Author: "Gruber, O." / Publication Year Range: Last 3 years - Searchworks@Jio Institute Digital Library Search Results

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49 results on '"Gruber, O."'

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

Author: Slot, MIE, van Hell, HH, Rossum, IW-V, Dazzan, P, Maat, A, de Haan, L, Crespo-Facorro, B, Glenthøj, B, Lawrie, SM, McDonald, C, Gruber, O, van Amelsvoort, T, Arango, C, Kircher, T, Nelson, B, Galderisi, S, Weiser, M, Sachs, G, Maatz, A, Bressan, RA, Kwon, JS, Mizrahi, R, PSYSCAN Consortium, McGuire, P, Kahn, RS, Slot, MIE, van Hell, HH, Rossum, IW-V, Dazzan, P, Maat, A, de Haan, L, Crespo-Facorro, B, Glenthøj, B, Lawrie, SM, McDonald, C, Gruber, O, van Amelsvoort, T, Arango, C, Kircher, T, Nelson, B, Galderisi, S, Weiser, M, Sachs, G, Maatz, A, Bressan, RA, Kwon, JS, Mizrahi, R, PSYSCAN Consortium, McGuire, P, and Kahn, RS
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

2. Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation

Author: Ge, R., Yu, Y, Qi, Y.X., Fan, Y.N., Chen, S., Gao, Chuntong, Haas, S.S., New, F., Boomsma, D.I., Brodaty, H., Brouwer, R.M., Buckner, R., Caseras, X., Crivello, F., Crone, E.A.M., Erk, S., Fisher, S.E., Franke, B., Glahn, D.C., Dannlowski, U., Grotegerd, D., Gruber, O., Pol, H.E. Hulshoff, Schumann, G., Tamnes, C.K., Walter, H., Wierenga, L.M., Jahanshad, N., Thompson, P.M., Frangou, S., Ge, R., Yu, Y, Qi, Y.X., Fan, Y.N., Chen, S., Gao, Chuntong, Haas, S.S., New, F., Boomsma, D.I., Brodaty, H., Brouwer, R.M., Buckner, R., Caseras, X., Crivello, F., Crone, E.A.M., Erk, S., Fisher, S.E., Franke, B., Glahn, D.C., Dannlowski, U., Grotegerd, D., Gruber, O., Pol, H.E. Hulshoff, Schumann, G., Tamnes, C.K., Walter, H., Wierenga, L.M., Jahanshad, N., Thompson, P.M., and Frangou, S.
Abstract: Contains fulltext : 305173.pdf (Publisher’s version ) (Open Access), The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain.
Published: 2024

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

Author: Schijven, Dick, Postema, M.C., Fukunaga, M., Matsumoto, J., Miura, K., Zwarte, S.M.C. de, Haren, N.E.M. van, Cahn, W., Hulshoff Pol, H.E., Kahn, R.S., Ayesa-Arriola, R., Ortoz-García de la Foz, V., Tordesillas-Gutierrez, D., Vázquez-Bourgon, J., Crespo-Facorro, B., Alnæs, D., Dahl, A., Westlye, L.T., Agartz, I., Andreassen, O.A., Jönsson, E.G., Kochunov, P., Bruggemann, J.M., Catts, S.V., Michie, P.T., Mowry, B.J., Quidé, Y., Rasser, P.E., Schall, U., Scott, R.J., Carr, V.J., Green, M.J., Henskens, F.A., Loughland, C.M., Pantelis, C., Weickert, C.S., Weickert, T.W., Haan, L. de, Brosch, K., Pfarr, J.K., Ringwald, K.G., Stein, F., Jansen, Andreas, Kircher, T.T.J., Nenadić, I., Krämer, Bernd, Gruber, O., Satterthwaite, T.D., Bustillo, J., Mathalon, D.H., Preda, A., Calhoun, V.D., Ford, J.M., Potkin, S.G., Chen, Jingxu, Tan, Yunlong, Wang, Zhiren, Xiang, Hong, Fan, Fengmei, Bernardoni, F., Ehrlich, S., Fuentes-Claramonte, P., Garcia-Leon, M.A., Guerrero-Pedraza, A., Salvador, R., Sarró, S., Pomarol-Clotet, E., Ciullo, V., Piras, F., Vecchio, D., Banaj, N., Spalletta, G., Michielse, S., Amelsvoort, T. van, Dickie, E.W., Voineskos, A.N., Sim, K., Ciufolini, S., Dazzan, P., Murray, R.M., Kim, W.S., Chung, Y.C., Andreou, C., Schmidt, A, Borgwardt, S., McIntosh, A.M., Whalley, H.C., Lawrie, S.M., Plessis, S. du, Luckhoff, H.K., Scheffler, F., Emsley, R., Grotegerd, D., Lencer, R., Dannlowski, U., Edmond, J.T., Rootes-Murdy, K., Stephen, J.M., Mayer, A.R., Antonucci, L.A., Fazio, L., Pergola, G., Bertolino, A., Díaz-Caneja, C.M., Janssen, J, Lois, N.G., Arango, C., Tomyshev, A.S., Lebedeva, I., Cervenka, S., Sellgren, C.M., Georgiadis, F., Kirschner, M., Kaiser, S., Hajek, T., Skoch, A., Spaniel, F., Kim, M., Kwak, Y.B., Oh, S., Kwon, J.S., James, A., Bakker, G., Knöchel, C., Stäblein, M., Oertel, V., Uhlmann, A., Howells, F.M., Stein, D.J., Temmingh, H.S., Diaz-Zuluaga, A.M., Pineda-Zapata, J.A., López-Jaramillo, C., Homan, S., Ji, E., Surbeck, W., Homan, P., Fisher, S.E., Franke, B., Glahn, D.C., Gur, R.C., Hashimoto, R., Jahanshad, N., Luders, E., Medland, S.E., Thompson, P.M., Turner, J.A., Erp, T.G. van, Francks, C., Schijven, Dick, Postema, M.C., Fukunaga, M., Matsumoto, J., Miura, K., Zwarte, S.M.C. de, Haren, N.E.M. van, Cahn, W., Hulshoff Pol, H.E., Kahn, R.S., Ayesa-Arriola, R., Ortoz-García de la Foz, V., Tordesillas-Gutierrez, D., Vázquez-Bourgon, J., Crespo-Facorro, B., Alnæs, D., Dahl, A., Westlye, L.T., Agartz, I., Andreassen, O.A., Jönsson, E.G., Kochunov, P., Bruggemann, J.M., Catts, S.V., Michie, P.T., Mowry, B.J., Quidé, Y., Rasser, P.E., Schall, U., Scott, R.J., Carr, V.J., Green, M.J., Henskens, F.A., Loughland, C.M., Pantelis, C., Weickert, C.S., Weickert, T.W., Haan, L. de, Brosch, K., Pfarr, J.K., Ringwald, K.G., Stein, F., Jansen, Andreas, Kircher, T.T.J., Nenadić, I., Krämer, Bernd, Gruber, O., Satterthwaite, T.D., Bustillo, J., Mathalon, D.H., Preda, A., Calhoun, V.D., Ford, J.M., Potkin, S.G., Chen, Jingxu, Tan, Yunlong, Wang, Zhiren, Xiang, Hong, Fan, Fengmei, Bernardoni, F., Ehrlich, S., Fuentes-Claramonte, P., Garcia-Leon, M.A., Guerrero-Pedraza, A., Salvador, R., Sarró, S., Pomarol-Clotet, E., Ciullo, V., Piras, F., Vecchio, D., Banaj, N., Spalletta, G., Michielse, S., Amelsvoort, T. van, Dickie, E.W., Voineskos, A.N., Sim, K., Ciufolini, S., Dazzan, P., Murray, R.M., Kim, W.S., Chung, Y.C., Andreou, C., Schmidt, A, Borgwardt, S., McIntosh, A.M., Whalley, H.C., Lawrie, S.M., Plessis, S. du, Luckhoff, H.K., Scheffler, F., Emsley, R., Grotegerd, D., Lencer, R., Dannlowski, U., Edmond, J.T., Rootes-Murdy, K., Stephen, J.M., Mayer, A.R., Antonucci, L.A., Fazio, L., Pergola, G., Bertolino, A., Díaz-Caneja, C.M., Janssen, J, Lois, N.G., Arango, C., Tomyshev, A.S., Lebedeva, I., Cervenka, S., Sellgren, C.M., Georgiadis, F., Kirschner, M., Kaiser, S., Hajek, T., Skoch, A., Spaniel, F., Kim, M., Kwak, Y.B., Oh, S., Kwon, J.S., James, A., Bakker, G., Knöchel, C., Stäblein, M., Oertel, V., Uhlmann, A., Howells, F.M., Stein, D.J., Temmingh, H.S., Diaz-Zuluaga, A.M., Pineda-Zapata, J.A., López-Jaramillo, C., Homan, S., Ji, E., Surbeck, W., Homan, P., Fisher, S.E., Franke, B., Glahn, D.C., Gur, R.C., Hashimoto, R., Jahanshad, N., Luders, E., Medland, S.E., Thompson, P.M., Turner, J.A., Erp, T.G. van, and Francks, C.
Abstract: Item does not contain fulltext, 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

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

Author: Schijven, D, Postema, MC, Fukunaga, M, Matsumoto, J, Miura, K, de Zwarte, SMC, van Haren, NEM, Cahn, W, Pol, HEH, Kahn, RS, Ayesa-Arriola, R, de la Foz, VO-G, Tordesillas-Gutierrez, D, Vazquez-Bourgon, J, Crespo-Facorro, B, Alnaes, D, Dahl, A, Westlye, LT, Agartz, I, Andreassen, OA, Jonsson, EG, Kochunov, P, Bruggemann, JM, Catts, SV, Michie, PT, Mowry, BJ, Quide, Y, Rasser, PE, Schall, U, Scott, RJ, Carr, VJ, Green, MJ, Henskens, FA, Loughland, CM, Pantelis, C, Weickert, CS, Weickert, TW, De Haan, L, Brosch, K, Pfarr, J-K, Ringwald, KG, Stein, F, Jansen, A, Kircher, TTJ, Nenadic, I, Kramer, B, Gruber, O, Satterthwaite, TD, Bustillo, J, Mathalon, DH, Preda, A, Calhoun, VD, Ford, JM, Potkin, SG, Chen, J, Tan, Y, Wang, Z, Xiang, H, Fan, F, Bernardoni, F, Ehrlich, S, Fuentes-Claramonte, P, Garcia-Leon, MA, Guerrero-Pedraza, A, Salvador, R, Sarro, S, Pomarol-Clotet, E, Ciullo, V, Piras, F, Vecchio, D, Banaj, N, Spalletta, G, Michielse, S, van Amelsvoort, T, Dickie, EW, Voineskos, AN, Sim, K, Ciufolini, S, Dazzan, P, Murray, RM, Kim, W-S, Chung, Y-C, Andreou, C, Schmidt, A, Borgwardt, S, McIntosh, AM, Whalley, HC, Lawrie, SM, Du Plessis, S, Luckhoff, HK, Scheffler, F, Emsley, R, Grotegerd, D, Lencer, R, Dannlowski, U, Edmond, JT, Rootes-Murdy, K, Stephen, JM, Mayer, AR, Antonucci, LA, Fazio, L, Pergola, G, Bertolino, A, Diaz-Caneja, CM, Janssen, J, Lois, NG, Arango, C, Tomyshev, AS, Lebedeva, I, Cervenkav, S, Sellgrenv, CM, Georgiadis, F, Kirschner, M, Kaiser, S, Hajek, T, Skoch, A, Spaniel, F, Kim, M, Bin Kwak, Y, Oh, S, Kwon, JS, James, A, Bakker, G, Knochel, C, Stablein, M, Oertel, V, Uhlmann, A, Howells, FM, Stein, DJ, Temmingh, HS, Diaz-Zuluaga, AM, Pineda-Zapata, JA, Lopez-Jaramillo, C, Homan, S, Ji, E, Surbeck, W, Homan, P, Fishera, SE, Franke, B, Glahn, DC, Gur, RC, Hashimoto, R, Jahanshad, N, Luders, E, Medland, SE, Thompson, PM, Turner, JA, van Erp, TGM, Francks, C, Schijven, D, Postema, MC, Fukunaga, M, Matsumoto, J, Miura, K, de Zwarte, SMC, van Haren, NEM, Cahn, W, Pol, HEH, Kahn, RS, Ayesa-Arriola, R, de la Foz, VO-G, Tordesillas-Gutierrez, D, Vazquez-Bourgon, J, Crespo-Facorro, B, Alnaes, D, Dahl, A, Westlye, LT, Agartz, I, Andreassen, OA, Jonsson, EG, Kochunov, P, Bruggemann, JM, Catts, SV, Michie, PT, Mowry, BJ, Quide, Y, Rasser, PE, Schall, U, Scott, RJ, Carr, VJ, Green, MJ, Henskens, FA, Loughland, CM, Pantelis, C, Weickert, CS, Weickert, TW, De Haan, L, Brosch, K, Pfarr, J-K, Ringwald, KG, Stein, F, Jansen, A, Kircher, TTJ, Nenadic, I, Kramer, B, Gruber, O, Satterthwaite, TD, Bustillo, J, Mathalon, DH, Preda, A, Calhoun, VD, Ford, JM, Potkin, SG, Chen, J, Tan, Y, Wang, Z, Xiang, H, Fan, F, Bernardoni, F, Ehrlich, S, Fuentes-Claramonte, P, Garcia-Leon, MA, Guerrero-Pedraza, A, Salvador, R, Sarro, S, Pomarol-Clotet, E, Ciullo, V, Piras, F, Vecchio, D, Banaj, N, Spalletta, G, Michielse, S, van Amelsvoort, T, Dickie, EW, Voineskos, AN, Sim, K, Ciufolini, S, Dazzan, P, Murray, RM, Kim, W-S, Chung, Y-C, Andreou, C, Schmidt, A, Borgwardt, S, McIntosh, AM, Whalley, HC, Lawrie, SM, Du Plessis, S, Luckhoff, HK, Scheffler, F, Emsley, R, Grotegerd, D, Lencer, R, Dannlowski, U, Edmond, JT, Rootes-Murdy, K, Stephen, JM, Mayer, AR, Antonucci, LA, Fazio, L, Pergola, G, Bertolino, A, Diaz-Caneja, CM, Janssen, J, Lois, NG, Arango, C, Tomyshev, AS, Lebedeva, I, Cervenkav, S, Sellgrenv, CM, Georgiadis, F, Kirschner, M, Kaiser, S, Hajek, T, Skoch, A, Spaniel, F, Kim, M, Bin Kwak, Y, Oh, S, Kwon, JS, James, A, Bakker, G, Knochel, C, Stablein, M, Oertel, V, Uhlmann, A, Howells, FM, Stein, DJ, Temmingh, HS, Diaz-Zuluaga, AM, Pineda-Zapata, JA, Lopez-Jaramillo, C, Homan, S, Ji, E, Surbeck, W, Homan, P, Fishera, SE, Franke, B, Glahn, DC, Gur, RC, Hashimoto, R, Jahanshad, N, Luders, E, Medland, SE, Thompson, PM, Turner, JA, van Erp, TGM, and Francks, C
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

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

Author: Dima, D., Modabbernia, A., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dannlowski, U., Dale, A.M., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Kalnin, A., Naaijen, J., Klein, M., Thompson, P.M., Frangou, S., Dima, D., Modabbernia, A., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dannlowski, U., Dale, A.M., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Kalnin, A., Naaijen, J., Klein, M., Thompson, P.M., and Frangou, S.
Abstract: Contains fulltext : 245411.pdf (Publisher’s version ) (Open Access), 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

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

Author: Frangou, S., Modabbernia, A., Williams, S.C.R., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dale, A.M., Dannlowski, U., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Klein, M., Frangou, S., Modabbernia, A., Williams, S.C.R., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dale, A.M., Dannlowski, U., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., and Klein, M.
Abstract: Contains fulltext : 245396.pdf (Publisher’s version ) (Open Access), 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

7. Greater male than female variability in regional brain structure across the lifespan

Author: Wierenga, L.M., Doucet, G.E., Dima, D., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andreassen, O.A., Anticevic, A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Braber, A., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Calhoun, V.D., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Chaim-Avancini, T.M., Ching, C.R., Clark, V.P., Conrod, P.J., Conzelmann, A., Crivello, F., Davey, C.G., Dickie, E.W., Ehrlich, S., Ent, D. van 't, Fisher, S.E., Fouche, J.P., Franke, B., Fuentes-Claramonte, P., Geus, E.J. de, Giorgio, A. Di, Glahn, D.C., Gotlib, I.H., Grabe, H.J., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Gurholt, T.P., Haan, L. de, Haatveit, B., Harrison, B.J., Hartman, C.A., Hatton, S.N., Heslenfeld, D.J., Heuvel, O.A. van den, Hickie, I.B., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A.C., Jiang, J., Jönsson, E.G., Joska, J.A., Kalnin, A.J., Klein, M., Koenders, L., Kolskår, K.K., Krämer, B., Kuntsi, J., Lagopoulos, J., Lazaro, L., Lebedeva, I.S., Lee, Phil H., Lochner, C., Machielsen, M.W., Maingault, S., Martin, N.G., Martínez-Zalacaín, I., Mataix-Cols, D., Mazoyer, B., McDonald, B.C., McDonald, C., McIntosh, A.M., McMahon, K.L., McPhilemy, G., Naaijen, J., Frangou, S., Tamnes, C.K., Wierenga, L.M., Doucet, G.E., Dima, D., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andreassen, O.A., Anticevic, A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Braber, A., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Calhoun, V.D., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Chaim-Avancini, T.M., Ching, C.R., Clark, V.P., Conrod, P.J., Conzelmann, A., Crivello, F., Davey, C.G., Dickie, E.W., Ehrlich, S., Ent, D. van 't, Fisher, S.E., Fouche, J.P., Franke, B., Fuentes-Claramonte, P., Geus, E.J. de, Giorgio, A. Di, Glahn, D.C., Gotlib, I.H., Grabe, H.J., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Gurholt, T.P., Haan, L. de, Haatveit, B., Harrison, B.J., Hartman, C.A., Hatton, S.N., Heslenfeld, D.J., Heuvel, O.A. van den, Hickie, I.B., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A.C., Jiang, J., Jönsson, E.G., Joska, J.A., Kalnin, A.J., Klein, M., Koenders, L., Kolskår, K.K., Krämer, B., Kuntsi, J., Lagopoulos, J., Lazaro, L., Lebedeva, I.S., Lee, Phil H., Lochner, C., Machielsen, M.W., Maingault, S., Martin, N.G., Martínez-Zalacaín, I., Mataix-Cols, D., Mazoyer, B., McDonald, B.C., McDonald, C., McIntosh, A.M., McMahon, K.L., McPhilemy, G., Naaijen, J., Frangou, S., and Tamnes, C.K.
Abstract: Contains fulltext : 248376.pdf (Publisher’s version ) (Open Access), For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
Published: 2022

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

Author: Haukvik, UK, Gurholt, TP, Nerland, S, Elvsåshagen, T, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Bauer, J, Baune, BT, Benedetti, F, Berk, Michael, Bettella, F, Bøen, E, Bonnín, CM, Brambilla, P, Canales-Rodríguez, EJ, Cannon, DM, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Díaz-Zuluaga, AM, van Erp, TGM, Fatjó-Vilas, M, Foley, SF, Förster, K, Fullerton, JM, Goikolea, JM, Grotegerd, D, Gruber, O, Haarman, BCM, Haatveit, B, Hajek, T, Hallahan, B, Harris, M, Hawkins, EL, Howells, FM, Hülsmann, C, Jahanshad, N, Jørgensen, KN, Kircher, T, Krämer, B, Krug, A, Kuplicki, R, Lagerberg, TV, Lancaster, TM, Lenroot, RK, Lonning, V, López-Jaramillo, C, Malt, UF, McDonald, C, McIntosh, AM, McPhilemy, G, van der Meer, D, Melle, I, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Oertel, V, Oldani, L, Opel, N, Otaduy, MCG, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Radua, J, Rauer, L, Redlich, R, Repple, J, Rive, MM, Roberts, G, Ruhe, HG, Salminen, LE, Salvador, R, Sarró, S, Savitz, J, Schene, AH, Sim, K, Soeiro-de-Souza, MG, Stäblein, M, Stein, DJ, Stein, F, Tamnes, CK, Temmingh, HS, Thomopoulos, SI, Veltman, DJ, Vieta, E, Waltemate, L, Westlye, LT, Whalley, HC, Sämann, PG, Thompson, PM, Ching, CRK, Andreassen, OA, Agartz, I, Haukvik, UK, Gurholt, TP, Nerland, S, Elvsåshagen, T, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Bauer, J, Baune, BT, Benedetti, F, Berk, Michael, Bettella, F, Bøen, E, Bonnín, CM, Brambilla, P, Canales-Rodríguez, EJ, Cannon, DM, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Díaz-Zuluaga, AM, van Erp, TGM, Fatjó-Vilas, M, Foley, SF, Förster, K, Fullerton, JM, Goikolea, JM, Grotegerd, D, Gruber, O, Haarman, BCM, Haatveit, B, Hajek, T, Hallahan, B, Harris, M, Hawkins, EL, Howells, FM, Hülsmann, C, Jahanshad, N, Jørgensen, KN, Kircher, T, Krämer, B, Krug, A, Kuplicki, R, Lagerberg, TV, Lancaster, TM, Lenroot, RK, Lonning, V, López-Jaramillo, C, Malt, UF, McDonald, C, McIntosh, AM, McPhilemy, G, van der Meer, D, Melle, I, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Oertel, V, Oldani, L, Opel, N, Otaduy, MCG, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Radua, J, Rauer, L, Redlich, R, Repple, J, Rive, MM, Roberts, G, Ruhe, HG, Salminen, LE, Salvador, R, Sarró, S, Savitz, J, Schene, AH, Sim, K, Soeiro-de-Souza, MG, Stäblein, M, Stein, DJ, Stein, F, Tamnes, CK, Temmingh, HS, Thomopoulos, SI, Veltman, DJ, Vieta, E, Waltemate, L, Westlye, LT, Whalley, HC, Sämann, PG, Thompson, PM, Ching, CRK, Andreassen, OA, and Agartz, I
Published: 2022

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

Author: Kong, XZ, Francks, C, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Asherson, P, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Cannon, DM, Caparelli, EC, Castellanos, FX, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dannlowski, U, de Bruttopilo, SA, de Zeeuw, P, Deary, IJ, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Flint, C, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, JM, Garavan, H, do Santos Garcia, D, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, del Carmen Valdés Hernández, M, Kong, XZ, Francks, C, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Asherson, P, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Cannon, DM, Caparelli, EC, Castellanos, FX, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dannlowski, U, de Bruttopilo, SA, de Zeeuw, P, Deary, IJ, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Flint, C, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, JM, Garavan, H, do Santos Garcia, D, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, and del Carmen Valdés Hernández, M
Published: 2022

10. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from theENIGMABipolar Disorder Working Group

Author: Ching, CRK, Hibar, DP, Gurholt, TP, Nunes, A, Thomopoulos, SI, Abe, C, Agartz, I, Brouwer, RM, Cannon, DM, de Zwarte, SMC, Eyler, LT, Favre, P, Hajek, T, Haukvik, UK, Houenou, J, Landen, M, Lett, TA, McDonald, C, Nabulsi, L, Patel, Y, Pauling, ME, Paus, T, Radua, J, Soeiro-de-Souza, MG, Tronchin, G, van Haren, NEM, Vieta, E, Walter, H, Zeng, L-L, Alda, M, Almeida, J, Alnaes, D, Alonso-Lana, S, Altimus, C, Bauer, M, Baune, BT, Bearden, CE, Bellani, M, Benedetti, F, Berk, M, Bilderbeck, AC, Blumberg, HP, Boen, E, Bollettini, I, del Mar Bonnin, C, Brambilla, P, Canales-Rodriguez, EJ, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Diaz-Zuluaga, AM, Dima, D, Duchesnay, E, Elvsashagen, T, Fears, SC, Frangou, S, Fullerton, JM, Glahn, DC, Goikolea, JM, Green, MJ, Grotegerd, D, Gruber, O, Haarman, BCM, Henry, C, Howells, FM, Ives-Deliperi, V, Jansen, A, Kircher, TTJ, Knoechel, C, Kramer, B, Lafer, B, Lopez-Jaramillo, C, Machado-Vieira, R, MacIntosh, BJ, Melloni, EMT, Mitchell, PB, Nenadic, I, Nery, F, Nugent, AC, Oertel, V, Ophoff, RA, Ota, M, Overs, BJ, Pham, DL, Phillips, ML, Pineda-Zapata, JA, Poletti, S, Polosan, M, Pomarol-Clotet, E, Pouchon, A, Quide, Y, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Schene, AH, Sim, K, Soares, JC, Staeblein, M, Stein, DJ, Tamnes, CK, Thomaidis, GV, Upegui, CV, Veltman, DJ, Wessa, M, Westlye, LT, Whalley, HC, Wolf, DH, Wu, M-J, Yatham, LN, Zarate, CA, Thompson, PM, Andreassen, OA, Ching, CRK, Hibar, DP, Gurholt, TP, Nunes, A, Thomopoulos, SI, Abe, C, Agartz, I, Brouwer, RM, Cannon, DM, de Zwarte, SMC, Eyler, LT, Favre, P, Hajek, T, Haukvik, UK, Houenou, J, Landen, M, Lett, TA, McDonald, C, Nabulsi, L, Patel, Y, Pauling, ME, Paus, T, Radua, J, Soeiro-de-Souza, MG, Tronchin, G, van Haren, NEM, Vieta, E, Walter, H, Zeng, L-L, Alda, M, Almeida, J, Alnaes, D, Alonso-Lana, S, Altimus, C, Bauer, M, Baune, BT, Bearden, CE, Bellani, M, Benedetti, F, Berk, M, Bilderbeck, AC, Blumberg, HP, Boen, E, Bollettini, I, del Mar Bonnin, C, Brambilla, P, Canales-Rodriguez, EJ, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Diaz-Zuluaga, AM, Dima, D, Duchesnay, E, Elvsashagen, T, Fears, SC, Frangou, S, Fullerton, JM, Glahn, DC, Goikolea, JM, Green, MJ, Grotegerd, D, Gruber, O, Haarman, BCM, Henry, C, Howells, FM, Ives-Deliperi, V, Jansen, A, Kircher, TTJ, Knoechel, C, Kramer, B, Lafer, B, Lopez-Jaramillo, C, Machado-Vieira, R, MacIntosh, BJ, Melloni, EMT, Mitchell, PB, Nenadic, I, Nery, F, Nugent, AC, Oertel, V, Ophoff, RA, Ota, M, Overs, BJ, Pham, DL, Phillips, ML, Pineda-Zapata, JA, Poletti, S, Polosan, M, Pomarol-Clotet, E, Pouchon, A, Quide, Y, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Schene, AH, Sim, K, Soares, JC, Staeblein, M, Stein, DJ, Tamnes, CK, Thomaidis, GV, Upegui, CV, Veltman, DJ, Wessa, M, Westlye, LT, Whalley, HC, Wolf, DH, Wu, M-J, Yatham, LN, Zarate, CA, Thompson, PM, and Andreassen, OA
Abstract: MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.
Published: 2022

11. Greater male than female variability in regional brain structure across the lifespan

Author: Wierenga, LM, Doucet, GE, Dima, D, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andreassen, OA, Anticevic, A, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, den Braber, A, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Calhoun, VD, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Chaim-Avancini, TM, Ching, CRK, Clark, VP, Conrod, PJ, Conzelmann, A, Crivello, F, Davey, CG, Dickie, EW, Ehrlich, S, Van't Ent, D, Fisher, SE, Fouche, J-P, Franke, B, Fuentes-Claramonte, P, de Geus, EJC, Di Giorgio, A, Glahn, DC, Gotlib, IH, Grabe, HJ, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Gurholt, TP, de Haan, L, Haatveit, B, Harrison, BJ, Hartman, CA, Hatton, SN, Heslenfeld, DJ, van den Heuvel, OA, Hickie, IB, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, AC, Jiang, J, Jonsson, EG, Joska, JA, Kalnin, AJ, Klein, M, Koenders, L, Kolskar, KK, Kramer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, IS, Lee, PH, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, BC, McDonald, C, McIntosh, AM, McMahon, KL, McPhilemy, G, van der Meer, D, Menchon, JM, Naaijen, J, Nyberg, L, Oosterlaan, J, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Radua, J, Reif, A, Richard, G, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Sim, K, Simmons, A, Smoller, JW, Sommer, IE, Soriano-Mas, C, Stein, DJ, Strike, LT, Szeszko, PR, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Trollor, JN, Uhlmann, A, Veer, IM, Veltman, DJ, Voineskos, A, Volzke, H, Walter, H, Wang, L, Wang, Y, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, HC, Williams, SCR, Wittfeld, K, Wolf, DH, Wright, MJ, Yoncheva, YN, Zanetti, M, Ziegler, GC, de Zubicaray, G, Thompson, PM, Crone, EA, Frangou, S, Tamnes, CK, Wierenga, LM, Doucet, GE, Dima, D, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andreassen, OA, Anticevic, A, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, den Braber, A, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Calhoun, VD, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Chaim-Avancini, TM, Ching, CRK, Clark, VP, Conrod, PJ, Conzelmann, A, Crivello, F, Davey, CG, Dickie, EW, Ehrlich, S, Van't Ent, D, Fisher, SE, Fouche, J-P, Franke, B, Fuentes-Claramonte, P, de Geus, EJC, Di Giorgio, A, Glahn, DC, Gotlib, IH, Grabe, HJ, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Gurholt, TP, de Haan, L, Haatveit, B, Harrison, BJ, Hartman, CA, Hatton, SN, Heslenfeld, DJ, van den Heuvel, OA, Hickie, IB, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, AC, Jiang, J, Jonsson, EG, Joska, JA, Kalnin, AJ, Klein, M, Koenders, L, Kolskar, KK, Kramer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, IS, Lee, PH, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, BC, McDonald, C, McIntosh, AM, McMahon, KL, McPhilemy, G, van der Meer, D, Menchon, JM, Naaijen, J, Nyberg, L, Oosterlaan, J, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Radua, J, Reif, A, Richard, G, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Sim, K, Simmons, A, Smoller, JW, Sommer, IE, Soriano-Mas, C, Stein, DJ, Strike, LT, Szeszko, PR, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Trollor, JN, Uhlmann, A, Veer, IM, Veltman, DJ, Voineskos, A, Volzke, H, Walter, H, Wang, L, Wang, Y, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, HC, Williams, SCR, Wittfeld, K, Wolf, DH, Wright, MJ, Yoncheva, YN, Zanetti, M, Ziegler, GC, de Zubicaray, G, Thompson, PM, Crone, EA, Frangou, S, and Tamnes, CK
Abstract: For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
Published: 2022

12. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics throughMeta-AnalysisBipolar Disorder Working Group

Author: Haukvik, UK, Gurholt, TP, Nerland, S, Elvsashagen, T, Akudjedu, TN, Alda, M, Alnaes, D, Alonso-Lana, S, Bauer, J, Baune, BT, Benedetti, F, Berk, M, Bettella, F, Boen, E, Bonnin, CM, Brambilla, P, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Diaz-Zuluaga, AM, Erp, TGM, Fatjo-Vilas, M, Foley, SF, Foerster, K, Fullerton, JM, Goikolea, JM, Grotegerd, D, Gruber, O, Haarman, BCM, Haatveit, B, Hajek, T, Hallahan, B, Harris, M, Hawkins, EL, Howells, FM, Huelsmann, C, Jahanshad, N, Jorgensen, KN, Kircher, T, Kraemer, B, Krug, A, Kuplicki, R, Lagerberg, T, Lancaster, TM, Lenroot, RK, Lonning, V, Lopez-Jaramillo, C, Malt, UF, McDonald, C, McIntosh, AM, McPhilemy, G, Meer, D, Melle, I, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadic, I, Oertel, V, Oldani, L, Opel, N, Otaduy, MCG, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Radua, J, Rauer, L, Redlich, R, Repple, J, Rive, MM, Roberts, G, Ruhe, HG, Salminen, LE, Salvador, R, Sarro, S, Savitz, J, Schene, AH, Sim, K, Soeiro-de-Souza, MG, Staeblein, M, Stein, DJ, Stein, F, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Veltman, DJ, Vieta, E, Waltemate, L, Westlye, LT, Whalley, HC, Saemann, PG, Thompson, PM, Ching, CRK, Andreassen, OA, Agartz, I, Haukvik, UK, Gurholt, TP, Nerland, S, Elvsashagen, T, Akudjedu, TN, Alda, M, Alnaes, D, Alonso-Lana, S, Bauer, J, Baune, BT, Benedetti, F, Berk, M, Bettella, F, Boen, E, Bonnin, CM, Brambilla, P, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Diaz-Zuluaga, AM, Erp, TGM, Fatjo-Vilas, M, Foley, SF, Foerster, K, Fullerton, JM, Goikolea, JM, Grotegerd, D, Gruber, O, Haarman, BCM, Haatveit, B, Hajek, T, Hallahan, B, Harris, M, Hawkins, EL, Howells, FM, Huelsmann, C, Jahanshad, N, Jorgensen, KN, Kircher, T, Kraemer, B, Krug, A, Kuplicki, R, Lagerberg, T, Lancaster, TM, Lenroot, RK, Lonning, V, Lopez-Jaramillo, C, Malt, UF, McDonald, C, McIntosh, AM, McPhilemy, G, Meer, D, Melle, I, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadic, I, Oertel, V, Oldani, L, Opel, N, Otaduy, MCG, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Radua, J, Rauer, L, Redlich, R, Repple, J, Rive, MM, Roberts, G, Ruhe, HG, Salminen, LE, Salvador, R, Sarro, S, Savitz, J, Schene, AH, Sim, K, Soeiro-de-Souza, MG, Staeblein, M, Stein, DJ, Stein, F, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Veltman, DJ, Vieta, E, Waltemate, L, Westlye, LT, Whalley, HC, Saemann, PG, Thompson, PM, Ching, CRK, Andreassen, OA, and Agartz, I
Abstract: The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.
Published: 2022

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

Author: Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Frangou, S, Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Frangou, S
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

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

Author: Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Dima, D, Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Dima, D
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

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

Author: Haukvik, U.K., Gurholt, T.P., Nerland, S., Elvsåshagen, T., Akudjedu, T.N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B.T., Benedetti, F. De, Berk, M., Bettella, F., Bøen, E., Bonnín, C.M., Brambilla, P., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Erp, T.G. van, Fatjó-Vilas, M., Foley, S.F., Förster, K., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Gruber, O., Haarman, B.C.M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E.L., Howells, F.M., Hülsmann, C., Jahanshad, N., Jørgensen, K.N., Kircher, T., Krämer, B., Krug, A., Kuplicki, R., Lagerberg, T.V., Lancaster, T.M., Lenroot, R.K., Lonning, V., López-Jaramillo, C., Malt, U.F., McDonald, C., McIntosh, A.M., McPhilemy, G., Meer, D. van der, Melle, I., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M.C.G., Overs, B.J., Pineda-Zapata, J.A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M.M., Roberts, G., Ruhe, H.G., Salminen, L.E., Salvador, R., Sarró, S., Savitz, J., Schene, A.H., Sim, K., Soeiro-de-Souza, M.G., Stäblein, M., Stein, D.J., Stein, F., Tamnes, C.K., Temmingh, H.S., Thomopoulos, S.I., Veltman, D.J., Vieta, E., Waltemate, L., Westlye, L.T., Whalley, H.C., Sämann, P.G., Thompson, P.M., Ching, C.R., Andreassen, O.A., Agartz, I., Haukvik, U.K., Gurholt, T.P., Nerland, S., Elvsåshagen, T., Akudjedu, T.N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B.T., Benedetti, F. De, Berk, M., Bettella, F., Bøen, E., Bonnín, C.M., Brambilla, P., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Erp, T.G. van, Fatjó-Vilas, M., Foley, S.F., Förster, K., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Gruber, O., Haarman, B.C.M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E.L., Howells, F.M., Hülsmann, C., Jahanshad, N., Jørgensen, K.N., Kircher, T., Krämer, B., Krug, A., Kuplicki, R., Lagerberg, T.V., Lancaster, T.M., Lenroot, R.K., Lonning, V., López-Jaramillo, C., Malt, U.F., McDonald, C., McIntosh, A.M., McPhilemy, G., Meer, D. van der, Melle, I., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M.C.G., Overs, B.J., Pineda-Zapata, J.A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M.M., Roberts, G., Ruhe, H.G., Salminen, L.E., Salvador, R., Sarró, S., Savitz, J., Schene, A.H., Sim, K., Soeiro-de-Souza, M.G., Stäblein, M., Stein, D.J., Stein, F., Tamnes, C.K., Temmingh, H.S., Thomopoulos, S.I., Veltman, D.J., Vieta, E., Waltemate, L., Westlye, L.T., Whalley, H.C., Sämann, P.G., Thompson, P.M., Ching, C.R., Andreassen, O.A., and Agartz, I.
Abstract: Contains fulltext : 252169.pdf (Publisher’s version ) (Open Access), The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.
Published: 2022

16. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author: Ching, C.R., Hibar, D.P., Gurholt, T.P., Nunes, A., Thomopoulos, S.I., Abé, C., Agartz, I., Brouwer, R.M., Cannon, D.M., Zwarte, S.M.C. de, Eyler, L.T., Favre, P., Hajek, T., Haukvik, U.K., Houenou, J., Landén, M., Lett, T.A., McDonald, C., Nabulsi, L., Patel, Y., Pauling, M.E., Paus, T., Radua, J., Soeiro-de-Souza, M.G., Tronchin, G., Haren, N.E.M. van, Vieta, E., Walter, H., Zeng, L.L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M, Baune, B.T., Bearden, C.E., Bellani, M., Benedetti, F. De, Berk, M., Bilderbeck, A.C., Blumberg, H.P., Bøen, E., Bollettini, I., Bonnin, C. Del Mar, Brambilla, P., Canales-Rodríguez, E.J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Dima, D., Duchesnay, É., Elvsåshagen, T., Fears, S.C., Frangou, S., Fullerton, J.M., Glahn, D.C., Goikolea, J.M., Green, M.J., Grotegerd, D., Gruber, O., Haarman, B.C.M., Henry, C., Howells, F.M., Ives-Deliperi, V., Jansen, Andreas, Kircher, T.T.J., Knöchel, C., Kramer, B., Lafer, B., López-Jaramillo, C., Machado-Vieira, R., MacIntosh, B.J., Melloni, E.M.T., Mitchell, P.B., Nenadic, I., Nery, F., Nugent, A.C., Oertel, V., Ophoff, R.A., Ota, M., Overs, B.J., Pham, D.L., Phillips, M.L., Pineda-Zapata, J.A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quidé, Y., Rive, M.M., Roberts, G., Ruhe, H.G., Salvador, R., Sarró, S., Satterthwaite, T.D., Schene, A.H., Sim, K., Thompson, P.M., Andreassen, O.A., Ching, C.R., Hibar, D.P., Gurholt, T.P., Nunes, A., Thomopoulos, S.I., Abé, C., Agartz, I., Brouwer, R.M., Cannon, D.M., Zwarte, S.M.C. de, Eyler, L.T., Favre, P., Hajek, T., Haukvik, U.K., Houenou, J., Landén, M., Lett, T.A., McDonald, C., Nabulsi, L., Patel, Y., Pauling, M.E., Paus, T., Radua, J., Soeiro-de-Souza, M.G., Tronchin, G., Haren, N.E.M. van, Vieta, E., Walter, H., Zeng, L.L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M, Baune, B.T., Bearden, C.E., Bellani, M., Benedetti, F. De, Berk, M., Bilderbeck, A.C., Blumberg, H.P., Bøen, E., Bollettini, I., Bonnin, C. Del Mar, Brambilla, P., Canales-Rodríguez, E.J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Dima, D., Duchesnay, É., Elvsåshagen, T., Fears, S.C., Frangou, S., Fullerton, J.M., Glahn, D.C., Goikolea, J.M., Green, M.J., Grotegerd, D., Gruber, O., Haarman, B.C.M., Henry, C., Howells, F.M., Ives-Deliperi, V., Jansen, Andreas, Kircher, T.T.J., Knöchel, C., Kramer, B., Lafer, B., López-Jaramillo, C., Machado-Vieira, R., MacIntosh, B.J., Melloni, E.M.T., Mitchell, P.B., Nenadic, I., Nery, F., Nugent, A.C., Oertel, V., Ophoff, R.A., Ota, M., Overs, B.J., Pham, D.L., Phillips, M.L., Pineda-Zapata, J.A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quidé, Y., Rive, M.M., Roberts, G., Ruhe, H.G., Salvador, R., Sarró, S., Satterthwaite, T.D., Schene, A.H., Sim, K., Thompson, P.M., and Andreassen, O.A.
Abstract: Contains fulltext : 252204.pdf (Publisher’s version ) (Open Access), MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.
Published: 2022

17. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author: Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A, Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.M., Landén, M., Landrø, N.I., Hoogman, M., Lawrie, S., Franke, B., Rooij, D. van, Buitelaar, J.K., Thompson, P., Paus, T., Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A, Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.M., Landén, M., Landrø, N.I., Hoogman, M., Lawrie, S., Franke, B., Rooij, D. van, Buitelaar, J.K., Thompson, P., and Paus, T.
Abstract: Contains fulltext : 281502.pdf (Publisher’s version ) (Closed access), BACKGROUND: Morphology 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. METHODS: Interregional 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. RESULTS: Across 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. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from t
Published: 2022

18. The Role of Educational Attainment and Brain Morphology in Major Depressive Disorder: Findings From the ENIGMA Major Depressive Disorder Consortium

Author: Whittle, S, Rakesh, D, Schmaal, L, Veltman, DJ, Thompson, PM, Singh, A, Gonul, AS, Aleman, A, Demir, AU, Krug, A, Mwangi, B, Kramer, B, Baune, BT, Stein, DJ, Grotegerd, D, Pomarol-Clotet, E, Rodriguez-Cano, E, Melloni, E, Benedetti, F, Stein, F, Grabe, HJ, Volzke, H, Gotlib, IH, Nenadic, I, Soares, JC, Repple, J, Sim, K, Brosch, K, Wittfeld, K, Berger, K, Hermesdorf, M, Portella, MJ, Sacchet, MD, Wu, M-J, Opel, N, Groenewold, NA, Gruber, O, Fuentes-Claramonte, P, Salvador, R, Goya-Maldonado, R, Sarro, S, Poletti, S, Meinert, SL, Kircher, T, Dannlowski, U, Pozzi, E, Whittle, S, Rakesh, D, Schmaal, L, Veltman, DJ, Thompson, PM, Singh, A, Gonul, AS, Aleman, A, Demir, AU, Krug, A, Mwangi, B, Kramer, B, Baune, BT, Stein, DJ, Grotegerd, D, Pomarol-Clotet, E, Rodriguez-Cano, E, Melloni, E, Benedetti, F, Stein, F, Grabe, HJ, Volzke, H, Gotlib, IH, Nenadic, I, Soares, JC, Repple, J, Sim, K, Brosch, K, Wittfeld, K, Berger, K, Hermesdorf, M, Portella, MJ, Sacchet, MD, Wu, M-J, Opel, N, Groenewold, NA, Gruber, O, Fuentes-Claramonte, P, Salvador, R, Goya-Maldonado, R, Sarro, S, Poletti, S, Meinert, SL, Kircher, T, Dannlowski, U, and Pozzi, E
Abstract: Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Published: 2022

19. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author: Patel, Y, Shin, J, Abe, C, Agartz, I, Alloza, C, Alnaes, D, Ambrogi, S, Antonucci, LA, Arango, C, Arolt, V, Auzias, G, Ayesa-Arriola, R, Banaj, N, Banaschewski, T, Bandeira, C, Basgoze, Z, Cupertino, RB, Bau, CHD, Bauer, J, Baumeister, S, Bernardoni, F, Bertolino, A, del Mar Bonnin, C, Brandeis, D, Brem, S, Bruggemann, J, Bulow, R, Bustillo, JR, Calderoni, S, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carmona, S, Carr, VJ, Catts, SV, Chenji, S, Chew, QH, Coghill, D, Connolly, CG, Conzelmann, A, Craven, AR, Crespo-Facorro, B, Cullen, K, Dahl, A, Dannlowski, U, Davey, CG, Deruelle, C, Diaz-Caneja, CM, Dohm, K, Ehrlich, S, Epstein, J, Erwin-Grabner, T, Eyler, LT, Fedor, J, Fitzgerald, J, Foran, W, Ford, JM, Fortea, L, Fuentes-Claramonte, P, Fullerton, J, Furlong, L, Gallagher, L, Gao, B, Gao, S, Goikolea, JM, Gotlib, I, Goya-Maldonado, R, Grabe, HJ, Green, M, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Haavik, J, Hahn, T, Harrison, BJ, Heindel, W, Henskens, F, Heslenfeld, DJ, Hilland, E, Hoekstra, PJ, Hohmann, S, Holz, N, Howells, FM, Ipser, JC, Jahanshad, N, Jakobi, B, Jansen, A, Janssen, J, Jonassen, R, Kaiser, A, Kaleda, V, Karantonis, J, King, JA, Kircher, T, Kochunov, P, Koopowitz, S-M, Landen, M, Landro, NI, Lawrie, S, Lebedeva, I, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Mathalon, DH, McDonald, C, McIntosh, A, Meinert, S, Michie, PT, Mitchell, P, Moreno-Alcazar, A, Mowry, B, Muratori, F, Nabulsi, L, Nenadic, I, Tuura, RO, Oosterlaan, J, Overs, B, Pantelis, C, Parellada, M, Pariente, JC, Pauli, P, Pergola, G, Piarulli, FM, Picon, F, Piras, F, Pomarol-Clotet, E, Pretus, C, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Reif, A, Retico, A, Roberts, G, Rossell, S, Rovaris, DL, Rubia, K, Sacchet, M, Salavert, J, Salvador, R, Sarro, S, Sawa, A, Schall, U, Scott, R, Selvaggi, P, Silk, T, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Stein, DJ, Steinstrater, O, Stolicyn, A, Takayanagi, Y, Tamm, L, Tavares, M, Teumer, A, Thiel, K, Thomopoulos, SI, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, Van Rheenen, T, Vazquez-Bourgon, J, Vernooij, MW, Vieta, E, Vilarroya, O, Weickert, C, Weickert, T, Westlye, LT, Whalley, H, Willinger, D, Winter, A, Wittfeld, K, Yang, TT, Yoncheva, Y, Zijlmans, JL, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, Ching, CRK, Andreassen, OA, Pozzi, E, Veltman, D, Schmaal, L, van Erp, TGM, Turner, J, Castellanos, FX, Pausova, Z, Thompson, P, Paus, T, Patel, Y, Shin, J, Abe, C, Agartz, I, Alloza, C, Alnaes, D, Ambrogi, S, Antonucci, LA, Arango, C, Arolt, V, Auzias, G, Ayesa-Arriola, R, Banaj, N, Banaschewski, T, Bandeira, C, Basgoze, Z, Cupertino, RB, Bau, CHD, Bauer, J, Baumeister, S, Bernardoni, F, Bertolino, A, del Mar Bonnin, C, Brandeis, D, Brem, S, Bruggemann, J, Bulow, R, Bustillo, JR, Calderoni, S, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carmona, S, Carr, VJ, Catts, SV, Chenji, S, Chew, QH, Coghill, D, Connolly, CG, Conzelmann, A, Craven, AR, Crespo-Facorro, B, Cullen, K, Dahl, A, Dannlowski, U, Davey, CG, Deruelle, C, Diaz-Caneja, CM, Dohm, K, Ehrlich, S, Epstein, J, Erwin-Grabner, T, Eyler, LT, Fedor, J, Fitzgerald, J, Foran, W, Ford, JM, Fortea, L, Fuentes-Claramonte, P, Fullerton, J, Furlong, L, Gallagher, L, Gao, B, Gao, S, Goikolea, JM, Gotlib, I, Goya-Maldonado, R, Grabe, HJ, Green, M, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Haavik, J, Hahn, T, Harrison, BJ, Heindel, W, Henskens, F, Heslenfeld, DJ, Hilland, E, Hoekstra, PJ, Hohmann, S, Holz, N, Howells, FM, Ipser, JC, Jahanshad, N, Jakobi, B, Jansen, A, Janssen, J, Jonassen, R, Kaiser, A, Kaleda, V, Karantonis, J, King, JA, Kircher, T, Kochunov, P, Koopowitz, S-M, Landen, M, Landro, NI, Lawrie, S, Lebedeva, I, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Mathalon, DH, McDonald, C, McIntosh, A, Meinert, S, Michie, PT, Mitchell, P, Moreno-Alcazar, A, Mowry, B, Muratori, F, Nabulsi, L, Nenadic, I, Tuura, RO, Oosterlaan, J, Overs, B, Pantelis, C, Parellada, M, Pariente, JC, Pauli, P, Pergola, G, Piarulli, FM, Picon, F, Piras, F, Pomarol-Clotet, E, Pretus, C, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Reif, A, Retico, A, Roberts, G, Rossell, S, Rovaris, DL, Rubia, K, Sacchet, M, Salavert, J, Salvador, R, Sarro, S, Sawa, A, Schall, U, Scott, R, Selvaggi, P, Silk, T, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Stein, DJ, Steinstrater, O, Stolicyn, A, Takayanagi, Y, Tamm, L, Tavares, M, Teumer, A, Thiel, K, Thomopoulos, SI, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, Van Rheenen, T, Vazquez-Bourgon, J, Vernooij, MW, Vieta, E, Vilarroya, O, Weickert, C, Weickert, T, Westlye, LT, Whalley, H, Willinger, D, Winter, A, Wittfeld, K, Yang, TT, Yoncheva, Y, Zijlmans, JL, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, Ching, CRK, Andreassen, OA, Pozzi, E, Veltman, D, Schmaal, L, van Erp, TGM, Turner, J, Castellanos, FX, Pausova, Z, Thompson, P, and Paus, T
Abstract: BACKGROUND: Morphology 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. METHODS: Interregional 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. RESULTS: Across 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. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from t
Published: 2022

20. Concurrent antiepileptic and antipsychotic use moderates lithium’s effects on regional brain volumes: a mega-analysis from the ENIGMA-Bipolar Disorder Working Group

Author: King, S., Tronchin, G., Nabulsi, L., Thomopoulos, S.I., Fontana, E., Radua, J., Sim, K., Gruber, O., Yatham, L., Dannlowski, U., Kircher, T., Nenadic, I., Stein, F., Brosch, K., Howells, F., Haarman, B.C.M., Pomarol-Clotet, E., Vieta, E., Landen, M., Cannon, D., Alnæs, D., Westlye, L.T., Jaramillo, C. López, Soeiro-de-Souza, M. Gerhardt, Berk, M., Elvsåshagen, T., Roberts, G., Mitchell, P.B., Fullerton, J.M., Green, M.J., Quidé, Y., Hermesdorf, M., Berger, K., Soares, J., Satterthwaite, T., Savitz, J., Benedetti, F., Glahn, D., Hajek, T., Kuplicki, R., Gotlib, I.H., Amoretti, S., Sacchet, M., Favre, P., Van Rheenen, T., Karantonis, J. Anthony, Furlong, L., Forte, F., Rossell, S., Goldstein, B., Kennedy, K., Canales-Rodriguez, E., Lahud, E., Mwangi, B., Rodriguez-Cano, E., Salvador, R., Wu, M.-J., Houenou, J., Rodrigue, A., Melloni, E.M.T., Sponheim, S., Urosevic, S., Demro, C., Goya-Maldonado, R., Eyler, L., Thompson, P.M., Andreassan, O.A., Ching, C.R.K., and McDonald, C.
Published: 2022
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21. Störungen der zerebralen Repräsentation des Arbeitsgedächtnisses bei Patienten mit idiopathischem Parkinson-Syndrom

Author: Binder, E, Becker, W, Gruber, O, and Kraft, E
Published: 2024
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22. What we learn about bipolar disorder from large-scale neuroimaging

Author: Christian K. Tamnes, Bartholomeus C M Haarman, Jair C. Soares, Ole A. Andreassen, Viola Oertel, Theodore D. Satterthwaite, G. Tronchin, Michael Stäblein, Bradley J. MacIntosh, Melissa Pauling, Christopher R.K. Ching, Daniel H. Wolf, Dick J. Veltman, Ingrid Agartz, Bernhard T. Baune, Salvador Sarró, Mon-Ju Wu, Scott C Fears, Eduard Vieta, Melissa J. Green, Neeltje E.M. van Haren, Yann Quidé, Erlend Bøen, Yash Patel, Igor Nenadic, Martin Alda, Lisa T. Eyler, Arnaud Pouchon, Danai Dima, Tomáš Paus, Irene Bollettini, Torbjørn Elvsåshagen, Rachel M. Brouwer, Lakshmi N. Yatham, Michael Bauer, Caterina del Mar Bonnín, C. McDonald, Udo Dannlowski, Bronwyn Overs, Edith Pomarol-Clotet, Cristian Vargas Upegui, Oliver Gruber, Henricus G. Ruhé, Márcio Gerhardt Soeiro-de-Souza, Edouard Duchesnay, Hilary P. Blumberg, Tilo Kircher, Miho Ota, Michael Berk, Christoph Abé, Andreas Jansen, Kang Sim, Heather C. Whalley, Derrek P. Hibar, Roel A. Ophoff, Georgios V Thomaidis, Henrik Walter, Sophia Frangou, Michèle Wessa, Dara M. Cannon, Cara M. Altimus, Allison C. Nugent, Rodrigo Machado-Vieira, Orwa Dandash, Marcella Bellani, Unn K. Haukvik, Philip B. Mitchell, Ling-Li Zeng, Christian Knöchel, Jose Manuel Goikolea, Sonja M C de Zwarte, Francesco Benedetti, Sara Poletti, Janice M. Fullerton, Carlos A. Zarate, Aart H. Schene, Dan J. Stein, Chantal Henry, Tristram A. Lett, Mikael Landén, Daniel L Pham, Paolo Brambilla, Silvia Alonso-Lana, Sophia I. Thomopoulos, Carlos López-Jaramillo, Tomas Hajek, Bernd Kramer, G. Delvecchio, Maria M. Rive, Lars T. Westlye, Erick J. Canales-Rodríguez, Victoria L. Ives-Deliperi, Dominik Grotegerd, Beny Lafer, Abraham Nunes, Carrie E. Bearden, Raymond Salvador, Joaquim Radua, Amy C Bilderbeck, Xavier Caseras, Paul M. Thompson, Jorge R. C. Almeida, Pauline Favre, Gloria Roberts, David C. Glahn, Dag Alnæs, Julian A Pineda-Zapata, Tiril P. Gurholt, Mircea Polosan, Josselin Houenou, Fabiano G. Nery, Leila Nabulsi, Mary L. Phillips, Fleur M. Howells, Ana M. Díaz-Zuluaga, Elisa M T Melloni, Ching, C. R. K., Hibar, D. P., Gurholt, T. P., Nunes, A., Thomopoulos, S. I., Abe, C., Agartz, I., Brouwer, R. M., Cannon, D. M., de Zwarte, S. M. C., Eyler, L. T., Favre, P., Hajek, T., Haukvik, U. K., Houenou, J., Landen, M., Lett, T. A., Mcdonald, C., Nabulsi, L., Patel, Y., Pauling, M. E., Paus, T., Radua, J., Soeiro-de-Souza, M. G., Tronchin, G., van Haren, N. E. M., Vieta, E., Walter, H., Zeng, L. -L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M., Baune, B. T., Bearden, C. E., Bellani, M., Benedetti, F., Berk, M., Bilderbeck, A. C., Blumberg, H. P., Boen, E., Bollettini, I., del Mar Bonnin, C., Brambilla, P., Canales-Rodriguez, E. J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Diaz-Zuluaga, A. M., Dima, D., Duchesnay, E., Elvsashagen, T., Fears, S. C., Frangou, S., Fullerton, J. M., Glahn, D. C., Goikolea, J. M., Green, M. J., Grotegerd, D., Gruber, O., Haarman, B. C. M., Henry, C., Howells, F. M., Ives-Deliperi, V., Jansen, A., Kircher, T. T. J., Knochel, C., Kramer, B., Lafer, B., Lopez-Jaramillo, C., Machado-Vieira, R., Macintosh, B. J., Melloni, E. M. T., Mitchell, P. B., Nenadic, I., Nery, F., Nugent, A. C., Oertel, V., Ophoff, R. A., Ota, M., Overs, B. J., Pham, D. L., Phillips, M. L., Pineda-Zapata, J. A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quide, Y., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarro, S., Satterthwaite, T. D., Schene, A. H., Sim, K., Soares, J. C., Stablein, M., Stein, D. J., Tamnes, C. K., Thomaidis, G. V., Upegui, C. V., Veltman, D. J., Wessa, M., Westlye, L. T., Whalley, H. C., Wolf, D. H., Wu, M. -J., Yatham, L. N., Zarate, C. A., Thompson, P. M., and Andreassen, O. A.
Subjects: mega-analysis, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], cortical surface area, Review Article, 0302 clinical medicine, Manic-depressive illness, Multicenter Studies as Topic, Spectrum disorder, Review Articles, bipolar disorder, Cerebral Cortex, Trastorn bipolar, neuroimaging, Radiological and Ultrasound Technology, 05 social sciences, ENIGMA, HUMAN BRAIN, Magnetic Resonance Imaging, psychiatry, 3. Good health, Neurology, Meta-analysis, Scale (social sciences), Anatomy, Psychology, Clinical risk factor, Clinical psychology, MRI, MAJOR PSYCHIATRIC-DISORDERS, Schizoaffective disorder, 050105 experimental psychology, 03 medical and health sciences, Magnetic resonance imaging, Neuroimaging, Meta-Analysis as Topic, SDG 3 - Good Health and Well-being, Imatges per ressonància magnètica, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Bipolar disorder, HIPPOCAMPAL VOLUMES, mega‐analysis, GRAY-MATTER VOLUME, SPECTRUM DISORDER, volume, DIABETES-MELLITUS, cortical thickness, COGNITIVE IMPAIRMENT, medicine.disease, Mental illness, meta-analysis, meta‐analysis, RC0321, Neurology (clinical), SCHIZOAFFECTIVE DISORDER, PSYCHOTIC FEATURES, 030217 neurology & neurosurgery
Abstract: MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large‐scale meta‐ and mega‐analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large‐scale, collaborative studies of mental illness., This review discusses the major challenges facing neuroimaging research of bipolar disorder and highlights the major accomplishments, ongoing challenges and future goals of the ENIGMA Bipolar Disorder Working Group.
Published: 2022
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23. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics throughMeta-AnalysisBipolar Disorder Working Group

Author: Sophia I. Thomopoulos, Julian A Pineda-Zapata, Ronny Redlich, Bartholomeus C M Haarman, Mathew A. Harris, Orwa Dandash, Ulrik Fredrik Malt, Lauren E. Salminen, Michael Stäblein, Theo G.M. van Erp, Gloria Roberts, Michael Berk, Jochen Bauer, Edith Pomarol-Clotet, Carlos López-Jaramillo, Dominik Grotegerd, Tomas Hajek, Paul M. Thompson, Philipp G. Sämann, Francesco Benedetti, Tilo Kircher, Brian Hallahan, Jonathan Repple, Lena Waltemate, Maria M. Rive, Heather C. Whalley, Caterina del Mar Bonnín, Oliver Gruber, Igor Nenadic, Udo Dannlowski, Henricus G. Ruhé, Raymond Salvador, Bronwyn Overs, Torbjørn Elvsåshagen, Márcio Gerhardt Soeiro-de-Souza, Ana M. Díaz-Zuluaga, Katharina Förster, Jose Manuel Goikolea, Emma L. Hawkins, Vera Lonning, Silvia Alonso-Lana, Dan J. Stein, Theophilus N. Akudjedu, Elisa M T Melloni, Dag Alnæs, Nils Opel, Martin Alda, Rayus Kuplicki, Erlend Bøen, Salvador Sarró, Unn K. Haukvik, Philip B. Mitchell, Kang Sim, Lisa Rauer, Ole A. Andreassen, Colm McDonald, Eduard Vieta, Erick J. Canales-Rodríguez, Axel Krug, Viola Oertel, Frederike Stein, Xavier Caseras, Christopher R.K. Ching, Lucio Oldani, Dara M. Cannon, Andrew M. McIntosh, Kjetil Nordbø Jørgensen, Ingrid Melle, Rhoshel K. Lenroot, Lars T. Westlye, Giuseppe Delvecchio, Dick J. Veltman, Mar Fatjó-Vilas, Trine Vik Lagerberg, Leila Nabulsi, Henk Temmingh, Carina Hülsmann, Francesco Bettella, Paolo Brambilla, Dennis van der Meer, Sonya Foley, Tiril P. Gurholt, Fleur M. Howells, Joaquim Radua, Thomas M. Lancaster, Christian K. Tamnes, Maria Cg Otaduy, Jonathan Savitz, Stener Nerland, Genevieve McPhilemy, Janice M. Fullerton, Aart H. Schene, Neda Jahanshad, Ingrid Agartz, Bernhard T. Baune, Beathe Haatveit, Bernd Krämer, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, Haukvik, U. K., Gurholt, T. P., Nerland, S., Elvsashagen, T., Akudjedu, T. N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B. T., Benedetti, F., Berk, M., Bettella, F., Boen, E., Bonnin, C. M., Brambilla, P., Canales-Rodriguez, E. J., Cannon, D. M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Diaz-Zuluaga, A. M., van Erp, T. G. M., Fatjo-Vilas, M., Foley, S. F., Forster, K., Fullerton, J. M., Goikolea, J. M., Grotegerd, D., Gruber, O., Haarman, B. C. M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E. L., Howells, F. M., Hulsmann, C., Jahanshad, N., Jorgensen, K. N., Kircher, T., Kramer, B., Krug, A., Kuplicki, R., Lagerberg, T. V., Lancaster, T. M., Lenroot, R. K., Lonning, V., Lopez-Jaramillo, C., Malt, U. F., Mcdonald, C., Mcintosh, A. M., Mcphilemy, G., van der Meer, D., Melle, I., Melloni, E. M. T., Mitchell, P. B., Nabulsi, L., Nenadic, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M. C. G., Overs, B. J., Pineda-Zapata, J. A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salminen, L. E., Salvador, R., Sarro, S., Savitz, J., Schene, A. H., Sim, K., Soeiro-de-Souza, M. G., Stablein, M., Stein, D. J., Stein, F., Tamnes, C. K., Temmingh, H. S., Thomopoulos, S. I., Veltman, D. J., Vieta, E., Waltemate, L., Westlye, L. T., Whalley, H. C., Samann, P. G., Thompson, P. M., Ching, C. R. K., Andreassen, O. A., Agartz, I., Clinical Cognitive Neuropsychiatry Research Program (CCNP), Psychiatry, Anatomy and neurosciences, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and Adult Psychiatry
Subjects: structural brain MRI, Bipolar Disorder, HALOPERIDOL, hippocampus, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], SEGMENTATION, Hippocampus, Hippocampal formation, 0302 clinical medicine, SCHIZOPHRENIA, Manic-depressive illness, psychosis, BRAIN, Research Articles, Trastorn bipolar, Radiological and Ultrasound Technology, 05 social sciences, Subiculum, ATLAS, Magnetic Resonance Imaging, Liti, 3. Good health, medicine.anatomical_structure, Neurology, Schizophrenia, lithium, Anatomy, Hippocampus (Brain), Research Article, MRI, INTERNEURONS, Psychosis, Hipocamp (Cervell), Neuroimaging, Amygdala, 050105 experimental psychology, CELL-PROLIFERATION, 03 medical and health sciences, Genetics, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Bipolar disorder, large‐scale, LITHIUM-TREATED PATIENTS, business.industry, Dentate gyrus, medicine.disease, nervous system, DENTATE GYRUS, large-scale, bipolar disorder subtype, Neurology (clinical), business, Neuroscience, 030217 neurology & neurosurgery
Abstract: The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta‐Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1‐weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed‐effects models and mega‐analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = −0.20), cornu ammonis (CA)1 (d = −0.18), CA2/3 (d = −0.11), CA4 (d = −0.19), molecular layer (d = −0.21), granule cell layer of dentate gyrus (d = −0.21), hippocampal tail (d = −0.10), subiculum (d = −0.15), presubiculum (d = −0.18), and hippocampal amygdala transition area (d = −0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non‐users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD., The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder.In the largest study of hippocampal subfields in bipolar disorder to date, from 23 sites worldwide, we report widespread reductions in nine of 12 subfields.The lack of differences between lithium users and healthy controls supports a possible protective role of lithium in bipolar disorder.
Published: 2022
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24. Genomic analysis of intracranial and subcortical brain volumes yields polygenic scores accounting for variation across ancestries.

Author: García-Marín LM, Campos AI, Diaz-Torres S, Rabinowitz JA, Ceja Z, Mitchell BL, Grasby KL, Thorp JG, Agartz I, Alhusaini S, Ames D, Amouyel P, Andreassen OA, Arfanakis K, Arias-Vasquez A, Armstrong NJ, Athanasiu L, Bastin ME, Beiser AS, Bennett DA, Bis JC, Boks MPM, Boomsma DI, Brodaty H, Brouwer RM, Buitelaar JK, Burkhardt R, Cahn W, Calhoun VD, Carmichael OT, Chakravarty M, Chen Q, Ching CRK, Cichon S, Crespo-Facorro B, Crivello F, Dale AM, Smith GD, de Geus EJC, De Jager PL, de Zubicaray GI, Debette S, DeCarli C, Depondt C, Desrivières S, Djurovic S, Ehrlich S, Erk S, Espeseth T, Fernández G, Filippi I, Fisher SE, Fleischman DA, Fletcher E, Fornage M, Forstner AJ, Francks C, Franke B, Ge T, Goldman AL, Grabe HJ, Green RC, Grimm O, Groenewold NA, Gruber O, Gudnason V, Håberg AK, Haukvik UK, Heinz A, Hibar DP, Hilal S, Himali JJ, Ho BC, Hoehn DF, Hoekstra PJ, Hofer E, Hoffmann W, Holmes AJ, Homuth G, Hosten N, Ikram MK, Ipser JC, Jack CR Jr, Jahanshad N, Jönsson EG, Kahn RS, Kanai R, Klein M, Knol MJ, Launer LJ, Lawrie SM, Hellard SL, Lee PH, Lemaître H, Li S, Liewald DCM, Lin H, Longstreth WT Jr, Lopez OL, Luciano M, Maillard P, Marquand AF, Martin NG, Martinot JL, Mather KA, Mattay VS, McMahon KL, Mecocci P, Melle I, Meyer-Lindenberg A, Mirza-Schreiber N, Milaneschi Y, Mosley TH, Mühleisen TW, Müller-Myhsok B, Maniega SM, Nauck M, Nho K, Niessen WJ, Nöthen MM, Nyquist PA, Oosterlaan J, Pandolfo M, Paus T, Pausova Z, Penninx BWJH, Pike GB, Psaty BM, Pütz B, Reppermund S, Rietschel MD, Risacher SL, Romanczuk-Seiferth N, Romero-Garcia R, Roshchupkin GV, Rotter JI, Sachdev PS, Sämann PG, Saremi A, Sargurupremraj M, Saykin AJ, Schmaal L, Schmidt H, Schmidt R, Schofield PR, Scholz M, Schumann G, Schwarz E, Shen L, Shin J, Sisodiya SM, Smith AV, Smoller JW, Soininen HS, Steen VM, Stein DJ, Stein JL, Thomopoulos SI, Toga AW, Tordesillas-Gutiérrez D, Trollor JN, Valdes-Hernandez MC, van T Ent D, van Bokhoven H, van der Meer D, van der Wee NJA, Vázquez-Bourgon J, Veltman DJ, Vernooij MW, Villringer A, Vinke LN, Völzke H, Walter H, Wardlaw JM, Weinberger DR, Weiner MW, Wen W, Westlye LT, Westman E, White T, Witte AV, Wolf C, Yang J, Zwiers MP, Ikram MA, Seshadri S, Thompson PM, Satizabal CL, Medland SE, and Rentería ME
Subjects: Humans, Female, Male, Organ Size genetics, Attention Deficit Disorder with Hyperactivity genetics, Attention Deficit Disorder with Hyperactivity pathology, Parkinson Disease genetics, Parkinson Disease pathology, Polymorphism, Single Nucleotide, Genomics methods, Adult, Genetic Predisposition to Disease, Middle Aged, White People genetics, Genome-Wide Association Study, Multifactorial Inheritance genetics, Brain pathology
Abstract: Subcortical brain structures are involved in developmental, psychiatric and neurological disorders. Here we performed genome-wide association studies meta-analyses of intracranial and nine subcortical brain volumes (brainstem, caudate nucleus, putamen, hippocampus, globus pallidus, thalamus, nucleus accumbens, amygdala and the ventral diencephalon) in 74,898 participants of European ancestry. We identified 254 independent loci associated with these brain volumes, explaining up to 35% of phenotypic variance. We observed gene expression in specific neural cell types across differentiation time points, including genes involved in intracellular signaling and brain aging-related processes. Polygenic scores for brain volumes showed predictive ability when applied to individuals of diverse ancestries. We observed causal genetic effects of brain volumes with Parkinson's disease and attention-deficit/hyperactivity disorder. Findings implicate specific gene expression patterns in brain development and genetic variants in comorbid neuropsychiatric disorders, which could point to a brain substrate and region of action for risk genes implicated in brain diseases., (© 2024. The Author(s), under exclusive licence to Springer Nature America, Inc.)
Published: 2024
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25. DNAJC13 influences responses of the extended reward system to conditioned stimuli: a genome-wide association study.

Author: Treutlein J, Einenkel KE, Krämer B, Awasthi S, and Gruber O
Abstract: Reward system dysfunction is implicated in the pathogenesis of major psychiatric disorders. We conducted a genome-wide association study (GWAS) to identify genes that influence activation strength of brain regions within the extended reward system in humans. A homogeneous sample of 214 participants was genotyped and underwent functional magnetic resonance imaging (fMRI). All subjects performed the 'desire-reason dilemma' (DRD) paradigm allowing systematic investigation of systems-level mechanisms of reward processing in humans. As a main finding, we identified the single nucleotide variant rs113408797 in the DnaJ Heat Shock Protein Family Member C13 gene [DNAJC13], alias Receptor-Mediated Endocytosis 8 [RME-8], that was associated with the activation strength of the ventral tegmental area (VTA; p = 2.50E-07) and the nucleus accumbens (NAcc; p = 5.31E-05) in response to conditioned reward stimuli. Moreover, haplotype analysis assessing the information across the entire DNAJC13 locus demonstrated an impact of a five-marker haplotype on VTA activation (p = 3.21E-07), which further corroborates a link between this gene and reward processing. The present findings provide first direct empirical evidence that genetic variation of DNAJC13 influences neural responses within the extended reward system to conditioned stimuli. Further studies are required to investigate the role of this gene in the pathogenesis and pathophysiology of neuropsychiatric disorders., (© 2024. Springer-Verlag GmbH Germany, part of Springer Nature.)
Published: 2024
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26. Multivariable prediction of functional outcome after first-episode psychosis: a crossover validation approach in EUFEST and PSYSCAN.

Author: Slot MIE, Urquijo Castro MF, Winter-van Rossum I, van Hell HH, Dwyer D, Dazzan P, Maat A, De Haan L, Crespo-Facorro B, Glenthøj BY, Lawrie SM, McDonald C, Gruber O, van Amelsvoort T, Arango C, Kircher T, Nelson B, Galderisi S, Weiser M, Sachs G, Kirschner M, Fleischhacker WW, McGuire P, Koutsouleris N, and Kahn RS
Abstract: Several multivariate prognostic models have been published to predict outcomes in patients with first episode psychosis (FEP), but it remains unclear whether those predictions generalize to independent populations. Using a subset of demographic and clinical baseline predictors, we aimed to develop and externally validate different models predicting functional outcome after a FEP in the context of a schizophrenia-spectrum disorder (FES), based on a previously published cross-validation and machine learning pipeline. A crossover validation approach was adopted in two large, international cohorts (EUFEST, n = 338, and the PSYSCAN FES cohort, n = 226). Scores on the Global Assessment of Functioning scale (GAF) at 12 month follow-up were dichotomized to differentiate between poor (GAF current < 65) and good outcome (GAF current ≥ 65). Pooled non-linear support vector machine (SVM) classifiers trained on the separate cohorts identified patients with a poor outcome with cross-validated balanced accuracies (BAC) of 65-66%, but BAC dropped substantially when the models were applied to patients from a different FES cohort (BAC = 50-56%). A leave-site-out analysis on the merged sample yielded better performance (BAC = 72%), highlighting the effect of combining data from different study designs to overcome calibration issues and improve model transportability. In conclusion, our results indicate that validation of prediction models in an independent sample is essential in assessing the true value of the model. Future external validation studies, as well as attempts to harmonize data collection across studies, are recommended., (© 2024. The Author(s).)
Published: 2024
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27. Association of Unc-51-like Kinase 4 ( ULK4 ) with the reactivity of the extended reward system in response to conditioned stimuli.

Author: Treutlein J, Löhlein S, Einenkel KE, Picotin R, Diekhof EK, and Gruber O
Subjects: Adult, Female, Humans, Male, Middle Aged, Young Adult, Brain diagnostic imaging, Mental Disorders genetics, Mental Disorders physiopathology, Nucleus Accumbens diagnostic imaging, Polymorphism, Single Nucleotide, Ventral Tegmental Area diagnostic imaging, Magnetic Resonance Imaging, Protein Serine-Threonine Kinases genetics, Reward
Abstract: Objectives: ULK4 is an established candidate gene for mental disorders and antipsychotic treatment response. We investigated the association of functional genetic variation at the ULK4 locus with the human extended dopaminergic reward system using fMRI during the performance of a well-established reward paradigm., Methods: Two hundred and thirty-four patients were included in this study. Association of genetic variation in the ULK4 gene with reward system functioning were determined using the Desire-Reason-Dilemma (DRD) paradigm which allows to assess brain activation in response to conditioned reward stimuli., Results: Variant prioritisation revealed the strongest functional signatures for the ULK4 variant rs17215589, coding for amino acid exchange Ala715Thr. For rs17215589 minor allele carriers, we detected increased activation responses to conditioned reward stimuli in the ventral tegmental area, nucleus accumbens and several cortical brain regions of the extended reward system., Conclusions: Our findings provide further evidence in humans that genetic variation in ULK4 may increase the vulnerability to mental disorders, by modulating the extended reward system function. Future studies are needed to confirm the modulation of the extended reward system by ULK4 and to specify the role of this mechanism in the pathogenesis of psychiatric disorders.
Published: 2024
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28. The German research consortium for the study of bipolar disorder (BipoLife): a quality assurance protocol for MR neuroimaging data.

Author: Vogelbacher C, Sommer J, Bopp MHA, Falkenberg I, Ritter PS, Bermpohl F, Attar CH, Einenkel KE, Gruber O, Juckel G, Flasbeck V, Hautzinger M, Pfennig A, Matura S, Reif A, Grotegerd D, Dannlowski U, Kircher T, Bauer M, and Jansen A
Abstract: Background: The German multicenter research consortium BipoLife aims to investigate the mechanisms underlying bipolar disorders. It focuses in particular on people at high risk of developing the disorder and young patients in the early stages of the disease. Functional and structural magnetic resonance imaging (MRI) data was collected in all participating centers. The collection of neuroimaging data in a longitudinal, multicenter study requires the implementation of a comprehensive quality assurance (QA) protocol. Here, we outline this protocol and illustrate its application within the BipoLife consortium., Methods: The QA protocol consisted of (1) a training of participating research staff, (2) regular phantom measurements to evaluate the MR scanner performance and its temporal stability across the course of the study, and (3) the assessment of the quality of human MRI data by evaluating a variety of image metrics (e.g., signal-to-noise ratio, ghosting level). In this article, we will provide an overview on these QA procedures and show exemplarily the influence of its application on the results of standard neuroimaging analysis pipelines., Discussion: The QA protocol helped to characterize the various MR scanners, to record their performance over the course of the study and to detect possible malfunctions at an early stage. It also assessed the quality of the human MRI data systematically to characterize its influence on various analyses. Furthermore, by setting up and publishing this protocol, we define standards that must be considered when analyzing data from the BipoLife consortium. It further promotes a systematic evaluation of data quality and a definition of subject inclusion criteria. In the long term, it will help to increase the chance of achieving clinically relevant results., (© 2024. The Author(s).)
Published: 2024
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29. Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Author: Yu Y, Cui HQ, Haas SS, New F, Sanford N, Yu K, Zhan D, Yang G, Gao JH, Wei D, Qiu J, Banaj N, Boomsma DI, Breier A, Brodaty H, Buckner RL, Buitelaar JK, Cannon DM, Caseras X, Clark VP, Conrod PJ, Crivello F, Crone EA, Dannlowski U, Davey CG, de Haan L, de Zubicaray GI, Di Giorgio A, Fisch L, Fisher SE, Franke B, Glahn DC, Grotegerd D, Gruber O, Gur RE, Gur RC, Hahn T, Harrison BJ, Hatton S, Hickie IB, Hulshoff Pol HE, Jamieson AJ, Jernigan TL, Jiang J, Kalnin AJ, Kang S, Kochan NA, Kraus A, Lagopoulos J, Lazaro L, McDonald BC, McDonald C, McMahon KL, Mwangi B, Piras F, Rodriguez-Cruces R, Royer J, Sachdev PS, Satterthwaite TD, Saykin AJ, Schumann G, Sevaggi P, Smoller JW, Soares JC, Spalletta G, Tamnes CK, Trollor JN, Van't Ent D, Vecchio D, Walter H, Wang Y, Weber B, Wen W, Wierenga LM, Williams SCR, Wu MJ, Zunta-Soares GB, Bernhardt B, Thompson P, Frangou S, and Ge R
Subjects: Humans, Adolescent, Female, Aged, Adult, Child, Young Adult, Male, Aged, 80 and over, Child, Preschool, Middle Aged, Neuroimaging methods, Neuroimaging standards, Sample Size, Brain diagnostic imaging, Brain anatomy & histology, Brain growth & development, Aging physiology, Magnetic Resonance Imaging methods
Abstract: Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics., (© 2024 The Author(s). Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2024
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30. Task-induced deactivation dysfunction during reward processing is associated with low self-esteem in a possible subtype of major depression.

Author: Jüllig AK, Hebib S, Metzker H, Gruber E, and Gruber O
Subjects: Humans, Male, Female, Adult, Middle Aged, Ventral Striatum physiopathology, Ventral Striatum diagnostic imaging, Depressive Disorder, Major physiopathology, Depressive Disorder, Major diagnostic imaging, Self Concept, Reward, Magnetic Resonance Imaging, Gyrus Cinguli physiopathology, Gyrus Cinguli diagnostic imaging
Abstract: Introduction: Low self-esteem is a frequent symptom in major depressive disorder (MDD). This functional magnetic resonance imaging study investigated whether MDD patients with low self-esteem show a distinct neural pathophysiology. Previous studies linked low self-esteem to reduced task-induced deactivation of the pregenual anterior cingulate cortex (pgACC) as a part of the default mode network, and to reduced connectivity between pgACC and reward system. Goya-Maldonado et al. identified an MDD subtype with pgACC and ventral striatal overactivations during reward processing. We hypothesized that this subtype might be characterized by low self-esteem., Methods: Eighty-three MDD patients performed the desire-reason dilemma task and completed the Rosenberg Self-Esteem Scale (RSES). Brain activity during bottom-up reward processing was regressed upon the RSES scores, controlling for depression severity measured by the Montgomery-Åsberg Depression Rating Scale. To corroborate the findings, we compared self-esteem scores between patient subgroups with impaired task-induced deactivation (n = 31) and with preserved task-induced deactivation (n = 31) of the pgACC., Results: Consistent with our a priori hypothesis, activity in a bilateral fronto-striatal network including pgACC and ventral striatum correlated negatively with RSES scores, also when controlling for depression severity. In the additional analysis, patients with impaired task-induced pgACC deactivation showed lower self-esteem (t (52.82) = -2.27; p = .027, d = 0.58) compared to those with preserved task-induced pgACC deactivation., Conclusions: We conclude that low self-esteem in MDD patients is linked to a task-induced deactivation dysfunction of the pgACC. Our findings suggest that a previously described possible subtype of MDD with pgACC and ventral striatal overactivations during reward processing is clinically characterized by low self-esteem., (© 2024 The Author(s). Brain and Behavior published by Wiley Periodicals LLC.)
Published: 2024
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31. A naturalistic cohort study of first-episode schizophrenia spectrum disorder: A description of the early phase of illness in the PSYSCAN cohort.

Author: Slot MIE, van Hell HH, Rossum IW, Dazzan P, Maat A, de Haan L, Crespo-Facorro B, Glenthøj B, Lawrie SM, McDonald C, Gruber O, van Amelsvoort T, Arango C, Kircher T, Nelson B, Galderisi S, Weiser M, Sachs G, Maatz A, Bressan RA, Kwon JS, Mizrahi R, McGuire P, and Kahn RS
Subjects: Humans, Male, Young Adult, Adult, Female, Cohort Studies, Prospective Studies, Treatment Outcome, Follow-Up Studies, Schizophrenia epidemiology, Schizophrenia therapy, Schizophrenia diagnosis, Psychotic Disorders epidemiology, Psychotic Disorders therapy, Psychotic Disorders diagnosis, Antipsychotic Agents therapeutic use
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., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Dr. Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. Dr. Glenthøj has been the leader of a Lundbeck Foundation Centre of Excellence for Clinical Intervention and Neuropsychiatric Schizophrenia Research (CINS) (January 2009 – December 2021), which was partially financed by an independent grant from the Lundbeck Foundation based on international review and partially financed by the Mental Health Services in the Capital Region of Denmark, the University of Copenhagen, and other foundations. All grants are the property of the Mental Health Services in the Capital Region of Denmark and administrated by them. She has no other conflicts to disclose. Dr. Sachs has been a consultant to or has received honoraria from Angelini, Janssen Cilag, Lundbeck, Mylan, Recordati. The other authors declare no competing interests., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Published: 2024
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32. PsyCog: A computerised mini battery for assessing cognition in psychosis.

Author: Gifford G, Cullen AE, Vieira S, Searle A, McCutcheon RA, Modinos G, Stone WS, Hird E, Barnett J, van Hell HH, Catalan A, Millgate E, Taptiklis N, Cormack F, Slot ME, Dazzan P, Maat A, de Haan L, Facorro BC, Glenthøj B, Lawrie SM, McDonald C, Gruber O, van Amelsvoort T, Arango C, Kircher T, Nelson B, Galderisi S, Bressan RA, Kwon JS, Weiser M, Mizrahi R, Sachs G, Kirschner M, Reichenberg A, Kahn R, and McGuire P
Abstract: Despite the functional impact of cognitive deficit in people with psychosis, objective cognitive assessment is not typically part of routine clinical care. This is partly due to the length of traditional assessments and the need for a highly trained administrator. Brief, automated computerised assessments could help to address this issue. We present data from an evaluation of PsyCog, a computerised, non-verbal, mini battery of cognitive tests. Healthy Control (HC) ( N = 135), Clinical High Risk (CHR) ( N = 233), and First Episode Psychosis (FEP) ( N = 301) participants from a multi-centre prospective study were assessed at baseline, 6 months, and 12 months. PsyCog was used to assess cognitive performance at baseline and at up to two follow-up timepoints. Mean total testing time was 35.95 min (SD = 2.87). Relative to HCs, effect sizes of performance impairments were medium to large in FEP patients (composite score G = 1.21, subtest range = 0.52-0.88) and small to medium in CHR patients (composite score G = 0.59, subtest range = 0.18-0.49). Site effects were minimal, and test-retest reliability of the PsyCog composite was good (ICC = 0.82-0.89), though some practice effects and differences in data completion between groups were found. The present implementation of PsyCog shows it to be a useful tool for assessing cognitive function in people with psychosis. Computerised cognitive assessments have the potential to facilitate the evaluation of cognition in psychosis in both research and in clinical care, though caution should still be taken in terms of implementation and study design., Competing Interests: The following conflicts of interest are declared: Robert A. McCutcheon has received speaker/consultancy fees from Karuna, Janssen, Boehringer Ingelheim, and Otsuka, and co-directs a company that designs digital resources to support treatment of mental illness. Gemma Modinos has received consultancy fees from Boehringer Ingelheim for work unrelated to this study. Silvana Galderisi received advisory board/consultant fees, or honoraria/expenses from the following drug companies: Angelini, Boehringer Ingelheim, Gedeon Richter-Recordati, Innova Pharma-Recordati Group, Janssen, Lundbeck, Otsuka, Recordati Pharmaceuticals, Rovi Pharma and Sunovion Pharmaceuticals outside the submitted work., (© 2024 Published by Elsevier Inc.)
Published: 2024
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33. Normative modelling of brain morphometry across the lifespan with CentileBrain: algorithm benchmarking and model optimisation.

Author: Ge R, Yu Y, Qi YX, Fan YN, Chen S, Gao C, Haas SS, New F, Boomsma DI, Brodaty H, Brouwer RM, Buckner R, Caseras X, Crivello F, Crone EA, Erk S, Fisher SE, Franke B, Glahn DC, Dannlowski U, Grotegerd D, Gruber O, Hulshoff Pol HE, Schumann G, Tamnes CK, Walter H, Wierenga LM, Jahanshad N, Thompson PM, and Frangou S
Subjects: Humans, Male, Female, Brain diagnostic imaging, Models, Statistical, Algorithms, Longevity, Benchmarking
Abstract: The value of normative models in research and clinical practice relies on their robustness and a systematic comparison of different modelling algorithms and parameters; however, this has not been done to date. We aimed to identify the optimal approach for normative modelling of brain morphometric data through systematic empirical benchmarking, by quantifying the accuracy of different algorithms and identifying parameters that optimised model performance. We developed this framework with regional morphometric data from 37 407 healthy individuals (53% female and 47% male; aged 3-90 years) from 87 datasets from Europe, Australia, the USA, South Africa, and east Asia following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The multivariate fractional polynomial regression (MFPR) emerged as the preferred algorithm, optimised with non-linear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3000 study participants. This model can inform about the biological and behavioural implications of deviations from typical age-related neuroanatomical changes and support future study designs. The model and scripts described here are freely available through CentileBrain., Competing Interests: Declaration of interests SSH is supported by the US National Institutes of Health (NIH)'s National Institute of Mental Health (T32MH122394) and received a travel award from the Society of Biological Psychiatry to attend the annual meeting in 2023. HB declares an institutional grant from the Australian National Health and Medical Research Council; has received compensation for being on an advisory board or a consultant to Biogen, Eisai, Eli Lilly, Roche, and Skin2Neuron; payment for being on the Cranbrook Care Medical Advisory Board; and honoraria for being on the Montefiore Homes Clinical Advisory Board. RMB and HEHP declare partial funding through the Geestkracht programme of the Dutch Health Research Council (Zon-Mw, grant No 10–000–1001) and matching funds from participating pharmaceutical companies (ie, Lundbeck, AstraZeneca, Eli Lilly, and Janssen Cilag), universities (Academic Psychiatric Centre of the Academic Medical Center, University Medical Center Groningen, Maastricht University Medical Centre, and University Medical Center Utrecht), and mental health care organisations (GGZ Ingeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord Holland Noord, Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht, Parnassia psycho-medical center The Hague, GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh voor Geestelijke Gezondheid, Mondriaan, Virenze riagg, Zuyderland GGZ, MET GGZ, Universitair Centrum Sint-Jozef Kortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem, Altrecht, and GGZ Centraal and Delta); and received funding from Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO 51·02·061 to HEHP, NWO 51·02·062 to DIB, NWO–NIHC Programs of excellence 433–09–220 to HEHP, NWO-MagW 480–04–004 to DIB, and NWO/SPI 56–464–14192 to DIB), FP7 Ideas: European Research Council (ERC-230374 to DIB), and Universiteit Utrecht (High Potential Grant to HEHP). RB declares funding by the NIH's National Institute on Aging (R01AG067420); received compensation for being on the scientific advisory board from Alkermes and Cognito Therapeutics with no conflict to the present work; received honoraria from academic institutions for talks (all under $1000) and $1000 for speaking at a Massachusetts General Hospital and Harvard Medical School course; received travel fees for services to attend the annual meeting from the Simons Foundation; serves as a Director on the Simons Foundation Collaborative Initiative on Aging; is a paid scientific advisory board member for philanthropic grants for The Foundation for OCD Research and the Klarman Family Foundation. BF has received educational speaking fees from Medice. DG reports funding from the NIH. UD is funded through the German Research Foundation (DFG; DA 1151/9–1, DA 1151/10–1, DA 1151/11–1). GS declares funding from the European Commission, DFG, and National Science Foundation of China. CKT has received grants from the Research Council of Norway and the Norwegian Regional Health Authority, unrelated to the current work. HW reports funding from the German Research Foundation (WA 1539/11–1). NJ reports funding from the NIH and compensation from the International Neuropsychological Society. PMT declares a grant from the NIH and travel funded by NIH grants. All other authors declare no competing interests., (Copyright © 2024 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)
Published: 2024
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34. Lithium response in bipolar disorder is associated with focal adhesion and PI3K-Akt networks: a multi-omics replication study.

Author: Ou AH, Rosenthal SB, Adli M, Akiyama K, Akula N, Alda M, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Bauer M, Baune BT, Bellivier F, Benabarre A, Bengesser S, Bhattacharjee AK, Biernacka JM, Cervantes P, Chen GB, Chen HC, Chillotti C, Cichon S, Clark SR, Colom F, Cousins DA, Cruceanu C, Czerski PM, Dantas CR, Dayer A, Del Zompo M, Degenhardt F, DePaulo JR, Étain B, Falkai P, Fellendorf FT, Ferensztajn-Rochowiak E, Forstner AJ, Frisén L, Frye MA, Fullerton JM, Gard S, Garnham JS, Goes FS, Grigoroiu-Serbanescu M, Grof P, Gruber O, Hashimoto R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hofmann A, Hou L, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kittel-Schneider S, König B, Kuo PH, Kusumi I, Lackner N, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband SG, Jaramillo CAL, MacQueen G, Maj M, Manchia M, Marie-Claire C, Martinsson L, Mattheisen M, McCarthy MJ, McElroy SL, McMahon FJ, Mitchell PB, Mitjans M, Mondimore FM, Monteleone P, Nievergelt CM, Nöthen MM, Novák T, Ösby U, Ozaki N, Papiol S, Perlis RH, Pisanu C, Potash JB, Pfennig A, Reich-Erkelenz D, Reif A, Reininghaus EZ, Rietschel M, Rouleau GA, Rybakowski JK, Schalling M, Schofield PR, Schubert KO, Schulze TG, Schweizer BW, Seemüller F, Severino G, Shekhtman T, Shilling PD, Shimoda K, Simhandl C, Slaney CM, Squassina A, Stamm T, Stopkova P, Tighe SK, Tortorella A, Turecki G, Vieta E, Volkert J, Witt S, Wray NR, Wright A, Young LT, Zandi PP, and Kelsoe JR
Subjects: Humans, Proto-Oncogene Proteins c-akt genetics, Phosphatidylinositol 3-Kinases genetics, Genome-Wide Association Study, Multiomics, Focal Adhesions, Lithium pharmacology, Lithium therapeutic use, Bipolar Disorder drug therapy, Bipolar Disorder genetics
Abstract: Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD., (© 2024. The Author(s).)
Published: 2024
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35. Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

Author: Ge R, Yu Y, Qi YX, Fan YV, Chen S, Gao C, Haas SS, Modabbernia A, New F, Agartz I, Asherson P, Ayesa-Arriola R, Banaj N, Banaschewski T, Baumeister S, Bertolino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buckner R, Buitelaar JK, Cannon DM, Caseras X, Cervenka S, Conrod PJ, Crespo-Facorro B, Crivello F, Crone EA, de Haan L, de Zubicaray GI, Di Giorgio A, Erk S, Fisher SE, Franke B, Frodl T, Glahn DC, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Harrison BJ, Hatton SN, Hickie I, Howells FM, Pol HEH, Huyser C, Jernigan TL, Jiang J, Joska JA, Kahn RS, Kalnin AJ, Kochan NA, Koops S, Kuntsi J, Lagopoulos J, Lazaro L, Lebedeva IS, Lochner C, Martin NG, Mazoyer B, McDonald BC, McDonald C, McMahon KL, Nakao T, Nyberg L, Piras F, Portella MJ, Qiu J, Roffman JL, Sachdev PS, Sanford N, Satterthwaite TD, Saykin AJ, Schumann G, Sellgren CM, Sim K, Smoller JW, Soares J, Sommer IE, Spalletta G, Stein DJ, Tamnes CK, Thomopolous SI, Tomyshev AS, Tordesillas-Gutiérrez D, Trollor JN, van 't Ent D, van den Heuvel OA, van Erp TG, van Haren NE, Vecchio D, Veltman DJ, Walter H, Wang Y, Weber B, Wei D, Wen W, Westlye LT, Wierenga LM, Williams SC, Wright MJ, Medland S, Wu MJ, Yu K, Jahanshad N, Thompson PM, and Frangou S
Abstract: We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/)., Competing Interests: Declaration of interests SSH is supported by NIH National Institute of Mental Health (T32MH122394), and received a travel award from the Society of Biological Psychiatry to attend the annual meeting in 2023. HB declares an institutional grant from the National Health and Medical Research Council; has received compensation for being on an advisory board or a consultant to Biogen, Eisai, Eli Lilly, Roche, and Skin2Neuron; payment for being on the Cranbrook Care Medical Advisory Board, and honoraria for being on the Montefiore Homes Clinical Advisory Board. RMB and HEHP declare partial funding through the Geestkracht programme of the Dutch Health Research Council (Zon-Mw, grant No 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly, Janssen Cilag) and universities and mental health care organizations (Amsterdam: Academic Psychiatric Centre of the Academic Medical Center and the mental health institutions: GGZ Ingeest, Arkin, Dijk en Duin, GGZ Rivierduinen, Erasmus Medical Centre, GGZ Noord Holland Noord. Groningen: University Medical Center Groningen and the mental health institutions: Lentis, GGZ Friesland, GGZ Drenthe, Dimence, Mediant, GGNet Warnsveld, Yulius Dordrecht and Parnassia psycho-medical center The Hague. Maastricht: Maastricht University Medical Centre and the mental health institutions: GGzE, GGZ Breburg, GGZ Oost-Brabant, Vincent van Gogh voor Geestelijke Gezondheid, Mondriaan, Virenze riagg, Zuyderland GGZ, MET ggz, Universitair Centrum Sint-Jozef Kortenberg, CAPRI University of Antwerp, PC Ziekeren Sint-Truiden, PZ Sancta Maria Sint-Truiden, GGZ Overpelt, OPZ Rekem. Utrecht: University Medical Center Utrecht and the mental health institutions Altrecht, GGZ Centraal and Delta), Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO 51.02.061 to H.H., NWO 51.02.062 to D. B., NWO–NIHC Programs of excellence 433-09-220 to H.H., NWO-MagW 480-04-004 to D. B., and NWO/SPI 56-464-14192 to D.B.); FP7 Ideas: European Research Council (ERC-230374 to D. B.); and Universiteit Utrecht (High Potential Grant to H. H.). RB declares funding by NIH National Institute on Aging (R01AG067420); compensation for being on the scientific advisory board from Alkermes and Cognito Therapeutics with no conflict to the present work; honoraria from academic institutions for talks all under $1000 and $1000 for speaking at MGH/HMS course; travel fees for services to attend the annual meeting from the Simons Foundation; serves as a Director on the Simons Foundation collaborative initiative on aging (SCPAB); is a paid scientific advisory board member for philanthropic grants for The Foundation for OCD Research and the Klarman Family Foundation. BF has received educational speaking fees from Medice. DG reports funding from the NIH. UD is funded through the German Research Foundation (DFG; DA 1151/9- 1, DA 1151/10- 1, DA 1151/11- 1). GS declares funding from the European Commission, DFG, and NSFC. CKT has received grants from the Research Council of Norway and the Norwegian Regional Health Authority, unrelated to the current work. HW reports funding from the German Research Foundation (WA 1539/11-1). NJ reports funding from the NIH and compensation from the International Neuropsychological Society. PT declares a grant from the NIH and travel funded by NIH grants. All other authors declare no competing interests.
Published: 2023
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36. Lithium Response in Bipolar Disorder is Associated with Focal Adhesion and PI3K-Akt Networks: A Multi-omics Replication Study.

Author: Kelsoe J, Ou A, Rosenthal S, Adli M, Akiyama K, Akula N, Alda M, Amare AT, Ardau R, Arias B, Aubry JM, Backlund L, Banzato C, Bauer M, Baune B, Bellivier F, Benabarre A, Bengesser S, Abesh B, Biernacka J, Bui E, Cervantes P, Chen GB, Chen HC, Chillotti C, Cichon S, Clark S, Colom F, Cousins D, Cruceanu C, Czerski P, Dantas C, Dayer A, Degenhardt F, DePaulo JR, Etain B, Falkai P, Fellendorf F, Ferensztajn-Rochowiak E, Forstner AJ, Frisen L, Frye M, Fullerton J, Gard S, Garnham J, Goes F, Grigoroiu-Serbanescu M, Grof P, Gruber O, Hashimoto R, Hauser J, Heilbronner U, Herms S, Hoffmann P, Hofmann A, Hou L, Jamain S, Jiménez E, Kahn JP, Kassem L, Kato T, Kittel-Schneider S, König B, Kuo PH, Kusumi I, Dalkner N, Laje G, Landén M, Lavebratt C, Leboyer M, Leckband S, Jaramillo CL, MacQueen G, Maj M, Manchia M, Marie-Claire C, Martinsson L, Mattheisen M, McCarthy M, McElroy S, McMahon F, Mitchell P, Mitjans M, Mondimore F, Monteleone P, Nievergelt C, Nöthen M, Novak T, Osby U, Ozaki N, Papiol S, Perlis R, Pfennig A, Potash J, Reich-Erkelenz D, Reif A, Reininghaus E, Rietschel M, Rouleau G, Rybakowski JK, Schalling M, Schofield P, Schubert KO, Schulze T, Schweizer B, Seemüller F, Severino G, Shekhtman T, Shilling P, Shimoda K, Simhandl C, Slaney C, Squassina A, Stamm T, Stopkova P, Tighe S, Tortorella A, Turecki G, Vieta E, Volkert J, Witt S, Wray N, Wright A, Young T, Zandi P, and Zompo MD
Abstract: Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2,039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD., Competing Interests: MAd has received a grant from Servier, speaker’s fees from Servier, Lundbeck, Aristo, Parexel, Gilead, ViiV, Deutsche Bank, MSD, and MyTomorrows, plus a non-financial support from Lundbeck. KA has received speaker’s fees from Taisho Toyama Pharmaceutical. MAl is funded by a grant of the Canadian Institutes of Health Research. MB has received speaker’s fees from AstraZeneca, Pfizer, Lilly, Lundbeck, GlaxoSmithKline, Servier, and Ferrer Internacional. BÉ received non-financial support from Labex Biopsy and Fondation Fondamental. RH received grants and speaker honoraria from Dainippon Sumitomo Pharma and Novartis plus speaker honoraria from Eli Lilly Japan, GlaxoSmithKline, Hisamitsu Pharmaceutical, Janssen Pharmaceutical, Nippon Zoki Pharmaceutical, Otsuka Pharmaceutical, Astellas Pharma, Pfizer, and the Yoshitomiyakuhin Corporation. TK received a grant from Takeda Pharmaceutical and fees from Kyowa Hakko Kirin, Eli Lilly Japan, Otsuka Pharmaceutical, GlaxoSmithKline, Taisho Toyama Pharmaceutical, Dainippon Sumitomo Pharma, Meiji Seika Pharma, PfizerJapan, Mochida Pharmaceutical, Shionogi & Co, Janssen Pharmaceutical, Yoshitomiyakuhin Corporation, Agilent Technologies, Astellas Pharma, and Wako Pure Chemical Industries. IK received grants and fees from Dainippon Sumitomo Pharma, Eisai, Eli Lilly, GlaxoSmithKline, Kyowa Hakko Kirin, Meiji Seika Pharma, MSD, Novartis, Otsuka, Ono Pharmaceutical, Pfizer, Tanabe Mitsubishi Pharma, Takeda Pharmaceutical, Shionogi, and Yoshitomi Pharmaceutical; he received grants from AbbVie GK, Asahi Kasei Pharma, Boehringer Ingelheim, Chugai Pharmaceutical, and Daiichi Sankyo and fees from Astellas Pharma and Janssen Pharmaceutical. MJM served as unpaid consultant for Pathway Genomic (San Diego, USA). SLM received a grant and fees from Naurex and Shire, further grants from Alkermes, Cephalon, Forest, Marriott Foundation, Orexigen Therapeutics, and Takeda Pharmaceutical, he further has served on the advisory boards for Bracket, Hoffmann-La Roche, MedAvante, Sunovion and received fees from Novo Nordisk. RHP received personal fees from RID Ventures, Genomind LLC, Healthrageous, P zer, Perfect Health, Proteus, and Psybrain. PRS received a grant from NHMRC. TGS received a grant and fees from Roche Pharmaceuticals. TSt received personal fees from Servier, Lundbeck, and Bristol-Myers Squibb. MM has received grants from Lundbeck and Angelini. EV has received grants and served as consultant, advisor or CME speaker for the following entities: AB-Biotics, AbbVie, Adamed, Angelini, Biogen, Biohaven, Boehringer-Ingelheim, Celon Pharma, Compass, Dainippon Sumitomo Pharma, Ethypharm, Ferrer, Gedeon Richter, GH Research, Glaxo-Smith Kline, HMNC, Idorsia, Janssen, Lundbeck, Medincell, Merck, Novartis, Orion Corporation, Organon, Otsuka, Roche, Rovi, Sage, Sanofi-Aventis, Sunovion, Takeda, and Viatris, outside the submitted work. SRC has participated in advisory and educational boards and received speaker’s fees from Janssen-Cilag, Lundbeck, Otsuka, and Servier; research funding from Janssen-Cilag, Lundbeck, Otsuka, and Gilead; and data sharing from Viatris Australia. ML has received lecture honoraria from Lundbeck pharmaceuticals. All above listed interests are outside of the submitted work. All other authors declare no competing interests.
Published: 2023
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37. Cortical morphology in patients with the deficit and non-deficit syndrome of schizophrenia: a worldwide meta- and mega-analyses.

Author: Banaj N, Vecchio D, Piras F, De Rossi P, Bustillo J, Ciufolini S, Dazzan P, Di Forti M, Dickie EW, Ford JM, Fuentes-Claramonte P, Gruber O, Guerrero-Pedraza A, Hamilton HK, Howells FM, Kraemer B, Lawrie SM, Mathalon DH, Murray R, Pomarol-Clotet E, Potkin SG, Preda A, Radua J, Richter A, Salvador R, Sawa A, Scheffler F, Sim K, Spaniel F, Stein DJ, Temmingh HS, Thomopoulos SI, Tomecek D, Uhlmann A, Voineskos A, Yang K, Jahanshad N, Thompson PM, Van Erp TGM, Turner JA, Spalletta G, and Piras F
Subjects: Humans, Magnetic Resonance Imaging, Neuroimaging, Parietal Lobe, Syndrome, Cerebral Cortex diagnostic imaging, Schizophrenia genetics
Abstract: Converging evidence suggests that schizophrenia (SZ) with primary, enduring negative symptoms (i.e., Deficit SZ (DSZ)) represents a distinct entity within the SZ spectrum while the neurobiological underpinnings remain undetermined. In the largest dataset of DSZ and Non-Deficit (NDSZ), we conducted a meta-analysis of data from 1560 individuals (168 DSZ, 373 NDSZ, 1019 Healthy Controls (HC)) and a mega-analysis of a subsampled data from 944 individuals (115 DSZ, 254 NDSZ, 575 HC) collected across 9 worldwide research centers of the ENIGMA SZ Working Group (8 in the mega-analysis), to clarify whether they differ in terms of cortical morphology. In the meta-analysis, sites computed effect sizes for differences in cortical thickness and surface area between SZ and control groups using a harmonized pipeline. In the mega-analysis, cortical values of individuals with schizophrenia and control participants were analyzed across sites using mixed-model ANCOVAs. The meta-analysis of cortical thickness showed a converging pattern of widespread thinner cortex in fronto-parietal regions of the left hemisphere in both DSZ and NDSZ, when compared to HC. However, DSZ have more pronounced thickness abnormalities than NDSZ, mostly involving the right fronto-parietal cortices. As for surface area, NDSZ showed differences in fronto-parietal-temporo-occipital cortices as compared to HC, and in temporo-occipital cortices as compared to DSZ. Although DSZ and NDSZ show widespread overlapping regions of thinner cortex as compared to HC, cortical thinning seems to better typify DSZ, being more extensive and bilateral, while surface area alterations are more evident in NDSZ. Our findings demonstrate for the first time that DSZ and NDSZ are characterized by different neuroimaging phenotypes, supporting a nosological distinction between DSZ and NDSZ and point toward the separate disease hypothesis., (© 2023. The Author(s).)
Published: 2023
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38. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium.

Author: Schijven D, Postema MC, Fukunaga M, Matsumoto J, Miura K, de Zwarte SMC, van Haren NEM, Cahn W, Hulshoff Pol HE, Kahn RS, Ayesa-Arriola R, Ortiz-García de la Foz V, Tordesillas-Gutierrez D, Vázquez-Bourgon J, Crespo-Facorro B, Alnæs D, Dahl A, Westlye LT, Agartz I, Andreassen OA, Jönsson EG, Kochunov P, Bruggemann JM, Catts SV, Michie PT, Mowry BJ, Quidé Y, Rasser PE, Schall U, Scott RJ, Carr VJ, Green MJ, Henskens FA, Loughland CM, Pantelis C, Weickert CS, Weickert TW, de Haan L, Brosch K, Pfarr JK, Ringwald KG, Stein F, Jansen A, Kircher TTJ, Nenadić I, Krämer B, Gruber O, Satterthwaite TD, Bustillo J, Mathalon DH, Preda A, Calhoun VD, Ford JM, Potkin SG, Chen J, Tan Y, Wang Z, Xiang H, Fan F, Bernardoni F, Ehrlich S, Fuentes-Claramonte P, Garcia-Leon MA, Guerrero-Pedraza A, Salvador R, Sarró S, Pomarol-Clotet E, Ciullo V, Piras F, Vecchio D, Banaj N, Spalletta G, Michielse S, van Amelsvoort T, Dickie EW, Voineskos AN, Sim K, Ciufolini S, Dazzan P, Murray RM, Kim WS, Chung YC, Andreou C, Schmidt A, Borgwardt S, McIntosh AM, Whalley HC, Lawrie SM, du Plessis S, Luckhoff HK, Scheffler F, Emsley R, Grotegerd D, Lencer R, Dannlowski U, Edmond JT, Rootes-Murdy K, Stephen JM, Mayer AR, Antonucci LA, Fazio L, Pergola G, Bertolino A, Díaz-Caneja CM, Janssen J, Lois NG, Arango C, Tomyshev AS, Lebedeva I, Cervenka S, Sellgren CM, Georgiadis F, Kirschner M, Kaiser S, Hajek T, Skoch A, Spaniel F, Kim M, Kwak YB, Oh S, Kwon JS, James A, Bakker G, Knöchel C, Stäblein M, Oertel V, Uhlmann A, Howells FM, Stein DJ, Temmingh HS, Diaz-Zuluaga AM, Pineda-Zapata JA, López-Jaramillo C, Homan S, Ji E, Surbeck W, Homan P, Fisher SE, Franke B, Glahn DC, Gur RC, Hashimoto R, Jahanshad N, Luders E, Medland SE, Thompson PM, Turner JA, van Erp TGM, and Francks C
Subjects: Male, Female, Humans, Case-Control Studies, Brain diagnostic imaging, Cerebral Cortex, Magnetic Resonance Imaging methods, Functional Laterality, Schizophrenia diagnostic imaging
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
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39. Effect of Minocycline on Depressive Symptoms in Patients With Treatment-Resistant Depression: A Randomized Clinical Trial.

Author: Hellmann-Regen J, Clemens V, Grözinger M, Kornhuber J, Reif A, Prvulovic D, Goya-Maldonado R, Wiltfang J, Gruber O, Schüle C, Padberg F, Ising M, Uhr M, Friede T, Huber C, Manook A, Baghai TC, Rupprecht R, and Heuser I
Subjects: Antidepressive Agents therapeutic use, Depression drug therapy, Double-Blind Method, Female, Humans, Male, Depressive Disorder, Treatment-Resistant drug therapy, Minocycline adverse effects, Minocycline therapeutic use
Abstract: Importance: Insufficient treatment response and resulting chronicity constitute a major problem in depressive disorders. Remission rates range as low as 15% to 40% and treatment-resistant depression (TRD) is associated with low-grade inflammation, suggesting anti-inflammatory interventions as a rational treatment strategy. Minocycline, which inhibits microglial activation, represents a promising repurposing candidate in the treatment of TRD., Objective: To determine whether 6 weeks of minocycline as add-on to antidepressant treatment as usual can significantly reduce depressive symptoms in patients with TRD., Design, Setting, and Participants: The study was conducted in Germany and designed as a multicenter double-blind randomized clinical trial (RCT) of 200 mg/d minocycline treatment over a course of 6 weeks with a 6-month follow-up. Participants were recruited from January 2016 to August 2020 at 9 university hospitals that served as study sites. Key inclusion criteria were a diagnosis of major depressive disorder (according to Diagnostic and Statistical Manual of Mental Disorders [Fifth Edition] criteria), severity of depressive symptoms on the Hamilton Depression Rating Scale (HAMD-17) greater than or equal to 16 points, aged 18 to 75 years, body mass index 18 to 40, Clinical Global Impression Scale (CGI-S) greater than or equal to 4, failure to adequately respond to an initial antidepressant standard medication as per Massachusetts General Hospital Antidepressant Treatment History Questionnaire, and stable medication for at least 2 weeks. A total of 258 patients were screened, of whom 173 were randomized and 168 were included into the intention-to-treat population. Statistical analysis was performed from April to November 2020., Interventions: Participants were randomized (1:1) to receive adjunct minocycline (200 mg/d) or placebo for 6 weeks., Main Outcomes and Measures: Primary outcome measure was the change in Montgomery-Åsberg Depression Rating Scale (MADRS) score from baseline to week 6 analyzed by intention-to-treat mixed model repeated measures. Secondary outcome measures were response, remission, and various other clinical rating scales., Results: Of 173 eligible and randomized participants (84 randomized to minocycline and 89 randomized to placebo), 168 formed the intention-to-treat sample (79 [47.0%] were women, 89 [53.0%] were men, 159 [94.6%] were White, 9 [6.4%] were of other race and ethnicity, including Asian and unknown ethnicity), with 81 in the minocycline group and 87 in the placebo group. The mean (SD) age was 46.1 (13.1) years, and the mean (SD) MADRS score at baseline was 26.5 (5.0). There was no difference in rates of completion between the minocycline (83.3% [70 of 81]) and the placebo group (83.1% [74 of 87]). Minocycline treatment did not alter the course of depression severity compared with placebo as assessed by a decrease in MADRS scores over 6 weeks of treatment (1.46 [-1.04 to 3.96], P = .25). Minocycline treatment also exhibited no statistically significant effect on secondary outcomes., Conclusions and Relevance: In this large randomized clinical trial with minocycline at a dose of 200 mg/d added to antidepressant treatment as usual for 6 weeks, minocycline was well tolerated but not superior to placebo in reducing depressive symptoms in patients with TRD. The results of this RCT emphasize the unmet need for therapeutic approaches and predictive biomarkers in TRD., Trial Registration: EU Clinical Trials Register Number: EudraCT 2015-001456-29.
Published: 2022
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40. Virtual Ontogeny of Cortical Growth Preceding Mental Illness.

Author: Patel Y, Shin J, Abé C, Agartz I, Alloza C, Alnæs D, Ambrogi S, Antonucci LA, Arango C, Arolt V, Auzias G, Ayesa-Arriola R, Banaj N, Banaschewski T, Bandeira C, Başgöze Z, Cupertino RB, Bau CHD, Bauer J, Baumeister S, Bernardoni F, Bertolino A, Bonnin CDM, Brandeis D, Brem S, Bruggemann J, Bülow R, Bustillo JR, Calderoni S, Calvo R, Canales-Rodríguez EJ, Cannon DM, Carmona S, Carr VJ, Catts SV, Chenji S, Chew QH, Coghill D, Connolly CG, Conzelmann A, Craven AR, Crespo-Facorro B, Cullen K, Dahl A, Dannlowski U, Davey CG, Deruelle C, Díaz-Caneja CM, Dohm K, Ehrlich S, Epstein J, Erwin-Grabner T, Eyler LT, Fedor J, Fitzgerald J, Foran W, Ford JM, Fortea L, Fuentes-Claramonte P, Fullerton J, Furlong L, Gallagher L, Gao B, Gao S, Goikolea JM, Gotlib I, Goya-Maldonado R, Grabe HJ, Green M, Grevet EH, Groenewold NA, Grotegerd D, Gruber O, Haavik J, Hahn T, Harrison BJ, Heindel W, Henskens F, Heslenfeld DJ, Hilland E, Hoekstra PJ, Hohmann S, Holz N, Howells FM, Ipser JC, Jahanshad N, Jakobi B, Jansen A, Janssen J, Jonassen R, Kaiser A, Kaleda V, Karantonis J, King JA, Kircher T, Kochunov P, Koopowitz SM, Landén M, Landrø NI, Lawrie S, Lebedeva I, Luna B, Lundervold AJ, MacMaster FP, Maglanoc LA, Mathalon DH, McDonald C, McIntosh A, Meinert S, Michie PT, Mitchell P, Moreno-Alcázar A, Mowry B, Muratori F, Nabulsi L, Nenadić I, O'Gorman Tuura R, Oosterlaan J, Overs B, Pantelis C, Parellada M, Pariente JC, Pauli P, Pergola G, Piarulli FM, Picon F, Piras F, Pomarol-Clotet E, Pretus C, Quidé Y, Radua J, Ramos-Quiroga JA, Rasser PE, Reif A, Retico A, Roberts G, Rossell S, Rovaris DL, Rubia K, Sacchet M, Salavert J, Salvador R, Sarró S, Sawa A, Schall U, Scott R, Selvaggi P, Silk T, Sim K, Skoch A, Spalletta G, Spaniel F, Stein DJ, Steinsträter O, Stolicyn A, Takayanagi Y, Tamm L, Tavares M, Teumer A, Thiel K, Thomopoulos SI, Tomecek D, Tomyshev AS, Tordesillas-Gutiérrez D, Tosetti M, Uhlmann A, Van Rheenen T, Vazquez-Bourgón J, Vernooij MW, Vieta E, Vilarroya O, Weickert C, Weickert T, Westlye LT, Whalley H, Willinger D, Winter A, Wittfeld K, Yang TT, Yoncheva Y, Zijlmans JL, Hoogman M, Franke B, van Rooij D, Buitelaar J, Ching CRK, Andreassen OA, Pozzi E, Veltman D, Schmaal L, van Erp TGM, Turner J, Castellanos FX, Pausova Z, Thompson P, and Paus T
Subjects: Cerebral Cortex, Child, Female, Humans, Infant, Newborn, Magnetic Resonance Imaging methods, Pregnancy, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder genetics, Autism Spectrum Disorder pathology, Bipolar Disorder, Depressive Disorder, Major pathology, Premature Birth pathology
Abstract: Background: Morphology 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., Methods: Interregional 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., Results: Across 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., Conclusions: Our 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., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)
Published: 2022
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41. The role of educational attainment and brain morphology in major depressive disorder: Findings from the ENIGMA major depressive disorder consortium.

Author: Whittle S, Rakesh D, Schmaal L, Veltman DJ, Thompson PM, Singh A, Gonul AS, Aleman A, Uyar Demir A, Krug A, Mwangi B, Krämer B, Baune BT, Stein DJ, Grotegerd D, Pomarol-Clotet E, Rodríguez-Cano E, Melloni E, Benedetti F, Stein F, Grabe HJ, Völzke H, Gotlib IH, Nenadić I, Soares JC, Repple J, Sim K, Brosch K, Wittfeld K, Berger K, Hermesdorf M, Portella MJ, Sacchet MD, Wu MJ, Opel N, Groenewold NA, Gruber O, Fuentes-Claramonte P, Salvador R, Goya-Maldonado R, Sarró S, Poletti S, Meinert SL, Kircher T, Dannlowski U, and Pozzi E
Subjects: Adult, Brain diagnostic imaging, Educational Status, Frontal Lobe, Humans, Magnetic Resonance Imaging, Depressive Disorder, Major diagnostic imaging
Abstract: Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
Published: 2022
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42. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Author: Frangou S, Modabbernia A, Williams SCR, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes-Eizagirre A, Alnaes D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur-Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales-Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim-Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo-Facorro B, Crivello F, Crone EA, Dale AM, Dannlowski U, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros-Bergman H, Fisher SE, Fouche JP, Franke B, Frodl T, Fuentes-Claramonte P, Glahn DC, Gotlib IH, Grabe HJ, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho BC, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch KP, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez-Zalacaín I, Mataix-Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer-Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol-Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez-Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano-Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas-Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, van 't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, and Dima D
Subjects: Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Humans, Male, Middle Aged, Young Adult, Cross-Sectional Studies, Cerebral Cortex anatomy & histology, Cerebral Cortex diagnostic imaging, Human Development physiology, Neuroimaging
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., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
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43. Greater male than female variability in regional brain structure across the lifespan.

Author: Wierenga LM, Doucet GE, Dima D, Agartz I, Aghajani M, Akudjedu TN, Albajes-Eizagirre A, Alnaes D, Alpert KI, Andreassen OA, Anticevic A, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur-Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, den Braber A, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Calhoun VD, Canales-Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Chaim-Avancini TM, Ching CR, Clark VP, Conrod PJ, Conzelmann A, Crivello F, Davey CG, Dickie EW, Ehrlich S, Van't Ent D, Fisher SE, Fouche JP, Franke B, Fuentes-Claramonte P, de Geus EJ, Di Giorgio A, Glahn DC, Gotlib IH, Grabe HJ, Gruber O, Gruner P, Gur RE, Gur RC, Gurholt TP, de Haan L, Haatveit B, Harrison BJ, Hartman CA, Hatton SN, Heslenfeld DJ, van den Heuvel OA, Hickie IB, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James AC, Jiang J, Jönsson EG, Joska JA, Kalnin AJ, Klein M, Koenders L, Kolskår KK, Krämer B, Kuntsi J, Lagopoulos J, Lazaro L, Lebedeva IS, Lee PH, Lochner C, Machielsen MW, Maingault S, Martin NG, Martínez-Zalacaín I, Mataix-Cols D, Mazoyer B, McDonald BC, McDonald C, McIntosh AM, McMahon KL, McPhilemy G, van der Meer D, Menchón JM, Naaijen J, Nyberg L, Oosterlaan J, Paloyelis Y, Pauli P, Pergola G, Pomarol-Clotet E, Portella MJ, Radua J, Reif A, Richard G, Roffman JL, Rosa PG, Sacchet MD, Sachdev PS, Salvador R, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Sim K, Simmons A, Smoller JW, Sommer IE, Soriano-Mas C, Stein DJ, Strike LT, Szeszko PR, Temmingh HS, Thomopoulos SI, Tomyshev AS, Trollor JN, Uhlmann A, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Wang L, Wang Y, Weber B, Wen W, West JD, Westlye LT, Whalley HC, Williams SC, Wittfeld K, Wolf DH, Wright MJ, Yoncheva YN, Zanetti MV, Ziegler GC, de Zubicaray GI, Thompson PM, Crone EA, Frangou S, and Tamnes CK
Subjects: Female, Humans, Male, Brain Cortical Thickness, Cerebral Cortex anatomy & histology, Cerebral Cortex diagnostic imaging, Biological Variation, Population physiology, Brain anatomy & histology, Brain diagnostic imaging, Human Development physiology, Magnetic Resonance Imaging, Neuroimaging, Sex Characteristics
Abstract: For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
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44. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group.

Author: Haukvik UK, Gurholt TP, Nerland S, Elvsåshagen T, Akudjedu TN, Alda M, Alnaes D, Alonso-Lana S, Bauer J, Baune BT, Benedetti F, Berk M, Bettella F, Bøen E, Bonnín CM, Brambilla P, Canales-Rodríguez EJ, Cannon DM, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, van Erp TGM, Fatjó-Vilas M, Foley SF, Förster K, Fullerton JM, Goikolea JM, Grotegerd D, Gruber O, Haarman BCM, Haatveit B, Hajek T, Hallahan B, Harris M, Hawkins EL, Howells FM, Hülsmann C, Jahanshad N, Jørgensen KN, Kircher T, Krämer B, Krug A, Kuplicki R, Lagerberg TV, Lancaster TM, Lenroot RK, Lonning V, López-Jaramillo C, Malt UF, McDonald C, McIntosh AM, McPhilemy G, van der Meer D, Melle I, Melloni EMT, Mitchell PB, Nabulsi L, Nenadić I, Oertel V, Oldani L, Opel N, Otaduy MCG, Overs BJ, Pineda-Zapata JA, Pomarol-Clotet E, Radua J, Rauer L, Redlich R, Repple J, Rive MM, Roberts G, Ruhe HG, Salminen LE, Salvador R, Sarró S, Savitz J, Schene AH, Sim K, Soeiro-de-Souza MG, Stäblein M, Stein DJ, Stein F, Tamnes CK, Temmingh HS, Thomopoulos SI, Veltman DJ, Vieta E, Waltemate L, Westlye LT, Whalley HC, Sämann PG, Thompson PM, Ching CRK, Andreassen OA, and Agartz I
Subjects: Bipolar Disorder drug therapy, Genetics, Hippocampus drug effects, Humans, Bipolar Disorder diagnostic imaging, Bipolar Disorder pathology, Hippocampus diagnostic imaging, Hippocampus pathology, Magnetic Resonance Imaging, Neuroimaging
Abstract: The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
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45. Intelligence, educational attainment, and brain structure in those at familial high-risk for schizophrenia or bipolar disorder.

Author: de Zwarte SMC, Brouwer RM, Agartz I, Alda M, Alonso-Lana S, Bearden CE, Bertolino A, Bonvino A, Bramon E, Buimer EEL, Cahn W, Canales-Rodríguez EJ, Cannon DM, Cannon TD, Caseras X, Castro-Fornieles J, Chen Q, Chung Y, De la Serna E, Del Mar Bonnin C, Demro C, Di Giorgio A, Doucet GE, Eker MC, Erk S, Fatjó-Vilas M, Fears SC, Foley SF, Frangou S, Fullerton JM, Glahn DC, Goghari VM, Goikolea JM, Goldman AL, Gonul AS, Gruber O, Hajek T, Hawkins EL, Heinz A, Hidiroglu Ongun C, Hillegers MHJ, Houenou J, Hulshoff Pol HE, Hultman CM, Ingvar M, Johansson V, Jönsson EG, Kane F, Kempton MJ, Koenis MMG, Kopecek M, Krämer B, Lawrie SM, Lenroot RK, Marcelis M, Mattay VS, McDonald C, Meyer-Lindenberg A, Michielse S, Mitchell PB, Moreno D, Murray RM, Mwangi B, Nabulsi L, Newport J, Olman CA, van Os J, Overs BJ, Ozerdem A, Pergola G, Picchioni MM, Piguet C, Pomarol-Clotet E, Radua J, Ramsay IS, Richter A, Roberts G, Salvador R, Saricicek Aydogan A, Sarró S, Schofield PR, Simsek EM, Simsek F, Soares JC, Sponheim SR, Sugranyes G, Toulopoulou T, Tronchin G, Vieta E, Walter H, Weinberger DR, Whalley HC, Wu MJ, Yalin N, Andreassen OA, Ching CRK, Thomopoulos SI, van Erp TGM, Jahanshad N, Thompson PM, Kahn RS, and van Haren NEM
Subjects: Bipolar Disorder complications, Bipolar Disorder diagnostic imaging, Cognitive Dysfunction diagnostic imaging, Family, Humans, Magnetic Resonance Imaging, Schizophrenia complications, Schizophrenia diagnostic imaging, Schizophrenia etiology, Bipolar Disorder pathology, Cognitive Dysfunction pathology, Educational Status, Genetic Predisposition to Disease, Intelligence physiology, Neuroimaging, Schizophrenia pathology
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., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
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46. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Author: Dima D, Modabbernia A, Papachristou E, Doucet GE, Agartz I, Aghajani M, Akudjedu TN, Albajes-Eizagirre A, Alnaes D, Alpert KI, Andersson M, Andreasen NC, Andreassen OA, Asherson P, Banaschewski T, Bargallo N, Baumeister S, Baur-Streubel R, Bertolino A, Bonvino A, Boomsma DI, Borgwardt S, Bourque J, Brandeis D, Breier A, Brodaty H, Brouwer RM, Buitelaar JK, Busatto GF, Buckner RL, Calhoun V, Canales-Rodríguez EJ, Cannon DM, Caseras X, Castellanos FX, Cervenka S, Chaim-Avancini TM, Ching CRK, Chubar V, Clark VP, Conrod P, Conzelmann A, Crespo-Facorro B, Crivello F, Crone EA, Dannlowski U, Dale AM, Davey C, de Geus EJC, de Haan L, de Zubicaray GI, den Braber A, Dickie EW, Di Giorgio A, Doan NT, Dørum ES, Ehrlich S, Erk S, Espeseth T, Fatouros-Bergman H, Fisher SE, Fouche JP, Franke B, Frodl T, Fuentes-Claramonte P, Glahn DC, Gotlib IH, Grabe HJ, Grimm O, Groenewold NA, Grotegerd D, Gruber O, Gruner P, Gur RE, Gur RC, Hahn T, Harrison BJ, Hartman CA, Hatton SN, Heinz A, Heslenfeld DJ, Hibar DP, Hickie IB, Ho BC, Hoekstra PJ, Hohmann S, Holmes AJ, Hoogman M, Hosten N, Howells FM, Hulshoff Pol HE, Huyser C, Jahanshad N, James A, Jernigan TL, Jiang J, Jönsson EG, Joska JA, Kahn R, Kalnin A, Kanai R, Klein M, Klyushnik TP, Koenders L, Koops S, Krämer B, Kuntsi J, Lagopoulos J, Lázaro L, Lebedeva I, Lee WH, Lesch KP, Lochner C, Machielsen MWJ, Maingault S, Martin NG, Martínez-Zalacaín I, Mataix-Cols D, Mazoyer B, McDonald C, McDonald BC, McIntosh AM, McMahon KL, McPhilemy G, Meinert S, Menchón JM, Medland SE, Meyer-Lindenberg A, Naaijen J, Najt P, Nakao T, Nordvik JE, Nyberg L, Oosterlaan J, de la Foz VO, Paloyelis Y, Pauli P, Pergola G, Pomarol-Clotet E, Portella MJ, Potkin SG, Radua J, Reif A, Rinker DA, Roffman JL, Rosa PGP, Sacchet MD, Sachdev PS, Salvador R, Sánchez-Juan P, Sarró S, Satterthwaite TD, Saykin AJ, Serpa MH, Schmaal L, Schnell K, Schumann G, Sim K, Smoller JW, Sommer I, Soriano-Mas C, Stein DJ, Strike LT, Swagerman SC, Tamnes CK, Temmingh HS, Thomopoulos SI, Tomyshev AS, Tordesillas-Gutiérrez D, Trollor JN, Turner JA, Uhlmann A, van den Heuvel OA, van den Meer D, van der Wee NJA, van Haren NEM, Van't Ent D, van Erp TGM, Veer IM, Veltman DJ, Voineskos A, Völzke H, Walter H, Walton E, Wang L, Wang Y, Wassink TH, Weber B, Wen W, West JD, Westlye LT, Whalley H, Wierenga LM, Williams SCR, Wittfeld K, Wolf DH, Worker A, Wright MJ, Yang K, Yoncheva Y, Zanetti MV, Ziegler GC, Thompson PM, and Frangou S
Subjects: Adolescent, Adult, Aged, Aged, 80 and over, Child, Child, Preschool, Female, Humans, Male, Middle Aged, Young Adult, Amygdala anatomy & histology, Amygdala diagnostic imaging, Corpus Striatum anatomy & histology, Corpus Striatum diagnostic imaging, Hippocampus anatomy & histology, Hippocampus diagnostic imaging, Human Development physiology, Neuroimaging, Thalamus anatomy & histology, Thalamus diagnostic imaging
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., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
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47. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group.

Author: Ching CRK, Hibar DP, Gurholt TP, Nunes A, Thomopoulos SI, Abé C, Agartz I, Brouwer RM, Cannon DM, de Zwarte SMC, Eyler LT, Favre P, Hajek T, Haukvik UK, Houenou J, Landén M, Lett TA, McDonald C, Nabulsi L, Patel Y, Pauling ME, Paus T, Radua J, Soeiro-de-Souza MG, Tronchin G, van Haren NEM, Vieta E, Walter H, Zeng LL, Alda M, Almeida J, Alnaes D, Alonso-Lana S, Altimus C, Bauer M, Baune BT, Bearden CE, Bellani M, Benedetti F, Berk M, Bilderbeck AC, Blumberg HP, Bøen E, Bollettini I, Del Mar Bonnin C, Brambilla P, Canales-Rodríguez EJ, Caseras X, Dandash O, Dannlowski U, Delvecchio G, Díaz-Zuluaga AM, Dima D, Duchesnay É, Elvsåshagen T, Fears SC, Frangou S, Fullerton JM, Glahn DC, Goikolea JM, Green MJ, Grotegerd D, Gruber O, Haarman BCM, Henry C, Howells FM, Ives-Deliperi V, Jansen A, Kircher TTJ, Knöchel C, Kramer B, Lafer B, López-Jaramillo C, Machado-Vieira R, MacIntosh BJ, Melloni EMT, Mitchell PB, Nenadic I, Nery F, Nugent AC, Oertel V, Ophoff RA, Ota M, Overs BJ, Pham DL, Phillips ML, Pineda-Zapata JA, Poletti S, Polosan M, Pomarol-Clotet E, Pouchon A, Quidé Y, Rive MM, Roberts G, Ruhe HG, Salvador R, Sarró S, Satterthwaite TD, Schene AH, Sim K, Soares JC, Stäblein M, Stein DJ, Tamnes CK, Thomaidis GV, Upegui CV, Veltman DJ, Wessa M, Westlye LT, Whalley HC, Wolf DH, Wu MJ, Yatham LN, Zarate CA, Thompson PM, and Andreassen OA
Subjects: Humans, Meta-Analysis as Topic, Multicenter Studies as Topic, Bipolar Disorder diagnostic imaging, Bipolar Disorder pathology, Cerebral Cortex diagnostic imaging, Cerebral Cortex pathology, Magnetic Resonance Imaging, Neuroimaging
Abstract: MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness., (© 2020 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2022
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48. Cortical activation abnormalities in bipolar and schizophrenia patients in a combined oddball-incongruence paradigm.

Author: Rauer L, Trost S, Petrovic A, and Gruber O
Subjects: Case-Control Studies, Humans, Magnetic Resonance Imaging, Bipolar Disorder diagnostic imaging, Bipolar Disorder physiopathology, Cerebral Cortex diagnostic imaging, Cerebral Cortex physiopathology, Schizophrenia diagnostic imaging, Schizophrenia physiopathology
Abstract: Patients with bipolar disorder and schizophrenia often suffer from severe cognitive impairment even during times of remission. This study investigated the pathomechanisms underlying their deficits in cognitive control. A combined oddball-incongruence fMRI task was applied to examine similarities and differences of neural activation patterns between patients and healthy controls. Bipolar and schizophrenia patients demonstrated hyperactivations in the intraparietal cortex during the oddball condition. Furthermore, bipolar patients revealed diagnosis-specific hyperactivation in the left middle frontal gyrus, precentral gyrus, anteroventral prefrontal cortex and orbitofrontal cortex regions compared to schizophrenia patients and healthy individuals. In comparison to healthy controls the patients showed hypoactivations in the inferior frontal junction and ventral pathway during the cognitively more demanding incongruence. Taken together, bipolar patients seem to recruit frontal and parietal areas during the oddball condition to compensate for potential deficits in their attentional network. During more challenging tasks, i.e., the incongruence condition, their compensatory mechanisms seem to collapse leading to hypoactivations in the same frontal areas as well as the ventral pathway., (© 2020. The Author(s).)
Published: 2021
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49. Correction to: Cortical activation abnormalities in bipolar and schizophrenia patients in a combined oddball-incongruence paradigm.

Author: Rauer L, Trost S, Petrovic A, and Gruber O
Published: 2021
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