamie D., Grazioplene, Rachael G., Gruner, Patricia, Guo, Joyce Y., Hagen, Kristen, Hansen, Bjarne, Hirano, Yoshiyuki, Hoexter, Marcelo Q., Jahanshad, Neda, Jaspers-Fayer, Fern, Kasprzak, Selina, Kim, Minah, Koch, Kathrin, Bin Kwak, Yoo, Kwon, Jun Soo, Lazaro, Luisa, Li, Chiang-Shan R., Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Menchon, Jose M., Moreira, Pedro S., Morgado, Pedro, Nakagawa, Akiko, Nakao, Tomohiro, Narayanaswamy, Janardhanan C., Nurmi, Erika L., Zorrilla, Jose C. Pariente, Piacentini, John, Picó-Pérez, Maria, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, Janardhan Y. C., Rodriguez-Manrique, Daniela, Sakai, Yuki, Shimizu, Eiji, Shivakumar, Venkataram, Simpson, Blair H., Soriano-Mas, Carles, Sousa, Nuno, Spalletta, Gianfranco, Stern, Emily R., Evelyn Stewart, S., Szeszko, Philip R., Tang, Jinsong, Thomopoulos, Sophia I., Thorsen, Anders L., Yoshida, Tokiko, Tomiyama, Hirofumi, Vai, Benedetta, Veer, Ilya M., Venkatasubramanian, Ganesan, Vetter, Nora C., Vriend, Chris, Walitza, Susanne, Waller, Lea, Wang, Zhen, Watanabe, Anri, Wolff, Nicole, Yun, Je-Yeon, Zhao, Qing, van Leeuwen, Wieke A., van Marle, Hein J. F., van de Mortel, Laurens A., van der Straten, Anouk, van der Werf, Ysbrand D., Thompson, Paul M., Stein, Dan J., van den Heuvel, Odile A., and van Wingen, Guido A.

Published
2023
Full Text
View/download PDF

34. 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

35. Multiscale neural gradients reflect transdiagnostic effects of major psychiatric conditions on cortical morphology

Author

Park, Bo-yong, Kebets, Valeria, Larivière, Sara, Hettwer, Meike D, Paquola, Casey, van Rooij, Daan, Buitelaar, Jan, Franke, Barbara, Hoogman, Martine, Schmaal, Lianne, Veltman, Dick J, van den Heuvel, Odile A, Stein, Dan J, Andreassen, Ole A, Ching, Christopher RK, Turner, Jessica A, van Erp, Theo GM, Evans, Alan C, Dagher, Alain, Thomopoulos, Sophia I, Thompson, Paul M, Valk, Sofie L, Kirschner, Matthias, and Bernhardt, Boris C

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Depression, Neurosciences, Behavioral and Social Science, Serious Mental Illness, Mental Health, Brain Disorders, Schizophrenia, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, Good Health and Well Being, Autism Spectrum Disorder, Connectome, Dopamine, Humans, Neural Pathways, Serotonin, Biological sciences, Biomedical and clinical sciences
Abstract

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability.

Published
2022

39. Exploratory study of ultraviolet B (UVB) radiation and age of onset of bipolar disorder

Author

Bauer, Michael, Glenn, Tasha, Achtyes, Eric D., Alda, Martin, Agaoglu, Esen, Altınbaş, Kürsat, Andreassen, Ole A., Angelopoulos, Elias, Ardau, Raffaella, Aydin, Memduha, Ayhan, Yavuz, Baethge, Christopher, Bauer, Rita, Baune, Bernhard T., Balaban, Ceylan, Becerra-Palars, Claudia, Behere, Aniruddh P., Behere, Prakash B., Belete, Habte, Belete, Tilahun, Belizario, Gabriel Okawa, Bellivier, Frank, Belmaker, Robert H., Benedetti, Francesco, Berk, Michael, Bersudsky, Yuly, Bicakci, Şule, Birabwa-Oketcho, Harriet, Bjella, Thomas D., Brady, Conan, Cabrera, Jorge, Cappucciati, Marco, Castro, Angela Marianne Paredes, Chen, Wei-Ling, Cheung, Eric Y. W., Chiesa, Silvia, Crowe, Marie, Cuomo, Alessandro, Dallaspezia, Sara, Del Zompo, Maria, Desai, Pratikkumar, Dodd, Seetal, Etain, Bruno, Fagiolini, Andrea, Fellendorf, Frederike T., Ferensztajn-Rochowiak, Ewa, Fiedorowicz, Jess G., Fountoulakis, Kostas N., Frye, Mark A., Geoffroy, Pierre A., Gitlin, Michael J., Gonzalez-Pinto, Ana, Gottlieb, John F., Grof, Paul, Haarman, Bartholomeus C. M., Harima, Hirohiko, Hasse-Sousa, Mathias, Henry, Chantal, Hoffding, Lone, Houenou, Josselin, Imbesi, Massimiliano, Isometsä, Erkki T., Ivkovic, Maja, Janno, Sven, Johnsen, Simon, Kapczinski, Flávio, Karakatsoulis, Gregory N., Kardell, Mathias, Kessing, Lars Vedel, Kim, Seong Jae, König, Barbara, Kot, Timur L., Koval, Michael, Kunz, Mauricio, Lafer, Beny, Landén, Mikael, Larsen, Erik R., Lenger, Melanie, Licht, Rasmus W., Lopez-Jaramillo, Carlos, MacKenzie, Alan, Madsen, Helle Østergaard, Madsen, Simone Alberte Kongstad A., Mahadevan, Jayant, Mahardika, Agustine, Manchia, Mirko, Marsh, Wendy, Martinez-Cengotitabengoa, Monica, Martini, Julia, Martiny, Klaus, Mashima, Yuki, McLoughlin, Declan M., Meesters, Ybe, Melle, Ingrid, Meza-Urzúa, Fátima, Mikolas, Pavol, Mok, Yee Ming, Monteith, Scott, Moorthy, Muthukumaran, Morken, Gunnar, Mosca, Enrica, Mozzhegorov, Anton A., Munoz, Rodrigo, Mythri, Starlin V., Nacef, Fethi, Nadella, Ravi K., Nakanotani, Takako, Nielsen, René Ernst, O’Donovan, Claire, Omrani, Adel, Osher, Yamima, Ouali, Uta, Pantovic-Stefanovic, Maja, Pariwatcharakul, Pornjira, Petite, Joanne, Petzold, Johannes, Pfennig, Andrea, Ruiz, Yolanda Pica, Pinna, Marco, Pompili, Maurizio, Porter, Richard J., Quiroz, Danilo, Rabelo-da-Ponte, Francisco Diego, Ramesar, Raj, Rasgon, Natalie, Ratta-apha, Woraphat, Ratzenhofer, Michaela, Redahan, Maria, Reddy, M. S., Reif, Andreas, Reininghaus, Eva Z., Richards, Jenny Gringer, Ritter, Philipp, Rybakowski, Janusz K., Sathyaputri, Leela, Scippa, Angela M., Simhandl, Christian, Smith, Daniel, Smith, José, Stackhouse, Jr, Paul W., Stein, Dan J., Stilwell, Kellen, Strejilevich, Sergio, Su, Kuan-Pin, Subramaniam, Mythily, Sulaiman, Ahmad Hatim, Suominen, Kirsi, Tanra, Andi J., Tatebayashi, Yoshitaka, Teh, Wen Lin, Tondo, Leonardo, Torrent, Carla, Tuinstra, Daniel, Uchida, Takahito, Vaaler, Arne E., Vieta, Eduard, Viswanath, Biju, Yoldi-Negrete, Maria, Yalcinkaya, Oguz Kaan, Young, Allan H., Zgueb, Yosra, and Whybrow, Peter C.

Published
2023
Full Text
View/download PDF

42. Determinants of effective treatment coverage for posttraumatic stress disorder: findings from the World Mental Health Surveys

Author

Stein, Dan J., Kazdin, Alan E., Munthali, Richard J., Hwang, Irving, Harris, Meredith G., Alonso, Jordi, Andrade, Laura Helena, Bruffaerts, Ronny, Cardoso, Graça, Chardoul, Stephanie, de Girolamo, Giovanni, Florescu, Silvia, Gureje, Oye, Haro, Josep Maria, Karam, Aimee N., Karam, Elie G., Kovess-Masfety, Viviane, Lee, Sing, Medina-Mora, Maria Elena, Navarro-Mateu, Fernando, Posada-Villa, José, Stagnaro, Juan Carlos, ten Have, Margreet, Sampson, Nancy A., Kessler, Ronald C., and Vigo, Daniel V.

Published
2023
Full Text
View/download PDF

44. Correction: White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group

Author

Kim, Bo-Gyeom, Kim, Gakyung, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie, Anticevic, Alan, Arnold, Paul D., Balachander, Srinivas, Banaj, Nerisa, Bargalló, Nuria, Batistuzzo, Marcelo C., Benedetti, Francesco, Bertolín, Sara, Beucke, Jan Carl, Bollettini, Irene, Brem, Silvia, Brennan, Brian P., Buitelaar, Jan K., Calvo, Rosa, Castelo-Branco, Miguel, Cheng, Yuqi, Chhatkuli, Ritu Bhusal, Ciullo, Valentina, Coelho, Ana, Couto, Beatriz, Dallaspezia, Sara, Ely, Benjamin A., Ferreira, Sónia, Fontaine, Martine, Fouche, Jean-Paul, Grazioplene, Rachael, Gruner, Patricia, Hagen, Kristen, Hansen, Bjarne, Hanna, Gregory L., Hirano, Yoshiyuki, Höxter, Marcelo Q., Hough, Morgan, Hu, Hao, Huyser, Chaim, Ikuta, Toshikazu, Jahanshad, Neda, James, Anthony, Jaspers-Fayer, Fern, Kasprzak, Selina, Kathmann, Norbert, Kaufmann, Christian, Kim, Minah, Koch, Kathrin, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Lee, Junhee, Lochner, Christine, Lu, Jin, Manrique, Daniela Rodriguez, Martínez-Zalacaín, Ignacio, Masuda, Yoshitada, Matsumoto, Koji, Maziero, Maria Paula, Menchón, Jose M., Minuzzi, Luciano, Moreira, Pedro Silva, Morgado, Pedro, Narayanaswamy, Janardhanan C., Narumoto, Jin, Ortiz, Ana E., Ota, Junko, Pariente, Jose C., Perriello, Chris, Picó-Pérez, Maria, Pittenger, Christopher, Poletti, Sara, Real, Eva, Reddy, Y. C. Janardhan, van Rooij, Daan, Sakai, Yuki, Sato, João Ricardo, Segalas, Cinto, Shavitt, Roseli G., Shen, Zonglin, Shimizu, Eiji, Shivakumar, Venkataram, Soreni, Noam, Soriano-Mas, Carles, Sousa, Nuno, Sousa, Mafalda Machado, Spalletta, Gianfranco, Stern, Emily R., Stewart, S. Evelyn, Szeszko, Philip R., Thomas, Rajat, Thomopoulos, Sophia I., Vecchio, Daniela, Venkatasubramanian, Ganesan, Vriend, Chris, Walitza, Susanne, Wang, Zhen, Watanabe, Anri, Wolters, Lidewij, Xu, Jian, Yamada, Kei, Yun, Je-Yeon, Zarei, Mojtaba, Zhao, Qing, Zhu, Xi, Thompson, Paul M., Bruin, Willem B., van Wingen, Guido A., Piras, Federica, Piras, Fabrizio, Stein, Dan J., van den Heuvel, Odile A., Simpson, Helen Blair, Marsh, Rachel, and Cha, Jiook

Published
2024
Full Text
View/download PDF

45. Event‐based modeling in temporal lobe epilepsy demonstrates progressive atrophy from cross‐sectional data

Author

Lopez, Seymour M, Aksman, Leon M, Oxtoby, Neil P, Vos, Sjoerd B, Rao, Jun, Kaestner, Erik, Alhusaini, Saud, Alvim, Marina, Bender, Benjamin, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Bonilha, Leonardo, Caciagli, Lorenzo, Caldairou, Benoit, Caligiuri, Maria Eugenia, Calvet, Angels, Cendes, Fernando, Concha, Luis, Conde‐Blanco, Estefania, Davoodi‐Bojd, Esmaeil, de Bézenac, Christophe, Delanty, Norman, Desmond, Patricia M, Devinsky, Orrin, Domin, Martin, Duncan, John S, Focke, Niels K, Foley, Sonya, Fortunato, Francesco, Galovic, Marian, Gambardella, Antonio, Gleichgerrcht, Ezequiel, Guerrini, Renzo, Hamandi, Khalid, Ives‐Deliperi, Victoria, Jackson, Graeme D, Jahanshad, Neda, Keller, Simon S, Kochunov, Peter, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Labate, Angelo, Larivière, Sara, Lenge, Matteo, Lui, Elaine, Malpas, Charles, Martin, Pascal, Mascalchi, Mario, Medland, Sarah E, Meletti, Stefano, Morita‐Sherman, Marcia E, Owen, Thomas W, Richardson, Mark, Riva, Antonella, Rüber, Theodor, Sinclair, Ben, Soltanian‐Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomopoulos, Sophia I, Thompson, Paul M, Tondelli, Manuela, Vaudano, Anna Elisabetta, Vivash, Lucy, Wang, Yujiang, Weber, Bernd, Whelan, Christopher D, Wiest, Roland, Winston, Gavin P, Yasuda, Clarissa Lin, McDonald, Carrie R, Alexander, Daniel C, Sisodiya, Sanjay M, Altmann, Andre, Bargalló, Núria, Bartolini, Emanuele, O’Brien, Terence J, and Thomas, Rhys H

Subjects
Brain Disorders, Epilepsy, Neurodegenerative, Neurosciences, Clinical Research, Biomedical Imaging, Aetiology, 2.1 Biological and endogenous factors, Neurological, Good Health and Well Being, Atrophy, Biomarkers, Cross-Sectional Studies, Epilepsy, Temporal Lobe, Hippocampus, Humans, Magnetic Resonance Imaging, Sclerosis, disease progression, duration of illness, event-based model, MTLE, patient staging, ENIGMA-Epilepsy Working Group, Clinical Sciences, Neurology & Neurosurgery
Abstract

ObjectiveRecent work has shown that people with common epilepsies have characteristic patterns of cortical thinning, and that these changes may be progressive over time. Leveraging a large multicenter cross-sectional cohort, we investigated whether regional morphometric changes occur in a sequential manner, and whether these changes in people with mesial temporal lobe epilepsy and hippocampal sclerosis (MTLE-HS) correlate with clinical features.MethodsWe extracted regional measures of cortical thickness, surface area, and subcortical brain volumes from T1-weighted (T1W) magnetic resonance imaging (MRI) scans collected by the ENIGMA-Epilepsy consortium, comprising 804 people with MTLE-HS and 1625 healthy controls from 25 centers. Features with a moderate case-control effect size (Cohen d ≥ .5) were used to train an event-based model (EBM), which estimates a sequence of disease-specific biomarker changes from cross-sectional data and assigns a biomarker-based fine-grained disease stage to individual patients. We tested for associations between EBM disease stage and duration of epilepsy, age at onset, and antiseizure medicine (ASM) resistance.ResultsIn MTLE-HS, decrease in ipsilateral hippocampal volume along with increased asymmetry in hippocampal volume was followed by reduced thickness in neocortical regions, reduction in ipsilateral thalamus volume, and finally, increase in ipsilateral lateral ventricle volume. EBM stage was correlated with duration of illness (Spearman ρ = .293, p = 7.03 × 10-16 ), age at onset (ρ = -.18, p = 9.82 × 10-7 ), and ASM resistance (area under the curve = .59, p = .043, Mann-Whitney U test). However, associations were driven by cases assigned to EBM Stage 0, which represents MTLE-HS with mild or nondetectable abnormality on T1W MRI.SignificanceFrom cross-sectional MRI, we reconstructed a disease progression model that highlights a sequence of MRI changes that aligns with previous longitudinal studies. This model could be used to stage MTLE-HS subjects in other cohorts and help establish connections between imaging-based progression staging and clinical features.

Published
2022

46. Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder

Author

Adamson, Chris, Adler, Sophie, Alexander-Bloch, Aaron F., Anagnostou, Evdokia, Anderson, Kevin M., Areces-Gonzalez, Ariosky, Astle, Duncan E., Auyeung, Bonnie, Ayub, Muhammad, Bae, Jong Bin, Ball, Gareth, Baron-Cohen, Simon, Beare, Richard, Bedford, Saashi A., Benegal, Vivek, Bethlehem, Richard A.I., Beyer, Frauke, Blangero, John, Cábez, Manuel Blesa, Boardman, James P., Borzage, Matthew, Bosch-Bayard, Jorge F., Bourke, Niall, Bullmore, Edward T., Calhoun, Vince D., Chakravarty, Mallar M., Chen, Christina, Chertavian, Casey, Chetelat, Gaël, Chong, Yap S., Corvin, Aiden, Costantino, Manuela, Courchesne, Eric, Crivello, Fabrice, Cropley, Vanessa L., Crosbie, Jennifer, Crossley, Nicolas, Delarue, Marion, Delorme, Richard, Desrivieres, Sylvane, Devenyi, Gabriel, Di Biase, Maria A., Dolan, Ray, Donald, Kirsten A., Donohoe, Gary, Dorfschmidt, Lena, Dunlop, Katharine, Edwards, Anthony D., Elison, Jed T., Ellis, Cameron T., Elman, Jeremy A., Eyler, Lisa, Fair, Damien A., Fletcher, Paul C., Fonagy, Peter, Franz, Carol E., Galan-Garcia, Lidice, Gholipour, Ali, Giedd, Jay, Gilmore, John H., Glahn, David C., Goodyer, Ian M., Grant, P.E., Groenewold, Nynke A., Gudapati, Shreya, Gunning, Faith M., Gur, Raquel E., Gur, Ruben C., Hammill, Christopher F., Hansson, Oskar, Hedden, Trey, Heinz, Andreas, Henson, Richard N., Heuer, Katja, Hoare, Jacqueline, Holla, Bharath, Holmes, Avram J., Huang, Hao, Ipser, Jonathan, Jack, Clifford R., Jr., Jackowski, Andrea P., Jia, Tianye, Jones, David T., Jones, Peter B., Kahn, Rene S., Karlsson, Hasse, Karlsson, Linnea, Kawashima, Ryuta, Kelley, Elizabeth A., Kern, Silke, Kim, Ki-Woong, Kitzbichler, Manfred G., Kremen, William S., Lalonde, François, Landeau, Brigitte, Lerch, Jason, Lewis, John D., Li, Jiao, Liao, Wei, Liston, Conor, Lombardo, Michael V., Lv, Jinglei, Mallard, Travis T., Marcelis, Machteld, Mathias, Samuel R., Mazoyer, Bernard, McGuire, Philip, Meaney, Michael J., Mechelli, Andrea, Misic, Bratislav, Morgan, Sarah E., Mothersill, David, Ortinau, Cynthia, Ossenkoppele, Rik, Ouyang, Minhui, Palaniyappan, Lena, Paly, Leo, Pan, Pedro M., Pantelis, Christos, Park, Min Tae M., Paus, Tomas, Pausova, Zdenka, Paz-Linares, Deirel, Binette, Alexa Pichet, Pierce, Karen, Qian, Xing, Qiu, Anqi, Raznahan, Armin, Rittman, Timothy, Rodrigue, Amanda, Rollins, Caitlin K., Romero-Garcia, Rafael, Ronan, Lisa, Rosenberg, Monica D., Rowitch, David H., Salum, Giovanni A., Satterthwaite, Theodore D., Schaare, H. Lina, Schabdach, Jenna, Schachar, Russell J., Schöll, Michael, Schultz, Aaron P., Seidlitz, Jakob, Sharp, David, Shinohara, Russell T., Skoog, Ingmar, Smyser, Christopher D., Sperling, Reisa A., Stein, Dan J., Stolicyn, Aleks, Suckling, John, Sullivan, Gemma, Thyreau, Benjamin, Toro, Roberto, Traut, Nicolas, Tsvetanov, Kamen A., Turk-Browne, Nicholas B., Tuulari, Jetro J., Tzourio, Christophe, Vachon-Presseau, Étienne, Valdes-Sosa, Mitchell J., Valdes-Sosa, Pedro A., Valk, Sofie L., van Amelsvoort, Therese, Vandekar, Simon N., Vasung, Lana, Vértes, Petra E., Victoria, Lindsay W., Villeneuve, Sylvia, Villringer, Arno, Vogel, Jacob W., Wagstyl, Konrad, Wang, Yin-Shan S., Warfield, Simon K., Warrier, Varun, Westman, Eric, Westwater, Margaret L., Whalley, Heather C., White, Simon R., Witte, A. Veronica, Yang, Ning, Yeo, B.T. Thomas, Yun, Hyuk Jin, Zalesky, Andrew, Zar, Heather J., Zettergren, Anna, Zhou, Juan H., Ziauddeen, Hisham, Zimmerman, Dabriel, Zugman, Andre, Zuo, Xi-Nian N., Ho, Natalie C.W., Nogovitsyn, Nikita, Metzak, Paul, Ballester, Pedro L., Hassel, Stefanie, Rotzinger, Susan, Poppenk, Jordan, Lam, Raymond W., Taylor, Valerie H., Milev, Roumen, Frey, Benicio N., Harkness, Kate L., Addington, Jean, and Kennedy, Sidney H.

Published
2024
Full Text
View/download PDF

48. Comparative effectiveness of remote digital gamified and group CBT skills training interventions for anxiety and depression among college students: Results of a three-arm randomised controlled trial

Author

Bantjes, Jason, Hunt, Xanthe, Cuijpers, Pim, Kazdin, Alan E., Kennedy, Chris J., Luedtke, Alex, Malenica, Ivana, Petukhova, Maria, Sampson, Nancy, Zainal, Nur Hani, Davids, Charl, Dunn-Coetzee, Munita, Gerber, Rone, Stein, Dan J., and Kessler, Ronald C.

Published
2024
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results