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1. Differences in the neural correlates of schizophrenia with positive and negative formal thought disorder in patients with schizophrenia in the ENIGMA dataset.

Author

Sharkey, Rachel, Bacon, Chelsea, Peterson, Zeru, Rootes-Murdy, Kelly, Salvador, Raymond, Pomarol-Clotet, Edith, Karuk, Andriana, Homan, Philipp, Ji, Ellen, Omlor, Wolfgang, Homan, Stephanie, Georgiadis, Foivos, Kaiser, Stefan, Kirschner, Matthias, Ehrlich, Stefan, Dannlowski, Udo, Grotegerd, Dominik, Goltermann, Janik, Meinert, Susanne, Kircher, Tilo, Stein, Frederike, Brosch, Katharina, Krug, Axel, Nenadic, Igor, Sim, Kang, Spalletta, Gianfranco, Banaj, Nerisa, Sponheim, Scott, Demro, Caroline, Ramsay, Ian, King, Margaret, Quidé, Yann, Green, Melissa, Nguyen, Dana, Preda, Adrian, Calhoun, Vince, Turner, Jessica, van Erp, Theo, and Nickl-Jockschat, Thomas

Subjects
Humans, Schizophrenia, Male, Female, Adult, Brain, Middle Aged, Schizophrenic Psychology, Neuroimaging, Cohort Studies, Magnetic Resonance Imaging, Thinking
Abstract

Formal thought disorder (FTD) is a clinical key factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, the relationship between FTD symptom dimensions and patterns of regional brain volume loss in schizophrenia remains to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles by enrolling a large multi-site cohort acquired by the ENIGMA Schizophrenia Working Group (752 schizophrenia patients and 1256 controls), to unravel the neuroanatomy of FTD in schizophrenia and using virtual histology tools on implicated brain regions to investigate the cellular basis. Based on the findings of previous clinical and neuroimaging studies, we decided to separately explore positive, negative and total formal thought disorder. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but positive and negative FTD demonstrated a dissociation: negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD also showed associations with microglial cell types. These results provide an important step towards linking FTD to brain structural changes and their cellular underpinnings, providing an avenue for a better mechanistic understanding of this syndrome.

Published
2024

2. Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Author

Kennedy, Eamonn, Liebel, Spencer, Lindsey, Hannah, Vadlamani, Shashank, Lei, Pui-Wa, Adamson, Maheen, Alda, Martin, Alonso-Lana, Silvia, Anderson, Tim, Arango, Celso, Asarnow, Robert, Avram, Mihai, Ayesa-Arriola, Rosa, Babikian, Talin, Banaj, Nerisa, Bird, Laura, Borgwardt, Stefan, Brodtmann, Amy, Brosch, Katharina, Caeyenberghs, Karen, Calhoun, Vince, Chiaravalloti, Nancy, Cifu, David, Crespo-Facorro, Benedicto, Dalrymple-Alford, John, Dams-OConnor, Kristen, Dannlowski, Udo, Darby, David, Davenport, Nicholas, DeLuca, John, Diaz-Caneja, Covadonga, Disner, Seth, Dobryakova, Ekaterina, Ehrlich, Stefan, Esopenko, Carrie, Ferrarelli, Fabio, Frank, Lea, Franz, Carol, Fuentes-Claramonte, Paola, Genova, Helen, Giza, Christopher, Goltermann, Janik, Grotegerd, Dominik, Gruber, Marius, Gutierrez-Zotes, Alfonso, Ha, Minji, Haavik, Jan, Hinkin, Charles, Hoskinson, Kristen, Hubl, Daniela, Irimia, Andrei, Jansen, Andreas, Kaess, Michael, Kang, Xiaojian, Kenney, Kimbra, Keřková, Barbora, Khlif, Mohamed, Kim, Minah, Kindler, Jochen, Kircher, Tilo, Knížková, Karolina, Kolskår, Knut, Krch, Denise, Kremen, William, Kuhn, Taylor, Kumari, Veena, Kwon, Junsoo, Langella, Roberto, Laskowitz, Sarah, Lee, Jungha, Lengenfelder, Jean, Liou-Johnson, Victoria, Lippa, Sara, Løvstad, Marianne, Lundervold, Astri, Marotta, Cassandra, Marquardt, Craig, Mattos, Paulo, Mayeli, Ahmad, McDonald, Carrie, Meinert, Susanne, Melzer, Tracy, Merchán-Naranjo, Jessica, Michel, Chantal, Morey, Rajendra, Mwangi, Benson, Myall, Daniel, Nenadić, Igor, Newsome, Mary, Nunes, Abraham, OBrien, Terence, Oertel, Viola, Ollinger, John, Olsen, Alexander, Ortiz García de la Foz, Victor, Ozmen, Mustafa, Pardoe, Heath, Parent, Marise, Piras, Fabrizio, and Piras, Federica

Subjects
Parkinson’s disease, attention-deficit/hyperactivity disorder, bipolar disorder, dementia, depression, memory, schizophrenia, stroke, traumatic brain injury, verbal learning
Abstract

Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinsons disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia (p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores (p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.

Published
2024

3. 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

4. Genetic and functional analyses of CTBP2 in anorexia nervosa and body weight regulation

Author

Giuranna, Johanna, Zheng, Yiran, Brandt, Matthäus, Jall, Sigrid, Mukherjee, Amrita, Shankhwar, Soni, Renner, Simone, Kurapati, Nirup Kumar, May, Caroline, Peters, Triinu, Herpertz-Dahlmann, Beate, Seitz, Jochen, de Zwaan, Martina, Herzog, Wolfgang, Ehrlich, Stefan, Zipfel, Stephan, Giel, Katrin, Egberts, Karin, Burghardt, Roland, Föcker, Manuel, Marcus, Katrin, Keyvani, Kathy, Müller, Timo D., Schmitz, Frank, Rajcsanyi, Luisa Sophie, and Hinney, Anke

Published
2024
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5. Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries

Author

García-Marín, Luis M., Campos, Adrian I., Diaz-Torres, Santiago, Rabinowitz, Jill A., Ceja, Zuriel, Mitchell, Brittany L., Grasby, Katrina L., Thorp, Jackson G., Agartz, Ingrid, Alhusaini, Saud, Ames, David, Amouyel, Philippe, Andreassen, Ole A., Arfanakis, Konstantinos, Arias-Vasquez, Alejandro, Armstrong, Nicola J., Athanasiu, Lavinia, Bastin, Mark E., Beiser, Alexa S., Bennett, David A., Bis, Joshua C., Boks, Marco P. M., Boomsma, Dorret I., Brodaty, Henry, Brouwer, Rachel M., Buitelaar, Jan K., Burkhardt, Ralph, Cahn, Wiepke, Calhoun, Vince D., Carmichael, Owen T., Chakravarty, Mallar, Chen, Qiang, Ching, Christopher R. K., Cichon, Sven, Crespo-Facorro, Benedicto, Crivello, Fabrice, Dale, Anders M., Smith, George Davey, de Geus, Eco J. C., De Jager, Philip L., de Zubicaray, Greig I., Debette, Stéphanie, DeCarli, Charles, Depondt, Chantal, Desrivières, Sylvane, Djurovic, Srdjan, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fernández, Guillén, Filippi, Irina, Fisher, Simon E., Fleischman, Debra A., Fletcher, Evan, Fornage, Myriam, Forstner, Andreas J., Francks, Clyde, Franke, Barbara, Ge, Tian, Goldman, Aaron L., Grabe, Hans J., Green, Robert C., Grimm, Oliver, Groenewold, Nynke A., Gruber, Oliver, Gudnason, Vilmundur, Håberg, Asta K., Haukvik, Unn K., Heinz, Andreas, Hibar, Derrek P., Hilal, Saima, Himali, Jayandra J., Ho, Beng-Choon, Hoehn, David F., Hoekstra, Pieter J., Hofer, Edith, Hoffmann, Wolfgang, Holmes, Avram J., Homuth, Georg, Hosten, Norbert, Ikram, M. Kamran, Ipser, Jonathan C., Jack Jr, Clifford R., Jahanshad, Neda, Jönsson, Erik G., Kahn, Rene S., Kanai, Ryota, Klein, Marieke, Knol, Maria J., Launer, Lenore J., Lawrie, Stephen M., Hellard, Stephanie Le, Lee, Phil H., Lemaître, Hervé, Li, Shuo, Liewald, David C. M., Lin, Honghuang, Longstreth, Jr, W. T., Lopez, Oscar L., Luciano, Michelle, Maillard, Pauline, Marquand, Andre F., Martin, Nicholas G., Martinot, Jean-Luc, Mather, Karen A., Mattay, Venkata S., McMahon, Katie L., Mecocci, Patrizia, Melle, Ingrid, Meyer-Lindenberg, Andreas, Mirza-Schreiber, Nazanin, Milaneschi, Yuri, Mosley, Thomas H., Mühleisen, Thomas W., Müller-Myhsok, Bertram, Maniega, Susana Muñoz, Nauck, Matthias, Nho, Kwangsik, Niessen, Wiro J., Nöthen, Markus M., Nyquist, Paul A., Oosterlaan, Jaap, Pandolfo, Massimo, Paus, Tomas, Pausova, Zdenka, Penninx, Brenda W. J. H., Pike, G. Bruce, Psaty, Bruce M., Pütz, Benno, Reppermund, Simone, Rietschel, Marcella D., Risacher, Shannon L., Romanczuk-Seiferth, Nina, Romero-Garcia, Rafael, Roshchupkin, Gennady V., Rotter, Jerome I., Sachdev, Perminder S., Sämann, Philipp G., Saremi, Arvin, Sargurupremraj, Muralidharan, Saykin, Andrew J., Schmaal, Lianne, Schmidt, Helena, Schmidt, Reinhold, Schofield, Peter R., Scholz, Markus, Schumann, Gunter, Schwarz, Emanuel, Shen, Li, Shin, Jean, Sisodiya, Sanjay M., Smith, Albert V., Smoller, Jordan W., Soininen, Hilkka S., Steen, Vidar M., Stein, Dan J., Stein, Jason L., Thomopoulos, Sophia I., Toga, Arthur W., Tordesillas-Gutiérrez, Diana, Trollor, Julian N., Valdes-Hernandez, Maria C., van ′t Ent, Dennis, van Bokhoven, Hans, van der Meer, Dennis, van der Wee, Nic J. A., Vázquez-Bourgon, Javier, Veltman, Dick J., Vernooij, Meike W., Villringer, Arno, Vinke, Louis N., Völzke, Henry, Walter, Henrik, Wardlaw, Joanna M., Weinberger, Daniel R., Weiner, Michael W., Wen, Wei, Westlye, Lars T., Westman, Eric, White, Tonya, Witte, A. Veronica, Wolf, Christiane, Yang, Jingyun, Zwiers, Marcel P., Ikram, M. Arfan, Seshadri, Sudha, Thompson, Paul M., Satizabal, Claudia L., Medland, Sarah E., and Rentería, Miguel E.

Published
2024
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7. Panoptica -- instance-wise evaluation of 3D semantic and instance segmentation maps

Author

Kofler, Florian, Möller, Hendrik, Buchner, Josef A., de la Rosa, Ezequiel, Ezhov, Ivan, Rosier, Marcel, Mekki, Isra, Shit, Suprosanna, Negwer, Moritz, Al-Maskari, Rami, Ertürk, Ali, Vinayahalingam, Shankeeth, Isensee, Fabian, Pati, Sarthak, Rueckert, Daniel, Kirschke, Jan S., Ehrlich, Stefan K., Reinke, Annika, Menze, Bjoern, Wiestler, Benedikt, and Piraud, Marie

Subjects
Computer Science - Computer Vision and Pattern Recognition, Computer Science - Artificial Intelligence, Computer Science - Machine Learning, Electrical Engineering and Systems Science - Image and Video Processing
Abstract

This paper introduces panoptica, a versatile and performance-optimized package designed for computing instance-wise segmentation quality metrics from 2D and 3D segmentation maps. panoptica addresses the limitations of existing metrics and provides a modular framework that complements the original intersection over union-based panoptic quality with other metrics, such as the distance metric Average Symmetric Surface Distance. The package is open-source, implemented in Python, and accompanied by comprehensive documentation and tutorials. panoptica employs a three-step metrics computation process to cover diverse use cases. The efficacy of panoptica is demonstrated on various real-world biomedical datasets, where an instance-wise evaluation is instrumental for an accurate representation of the underlying clinical task. Overall, we envision panoptica as a valuable tool facilitating in-depth evaluation of segmentation methods., Comment: 15 pages, 6 figures, 3 tables

Published
2023

8. Structural brain abnormalities and aggressive behaviour in schizophrenia: Mega-analysis of data from 2095 patients and 2861 healthy controls via the ENIGMA consortium

Author

Lamsma, Jelle, Raine, Adrian, Kia, Seyed M, Cahn, Wiepke, Arold, Dominic, Banaj, Nerisa, Barone, Annarita, Brosch, Katharina, Brouwer, Rachel, Brunetti, Arturo, Calhoun, Vince D, Chew, Qian H, Choi, Sunah, Chung, Young-Chul, Ciccarelli, Mariateresa, Cobia, Derin, Cocozza, Sirio, Dannlowski, Udo, Dazzan, Paola, de Bartolomeis, Andrea, Di Forti, Marta, Dumais, Alexandre, Edmond, Jesse T, Ehrlich, Stefan, Evermann, Ulrika, Flinkenflügel, Kira, Georgiadis, Foivos, Glahn, David C, Goltermann, Janik, Green, Melissa J, Grotegerd, Dominik, Guerrero-Pedraza, Amalia, Ha, Minji, Hong, Elliot L, Pol, Hilleke Hulshoff, Iasevoli, Felice, Kaiser, Stefan, Kaleda, Vasily, Karuk, Andriana, Kim, Minah, Kircher, Tilo, Kirschner, Matthias, Kochunov, Peter, Kwon, Jun Soo, Lebedeva, Irina, Lencer, Rebekka, Marques, Tiago R, Meinert, Susanne, Murray, Robin, Nenadić, Igor, Nguyen, Dana, Pearlson, Godfrey, Piras, Fabrizio, Pomarol-Clotet, Edith, Pontillo, Giuseppe, Potvin, Stéphane, Preda, Adrian, Quidé, Yann, Rodrigue, Amanda, Rootes-Murdy, Kelly, Salvador, Raymond, Skoch, Antonin, Sim, Kang, Spalletta, Gianfranco, Spaniel, Filip, Stein, Frederike, Thomas-Odenthal, Florian, Tikàsz, Andràs, Tomecek, David, Tomyshev, Alexander, Tranfa, Mario, Tsogt, Uyanga, Turner, Jessica A, van Erp, Theo GM, van Haren, Neeltje EM, van Os, Jim, Vecchio, Daniela, Wang, Lei, Wroblewski, Adrian, and Nickl-Jockschat, Thomas

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Schizophrenia, Brain Disorders, Neurosciences, Biomedical Imaging, Serious Mental Illness, Mental Health, Mental Illness, Mental health
Abstract

BACKGROUND: Schizophrenia is associated with an increased risk of aggressive behaviour, which may partly be explained by illness-related changes in brain structure. However, previous studies have been limited by group-level analyses, small and selective samples of inpatients and long time lags between exposure and outcome. METHODS: This cross-sectional study pooled data from 20 sites participating in the international ENIGMA-Schizophrenia Working Group. Sites acquired T1-weighted and diffusion-weighted magnetic resonance imaging scans in a total of 2095 patients with schizophrenia and 2861 healthy controls. Measures of grey matter volume and white matter microstructural integrity were extracted from the scans using harmonised protocols. For each measure, normative modelling was used to calculate how much patients deviated (in z-scores) from healthy controls at the individual level. Ordinal regression models were used to estimate the associations of these deviations with concurrent aggressive behaviour (as odds ratios [ORs] with 99% confidence intervals [CIs]). Mediation analyses were performed for positive symptoms (i.e., delusions, hallucinations and disorganised thinking), impulse control and illness insight. Aggression and potential mediators were assessed with the Positive and Negative Syndrome Scale, Scale for the Assessment of Positive Symptoms or Brief Psychiatric Rating Scale. RESULTS: Aggressive behaviour was significantly associated with reductions in total cortical volume (OR [99% CI] = 0.88 [0.78, 0.98], p = .003) and global white matter integrity (OR [99% CI] = 0.72 [0.59, 0.88], p = 3.50 × 10-5) and additional reductions in dorsolateral prefrontal cortex volume (OR [99% CI] = 0.85 [0.74, 0.97], p =.002), inferior parietal lobule volume (OR [99% CI] = 0.76 [0.66, 0.87], p = 2.20 × 10-7) and internal capsule integrity (OR [99% CI] = 0.76 [0.63, 0.92], p = 2.90 × 10-4). Except for inferior parietal lobule volume, these associations were largely mediated by increased severity of positive symptoms and reduced impulse control. CONCLUSIONS: This study provides evidence that the co-occurrence of positive symptoms, poor impulse control and aggressive behaviour in schizophrenia has a neurobiological basis, which may inform the development of therapeutic interventions.

Published
2024

9. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers.

Author

Boen, Rune, Kaufmann, Tobias, van der Meer, Dennis, Frei, Oleksandr, Agartz, Ingrid, Ames, David, Andersson, Micael, Armstrong, Nicola, Artiges, Eric, Atkins, Joshua, Bauer, Jochen, Benedetti, Francesco, Boomsma, Dorret, Brodaty, Henry, Brosch, Katharina, Buckner, Randy, Cairns, Murray, Calhoun, Vince, Caspers, Svenja, Cichon, Sven, Corvin, Aiden, Crespo-Facorro, Benedicto, Dannlowski, Udo, David, Friederike, de Geus, Eco, de Zubicaray, Greig, Desrivières, Sylvane, Doherty, Joanne, Donohoe, Gary, Ehrlich, Stefan, Eising, Else, Espeseth, Thomas, Fisher, Simon, Forstner, Andreas, Fortaner-Uyà, Lidia, Frouin, Vincent, Fukunaga, Masaki, Ge, Tian, Glahn, David, Goltermann, Janik, Grabe, Hans, Green, Melissa, Groenewold, Nynke, Grotegerd, Dominik, Grøntvedt, Gøril, Hahn, Tim, Hashimoto, Ryota, Hehir-Kwa, Jayne, Henskens, Frans, Holmes, Avram, Håberg, Asta, Haavik, Jan, Jacquemont, Sebastien, Jansen, Andreas, Jockwitz, Christiane, Jönsson, Erik, Kikuchi, Masataka, Kircher, Tilo, Kumar, Kuldeep, Le Hellard, Stephanie, Leu, Costin, Linden, David, Liu, Jingyu, Loughnan, Robert, Mather, Karen, McMahon, Katie, McRae, Allan, Medland, Sarah, Meinert, Susanne, Moreau, Clara, Morris, Derek, Mowry, Bryan, Mühleisen, Thomas, Nenadić, Igor, Nöthen, Markus, Nyberg, Lars, Ophoff, Roel, Owen, Michael, Pantelis, Christos, Paolini, Marco, Paus, Tomas, Pausova, Zdenka, Persson, Karin, Quidé, Yann, Marques, Tiago, Sachdev, Perminder, Sando, Sigrid, Schall, Ulrich, Scott, Rodney, Selbæk, Geir, Shumskaya, Elena, Silva, Ana, Sisodiya, Sanjay, Stein, Frederike, Stein, Dan, Straube, Benjamin, Streit, Fabian, Strike, Lachlan, Teumer, Alexander, and Teutenberg, Lea

Subjects
15q11.2 BP1-BP2, 1q21.1 distal, Brain structure, Copy number variants, Intraindividual variability, Magnetic resonance imaging, Humans, Chromosome Deletion, Brain, Magnetic Resonance Imaging, Abnormalities, Multiple, Chromosomes, Human, Pair 15, DNA Copy Number Variations
Abstract

BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individuals regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.

Published
2024

11. Framing image registration as a landmark detection problem for label-noise-aware task representation (HitR)

Author

Waldmannstetter, Diana, Ezhov, Ivan, Wiestler, Benedikt, Campi, Francesco, Kukuljan, Ivan, Ehrlich, Stefan, Vinayahalingam, Shankeeth, Baheti, Bhakti, Chakrabarty, Satrajit, Baid, Ujjwal, Bakas, Spyridon, Schwarting, Julian, Metz, Marie, Kirschke, Jan S., Rueckert, Daniel, Heckemann, Rolf A., Piraud, Marie, Menze, Bjoern H., and Kofler, Florian

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Physics - Medical Physics
Abstract

Accurate image registration is pivotal in biomedical image analysis, where selecting suitable registration algorithms demands careful consideration. While numerous algorithms are available, the evaluation metrics to assess their performance have remained relatively static. This study addresses this challenge by introducing a novel evaluation metric termed Landmark Hit Rate (HitR), which focuses on the clinical relevance of image registration accuracy. Unlike traditional metrics such as Target Registration Error, which emphasize subresolution differences, HitR considers whether registration algorithms successfully position landmarks within defined confidence zones. This paradigm shift acknowledges the inherent annotation noise in medical images, allowing for more meaningful assessments. To equip HitR with label-noise-awareness, we propose defining these confidence zones based on an Inter-rater Variance analysis. Consequently, hit rate curves are computed for varying landmark zone sizes, enabling performance measurement for a task-specific level of accuracy. Our approach offers a more realistic and meaningful assessment of image registration algorithms, reflecting their suitability for clinical and biomedical applications.

Published
2023

14. The Brain Tumor Segmentation (BraTS) Challenge: Local Synthesis of Healthy Brain Tissue via Inpainting

Author

Kofler, Florian, Meissen, Felix, Steinbauer, Felix, Graf, Robert, Ehrlich, Stefan K, Reinke, Annika, Oswald, Eva, Waldmannstetter, Diana, Hoelzl, Florian, Horvath, Izabela, Turgut, Oezguen, Shit, Suprosanna, Bukas, Christina, Yang, Kaiyuan, Paetzold, Johannes C., de da Rosa, Ezequiel, Mekki, Isra, Vinayahalingam, Shankeeth, Kassem, Hasan, Zhang, Juexin, Chen, Ke, Weng, Ying, Durrer, Alicia, Cattin, Philippe C., Wolleb, Julia, Sadique, M. S., Rahman, M. M., Farzana, W., Temtam, A., Iftekharuddin, K. M., Adewole, Maruf, Anwar, Syed Muhammad, Baid, Ujjwal, Janas, Anastasia, Kazerooni, Anahita Fathi, LaBella, Dominic, Li, Hongwei Bran, Moawad, Ahmed W, Conte, Gian-Marco, Farahani, Keyvan, Eddy, James, Sheller, Micah, Pati, Sarthak, Karagyris, Alexandros, Aristizabal, Alejandro, Bergquist, Timothy, Chung, Verena, Shinohara, Russell Takeshi, Dako, Farouk, Wiggins, Walter, Reitman, Zachary, Wang, Chunhao, Liu, Xinyang, Jiang, Zhifan, Johanson, Elaine, Meier, Zeke, Familiar, Ariana, Davatzikos, Christos, Freymann, John, Kirby, Justin, Bilello, Michel, Fathallah-Shaykh, Hassan M, Wiest, Roland, Kirschke, Jan, Colen, Rivka R, Kotrotsou, Aikaterini, Lamontagne, Pamela, Marcus, Daniel, Milchenko, Mikhail, Nazeri, Arash, Weber, Marc-André, Mahajan, Abhishek, Mohan, Suyash, Mongan, John, Hess, Christopher, Cha, Soonmee, Villanueva-Meyer, Javier, Colak, Errol, Crivellaro, Priscila, Jakab, Andras, Fatade, Abiodun, Omidiji, Olubukola, Lagos, Rachel Akinola, Olatunji, O O, Khanna, Goldey, Kirkpatrick, John, Alonso-Basanta, Michelle, Rashid, Arif, Bornhorst, Miriam, Nabavizadeh, Ali, Lepore, Natasha, Palmer, Joshua, Porras, Antonio, Albrecht, Jake, Anazodo, Udunna, Aboian, Mariam, Calabrese, Evan, Rudie, Jeffrey David, Linguraru, Marius George, Iglesias, Juan Eugenio, Van Leemput, Koen, Bakas, Spyridon, Wiestler, Benedikt, Ezhov, Ivan, Piraud, Marie, and Menze, Bjoern H

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

A myriad of algorithms for the automatic analysis of brain MR images is available to support clinicians in their decision-making. For brain tumor patients, the image acquisition time series typically starts with an already pathological scan. This poses problems, as many algorithms are designed to analyze healthy brains and provide no guarantee for images featuring lesions. Examples include, but are not limited to, algorithms for brain anatomy parcellation, tissue segmentation, and brain extraction. To solve this dilemma, we introduce the BraTS inpainting challenge. Here, the participants explore inpainting techniques to synthesize healthy brain scans from lesioned ones. The following manuscript contains the task formulation, dataset, and submission procedure. Later, it will be updated to summarize the findings of the challenge. The challenge is organized as part of the ASNR-BraTS MICCAI challenge., Comment: 14 pages, 6 figures

Published
2023

15. Parameter Optimization of LLC-Converter with multiple operation points using Reinforcement Learning

Author

Kruse, Georg, Happel, Dominik, Ditze, Stefan, Ehrlich, Stefan, and Rosskopf, Andreas

Subjects
Computer Science - Machine Learning
Abstract

The optimization of electrical circuits is a difficult and time-consuming process performed by experts, but also increasingly by sophisticated algorithms. In this paper, a reinforcement learning (RL) approach is adapted to optimize a LLC converter at multiple operation points corresponding to different output powers at high converter efficiency at different switching frequencies. During a training period, the RL agent learns a problem specific optimization policy enabling optimizations for any objective and boundary condition within a pre-defined range. The results show, that the trained RL agent is able to solve new optimization problems based on LLC converter simulations using Fundamental Harmonic Approximation (FHA) within 50 tuning steps for two operation points with power efficiencies greater than 90%. Therefore, this AI technique provides the potential to augment expert-driven design processes with data-driven strategy extraction in the field of power electronics and beyond., Comment: 5 pages, 6 figures, results were already presented at CEFC 2022

Published
2023

17. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium.

Author

Schijven, Dick, Postema, Merel C, Fukunaga, Masaki, Matsumoto, Junya, Miura, Kenichiro, de Zwarte, Sonja MC, van Haren, Neeltje EM, Cahn, Wiepke, Hulshoff Pol, Hilleke E, Kahn, René S, Ayesa-Arriola, Rosa, Ortiz-García de la Foz, Víctor, Tordesillas-Gutierrez, Diana, Vázquez-Bourgon, Javier, Crespo-Facorro, Benedicto, Alnæs, Dag, Dahl, Andreas, Westlye, Lars T, Agartz, Ingrid, Andreassen, Ole A, Jönsson, Erik G, Kochunov, Peter, Bruggemann, Jason M, Catts, Stanley V, Michie, Patricia T, Mowry, Bryan J, Quidé, Yann, Rasser, Paul E, Schall, Ulrich, Scott, Rodney J, Carr, Vaughan J, Green, Melissa J, Henskens, Frans A, Loughland, Carmel M, Pantelis, Christos, Weickert, Cynthia Shannon, Weickert, Thomas W, de Haan, Lieuwe, Brosch, Katharina, Pfarr, Julia-Katharina, Ringwald, Kai G, Stein, Frederike, Jansen, Andreas, Kircher, Tilo TJ, Nenadić, Igor, Krämer, Bernd, Gruber, Oliver, Satterthwaite, Theodore D, Bustillo, Juan, Mathalon, Daniel H, Preda, Adrian, Calhoun, Vince D, Ford, Judith M, Potkin, Steven G, Chen, Jingxu, Tan, Yunlong, Wang, Zhiren, Xiang, Hong, Fan, Fengmei, Bernardoni, Fabio, Ehrlich, Stefan, Fuentes-Claramonte, Paola, Garcia-Leon, Maria Angeles, Guerrero-Pedraza, Amalia, Salvador, Raymond, Sarró, Salvador, Pomarol-Clotet, Edith, Ciullo, Valentina, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Spalletta, Gianfranco, Michielse, Stijn, van Amelsvoort, Therese, Dickie, Erin W, Voineskos, Aristotle N, Sim, Kang, Ciufolini, Simone, Dazzan, Paola, Murray, Robin M, Kim, Woo-Sung, Chung, Young-Chul, Andreou, Christina, Schmidt, André, Borgwardt, Stefan, McIntosh, Andrew M, Whalley, Heather C, Lawrie, Stephen M, du Plessis, Stefan, Luckhoff, Hilmar K, Scheffler, Freda, Emsley, Robin, Grotegerd, Dominik, Lencer, Rebekka, Dannlowski, Udo, Edmond, Jesse T, Rootes-Murdy, Kelly, Stephen, Julia M, Mayer, Andrew R, and Antonucci, Linda A

Subjects
Brain, Cerebral Cortex, Humans, Magnetic Resonance Imaging, Case-Control Studies, Schizophrenia, Female, Male, Functional Laterality, asymmetry, brain imaging, cortical, subcortical, Clinical Research, Mental Health, Neurosciences, Brain Disorders, Mental health
Abstract

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Published
2023

18. 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

19. Common Genetic Variation and Age of Onset of Anorexia Nervosa.

Author

Watson, Hunna J, Thornton, Laura M, Yilmaz, Zeynep, Baker, Jessica H, Coleman, Jonathan RI, Adan, Roger AH, Alfredsson, Lars, Andreassen, Ole A, Ask, Helga, Berrettini, Wade H, Boehnke, Michael, Boehm, Ilka, Boni, Claudette, Buehren, Katharina, Bulant, Josef, Burghardt, Roland, Chang, Xiao, Cichon, Sven, Cone, Roger D, Courtet, Philippe, Crow, Scott, Crowley, James J, Danner, Unna N, de Zwaan, Martina, Dedoussis, George, DeSocio, Janiece E, Dick, Danielle M, Dikeos, Dimitris, Dina, Christian, Djurovic, Srdjan, Dmitrzak-Weglarz, Monika, Docampo-Martinez, Elisa, Duriez, Philibert, Egberts, Karin, Ehrlich, Stefan, Eriksson, Johan G, Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Farmer, Anne, Fernández-Aranda, Fernando, Fichter, Manfred M, Föcker, Manuel, Foretova, Lenka, Forstner, Andreas J, Frei, Oleksandr, Gallinger, Steven, Giegling, Ina, Giuranna, Johanna, Gonidakis, Fragiskos, Gorwood, Philip, Gratacòs, Mònica, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Hauser, Joanna, Havdahl, Alexandra, Hebebrand, Johannes, Helder, Sietske G, Herms, Stefan, Herpertz-Dahlmann, Beate, Herzog, Wolfgang, Hinney, Anke, Hübel, Christopher, Hudson, James I, Imgart, Hartmut, Jamain, Stephanie, Janout, Vladimir, Jiménez-Murcia, Susana, Jones, Ian R, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Kaprio, Jaakko, Karhunen, Leila, Kas, Martien JH, Keel, Pamela K, Kennedy, James L, Keski-Rahkonen, Anna, Kiezebrink, Kirsty, Klareskog, Lars, Klump, Kelly L, Knudsen, Gun Peggy S, La Via, Maria C, Le Hellard, Stephanie, Leboyer, Marion, Li, Dong, Lilenfeld, Lisa, Lin, Bochao, Lissowska, Jolanta, Luykx, Jurjen, Magistretti, Pierre, Maj, Mario, Marsal, Sara, Marshall, Christian R, Mattingsdal, Morten, Meulenbelt, Ingrid, Micali, Nadia, Mitchell, Karen S, and Monteleone, Alessio Maria

Subjects
Age of onset, Anorexia nervosa, Early-onset, GWAS, Genetic risk score, Genetics, Menarche, Mendelian randomization, Puberty, Mental Health, Human Genome, Eating Disorders, Anorexia, Brain Disorders, Pediatric, Prevention, Aetiology, 2.1 Biological and endogenous factors
Abstract

BackgroundGenetics and biology may influence the age of onset of anorexia nervosa (AN). The aims of this study were to determine whether common genetic variation contributes to age of onset of AN and to investigate the genetic associations between age of onset of AN and age at menarche.MethodsA secondary analysis of the Psychiatric Genomics Consortium genome-wide association study (GWAS) of AN was performed, which included 9335 cases and 31,981 screened controls, all from European ancestries. We conducted GWASs of age of onset, early-onset AN (

Published
2022

20. 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

23. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Yash, Shin, Jean, Abé, Christoph, Agartz, Ingrid, Alloza, Clara, Alnæs, Dag, Ambrogi, Sonia, Antonucci, Linda A, Arango, Celso, Arolt, Volker, Auzias, Guillaume, Ayesa-Arriola, Rosa, Banaj, Nerisa, Banaschewski, Tobias, Bandeira, Cibele, Başgöze, Zeynep, Cupertino, Renata Basso, Bau, Claiton HD, Bauer, Jochen, Baumeister, Sarah, Bernardoni, Fabio, Bertolino, Alessandro, Bonnin, Caterina Del Mar, Brandeis, Daniel, Brem, Silvia, Bruggemann, Jason, Bülow, Robin, Bustillo, Juan R, Calderoni, Sara, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carmona, Susanna, Carr, Vaughan J, Catts, Stanley V, Chenji, Sneha, Chew, Qian Hui, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Craven, Alexander R, Crespo-Facorro, Benedicto, Cullen, Kathryn, Dahl, Andreas, Dannlowski, Udo, Davey, Christopher G, Deruelle, Christine, Díaz-Caneja, Covadonga M, Dohm, Katharina, Ehrlich, Stefan, Epstein, Jeffery, Erwin-Grabner, Tracy, Eyler, Lisa T, Fedor, Jennifer, Fitzgerald, Jacqueline, Foran, William, Ford, Judith M, Fortea, Lydia, Fuentes-Claramonte, Paola, Fullerton, Janice, Furlong, Lisa, Gallagher, Louise, Gao, Bingchen, Gao, Si, Goikolea, Jose M, Gotlib, Ian, Goya-Maldonado, Roberto, Grabe, Hans J, Green, Melissa, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Haavik, Jan, Hahn, Tim, Harrison, Ben J, Heindel, Walter, Henskens, Frans, Heslenfeld, Dirk J, Hilland, Eva, Hoekstra, Pieter J, Hohmann, Sarah, Holz, Nathalie, Howells, Fleur M, Ipser, Jonathan C, Jahanshad, Neda, Jakobi, Babette, Jansen, Andreas, Janssen, Joost, Jonassen, Rune, Kaiser, Anna, Kaleda, Vasiliy, Karantonis, James, King, Joseph A, Kircher, Tilo, Kochunov, Peter, Koopowitz, Sheri-Michelle, Landén, Mikael, Landrø, Nils Inge, and Lawrie, Stephen

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Neurosciences, Genetics, Mental Health, Serious Mental Illness, Mental Illness, Women's Health, Brain Disorders, Preterm, Low Birth Weight and Health of the Newborn, Pregnancy, Pediatric, Perinatal Period - Conditions Originating in Perinatal Period, Behavioral and Social Science, Prevention, Schizophrenia, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Neurological, Reproductive health and childbirth, Mental health, Good Health and Well Being, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Bipolar Disorder, Cerebral Cortex, Child, Depressive Disorder, Major, Female, Humans, Infant, Newborn, Magnetic Resonance Imaging, Premature Birth, Cortical growth, Cortical surface area, Mental illness, Neurodevelopment, Neurogenesis, Psychiatric disorders, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundMorphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life.MethodsInterregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed.ResultsAcross the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth.ConclusionsOur findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Published
2022

27. Clinical and cortical similarities identified between bipolar disorder I and schizophrenia: A multivariate approach

Author

Rootes-Murdy, Kelly, Edmond, Jesse T, Jiang, Wenhao, Rahaman, Md A, Chen, Jiayu, Perrone-Bizzozero, Nora I, Calhoun, Vince D, van Erp, Theo GM, Ehrlich, Stefan, Agartz, Ingrid, Jönsson, Erik G, Andreassen, Ole A, Westlye, Lars T, Wang, Lei, Pearlson, Godfrey D, Glahn, David C, Hong, Elliot, Buchanan, Robert W, Kochunov, Peter, Voineskos, Aristotle, Malhotra, Anil, Tamminga, Carol A, Liu, Jingyu, and Turner, Jessica A

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Clinical Research, Bipolar Disorder, Serious Mental Illness, Mental Health, Brain Disorders, Schizophrenia, Mental health, bipolar disorder, schizophrenia, multivariate analysis, ICA, PANSS, Neurosciences, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

BackgroundStructural neuroimaging studies have identified similarities in the brains of individuals diagnosed with schizophrenia (SZ) and bipolar I disorder (BP), with overlap in regions of gray matter (GM) deficits between the two disorders. Recent studies have also shown that the symptom phenotypes associated with SZ and BP may allow for a more precise categorization than the current diagnostic criteria. In this study, we sought to identify GM alterations that were unique to each disorder and whether those alterations were also related to unique symptom profiles.Materials and methodsWe analyzed the GM patterns and clinical symptom presentations using independent component analysis (ICA), hierarchical clustering, and n-way biclustering in a large (N ∼ 3,000), merged dataset of neuroimaging data from healthy volunteers (HV), and individuals with either SZ or BP.ResultsComponent A showed a SZ and BP < HV GM pattern in the bilateral insula and cingulate gyrus. Component B showed a SZ and BP < HV GM pattern in the cerebellum and vermis. There were no significant differences between diagnostic groups in these components. Component C showed a SZ < HV and BP GM pattern bilaterally in the temporal poles. Hierarchical clustering of the PANSS scores and the ICA components did not yield new subgroups. N-way biclustering identified three unique subgroups of individuals within the sample that mapped onto different combinations of ICA components and symptom profiles categorized by the PANSS but no distinct diagnostic group differences.ConclusionThese multivariate results show that diagnostic boundaries are not clearly related to structural differences or distinct symptom profiles. Our findings add support that (1) BP tend to have less severe symptom profiles when compared to SZ on the PANSS without a clear distinction, and (2) all the gray matter alterations follow the pattern of SZ < BP < HV without a clear distinction between SZ and BP.

Published
2022

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

Author

Sønderby, Ida E, Ching, Christopher RK, Thomopoulos, Sophia I, van der Meer, Dennis, Sun, Daqiang, Villalon‐Reina, Julio E, Agartz, Ingrid, Amunts, Katrin, Arango, Celso, Armstrong, Nicola J, Ayesa‐Arriola, Rosa, Bakker, Geor, Bassett, Anne S, Boomsma, Dorret I, Bülow, Robin, Butcher, Nancy J, Calhoun, Vince D, Caspers, Svenja, Chow, Eva WC, Cichon, Sven, Ciufolini, Simone, Craig, Michael C, Crespo‐Facorro, Benedicto, Cunningham, Adam C, Dale, Anders M, Dazzan, Paola, de Zubicaray, Greig I, Djurovic, Srdjan, Doherty, Joanne L, Donohoe, Gary, Draganski, Bogdan, Durdle, Courtney A, Ehrlich, Stefan, Emanuel, Beverly S, Espeseth, Thomas, Fisher, Simon E, Ge, Tian, Glahn, David C, Grabe, Hans J, Gur, Raquel E, Gutman, Boris A, Haavik, Jan, Håberg, Asta K, Hansen, Laura A, Hashimoto, Ryota, Hibar, Derrek P, Holmes, Avram J, Hottenga, Jouke‐Jan, Pol, Hilleke E Hulshoff, Jalbrzikowski, Maria, Knowles, Emma EM, Kushan, Leila, Linden, David EJ, Liu, Jingyu, Lundervold, Astri J, Martin‐Brevet, Sandra, Martínez, Kenia, Mather, Karen A, Mathias, Samuel R, McDonald‐McGinn, Donna M, McRae, Allan F, Medland, Sarah E, Moberget, Torgeir, Modenato, Claudia, Sánchez, Jennifer Monereo, Moreau, Clara A, Mühleisen, Thomas W, Paus, Tomas, Pausova, Zdenka, Prieto, Carlos, Ragothaman, Anjanibhargavi, Reinbold, Céline S, Marques, Tiago Reis, Repetto, Gabriela M, Reymond, Alexandre, Roalf, David R, Rodriguez‐Herreros, Borja, Rucker, James J, Sachdev, Perminder S, Schmitt, James E, Schofield, Peter R, Silva, Ana I, Stefansson, Hreinn, Stein, Dan J, Tamnes, Christian K, Tordesillas‐Gutiérrez, Diana, Ulfarsson, Magnus O, Vajdi, Ariana, van 't Ent, Dennis, van den Bree, Marianne BM, Vassos, Evangelos, Vázquez‐Bourgon, Javier, Vila‐Rodriguez, Fidel, Walters, G Bragi, Wen, Wei, Westlye, Lars T, Wittfeld, Katharina, Zackai, Elaine H, Stefánsson, Kári, and Jacquemont, Sebastien

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Mental Health, Clinical Research, Pediatric, Genetics, Basic Behavioral and Social Science, Human Genome, Prevention, Brain Disorders, Behavioral and Social Science, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Mental health, Neurological, Brain, DNA Copy Number Variations, Humans, Magnetic Resonance Imaging, Mental Disorders, Multicenter Studies as Topic, Neurodevelopmental Disorders, Neuroimaging, brain structural imaging, copy number variant, diffusion tensor imaging, evolution, genetics-first approach, neurodevelopmental disorders, psychiatric disorders, ENIGMA-CNV Working Group, ENIGMA 22q11.2 Deletion Syndrome Working Group, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

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

Published
2022

29. A meta‐analysis of deep brain structural shape and asymmetry abnormalities in 2,833 individuals with schizophrenia compared with 3,929 healthy volunteers via the ENIGMA Consortium

Author

Gutman, Boris A, Erp, Theo GM, Alpert, Kathryn, Ching, Christopher RK, Isaev, Dmitry, Ragothaman, Anjani, Jahanshad, Neda, Saremi, Arvin, Zavaliangos‐Petropulu, Artemis, Glahn, David C, Shen, Li, Cong, Shan, Alnæs, Dag, Andreassen, Ole Andreas, Doan, Nhat Trung, Westlye, Lars T, Kochunov, Peter, Satterthwaite, Theodore D, Wolf, Daniel H, Huang, Alexander J, Kessler, Charles, Weideman, Andrea, Nguyen, Dana, Mueller, Bryon A, Faziola, Lawrence, Potkin, Steven G, Preda, Adrian, Mathalon, Daniel H, Bustillo, Juan, Calhoun, Vince, Ford, Judith M, Walton, Esther, Ehrlich, Stefan, Ducci, Giuseppe, Banaj, Nerisa, Piras, Fabrizio, Piras, Federica, Spalletta, Gianfranco, Canales‐Rodríguez, Erick J, Fuentes‐Claramonte, Paola, Pomarol‐Clotet, Edith, Radua, Joaquim, Salvador, Raymond, Sarró, Salvador, Dickie, Erin W, Voineskos, Aristotle, Tordesillas‐Gutiérrez, Diana, Crespo‐Facorro, Benedicto, Setién‐Suero, Esther, Son, Jacqueline Mayoral, Borgwardt, Stefan, Schönborn‐Harrisberger, Fabienne, Morris, Derek, Donohoe, Gary, Holleran, Laurena, Cannon, Dara, McDonald, Colm, Corvin, Aiden, Gill, Michael, Filho, Geraldo Busatto, Rosa, Pedro GP, Serpa, Mauricio H, Zanetti, Marcus V, Lebedeva, Irina, Kaleda, Vasily, Tomyshev, Alexander, Crow, Tim, James, Anthony, Cervenka, Simon, Sellgren, Carl M, Fatouros‐Bergman, Helena, Agartz, Ingrid, Howells, Fleur, Stein, Dan J, Temmingh, Henk, Uhlmann, Anne, Zubicaray, Greig I, McMahon, Katie L, Wright, Margie, Cobia, Derin, Csernansky, John G, Thompson, Paul M, Turner, Jessica A, and Wang, Lei

Subjects
Brain Disorders, Mental Health, Neurosciences, Schizophrenia, Mental health, Good Health and Well Being, Amygdala, Corpus Striatum, Hippocampus, Humans, Multicenter Studies as Topic, Neuroimaging, Thalamus, schizophrenia, structure, subcortical shape, Cognitive Sciences, Experimental Psychology
Abstract

Schizophrenia is associated with widespread alterations in subcortical brain structure. While analytic methods have enabled more detailed morphometric characterization, findings are often equivocal. In this meta-analysis, we employed the harmonized ENIGMA shape analysis protocols to collaboratively investigate subcortical brain structure shape differences between individuals with schizophrenia and healthy control participants. The study analyzed data from 2,833 individuals with schizophrenia and 3,929 healthy control participants contributed by 21 worldwide research groups participating in the ENIGMA Schizophrenia Working Group. Harmonized shape analysis protocols were applied to each site's data independently for bilateral hippocampus, amygdala, caudate, accumbens, putamen, pallidum, and thalamus obtained from T1-weighted structural MRI scans. Mass univariate meta-analyses revealed more-concave-than-convex shape differences in the hippocampus, amygdala, accumbens, and thalamus in individuals with schizophrenia compared with control participants, more-convex-than-concave shape differences in the putamen and pallidum, and both concave and convex shape differences in the caudate. Patterns of exaggerated asymmetry were observed across the hippocampus, amygdala, and thalamus in individuals with schizophrenia compared to control participants, while diminished asymmetry encompassed ventral striatum and ventral and dorsal thalamus. Our analyses also revealed that higher chlorpromazine dose equivalents and increased positive symptom levels were associated with patterns of contiguous convex shape differences across multiple subcortical structures. Findings from our shape meta-analysis suggest that common neurobiological mechanisms may contribute to gray matter reduction across multiple subcortical regions, thus enhancing our understanding of the nature of network disorganization in schizophrenia.

Published
2022

30. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Author

Dima, Danai, Modabbernia, Amirhossein, Papachristou, Efstathios, Doucet, Gaelle E, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N, Albajes-Eizagirre, Anton, Alnaes, Dag, Alpert, Kathryn I, Andersson, Micael, Andreasen, Nancy C, Andreassen, Ole A, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur-Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M, Buitelaar, Jan K, Busatto, Geraldo F, Buckner, Randy L, Calhoun, Vincent, Canales-Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Castellanos, Francisco X, Cervenka, Simon, Chaim-Avancini, Tiffany M, Ching, Christopher RK, Chubar, Victoria, Clark, Vincent P, Conrod, Patricia, Conzelmann, Annette, Crespo-Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A, Dannlowski, Udo, Dale, Anders M, Davey, Christopher, de Geus, Eco JC, de Haan, Lieuwe, de Zubicaray, Greig I, den Braber, Anouk, Dickie, Erin W, Di Giorgio, Annabella, Doan, Nhat Trung, Dørum, Erlend S, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros-Bergman, Helena, Fisher, Simon E, Fouche, Jean-Paul, Franke, Barbara, Frodl, Thomas, Fuentes-Claramonte, Paola, Glahn, David C, Gotlib, Ian H, Grabe, Hans-Jörgen, Grimm, Oliver, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hartman, Catharine A, Hatton, Sean N, Heinz, Andreas, Heslenfeld, Dirk J, Hibar, Derrek P, Hickie, Ian B, Ho, Beng-Choon, Hoekstra, Pieter J, Hohmann, Sarah, Holmes, Avram J, Hoogman, Martine, Hosten, Norbert, Howells, Fleur M, Hulshoff Pol, Hilleke E, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L, Jiang, Jiyang, Jönsson, Erik G, Joska, John A, Kahn, Rene, and Kalnin, Andrew

Subjects
Karolinska Schizophrenia Project, Amygdala, Hippocampus, Thalamus, Corpus Striatum, Humans, Human Development, Adolescent, Adult, Aged, Aged, 80 and over, Middle Aged, Child, Child, Preschool, Female, Male, Young Adult, Neuroimaging, ENIGMA, brain morphometry, longitudinal trajectories, multisite, Neurosciences, Aging, Aetiology, 2.1 Biological and endogenous factors, Mental health, Cognitive Sciences, Experimental Psychology
Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Published
2022

31. Reproducibility in the absence of selective reporting: An illustration from large‐scale brain asymmetry research

Author

Kong, Xiang‐Zhen, Mathias, Samuel R, Guadalupe, Tulio, Abé, Christoph, Agartz, Ingrid, Akudjedu, Theophilus N, Aleman, Andre, Alhusaini, Saud, Allen, Nicholas B, Ames, David, Andreassen, Ole A, Vasquez, Alejandro Arias, Armstrong, Nicola J, Asherson, Phil, Bergo, Felipe, Bastin, Mark E, Batalla, Albert, Bauer, Jochen, Baune, Bernhard T, Baur‐Streubel, Ramona, Biederman, Joseph, Blaine, Sara K, Boedhoe, Premika, Bøen, Erlend, Bose, Anushree, Bralten, Janita, Brandeis, Daniel, Brem, Silvia, Brodaty, Henry, Yüksel, Dilara, Brooks, Samantha J, Buitelaar, Jan, Bürger, Christian, Bülow, Robin, Calhoun, Vince, Calvo, Anna, Canales‐Rodríguez, Erick Jorge, Cannon, Dara M, Caparelli, Elisabeth C, Castellanos, Francisco X, Cendes, Fernando, Chaim‐Avancini, Tiffany Moukbel, Chantiluke, Kaylita, Chen, Qun‐lin, Chen, Xiayu, Cheng, Yuqi, Christakou, Anastasia, Clark, Vincent P, Coghill, David, Connolly, Colm G, Conzelmann, Annette, Córdova‐Palomera, Aldo, Cousijn, Janna, Crow, Tim, Cubillo, Ana, Dannlowski, Udo, de Bruttopilo, Sara Ambrosino, de Zeeuw, Patrick, Deary, Ian J, Demeter, Damion V, Di Martino, Adriana, Dickie, Erin W, Dietsche, Bruno, Doan, Nhat Trung, Doherty, Colin P, Doyle, Alysa, Durston, Sarah, Earl, Eric, Ehrlich, Stefan, Ekman, Carl Johan, Elvsåshagen, Torbjørn, Epstein, Jeffery N, Fair, Damien A, Faraone, Stephen V, Fernández, Guillén, Flint, Claas, Filho, Geraldo Busatto, Förster, Katharina, Fouche, Jean‐Paul, Foxe, John J, Frodl, Thomas, Fuentes‐Claramonte, Paola, Fullerton, Janice M, Garavan, Hugh, do Santos Garcia, Danielle, Gotlib, Ian H, Goudriaan, Anna E, Grabe, Hans Jörgen, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gurholt, Tiril, Haavik, Jan, Hahn, Tim, Hansell, Narelle K, Harris, Mathew A, Hartman, Catharina A, del Carmen Valdés Hernández, Maria, and Heslenfeld, Dirk

Subjects
Biological Psychology, Psychology, Neurosciences, Neurological, Adolescent, Adult, Aged, Brain Cortical Thickness, Cerebral Cortex, Datasets as Topic, Humans, Magnetic Resonance Imaging, Middle Aged, Multicenter Studies as Topic, Neuroimaging, Publication Bias, Reproducibility of Results, Young Adult, ENIGMA Laterality Working Group, P-hacking, multisite collaboration, publication bias, reproducibility, team science, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

The problem of poor reproducibility of scientific findings has received much attention over recent years, in a variety of fields including psychology and neuroscience. The problem has been partly attributed to publication bias and unwanted practices such as p-hacking. Low statistical power in individual studies is also understood to be an important factor. In a recent multisite collaborative study, we mapped brain anatomical left-right asymmetries for regional measures of surface area and cortical thickness, in 99 MRI datasets from around the world, for a total of over 17,000 participants. In the present study, we revisited these hemispheric effects from the perspective of reproducibility. Within each dataset, we considered that an effect had been reproduced when it matched the meta-analytic effect from the 98 other datasets, in terms of effect direction and significance threshold. In this sense, the results within each dataset were viewed as coming from separate studies in an "ideal publishing environment," that is, free from selective reporting and p hacking. We found an average reproducibility rate of 63.2% (SD = 22.9%, min = 22.2%, max = 97.0%). As expected, reproducibility was higher for larger effects and in larger datasets. Reproducibility was not obviously related to the age of participants, scanner field strength, FreeSurfer software version, cortical regional measurement reliability, or regional size. These findings constitute an empirical illustration of reproducibility in the absence of publication bias or p hacking, when assessing realistic biological effects in heterogeneous neuroscience data, and given typically-used sample sizes.

Published
2022

32. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years

Author

Frangou, Sophia, Modabbernia, Amirhossein, Williams, Steven CR, Papachristou, Efstathios, Doucet, Gaelle E, Agartz, Ingrid, Aghajani, Moji, Akudjedu, Theophilus N, Albajes‐Eizagirre, Anton, Alnæs, Dag, Alpert, Kathryn I, Andersson, Micael, Andreasen, Nancy C, Andreassen, Ole A, Asherson, Philip, Banaschewski, Tobias, Bargallo, Nuria, Baumeister, Sarah, Baur‐Streubel, Ramona, Bertolino, Alessandro, Bonvino, Aurora, Boomsma, Dorret I, Borgwardt, Stefan, Bourque, Josiane, Brandeis, Daniel, Breier, Alan, Brodaty, Henry, Brouwer, Rachel M, Buitelaar, Jan K, Busatto, Geraldo F, Buckner, Randy L, Calhoun, Vincent, Canales‐Rodríguez, Erick J, Cannon, Dara M, Caseras, Xavier, Castellanos, Francisco X, Cervenka, Simon, Chaim‐Avancini, Tiffany M, Ching, Christopher RK, Chubar, Victoria, Clark, Vincent P, Conrod, Patricia, Conzelmann, Annette, Crespo‐Facorro, Benedicto, Crivello, Fabrice, Crone, Eveline A, Dale, Anders M, Dannlowski, Udo, Davey, Christopher, Geus, Eco JC, Haan, Lieuwe, Zubicaray, Greig I, Braber, Anouk, Dickie, Erin W, Di Giorgio, Annabella, Doan, Nhat Trung, Dørum, Erlend S, Ehrlich, Stefan, Erk, Susanne, Espeseth, Thomas, Fatouros‐Bergman, Helena, Fisher, Simon E, Fouche, Jean‐Paul, Franke, Barbara, Frodl, Thomas, Fuentes‐Claramonte, Paola, Glahn, David C, Gotlib, Ian H, Grabe, Hans‐Jörgen, Grimm, Oliver, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Gur, Rachel E, Gur, Ruben C, Hahn, Tim, Harrison, Ben J, Hartman, Catharine A, Hatton, Sean N, Heinz, Andreas, Heslenfeld, Dirk J, Hibar, Derrek P, Hickie, Ian B, Ho, Beng‐Choon, Hoekstra, Pieter J, Hohmann, Sarah, Holmes, Avram J, Hoogman, Martine, Hosten, Norbert, Howells, Fleur M, Pol, Hilleke E Hulshoff, Huyser, Chaim, Jahanshad, Neda, James, Anthony, Jernigan, Terry L, Jiang, Jiyang, Jönsson, Erik G, Joska, John A, and Kahn, Rene

Subjects
Behavioral and Social Science, Neurosciences, Aging, Adolescent, Adult, Aged, Aged, 80 and over, Cerebral Cortex, Child, Child, Preschool, Cross-Sectional Studies, Female, Human Development, Humans, Male, Middle Aged, Neuroimaging, Young Adult, aging, cortical thickness, development, trajectories, Karolinska Schizophrenia Project, Cognitive Sciences, Experimental Psychology
Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Published
2022

33. Multivariate alterations in insula - Medial prefrontal cortex linked to genetics in 12q24 in schizophrenia

Author

Jiang, Wenhao, Rootes-Murdy, Kelly, Chen, Jiayu, Bizzozero, Nora I Perrone-, Calhoun, Vince D, van Erp, Theo GM, Ehrlich, Stefan, Agartz, Ingrid, Jönsson, Erik G, Andreassen, Ole A, Wang, Lei, Pearlson, Godfrey D, Glahn, David C, Hong, Elliot, Liu, Jingyu, and Turner, Jessica A

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Acquired Cognitive Impairment, Neurosciences, Genetics, Serious Mental Illness, Schizophrenia, Mental Health, 2.1 Biological and endogenous factors, Aetiology, Mental health, Brain, Cognition, Gray Matter, Humans, Magnetic Resonance Imaging, Prefrontal Cortex, QTL, Insula, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

The direct effect of genetic variations on clinical phenotypes within schizophrenia (SZ) remains elusive. We examined the previously identified association of reduced gray matter concentration in the insula - medial prefrontal cortex and a quantitative trait locus located in 12q24 in a SZ dataset. The main analysis was performed on 1461 SNPs and 830 participants. The highest contributing SNPs were localized in five genes including TMEM119, which encodes a microglial marker, that is associated with neuroinflammation and Alzheimer's disease. The gene set in 12q4 may partially explain brain alterations in SZ, but they may also relate to other psychiatric and developmental disorders.

Published
2021

34. 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

36. 1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans.

Author

Sønderby, Ida E, van der Meer, Dennis, Moreau, Clara, Kaufmann, Tobias, Walters, G Bragi, Ellegaard, Maria, Abdellaoui, Abdel, Ames, David, Amunts, Katrin, Andersson, Micael, Armstrong, Nicola J, Bernard, Manon, Blackburn, Nicholas B, Blangero, John, Boomsma, Dorret I, Brodaty, Henry, Brouwer, Rachel M, Bülow, Robin, Bøen, Rune, Cahn, Wiepke, Calhoun, Vince D, Caspers, Svenja, Ching, Christopher RK, Cichon, Sven, Ciufolini, Simone, Crespo-Facorro, Benedicto, Curran, Joanne E, Dale, Anders M, Dalvie, Shareefa, Dazzan, Paola, de Geus, Eco JC, de Zubicaray, Greig I, de Zwarte, Sonja MC, Desrivieres, Sylvane, Doherty, Joanne L, Donohoe, Gary, Draganski, Bogdan, Ehrlich, Stefan, Eising, Else, Espeseth, Thomas, Fejgin, Kim, Fisher, Simon E, Fladby, Tormod, Frei, Oleksandr, Frouin, Vincent, Fukunaga, Masaki, Gareau, Thomas, Ge, Tian, Glahn, David C, Grabe, Hans J, Groenewold, Nynke A, Gústafsson, Ómar, Haavik, Jan, Haberg, Asta K, Hall, Jeremy, Hashimoto, Ryota, Hehir-Kwa, Jayne Y, Hibar, Derrek P, Hillegers, Manon HJ, Hoffmann, Per, Holleran, Laurena, Holmes, Avram J, Homuth, Georg, Hottenga, Jouke-Jan, Hulshoff Pol, Hilleke E, Ikeda, Masashi, Jahanshad, Neda, Jockwitz, Christiane, Johansson, Stefan, Jönsson, Erik G, Jørgensen, Niklas R, Kikuchi, Masataka, Knowles, Emma EM, Kumar, Kuldeep, Le Hellard, Stephanie, Leu, Costin, Linden, David EJ, Liu, Jingyu, Lundervold, Arvid, Lundervold, Astri Johansen, Maillard, Anne M, Martin, Nicholas G, Martin-Brevet, Sandra, Mather, Karen A, Mathias, Samuel R, McMahon, Katie L, McRae, Allan F, Medland, Sarah E, Meyer-Lindenberg, Andreas, Moberget, Torgeir, Modenato, Claudia, Sánchez, Jennifer Monereo, Morris, Derek W, Mühleisen, Thomas W, Murray, Robin M, Nielsen, Jacob, Nordvik, Jan E, Nyberg, Lars, Loohuis, Loes M Olde, and Ophoff, Roel A

Subjects
ENIGMA-CNV working group, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Published
2021

37. Shared genetic risk between eating disorder‐ and substance‐use‐related phenotypes: Evidence from genome‐wide association studies

Author

Munn‐Chernoff, Melissa A, Johnson, Emma C, Chou, Yi‐Ling, Coleman, Jonathan RI, Thornton, Laura M, Walters, Raymond K, Yilmaz, Zeynep, Baker, Jessica H, Hübel, Christopher, Gordon, Scott, Medland, Sarah E, Watson, Hunna J, Gaspar, Héléna A, Bryois, Julien, Hinney, Anke, Leppä, Virpi M, Mattheisen, Manuel, Ripke, Stephan, Yao, Shuyang, Giusti‐Rodríguez, Paola, Hanscombe, Ken B, Adan, Roger AH, Alfredsson, Lars, Ando, Tetsuya, Andreassen, Ole A, Berrettini, Wade H, Boehm, Ilka, Boni, Claudette, Perica, Vesna Boraska, Buehren, Katharina, Burghardt, Roland, Cassina, Matteo, Cichon, Sven, Clementi, Maurizio, Cone, Roger D, Courtet, Philippe, Crow, Scott, Crowley, James J, Danner, Unna N, Davis, Oliver SP, de Zwaan, Martina, Dedoussis, George, Degortes, Daniela, DeSocio, Janiece E, Dick, Danielle M, Dikeos, Dimitris, Dina, Christian, Dmitrzak‐Weglarz, Monika, Docampo, Elisa, Duncan, Laramie E, Egberts, Karin, Ehrlich, Stefan, Escaramís, Geòrgia, Esko, Tõnu, Estivill, Xavier, Farmer, Anne, Favaro, Angela, Fernández‐Aranda, Fernando, Fichter, Manfred M, Fischer, Krista, Föcker, Manuel, Foretova, Lenka, Forstner, Andreas J, Forzan, Monica, Franklin, Christopher S, Gallinger, Steven, Giegling, Ina, Giuranna, Johanna, Gonidakis, Fragiskos, Gorwood, Philip, Mayora, Monica Gratacos, Guillaume, Sébastien, Guo, Yiran, Hakonarson, Hakon, Hatzikotoulas, Konstantinos, Hauser, Joanna, Hebebrand, Johannes, Helder, Sietske G, Herms, Stefan, Herpertz‐Dahlmann, Beate, Herzog, Wolfgang, Huckins, Laura M, Hudson, James I, Imgart, Hartmut, Inoko, Hidetoshi, Janout, Vladimir, Jiménez‐Murcia, Susana, Julià, Antonio, Kalsi, Gursharan, Kaminská, Deborah, Karhunen, Leila, Karwautz, Andreas, Kas, Martien JH, Kennedy, James L, Keski‐Rahkonen, Anna, Kiezebrink, Kirsty, Kim, Youl‐Ri, Klump, Kelly L, Knudsen, Gun Peggy S, and La Via, Maria C

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Epidemiology, Health Sciences, Psychology, Pharmacology and Pharmaceutical Sciences, Nutrition, Brain Disorders, Alcoholism, Alcohol Use and Health, Mental Health, Eating Disorders, Substance Misuse, Genetics, Tobacco Smoke and Health, Tobacco, Human Genome, Drug Abuse (NIDA only), Prevention, Clinical Research, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Good Health and Well Being, Alcoholism, Depressive Disorder, Major, Feeding and Eating Disorders, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Phenotype, Polymorphism, Single Nucleotide, Risk Factors, Schizophrenia, Substance-Related Disorders, Tobacco Use Disorder, eating disorders, genetic correlation, substance use, Medical and Health Sciences, Psychology and Cognitive Sciences, Substance Abuse, Biomedical and clinical sciences, Health sciences
Abstract

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [rg ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (rg = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (rg = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (rg = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (rgs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors.

Published
2021

38. 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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40. Subcortical Brain Volume, Regional Cortical Thickness, and Cortical Surface Area Across Disorders: Findings From the ENIGMA ADHD, ASD, and OCD Working Groups

Author

Boedhoe, Premika SW, van Rooij, Daan, Hoogman, Martine, Twisk, Jos WR, Schmaal, Lianne, Abe, Yoshinari, Alonso, Pino, Ameis, Stephanie H, Anikin, Anatoly, Anticevic, Alan, Arango, Celso, Arnold, Paul D, Asherson, Philip, Assogna, Francesca, Auzias, Guillaume, Banaschewski, Tobias, Baranov, Alexander, Batistuzzo, Marcelo C, Baumeister, Sarah, Baur-Streubel, Ramona, Behrmann, Marlene, Bellgrove, Mark A, Benedetti, Francesco, Beucke, Jan C, Biederman, Joseph, Bollettini, Irene, Bose, Anushree, Bralten, Janita, Bramati, Ivanei E, Brandeis, Daniel, Brem, Silvia, Brennan, Brian P, Busatto, Geraldo F, Calderoni, Sara, Calvo, Anna, Calvo, Rosa, Castellanos, Francisco X, Cercignani, Mara, Chaim-Avancini, Tiffany M, Chantiluke, Kaylita C, Cheng, Yuqi, Cho, Kang Ik K, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Cubillo, Ana I, Dale, Anders M, Dallaspezia, Sara, Daly, Eileen, Denys, Damiaan, Deruelle, Christine, Di Martino, Adriana, Dinstein, Ilan, Doyle, Alysa E, Durston, Sarah, Earl, Eric A, Ecker, Christine, Ehrlich, Stefan, Ely, Benjamin A, Epstein, Jeffrey N, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas J, Faraone, Stephen V, Fedor, Jennifer, Feng, Xin, Feusner, Jamie D, Fitzgerald, Jackie, Fitzgerald, Kate D, Fouche, Jean-Paul, Freitag, Christine M, Fridgeirsson, Egill A, Frodl, Thomas, Gabel, Matt C, Gallagher, Louise, Gogberashvili, Tinatin, Gori, Ilaria, Gruner, Patricia, Gürsel, Deniz A, Haar, Shlomi, Haavik, Jan, Hall, Geoffrey B, Harrison, Neil A, Hartman, Catharina A, Heslenfeld, Dirk J, Hirano, Yoshiyuki, Hoekstra, Pieter J, Hoexter, Marcelo Q, Hohmann, Sarah, Høvik, Marie F, Hu, Hao, Huyser, Chaim, Jahanshad, Neda, Jalbrzikowski, Maria, James, Anthony, Janssen, Joost, Jaspers-Fayer, Fern, Jernigan, Terry L, Kapilushniy, Dmitry, and Kardatzki, Bernd

Subjects
Attention Deficit Hyperactivity Disorder (ADHD), Behavioral and Social Science, Clinical Research, Mental Health, Neurosciences, Pediatric, Autism, Intellectual and Developmental Disabilities (IDD), Brain Disorders, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Aetiology, Mental health, Neurological, Adolescent, Adult, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Cerebrum, Child, Female, Human Development, Humans, Male, Neuroimaging, Obsessive-Compulsive Disorder, Organ Size, Psychopathology, Research Report, Systems Analysis, ENIGMA ADHD working group, ENIGMA ASD working group, ENIGMA OCD working group, Attention Deficit Hyperactivity Disorder, ENIGMA, Structural MRI, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

ObjectiveAttention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data.MethodsStructural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures).ResultsNo shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood.ConclusionsThe study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.

Published
2020

41. Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA

Author

Radua, Joaquim, Vieta, Eduard, Shinohara, Russell, Kochunov, Peter, Quidé, Yann, Green, Melissa J, Weickert, Cynthia S, Weickert, Thomas, Bruggemann, Jason, Kircher, Tilo, Nenadić, Igor, Cairns, Murray J, Seal, Marc, Schall, Ulrich, Henskens, Frans, Fullerton, Janice M, Mowry, Bryan, Pantelis, Christos, Lenroot, Rhoshel, Cropley, Vanessa, Loughland, Carmel, Scott, Rodney, Wolf, Daniel, Satterthwaite, Theodore D, Tan, Yunlong, Sim, Kang, Piras, Fabrizio, Spalletta, Gianfranco, Banaj, Nerisa, Pomarol-Clotet, Edith, Solanes, Aleix, Albajes-Eizagirre, Anton, Canales-Rodríguez, Erick J, Sarro, Salvador, Di Giorgio, Annabella, Bertolino, Alessandro, Stäblein, Michael, Oertel, Viola, Knöchel, Christian, Borgwardt, Stefan, du Plessis, Stefan, Yun, Je-Yeon, Kwon, Jun Soo, Dannlowski, Udo, Hahn, Tim, Grotegerd, Dominik, Alloza, Clara, Arango, Celso, Janssen, Joost, Díaz-Caneja, Covadonga, Jiang, Wenhao, Calhoun, Vince, Ehrlich, Stefan, Yang, Kun, Cascella, Nicola G, Takayanagi, Yoichiro, Sawa, Akira, Tomyshev, Alexander, Lebedeva, Irina, Kaleda, Vasily, Kirschner, Matthias, Hoschl, Cyril, Tomecek, David, Skoch, Antonin, van Amelsvoort, Therese, Bakker, Geor, James, Anthony, Preda, Adrian, Weideman, Andrea, Stein, Dan J, Howells, Fleur, Uhlmann, Anne, Temmingh, Henk, López-Jaramillo, Carlos, Díaz-Zuluaga, Ana, Fortea, Lydia, Martinez-Heras, Eloy, Solana, Elisabeth, Llufriu, Sara, Jahanshad, Neda, Thompson, Paul, Turner, Jessica, van Erp, Theo, collaborators, ENIGMA Consortium, Glahn, David, Pearlson, Godfrey, Hong, Elliot, Krug, Axel, Carr, Vaughan, Tooney, Paul, Cooper, Gavin, Rasser, Paul, Michie, Patricia, Catts, Stanley, Gur, Raquel, Gur, Ruben, Yang, Fude, Fan, Fengmei, Chen, Jingxu, and Guo, Hua

Subjects
Brain Disorders, Biomedical Imaging, Mental Health, Schizophrenia, Neurosciences, Mental health, Adult, Algorithms, Cerebral Cortex, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Meta-Analysis as Topic, Middle Aged, Neuroimaging, Young Adult, Brain, Cortical thickness, Gray matter, Mega-analysis, Volume, ENIGMA Consortium collaborators, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).

Published
2020

42. The genetic architecture of the human cerebral cortex

Author

Grasby, Katrina L, Jahanshad, Neda, Painter, Jodie N, Colodro-Conde, Lucía, Bralten, Janita, Hibar, Derrek P, Lind, Penelope A, Pizzagalli, Fabrizio, Ching, Christopher RK, McMahon, Mary Agnes B, Shatokhina, Natalia, Zsembik, Leo CP, Thomopoulos, Sophia I, Zhu, Alyssa H, Strike, Lachlan T, Agartz, Ingrid, Alhusaini, Saud, Almeida, Marcio AA, Alnæs, Dag, Amlien, Inge K, Andersson, Micael, Ard, Tyler, Armstrong, Nicola J, Ashley-Koch, Allison, Atkins, Joshua R, Bernard, Manon, Brouwer, Rachel M, Buimer, Elizabeth EL, Bülow, Robin, Bürger, Christian, Cannon, Dara M, Chakravarty, Mallar, Chen, Qiang, Cheung, Joshua W, Couvy-Duchesne, Baptiste, Dale, Anders M, Dalvie, Shareefa, de Araujo, Tânia K, de Zubicaray, Greig I, de Zwarte, Sonja MC, Braber, Anouk den, Doan, Nhat Trung, Dohm, Katharina, Ehrlich, Stefan, Engelbrecht, Hannah-Ruth, Erk, Susanne, Fan, Chun Chieh, Fedko, Iryna O, Foley, Sonya F, Ford, Judith M, Fukunaga, Masaki, Garrett, Melanie E, Ge, Tian, Giddaluru, Sudheer, Goldman, Aaron L, Green, Melissa J, Groenewold, Nynke A, Grotegerd, Dominik, Gurholt, Tiril P, Gutman, Boris A, Hansell, Narelle K, Harris, Mathew A, Harrison, Marc B, Haswell, Courtney C, Hauser, Michael, Herms, Stefan, Heslenfeld, Dirk J, Ho, New Fei, Hoehn, David, Hoffmann, Per, Holleran, Laurena, Hoogman, Martine, Hottenga, Jouke-Jan, Ikeda, Masashi, Janowitz, Deborah, Jansen, Iris E, Jia, Tianye, Jockwitz, Christiane, Kanai, Ryota, Karama, Sherif, Kasperaviciute, Dalia, Kaufmann, Tobias, Kelly, Sinead, Kikuchi, Masataka, Klein, Marieke, Knapp, Michael, Knodt, Annchen R, Krämer, Bernd, Lam, Max, Lancaster, Thomas M, Lee, Phil H, Lett, Tristram A, Lewis, Lindsay B, Lopes-Cendes, Iscia, Luciano, Michelle, Macciardi, Fabio, Marquand, Andre F, Mathias, Samuel R, Melzer, Tracy R, and Milaneschi, Yuri

Subjects
Biological Sciences, Genetics, Neurosciences, Mental Health, Brain Disorders, Stem Cell Research, 2.1 Biological and endogenous factors, Aetiology, Neurological, Attention Deficit Disorder with Hyperactivity, Brain Mapping, Cerebral Cortex, Cognition, Genetic Loci, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Organ Size, Parkinson Disease, Alzheimer’s Disease Neuroimaging Initiative, CHARGE Consortium, EPIGEN Consortium, IMAGEN Consortium, SYS Consortium, Parkinson’s Progression Markers Initiative, Enhancing NeuroImaging Genetics through Meta-Analysis Consortium (ENIGMA)—Genetics working group, General Science & Technology
Abstract

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

Published
2020

43. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries.

Author

Thompson, Paul M, Jahanshad, Neda, Ching, Christopher RK, Salminen, Lauren E, Thomopoulos, Sophia I, Bright, Joanna, Baune, Bernhard T, Bertolín, Sara, Bralten, Janita, Bruin, Willem B, Bülow, Robin, Chen, Jian, Chye, Yann, Dannlowski, Udo, de Kovel, Carolien GF, Donohoe, Gary, Eyler, Lisa T, Faraone, Stephen V, Favre, Pauline, Filippi, Courtney A, Frodl, Thomas, Garijo, Daniel, Gil, Yolanda, Grabe, Hans J, Grasby, Katrina L, Hajek, Tomas, Han, Laura KM, Hatton, Sean N, Hilbert, Kevin, Ho, Tiffany C, Holleran, Laurena, Homuth, Georg, Hosten, Norbert, Houenou, Josselin, Ivanov, Iliyan, Jia, Tianye, Kelly, Sinead, Klein, Marieke, Kwon, Jun Soo, Laansma, Max A, Leerssen, Jeanne, Lueken, Ulrike, Nunes, Abraham, Neill, Joseph O', Opel, Nils, Piras, Fabrizio, Piras, Federica, Postema, Merel C, Pozzi, Elena, Shatokhina, Natalia, Soriano-Mas, Carles, Spalletta, Gianfranco, Sun, Daqiang, Teumer, Alexander, Tilot, Amanda K, Tozzi, Leonardo, van der Merwe, Celia, Van Someren, Eus JW, van Wingen, Guido A, Völzke, Henry, Walton, Esther, Wang, Lei, Winkler, Anderson M, Wittfeld, Katharina, Wright, Margaret J, Yun, Je-Yeon, Zhang, Guohao, Zhang-James, Yanli, Adhikari, Bhim M, Agartz, Ingrid, Aghajani, Moji, Aleman, André, Althoff, Robert R, Altmann, Andre, Andreassen, Ole A, Baron, David A, Bartnik-Olson, Brenda L, Marie Bas-Hoogendam, Janna, Baskin-Sommers, Arielle R, Bearden, Carrie E, Berner, Laura A, Boedhoe, Premika SW, Brouwer, Rachel M, Buitelaar, Jan K, Caeyenberghs, Karen, Cecil, Charlotte AM, Cohen, Ronald A, Cole, James H, Conrod, Patricia J, De Brito, Stephane A, de Zwarte, Sonja MC, Dennis, Emily L, Desrivieres, Sylvane, Dima, Danai, Ehrlich, Stefan, Esopenko, Carrie, Fairchild, Graeme, Fisher, Simon E, Fouche, Jean-Paul, and Francks, Clyde

Subjects
ENIGMA Consortium, Brain, Humans, Magnetic Resonance Imaging, Reproducibility of Results, Depressive Disorder, Major, Neuroimaging, Neurosciences, Clinical Research, Mental Health, Brain Disorders, Behavioral and Social Science, Genetics, Basic Behavioral and Social Science, Prevention, 2.1 Biological and endogenous factors, 2.3 Psychological, social and economic factors, Mental health, Neurological, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Published
2020

44. 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 JC, de Zubicaray, Greig I, de Zwarte, Sonja MC, 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 HJ, 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 EM, 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, and Prieto, Carlos

Subjects
Intellectual and Developmental Disabilities (IDD), Neurosciences, Brain Disorders, Autism, Biomedical Imaging, Mental Health, Mental health, Adult, Autism Spectrum Disorder, Autistic Disorder, Basal Ganglia, Brain, Chromosome Deletion, Chromosome Disorders, Chromosome Duplication, Chromosomes, Human, Pair 16, DNA Copy Number Variations, Databases, Factual, Female, Globus Pallidus, Humans, Image Processing, Computer-Assisted, Intellectual Disability, Magnetic Resonance Imaging, Male, Middle Aged, Neurodevelopmental Disorders, Organ Size, Putamen, Schizophrenia, 16p11.2 European Consortium, for the ENIGMA-CNV working group, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Carriers of large recurrent copy number variants (CNVs) have a higher risk of developing neurodevelopmental disorders. The 16p11.2 distal CNV predisposes carriers to e.g., autism spectrum disorder and schizophrenia. We compared subcortical brain volumes of 12 16p11.2 distal deletion and 12 duplication carriers to 6882 non-carriers from the large-scale brain Magnetic Resonance Imaging collaboration, ENIGMA-CNV. After stringent CNV calling procedures, and standardized FreeSurfer image analysis, we found negative dose-response associations with copy number on intracranial volume and on regional caudate, pallidum and putamen volumes (β = -0.71 to -1.37; P

Published
2020

45. 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 JC, de Zubicaray, Greig I, de Zwarte, Sonja MC, 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 HJ, 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 EM, 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, and Prieto, Carlos

Subjects
16p11.2 European Consortium, for the ENIGMA-CNV working group, Neurosciences, Psychiatry, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences
Abstract

Prior to and following the publication of this article the authors noted that the complete list of authors was not included in the main article and was only present in Supplementary Table 1. The author list in the original article has now been updated to include all authors, and Supplementary Table 1 has been removed. All other supplementary files have now been updated accordingly. Furthermore, in Table 1 of this Article, the replication cohort for the row Close relative in data set, n (%) was incorrect. All values have now been corrected to 0(0%). The publishers would like to apologise for this error and the inconvenience it may have caused.

Published
2020

46. Acute tryptophan depletion balances altered resting-state functional connectivity of the salience network in female patients recovered from anorexia nervosa

Author

Boehm, Ilka, Hennig, Julius, Ritschel, Franziska, Geisler, Daniel, King, Joseph A., Lesch, Isabel, Roessner, Veit, Zepf, Florian Daniel, and Ehrlich, Stefan

Subjects
Neural circuitry -- Research -- Health aspects -- Physiological aspects, Women patients -- Psychological aspects, Anorexia nervosa -- Complications and side effects, Tryptophan -- Health aspects -- Physiological aspects, Health, Psychology and mental health
Abstract

Background: It has been suggested that individuals predisposed to or recovered from anorexia nervosa experience a hyperserotonergic state associated with anxiety that might be mitigated by restricted food intake, because diminished levels of the tryptophan precursor lower the central availability of serotonin (5-HT). At the neural level, the salience network is a system of functionally connected brain regions; it has been closely associated with 5-HT functioning and mental disorders (including anorexia nervosa). The aim of the present study was to investigate the effect on the salience network of a temporary dietary manipulation of 5-HT synthesis in patients with anorexia nervosa. Methods: In this double-blind crossover study, we obtained data on resting-state functional connectivity from 22 weight-recovered female patients with a history of anorexia nervosa, and 22 age-matched female healthy controls. The study procedure included acute tryptophan depletion (a dietary intervention that lowers the central 5-HT synthesis rate) and a sham condition. Results: We identified an interaction of group and experimental condition in resting-state functional connectivity between the salience network and the orbitofrontal cortex extending to the frontal pole ([F.sub.1,42] = 12.52; [p.sub.FWE] = 0.026). Further analysis revealed increased resting-state functional connectivity during acute tryptophan depletion in patients recovered from anorexia nervosa, resembling that of healthy controls during the sham condition ([T.sub.42] = -0.66; p = 0.51). Limitations: The effect of acute tryptophan depletion on the central availability of 5-HT can be judged only indirectly using plasma ratios of tryptophan to large neutral amino acids. Moreover, the definition of anorexia nervosa recovery varies widely across studies, limiting comparability. Conclusion: Taken together, our findings support the notion of 5-HT dysregulation in anorexia nervosa and indicate that reduced 5-HT synthesis and availability during acute tryptophan depletion (and possibly with food restriction) may balance hyperserotonergic functioning and the associated resting-state functional connectivity of the salience network., Introduction Mood regulation, anxiety and the modulation of appetite are functionally associated with the brain serotonin (5-HT) system, (1-3) which is hypothesized to play an important role in the etiology [...]

Published
2022
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49. Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Author

Petrov, Dmitry, Kuznetsov, Boris A. Gutman Egor, van Erp, Theo G. M., Turner, Jessica A., Schmaal, Lianne, Veltman, Dick, Wang, Lei, Alpert, Kathryn, Isaev, Dmitry, Zavaliangos-Petropulu, Artemis, Ching, Christopher R. K., Calhoun, Vince, Glahn, David, Satterthwaite, Theodore D., Andreassen, Ole Andreas, Borgwardt, Stefan, Howells, Fleur, Groenewold, Nynke, Voineskos, Aristotle, Radua, Joaquim, Potkin, Steven G., Crespo-Facorro, Benedicto, Tordesillas-Gutierrez, Diana, Shen, Li, Lebedeva, Irina, Spalletta, Gianfranco, Donohoe, Gary, Kochunov, Peter, Rosa, Pedro G. P., James, Anthony, Dannlowski, Udo, Baune, Bernhard T., Aleman, Andre, Gotlib, Ian H., Walter, Henrik, Walter, Martin, Soares, Jair C., Ehrlich, Stefan, Gur, Ruben C., Doan, N. Trung, Agartz, Ingrid, Westlye, Lars T., Harrisberger, Fabienne, Riecher-Rossler, Anita, Uhlmann, Anne, Stein, Dan J., Dickie, Erin W., Pomarol-Clotet, Edith, Fuentes-Claramonte, Paola, Canales-Rodriguez, Erick Jorge, Salvador, Raymond, Huang, Alexander J., Roiz-Santianez, Roberto, Cong, Shan, Tomyshev, Alexander, Piras, Fabrizio, Vecchio, Daniela, Banaj, Nerisa, Ciullo, Valentina, Hong, Elliot, Busatto, Geraldo, Zanetti, Marcus V., Serpa, Mauricio H., Cervenka, Simon, Kelly, Sinead, Grotegerd, Dominik, Sacchet, Matthew D., Veer, Ilya M., Li, Meng, Wu, Mon-Ju, Irungu, Benson, Walton, Esther, and Thompson, Paul M.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional neural net architectures (VGGNet, ResNet and Inception) over 2D maps of geometric features. Further, we present a novel geometry feature augmentation technique based on a parametric spherical mapping. Finally, we present an approach for model decision visualization, allowing human raters to see the areas of subcortical shapes most likely to be deemed of failing quality by the machine. Our training data is comprised of 5200 subjects from the ENIGMA Schizophrenia MRI cohorts, and our test dataset contains 1500 subjects from the ENIGMA Major Depressive Disorder cohorts. Our final models reduce human rater time by 46-70%. ResNet outperforms VGGNet and Inception for all of our predictive tasks., Comment: Accepted to Shape in Medical Imaging (ShapeMI) workshop at MICCAI 2018. arXiv admin note: substantial text overlap with arXiv:1707.06353

Published
2018

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