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165 results on '"Thompson, Paul"'

1. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study.

Author

Georgiadis, Foivos, Larivière, Sara, Glahn, David, Hong, L, Kochunov, Peter, Mowry, Bryan, Loughland, Carmel, Pantelis, Christos, Henskens, Frans, Green, Melissa, Cairns, Murray, Michie, Patricia, Rasser, Paul, Catts, Stanley, Tooney, Paul, Scott, Rodney, Schall, Ulrich, Carr, Vaughan, Quidé, Yann, Krug, Axel, Stein, Frederike, Nenadić, Igor, Brosch, Katharina, Kircher, Tilo, Gur, Raquel, Gur, Ruben, Satterthwaite, Theodore, Karuk, Andriana, Pomarol-Clotet, Edith, Radua, Joaquim, Fuentes-Claramonte, Paola, Salvador, Raymond, Spalletta, Gianfranco, Voineskos, Aristotle, Sim, Kang, Crespo-Facorro, Benedicto, Tordesillas Gutiérrez, Diana, Ehrlich, Stefan, Crossley, Nicolas, Grotegerd, Dominik, Repple, Jonathan, Lencer, Rebekka, Dannlowski, Udo, Calhoun, Vince, Rootes-Murdy, Kelly, Demro, Caroline, Ramsay, Ian, Sponheim, Scott, Schmidt, Andre, Borgwardt, Stefan, Tomyshev, Alexander, Lebedeva, Irina, Höschl, Cyril, Spaniel, Filip, Preda, Adrian, Nguyen, Dana, Uhlmann, Anne, Stein, Dan, Howells, Fleur, Temmingh, Henk, Diaz Zuluaga, Ana, López Jaramillo, Carlos, Iasevoli, Felice, Ji, Ellen, Homan, Stephanie, Omlor, Wolfgang, Homan, Philipp, Kaiser, Stefan, Seifritz, Erich, Misic, Bratislav, Valk, Sofie, Thompson, Paul, Van Erp, Theodorus, Turner, Jessica, Bernhardt, Boris, and Kirschner, Matthias

Subjects
Humans, Schizophrenia, Connectome, Adult, Female, Male, Magnetic Resonance Imaging, Cerebral Cortex, Nerve Net, Brain, Middle Aged, Neural Pathways, Young Adult
Abstract

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenias alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Published
2024

2. Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk.

Author

Zhu, Yinghan, Maikusa, Norihide, Radua, Joaquim, Sämann, Philipp, Fusar-Poli, Paolo, Agartz, Ingrid, Andreassen, Ole, Bachman, Peter, Baeza, Inmaculada, Chen, Xiaogang, Choi, Sunah, Corcoran, Cheryl, Ebdrup, Bjørn, Fortea, Adriana, Garani, Ranjini, Glenthøj, Birte, Glenthøj, Louise, Haas, Shalaila, Hamilton, Holly, Hayes, Rebecca, He, Ying, Heekeren, Karsten, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kristensen, Tina, Kwon, Jun, Lawrie, Stephen, Lebedeva, Irina, Lee, Jimmy, Loewy, Rachel, Mathalon, Daniel, McGuire, Philip, Mizrahi, Romina, Mizuno, Masafumi, Møller, Paul, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria, Raghava, Jayachandra, Røssberg, Jan, Rössler, Wulf, Salisbury, Dean, Sasabayashi, Daiki, Smigielski, Lukasz, Sugranyes, Gisela, Takahashi, Tsutomu, Tamnes, Christian, Tang, Jinsong, Theodoridou, Anastasia, Tomyshev, Alexander, Uhlhaas, Peter, Værnes, Tor, van Amelsvoort, Therese, Waltz, James, Westlye, Lars, Zhou, Juan, Thompson, Paul, Hernaus, Dennis, Jalbrzikowski, Maria, and Koike, Shinsuke

Subjects
Humans, Psychotic Disorders, Magnetic Resonance Imaging, Male, Female, Brain, Neuroimaging, Adult, Young Adult, Machine Learning, Adolescent, Prodromal Symptoms
Abstract

Machine learning approaches using structural magnetic resonance imaging (sMRI) can be informative for disease classification, although their ability to predict psychosis is largely unknown. We created a model with individuals at CHR who developed psychosis later (CHR-PS+) from healthy controls (HCs) that can differentiate each other. We also evaluated whether we could distinguish CHR-PS+ individuals from those who did not develop psychosis later (CHR-PS-) and those with uncertain follow-up status (CHR-UNK). T1-weighted structural brain MRI scans from 1165 individuals at CHR (CHR-PS+, n = 144; CHR-PS-, n = 793; and CHR-UNK, n = 228), and 1029 HCs, were obtained from 21 sites. We used ComBat to harmonize measures of subcortical volume, cortical thickness and surface area data and corrected for non-linear effects of age and sex using a general additive model. CHR-PS+ (n = 120) and HC (n = 799) data from 20 sites served as a training dataset, which we used to build a classifier. The remaining samples were used external validation datasets to evaluate classifier performance (test, independent confirmatory, and independent group [CHR-PS- and CHR-UNK] datasets). The accuracy of the classifier on the training and independent confirmatory datasets was 85% and 73% respectively. Regional cortical surface area measures-including those from the right superior frontal, right superior temporal, and bilateral insular cortices strongly contributed to classifying CHR-PS+ from HC. CHR-PS- and CHR-UNK individuals were more likely to be classified as HC compared to CHR-PS+ (classification rate to HC: CHR-PS+, 30%; CHR-PS-, 73%; CHR-UNK, 80%). We used multisite sMRI to train a classifier to predict psychosis onset in CHR individuals, and it showed promise predicting CHR-PS+ in an independent sample. The results suggest that when considering adolescent brain development, baseline MRI scans for CHR individuals may be helpful to identify their prognosis. Future prospective studies are required about whether the classifier could be actually helpful in the clinical settings.

Published
2024

3. Cortical microstructural associations with CSF amyloid and pTau

Author

Nir, Talia M, Villalón-Reina, Julio E, Salminen, Lauren E, Haddad, Elizabeth, Zheng, Hong, Thomopoulos, Sophia I, Jack, Clifford R, Weiner, Michael W, Thompson, Paul M, and Jahanshad, Neda

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Clinical and Health Psychology, Clinical Sciences, Psychology, Brain Disorders, Behavioral and Social Science, Clinical Research, Basic Behavioral and Social Science, Acquired Cognitive Impairment, Aging, Dementia, Neurodegenerative, Alzheimer's Disease, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Neurosciences, Biomedical Imaging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Aged, Aged, 80 and over, Female, Humans, Male, Alzheimer Disease, Amyloid, Amyloid beta-Peptides, Biomarkers, Brain, Cerebral Cortex, Cognitive Dysfunction, Diffusion Magnetic Resonance Imaging, Gray Matter, Neuroimaging, Peptide Fragments, tau Proteins, Middle Aged, Alzheimer’s Disease Neuroimaging Initiative, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Diffusion MRI (dMRI) can be used to probe microstructural properties of brain tissue and holds great promise as a means to non-invasively map Alzheimer's disease (AD) pathology. Few studies have evaluated multi-shell dMRI models such as neurite orientation dispersion and density imaging (NODDI) and mean apparent propagator (MAP)-MRI in cortical gray matter where many of the earliest histopathological changes occur in AD. Here, we investigated the relationship between CSF pTau181 and Aβ1-42 burden and regional cortical NODDI and MAP-MRI indices in 46 cognitively unimpaired individuals, 18 with mild cognitive impairment, and two with dementia (mean age: 71.8 ± 6.2 years) from the Alzheimer's Disease Neuroimaging Initiative. We compared findings to more conventional cortical thickness measures. Lower CSF Aβ1-42 and higher pTau181 were associated with cortical dMRI measures reflecting less hindered or restricted diffusion and greater diffusivity. Cortical dMRI measures, but not cortical thickness measures, were more widely associated with Aβ1-42 than pTau181 and better distinguished Aβ+ from Aβ- participants than pTau+ from pTau- participants. dMRI associations mediated the relationship between CSF markers and delayed logical memory performance, commonly impaired in early AD. dMRI metrics sensitive to early AD pathogenesis and microstructural damage may be better measures of subtle neurodegeneration in comparison to standard cortical thickness and help to elucidate mechanisms underlying cognitive decline.

Published
2024

4. Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification.

Author

Okada, Naohiro, Fukunaga, Masaki, Miura, Kenichiro, Nemoto, Kiyotaka, Matsumoto, Junya, Hashimoto, Naoki, Kiyota, Masahiro, Morita, Kentaro, Koshiyama, Daisuke, Ohi, Kazutaka, Takahashi, Tsutomu, Koeda, Michihiko, Yamamori, Hidenaga, Fujimoto, Michiko, Yasuda, Yuka, Hasegawa, Naomi, Narita, Hisashi, Yokoyama, Satoshi, Mishima, Ryo, Kawashima, Takahiko, Kobayashi, Yuko, Sasabayashi, Daiki, Harada, Kenichiro, Yamamoto, Maeri, Hirano, Yoji, Itahashi, Takashi, Nakataki, Masahito, Hashimoto, Ryu-Ichiro, Tha, Khin, Koike, Shinsuke, Matsubara, Toshio, Okada, Go, Jahanshad, Neda, Yoshimura, Reiji, Abe, Osamu, Onitsuka, Toshiaki, Watanabe, Yoshiyuki, Matsuo, Koji, Yamasue, Hidenori, Okamoto, Yasumasa, Suzuki, Michio, Turner, Jessica, Thompson, Paul, Ozaki, Norio, Kasai, Kiyoto, Hashimoto, Ryota, and Van Erp, Theodorus

Subjects
Humans, Schizophrenia, Depressive Disorder, Major, Bipolar Disorder, Female, Male, Magnetic Resonance Imaging, Adult, Neuroimaging, Brain, Autism Spectrum Disorder, Middle Aged, Mental Disorders, Organ Size
Abstract

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.

Published
2023

5. Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals.

Author

Matsumoto, Junya, Fukunaga, Masaki, Miura, Kenichiro, Nemoto, Kiyotaka, Okada, Naohiro, Hashimoto, Naoki, Morita, Kentaro, Koshiyama, Daisuke, Ohi, Kazutaka, Takahashi, Tsutomu, Koeda, Michihiko, Yamamori, Hidenaga, Fujimoto, Michiko, Yasuda, Yuka, Ito, Satsuki, Yamazaki, Ryuichi, Hasegawa, Naomi, Narita, Hisashi, Yokoyama, Satoshi, Mishima, Ryo, Miyata, Jun, Kobayashi, Yuko, Sasabayashi, Daiki, Harada, Kenichiro, Yamamoto, Maeri, Hirano, Yoji, Itahashi, Takashi, Nakataki, Masahito, Hashimoto, Ryu-Ichiro, Tha, Khin, Koike, Shinsuke, Matsubara, Toshio, Okada, Go, Yoshimura, Reiji, Abe, Osamu, Turner, Jessica, Jahanshad, Neda, Thompson, Paul, Onitsuka, Toshiaki, Watanabe, Yoshiyuki, Matsuo, Koji, Yamasue, Hidenori, Okamoto, Yasumasa, Suzuki, Michio, Ozaki, Norio, Kasai, Kiyoto, Hashimoto, Ryota, and Van Erp, Theodorus

Subjects
Humans, Depressive Disorder, Major, Autism Spectrum Disorder, Bipolar Disorder, Mental Disorders, Cerebral Cortex, Magnetic Resonance Imaging
Abstract

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

Published
2023

6. 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, Ford, Judith, Fuentes-Claramonte, Paola, Gruber, Oliver, Guerrero-Pedraza, Amalia, Hamilton, Holly, Howells, Fleur, Kraemer, Bernd, Lawrie, Stephen, Radua, Joaquim, Richter, Anja, Salvador, Raymond, Sawa, Akira, Scheffler, Freda, Sim, Kang, Spaniel, Filip, Stein, Dan, Temmingh, Henk, Thomopoulos, Sophia, Tomecek, David, Uhlmann, Anne, Voineskos, Aristotle, Yang, Kun, Jahanshad, Neda, Thompson, Paul, Murray, Robin, Pomarol-Clotet, Edith, Turner, Jessica, Spalletta, Gianfranco, Piras, Federica, Mathalon, Daniel, Potkin, Steven, Van Erp, Theodorus, and Preda, Adrian

Subjects
Humans, Schizophrenia, Magnetic Resonance Imaging, Neuroimaging, Parietal Lobe, Syndrome, Cerebral Cortex
Abstract

Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis.

Published
2023

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

Author

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

Subjects
Humans, Connectome, Brain Mapping, Magnetic Resonance Imaging, Brain, Obsessive-Compulsive Disorder, Biomarkers, Neural Pathways
Abstract

Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohens d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohens d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level.

Published
2023

8. 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
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9. Smaller total and subregional cerebellar volumes in posttraumatic stress disorder: a mega-analysis by the ENIGMA-PGC PTSD workgroup

Author

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

Published
2024
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10. Mapping gray and white matter volume abnormalities in early-onset psychosis: an ENIGMA multicenter voxel-based morphometry study

Author

Si, Shuqing, Bi, Anbreen, Yu, Zhaoying, See, Cheryl, Kelly, Sinead, Ambrogi, Sonia, Arango, Celso, Baeza, Inmaculada, Banaj, Nerisa, Berk, Michael, Castro-Fornieles, Josefina, Crespo-Facorro, Benedicto, Crouse, Jacob J., Díaz-Caneja, Covadonga M., Fett, Anne-Kathrin, Fortea, Adriana, Frangou, Sophia, Goldstein, Benjamin I., Hickie, Ian B., Janssen, Joost, Kennedy, Kody G., Krabbendam, Lydia, Kyriakopoulos, Marinos, MacIntosh, Bradley J., Morgado, Pedro, Nerland, Stener, Pascual-Diaz, Saül, Picó-Pérez, Maria, Piras, Fabrizio, Rund, Bjørn Rishovd, de la Serna, Elena, Spalletta, Gianfranco, Sugranyes, Gisela, Suo, Chao, Tordesillas-Gutiérrez, Diana, Vecchio, Daniela, Radua, Joaquim, McGuire, Philip, Thomopoulos, Sophia I., Jahanshad, Neda, Thompson, Paul M., Barth, Claudia, Agartz, Ingrid, James, Anthony, and Kempton, Matthew J.

Published
2024
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11. Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group.

Author

Groenewold, Nynke, Bas-Hoogendam, Janna, Amod, Alyssa, Laansma, Max, Van Velzen, Laura, Aghajani, Moji, Hilbert, Kevin, Oh, Hyuntaek, Salas, Ramiro, Jackowski, Andrea, Pan, Pedro, Salum, Giovanni, Blair, James, Blair, Karina, Hirsch, Joy, Pantazatos, Spiro, Schneier, Franklin, Talati, Ardesheer, Roelofs, Karin, Volman, Inge, Blanco-Hinojo, Laura, Cardoner, Narcís, Pujol, Jesus, Beesdo-Baum, Katja, Ching, Christopher, Thomopoulos, Sophia, Jansen, Andreas, Kircher, Tilo, Krug, Axel, Nenadić, Igor, Stein, Frederike, Dannlowski, Udo, Grotegerd, Dominik, Lemke, Hannah, Meinert, Susanne, Winter, Alexandra, Erb, Michael, Kreifelts, Benjamin, Gong, Qiyong, Lui, Su, Zhu, Fei, Mwangi, Benson, Soares, Jair, Wu, Mon-Ju, Bayram, Ali, Canli, Mesut, Tükel, Raşit, Westenberg, P, Heeren, Alexandre, Cremers, Henk, Hofmann, David, Straube, Thomas, Doruyter, Alexander, Lochner, Christine, Peterburs, Jutta, Van Tol, Marie-José, Gur, Raquel, Kaczkurkin, Antonia, Larsen, Bart, Satterthwaite, Theodore, Filippi, Courtney, Gold, Andrea, Harrewijn, Anita, Zugman, André, Bülow, Robin, Grabe, Hans, Völzke, Henry, Wittfeld, Katharina, Böhnlein, Joscha, Dohm, Katharina, Kugel, Harald, Schrammen, Elisabeth, Zwanzger, Peter, Leehr, Elisabeth, Sindermann, Lisa, Ball, Tali, Fonzo, Gregory, Paulus, Martin, Stein, Murray, Klumpp, Heide, Phan, K, Furmark, Tomas, Månsson, Kristoffer, Manzouri, Amirhossein, Avery, Suzanne, Blackford, Jennifer, Clauss, Jacqueline, Feola, Brandee, Harper, Jennifer, Sylvester, Chad, Lueken, Ulrike, Veltman, Dick, Winkler, Anderson, Jahanshad, Neda, Pine, Daniel, Thompson, Paul, Stein, Dan, Van der Wee, Nic, and Simmons, Alan

Subjects
Adult, Adolescent, Humans, Phobia, Social, Magnetic Resonance Imaging, Brain, Anxiety, Neuroimaging
Abstract

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE

Published
2023

12. In vivo white matter microstructure in adolescents with early-onset psychosis: a multi-site mega-analysis

Author

Barth, Claudia, Kelly, Sinead, Nerland, Stener, Jahanshad, Neda, Alloza, Clara, Ambrogi, Sonia, Andreassen, Ole A, Andreou, Dimitrios, Arango, Celso, Baeza, Inmaculada, Banaj, Nerisa, Bearden, Carrie E, Berk, Michael, Bohman, Hannes, Castro-Fornieles, Josefina, Chye, Yann, Crespo-Facorro, Benedicto, de la Serna, Elena, Díaz-Caneja, Covadonga M, Gurholt, Tiril P, Hegarty, Catherine E, James, Anthony, Janssen, Joost, Johannessen, Cecilie, Jönsson, Erik G, Karlsgodt, Katherine H, Kochunov, Peter, Lois, Noemi G, Lundberg, Mathias, Myhre, Anne M, Pascual-Diaz, Saül, Piras, Fabrizio, Smelror, Runar E, Spalletta, Gianfranco, Stokkan, Therese S, Sugranyes, Gisela, Suo, Chao, Thomopoulos, Sophia I, Tordesillas-Gutiérrez, Diana, Vecchio, Daniela, Wedervang-Resell, Kirsten, Wortinger, Laura A, Thompson, Paul M, and Agartz, Ingrid

Subjects
Brain Disorders, Serious Mental Illness, Pediatric, Biomedical Imaging, Clinical Research, Neurosciences, Mental Health, Schizophrenia, Mental health, Good Health and Well Being, Female, Humans, Male, Adolescent, White Matter, Diffusion Tensor Imaging, Brain, Psychotic Disorders, Anisotropy, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Emerging evidence suggests brain white matter alterations in adolescents with early-onset psychosis (EOP; age of onset

Published
2023

13. Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium.

Author

Constantinides, Constantinos, Han, Laura KM, Alloza, Clara, Antonucci, Linda Antonella, Arango, Celso, Ayesa-Arriola, Rosa, Banaj, Nerisa, Bertolino, Alessandro, Borgwardt, Stefan, Bruggemann, Jason, Bustillo, Juan, Bykhovski, Oleg, Calhoun, Vince, Carr, Vaughan, Catts, Stanley, Chung, Young-Chul, Crespo-Facorro, Benedicto, Díaz-Caneja, Covadonga M, Donohoe, Gary, Plessis, Stefan Du, Edmond, Jesse, Ehrlich, Stefan, Emsley, Robin, Eyler, Lisa T, Fuentes-Claramonte, Paola, Georgiadis, Foivos, Green, Melissa, Guerrero-Pedraza, Amalia, Ha, Minji, Hahn, Tim, Henskens, Frans A, Holleran, Laurena, Homan, Stephanie, Homan, Philipp, Jahanshad, Neda, Janssen, Joost, Ji, Ellen, Kaiser, Stefan, Kaleda, Vasily, Kim, Minah, Kim, Woo-Sung, Kirschner, Matthias, Kochunov, Peter, Kwak, Yoo Bin, Kwon, Jun Soo, Lebedeva, Irina, Liu, Jingyu, Mitchie, Patricia, Michielse, Stijn, Mothersill, David, Mowry, Bryan, de la Foz, Víctor Ortiz-García, Pantelis, Christos, Pergola, Giulio, Piras, Fabrizio, Pomarol-Clotet, Edith, Preda, Adrian, Quidé, Yann, Rasser, Paul E, Rootes-Murdy, Kelly, Salvador, Raymond, Sangiuliano, Marina, Sarró, Salvador, Schall, Ulrich, Schmidt, André, Scott, Rodney J, Selvaggi, Pierluigi, Sim, Kang, Skoch, Antonin, Spalletta, Gianfranco, Spaniel, Filip, Thomopoulos, Sophia I, Tomecek, David, Tomyshev, Alexander S, Tordesillas-Gutiérrez, Diana, van Amelsvoort, Therese, Vázquez-Bourgon, Javier, Vecchio, Daniela, Voineskos, Aristotle, Weickert, Cynthia S, Weickert, Thomas, Thompson, Paul M, Schmaal, Lianne, van Erp, Theo GM, Turner, Jessica, Cole, James H, ENIGMA Schizophrenia Consortium, Dima, Danai, and Walton, Esther

Subjects
ENIGMA Schizophrenia Consortium, Brain, Humans, Magnetic Resonance Imaging, Prospective Studies, Schizophrenia, Aging, Adolescent, Adult, Aged, Middle Aged, Female, Male, Young Adult, Mental Health, Serious Mental Illness, Brain Disorders, Neurosciences, Biomedical Imaging, Clinical Research, Behavioral and Social Science, Neurological, Mental health, Good Health and Well Being, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

Published
2023

14. Obesity and brain structure in schizophrenia – ENIGMA study in 3021 individuals

Author

McWhinney, Sean R, Brosch, Katharina, Calhoun, Vince D, Crespo-Facorro, Benedicto, Crossley, Nicolas A, Dannlowski, Udo, Dickie, Erin, Dietze, Lorielle MF, Donohoe, Gary, Du Plessis, Stefan, Ehrlich, Stefan, Emsley, Robin, Furstova, Petra, Glahn, David C, Gonzalez- Valderrama, Alfonso, Grotegerd, Dominik, Holleran, Laurena, Kircher, Tilo TJ, Knytl, Pavel, Kolenic, Marian, Lencer, Rebekka, Nenadić, Igor, Opel, Nils, Pfarr, Julia-Katharina, Rodrigue, Amanda L, Rootes-Murdy, Kelly, Ross, Alex J, Sim, Kang, Škoch, Antonín, Spaniel, Filip, Stein, Frederike, Švancer, Patrik, Tordesillas-Gutiérrez, Diana, Undurraga, Juan, Vázquez-Bourgon, Javier, Voineskos, Aristotle, Walton, Esther, Weickert, Thomas W, Weickert, Cynthia Shannon, Thompson, Paul M, van Erp, Theo GM, Turner, Jessica A, and Hajek, Tomas

Subjects
Biomedical Imaging, Obesity, Neurosciences, Serious Mental Illness, Mental Health, Schizophrenia, Nutrition, Clinical Research, Brain Disorders, 2.1 Biological and endogenous factors, Aetiology, Mental health, Humans, Depressive Disorder, Major, Brain, Magnetic Resonance Imaging, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Schizophrenia is frequently associated with obesity, which is linked with neurostructural alterations. Yet, we do not understand how the brain correlates of obesity map onto the brain changes in schizophrenia. We obtained MRI-derived brain cortical and subcortical measures and body mass index (BMI) from 1260 individuals with schizophrenia and 1761 controls from 12 independent research sites within the ENIGMA-Schizophrenia Working Group. We jointly modeled the statistical effects of schizophrenia and BMI using mixed effects. BMI was additively associated with structure of many of the same brain regions as schizophrenia, but the cortical and subcortical alterations in schizophrenia were more widespread and pronounced. Both BMI and schizophrenia were primarily associated with changes in cortical thickness, with fewer correlates in surface area. While, BMI was negatively associated with cortical thickness, the significant associations between BMI and surface area or subcortical volumes were positive. Lastly, the brain correlates of obesity were replicated among large studies and closely resembled neurostructural changes in major depressive disorders. We confirmed widespread associations between BMI and brain structure in individuals with schizophrenia. People with both obesity and schizophrenia showed more pronounced brain alterations than people with only one of these conditions. Obesity appears to be a relevant factor which could account for heterogeneity of brain imaging findings and for differences in brain imaging outcomes among people with schizophrenia.

Published
2022

15. Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Author

Kirschner, Matthias, Hodzic-Santor, Benazir, Antoniades, Mathilde, Nenadic, Igor, Kircher, Tilo, Krug, Axel, Meller, Tina, Grotegerd, Dominik, Fornito, Alex, Arnatkeviciute, Aurina, Bellgrove, Mark A, Tiego, Jeggan, Dannlowski, Udo, Koch, Katharina, Hülsmann, Carina, Kugel, Harald, Enneking, Verena, Klug, Melissa, Leehr, Elisabeth J, Böhnlein, Joscha, Gruber, Marius, Mehler, David, DeRosse, Pamela, Moyett, Ashley, Baune, Bernhard T, Green, Melissa, Quidé, Yann, Pantelis, Christos, Chan, Raymond, Wang, Yi, Ettinger, Ulrich, Debbané, Martin, Derome, Melodie, Gaser, Christian, Besteher, Bianca, Diederen, Kelly, Spencer, Tom J, Fletcher, Paul, Rössler, Wulf, Smigielski, Lukasz, Kumari, Veena, Premkumar, Preethi, Park, Haeme RP, Wiebels, Kristina, Lemmers-Jansen, Imke, Gilleen, James, Allen, Paul, Kozhuharova, Petya, Marsman, Jan-Bernard, Lebedeva, Irina, Tomyshev, Alexander, Mukhorina, Anna, Kaiser, Stefan, Fett, Anne-Kathrin, Sommer, Iris, Schuite-Koops, Sanne, Paquola, Casey, Larivière, Sara, Bernhardt, Boris, Dagher, Alain, Grant, Phillip, van Erp, Theo GM, Turner, Jessica A, Thompson, Paul M, Aleman, André, and Modinos, Gemma

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Neurosciences, Serious Mental Illness, Schizophrenia, Clinical Research, Mental Health, Mental health, Good Health and Well Being, Bipolar Disorder, Female, Humans, Magnetic Resonance Imaging, Male, Psychotic Disorders, Schizotypal Personality Disorder, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Published
2022

17. 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
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18. Association between body mass index and subcortical brain volumes in bipolar disorders–ENIGMA study in 2735 individuals

Author

McWhinney, Sean R, Abé, Christoph, Alda, Martin, Benedetti, Francesco, Bøen, Erlend, del Mar Bonnin, Caterina, Borgers, Tiana, Brosch, Katharina, Canales-Rodríguez, Erick J, Cannon, Dara M, Dannlowski, Udo, Díaz-Zuluaga, Ana M, Elvsåshagen, Torbjørn, Eyler, Lisa T, Fullerton, Janice M, Goikolea, Jose M, Goltermann, Janik, Grotegerd, Dominik, Haarman, Bartholomeus CM, Hahn, Tim, Howells, Fleur M, Ingvar, Martin, Kircher, Tilo TJ, Krug, Axel, Kuplicki, Rayus T, Landén, Mikael, Lemke, Hannah, Liberg, Benny, Lopez-Jaramillo, Carlos, Malt, Ulrik F, Martyn, Fiona M, Mazza, Elena, McDonald, Colm, McPhilemy, Genevieve, Meier, Sandra, Meinert, Susanne, Meller, Tina, Melloni, Elisa MT, Mitchell, Philip B, Nabulsi, Leila, Nenadic, Igor, Opel, Nils, Ophoff, Roel A, Overs, Bronwyn J, Pfarr, Julia-Katharina, Pineda-Zapata, Julian A, Pomarol-Clotet, Edith, Raduà, Joaquim, Repple, Jonathan, Richter, Maike, Ringwald, Kai G, Roberts, Gloria, Salvador, Raymond, Savitz, Jonathan, Schmitt, Simon, Schofield, Peter R, Sim, Kang, Stein, Dan J, Stein, Frederike, Temmingh, Henk S, Thiel, Katharina, van Haren, Neeltje EM, Gestel, Holly Van, Vargas, Cristian, Vieta, Eduard, Vreeker, Annabel, Waltemate, Lena, Yatham, Lakshmi N, Ching, Christopher RK, Andreassen, Ole, Thompson, Paul M, and Hajek, Tomas

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Mental Health, Biomedical Imaging, Nutrition, Brain Disorders, Obesity, Neurosciences, Clinical Research, Prevention, Mental health, Amygdala, Bipolar Disorder, Body Mass Index, Brain, Humans, Magnetic Resonance Imaging, ENIGMA Bipolar Disorders Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles  and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

Published
2021

19. Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis

Author

Wang, Xin, Xie, Hong, Chen, Tian, Cotton, Andrew S, Salminen, Lauren E, Logue, Mark W, Clarke-Rubright, Emily K, Wall, John, Dennis, Emily L, O’Leary, Brian M, Abdallah, Chadi G, Andrew, Elpiniki, Baugh, Lee A, Bomyea, Jessica, Bruce, Steven E, Bryant, Richard, Choi, Kyle, Daniels, Judith K, Davenport, Nicholas D, Davidson, Richard J, DeBellis, Michael, deRoon-Cassini, Terri, Disner, Seth G, Fani, Negar, Fercho, Kelene A, Fitzgerald, Jacklynn, Forster, Gina L, Frijling, Jessie L, Geuze, Elbert, Gomaa, Hassaan, Gordon, Evan M, Grupe, Dan, Harpaz-Rotem, Ilan, Haswell, Courtney C, Herzog, Julia I, Hofmann, David, Hollifield, Michael, Hosseini, Bobak, Hudson, Anna R, Ipser, Jonathan, Jahanshad, Neda, Jovanovic, Tanja, Kaufman, Milissa L, King, Anthony P, Koch, Saskia BJ, Koerte, Inga K, Korgaonkar, Mayuresh S, Krystal, John H, Larson, Christine, Lebois, Lauren AM, Levy, Ifat, Li, Gen, Magnotta, Vincent A, Manthey, Antje, May, Geoffrey, McLaughlin, Katie A, Mueller, Sven C, Nawijn, Laura, Nelson, Steven M, Neria, Yuval, Nitschke, Jack B, Olff, Miranda, Olson, Elizabeth A, Peverill, Matthew, Phan, K Luan, Rashid, Faisal M, Ressler, Kerry, Rosso, Isabelle M, Sambrook, Kelly, Schmahl, Christian, Shenton, Martha E, Sierk, Anika, Simons, Jeffrey S, Simons, Raluca M, Sponheim, Scott R, Stein, Murray B, Stein, Dan J, Stevens, Jennifer S, Straube, Thomas, Suarez-Jimenez, Benjamin, Tamburrino, Marijo, Thomopoulos, Sophia I, van der Wee, Nic JA, van der Werff, Steven JA, van Erp, Theo GM, van Rooij, Sanne JH, van Zuiden, Mirjam, Varkevisser, Tim, Veltman, Dick J, Vermeiren, Robert RJM, Walter, Henrik, Wang, Li, Zhu, Ye, Zhu, Xi, Thompson, Paul M, Morey, Rajendra A, and Liberzon, Israel

Subjects
Clinical Research, Behavioral and Social Science, Mental Health, Post-Traumatic Stress Disorder (PTSD), Neurosciences, Brain Disorders, Mental health, Cerebral Cortex, Genomics, Humans, Magnetic Resonance Imaging, Stress Disorders, Post-Traumatic, Temporal Lobe, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Studies of posttraumatic stress disorder (PTSD) report volume abnormalities in multiple regions of the cerebral cortex. However, findings for many regions, particularly regions outside commonly studied emotion-related prefrontal, insular, and limbic regions, are inconsistent and tentative. Also, few studies address the possibility that PTSD abnormalities may be confounded by comorbid depression. A mega-analysis investigating all cortical regions in a large sample of PTSD and control subjects can potentially provide new insight into these issues. Given this perspective, our group aggregated regional volumes data of 68 cortical regions across both hemispheres from 1379 PTSD patients to 2192 controls without PTSD after data were processed by 32 international laboratories using ENIGMA standardized procedures. We examined whether regional cortical volumes were different in PTSD vs. controls, were associated with posttraumatic stress symptom (PTSS) severity, or were affected by comorbid depression. Volumes of left and right lateral orbitofrontal gyri (LOFG), left superior temporal gyrus, and right insular, lingual and superior parietal gyri were significantly smaller, on average, in PTSD patients than controls (standardized coefficients = -0.111 to -0.068, FDR corrected P values

Published
2021

20. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author

Jia, Tianye, Chu, Congying, Liu, Yun, van Dongen, Jenny, Papastergios, Evangelos, Armstrong, Nicola J, Bastin, Mark E, Carrillo-Roa, Tania, den Braber, Anouk, Harris, Mathew, Jansen, Rick, Liu, Jingyu, Luciano, Michelle, Ori, Anil PS, Roiz Santiañez, Roberto, Ruggeri, Barbara, Sarkisyan, Daniil, Shin, Jean, Sungeun, Kim, Tordesillas Gutiérrez, Diana, van’t Ent, Dennis, Ames, David, Artiges, Eric, Bakalkin, Georgy, Banaschewski, Tobias, Bokde, Arun LW, Brodaty, Henry, Bromberg, Uli, Brouwer, Rachel, Büchel, Christian, Burke Quinlan, Erin, Cahn, Wiepke, de Zubicaray, Greig I, Ehrlich, Stefan, Ekström, Tomas J, Flor, Herta, Fröhner, Juliane H, Frouin, Vincent, Garavan, Hugh, Gowland, Penny, Heinz, Andreas, Hoare, Jacqueline, Ittermann, Bernd, Jahanshad, Neda, Jiang, Jiyang, Kwok, John B, Martin, Nicholas G, Martinot, Jean-Luc, Mather, Karen A, McMahon, Katie L, McRae, Allan F, Nees, Frauke, Papadopoulos Orfanos, Dimitri, Paus, Tomáš, Poustka, Luise, Sämann, Philipp G, Schofield, Peter R, Smolka, Michael N, Stein, Dan J, Strike, Lachlan T, Teeuw, Jalmar, Thalamuthu, Anbupalam, Trollor, Julian, Walter, Henrik, Wardlaw, Joanna M, Wen, Wei, Whelan, Robert, Apostolova, Liana G, Binder, Elisabeth B, Boomsma, Dorret I, Calhoun, Vince, Crespo-Facorro, Benedicto, Deary, Ian J, Hulshoff Pol, Hilleke, Ophoff, Roel A, Pausova, Zdenka, Sachdev, Perminder S, Saykin, Andrew, Wright, Margaret J, Thompson, Paul M, Schumann, Gunter, and Desrivières, Sylvane

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Mental Health, Neurosciences, Genetics, Human Genome, Diabetes, Neurodegenerative, 2.1 Biological and endogenous factors, Aetiology, Neurological, Mental health, CpG Islands, DNA Methylation, Epigenesis, Genetic, Epigenome, Genome-Wide Association Study, Humans, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

DNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)-three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

Published
2021

21. Cortical profiles of numerous psychiatric disorders and normal development share a common pattern

Author

Cao, Zhipeng, Cupertino, Renata B., Ottino-Gonzalez, Jonatan, Murphy, Alistair, Pancholi, Devarshi, Juliano, Anthony, Chaarani, Bader, Albaugh, Matthew, Yuan, Dekang, Schwab, Nathan, Stafford, James, Goudriaan, Anna E., Hutchison, Kent, Li, Chiang-Shan R., Luijten, Maartje, Groefsema, Martine, Momenan, Reza, Schmaal, Lianne, Sinha, Rajita, van Holst, Ruth J., Veltman, Dick J., Wiers, Reinout W., Porjesz, Bernice, Lett, Tristram, Banaschewski, Tobias, Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Millenet, Sabina, Fröhner, Juliane H., Robinson, Lauren, Smolka, Michael N., Walter, Henrik, Winterer, Jeanne, Schumann, Gunter, Whelan, Robert, Bhatt, Ravi R., Zhu, Alyssa, Conrod, Patricia, Jahanshad, Neda, Thompson, Paul M., Mackey, Scott, and Garavan, Hugh

Published
2023
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22. Structural brain imaging studies offer clues about the effects of the shared genetic etiology among neuropsychiatric disorders

Author

Radonjić, Nevena V, Hess, Jonathan L, Rovira, Paula, Andreassen, Ole, Buitelaar, Jan K, Ching, Christopher RK, Franke, Barbara, Hoogman, Martine, Jahanshad, Neda, McDonald, Carrie, Schmaal, Lianne, Sisodiya, Sanjay M, Stein, Dan J, van den Heuvel, Odile A, van Erp, Theo GM, van Rooij, Daan, Veltman, Dick J, Thompson, Paul, and Faraone, Stephen V

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Serious Mental Illness, Genetics, Brain Disorders, Clinical Research, Autism, Intellectual and Developmental Disabilities (IDD), Schizophrenia, Mental Health, Prevention, Aetiology, 2.1 Biological and endogenous factors, Mental health, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Brain, Depressive Disorder, Major, Humans, Neuroimaging, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Genomewide association studies have found significant genetic correlations among many neuropsychiatric disorders. In contrast, we know much less about the degree to which structural brain alterations are similar among disorders and, if so, the degree to which such similarities have a genetic etiology. From the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium, we acquired standardized mean differences (SMDs) in regional brain volume and cortical thickness between cases and controls. We had data on 41 brain regions for: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), epilepsy, major depressive disorder (MDD), obsessive compulsive disorder (OCD), and schizophrenia (SCZ). These data had been derived from 24,360 patients and 37,425 controls. The SMDs were significantly correlated between SCZ and BD, OCD, MDD, and ASD. MDD was positively correlated with BD and OCD. BD was positively correlated with OCD and negatively correlated with ADHD. These pairwise correlations among disorders were correlated with the corresponding pairwise correlations among disorders derived from genomewide association studies (r = 0.494). Our results show substantial similarities in sMRI phenotypes among neuropsychiatric disorders and suggest that these similarities are accounted for, in part, by corresponding similarities in common genetic variant architectures.

Published
2021

23. Correction: Obesity and brain structure in schizophrenia – ENIGMA study in 3021 individuals

Author

McWhinney, Sean R., Brosch, Katharina, Calhoun, Vince D., Crespo-Facorro, Benedicto, Crossley, Nicolas A., Dannlowski, Udo, Dickie, Erin, Dietze, Lorielle M. F., Donohoe, Gary, Du Plessis, Stefan, Ehrlich, Stefan, Emsley, Robin, Furstova, Petra, Glahn, David C., Gonzalez- Valderrama, Alfonso, Grotegerd, Dominik, Holleran, Laurena, Kircher, Tilo T. J., Knytl, Pavel, Kolenic, Marian, Lencer, Rebekka, Nenadić, Igor, Opel, Nils, Pfarr, Julia-Katharina, Rodrigue, Amanda L., Rootes-Murdy, Kelly, Ross, Alex J., Sim, Kang, Škoch, Antonín, Spaniel, Filip, Stein, Frederike, Švancer, Patrik, Tordesillas-Gutiérrez, Diana, Undurraga, Juan, Vázquez-Bourgon, Javier, Voineskos, Aristotle, Walton, Esther, Weickert, Thomas W., Weickert, Cynthia Shannon, Thompson, Paul M., van Erp, Theo G. M., Turner, Jessica A., and Hajek, Tomas

Published
2024
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24. Altered white matter microstructure in 22q11.2 deletion syndrome: a multisite diffusion tensor imaging study

Author

Villalón-Reina, Julio E, Martínez, Kenia, Qu, Xiaoping, Ching, Christopher RK, Nir, Talia M, Kothapalli, Deydeep, Corbin, Conor, Sun, Daqiang, Lin, Amy, Forsyth, Jennifer K, Kushan, Leila, Vajdi, Ariana, Jalbrzikowski, Maria, Hansen, Laura, Jonas, Rachel K, van Amelsvoort, Therese, Bakker, Geor, Kates, Wendy R, Antshel, Kevin M, Fremont, Wanda, Campbell, Linda E, McCabe, Kathryn L, Daly, Eileen, Gudbrandsen, Maria, Murphy, Clodagh M, Murphy, Declan, Craig, Michael, Emanuel, Beverly, McDonald-McGinn, Donna M, Vorstman, Jacob AS, Fiksinski, Ania M, Koops, Sanne, Ruparel, Kosha, Roalf, David, Gur, Raquel E, Eric Schmitt, J, Simon, Tony J, Goodrich-Hunsaker, Naomi J, Durdle, Courtney A, Doherty, Joanne L, Cunningham, Adam C, van den Bree, Marianne, Linden, David EJ, Owen, Michael, Moss, Hayley, Kelly, Sinead, Donohoe, Gary, Murphy, Kieran C, Arango, Celso, Jahanshad, Neda, Thompson, Paul M, and Bearden, Carrie E

Subjects
Paediatrics, Biomedical and Clinical Sciences, Neurosciences, Pediatric, Biomedical Imaging, Mental Health, Clinical Research, Brain Disorders, Mental health, Adolescent, Adult, Anisotropy, Child, DiGeorge Syndrome, Diffusion Magnetic Resonance Imaging, Female, Humans, Male, Middle Aged, White Matter, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

22q11.2 deletion syndrome (22q11DS)-a neurodevelopmental condition caused by a hemizygous deletion on chromosome 22-is associated with an elevated risk of psychosis and other developmental brain disorders. Prior single-site diffusion magnetic resonance imaging (dMRI) studies have reported altered white matter (WM) microstructure in 22q11DS, but small samples and variable methods have led to contradictory results. Here we present the largest study ever conducted of dMRI-derived measures of WM microstructure in 22q11DS (334 22q11.2 deletion carriers and 260 healthy age- and sex-matched controls; age range 6-52 years). Using harmonization protocols developed by the ENIGMA-DTI working group, we identified widespread reductions in mean, axial and radial diffusivities in 22q11DS, most pronounced in regions with major cortico-cortical and cortico-thalamic fibers: the corona radiata, corpus callosum, superior longitudinal fasciculus, posterior thalamic radiations, and sagittal stratum (Cohen's d's ranging from -0.9 to -1.3). Only the posterior limb of the internal capsule (IC), comprised primarily of corticofugal fibers, showed higher axial diffusivity in 22q11DS. 22q11DS patients showed higher mean fractional anisotropy (FA) in callosal and projection fibers (IC and corona radiata) relative to controls, but lower FA than controls in regions with predominantly association fibers. Psychotic illness in 22q11DS was associated with more substantial diffusivity reductions in multiple regions. Overall, these findings indicate large effects of the 22q11.2 deletion on WM microstructure, especially in major cortico-cortical connections. Taken together with findings from animal models, this pattern of abnormalities may reflect disrupted neurogenesis of projection neurons in outer cortical layers.

Published
2020

25. Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium

Author

van Velzen, Laura S., Dauvermann, Maria R., Colic, Lejla, Villa, Luca M., Savage, Hannah S., Toenders, Yara J., Zhu, Alyssa H., Bright, Joanna K., Campos, Adrián I., Salminen, Lauren E., Ambrogi, Sonia, Ayesa-Arriola, Rosa, Banaj, Nerisa, Başgöze, Zeynep, Bauer, Jochen, Blair, Karina, Blair, Robert James, Brosch, Katharina, Cheng, Yuqi, Colle, Romain, Connolly, Colm G., Corruble, Emmanuelle, Couvy-Duchesne, Baptiste, Crespo-Facorro, Benedicto, Cullen, Kathryn R., Dannlowski, Udo, Davey, Christopher G., Dohm, Katharina, Fullerton, Janice M., Gonul, Ali Saffet, Gotlib, Ian H., Grotegerd, Dominik, Hahn, Tim, Harrison, Ben J., He, Mengxin, Hickie, Ian B., Ho, Tiffany C., Iorfino, Frank, Jansen, Andreas, Jollant, Fabrice, Kircher, Tilo, Klimes-Dougan, Bonnie, Klug, Melissa, Leehr, Elisabeth J., Lippard, Elizabeth T. C., McLaughlin, Katie A., Meinert, Susanne, Miller, Adam Bryant, Mitchell, Philip B., Mwangi, Benson, Nenadić, Igor, Ojha, Amar, Overs, Bronwyn J., Pfarr, Julia-Katharina, Piras, Fabrizio, Ringwald, Kai G., Roberts, Gloria, Romer, Georg, Sanches, Marsal, Sheridan, Margaret A., Soares, Jair C., Spalletta, Gianfranco, Stein, Frederike, Teresi, Giana I., Tordesillas-Gutiérrez, Diana, Uyar-Demir, Aslihan, van der Wee, Nic J. A., van der Werff, Steven J., Vermeiren, Robert R. J. M., Winter, Alexandra, Wu, Mon-Ju, Yang, Tony T., Thompson, Paul M., Rentería, Miguel E., Jahanshad, Neda, Blumberg, Hilary P., van Harmelen, Anne-Laura, and Schmaal, Lianne

Published
2022
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26. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Author

Nunes, Abraham, Schnack, Hugo G, Ching, Christopher RK, Agartz, Ingrid, Akudjedu, Theophilus N, Alda, Martin, Alnæs, Dag, Alonso-Lana, Silvia, Bauer, Jochen, Baune, Bernhard T, Bøen, Erlend, Bonnin, Caterina del Mar, Busatto, Geraldo F, Canales-Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Chaim-Avancini, Tiffany M, Dannlowski, Udo, Díaz-Zuluaga, Ana M, Dietsche, Bruno, Doan, Nhat Trung, Duchesnay, Edouard, Elvsåshagen, Torbjørn, Emden, Daniel, Eyler, Lisa T, Fatjó-Vilas, Mar, Favre, Pauline, Foley, Sonya F, Fullerton, Janice M, Glahn, David C, Goikolea, Jose M, Grotegerd, Dominik, Hahn, Tim, Henry, Chantal, Hibar, Derrek P, Houenou, Josselin, Howells, Fleur M, Jahanshad, Neda, Kaufmann, Tobias, Kenney, Joanne, Kircher, Tilo TJ, Krug, Axel, Lagerberg, Trine V, Lenroot, Rhoshel K, López-Jaramillo, Carlos, Machado-Vieira, Rodrigo, Malt, Ulrik F, McDonald, Colm, Mitchell, Philip B, Mwangi, Benson, Nabulsi, Leila, Opel, Nils, Overs, Bronwyn J, Pineda-Zapata, Julian A, Pomarol-Clotet, Edith, Redlich, Ronny, Roberts, Gloria, Rosa, Pedro G, Salvador, Raymond, Satterthwaite, Theodore D, Soares, Jair C, Stein, Dan J, Temmingh, Henk S, Trappenberg, Thomas, Uhlmann, Anne, van Haren, Neeltje EM, Vieta, Eduard, Westlye, Lars T, Wolf, Daniel H, Yüksel, Dilara, Zanetti, Marcus V, Andreassen, Ole A, Thompson, Paul M, and Hajek, Tomas

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Brain Disorders, Biomedical Imaging, Neurosciences, Mental Health, Clinical Research, Mental health, Bipolar Disorder, Brain, Humans, Machine Learning, Magnetic Resonance Imaging, Neuroimaging, ENIGMA Bipolar Disorders Working Group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.

Published
2020

27. Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size

Author

Sun, Daqiang, Ching, Christopher RK, Lin, Amy, Forsyth, Jennifer K, Kushan, Leila, Vajdi, Ariana, Jalbrzikowski, Maria, Hansen, Laura, Villalon-Reina, Julio E, Qu, Xiaoping, Jonas, Rachel K, van Amelsvoort, Therese, Bakker, Geor, Kates, Wendy R, Antshel, Kevin M, Fremont, Wanda, Campbell, Linda E, McCabe, Kathryn L, Daly, Eileen, Gudbrandsen, Maria, Murphy, Clodagh M, Murphy, Declan, Craig, Michael, Vorstman, Jacob, Fiksinski, Ania, Koops, Sanne, Ruparel, Kosha, Roalf, David R, Gur, Raquel E, Schmitt, J Eric, Simon, Tony J, Goodrich-Hunsaker, Naomi J, Durdle, Courtney A, Bassett, Anne S, Chow, Eva WC, Butcher, Nancy J, Vila-Rodriguez, Fidel, Doherty, Joanne, Cunningham, Adam, van den Bree, Marianne BM, Linden, David EJ, Moss, Hayley, Owen, Michael J, Murphy, Kieran C, McDonald-McGinn, Donna M, Emanuel, Beverly, van Erp, Theo GM, Turner, Jessica A, Thompson, Paul M, and Bearden, Carrie E

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Pediatric, Serious Mental Illness, Clinical Research, Mental Health, Schizophrenia, Brain Disorders, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adolescent, Adult, Cerebral Cortex, Chromosome Deletion, DiGeorge Syndrome, Female, Gray Matter, Humans, Magnetic Resonance Imaging, Male, Psychotic Disorders, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

The 22q11.2 deletion (22q11DS) is a common chromosomal microdeletion and a potent risk factor for psychotic illness. Prior studies reported widespread cortical changes in 22q11DS, but were generally underpowered to characterize neuroanatomic abnormalities associated with psychosis in 22q11DS, and/or neuroanatomic effects of variability in deletion size. To address these issues, we developed the ENIGMA (Enhancing Neuro Imaging Genetics Through Meta-Analysis) 22q11.2 Working Group, representing the largest analysis of brain structural alterations in 22q11DS to date. The imaging data were collected from 10 centers worldwide, including 474 subjects with 22q11DS (age = 18.2 ± 8.6; 46.9% female) and 315 typically developing, matched controls (age = 18.0 ± 9.2; 45.9% female). Compared to controls, 22q11DS individuals showed thicker cortical gray matter overall (left/right hemispheres: Cohen's d = 0.61/0.65), but focal thickness reduction in temporal and cingulate cortex. Cortical surface area (SA), however, showed pervasive reductions in 22q11DS (left/right hemispheres: d = -1.01/-1.02). 22q11DS cases vs. controls were classified with 93.8% accuracy based on these neuroanatomic patterns. Comparison of 22q11DS-psychosis to idiopathic schizophrenia (ENIGMA-Schizophrenia Working Group) revealed significant convergence of affected brain regions, particularly in fronto-temporal cortex. Finally, cortical SA was significantly greater in 22q11DS cases with smaller 1.5 Mb deletions, relative to those with typical 3 Mb deletions. We found a robust neuroanatomic signature of 22q11DS, and the first evidence that deletion size impacts brain structure. Psychotic illness in this highly penetrant deletion was associated with similar neuroanatomic abnormalities to idiopathic schizophrenia. These consistent cross-site findings highlight the homogeneity of this single genetic etiology, and support the suitability of 22q11DS as a biological model of schizophrenia.

Published
2020

28. White matter microstructural alterations across four major psychiatric disorders: mega-analysis study in 2937 individuals

Author

Koshiyama, Daisuke, Fukunaga, Masaki, Okada, Naohiro, Morita, Kentaro, Nemoto, Kiyotaka, Usui, Kaori, Yamamori, Hidenaga, Yasuda, Yuka, Fujimoto, Michiko, Kudo, Noriko, Azechi, Hirotsugu, Watanabe, Yoshiyuki, Hashimoto, Naoki, Narita, Hisashi, Kusumi, Ichiro, Ohi, Kazutaka, Shimada, Takamitsu, Kataoka, Yuzuru, Yamamoto, Maeri, Ozaki, Norio, Okada, Go, Okamoto, Yasumasa, Harada, Kenichiro, Matsuo, Koji, Yamasue, Hidenori, Abe, Osamu, Hashimoto, Ryuichiro, Takahashi, Tsutomu, Hori, Tomoki, Nakataki, Masahito, Onitsuka, Toshiaki, Holleran, Laurena, Jahanshad, Neda, van Erp, Theo GM, Turner, Jessica, Donohoe, Gary, Thompson, Paul M, Kasai, Kiyoto, and Hashimoto, Ryota

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Schizophrenia, Neurosciences, Autism, Serious Mental Illness, Depression, Intellectual and Developmental Disabilities (IDD), Mental Health, Brain Disorders, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adult, Autism Spectrum Disorder, Bipolar Disorder, Brain, Depressive Disorder, Major, Diffusion Tensor Imaging, Female, Humans, Male, Mental Disorders, Middle Aged, White Matter, COCORO, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Identifying both the commonalities and differences in brain structures among psychiatric disorders is important for understanding the pathophysiology. Recently, the ENIGMA-Schizophrenia DTI Working Group performed a large-scale meta-analysis and reported widespread white matter microstructural alterations in schizophrenia; however, no similar cross-disorder study has been carried out to date. Here, we conducted mega-analyses comparing white matter microstructural differences between healthy comparison subjects (HCS; N = 1506) and patients with schizophrenia (N = 696), bipolar disorder (N = 211), autism spectrum disorder (N = 126), or major depressive disorder (N = 398; total N = 2937 from 12 sites). In comparison with HCS, we found that schizophrenia, bipolar disorder, and autism spectrum disorder share similar white matter microstructural differences in the body of the corpus callosum; schizophrenia and bipolar disorder featured comparable changes in the limbic system, such as the fornix and cingulum. By comparison, alterations in tracts connecting neocortical areas, such as the uncinate fasciculus, were observed only in schizophrenia. No significant difference was found in major depressive disorder. In a direct comparison between schizophrenia and bipolar disorder, there were no significant differences. Significant differences between schizophrenia/bipolar disorder and major depressive disorder were found in the limbic system, which were similar to the differences in schizophrenia and bipolar disorder relative to HCS. While schizophrenia and bipolar disorder may have similar pathological characteristics, the biological characteristics of major depressive disorder may be close to those of HCS. Our findings provide insights into nosology and encourage further investigations of shared and unique pathophysiology of psychiatric disorders.

Published
2020

29. Correction: 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
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30. Subtly altered topological asymmetry of brain structural covariance networks in autism spectrum disorder across 43 datasets from the ENIGMA consortium

Author

Sha, Zhiqiang, van Rooij, Daan, Anagnostou, Evdokia, Arango, Celso, Auzias, Guillaume, Behrmann, Marlene, Bernhardt, Boris, Bolte, Sven, Busatto, Geraldo F., Calderoni, Sara, Calvo, Rosa, Daly, Eileen, Deruelle, Christine, Duan, Meiyu, Duran, Fabio Luis Souza, Durston, Sarah, Ecker, Christine, Ehrlich, Stefan, Fair, Damien, Fedor, Jennifer, Fitzgerald, Jacqueline, Floris, Dorothea L., Franke, Barbara, Freitag, Christine M., Gallagher, Louise, Glahn, David C., Haar, Shlomi, Hoekstra, Liesbeth, Jahanshad, Neda, Jalbrzikowski, Maria, Janssen, Joost, King, Joseph A., Lazaro, Luisa, Luna, Beatriz, McGrath, Jane, Medland, Sarah E., Muratori, Filippo, Murphy, Declan G. M., Neufeld, Janina, O’Hearn, Kirsten, Oranje, Bob, Parellada, Mara, Pariente, Jose C., Postema, Merel C., Remnelius, Karl Lundin, Retico, Alessandra, Rosa, Pedro Gomes Penteado, Rubia, Katya, Shook, Devon, Tammimies, Kristiina, Taylor, Margot J., Tosetti, Michela, Wallace, Gregory L., Zhou, Fengfeng, Thompson, Paul M., Fisher, Simon E., Buitelaar, Jan K., and Francks, Clyde

Published
2022
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31. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, Laura K. M., Dinga, Richard, Hahn, Tim, Ching, Christopher R. K., Eyler, Lisa T., Aftanas, Lyubomir, Aghajani, Moji, Aleman, André, Baune, Bernhard T., Berger, Klaus, Brak, Ivan, Filho, Geraldo Busatto, Carballedo, Angela, Connolly, Colm G., Couvy-Duchesne, Baptiste, Cullen, Kathryn R., Dannlowski, Udo, Davey, Christopher G., Dima, Danai, Duran, Fabio L. S., Enneking, Verena, Filimonova, Elena, Frenzel, Stefan, Frodl, Thomas, Fu, Cynthia H. Y., Godlewska, Beata R., Gotlib, Ian H., Grabe, Hans J., Groenewold, Nynke A., Grotegerd, Dominik, Gruber, Oliver, Hall, Geoffrey B., Harrison, Ben J., Hatton, Sean N., Hermesdorf, Marco, Hickie, Ian B., Ho, Tiffany C., Hosten, Norbert, Jansen, Andreas, Kähler, Claas, Kircher, Tilo, Klimes-Dougan, Bonnie, Krämer, Bernd, Krug, Axel, Lagopoulos, Jim, Leenings, Ramona, MacMaster, Frank P., MacQueen, Glenda, McIntosh, Andrew, McLellan, Quinn, McMahon, Katie L., Medland, Sarah E., Mueller, Bryon A., Mwangi, Benson, Osipov, Evgeny, Portella, Maria J., Pozzi, Elena, Reneman, Liesbeth, Repple, Jonathan, Rosa, Pedro G. P., Sacchet, Matthew D., Sämann, Philipp G., Schnell, Knut, Schrantee, Anouk, Simulionyte, Egle, Soares, Jair C., Sommer, Jens, Stein, Dan J., Steinsträter, Olaf, Strike, Lachlan T., Thomopoulos, Sophia I., van Tol, Marie-José, Veer, Ilya M., Vermeiren, Robert R. J. M., Walter, Henrik, van der Wee, Nic J. A., van der Werff, Steven J. A., Whalley, Heather, Winter, Nils R., Wittfeld, Katharina, Wright, Margaret J., Wu, Mon-Ju, Völzke, Henry, Yang, Tony T., Zannias, Vasileios, de Zubicaray, Greig I., Zunta-Soares, Giovana B., Abé, Christoph, Alda, Martin, Andreassen, Ole A., Bøen, Erlend, Bonnin, Caterina M., Canales-Rodriguez, Erick J., Cannon, Dara, Caseras, Xavier, Chaim-Avancini, Tiffany M., Elvsåshagen, Torbjørn, Favre, Pauline, Foley, Sonya F., Fullerton, Janice M., Goikolea, Jose M., Haarman, Bartholomeus C. M., Hajek, Tomas, Henry, Chantal, Houenou, Josselin, Howells, Fleur M., Ingvar, Martin, Kuplicki, Rayus, Lafer, Beny, Landén, Mikael, Machado-Vieira, Rodrigo, Malt, Ulrik F., McDonald, Colm, Mitchell, Philip B., Nabulsi, Leila, Otaduy, Maria Concepcion Garcia, Overs, Bronwyn J., Polosan, Mircea, Pomarol-Clotet, Edith, Radua, Joaquim, Rive, Maria M., Roberts, Gloria, Ruhe, Henricus G., Salvador, Raymond, Sarró, Salvador, Satterthwaite, Theodore D., Savitz, Jonathan, Schene, Aart H., Schofield, Peter R., Serpa, Mauricio H., Sim, Kang, Soeiro-de-Souza, Marcio Gerhardt, Sutherland, Ashley N., Temmingh, Henk S., Timmons, Garrett M., Uhlmann, Anne, Vieta, Eduard, Wolf, Daniel H., Zanetti, Marcus V., Jahanshad, Neda, Thompson, Paul M., Veltman, Dick J., Penninx, Brenda W. J. H., Marquand, Andre F., Cole, James H., and Schmaal, Lianne

Published
2021
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32. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders: Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Published
2021
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33. Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

Author

Dennis, Emily L., Disner, Seth G., Fani, Negar, Salminen, Lauren E., Logue, Mark, Clarke, Emily K., Haswell, Courtney C., Averill, Christopher L., Baugh, Lee A., Bomyea, Jessica, Bruce, Steven E., Cha, Jiook, Choi, Kyle, Davenport, Nicholas D., Densmore, Maria, du Plessis, Stefan, Forster, Gina L., Frijling, Jessie L., Gonenc, Atilla, Gruber, Staci, Grupe, Daniel W., Guenette, Jeffrey P., Hayes, Jasmeet, Hofmann, David, Ipser, Jonathan, Jovanovic, Tanja, Kelly, Sinead, Kennis, Mitzy, Kinzel, Philipp, Koch, Saskia B. J., Koerte, Inga, Koopowitz, Sheri, Korgaonkar, Mayuresh, Krystal, John, Lebois, Lauren A. M., Li, Gen, Magnotta, Vincent A., Manthey, Antje, May, Geoff J., Menefee, Deleene S., Nawijn, Laura, Nelson, Steven M., Neufeld, Richard W. J., Nitschke, Jack B., O’Doherty, Daniel, Peverill, Matthew, Ressler, Kerry J., Roos, Annerine, Sheridan, Margaret A., Sierk, Anika, Simmons, Alan, Simons, Raluca M., Simons, Jeffrey S., Stevens, Jennifer, Suarez-Jimenez, Benjamin, Sullivan, Danielle R., Théberge, Jean, Tran, Jana K., van den Heuvel, Leigh, van der Werff, Steven J. A., van Rooij, Sanne J. H., van Zuiden, Mirjam, Velez, Carmen, Verfaellie, Mieke, Vermeiren, Robert R. J. M., Wade, Benjamin S. C., Wager, Tor, Walter, Henrik, Winternitz, Sherry, Wolff, Jonathan, York, Gerald, Zhu, Ye, Zhu, Xi, Abdallah, Chadi G., Bryant, Richard, Daniels, Judith K, Davidson, Richard J, Fercho, Kelene A, Franz, Carol, Geuze, Elbert, Gordon, Evan M, Kaufman, Milissa L, Kremen, William S., Lagopoulos, Jim, Lanius, Ruth A, Lyons, Michael J., McCauley, Stephen R, McGlinchey, Regina, McLaughlin, Katie A., Milberg, William, Neria, Yuval, Olff, Miranda, Seedat, Soraya, Shenton, Martha, Sponheim, Scott R., Stein, Dan J., Stein, Murray B., Straube, Thomas, Tate, David F., van der Wee, Nic J. A., Veltman, Dick J., Wang, Li., Wilde, Elisabeth A., Thompson, Paul M., Kochunov, Peter, Jahanshad, Neda, and Morey, Rajendra A.

Published
2021
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34. Correction: Obesity and brain structure in schizophrenia – ENIGMA study in 3021 individuals

Author

McWhinney, Sean R., Brosch, Katharina, Calhoun, Vince D., Crespo-Facorro, Benedicto, Crossley, Nicolas A., Dannlowski, Udo, Dickie, Erin, Dietze, Lorielle M. F., Donohoe, Gary, Du Plessis, Stefan, Ehrlich, Stefan, Emsley, Robin, Furstova, Petra, Glahn, David C., Gonzalez- Valderrama, Alfonso, Grotegerd, Dominik, Holleran, Laurena, Kircher, Tilo T. J., Knytl, Pavel, Kolenic, Marian, Lencer, Rebekka, Nenadić, Igor, Opel, Nils, Pfarr, Julia-Katharina, Rodrigue, Amanda L., Rootes-Murdy, Kelly, Ross, Alex J., Sim, Kang, Škoch, Antonín, Spaniel, Filip, Stein, Frederike, Švancer, Patrik, Tordesillas-Gutiérrez, Diana, Undurraga, Juan, Váquez-Bourgon, Javier, Voineskos, Aristotle, Walton, Esther, Weickert, Thomas W., Weickert, Cynthia Shannon, Thompson, Paul M., van Erp, Theo G. M., Turner, Jessica A., and Hajek, Tomas

Published
2022
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35. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Author

van Velzen, Laura S., Kelly, Sinead, Isaev, Dmitry, Aleman, Andre, Aftanas, Lyubomir I., Bauer, Jochen, Baune, Bernhard T., Brak, Ivan V., Carballedo, Angela, Connolly, Colm G., Couvy-Duchesne, Baptiste, Cullen, Kathryn R., Danilenko, Konstantin V., Dannlowski, Udo, Enneking, Verena, Filimonova, Elena, Förster, Katharina, Frodl, Thomas, Gotlib, Ian H., Groenewold, Nynke A., Grotegerd, Dominik, Harris, Mathew A., Hatton, Sean N., Hawkins, Emma L., Hickie, Ian B., Ho, Tiffany C., Jansen, Andreas, Kircher, Tilo, Klimes-Dougan, Bonnie, Kochunov, Peter, Krug, Axel, Lagopoulos, Jim, Lee, Renick, Lett, Tristram A., Li, Meng, MacMaster, Frank P., Martin, Nicholas G., McIntosh, Andrew M., McLellan, Quinn, Meinert, Susanne, Nenadić, Igor, Osipov, Evgeny, Penninx, Brenda W. J. H., Portella, Maria J., Repple, Jonathan, Roos, Annerine, Sacchet, Matthew D., Sämann, Philipp G., Schnell, Knut, Shen, Xueyi, Sim, Kang, Stein, Dan J., van Tol, Marie-Jose, Tomyshev, Alexander S., Tozzi, Leonardo, Veer, Ilya M., Vermeiren, Robert, Vives-Gilabert, Yolanda, Walter, Henrik, Walter, Martin, van der Wee, Nic J. A., van der Werff, Steven J. A., Schreiner, Melinda Westlund, Whalley, Heather C., Wright, Margaret J., Yang, Tony T., Zhu, Alyssa, Veltman, Dick J., Thompson, Paul M., Jahanshad, Neda, and Schmaal, Lianne

Published
2020
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36. Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Author

Sønderby, Ida E, Gústafsson, Ómar, Doan, Nhat Trung, Hibar, Derrek P, Martin-Brevet, Sandra, Abdellaoui, Abdel, Ames, David, Amunts, Katrin, Andersson, Michael, Armstrong, Nicola J, Bernard, Manon, Blackburn, Nicholas, Blangero, John, Boomsma, Dorret I, Bralten, Janita, Brattbak, Hans-Richard, Brodaty, Henry, Brouwer, Rachel M, Bülow, Robin, Calhoun, Vince, Caspers, Svenja, Cavalleri, Gianpiero, Chen, Chi-Hua, Cichon, Sven, Ciufolini, Simone, Corvin, Aiden, Crespo-Facorro, Benedicto, Curran, Joanne E, Dale, Anders M, Dalvie, Shareefa, Dazzan, Paola, de Geus, Eco J C, de Zubicaray, Greig I., de Zwarte, Sonja M. C., Delanty, Norman, den Braber, Anouk, Desrivières, Sylvane, Donohoe, Gary, Draganski, Bogdan, Ehrlich, Stefan, Espeseth, Thomas, Fisher, Simon E, Franke, Barbara, Frouin, Vincent, Fukunaga, Masaki, Gareau, Thomas, Glahn, David C, Grabe, Hans, Groenewold, Nynke A., Haavik, Jan, Håberg, Asta, Hashimoto, Ryota, Hehir-Kwa, Jayne Y, Heinz, Andreas, Hillegers, Manon H. J., Hoffmann, Per, Holleran, Laurena, Hottenga, Jouke-Jan, Hulshoff, Hilleke E, Ikeda, Masashi, Jahanshad, Neda, Jernigan, Terry, Jockwitz, Christiane, Johansson, Stefan, Jonsdottir, Gudrun A, Jönsson, Erik G, Kahn, Rene, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Knowles, Emma E M, Kolskår, Knut K, Kwok, John B, Hellard, Stephanie Le, Leu, Costin, Liu, Jingyu, Lundervold, Astri J, Lundervold, Arvid, Martin, Nicholas G., Mather, Karen, Mathias, Samuel R., McCormack, Mark, McMahon, Katie L., McRae, Allan, Milaneschi, Yuri, Moreau, Clara, Morris, Derek, Mothersill, David, Mühleisen, Thomas W, Murray, Robin, Nordvik, Jan E, Nyberg, Lars, Olde Loohuis, Loes M, Ophoff, Roel, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda, Peralta, Juan M, Pike, Bruce, Prieto, Carlos, Pudas, Sara, Quinlan, Erin, Quintana, Daniel S, Reinbold, Céline S, Marques, Tiago Reis, Reymond, Alexandre, Richard, Genevieve, Rodriguez-Herreros, Borja, Roiz-Santiañez, Roberto, Rokicki, Jarek, Rucker, James, Sachdev, Perminder, Sanders, Anne-Marthe, Sando, Sigrid B, Schmaal, Lianne, Schofield, Peter R, Schork, Andrew J., Schumann, Gunter, Shin, Jean, Shumskaya, Elena, Sisodiya, Sanjay, Steen, Vidar M, Stein, Dan J, Steinberg, Stacy, Strike, Lachlan, Teumer, Alexander, Thalamuthu, Anbu, Tordesillas-Gutierrez, Diana, Turner, Jessica, Ueland, Torill, Uhlmann, Anne, Ulfarsson, Magnus O., van ’t Ent, Dennis, van der Meer, Dennis, van Haren, Neeltje E. M., Vaskinn, Anja, Vassos, Evangelos, Walters, G. Bragi, Wang, Yunpeng, Wen, Wei, Whelan, Christopher D, Wittfeld, Katharina, Wright, Margie, Yamamori, Hidenaga, Zayats, Tetyana, Agartz, Ingrid, Westlye, Lars T, Jacquemont, Sébastien, Djurovic, Srdjan, Stefánsson, Hreinn, Stefánsson, Kári, Thompson, Paul, and Andreassen, Ole A.

Published
2020
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37. Correction: Dose response of the 16p11.2 distal copy number variant on intracranial volume and basal ganglia

Author

Sønderby, Ida E., Gústafsson, Ómar, Doan, Nhat Trung, Hibar, Derrek P., Martin-Brevet, Sandra, Abdellaoui, Abdel, Ames, David, Amunts, Katrin, Andersson, Michael, Armstrong, Nicola J., Bernard, Manon, Blackburn, Nicholas, Blangero, John, Boomsma, Dorret I., Bralten, Janita, Brattbak, Hans-Richard, Brodaty, Henry, Brouwer, Rachel M., Bülow, Robin, Calhoun, Vince, Caspers, Svenja, Cavalleri, Gianpiero, Chen, Chi-Hua, Cichon, Sven, Ciufolini, Simone, Corvin, Aiden, Crespo-Facorro, Benedicto, Curran, Joanne E., Dale, Anders M., Dalvie, Shareefa, Dazzan, Paola, de Geus, Eco J. C., de Zubicaray, Greig I., de Zwarte, Sonja M. C., Delanty, Norman, den Braber, Anouk, Desrivières, Sylvane, Donohoe, Gary, Draganski, Bogdan, Ehrlich, Stefan, Espeseth, Thomas, Fisher, Simon E., Franke, Barbara, Frouin, Vincent, Fukunaga, Masaki, Gareau, Thomas, Glahn, David C., Grabe, Hans, Groenewold, Nynke A., Haavik, Jan, Håberg, Asta, Hashimoto, Ryota, Hehir-Kwa, Jayne Y., Heinz, Andreas, Hillegers, Manon H. J., Hoffmann, Per, Holleran, Laurena, Hottenga, Jouke-Jan, Hulshoff, Hilleke E., Ikeda, Masashi, Jahanshad, Neda, Jernigan, Terry, Jockwitz, Christiane, Johansson, Stefan, Jonsdottir, Gudrun A., Jönsson, Erik G., Kahn, Rene, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Knowles, Emma E. M., Kolskår, Knut K., Kwok, John B., Hellard, Stephanie Le, Leu, Costin, Liu, Jingyu, Lundervold, Astri J., Lundervold, Arvid, Martin, Nicholas G., Mather, Karen, Mathias, Samuel R., McCormack, Mark, McMahon, Katie L., McRae, Allan, Milaneschi, Yuri, Moreau, Clara, Morris, Derek, Mothersill, David, Mühleisen, Thomas W., Murray, Robin, Nordvik, Jan E., Nyberg, Lars, Olde Loohuis, Loes M., Ophoff, Roel, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda, Peralta, Juan M., Pike, Bruce, Prieto, Carlos, Pudas, Sara, Quinlan, Erin, Quintana, Daniel S., Reinbold, Céline S., Marques, Tiago Reis, Reymond, Alexandre, Richard, Genevieve, Rodriguez-Herreros, Borja, Roiz-Santiañez, Roberto, Rokicki, Jarek, Rucker, James, Sachdev, Perminder, Sanders, Anne-Marthe, Sando, Sigrid B., Schmaal, Lianne, Schofield, Peter R., Schork, Andrew J., Schumann, Gunter, Shin, Jean, Shumskaya, Elena, Sisodiya, Sanjay, Steen, Vidar M., Stein, Dan J., Steinberg, Stacy, Strike, Lachlan, Teumer, Alexander, Thalamuthu, Anbu, Tordesillas-Gutierrez, Diana, Turner, Jessica, Ueland, Torill, Uhlmann, Anne, Ulfarsson, Magnus O., van ’t Ent, Dennis, van der Meer, Dennis, van Haren, Neeltje E. M., Vaskinn, Anja, Vassos, Evangelos, Walters, G. Bragi, Wang, Yunpeng, Wen, Wei, Whelan, Christopher D., Wittfeld, Katharina, Wright, Margie, Yamamori, Hidenaga, Zayats, Tetyana, Agartz, Ingrid, Westlye, Lars T., Jacquemont, Sébastien, Djurovic, Srdjan, Stefánsson, Hreinn, Stefánsson, Kári, Thompson, Paul, and Andreassen, Ole A.

Published
2020
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38. Correction: Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Published
2021
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39. Correction: Obesity and brain structure in schizophrenia – ENIGMA study in 3021 individuals

Author

McWhinney, Sean R., primary, Brosch, Katharina, additional, Calhoun, Vince D., additional, Crespo-Facorro, Benedicto, additional, Crossley, Nicolas A., additional, Dannlowski, Udo, additional, Dickie, Erin, additional, Dietze, Lorielle M. F., additional, Donohoe, Gary, additional, Du Plessis, Stefan, additional, Ehrlich, Stefan, additional, Emsley, Robin, additional, Furstova, Petra, additional, Glahn, David C., additional, Gonzalez- Valderrama, Alfonso, additional, Grotegerd, Dominik, additional, Holleran, Laurena, additional, Kircher, Tilo T. J., additional, Knytl, Pavel, additional, Kolenic, Marian, additional, Lencer, Rebekka, additional, Nenadić, Igor, additional, Opel, Nils, additional, Pfarr, Julia-Katharina, additional, Rodrigue, Amanda L., additional, Rootes-Murdy, Kelly, additional, Ross, Alex J., additional, Sim, Kang, additional, Škoch, Antonín, additional, Spaniel, Filip, additional, Stein, Frederike, additional, Švancer, Patrik, additional, Tordesillas-Gutiérrez, Diana, additional, Undurraga, Juan, additional, Vázquez-Bourgon, Javier, additional, Voineskos, Aristotle, additional, Walton, Esther, additional, Weickert, Thomas W., additional, Weickert, Cynthia Shannon, additional, Thompson, Paul M., additional, van Erp, Theo G. M., additional, Turner, Jessica A., additional, and Hajek, Tomas, additional

Published
2023
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40. In vivo white matter microstructure in adolescents with early-onset psychosis: a multi-site mega-analysis

Author

Barth, Claudia, primary, Kelly, Sinead, additional, Nerland, Stener, additional, Jahanshad, Neda, additional, Alloza, Clara, additional, Ambrogi, Sonia, additional, Andreassen, Ole A., additional, Andreou, Dimitrios, additional, Arango, Celso, additional, Baeza, Inmaculada, additional, Banaj, Nerisa, additional, Bearden, Carrie E., additional, Berk, Michael, additional, Bohman, Hannes, additional, Castro-Fornieles, Josefina, additional, Chye, Yann, additional, Crespo-Facorro, Benedicto, additional, de la Serna, Elena, additional, Díaz-Caneja, Covadonga M., additional, Gurholt, Tiril P., additional, Hegarty, Catherine E., additional, James, Anthony, additional, Janssen, Joost, additional, Johannessen, Cecilie, additional, Jönsson, Erik G., additional, Karlsgodt, Katherine H., additional, Kochunov, Peter, additional, Lois, Noemi G., additional, Lundberg, Mathias, additional, Myhre, Anne M., additional, Pascual-Diaz, Saül, additional, Piras, Fabrizio, additional, Smelror, Runar E., additional, Spalletta, Gianfranco, additional, Stokkan, Therese S., additional, Sugranyes, Gisela, additional, Suo, Chao, additional, Thomopoulos, Sophia I., additional, Tordesillas-Gutiérrez, Diana, additional, Vecchio, Daniela, additional, Wedervang-Resell, Kirsten, additional, Wortinger, Laura A., additional, Thompson, Paul M., additional, and Agartz, Ingrid, additional

Published
2022
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41. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders

Author

Opel, Nils, Thalamuthu, Anbupalam, Milaneschi, Yuri, Grotegerd, Dominik, Flint, Claas, Leenings, Ramona, Goltermann, Janik, Richter, Maike, Hahn, Tim, Woditsch, Georg, Berger, Klaus, Hermesdorf, Marco, McIntosh, Andrew, Whalley, Heather C., Harris, Mathew A., MacMaster, Frank P., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Carballedo, Angela, Krug, Axel, Nenadic, Igor, Kircher, Tilo, Aleman, Andre, Groenewold, Nynke A., Stein, Dan J., Soares, Jair C., Zunta-Soares, Giovana B., Mwangi, Benson, Wu, Mon-Ju, Walter, Martin, Li, Meng, Harrison, Ben J., Davey, Christopher G., Cullen, Kathryn R., Klimes-Dougan, Bonnie, Mueller, Bryon A., Sämann, Philipp G., Penninx, Brenda, Nawijn, Laura, Veltman, Dick J., Aftanas, Lyubomir, Brak, Ivan V., Filimonova, Elena A., Osipov, Evgeniy A., Reneman, Liesbeth, Schrantee, Anouk, Grabe, Hans J., Van der Auwera, Sandra, Wittfeld, Katharina, Hosten, Norbert, Völzke, Henry, Sim, Kang, Gotlib, Ian H., Sacchet, Matthew D., Lagopoulos, Jim, Hatton, Sean N., Hickie, Ian, Pozzi, Elena, Thompson, Paul M., Jahanshad, Neda, Schmaal, Lianne, Baune, Bernhard T., and Dannlowski, Udo

Subjects
Depression, Diagnostic markers, Article
Abstract

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = −0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Published
2020

42. Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Author

Kirschner, Matthias, primary, Hodzic-Santor, Benazir, additional, Antoniades, Mathilde, additional, Nenadic, Igor, additional, Kircher, Tilo, additional, Krug, Axel, additional, Meller, Tina, additional, Grotegerd, Dominik, additional, Fornito, Alex, additional, Arnatkeviciute, Aurina, additional, Bellgrove, Mark A., additional, Tiego, Jeggan, additional, Dannlowski, Udo, additional, Koch, Katharina, additional, Hülsmann, Carina, additional, Kugel, Harald, additional, Enneking, Verena, additional, Klug, Melissa, additional, Leehr, Elisabeth J., additional, Böhnlein, Joscha, additional, Gruber, Marius, additional, Mehler, David, additional, DeRosse, Pamela, additional, Moyett, Ashley, additional, Baune, Bernhard T., additional, Green, Melissa, additional, Quidé, Yann, additional, Pantelis, Christos, additional, Chan, Raymond, additional, Wang, Yi, additional, Ettinger, Ulrich, additional, Debbané, Martin, additional, Derome, Melodie, additional, Gaser, Christian, additional, Besteher, Bianca, additional, Diederen, Kelly, additional, Spencer, Tom J., additional, Fletcher, Paul, additional, Rössler, Wulf, additional, Smigielski, Lukasz, additional, Kumari, Veena, additional, Premkumar, Preethi, additional, Park, Haeme R. P., additional, Wiebels, Kristina, additional, Lemmers-Jansen, Imke, additional, Gilleen, James, additional, Allen, Paul, additional, Kozhuharova, Petya, additional, Marsman, Jan-Bernard, additional, Lebedeva, Irina, additional, Tomyshev, Alexander, additional, Mukhorina, Anna, additional, Kaiser, Stefan, additional, Fett, Anne-Kathrin, additional, Sommer, Iris, additional, Schuite-Koops, Sanne, additional, Paquola, Casey, additional, Larivière, Sara, additional, Bernhardt, Boris, additional, Dagher, Alain, additional, Grant, Phillip, additional, van Erp, Theo G. M., additional, Turner, Jessica A., additional, Thompson, Paul M., additional, Aleman, André, additional, and Modinos, Gemma, additional

Published
2021
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43. Cortical volume abnormalities in posttraumatic stress disorder: an ENIGMA-psychiatric genomics consortium PTSD workgroup mega-analysis

Author

Wang, Xin, primary, Xie, Hong, additional, Chen, Tian, additional, Cotton, Andrew S., additional, Salminen, Lauren E., additional, Logue, Mark W., additional, Clarke-Rubright, Emily K., additional, Wall, John, additional, Dennis, Emily L., additional, O’Leary, Brian M., additional, Abdallah, Chadi G., additional, Andrew, Elpiniki, additional, Baugh, Lee A., additional, Bomyea, Jessica, additional, Bruce, Steven E., additional, Bryant, Richard, additional, Choi, Kyle, additional, Daniels, Judith K., additional, Davenport, Nicholas D., additional, Davidson, Richard J., additional, DeBellis, Michael, additional, deRoon-Cassini, Terri, additional, Disner, Seth G., additional, Fani, Negar, additional, Fercho, Kelene A., additional, Fitzgerald, Jacklynn, additional, Forster, Gina L., additional, Frijling, Jessie L., additional, Geuze, Elbert, additional, Gomaa, Hassaan, additional, Gordon, Evan M., additional, Grupe, Dan, additional, Harpaz-Rotem, Ilan, additional, Haswell, Courtney C., additional, Herzog, Julia I., additional, Hofmann, David, additional, Hollifield, Michael, additional, Hosseini, Bobak, additional, Hudson, Anna R., additional, Ipser, Jonathan, additional, Jahanshad, Neda, additional, Jovanovic, Tanja, additional, Kaufman, Milissa L., additional, King, Anthony P., additional, Koch, Saskia B. J., additional, Koerte, Inga K., additional, Korgaonkar, Mayuresh S., additional, Krystal, John H., additional, Larson, Christine, additional, Lebois, Lauren A. M., additional, Levy, Ifat, additional, Li, Gen, additional, Magnotta, Vincent A., additional, Manthey, Antje, additional, May, Geoffrey, additional, McLaughlin, Katie A., additional, Mueller, Sven C., additional, Nawijn, Laura, additional, Nelson, Steven M., additional, Neria, Yuval, additional, Nitschke, Jack B., additional, Olff, Miranda, additional, Olson, Elizabeth A., additional, Peverill, Matthew, additional, Phan, K. Luan, additional, Rashid, Faisal M., additional, Ressler, Kerry, additional, Rosso, Isabelle M., additional, Sambrook, Kelly, additional, Schmahl, Christian, additional, Shenton, Martha E., additional, Sierk, Anika, additional, Simons, Jeffrey S., additional, Simons, Raluca M., additional, Sponheim, Scott R., additional, Stein, Murray B., additional, Stein, Dan J., additional, Stevens, Jennifer S., additional, Straube, Thomas, additional, Suarez-Jimenez, Benjamin, additional, Tamburrino, Marijo, additional, Thomopoulos, Sophia I., additional, van der Wee, Nic J. A., additional, van der Werff, Steven J. A., additional, van Erp, Theo G. M., additional, van Rooij, Sanne J. H., additional, van Zuiden, Mirjam, additional, Varkevisser, Tim, additional, Veltman, Dick J., additional, Vermeiren, Robert R. J. M., additional, Walter, Henrik, additional, Wang, Li, additional, Zhu, Ye, additional, Zhu, Xi, additional, Thompson, Paul M., additional, Morey, Rajendra A., additional, and Liberzon, Israel, additional

Published
2020
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44. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, Laura K. M., primary, Dinga, Richard, additional, Hahn, Tim, additional, Ching, Christopher R. K., additional, Eyler, Lisa T., additional, Aftanas, Lyubomir, additional, Aghajani, Moji, additional, Aleman, André, additional, Baune, Bernhard T., additional, Berger, Klaus, additional, Brak, Ivan, additional, Filho, Geraldo Busatto, additional, Carballedo, Angela, additional, Connolly, Colm G., additional, Couvy-Duchesne, Baptiste, additional, Cullen, Kathryn R., additional, Dannlowski, Udo, additional, Davey, Christopher G., additional, Dima, Danai, additional, Duran, Fabio L. S., additional, Enneking, Verena, additional, Filimonova, Elena, additional, Frenzel, Stefan, additional, Frodl, Thomas, additional, Fu, Cynthia H. Y., additional, Godlewska, Beata R., additional, Gotlib, Ian H., additional, Grabe, Hans J., additional, Groenewold, Nynke A., additional, Grotegerd, Dominik, additional, Gruber, Oliver, additional, Hall, Geoffrey B., additional, Harrison, Ben J., additional, Hatton, Sean N., additional, Hermesdorf, Marco, additional, Hickie, Ian B., additional, Ho, Tiffany C., additional, Hosten, Norbert, additional, Jansen, Andreas, additional, Kähler, Claas, additional, Kircher, Tilo, additional, Klimes-Dougan, Bonnie, additional, Krämer, Bernd, additional, Krug, Axel, additional, Lagopoulos, Jim, additional, Leenings, Ramona, additional, MacMaster, Frank P., additional, MacQueen, Glenda, additional, McIntosh, Andrew, additional, McLellan, Quinn, additional, McMahon, Katie L., additional, Medland, Sarah E., additional, Mueller, Bryon A., additional, Mwangi, Benson, additional, Osipov, Evgeny, additional, Portella, Maria J., additional, Pozzi, Elena, additional, Reneman, Liesbeth, additional, Repple, Jonathan, additional, Rosa, Pedro G. P., additional, Sacchet, Matthew D., additional, Sämann, Philipp G., additional, Schnell, Knut, additional, Schrantee, Anouk, additional, Simulionyte, Egle, additional, Soares, Jair C., additional, Sommer, Jens, additional, Stein, Dan J., additional, Steinsträter, Olaf, additional, Strike, Lachlan T., additional, Thomopoulos, Sophia I., additional, van Tol, Marie-José, additional, Veer, Ilya M., additional, Vermeiren, Robert R. J. M., additional, Walter, Henrik, additional, van der Wee, Nic J. A., additional, van der Werff, Steven J. A., additional, Whalley, Heather, additional, Winter, Nils R., additional, Wittfeld, Katharina, additional, Wright, Margaret J., additional, Wu, Mon-Ju, additional, Völzke, Henry, additional, Yang, Tony T., additional, Zannias, Vasileios, additional, de Zubicaray, Greig I., additional, Zunta-Soares, Giovana B., additional, Abé, Christoph, additional, Alda, Martin, additional, Andreassen, Ole A., additional, Bøen, Erlend, additional, Bonnin, Caterina M., additional, Canales-Rodriguez, Erick J., additional, Cannon, Dara, additional, Caseras, Xavier, additional, Chaim-Avancini, Tiffany M., additional, Elvsåshagen, Torbjørn, additional, Favre, Pauline, additional, Foley, Sonya F., additional, Fullerton, Janice M., additional, Goikolea, Jose M., additional, Haarman, Bartholomeus C. M., additional, Hajek, Tomas, additional, Henry, Chantal, additional, Houenou, Josselin, additional, Howells, Fleur M., additional, Ingvar, Martin, additional, Kuplicki, Rayus, additional, Lafer, Beny, additional, Landén, Mikael, additional, Machado-Vieira, Rodrigo, additional, Malt, Ulrik F., additional, McDonald, Colm, additional, Mitchell, Philip B., additional, Nabulsi, Leila, additional, Otaduy, Maria Concepcion Garcia, additional, Overs, Bronwyn J., additional, Polosan, Mircea, additional, Pomarol-Clotet, Edith, additional, Radua, Joaquim, additional, Rive, Maria M., additional, Roberts, Gloria, additional, Ruhe, Henricus G., additional, Salvador, Raymond, additional, Sarró, Salvador, additional, Satterthwaite, Theodore D., additional, Savitz, Jonathan, additional, Schene, Aart H., additional, Schofield, Peter R., additional, Serpa, Mauricio H., additional, Sim, Kang, additional, Soeiro-de-Souza, Marcio Gerhardt, additional, Sutherland, Ashley N., additional, Temmingh, Henk S., additional, Timmons, Garrett M., additional, Uhlmann, Anne, additional, Vieta, Eduard, additional, Wolf, Daniel H., additional, Zanetti, Marcus V., additional, Jahanshad, Neda, additional, Thompson, Paul M., additional, Veltman, Dick J., additional, Penninx, Brenda W. J. H., additional, Marquand, Andre F., additional, Cole, James H., additional, and Schmaal, Lianne, additional

Published
2020
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45. Altered white matter microstructural organization in posttraumatic stress disorder across 3047 adults: results from the PGC-ENIGMA PTSD consortium

Author

Dennis, Emily L., primary, Disner, Seth G., additional, Fani, Negar, additional, Salminen, Lauren E., additional, Logue, Mark, additional, Clarke, Emily K., additional, Haswell, Courtney C., additional, Averill, Christopher L., additional, Baugh, Lee A., additional, Bomyea, Jessica, additional, Bruce, Steven E., additional, Cha, Jiook, additional, Choi, Kyle, additional, Davenport, Nicholas D., additional, Densmore, Maria, additional, du Plessis, Stefan, additional, Forster, Gina L., additional, Frijling, Jessie L., additional, Gonenc, Atilla, additional, Gruber, Staci, additional, Grupe, Daniel W., additional, Guenette, Jeffrey P., additional, Hayes, Jasmeet, additional, Hofmann, David, additional, Ipser, Jonathan, additional, Jovanovic, Tanja, additional, Kelly, Sinead, additional, Kennis, Mitzy, additional, Kinzel, Philipp, additional, Koch, Saskia B. J., additional, Koerte, Inga, additional, Koopowitz, Sheri, additional, Korgaonkar, Mayuresh, additional, Krystal, John, additional, Lebois, Lauren A. M., additional, Li, Gen, additional, Magnotta, Vincent A., additional, Manthey, Antje, additional, May, Geoff J., additional, Menefee, Deleene S., additional, Nawijn, Laura, additional, Nelson, Steven M., additional, Neufeld, Richard W. J., additional, Nitschke, Jack B., additional, O’Doherty, Daniel, additional, Peverill, Matthew, additional, Ressler, Kerry J., additional, Roos, Annerine, additional, Sheridan, Margaret A., additional, Sierk, Anika, additional, Simmons, Alan, additional, Simons, Raluca M., additional, Simons, Jeffrey S., additional, Stevens, Jennifer, additional, Suarez-Jimenez, Benjamin, additional, Sullivan, Danielle R., additional, Théberge, Jean, additional, Tran, Jana K., additional, van den Heuvel, Leigh, additional, van der Werff, Steven J. A., additional, van Rooij, Sanne J. H., additional, van Zuiden, Mirjam, additional, Velez, Carmen, additional, Verfaellie, Mieke, additional, Vermeiren, Robert R. J. M., additional, Wade, Benjamin S. C., additional, Wager, Tor, additional, Walter, Henrik, additional, Winternitz, Sherry, additional, Wolff, Jonathan, additional, York, Gerald, additional, Zhu, Ye, additional, Zhu, Xi, additional, Abdallah, Chadi G., additional, Bryant, Richard, additional, Daniels, Judith K, additional, Davidson, Richard J, additional, Fercho, Kelene A, additional, Franz, Carol, additional, Geuze, Elbert, additional, Gordon, Evan M, additional, Kaufman, Milissa L, additional, Kremen, William S., additional, Lagopoulos, Jim, additional, Lanius, Ruth A, additional, Lyons, Michael J., additional, McCauley, Stephen R, additional, McGlinchey, Regina, additional, McLaughlin, Katie A., additional, Milberg, William, additional, Neria, Yuval, additional, Olff, Miranda, additional, Seedat, Soraya, additional, Shenton, Martha, additional, Sponheim, Scott R., additional, Stein, Dan J., additional, Stein, Murray B., additional, Straube, Thomas, additional, Tate, David F., additional, van der Wee, Nic J. A., additional, Veltman, Dick J., additional, Wang, Li., additional, Wilde, Elisabeth A., additional, Thompson, Paul M., additional, Kochunov, Peter, additional, Jahanshad, Neda, additional, and Morey, Rajendra A., additional

Published
2019
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46. Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

Author

Jia, Tianye, primary, Chu, Congying, additional, Liu, Yun, additional, van Dongen, Jenny, additional, Papastergios, Evangelos, additional, Armstrong, Nicola J., additional, Bastin, Mark E., additional, Carrillo-Roa, Tania, additional, den Braber, Anouk, additional, Harris, Mathew, additional, Jansen, Rick, additional, Liu, Jingyu, additional, Luciano, Michelle, additional, Ori, Anil P. S., additional, Roiz Santiañez, Roberto, additional, Ruggeri, Barbara, additional, Sarkisyan, Daniil, additional, Shin, Jean, additional, Sungeun, Kim, additional, Tordesillas Gutiérrez, Diana, additional, van’t Ent, Dennis, additional, Ames, David, additional, Artiges, Eric, additional, Bakalkin, Georgy, additional, Banaschewski, Tobias, additional, Bokde, Arun L. W., additional, Brodaty, Henry, additional, Bromberg, Uli, additional, Brouwer, Rachel, additional, Büchel, Christian, additional, Burke Quinlan, Erin, additional, Cahn, Wiepke, additional, de Zubicaray, Greig I., additional, Ehrlich, Stefan, additional, Ekström, Tomas J., additional, Flor, Herta, additional, Fröhner, Juliane H., additional, Frouin, Vincent, additional, Garavan, Hugh, additional, Gowland, Penny, additional, Heinz, Andreas, additional, Hoare, Jacqueline, additional, Ittermann, Bernd, additional, Jahanshad, Neda, additional, Jiang, Jiyang, additional, Kwok, John B., additional, Martin, Nicholas G., additional, Martinot, Jean-Luc, additional, Mather, Karen A., additional, McMahon, Katie L., additional, McRae, Allan F., additional, Nees, Frauke, additional, Papadopoulos Orfanos, Dimitri, additional, Paus, Tomáš, additional, Poustka, Luise, additional, Sämann, Philipp G., additional, Schofield, Peter R., additional, Smolka, Michael N., additional, Stein, Dan J., additional, Strike, Lachlan T., additional, Teeuw, Jalmar, additional, Thalamuthu, Anbupalam, additional, Trollor, Julian, additional, Walter, Henrik, additional, Wardlaw, Joanna M., additional, Wen, Wei, additional, Whelan, Robert, additional, Apostolova, Liana G., additional, Binder, Elisabeth B., additional, Boomsma, Dorret I., additional, Calhoun, Vince, additional, Crespo-Facorro, Benedicto, additional, Deary, Ian J., additional, Hulshoff Pol, Hilleke, additional, Ophoff, Roel A., additional, Pausova, Zdenka, additional, Sachdev, Perminder S., additional, Saykin, Andrew, additional, Wright, Margaret J., additional, Thompson, Paul M., additional, Schumann, Gunter, additional, and Desrivières, Sylvane, additional

Published
2019
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47. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Author

van Velzen, Laura S., primary, Kelly, Sinead, additional, Isaev, Dmitry, additional, Aleman, Andre, additional, Aftanas, Lyubomir I., additional, Bauer, Jochen, additional, Baune, Bernhard T., additional, Brak, Ivan V., additional, Carballedo, Angela, additional, Connolly, Colm G., additional, Couvy-Duchesne, Baptiste, additional, Cullen, Kathryn R., additional, Danilenko, Konstantin V., additional, Dannlowski, Udo, additional, Enneking, Verena, additional, Filimonova, Elena, additional, Förster, Katharina, additional, Frodl, Thomas, additional, Gotlib, Ian H., additional, Groenewold, Nynke A., additional, Grotegerd, Dominik, additional, Harris, Mathew A., additional, Hatton, Sean N., additional, Hawkins, Emma L., additional, Hickie, Ian B., additional, Ho, Tiffany C., additional, Jansen, Andreas, additional, Kircher, Tilo, additional, Klimes-Dougan, Bonnie, additional, Kochunov, Peter, additional, Krug, Axel, additional, Lagopoulos, Jim, additional, Lee, Renick, additional, Lett, Tristram A., additional, Li, Meng, additional, MacMaster, Frank P., additional, Martin, Nicholas G., additional, McIntosh, Andrew M., additional, McLellan, Quinn, additional, Meinert, Susanne, additional, Nenadić, Igor, additional, Osipov, Evgeny, additional, Penninx, Brenda W. J. H., additional, Portella, Maria J., additional, Repple, Jonathan, additional, Roos, Annerine, additional, Sacchet, Matthew D., additional, Sämann, Philipp G., additional, Schnell, Knut, additional, Shen, Xueyi, additional, Sim, Kang, additional, Stein, Dan J., additional, van Tol, Marie-Jose, additional, Tomyshev, Alexander S., additional, Tozzi, Leonardo, additional, Veer, Ilya M., additional, Vermeiren, Robert, additional, Vives-Gilabert, Yolanda, additional, Walter, Henrik, additional, Walter, Martin, additional, van der Wee, Nic J. A., additional, van der Werff, Steven J. A., additional, Schreiner, Melinda Westlund, additional, Whalley, Heather C., additional, Wright, Margaret J., additional, Yang, Tony T., additional, Zhu, Alyssa, additional, Veltman, Dick J., additional, Thompson, Paul M., additional, Jahanshad, Neda, additional, and Schmaal, Lianne, additional

Published
2019
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48. Altered white matter microstructure in 22q11.2 deletion syndrome: a multisite diffusion tensor imaging study

Author

Villalón-Reina, Julio E., primary, Martínez, Kenia, additional, Qu, Xiaoping, additional, Ching, Christopher R. K., additional, Nir, Talia M., additional, Kothapalli, Deydeep, additional, Corbin, Conor, additional, Sun, Daqiang, additional, Lin, Amy, additional, Forsyth, Jennifer K., additional, Kushan, Leila, additional, Vajdi, Ariana, additional, Jalbrzikowski, Maria, additional, Hansen, Laura, additional, Jonas, Rachel K., additional, van Amelsvoort, Therese, additional, Bakker, Geor, additional, Kates, Wendy R., additional, Antshel, Kevin M., additional, Fremont, Wanda, additional, Campbell, Linda E., additional, McCabe, Kathryn L., additional, Daly, Eileen, additional, Gudbrandsen, Maria, additional, Murphy, Clodagh M., additional, Murphy, Declan, additional, Craig, Michael, additional, Emanuel, Beverly, additional, McDonald-McGinn, Donna M., additional, Vorstman, Jacob A.S., additional, Fiksinski, Ania M., additional, Koops, Sanne, additional, Ruparel, Kosha, additional, Roalf, David, additional, Gur, Raquel E., additional, Eric Schmitt, J., additional, Simon, Tony J., additional, Goodrich-Hunsaker, Naomi J., additional, Durdle, Courtney A., additional, Doherty, Joanne L., additional, Cunningham, Adam C., additional, van den Bree, Marianne, additional, Linden, David E. J., additional, Owen, Michael, additional, Moss, Hayley, additional, Kelly, Sinead, additional, Donohoe, Gary, additional, Murphy, Kieran C., additional, Arango, Celso, additional, Jahanshad, Neda, additional, Thompson, Paul M., additional, and Bearden, Carrie E., additional

Published
2019
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49. Cortical profiles of numerous psychiatric disorders and normal development share a common pattern

Author

Cao, Zhipeng, Cupertino, Renata B., Ottino-Gonzalez, Jonatan, Murphy, Alistair, Pancholi, Devarshi, Juliano, Anthony, Chaarani, Bader, Albaugh, Matthew, Yuan, Dekang, Schwab, Nathan, Stafford, James, Goudriaan, Anna E., Hutchison, Kent, Li, Chiang-Shan R., Luijten, Maartje, Groefsema, Martine, Momenan, Reza, Schmaal, Lianne, Sinha, Rajita, van Holst, Ruth J., Veltman, Dick J., Wiers, Reinout W., Porjesz, Bernice, Lett, Tristram, Banaschewski, Tobias, Bokde, Arun L. W., Desrivières, Sylvane, Flor, Herta, Grigis, Antoine, Gowland, Penny, Heinz, Andreas, Brühl, Rüdiger, Martinot, Jean-Luc, Martinot, Marie-Laure Paillère, Artiges, Eric, Nees, Frauke, Orfanos, Dimitri Papadopoulos, Paus, Tomáš, Poustka, Luise, Hohmann, Sarah, Millenet, Sabina, Fröhner, Juliane H., Robinson, Lauren, Smolka, Michael N., Walter, Henrik, Winterer, Jeanne, Schumann, Gunter, Whelan, Robert, Bhatt, Ravi R., Zhu, Alyssa, Conrod, Patricia, Jahanshad, Neda, Thompson, Paul M., Mackey, Scott, and Garavan, Hugh

Abstract

The neurobiological bases of the association between development and psychopathology remain poorly understood. Here, we identify a shared spatial pattern of cortical thickness (CT) in normative development and several psychiatric and neurological disorders. Principal component analysis (PCA) was applied to CT of 68 regions in the Desikan-Killiany atlas derived from three large-scale datasets comprising a total of 41,075 neurotypical participants. PCA produced a spatially broad first principal component (PC1) that was reproducible across datasets. Then PC1 derived from healthy adult participants was compared to the pattern of CT differences associated with psychiatric and neurological disorders comprising a total of 14,886 cases and 20,962 controls from seven ENIGMA disease-related working groups, normative maturation and aging comprising a total of 17,697 scans from the ABCD Study® and the IMAGEN developmental study, and 17,075 participants from the ENIGMA Lifespan working group, as well as gene expression maps from the Allen Human Brain Atlas. Results revealed substantial spatial correspondences between PC1 and widespread lower CT observed in numerous psychiatric disorders. Moreover, the PC1 pattern was also correlated with the spatial pattern of normative maturation and aging. The transcriptional analysis identified a set of genes including KCNA2, KCNS1and KCNS2with expression patterns closely related to the spatial pattern of PC1. The gene category enrichment analysis indicated that the transcriptional correlations of PC1 were enriched to multiple gene ontology categories and were specifically over-represented starting at late childhood, coinciding with the onset of significant cortical maturation and emergence of psychopathology during the prepubertal-to-pubertal transition. Collectively, the present study reports a reproducible latent pattern of CT that captures interregional profiles of cortical changes in both normative brain maturation and a spectrum of psychiatric disorders. The pubertal timing of the expression of PC1-related genes implicates disrupted neurodevelopment in the pathogenesis of the spectrum of psychiatric diseases emerging during adolescence.

Published
2022
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50. Large-scale mapping of cortical alterations in 22q11.2 deletion syndrome: Convergence with idiopathic psychosis and effects of deletion size

Author

Sun, Daqiang, primary, Ching, Christopher R. K., additional, Lin, Amy, additional, Forsyth, Jennifer K., additional, Kushan, Leila, additional, Vajdi, Ariana, additional, Jalbrzikowski, Maria, additional, Hansen, Laura, additional, Villalon-Reina, Julio E., additional, Qu, Xiaoping, additional, Jonas, Rachel K., additional, van Amelsvoort, Therese, additional, Bakker, Geor, additional, Kates, Wendy R., additional, Antshel, Kevin M., additional, Fremont, Wanda, additional, Campbell, Linda E., additional, McCabe, Kathryn L., additional, Daly, Eileen, additional, Gudbrandsen, Maria, additional, Murphy, Clodagh M., additional, Murphy, Declan, additional, Craig, Michael, additional, Vorstman, Jacob, additional, Fiksinski, Ania, additional, Koops, Sanne, additional, Ruparel, Kosha, additional, Roalf, David R., additional, Gur, Raquel E., additional, Schmitt, J. Eric, additional, Simon, Tony J., additional, Goodrich-Hunsaker, Naomi J., additional, Durdle, Courtney A., additional, Bassett, Anne S., additional, Chow, Eva W. C., additional, Butcher, Nancy J., additional, Vila-Rodriguez, Fidel, additional, Doherty, Joanne, additional, Cunningham, Adam, additional, van den Bree, Marianne B.M., additional, Linden, David E. J., additional, Moss, Hayley, additional, Owen, Michael J., additional, Murphy, Kieran C., additional, McDonald-McGinn, Donna M., additional, Emanuel, Beverly, additional, van Erp, Theo G. M., additional, Turner, Jessica A., additional, Thompson, Paul M., additional, and Bearden, Carrie E., additional

Published
2018
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