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1. 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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2. Wearable data from subjects playing Super Mario, sitting university exams, or performing physical exercise help detect acute mood episodes via self-supervised learning

Author

Corponi, Filippo, Li, Bryan M., Anmella, Gerard, Valenzuela-Pascual, Clàudia, Mas, Ariadna, Pacchiarotti, Isabella, Valentí, Marc, Grande, Iria, Benabarre, Antonio, Garriga, Marina, Vieta, Eduard, Young, Allan H, Lawrie, Stephen M., Whalley, Heather C., Hidalgo-Mazzei, Diego, and Vergari, Antonio

Subjects
Computer Science - Machine Learning, Computer Science - Artificial Intelligence, Electrical Engineering and Systems Science - Signal Processing
Abstract

Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of worldwide disease burden. However, collecting and annotating wearable data is very resource-intensive. Studies of this kind can thus typically afford to recruit only a couple dozens of patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MDs detection. In this paper, we overcome this data bottleneck and advance the detection of MDs acute episode vs stable state from wearables data on the back of recent advances in self-supervised learning (SSL). This leverages unlabelled data to learn representations during pre-training, subsequently exploited for a supervised task. First, we collected open-access datasets recording with an Empatica E4 spanning different, unrelated to MD monitoring, personal sensing tasks -- from emotion recognition in Super Mario players to stress detection in undergraduates -- and devised a pre-processing pipeline performing on-/off-body detection, sleep-wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduce E4SelfLearning, the largest to date open access collection, and its pre-processing pipeline. Second, we show that SSL confidently outperforms fully-supervised pipelines using either our novel E4-tailored Transformer architecture (E4mer) or classical baseline XGBoost: 81.23% against 75.35% (E4mer) and 72.02% (XGBoost) correctly classified recording segments from 64 (half acute, half stable) patients. Lastly, we illustrate that SSL performance is strongly associated with the specific surrogate task employed for pre-training as well as with unlabelled data availability.

Published
2023
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3. Multivariable prediction of functional outcome after first-episode psychosis: a crossover validation approach in EUFEST and PSYSCAN

Author

Slot, Margot I. E., Urquijo Castro, Maria F., Winter - van Rossum, Inge, van Hell, Hendrika H., Dwyer, Dominic, Dazzan, Paola, Maat, Arija, De Haan, Lieuwe, Crespo-Facorro, Benedicto, Glenthøj, Birte Y., Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Weiser, Mark, Sachs, Gabriele, Kirschner, Matthias, Fleischhacker, W. Wolfgang, McGuire, Philip, Koutsouleris, Nikolaos, and Kahn, René S.

Published
2024
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6. Using brain structural neuroimaging measures to predict psychosis onset for individuals at clinical high-risk

Author

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

Published
2024
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7. 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

8. PsyCog: A computerised mini battery for assessing cognition in psychosis

Author

Gifford, George, Cullen, Alexis E., Vieira, Sandra, Searle, Anja, McCutcheon, Robert A., Modinos, Gemma, Stone, William S., Hird, Emily, Barnett, Jennifer, van Hell, Hendrika H., Catalan, Ana, Millgate, Edward, Taptiklis, Nick, Cormack, Francesca, Slot, Margot E., Dazzan, Paola, Maat, Arija, de Haan, Lieuwe, Facorro, Benedicto Crespo, Glenthøj, Birte, Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Bressan, Rodrigo A., Kwon, Jun Soo, Weiser, Mark, Mizrahi, Romina, Sachs, Gabriele, Kirschner, Matthias, Reichenberg, Abraham, Kahn, René, and McGuire, Philip

Published
2024
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9. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses

Author

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

Published
2023
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10. Network analysis of inflammation and symptoms in recent onset schizophrenia and the influence of minocycline during a clinical trial

Author

Herniman, Sarah E., Wood, Stephen J., Khandaker, Golam, Dazzan, Paola, Pariante, Carmine M., Barnes, Nicholas M., Krynicki, Carl R., Nikkheslat, Naghmeh, Vincent, Rachel C., Roberts, Alex, Giordano, Annalisa, Watson, Andrew, Suckling, John, Barnes, Thomas R. E., Husain, Nusrat, Jones, Peter B., Joyce, Eileen, Lawrie, Stephen M., Lewis, Shôn, Deakin, Bill, and Upthegrove, Rachel

Published
2023
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12. A leaky umbrella has little value: evidence clearly indicates the serotonin system is implicated in depression

Author

Jauhar, Sameer, Arnone, Danilo, Baldwin, David S., Bloomfield, Michael, Browning, Michael, Cleare, Anthony J., Corlett, Phillip, Deakin, J. F. William, Erritzoe, David, Fu, Cynthia, Fusar-Poli, Paolo, Goodwin, Guy M., Hayes, Joseph, Howard, Robert, Howes, Oliver D., Juruena, Mario F., Lam, Raymond W., Lawrie, Stephen M., McAllister-Williams, Hamish, Marwaha, Steven, Matuskey, David, McCutcheon, Robert A., Nutt, David J., Pariante, Carmine, Pillinger, Toby, Radhakrishnan, Rajiv, Rucker, James, Selvaraj, Sudhakar, Stokes, Paul, Upthegrove, Rachel, Yalin, Nefize, Yatham, Lakshmi, Young, Allan H., Zahn, Roland, and Cowen, Philip J.

Published
2023
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14. A naturalistic cohort study of first-episode schizophrenia spectrum disorder: A description of the early phase of illness in the PSYSCAN cohort

Author

Slot, Margot I.E., van Hell, Hendrika H., Rossum, Inge Winter-van, Dazzan, Paola, Maat, Arija, de Haan, Lieuwe, Crespo-Facorro, Benedicto, Glenthøj, Birte, Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Weiser, Mark, Sachs, Gabriele, Maatz, Anke, Bressan, Rodrigo A., Kwon, Jun Soo, Mizrahi, Romina, McGuire, Philip, and Kahn, René S.

Published
2024
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15. Intelligence, educational attainment, and brain structure in those at familial high‐risk for schizophrenia or bipolar disorder

Author

Zwarte, Sonja MC, Brouwer, Rachel M, Agartz, Ingrid, Alda, Martin, Alonso‐Lana, Silvia, Bearden, Carrie E, Bertolino, Alessandro, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth EL, Cahn, Wiepke, Canales‐Rodríguez, Erick J, Cannon, Dara M, Cannon, Tyrone D, Caseras, Xavier, Castro‐Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Bonnin, Caterina Mar, Demro, Caroline, Di Giorgio, Annabella, Doucet, Gaelle E, Eker, Mehmet Cagdas, Erk, Susanne, Fatjó‐Vilas, Mar, Fears, Scott C, Foley, Sonya F, Frangou, Sophia, Fullerton, Janice M, Glahn, David C, Goghari, Vina M, Goikolea, Jose M, Goldman, Aaron L, Gonul, Ali Saffet, Gruber, Oliver, Hajek, Tomas, Hawkins, Emma L, Heinz, Andreas, Ongun, Ceren Hidiroglu, Hillegers, Manon HJ, Houenou, Josselin, Pol, Hilleke E Hulshoff, Hultman, Christina M, Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G, Kane, Fergus, Kempton, Matthew J, Koenis, Marinka MG, Kopecek, Miloslav, Krämer, Bernd, Lawrie, Stephen M, Lenroot, Rhoshel K, Marcelis, Machteld, Mattay, Venkata S, McDonald, Colm, Meyer‐Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B, Moreno, Dolores, Murray, Robin M, Mwangi, Benson, Nabulsi, Leila, Newport, Jason, Olman, Cheryl A, Os, Jim, Overs, Bronwyn J, Ozerdem, Aysegul, Pergola, Giulio, Picchioni, Marco M, Piguet, Camille, Pomarol‐Clotet, Edith, Radua, Joaquim, Ramsay, Ian S, Richter, Anja, Roberts, Gloria, Salvador, Raymond, Aydogan, Aybala Saricicek, Sarró, Salvador, Schofield, Peter R, Simsek, Esma M, Simsek, Fatma, Soares, Jair C, Sponheim, Scott R, Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Vieta, Eduard, Walter, Henrik, Weinberger, Daniel R, Whalley, Heather C, Wu, Mon‐Ju, Yalin, Nefize, Andreassen, Ole A, Ching, Christopher RK, Thomopoulos, Sophia I, Erp, Theo GM, Jahanshad, Neda, and Thompson, Paul M

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Bipolar Disorder, Clinical Research, Serious Mental Illness, Neurosciences, Schizophrenia, Mental Health, Aetiology, 2.3 Psychological, social and economic factors, 2.1 Biological and endogenous factors, Mental health, Cognitive Dysfunction, Educational Status, Family, Genetic Predisposition to Disease, Humans, Intelligence, Magnetic Resonance Imaging, Neuroimaging, bipolar disorder, education, intelligence, neuroimaging, relatives, schizophrenia, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

First-degree relatives of patients diagnosed with schizophrenia (SZ-FDRs) show similar patterns of brain abnormalities and cognitive alterations to patients, albeit with smaller effect sizes. First-degree relatives of patients diagnosed with bipolar disorder (BD-FDRs) show divergent patterns; on average, intracranial volume is larger compared to controls, and findings on cognitive alterations in BD-FDRs are inconsistent. Here, we performed a meta-analysis of global and regional brain measures (cortical and subcortical), current IQ, and educational attainment in 5,795 individuals (1,103 SZ-FDRs, 867 BD-FDRs, 2,190 controls, 942 schizophrenia patients, 693 bipolar patients) from 36 schizophrenia and/or bipolar disorder family cohorts, with standardized methods. Compared to controls, SZ-FDRs showed a pattern of widespread thinner cortex, while BD-FDRs had widespread larger cortical surface area. IQ was lower in SZ-FDRs (d = -0.42, p = 3 × 10-5 ), with weak evidence of IQ reductions among BD-FDRs (d = -0.23, p = .045). Both relative groups had similar educational attainment compared to controls. When adjusting for IQ or educational attainment, the group-effects on brain measures changed, albeit modestly. Changes were in the expected direction, with less pronounced brain abnormalities in SZ-FDRs and more pronounced effects in BD-FDRs. To conclude, SZ-FDRs and BD-FDRs show a differential pattern of structural brain abnormalities. In contrast, both had lower IQ scores and similar school achievements compared to controls. Given that brain differences between SZ-FDRs and BD-FDRs remain after adjusting for IQ or educational attainment, we suggest that differential brain developmental processes underlying predisposition for schizophrenia or bipolar disorder are likely independent of general cognitive impairment.

Published
2022

16. Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Author

Baldwin, Helen, Radua, Joaquim, Antoniades, Mathilde, Haas, Shalaila S, Frangou, Sophia, Agartz, Ingrid, Allen, Paul, Andreassen, Ole A, Atkinson, Kimberley, Bachman, Peter, Baeza, Inmaculada, Bartholomeusz, Cali F, Chee, Michael WL, Colibazzi, Tiziano, Cooper, Rebecca E, Corcoran, Cheryl M, Cropley, Vanessa L, Ebdrup, Bjørn H, Fortea, Adriana, Glenthøj, Louise Birkedal, Hamilton, Holly K, Haut, Kristen M, Hayes, Rebecca A, He, Ying, Heekeren, Karsten, Kaess, Michael, Kasai, Kiyoto, Katagiri, Naoyuki, Kim, Minah, Kindler, Jochen, Klaunig, Mallory J, Koike, Shinsuke, Koppel, Alex, Kristensen, Tina D, Bin Kwak, Yoo, Kwon, Jun Soo, Lawrie, Stephen M, Lebedeva, Irina, Lee, Jimmy, Lin, Ashleigh, Loewy, Rachel L, Mathalon, Daniel H, Michel, Chantal, Mizrahi, Romina, Møller, Paul, Nelson, Barnaby, Nemoto, Takahiro, Nordholm, Dorte, Omelchenko, Maria A, Pantelis, Christos, Raghava, Jayachandra M, Røssberg, Jan I, Rössler, Wulf, Salisbury, Dean F, Sasabayashi, Daiki, Schall, Ulrich, Smigielski, Lukasz, Sugranyes, Gisela, Suzuki, Michio, Takahashi, Tsutomu, Tamnes, Christian K, Tang, Jinsong, Theodoridou, Anastasia, Thomopoulos, Sophia I, Tomyshev, Alexander S, Uhlhaas, Peter J, Værnes, Tor G, van Amelsvoort, Therese AMJ, Van Erp, Theo GM, Waltz, James A, Westlye, Lars T, Wood, Stephen J, Zhou, Juan H, McGuire, Philip, Thompson, Paul M, Jalbrzikowski, Maria, Hernaus, Dennis, and Fusar-Poli, Paolo

Subjects
Serious Mental Illness, Prevention, Biomedical Imaging, Mental Health, Clinical Research, Neurosciences, Brain, Humans, Magnetic Resonance Imaging, Psychotic Disorders, ENIGMA Clinical High Risk for Psychosis Working Group, Clinical Sciences, Public Health and Health Services, Psychology
Abstract

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the 'normativeness' of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irrespective of psychosis conversion. Further large-scale investigations are required of those who demonstrate marked deviation.

Published
2022

18. Inflammatory subgroups of schizophrenia and their association with brain structure: A semi-supervised machine learning examination of heterogeneity

Author

Alexandros Lalousis, Paris, Schmaal, Lianne, Wood, Stephen J., L.E.P Reniers, Renate, Cropley, Vanessa L., Watson, Andrew, Pantelis, Christos, Suckling, John, Barnes, Nicholas M., Pariante, Carmine, Jones, Peter B., Joyce, Eileen, Barnes, Thomas R.E., Lawrie, Stephen M., Husain, Nusrat, Dazzan, Paola, Deakin, Bill, Shannon Weickert, Cynthia, and Upthegrove, Rachel

Published
2023
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22. The Relationship Between White Matter Microstructure and General Cognitive Ability in Patients With Schizophrenia and Healthy Participants in the ENIGMA Consortium

Author

Holleran, Laurena, Kelly, Sinead, Alloza, Clara, Agartz, Ingrid, Andreassen, Ole A, Arango, Celso, Banaj, Nerisa, Calhoun, Vince, Cannon, Dara, Carr, Vaughan, Corvin, Aiden, Glahn, David C, Gur, Ruben, Hong, Elliot, Hoschl, Cyril, Howells, Fleur M, James, Anthony, Janssen, Joost, Kochunov, Peter, Lawrie, Stephen M, Liu, Jingyu, Martinez, Covadonga, McDonald, Colm, Morris, Derek, Mothersill, David, Pantelis, Christos, Piras, Fabrizio, Potkin, Steven, Rasser, Paul E, Roalf, David, Rowland, Laura, Satterthwaite, Theodore, Schall, Ulrich, Spalletta, Gianfranco, Spaniel, Filip, Stein, Dan J, Uhlmann, Anne, Voineskos, Aristotle, Zalesky, Andrew, van Erp, Theo GM, Turner, Jessica A, Deary, Ian J, Thompson, Paul M, Jahanshad, Neda, and Donohoe, Gary

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Prevention, Neurosciences, Behavioral and Social Science, Clinical Research, Brain Disorders, Serious Mental Illness, Schizophrenia, Mental Health, Mental health, Adult, Anisotropy, Brain, Case-Control Studies, Cognition, Diffusion Tensor Imaging, Factor Analysis, Statistical, Female, Healthy Volunteers, Humans, Intelligence, Male, Middle Aged, Neural Pathways, Principal Component Analysis, Schizophrenic Psychology, Wechsler Scales, White Matter, ENIGMA, Meta-Analysis, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Clinical and health psychology
Abstract

ObjectiveSchizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants.MethodsThe meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition.ResultsMeta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges' g]=0.27, CI=0.17-0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05-0.35) and healthy participant groups (effect size=0.32, CI=0.18-0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18-0.37), the patient group (effect size=0.23, CI=0.09-0.38), and the healthy participant group (effect size=0.31, CI=0.18-0.44).ConclusionsThis study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association.

Published
2020

23. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Author

Favre, Pauline, Pauling, Melissa, Stout, Jacques, Hozer, Franz, Sarrazin, Samuel, Abé, Christoph, Alda, Martin, Alloza, Clara, Alonso-Lana, Silvia, Andreassen, Ole A, Baune, Bernhard T, Benedetti, Francesco, Busatto, Geraldo F, Canales-Rodríguez, Erick J, Caseras, Xavier, Chaim-Avancini, Tiffany Moukbel, Ching, Christopher RK, Dannlowski, Udo, Deppe, Michael, Eyler, Lisa T, Fatjo-Vilas, Mar, Foley, Sonya F, Grotegerd, Dominik, Hajek, Tomas, Haukvik, Unn K, Howells, Fleur M, Jahanshad, Neda, Kugel, Harald, Lagerberg, Trine V, Lawrie, Stephen M, Linke, Julia O, McIntosh, Andrew, Melloni, Elisa MT, Mitchell, Philip B, Polosan, Mircea, Pomarol-Clotet, Edith, Repple, Jonathan, Roberts, Gloria, Roos, Annerine, Rosa, Pedro GP, Salvador, Raymond, Sarró, Salvador, Schofield, Peter R, Serpa, Mauricio H, Sim, Kang, Stein, Dan J, Sussmann, Jess E, Temmingh, Henk S, Thompson, Paul M, Verdolini, Norma, Vieta, Eduard, Wessa, Michele, Whalley, Heather C, Zanetti, Marcus V, Leboyer, Marion, Mangin, Jean-François, Henry, Chantal, Duchesnay, Edouard, and Houenou, Josselin

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Serious Mental Illness, Neurosciences, Bipolar Disorder, Biomedical Imaging, Mental Health, Clinical Research, Mental health, Adult, Brain, Corpus Callosum, Diffusion Tensor Imaging, Female, Humans, Male, Neural Pathways, White Matter, ENIGMA Bipolar Disorder Working Group, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological psychology
Abstract

Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr

Published
2019

24. Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Author

Favre, Pauline, Pauling, Melissa, Stout, Jacques, Hozer, Franz, Sarrazin, Samuel, Abé, Christoph, Alda, Martin, Alloza, Clara, Alonso-Lana, Silvia, Andreassen, Ole A, Baune, Bernhard T, Benedetti, Francesco, Busatto, Geraldo F, Canales-Rodríguez, Erick J, Caseras, Xavier, Chaim-Avancini, Tiffany Moukbel, Ching, Christopher RK, Dannlowski, Udo, Deppe, Michael, Eyler, Lisa T, Fatjo-Vilas, Mar, Foley, Sonya F, Grotegerd, Dominik, Hajek, Tomas, Haukvik, Unn K, Howells, Fleur M, Jahanshad, Neda, Kugel, Harald, Lagerberg, Trine V, Lawrie, Stephen M, Linke, Julia O, McIntosh, Andrew, Melloni, Elisa MT, Mitchell, Philip B, Polosan, Mircea, Pomarol-Clotet, Edith, Repple, Jonathan, Roberts, Gloria, Roos, Annerine, Rosa, Pedro GP, Salvador, Raymond, Sarró, Salvador, Schofield, Peter R, Serpa, Mauricio H, Sim, Kang, Stein, Dan J, Sussmann, Jess E, Temmingh, Henk S, Thompson, Paul M, Verdolini, Norma, Vieta, Eduard, Wessa, Michele, Whalley, Heather C, Zanetti, Marcus V, Leboyer, Marion, Mangin, Jean-François, Henry, Chantal, Duchesnay, Edouard, and Houenou, Josselin

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Neurosciences, Psychology, ENIGMA Bipolar Disorder Working Group, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological psychology
Abstract

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Published
2019

25. Genetic architecture of subcortical brain structures in 38,851 individuals

Author

Satizabal, Claudia L, Adams, Hieab HH, Hibar, Derrek P, White, Charles C, Knol, Maria J, Stein, Jason L, Scholz, Markus, Sargurupremraj, Muralidharan, Jahanshad, Neda, Roshchupkin, Gennady V, Smith, Albert V, Bis, Joshua C, Jian, Xueqiu, Luciano, Michelle, Hofer, Edith, Teumer, Alexander, van der Lee, Sven J, Yang, Jingyun, Yanek, Lisa R, Lee, Tom V, Li, Shuo, Hu, Yanhui, Koh, Jia Yu, Eicher, John D, Desrivières, Sylvane, Arias-Vasquez, Alejandro, Chauhan, Ganesh, Athanasiu, Lavinia, Rentería, Miguel E, Kim, Sungeun, Hoehn, David, Armstrong, Nicola J, Chen, Qiang, Holmes, Avram J, den Braber, Anouk, Kloszewska, Iwona, Andersson, Micael, Espeseth, Thomas, Grimm, Oliver, Abramovic, Lucija, Alhusaini, Saud, Milaneschi, Yuri, Papmeyer, Martina, Axelsson, Tomas, Ehrlich, Stefan, Roiz-Santiañez, Roberto, Kraemer, Bernd, Håberg, Asta K, Jones, Hannah J, Pike, G Bruce, Stein, Dan J, Stevens, Allison, Bralten, Janita, Vernooij, Meike W, Harris, Tamara B, Filippi, Irina, Witte, A Veronica, Guadalupe, Tulio, Wittfeld, Katharina, Mosley, Thomas H, Becker, James T, Doan, Nhat Trung, Hagenaars, Saskia P, Saba, Yasaman, Cuellar-Partida, Gabriel, Amin, Najaf, Hilal, Saima, Nho, Kwangsik, Mirza-Schreiber, Nazanin, Arfanakis, Konstantinos, Becker, Diane M, Ames, David, Goldman, Aaron L, Lee, Phil H, Boomsma, Dorret I, Lovestone, Simon, Giddaluru, Sudheer, Le Hellard, Stephanie, Mattheisen, Manuel, Bohlken, Marc M, Kasperaviciute, Dalia, Schmaal, Lianne, Lawrie, Stephen M, Agartz, Ingrid, Walton, Esther, Tordesillas-Gutierrez, Diana, Davies, Gareth E, Shin, Jean, Ipser, Jonathan C, Vinke, Louis N, Hoogman, Martine, Jia, Tianye, Burkhardt, Ralph, Klein, Marieke, Crivello, Fabrice, Janowitz, Deborah, Carmichael, Owen, Haukvik, Unn K, Aribisala, Benjamin S, and Schmidt, Helena

Subjects
Biological Sciences, Genetics, Brain Disorders, Mental Health, Neurosciences, Human Genome, 2.1 Biological and endogenous factors, Neurological, Adult, Aged, Animals, Brain, Cohort Studies, Drosophila melanogaster, Genetic Variation, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Middle Aged, Neurodevelopmental Disorders, Organ Size, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Subcortical brain structures are integral to motion, consciousness, emotions and learning. We identified common genetic variation related to the volumes of the nucleus accumbens, amygdala, brainstem, caudate nucleus, globus pallidus, putamen and thalamus, using genome-wide association analyses in almost 40,000 individuals from CHARGE, ENIGMA and UK Biobank. We show that variability in subcortical volumes is heritable, and identify 48 significantly associated loci (40 novel at the time of analysis). Annotation of these loci by utilizing gene expression, methylation and neuropathological data identified 199 genes putatively implicated in neurodevelopment, synaptic signaling, axonal transport, apoptosis, inflammation/infection and susceptibility to neurological disorders. This set of genes is significantly enriched for Drosophila orthologs associated with neurodevelopmental phenotypes, suggesting evolutionarily conserved mechanisms. Our findings uncover novel biology and potential drug targets underlying brain development and disease.

Published
2019

26. The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

Author

de Zwarte, Sonja MC, Brouwer, Rachel M, Agartz, Ingrid, Alda, Martin, Aleman, André, Alpert, Kathryn I, Bearden, Carrie E, Bertolino, Alessandro, Bois, Catherine, Bonvino, Aurora, Bramon, Elvira, Buimer, Elizabeth EL, Cahn, Wiepke, Cannon, Dara M, Cannon, Tyrone D, Caseras, Xavier, Castro-Fornieles, Josefina, Chen, Qiang, Chung, Yoonho, De la Serna, Elena, Di Giorgio, Annabella, Doucet, Gaelle E, Eker, Mehmet Cagdas, Erk, Susanne, Fears, Scott C, Foley, Sonya F, Frangou, Sophia, Frankland, Andrew, Fullerton, Janice M, Glahn, David C, Goghari, Vina M, Goldman, Aaron L, Gonul, Ali Saffet, Gruber, Oliver, de Haan, Lieuwe, Hajek, Tomas, Hawkins, Emma L, Heinz, Andreas, Hillegers, Manon HJ, Pol, Hilleke E Hulshoff, Hultman, Christina M, Ingvar, Martin, Johansson, Viktoria, Jönsson, Erik G, Kane, Fergus, Kempton, Matthew J, Koenis, Marinka MG, Kopecek, Miloslav, Krabbendam, Lydia, Krämer, Bernd, Lawrie, Stephen M, Lenroot, Rhoshel K, Marcelis, Machteld, Marsman, Jan-Bernard C, Mattay, Venkata S, McDonald, Colm, Meyer-Lindenberg, Andreas, Michielse, Stijn, Mitchell, Philip B, Moreno, Dolores, Murray, Robin M, Mwangi, Benson, Najt, Pablo, Neilson, Emma, Newport, Jason, van Os, Jim, Overs, Bronwyn, Ozerdem, Aysegul, Picchioni, Marco M, Richter, Anja, Roberts, Gloria, Aydogan, Aybala Saricicek, Schofield, Peter R, Simsek, Fatma, Soares, Jair C, Sugranyes, Gisela, Toulopoulou, Timothea, Tronchin, Giulia, Walter, Henrik, Wang, Lei, Weinberger, Daniel R, Whalley, Heather C, Yalin, Nefize, Andreassen, Ole A, Ching, Christopher RK, van Erp, Theo GM, Turner, Jessica A, Jahanshad, Neda, Thompson, Paul M, Kahn, René S, and van Haren, Neeltje EM

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Mental Health, Brain Disorders, Serious Mental Illness, Schizophrenia, Genetics, Neurosciences, Clinical Research, Bipolar Disorder, 2.3 Psychological, social and economic factors, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adult, Brain, Cohort Studies, Female, Genetic Predisposition to Disease, Humans, Male, Middle Aged, Young Adult, Bipolar disorder, Familial risk, Imaging, Meta-analysis, Neurodevelopment, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Biological sciences, Biomedical and clinical sciences
Abstract

BackgroundSchizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects.MethodsWe performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects.ResultsFDRs-BD had significantly larger ICV (d = +0.16, q < .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = -0.12, q < .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d

Published
2019

27. Acquisition of visual priors and induced hallucinations in chronic schizophrenia

Author

Valton, Vincent, Karvelis, Povilas, Richards, Katie L, Seitz, Aaron R, Lawrie, Stephen M, and Seriès, Peggy

Subjects
Schizophrenia, Brain Disorders, Clinical Research, Mental Health, Mental health, Adult, Bayes Theorem, Female, Hallucinations, Humans, Male, Middle Aged, Models, Neurological, Motion Perception, schizophrenia, inference, statistical learning, hallucinations, Bayes, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Prominent theories suggest that symptoms of schizophrenia stem from learning deficiencies resulting in distorted internal models of the world. To test these theories further, we used a visual statistical learning task known to induce rapid implicit learning of the stimulus statistics. In this task, participants are presented with a field of coherently moving dots and are asked to report the presented direction of the dots (estimation task), and whether they saw any dots or not (detection task). Two of the directions were more frequently presented than the others. In controls, the implicit acquisition of the stimuli statistics influences their perception in two ways: (i) motion directions are perceived as being more similar to the most frequently presented directions than they really are (estimation biases); and (ii) in the absence of stimuli, participants sometimes report perceiving the most frequently presented directions (a form of hallucinations). Such behaviour is consistent with probabilistic inference, i.e. combining learnt perceptual priors with sensory evidence. We investigated whether patients with chronic, stable, treated schizophrenia (n = 20) differ from controls (n = 23) in the acquisition of the perceptual priors and/or their influence on perception. We found that although patients were slower than controls, they showed comparable acquisition of perceptual priors, approximating the stimulus statistics. This suggests that patients have no statistical learning deficits in our task. This may reflect our patients' relative wellbeing on antipsychotic medication. Intriguingly, however, patients experienced significantly fewer (P = 0.016) hallucinations of the most frequently presented directions than controls when the stimulus was absent or when it was very weak (prior-based lapse estimations). This suggests that prior expectations had less influence on patients' perception than on controls when stimuli were absent or below perceptual threshold.

Published
2019

28. 10Kin1day: A Bottom-Up Neuroimaging Initiative

Author

van den Heuvel, Martijn P, Scholtens, Lianne H, van der Burgh, Hannelore K, Agosta, Federica, Alloza, Clara, Arango, Celso, Auyeung, Bonnie, Baron-Cohen, Simon, Basaia, Silvia, Benders, Manon JNL, Beyer, Frauke, Booij, Linda, Braun, Kees PJ, Filho, Geraldo Busatto, Cahn, Wiepke, Cannon, Dara M, Chaim-Avancini, Tiffany M, Chan, Sandra SM, Chen, Eric YH, Crespo-Facorro, Benedicto, Crone, Eveline A, Dannlowski, Udo, de Zwarte, Sonja MC, Dietsche, Bruno, Donohoe, Gary, Du Plessis, Stefan, Durston, Sarah, Díaz-Caneja, Covadonga M, Díaz-Zuluaga, Ana M, Emsley, Robin, Filippi, Massimo, Frodl, Thomas, Gorges, Martin, Graff, Beata, Grotegerd, Dominik, Gąsecki, Dariusz, Hall, Julie M, Holleran, Laurena, Holt, Rosemary, Hopman, Helene J, Jansen, Andreas, Janssen, Joost, Jodzio, Krzysztof, Jäncke, Lutz, Kaleda, Vasiliy G, Kassubek, Jan, Masouleh, Shahrzad Kharabian, Kircher, Tilo, Koevoets, Martijn GJC, Kostic, Vladimir S, Krug, Axel, Lawrie, Stephen M, Lebedeva, Irina S, Lee, Edwin HM, Lett, Tristram A, Lewis, Simon JG, Liem, Franziskus, Lombardo, Michael V, Lopez-Jaramillo, Carlos, Margulies, Daniel S, Markett, Sebastian, Marques, Paulo, Martínez-Zalacaín, Ignacio, McDonald, Colm, McIntosh, Andrew M, McPhilemy, Genevieve, Meinert, Susanne L, Menchón, José M, Montag, Christian, Moreira, Pedro S, Morgado, Pedro, Mothersill, David O, Mérillat, Susan, Müller, Hans-Peter, Nabulsi, Leila, Najt, Pablo, Narkiewicz, Krzysztof, Naumczyk, Patrycja, Oranje, Bob, de la Foz, Victor Ortiz-Garcia, Peper, Jiska S, Pineda, Julian A, Rasser, Paul E, Redlich, Ronny, Repple, Jonathan, Reuter, Martin, Rosa, Pedro GP, Ruigrok, Amber NV, Sabisz, Agnieszka, Schall, Ulrich, Seedat, Soraya, Serpa, Mauricio H, Skouras, Stavros, Soriano-Mas, Carles, Sousa, Nuno, Szurowska, Edyta, Tomyshev, Alexander S, Tordesillas-Gutierrez, Diana, Valk, Sofie L, and van den Berg, Leonard H

Subjects
Biological Psychology, Psychology, Biomedical Imaging, Brain Disorders, Neurosciences, Neurological, MRI, connectome analysis, diffusion weighted MRI, brain, network, Clinical Sciences, Clinical sciences, Biological psychology
Abstract

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

Published
2019

32. Impaired verbal memory function is related to anterior cingulate glutamate levels in schizophrenia: findings from the STRATA study

Author

Griffiths, Kira, Egerton, Alice, Millgate, Edward, Anton, Adriana, Barker, Gareth J., Deakin, Bill, Drake, Richard, Eliasson, Emma, Gregory, Catherine J., Howes, Oliver D., Kravariti, Eugenia, Lawrie, Stephen M., Lewis, Shôn, Lythgoe, David J., Murphy, Anna, McGuire, Philip, Semple, Scott, Stockton-Powdrell, Charlotte, Walters, James T. R., Williams, Stephen R., and MacCabe, James H.

Published
2022
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38. Autistic traits, but not schizotypy, predict increased weighting of sensory information in Bayesian visual integration.

Author

Karvelis, Povilas, Seitz, Aaron R, Lawrie, Stephen M, and Seriès, Peggy

Subjects
Humans, Motivation, Learning, Visual Perception, Autistic Disorder, Schizotypal Personality Disorder, Models, Neurological, Adolescent, Adult, Aged, Middle Aged, Female, Male, Young Adult, Bayesian cognition, autism, computational psychiatry, human, neuroscience, schizophrenia, Models, Neurological, Biochemistry and Cell Biology
Abstract

Recent theories propose that schizophrenia/schizotypy and autistic spectrum disorder are related to impairments in Bayesian inference that is, how the brain integrates sensory information (likelihoods) with prior knowledge. However existing accounts fail to clarify: (i) how proposed theories differ in accounts of ASD vs. schizophrenia and (ii) whether the impairments result from weaker priors or enhanced likelihoods. Here, we directly address these issues by characterizing how 91 healthy participants, scored for autistic and schizotypal traits, implicitly learned and combined priors with sensory information. This was accomplished through a visual statistical learning paradigm designed to quantitatively assess variations in individuals' likelihoods and priors. The acquisition of the priors was found to be intact along both traits spectra. However, autistic traits were associated with more veridical perception and weaker influence of expectations. Bayesian modeling revealed that this was due, not to weaker prior expectations, but to more precise sensory representations.

Published
2018

40. A comprehensive hierarchical comparison of structural connectomes in Major Depressive Disorder cases v. controls in two large population samples

Author

Thng, Gladi, primary, Shen, Xueyi, additional, Stolicyn, Aleks, additional, Adams, Mark J., additional, Yeung, Hon Wah, additional, Batziou, Venia, additional, Conole, Eleanor L. S., additional, Buchanan, Colin R., additional, Lawrie, Stephen M., additional, Bastin, Mark E., additional, McIntosh, Andrew M., additional, Deary, Ian J., additional, Tucker-Drob, Elliot M., additional, Cox, Simon R., additional, Smith, Keith M., additional, Romaniuk, Liana, additional, and Whalley, Heather C., additional

Published
2024
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44. Participants aux Davidson's Principles and Practice of Medicine, 23eédition

Author

Angus, Brian J., primary, Anstee, Quentin M., additional, Burnett, Leslie, additional, Byers, Mark, additional, Campbell, Harry, additional, Clunie, Gavin P.R., additional, Colvin, Lesley A., additional, Conway, Bryan, additional, Cooper, Nicola, additional, Cracknell, Alison L., additional, Culligan, Dominic J., additional, Dark, Graham G., additional, Davenport, Richard J., additional, Dockrell, David H., additional, El-Omar, Emad, additional, Fallon, Marie, additional, FitzPatrick, David R., additional, Grubb, Neil R., additional, Ibbotson, Sally H., additional, Innes, J. Alastair, additional, Jenks, Sara J., additional, Johnston, Sarah L., additional, Jones, David E.J., additional, Langhorne, Peter, additional, Lawrie, Stephen M., additional, Leach, John Paul, additional, Maartens, Gary, additional, Mackillop, Lucy, additional, MacMahon, Michael J., additional, Mann, Rebecca, additional, Manson, Lynn M., additional, Marshall, Sara E., additional, Mather, Amanda, additional, Maxwell, Simon R., additional, McAllister, David A., additional, McCrimmon, Rory J., additional, McLean, Mairi, additional, Neuberger, Francesca E.M., additional, Newby, David E., additional, Newell-Price, John D.C., additional, Olson, John, additional, Pearson, Ewan R., additional, Phelan, Paul J., additional, Ralston, Stuart H., additional, Reid, Peter T., additional, Sandoe, Jonathan A.T., additional, Scott, Gordon R., additional, Shand, Alan G., additional, Steel, Robby M., additional, Stewart, Grant D., additional, Stewart, Peter, additional, Strachan, Mark W.J., additional, Sullivan, David R., additional, Sundar, Shyam, additional, Tallentire, Victoria R., additional, Tatton-Brown, Katrina, additional, Thomas, Simon H.L., additional, Watson, Henry G., additional, White, Julian, additional, Wilding, John P.H., additional, and Witham, Miles D., additional

Published
2022
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47. Structural brain correlates of serum and epigenetic markers of inflammation in major depressive disorder

Author

Green, Claire, Shen, Xueyi, Stevenson, Anna J., Conole, Eleanor L.S., Harris, Mathew A., Barbu, Miruna C., Hawkins, Emma L., Adams, Mark J., Hillary, Robert F., Lawrie, Stephen M., Evans, Kathryn L., Walker, Rosie M., Morris, Stewart W., Porteous, David J., Wardlaw, Joanna M., Steele, J Douglas, Waiter, Gordon D., Sandu, Anca-Larisa, Campbell, Archie, Marioni, Riccardo E., Cox, Simon R., Cavanagh, Jonathan, McIntosh, Andrew M., and Whalley, Heather C.

Published
2021
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48. Deconstructing depression and negative symptoms of schizophrenia; differential and longitudinal immune correlates, and response to minocycline treatment

Author

Krynicki, Carl R., Dazzan, Paola, Pariante, Carmine M., Barnes, Nicholas M., Vincent, Rachel C., Roberts, Alex, Giordano, Annalisa, Watson, Andrew, Suckling, John, Barnes, Thomas R.E., Husain, Nusrat, Jones, Peter B., Joyce, Eileen, Lawrie, Stephen M., Lewis, Shôn, Deakin, Bill, and Upthegrove, Rachel

Published
2021
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49. Supplements to: A naturalistic cohort study of first-episode schizophrenia spectrum disorder: a description of the early phase of illness in the PSYSCAN cohort

Author

Slot, Margot I. E. [I.E.Slot-3@umcutrecht.nl], Slot, Margot I. E., van Hell, Hendrika H., Rossum, Inge Winter-van, Dazzan, Paola, Maat, Arija, de Haan, Lieuwe, Crespo-Facorro, Benedicto, Glenthøj, Birte, Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Weiser, Mark, Sachs, Gabriele, Maatz, Anke, Bressan, Rodrigo A., Kwon, Jun Soo, Mizrahi, Romina, McGuire, Philip, Kahn, René S., Slot, Margot I. E. [I.E.Slot-3@umcutrecht.nl], Slot, Margot I. E., van Hell, Hendrika H., Rossum, Inge Winter-van, Dazzan, Paola, Maat, Arija, de Haan, Lieuwe, Crespo-Facorro, Benedicto, Glenthøj, Birte, Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Weiser, Mark, Sachs, Gabriele, Maatz, Anke, Bressan, Rodrigo A., Kwon, Jun Soo, Mizrahi, Romina, McGuire, Philip, and Kahn, René S.

Abstract

Suppl. Figure 1. Percentage of FES patients in symptomatic remission throughout the study., Suppl. Figure 2. Percentage of FES patients in functional remission throughout the study., Suppl. Figure 3. Clustered boxplot displaying the mean depression scores per time point (measured using the Hamilton Depression Rating Scale) in the subgroup meeting criteria for a depressive episode at baseline (assessed through the SCID-I) versus the subgroup without a depressive episode at baseline., Suppl. Table 1. Baseline demographics and clinical characteristics of study completers and drop-outs., Suppl. Table 2. Number of patients in symptomatic and functional remission throughout the period of follow-up., Suppl. Table 3. Generalized linear mixed models: pairwise contrasts for symptomatic and functional remission., Suppl. Table 4. Linear mixed models: estimated marginal means for PANSS, GAF, SOFAS, CGI, GF-S, GF-R and HAM-D., Suppl. Table 5. Linear mixed models: estimates of fixed effect time on PANSS, GAF, SOFAS, CGI, GF-S, GF-R and HAM-D., Suppl. Table 6. Number of patients admitted to the hospital since the previous visit due to psychotic symptoms and due to psychiatric reasons in general., Suppl. Table 7. Substances used at least once in the past three months (WHO-ASSIST)., Suppl. Table 8. Number of patients reporting daily or almost daily substance use in the past three months, separated per time point and substance category (WHO-ASSIST)., Suppl. Table 9. Number of patients reporting daily or almost daily substance use in the past three months, separated for the group of symptomatic remitters and non-remitters at month 12., Suppl. Table 10. Baseline demographics and clinical characteristics of symptomatic remitters and non-remitters at month 12., Suppl. Table 11. Summary of sociodemographics and baseline clinical characteristics of FES participants, separated per country., Suppl. Table 12. Number of FES patients in symptomatic remission throughout the period of follow-up, separated per country., Suppl. Table 13. Number of FES patients in functional remission throughout the period of follow-up, separated per country., Suppl. Table 14. Number of FES patients admitted to the hospital for psychiatric reasons throughout the period of follow-up, separated per country., Suppl. Table 15. Number of FES patients admitted to the hospital for psychosis throughout the period of follow-up, separated per country., Suppl. Table 16. Number of FES patients using antipsychotic medication throughout the period of follow-up, separated per country., Suppl. Table 17. Overview of subjects not meeting eligibility criteria., Suppl. Table 18. Number of patients in symptomatic and functional remission throughout the period of follow-up when using alternative definitions., Suppl. Table 19. Generalized linear mixed models: pairwise contrasts for symptomatic and functional remission when using alternative definitions.

Published
2024

50. A naturalistic cohort study of first-episode schizophrenia spectrum disorder: A description of the early phase of illness in the PSYSCAN cohort

Author

European Commission, Slot, Margot I. E., van Hell, Hendrika H., Rossum, Inge Winter-van, Dazzan, Paola, Maat, Arija, de Haan, Lieuwe, Crespo-Facorro, Benedicto, Glenthøj, Birte, Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Weiser, Mark, Sachs, Gabriele, Maatz, Anke, Bressan, Rodrigo A., Kwon, Jun Soo, Mizrahi, Romina, McGuire, Philip, Kahn, René S., European Commission, Slot, Margot I. E., van Hell, Hendrika H., Rossum, Inge Winter-van, Dazzan, Paola, Maat, Arija, de Haan, Lieuwe, Crespo-Facorro, Benedicto, Glenthøj, Birte, Lawrie, Stephen M., McDonald, Colm, Gruber, Oliver, van Amelsvoort, Thérèse, Arango, Celso, Kircher, Tilo, Nelson, Barnaby, Galderisi, Silvana, Weiser, Mark, Sachs, Gabriele, Maatz, Anke, Bressan, Rodrigo A., Kwon, Jun Soo, Mizrahi, Romina, McGuire, Philip, and Kahn, René S.

Abstract

[Background] We examined the course of illness over a 12-month period in a large, international multi-center cohort of people with a first-episode schizophrenia spectrum disorder (FES) in a naturalistic, prospective study (PSYSCAN)., [Method] Patients with a first episode of schizophrenia, schizoaffective disorder (depressive type) or schizophreniform disorder were recruited at 16 institutions in Europe, Israel and Australia. Participants (N = 304) received clinical treatment as usual throughout the study., [Results] The mean age of the cohort was 24.3 years (SD = 5.6), and 67 % were male. At baseline, participants presented with a range of intensities of psychotic symptoms, 80 % were taking antipsychotic medication, 68 % were receiving psychological treatment, with 46.5 % in symptomatic remission. The mean duration of untreated psychosis was 6.2 months (SD = 17.0). After one year, 67 % were in symptomatic remission and 61 % were in functional remission, but 31 % had been readmitted to hospital at some time after baseline. In the cohort as a whole, depressive symptoms remained stable over the follow-up period. In patients with a current depressive episode at baseline, depressive symptoms slightly improved. Alcohol, tobacco and cannabis were the most commonly used substances, with daily users of cannabis ranging between 9 and 11 % throughout the follow-up period., [Conclusions] This study provides valuable insight into the early course of a broad range of clinical and functional aspects of illness in FES patients in routine clinical practice.

Published
2024

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