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1. Brain‐age prediction: Systematic evaluation of site effects, and sample age range and size

Author

Yu, Yuetong, Cui, Hao‐Qi, Haas, Shalaila S, New, Faye, Sanford, Nicole, Yu, Kevin, Zhan, Denghuang, Yang, Guoyuan, Gao, Jia‐Hong, Wei, Dongtao, Qiu, Jiang, Banaj, Nerisa, Boomsma, Dorret I, Breier, Alan, Brodaty, Henry, Buckner, Randy L, Buitelaar, Jan K, Cannon, Dara M, Caseras, Xavier, Clark, Vincent P, Conrod, Patricia J, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Davey, Christopher G, de Haan, Lieuwe, de Zubicaray, Greig I, Di Giorgio, Annabella, Fisch, Lukas, Fisher, Simon E, Franke, Barbara, Glahn, David C, Grotegerd, Dominik, Gruber, Oliver, Gur, Raquel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hatton, Sean, Hickie, Ian B, Pol, Hilleke E Hulshoff, Jamieson, Alec J, Jernigan, Terry L, Jiang, Jiyang, Kalnin, Andrew J, Kang, Sim, Kochan, Nicole A, Kraus, Anna, Lagopoulos, Jim, Lazaro, Luisa, McDonald, Brenna C, McDonald, Colm, McMahon, Katie L, Mwangi, Benson, Piras, Fabrizio, Rodriguez‐Cruces, Raul, Royer, Jessica, Sachdev, Perminder S, Satterthwaite, Theodore D, Saykin, Andrew J, Schumann, Gunter, Sevaggi, Pierluigi, Smoller, Jordan W, Soares, Jair C, Spalletta, Gianfranco, Tamnes, Christian K, Trollor, Julian N, Ent, Dennis Van't, Vecchio, Daniela, Walter, Henrik, Wang, Yang, Weber, Bernd, Wen, Wei, Wierenga, Lara M, Williams, Steven CR, Wu, Mon‐Ju, Zunta‐Soares, Giovana B, Bernhardt, Boris, Thompson, Paul, Frangou, Sophia, Ge, Ruiyang, and Group, ENIGMA‐Lifespan Working

Subjects
Biological Psychology, Psychology, Neurosciences, Clinical Research, Aging, Mental health, Neurological, Humans, Adolescent, Female, Aged, Adult, Child, Young Adult, Male, Brain, Aged, 80 and over, Child, Preschool, Middle Aged, Magnetic Resonance Imaging, Neuroimaging, Sample Size, benchmarking, brain aging, brainAGE, ENIGMA‐Lifespan Working Group, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

Published
2024

2. In vivo hippocampal subfield volumes in bipolar disorder—A mega‐analysis from The Enhancing Neuro Imaging Genetics through Meta‐Analysis Bipolar Disorder Working Group

Author

Haukvik, Unn K, Gurholt, Tiril P, Nerland, Stener, Elvsåshagen, Torbjørn, Akudjedu, Theophilus N, Alda, Martin, Alnæs, Dag, Alonso‐Lana, Silvia, Bauer, Jochen, Baune, Bernhard T, Benedetti, Francesco, Berk, Michael, Bettella, Francesco, Bøen, Erlend, Bonnín, Caterina M, Brambilla, Paolo, Canales‐Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Dandash, Orwa, Dannlowski, Udo, Delvecchio, Giuseppe, Díaz‐Zuluaga, Ana M, Erp, Theo GM, Fatjó‐Vilas, Mar, Foley, Sonya F, Förster, Katharina, Fullerton, Janice M, Goikolea, José M, Grotegerd, Dominik, Gruber, Oliver, Haarman, Bartholomeus CM, Haatveit, Beathe, Hajek, Tomas, Hallahan, Brian, Harris, Mathew, Hawkins, Emma L, Howells, Fleur M, Hülsmann, Carina, Jahanshad, Neda, Jørgensen, Kjetil N, Kircher, Tilo, Krämer, Bernd, Krug, Axel, Kuplicki, Rayus, Lagerberg, Trine V, Lancaster, Thomas M, Lenroot, Rhoshel K, Lonning, Vera, López‐Jaramillo, Carlos, Malt, Ulrik F, McDonald, Colm, McIntosh, Andrew M, McPhilemy, Genevieve, Meer, Dennis, Melle, Ingrid, Melloni, Elisa MT, Mitchell, Philip B, Nabulsi, Leila, Nenadić, Igor, Oertel, Viola, Oldani, Lucio, Opel, Nils, Otaduy, Maria CG, Overs, Bronwyn J, Pineda‐Zapata, Julian A, Pomarol‐Clotet, Edith, Radua, Joaquim, Rauer, Lisa, Redlich, Ronny, Repple, Jonathan, Rive, Maria M, Roberts, Gloria, Ruhe, Henricus G, Salminen, Lauren E, Salvador, Raymond, Sarró, Salvador, Savitz, Jonathan, Schene, Aart H, Sim, Kang, Soeiro‐de‐Souza, Marcio G, Stäblein, Michael, Stein, Dan J, Stein, Frederike, Tamnes, Christian K, Temmingh, Henk S, Thomopoulos, Sophia I, Veltman, Dick J, Vieta, Eduard, Waltemate, Lena, Westlye, Lars T, Whalley, Heather C, Sämann, Philipp G, Thompson, Paul M, Ching, Christopher RK, Andreassen, Ole A, Agartz, Ingrid, and Group, ENIGMA Bipolar Disorder Working

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Mental Health, Serious Mental Illness, Neurosciences, Biomedical Imaging, Bipolar Disorder, Mental health, Genetics, Hippocampus, Humans, Magnetic Resonance Imaging, Neuroimaging, ENIGMA Bipolar Disorder Working Group, bipolar disorder subtype, hippocampus, large-scale, lithium, psychosis, structural brain MRI, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.

Published
2022

3. Artificial intelligence for classification of temporal lobe epilepsy with ROI-level MRI data: A worldwide ENIGMA-Epilepsy study

Author

Gleichgerrcht, Ezequiel, Munsell, Brent C, Alhusaini, Saud, Alvim, Marina KM, Bargalló, Núria, Bender, Benjamin, Bernasconi, Andrea, Bernasconi, Neda, Bernhardt, Boris, Blackmon, Karen, Caligiuri, Maria Eugenia, Cendes, Fernando, Concha, Luis, Desmond, Patricia M, Devinsky, Orrin, Doherty, Colin P, Domin, Martin, Duncan, John S, Focke, Niels K, Gambardella, Antonio, Gong, Bo, Guerrini, Renzo, Hatton, Sean N, Kälviäinen, Reetta, Keller, Simon S, Kochunov, Peter, Kotikalapudi, Raviteja, Kreilkamp, Barbara AK, Labate, Angelo, Langner, Soenke, Larivière, Sara, Lenge, Matteo, Lui, Elaine, Martin, Pascal, Mascalchi, Mario, Meletti, Stefano, O'Brien, Terence J, Pardoe, Heath R, Pariente, Jose C, Rao, Jun Xian, Richardson, Mark P, Rodríguez-Cruces, Raúl, Rüber, Theodor, Sinclair, Ben, Soltanian-Zadeh, Hamid, Stein, Dan J, Striano, Pasquale, Taylor, Peter N, Thomas, Rhys H, Vaudano, Anna Elisabetta, Vivash, Lucy, von Podewills, Felix, Vos, Sjoerd B, Weber, Bernd, Yao, Yi, Yasuda, Clarissa Lin, Zhang, Junsong, Thompson, Paul M, Sisodiya, Sanjay M, McDonald, Carrie R, Bonilha, Leonardo, Group, ENIGMA-Epilepsy Working, Altmann, Andre, Depondt, Chantal, Galovic, Marian, Thomopoulos, Sophia I, and Wiest, Roland

Subjects
Biomedical Imaging, Neurodegenerative, Neurosciences, Brain Disorders, Prevention, Epilepsy, 2.1 Biological and endogenous factors, Aetiology, Neurological, Artificial Intelligence, Brain, Epilepsy, Temporal Lobe, Hippocampus, Humans, Magnetic Resonance Imaging, Sclerosis, Support Vector Machine, Temporal lobe epilepsy, Machine learning, Artificial inteligence, ENIGMA-Epilepsy Working Group
Abstract

Artificial intelligence has recently gained popularity across different medical fields to aid in the detection of diseases based on pathology samples or medical imaging findings. Brain magnetic resonance imaging (MRI) is a key assessment tool for patients with temporal lobe epilepsy (TLE). The role of machine learning and artificial intelligence to increase detection of brain abnormalities in TLE remains inconclusive. We used support vector machine (SV) and deep learning (DL) models based on region of interest (ROI-based) structural (n = 336) and diffusion (n = 863) brain MRI data from patients with TLE with ("lesional") and without ("non-lesional") radiographic features suggestive of underlying hippocampal sclerosis from the multinational (multi-center) ENIGMA-Epilepsy consortium. Our data showed that models to identify TLE performed better or similar (68-75%) compared to models to lateralize the side of TLE (56-73%, except structural-based) based on diffusion data with the opposite pattern seen for structural data (67-75% to diagnose vs. 83% to lateralize). In other aspects, structural and diffusion-based models showed similar classification accuracies. Our classification models for patients with hippocampal sclerosis were more accurate (68-76%) than models that stratified non-lesional patients (53-62%). Overall, SV and DL models performed similarly with several instances in which SV mildly outperformed DL. We discuss the relative performance of these models with ROI-level data and the implications for future applications of machine learning and artificial intelligence in epilepsy care.

Published
2021

4. Mapping Cortical and Subcortical Asymmetry in Obsessive-Compulsive Disorder: Findings From the ENIGMA Consortium

Author

Kong, Xiang-Zhen, Boedhoe, Premika SW, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Arnold, Paul D, Assogna, Francesca, Baker, Justin T, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Brennan, Brian P, Buitelaar, Jan, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Dallaspezia, Sara, Denys, Damiaan, Ely, Benjamin A, Feusner, Jamie, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Glahn, David C, Gruner, Patricia, Gürsel, Deniz A, Hauser, Tobias U, Hirano, Yoshiyuki, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, James, Anthony, Jaspers-Fayer, Fern, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kuno, Masaru, Kvale, Gerd, Kwon, Jun Soo, Lazaro, Luisa, Liu, Yanni, Lochner, Christine, Marques, Paulo, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Medland, Sarah E, Menchón, José M, Minuzzi, Luciano, Moreira, Pedro S, Morer, Astrid, Morgado, Pedro, Nakagawa, Akiko, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nurmi, Erika L, O'Neill, Joseph, Pariente, Jose C, Perriello, Chris, Piacentini, John, Piras, Fabrizio, Piras, Federica, Pittenger, Christopher, Reddy, YC Janardhan, Rus-Oswald, Oana Georgiana, Sakai, Yuki, Sato, Joao R, Schmaal, Lianne, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stern, Emily R, Stevens, Michael C, Stewart, S Evelyn, Szeszko, Philip R, Tolin, David F, Tsuchiyagaito, Aki, van Rooij, Daan, van Wingen, Guido A, Venkatasubramanian, Ganesan, Wang, Zhen, Yun, Je-Yeon, Group, ENIGMA OCD Working, Anticevic, Alan, Banaj, Nerisa, and Bargalló, Nuria

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Serious Mental Illness, Mental Health, Neurosciences, Brain Disorders, Clinical Research, Anxiety Disorders, Neurological, Mental health, Adult, Brain, Brain Mapping, Child, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Obsessive-Compulsive Disorder, Thalamus, Brain asymmetry, Laterality, Mega-analysis, Obsessive-compulsive disorder, Pallidum, ENIGMA OCD Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundLateralized dysfunction has been suggested in obsessive-compulsive disorder (OCD). However, it is currently unclear whether OCD is characterized by abnormal patterns of brain structural asymmetry. Here we carried out what is by far the largest study of brain structural asymmetry in OCD.MethodsWe studied a collection of 16 pediatric datasets (501 patients with OCD and 439 healthy control subjects), as well as 30 adult datasets (1777 patients and 1654 control subjects) from the OCD Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium. Asymmetries of the volumes of subcortical structures, and of measures of regional cortical thickness and surface areas, were assessed based on T1-weighted magnetic resonance imaging scans, using harmonized image analysis and quality control protocols. We investigated possible alterations of brain asymmetry in patients with OCD. We also explored potential associations of asymmetry with specific aspects of the disorder and medication status.ResultsIn the pediatric datasets, the largest case-control differences were observed for volume asymmetry of the thalamus (more leftward; Cohen's d = 0.19) and the pallidum (less leftward; d = -0.21). Additional analyses suggested putative links between these asymmetry patterns and medication status, OCD severity, or anxiety and depression comorbidities. No significant case-control differences were found in the adult datasets.ConclusionsThe results suggest subtle changes of the average asymmetry of subcortical structures in pediatric OCD, which are not detectable in adults with the disorder. These findings may reflect altered neurodevelopmental processes in OCD.

Published
2020

5. An Empirical Comparison of Meta- and Mega-Analysis With Data From the ENIGMA Obsessive-Compulsive Disorder Working Group

Author

Boedhoe, Premika SW, Heymans, Martijn W, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anticevic, Alan, Arnold, Paul D, Batistuzzo, Marcelo C, Benedetti, Francesco, Beucke, Jan C, Bollettini, Irene, Bose, Anushree, Brem, Silvia, Calvo, Anna, Calvo, Rosa, Cheng, Yuqi, Cho, Kang Ik K, Ciullo, Valentina, Dallaspezia, Sara, Denys, Damiaan, Feusner, Jamie D, Fitzgerald, Kate D, Fouche, Jean-Paul, Fridgeirsson, Egill A, Gruner, Patricia, Hanna, Gregory L, Hibar, Derrek P, Hoexter, Marcelo Q, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Kathmann, Norbert, Kaufmann, Christian, Koch, Kathrin, Kwon, Jun Soo, Lazaro, Luisa, Lochner, Christine, Marsh, Rachel, Martínez-Zalacaín, Ignacio, Mataix-Cols, David, Menchón, José M, Minuzzi, Luciano, Morer, Astrid, Nakamae, Takashi, Nakao, Tomohiro, Narayanaswamy, Janardhanan C, Nishida, Seiji, Nurmi, Erika L, O'Neill, Joseph, Piacentini, John, Piras, Fabrizio, Piras, Federica, Reddy, YC Janardhan, Reess, Tim J, Sakai, Yuki, Sato, Joao R, Simpson, H Blair, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Stevens, Michael C, Szeszko, Philip R, Tolin, David F, van Wingen, Guido A, Venkatasubramanian, Ganesan, Walitza, Susanne, Wang, Zhen, Yun, Je-Yeon, Working-Group, ENIGMA-OCD, Thompson, Paul M, Stein, Dan J, van den Heuvel, Odile A, and Twisk, Jos WR

Subjects
Biomedical and Clinical Sciences, Information and Computing Sciences, Neurosciences, Applied Computing, Machine Learning, neuroimaging, MRI, IPD meta-analysis, mega-analysis, linear mixed-effect models, ENIGMA-OCD Working-Group, Cognitive Sciences, Applied computing, Machine learning
Abstract

Objective: Brain imaging communities focusing on different diseases have increasingly started to collaborate and to pool data to perform well-powered meta- and mega-analyses. Some methodologists claim that a one-stage individual-participant data (IPD) mega-analysis can be superior to a two-stage aggregated data meta-analysis, since more detailed computations can be performed in a mega-analysis. Before definitive conclusions regarding the performance of either method can be drawn, it is necessary to critically evaluate the methodology of, and results obtained by, meta- and mega-analyses. Methods: Here, we compare the inverse variance weighted random-effect meta-analysis model with a multiple linear regression mega-analysis model, as well as with a linear mixed-effects random-intercept mega-analysis model, using data from 38 cohorts including 3,665 participants of the ENIGMA-OCD consortium. We assessed the effect sizes and standard errors, and the fit of the models, to evaluate the performance of the different methods. Results: The mega-analytical models showed lower standard errors and narrower confidence intervals than the meta-analysis. Similar standard errors and confidence intervals were found for the linear regression and linear mixed-effects random-intercept models. Moreover, the linear mixed-effects random-intercept models showed better fit indices compared to linear regression mega-analytical models. Conclusions: Our findings indicate that results obtained by meta- and mega-analysis differ, in favor of the latter. In multi-center studies with a moderate amount of variation between cohorts, a linear mixed-effects random-intercept mega-analytical framework appears to be the better approach to investigate structural neuroimaging data.

Published
2019

7. PRS Associations With Subcortical Volumes, Cortical Thickness and Surface Area in ENIGMA-OCD

Author

Dalvie, Shareefa, primary, Milaneschi, Yuri, additional, Mattheisen, Manuel, additional, Yu, Dongmei, additional, Strom, Nora, additional, Gruner, Patricia, additional, Hoexter, Marcelo, additional, Lazaro, Luisa, additional, Walitza, Susanne, additional, Grunblatt, Edna, additional, Menchon, Jose, additional, Soriano-Mas, Carles, additional, Thompson, Paul M., additional, van den Heuvel, Odile, additional, Stein, Dan J., additional, and Group, ENIGMA-OCD Working, additional

Published
2023
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8. ENIGMA-Anxiety Specific Phobia

Author

Hilbert, Kevin, Groenewold, Nynke, Bas-Hoogendam, Janna Marie, Jahanshad, Neda, Thompson, Paul, group, ENIGMA, Stein, Dan, van der Wee, Nic, and Lueken, Ulrike

Published
2022
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9. ENIGMA generalized anxiety disorder

Author

Harrewijn, Anita, Cardinale, Elise, Bas-Hoogendam, Janna Marie, Groenewold, Nynke, Stein, Dan, van der Wee, Nic, Buckner, Randy, Fonzo, Gregory, Manfro, Gisele, Mwangi, Benson, Nielsen, Jared, Paulus, Martin, Salum, Giovanni, Jordan Smoller, ScD, Soares, Jair, Stein, Murray, Strawn, Jeffrey, Wu, Mon-Ju, group, ENIGMA, Thompson, Paul, Winkler, Anderson, and Pine, Daniel

Subjects
endocrine system
Abstract

Comparing cortical and subcortical brain structure between patients with generalized anxiety disorder and healthy comparison subjects – findings from the ENIGMA Generalized Anxiety Disorder Working Group

Published
2022
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11. Effects of copy number variations on brain structure and risk for psychiatric illness: Large-scale studies from the ENIGMA working groups on CNVs

Author

Sønderby, Ida E, Ching, Christopher R K, Ayesa-Arriola, Rosa, Thompson, Paul M, Bearden, Carrie E, Andreassen, Ole A, Group, ENIGMA-CNV Working, 2 Deletion Syndrome Working Group, ENIGMA 22q11., Bernard, Manon, Blackburn, Nicholas B, Bøen, Rune, de Geus, Eco, de Zwarte, Sonja M C, Bakker, Geor, Forti, Marta Di, Frei, Oleksandr, Fukunaga, Masaki, Hehir-Kwa, Jayne Y, Hillegers, Manon H J, Hoffmann, Per, Homuth, Georg, Jahanshad, Neda, Koops, Sanne, Kumar, Kuldeep, Bassett, Anne S, Kikuchi, Masataka, Le Hellard, Stephanie, Leu, Costin, Murray, Robin M, Naerland, Terje, Nyberg, Lars, Ophoff, Roel A, Pike, G Bruce, Sando, Sigrid B, Shin, Jean, Boomsma, Dorret I, Shumskaya, Elena, Sisodiya, Sanjay M, Steen, Vidar M, Teumer, Alexander, Uhlmann, Anne, Wright, Margaret J, Antshel, Kevin M, Campbell, Linda E, Crossley, Nicolas A, Crowley, T Blaine, Bülow, Robin, Daly, Eileen, Fiksinski, Ania M, Forsyth, Jennifer K, Fremont, Wanda, Goodrich-Hunsaker, Naomi J, Gudbrandsen, Maria, Jonas, Rachel K, Kates, Wendy R, Lin, Amy, McCabe, Kathryn L, Butcher, Nancy J, Moss, Hayley, Murphy, Declan G, Murphy, Kieran C, Owen, Michael J, Ruparel, Kosha, Simon, Tony J, van Amelsvoort, Therese, Vorstman, Jacob A S, Calhoun, Vince D, Caspers, Svenja, Chow, Eva W C, Cichon, Sven, Thomopoulos, Sophia I, Ciufolini, Simone, Craig, Michael C, Crespo-Facorro, Benedicto, Cunningham, Adam C, Dale, Anders M, Dazzan, Paola, de Zubicaray, Greig I, Djurovic, Srdjan, Doherty, Joanne L, Donohoe, Gary, van der Meer, Dennis, Draganski, Bogdan, Durdle, Courtney A, Ehrlich, Stefan, Emanuel, Beverly S, Espeseth, Thomas, Fisher, Simon E, Ge, Tian, Glahn, David C, Grabe, Hans J, Gur, Raquel E, Sun, Daqiang, Gutman, Boris A, Haavik, Jan, Håberg, Asta K, Hansen, Laura A, Hashimoto, Ryota, Hibar, Derrek P, Holmes, Avram J, Hottenga, Jouke-Jan, Hulshoff Pol, Hilleke E, Jalbrzikowski, Maria, Villalon-Reina, Julio E, Knowles, Emma E M, Kushan, Leila, Linden, David E J, Liu, Jingyu, Lundervold, Astri J, Martin-Brevet, Sandra, Martínez, Kenia, Mather, Karen A, Mathias, Samuel R, McDonald-McGinn, Donna M, Agartz, Ingrid, McRae, Allan F, Medland, Sarah E, Moberget, Torgeir, Modenato, Claudia, Monereo Sánchez, Jennifer, Moreau, Clara A, Mühleisen, Thomas W, Paus, Tomas, Pausova, Zdenka, Prieto, Carlos, Amunts, Katrin, Ragothaman, Anjanibhargavi, Reinbold, Céline S, Reis Marques, Tiago, Repetto, Gabriela M, Reymond, Alexandre, Roalf, David R, Rodriguez-Herreros, Borja, Rucker, James J, Sachdev, Perminder S, Schmitt, James E, Arango, Celso, Schofield, Peter R, Silva, Ana I, Stefansson, Hreinn, Stein, Dan J, Tamnes, Christian K, Tordesillas-Gutiérrez, Diana, Ulfarsson, Magnus O, Vajdi, Ariana, van 't Ent, Dennis, van den Bree, Marianne B M, Armstrong, Nicola J, Vassos, Evangelos, Vázquez-Bourgon, Javier, Vila-Rodriguez, Fidel, Walters, G Bragi, Wen, Wei, Westlye, Lars T, Wittfeld, Katharina, Zackai, Elaine H, Stefánsson, Kári, Jacquemont, Sebastien, the ENIGMA-CNV Working Group, the ENIGMA 22q11.2 Deletion Syndrome Working Group, Stochastics, Biological Psychology, APH - Mental Health, APH - Methodology, APH - Personalized Medicine, APH - Health Behaviors & Chronic Diseases, ENIGMA-CNV Working Group, ENIGMA 22q11.2 Deletion Syndrome Working Group, and Universidad de Cantabria

Subjects
Review Article, genetics [Mental Disorders], 0302 clinical medicine, genetics-first approach, pathology [Brain], Multicenter Studies as Topic, Copy-number variation, Review Articles, education.field_of_study, brain structural imaging, Radiological and Ultrasound Technology, genetics [Neurodevelopmental Disorders], Mental Disorders, neurodevelopmental disorders, 05 social sciences, growth & development [Brain], Brain, pathology [Mental Disorders], Cognition, Human brain, diffusion tensor imaging, Magnetic Resonance Imaging, diagnostic imaging [Neurodevelopmental Disorders], medicine.anatomical_structure, psychiatric disorders, Neurology, Anatomy, medicine.medical_specialty, Brain development, DNA Copy Number Variations, Population, Neuroimaging, Biology, 050105 experimental psychology, 03 medical and health sciences, evolution, medicine, pathology [Neurodevelopmental Disorders], Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Deletion syndrome, copy number variant, ddc:610, genetics‐first approach, education, Psychiatry, diagnostic imaging [Brain], Neurology (clinical), Working group, 030217 neurology & neurosurgery, diagnostic imaging [Mental Disorders]
Abstract

The Enhancing NeuroImaging Genetics through Meta‐Analysis copy number variant (ENIGMA‐CNV) and 22q11.2 Deletion Syndrome Working Groups (22q‐ENIGMA WGs) were created to gain insight into the involvement of genetic factors in human brain development and related cognitive, psychiatric and behavioral manifestations. To that end, the ENIGMA‐CNV WG has collated CNV and magnetic resonance imaging (MRI) data from ~49,000 individuals across 38 global research sites, yielding one of the largest studies to date on the effects of CNVs on brain structures in the general population. The 22q‐ENIGMA WG includes 12 international research centers that assessed over 533 individuals with a confirmed 22q11.2 deletion syndrome, 40 with 22q11.2 duplications, and 333 typically developing controls, creating the largest‐ever 22q11.2 CNV neuroimaging data set. In this review, we outline the ENIGMA infrastructure and procedures for multi‐site analysis of CNVs and MRI data. So far, ENIGMA has identified effects of the 22q11.2, 16p11.2 distal, 15q11.2, and 1q21.1 distal CNVs on subcortical and cortical brain structures. Each CNV is associated with differences in cognitive, neurodevelopmental and neuropsychiatric traits, with characteristic patterns of brain structural abnormalities. Evidence of gene‐dosage effects on distinct brain regions also emerged, providing further insight into genotype–phenotype relationships. Taken together, these results offer a more comprehensive picture of molecular mechanisms involved in typical and atypical brain development. This “genotype‐first” approach also contributes to our understanding of the etiopathogenesis of brain disorders. Finally, we outline future directions to better understand effects of CNVs on brain structure and behavior., The enhancing neuroimaging genetics through meta‐analysis (ENIGMA) copy number variant (CNV) and 22q11.2 Working Groups focus on gaining insight into how rare genetic variants affect human brain development, cognition, and behavior. The two ENIGMA working groups have collated CNV and brain‐imaging data from numerous individuals, gathered by numerous international research centers, and analyzed this data with standardized processing and analysis pipelines. Future directions for the ENIGMA CNV and 22q11.2 working groups are to analyze CNVs with larger sample sizes and more imaging modalities to better understand how rare genetic variants affect the brain, and their clinical and behavioral consequences.

Published
2021

12. ENIGMA Mega-Analysis of Brain Structure in Generalized Anxiety Disorder

Author

Harrewijn, Anita, primary, Cardinale, Elise M., additional, Groenewold, Nynke, additional, Bas-Hoogendam, Janna Marie, additional, Aghajani, Moji, additional, Working group, ENIGMA-GAD, additional, Veltman, Dick, additional, Thompson, Paul M., additional, Stein, Dan J., additional, van der Wee, Nic.J.A., additional, Winkler, Anderson, additional, and Pine, Daniel, additional

Published
2020
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13. Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium

Author

Kong, Xiang-Zhen, Mathias, Samuel R, Francks, Clyde, Grabe, Hans, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K, Harris, Mathew A, Hartman, Catharina A, Hernández, Maria Del Carmen Valdés, Heslenfeld, Dirk, Hester, Robert, Hibar, Derrek Paul, Ho, Beng-Choon, Ho, Tiffany C, Hoekstra, Pieter J, van Holst, Ruth J, Hoogman, Martine, Høvik, Marie F, Howells, Fleur M, Hugdahl, Kenneth, Huyser, Chaim, Ingvar, Martin, Irwin, Lourdes, Ishikawa, Akari, James, Anthony, Jahanshad, Neda, Jernigan, Terry L, Jönsson, Erik G, Guadalupe, Tulio, Kähler, Claas, Kaleda, Vasily, Kelly, Clare, Kerich, Michael, Keshavan, Matcheri S, Khadka, Sabin, Kircher, Tilo, Kohls, Gregor, Konrad, Kerstin, Korucuoglu, Ozlem, Abé, Christoph, Krämer, Bernd, Krug, Axel, Kwon, Jun Soo, Lambregts-Rommelse, Nanda, Landén, Mikael, Lázaro, Luisa, Lebedeva, Irina, Lenroot, Rhoshel, Lesch, Klaus-Peter, Li, Qinqin, Agartz, Ingrid, Lim, Kelvin O, Liu, Jia, Lochner, Christine, London, Edythe D, Lonning, Vera, Lorenzetti, Valentina, Luciano, Michelle, Luijten, Maartje, Lundervold, Astri J, Mackey, Scott, Akudjedu, Theophilus N, MacMaster, Frank P, Maingault, Sophie, Malpas, Charles B, Malt, Ulrik F, Mataix-Cols, David, Martin-Santos, Rocio, Mayer, Andrew R, McCarthy, Hazel, Mitchell, Philip B, Mueller, Bryon A, Aleman, Andre, Maniega, Susana Muñoz, Mazoyer, Bernard, McDonald, Colm, McLellan, Quinn, McMahon, Katie L, McPhilemy, Genevieve, Momenan, Reza, Morales, Angelica M, Narayanaswamy, Janardhanan C, Moreira, José Carlos Vasques, Alhusaini, Saud, Nerland, Stener, Nestor, Liam, Newman, Erik, Nigg, Joel T, Nordvik, Jan Egil, Novotny, Stephanie, Weiss, Eileen Oberwelland, O'Gorman, Ruth L, Oosterlaan, Jaap, Oranje, Bob, Allen, Nicholas B, Orr, Catherine, Overs, Bronwyn, Pauli, Paul, Paulus, Martin, Plessen, Kerstin Jessica, von Polier, Georg G, Pomarol-Clotet, Edith, Portella, Maria J, Qiu, Jiang, Radua, Joaquim, Ames, David, Ramos-Quiroga, Josep Antoni, Reddy, Y C Janardhan, Reif, Andreas, Roberts, Gloria, Rosa, Pedro, Rubia, Katya, Sacchet, Matthew D, Sachdev, Perminder S, Salvador, Raymond, Schmaal, Lianne, Andreassen, Ole A, Schulte-Rüther, Martin, Schweren, Lizanne, Seidman, Larry, Seitz, Jochen, Serpa, Mauricio Henriques, Shaw, Philip, Shumskaya, Elena, Silk, Timothy J, Simmons, Alan N, Simulionyte, Egle, Vasquez, Alejandro Arias, Sinha, Rajita, Sjoerds, Zsuzsika, Smelror, Runar Elle, Soliva, Joan Carlos, Solowij, Nadia, Souza-Duran, Fabio Luisde, Sponheim, Scott R, Stein, Dan J, Stein, Elliot A, Stevens, Michael, Armstrong, Nicola J, Strike, Lachlan T, Sudre, Gustavo, Sui, Jing, Tamm, Leanne, Temmingh, Hendrik S, Thoma, Robert J, Tomyshev, Alexander, Tronchin, Giulia, Turner, Jessica, Uhlmann, Anne, Bergo, Felipe, van Erp, Theo G M, van den Heuvel, Odile A, van der Meer, Dennis, van Eijk, Liza, Vance, Alasdair, Veer, Ilya M, Veltman, Dick J, Venkatasubramanian, Ganesan, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Bastin, Mark E, Voineskos, Aristotle N, Völzke, Henry, Vuletic, Daniella, Walitza, Susanne, Walter, Henrik, Walton, Esther, Wardlaw, Joanna M, Wen, Wei, Westlye, Lars T, Whelan, Christopher D, Batalla, Albert, White, Tonya, Wiers, Reinout W, Wright, Margaret J, Wittfeld, Katharina, Yang, Tony T, Yasuda, Clarissa L, Yoncheva, Yuliya, Yücel, Murat, Yun, Je-Yeon, Zanetti, Marcus Vinicius, Bauer, Jochen, Zhen, Zonglei, Zhu, Xing-Xing, Ziegler, Georg C, Zierhut, Kathrin, de Zubicaray, Greig I, Zwiers, Marcel, Glahn, David C, Franke, Barbara, Crivello, Fabrice, Tzourio-Mazoyer, Nathalie, Baune, Bernhard T, Fisher, Simon E, Thompson, Paul M, Farde, Lars, Flyckt, Lena, Engberg, Göran, Erhardt, Sophie, Fatouros-Bergman, Helena, Cervenka, Simon, Schwieler, Lilly, Baur-Streubel, Ramona, Piehl, Fredrik, Collste, Karin, Victorsson, Pauliina, Malmqvist, Anna, Hedberg, Mikael, Orhan, Funda, Group, ENIGMA Laterality Working, Biederman, Joseph, Blaine, Sara K, Boedhoe, Premika, Bøen, Erlend, Bose, Anushree, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J, Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales-Rodríguez, Erick Jorge, Canive, Jose M, Cannon, Dara M, Caparelli, Elisabeth C, Castellanos, Francisco X, Cavalleri, Gianpiero L, Cendes, Fernando, Chaim-Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun-Lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Córdova-Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dale, Anders, Dannlowski, Udo, Ambrosino de Bruttopilo, Sara, de Zeeuw, Patrick, Deary, Ian J, Delanty, Norman, Demeter, Damion V, Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, N Trung, Doherty, Colin P, Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N, Fair, Damien A, Faraone, Stephen V, Fernández, Guillén, Filho, Geraldo Busatto, Förster, Katharina, Fouche, Jean-Paul, Foxe, John J, Frodl, Thomas, Fuentes-Claramonte, Paola, Fullerton, Janice, Garavan, Hugh, Garcia, Danielle do Santos, Gotlib, Ian H, Goudriaan, Anna E, [GIN] Grenoble Institut des Neurosciences (GIN), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Stochastics, Clinical Neuropsychology, Cognitive Psychology, IBBA, APH - Mental Health, Ontwikkelingspsychologie (Psychologie, FMG), Anatomy and neurosciences, Psychiatry, Pediatric surgery, Amsterdam Neuroscience - Brain Imaging, Child Psychiatry, Adult Psychiatry, ANS - Brain Imaging, AGEM - Endocrinology, metabolism and nutrition, Graduate School, AGEM - Inborn errors of metabolism, ARD - Amsterdam Reproduction and Development, General Paediatrics, APH - Digital Health, Radiology & Nuclear Medicine, Child and Adolescent Psychiatry / Psychology, and Universitat de Barcelona

Subjects
Dominància cerebral, Male, Databases, Factual, Planum temporale, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], 0302 clinical medicine, Transverse temporal gyrus, 130 000 Cognitive Neurology & Memory, diagnostic imaging [Cerebral Cortex], 80 and over, Brain asymmetry, Neuroimaging/methods, Child, ENIGMA Laterality Working Group, Aged, 80 and over, Cerebral Cortex, Multidisciplinary, Laterality, 05 social sciences, Human brain, Middle Aged, Databases, Factual/statistics & numerical data, medicine.anatomical_structure, Mental Health, PNAS Plus, Lateralitat, Child, Preschool, Brain size, Neurological, Biomedical Imaging, Female, ddc:500, methods [Neuroimaging], Parahippocampal gyrus, Neuroinformatics, Adult, statistics & numerical data [Databases, Factual], Adolescent, Cerebral Cortex/diagnostic imaging, 1.1 Normal biological development and functioning, BF, Inferior frontal gyrus, Neuroimaging, and over, Biology, 050105 experimental psychology, Lateralization of brain function, 03 medical and health sciences, Databases, Young Adult, All institutes and research themes of the Radboud University Medical Center, Clinical Research, Underpinning research, Journal Article, medicine, Humans, lateralization, 0501 psychology and cognitive sciences, General, Preschool, Factual, Aged, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], [SCCO.NEUR]Cognitive science/Neuroscience, Neurosciences, Infant, surface area, cortical thickness, Brain Disorders, meta-analysis, Cerebral dominance, brain asymmetry, Neuroscience, Developmental Psychopathology, 030217 neurology & neurosurgery
Abstract

Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here the ENIGMA consortium presents the largest ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and brain size (indexed by intracranial volume). Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (N = 1,443 and 1,113, respectively), we found several asymmetries showing modest but highly reliable heritability. The structural asymmetries identified, and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.Significance StatementLeft-right asymmetry is a key feature of the human brain's structure and function. It remains unclear which cortical regions are asymmetrical on average in the population, and how biological factors such as age, sex and genetic variation affect these asymmetries. Here we describe by far the largest ever study of cerebral cortical brain asymmetry, based on data from 17,141 participants. We found a global anterior-posterior 'torque' pattern in cortical thickness, together with various regional asymmetries at the population level, which have not been previously described, as well as effects of age, sex, and heritability estimates. From these data, we have created an on-line resource that will serve future studies of human brain anatomy in health and disease.

Published
2018

16. Smaller Limbic Structures Are Associated with Immunosuppression and Viral Load in Over 1000 HIV-Infected Adults Across Five Continents: Findings from the ENIGMA-HIV Working Group

Author

Nir, Talia M., primary, Fouche, Jean-Paul, additional, Ananworanich, Jintanat, additional, Ances, Beau M., additional, Boban, Jasmina, additional, Brew, Bruce J., additional, Chaganti, Joga R., additional, Chang, Linda, additional, Ching, Christopher R.K., additional, Cysique, Lucette A., additional, Ernst, Thomas, additional, Faskowitz, Joshua, additional, Gupta, Vikash, additional, Harezlak, Jaroslaw, additional, Heaps-Woodruff, Jodi M., additional, Hinkin, Charles H., additional, Hoare, Jacqueline, additional, Joska, John A., additional, Kallianpur, Kalpana J., additional, Kuhn, Taylor, additional, Lam, Hei Y., additional, Law, Meng, additional, Lebrun-Frenay, Christine, additional, Levine, Andrew J., additional, Mondot, Lydiane, additional, Nakamoto, Beau K., additional, Navia, Bradford A., additional, Pennec, Xavier, additional, Porges, Eric C., additional, Shikuma, Cecilia M., additional, Thames, April D., additional, Valcour, Victor, additional, Vassallo, Matteo, additional, Woods, Adam J., additional, Thompson, Paul M., additional, Cohen, Ronald A., additional, Paul, Robert, additional, Stein, Dan J, additional, Jahanshad, Neda, additional, and Group, ENIGMA-HIV Working, additional

Published
2019
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17. 278. ENIGMA-Relatives – Brain Volumes in First-Degree Relatives of Schizophrenia and Bipolar Patients

Author

Sonja de Zwarte, Rachel Brouwer, Manon Hillegers, Wiepke Cahn, Hilleke Hulshoff Pol, René Kahn, Kathryn Alpert, Lei Wang, Elvira Bramon, Fergus Kane, Robin Murray, Tomas Hajek, Martin Alda, Gloria Roberts, Philip Mitchell, Peter Schofield, Janice Fullerton, Anja Richter, Oliver Gruber, Aurora Bonvino, Alessandro Bertolino, Annabella Di Giorgio, Xavier Caseras, Ali Saffet Gonul, Mehmet Cagdas Eker, Fatma Simsek, Scott Fears, Carrie Bearden, David Glahn, Theo van Erp, Paul Thompson, Ole Andreassen, Jessica Turner, Neeltje van Haren, and null group ENIGMA-Relatives Group

Subjects
medicine.medical_specialty, Schizophrenia, business.industry, Meta-analysis, medicine, Bipolar disorder, First-degree relatives, medicine.disease, business, Psychiatry, Biological Psychiatry
Published
2017

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