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1. 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

2. 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

3. 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

4. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Author: Hoogman, M, van Rooij, D, Klein, M, Boedhoe, P, Ilioska, I, Li, T, Patel, Y, Postema, MC, Zhang-James, Y, Anagnostou, E, Arango, C, Auzias, G, Banaschewski, T, Bau, CHD, Behrmann, M, Bellgrove, MA, Brandeis, D, Brem, S, Busatto, GF, Calderoni, S, Calvo, R, Castellanos, FX, Coghill, D, Conzelmann, A, Daly, E, Deruelle, C, Dinstein, I, Durston, S, Ecker, C, Ehrlich, S, Epstein, JN, Fair, DA, Fitzgerald, J, Freitag, CM, Frodl, T, Gallagher, L, Grevet, EH, Haavik, J, Hoekstra, PJ, Janssen, J, Karkashadze, G, King, JA, Konrad, K, Kuntsi, J, Lazaro, L, Lerch, JP, Lesch, K-P, Louza, MR, Luna, B, Mattos, P, McGrath, J, Muratori, F, Murphy, C, Nigg, JT, Oberwelland-Weiss, E, Tuura, RLO, O'Hearn, K, Oosterlaan, J, Parellada, M, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Shaw, P, Silk, TJ, Tamm, L, Vilarroya, O, Walitza, S, Jahanshad, N, Faraone, S, Francks, C, van den Heuvel, OA, Paus, T, Thompson, PM, Buitelaar, JK, Franke, B, Hoogman, M, van Rooij, D, Klein, M, Boedhoe, P, Ilioska, I, Li, T, Patel, Y, Postema, MC, Zhang-James, Y, Anagnostou, E, Arango, C, Auzias, G, Banaschewski, T, Bau, CHD, Behrmann, M, Bellgrove, MA, Brandeis, D, Brem, S, Busatto, GF, Calderoni, S, Calvo, R, Castellanos, FX, Coghill, D, Conzelmann, A, Daly, E, Deruelle, C, Dinstein, I, Durston, S, Ecker, C, Ehrlich, S, Epstein, JN, Fair, DA, Fitzgerald, J, Freitag, CM, Frodl, T, Gallagher, L, Grevet, EH, Haavik, J, Hoekstra, PJ, Janssen, J, Karkashadze, G, King, JA, Konrad, K, Kuntsi, J, Lazaro, L, Lerch, JP, Lesch, K-P, Louza, MR, Luna, B, Mattos, P, McGrath, J, Muratori, F, Murphy, C, Nigg, JT, Oberwelland-Weiss, E, Tuura, RLO, O'Hearn, K, Oosterlaan, J, Parellada, M, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Shaw, P, Silk, TJ, Tamm, L, Vilarroya, O, Walitza, S, Jahanshad, N, Faraone, S, Francks, C, van den Heuvel, OA, Paus, T, Thompson, PM, Buitelaar, JK, and Franke, B
Abstract: Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.
Published: 2022

5. Virtual histology of cortical thickness and shared neurobiology in 6 psychiatric disorders

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abé, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargalló, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, Del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bülow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodríguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjó-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Silk, Timothy, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abé, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargalló, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, Del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bülow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodríguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjó-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, and Silk, Timothy
Published: 2021

6. Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes

Author: Li, T, van Rooij, D, Roth Mota, N, Buitelaar, JK, Hoogman, M, Arias Vasquez, A, Franke, B, Ambrosino, S, Banaschewski, T, Bandeira, CE, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Berm, S, Busatto, GF, Calvo, A, Castellanos, FX, Cercignani, M, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fallgatter, AJ, Fair, DA, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Høvik, MF, Jahanshad, N, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Nicolau, R, Nigg, JT, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Carlos Soliva Vila, J, Soloveva, A, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Anikin, A, Asherson, P, Li, T, van Rooij, D, Roth Mota, N, Buitelaar, JK, Hoogman, M, Arias Vasquez, A, Franke, B, Ambrosino, S, Banaschewski, T, Bandeira, CE, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Berm, S, Busatto, GF, Calvo, A, Castellanos, FX, Cercignani, M, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fallgatter, AJ, Fair, DA, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Høvik, MF, Jahanshad, N, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Nicolau, R, Nigg, JT, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Carlos Soliva Vila, J, Soloveva, A, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Anikin, A, and Asherson, P
Published: 2021

7. Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

Author: Zhang-James, Y, Helminen, EC, Liu, J, Busatto, GF, Calvo, A, Cercignani, M, Chaim-Avancini, TM, Gabel, MC, Harrison, NA, Lazaro, L, Lera-Miguel, S, Louza, MR, Nicolau, R, Rosa, PGP, Schulte-Rutte, M, Zanetti, MV, Ambrosino, S, Asherson, P, Banaschewski, T, Baranov, A, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Buitelaar, JK, Castellanos, FX, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Dale, AM, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Frodl, T, Gogberashvili, T, Haavik, J, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jahanshad, N, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lesch, KP, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Mehta, MA, Namazova-Baranova, L, Nigg, JT, Novotny, SE, O’Gorman Tuura, RL, Weiss, EO, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rubia, K, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Silk, Timothy, Skokauskas, N, Vila, JCS, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zhang-James, Y, Helminen, EC, Liu, J, Busatto, GF, Calvo, A, Cercignani, M, Chaim-Avancini, TM, Gabel, MC, Harrison, NA, Lazaro, L, Lera-Miguel, S, Louza, MR, Nicolau, R, Rosa, PGP, Schulte-Rutte, M, Zanetti, MV, Ambrosino, S, Asherson, P, Banaschewski, T, Baranov, A, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Buitelaar, JK, Castellanos, FX, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Dale, AM, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Frodl, T, Gogberashvili, T, Haavik, J, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jahanshad, N, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lesch, KP, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Mehta, MA, Namazova-Baranova, L, Nigg, JT, Novotny, SE, O’Gorman Tuura, RL, Weiss, EO, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rubia, K, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Silk, Timothy, Skokauskas, N, Vila, JCS, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, and Yoncheva, YN
Published: 2021

8. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

Author: Postema, MC, Hoogman, M, Ambrosino, S, Asherson, P, Banaschewski, T, Bandeira, CE, Baranov, A, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Brandeis, D, Brem, S, Buitelaar, JK, Busatto, GF, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Namazova-Baranova, L, Nicolau, R, Nigg, JT, Novotny, SE, Oberwelland Weiss, E, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Soliva Vila, JC, Stevens, MC, Sudre, G, Tamm, L, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Glahn, DC, Jahanshad, N, Postema, MC, Hoogman, M, Ambrosino, S, Asherson, P, Banaschewski, T, Bandeira, CE, Baranov, A, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Brandeis, D, Brem, S, Buitelaar, JK, Busatto, GF, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Namazova-Baranova, L, Nicolau, R, Nigg, JT, Novotny, SE, Oberwelland Weiss, E, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Soliva Vila, JC, Stevens, MC, Sudre, G, Tamm, L, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Glahn, DC, and Jahanshad, N
Published: 2021

9. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

Author: Postema, MC, Hoogman, M, Ambrosino, S, Asherson, P, Banaschewski, T, Bandeira, CE, Baranov, A, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Brandeis, D, Brem, S, Buitelaar, JK, Busatto, GF, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Hovik, MF, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, K-P, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Namazova-Baranova, L, Nicolau, R, Nigg, JT, Novotny, SE, Oberwelland Weiss, E, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, TJ, Skokauskas, N, Soliva Vila, JC, Stevens, MC, Sudre, G, Tamm, L, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Glahn, DC, Jahanshad, N, Medland, SE, Thompson, PM, Fisher, SE, Franke, B, Francks, C, Postema, MC, Hoogman, M, Ambrosino, S, Asherson, P, Banaschewski, T, Bandeira, CE, Baranov, A, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Brandeis, D, Brem, S, Buitelaar, JK, Busatto, GF, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Hovik, MF, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, K-P, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Namazova-Baranova, L, Nicolau, R, Nigg, JT, Novotny, SE, Oberwelland Weiss, E, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, TJ, Skokauskas, N, Soliva Vila, JC, Stevens, MC, Sudre, G, Tamm, L, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Glahn, DC, Jahanshad, N, Medland, SE, Thompson, PM, Fisher, SE, Franke, B, and Francks, C
Abstract: OBJECTIVE: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. METHODS: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. RESULTS: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing. CONCLUSION: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
Published: 2021

10. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, Paus, T, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, and Paus, T
Abstract: IMPORTANCE: Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. OBJECTIVE: To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. DESIGN, SETTING, AND PARTICIPANTS: Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. MAIN OUTCOMES AND MEASURES: Interregional profiles of group difference in cortical thickness between cases and controls. RESULTS: A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene
Published: 2021

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

Author: Nunes, A, Schnack, HG, Ching, CRK, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Bauer, J, Baune, BT, Bøen, E, Bonnin, CDM, Busatto, GF, Canales-Rodríguez, EJ, Cannon, DM, Caseras, X, Chaim-Avancini, TM, Dannlowski, U, Díaz-Zuluaga, AM, Dietsche, B, Doan, NT, Duchesnay, E, Elvsåshagen, T, Emden, D, Eyler, LT, Fatjó-Vilas, M, Favre, P, Foley, SF, Fullerton, JM ; https://orcid.org/0000-0003-4014-4490, Glahn, DC, Goikolea, JM, Grotegerd, D, Hahn, T, Henry, C, Hibar, DP, Houenou, J, Howells, FM, Jahanshad, N, Kaufmann, T, Kenney, J, Kircher, TTJ, Krug, A, Lagerberg, TV, Lenroot, RK ; https://orcid.org/0000-0002-0949-5121, López-Jaramillo, C, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Mwangi, B, Nabulsi, L, Opel, N, Overs, BJ ; https://orcid.org/0000-0002-7138-5556, Pineda-Zapata, JA, Pomarol-Clotet, E, Redlich, R, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Rosa, PG, Salvador, R, Satterthwaite, TD, Soares, JC, Stein, DJ, Temmingh, HS, Trappenberg, T, Uhlmann, A, van Haren, NEM, Vieta, E, Westlye, LT, Wolf, DH, Yüksel, D, Zanetti, MV, Andreassen, OA, Thompson, PM, Hajek, T, Nunes, A, Schnack, HG, Ching, CRK, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Bauer, J, Baune, BT, Bøen, E, Bonnin, CDM, Busatto, GF, Canales-Rodríguez, EJ, Cannon, DM, Caseras, X, Chaim-Avancini, TM, Dannlowski, U, Díaz-Zuluaga, AM, Dietsche, B, Doan, NT, Duchesnay, E, Elvsåshagen, T, Emden, D, Eyler, LT, Fatjó-Vilas, M, Favre, P, Foley, SF, Fullerton, JM ; https://orcid.org/0000-0003-4014-4490, Glahn, DC, Goikolea, JM, Grotegerd, D, Hahn, T, Henry, C, Hibar, DP, Houenou, J, Howells, FM, Jahanshad, N, Kaufmann, T, Kenney, J, Kircher, TTJ, Krug, A, Lagerberg, TV, Lenroot, RK ; https://orcid.org/0000-0002-0949-5121, López-Jaramillo, C, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Mwangi, B, Nabulsi, L, Opel, N, Overs, BJ ; https://orcid.org/0000-0002-7138-5556, Pineda-Zapata, JA, Pomarol-Clotet, E, Redlich, R, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Rosa, PG, Salvador, R, Satterthwaite, TD, Soares, JC, Stein, DJ, Temmingh, HS, Trappenberg, T, Uhlmann, A, van Haren, NEM, Vieta, E, Westlye, LT, Wolf, DH, Yüksel, D, Zanetti, MV, Andreassen, OA, Thompson, PM, and Hajek, T
Abstract: Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.
Published: 2020

12. Using structural MRI to identify bipolar disorders-13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

Author: Nunes, A, Schnack, HG, Ching, CRK, Agartz, I, Akudjedu, TN, Alda, M, Alnaes, D, Alonso-Lana, S, Bauer, J, Baune, BT, Boen, E, del Mar Bonnin, C, Busatto, GF, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Chaim-Avancini, TM, Dannlowski, U, Diaz-Zuluaga, AM, Dietsche, B, Nhat, TD, Duchesnay, E, Elvsashagen, T, Emden, D, Eyler, LT, Fatjo-Vilas, M, Favre, P, Foley, SF, Fullerton, JM, Glahn, DC, Goikolea, JM, Grotegerd, D, Hahn, T, Henry, C, Hibar, DP, Houenou, J, Howells, FM, Jahanshad, N, Kaufmann, T, Kenney, J, Kircher, TTJ, Krug, A, Lagerberg, T, Lenroot, RK, Lopez-Jaramillo, C, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Mwangi, B, Nabulsi, L, Opel, N, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Redlich, R, Roberts, G, Rosa, PG, Salvador, R, Satterthwaite, TD, Soares, JC, Stein, DJ, Temmingh, HS, Trappenberg, T, Uhlmann, A, van Haren, NEM, Vieta, E, Westlye, LT, Wolf, DH, Yueksel, D, Zanetti, M, Andreassen, OA, Thompson, PM, Hajek, T, Nunes, A, Schnack, HG, Ching, CRK, Agartz, I, Akudjedu, TN, Alda, M, Alnaes, D, Alonso-Lana, S, Bauer, J, Baune, BT, Boen, E, del Mar Bonnin, C, Busatto, GF, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Chaim-Avancini, TM, Dannlowski, U, Diaz-Zuluaga, AM, Dietsche, B, Nhat, TD, Duchesnay, E, Elvsashagen, T, Emden, D, Eyler, LT, Fatjo-Vilas, M, Favre, P, Foley, SF, Fullerton, JM, Glahn, DC, Goikolea, JM, Grotegerd, D, Hahn, T, Henry, C, Hibar, DP, Houenou, J, Howells, FM, Jahanshad, N, Kaufmann, T, Kenney, J, Kircher, TTJ, Krug, A, Lagerberg, T, Lenroot, RK, Lopez-Jaramillo, C, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Mwangi, B, Nabulsi, L, Opel, N, Overs, BJ, Pineda-Zapata, JA, Pomarol-Clotet, E, Redlich, R, Roberts, G, Rosa, PG, Salvador, R, Satterthwaite, TD, Soares, JC, Stein, DJ, Temmingh, HS, Trappenberg, T, Uhlmann, A, van Haren, NEM, Vieta, E, Westlye, LT, Wolf, DH, Yueksel, D, Zanetti, M, Andreassen, OA, Thompson, PM, and Hajek, T
Abstract: Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47-67.00, ROC-AUC = 71.49%, 95% CI = 69.39-73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70-60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen's Kappa = 0.83, 95% CI = 0.829-0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the results are promising and provide a fair and realistic estimate of classification performance, which can be achieved in a large, ecologically valid, multi-site sample of BD participants based on regional neurostructural measures. Furthermore, the significant classification in different samples was based on plausible and similar neuroanatomical features. Future multi-site studies should move towards sharing of raw/voxelwise neuroimaging data.
Published: 2020

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

Author: Boedhoe, PSW, van Rooij, D, Hoogman, M, Twisk, JWR, Schmaal, L, Abe, Y, Alonso, P, Ameis, SH, Anikin, A, Anticevic, A, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Banaschewski, T, Baranov, A, Batistuzzo, MC, Baumeister, S, Baur-Streubel, R, Behrmann, M, Bellgrove, MA, Benedetti, F, Beucke, JC, Biederman, J, Bollettini, I, Bose, A, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Brennan, BP, Busatto, GF, Calderoni, S, Calvo, A, Calvo, R, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Cheng, Y, Cho, KIK, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, A, Dale, AM, Dallaspezia, S, Daly, E, Denys, D, Deruelle, C, Di Martino, A, Dinstein, I, Doyle, AE, Durston, S, Earl, EA, Ecker, C, Ehrlich, S, Ely, BA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, S, Fedor, J, Feng, X, Feusner, JD, Fitzgerald, J, Fitzgerald, KD, Fouche, J-P, Freitag, CM, Fridgeirsson, EA, Frodl, T, Gabel, MC, Gallagher, L, Gogberashvili, T, Gori, I, Gruner, P, Gursel, DA, Haar, S, Haavik, J, Hall, GB, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hirano, Y, Hoekstra, PJ, Hoexter, MQ, Hohmann, S, Hovik, MF, Hu, H, Huyser, C, Jahanshad, N, Jalbrzikowski, M, James, A, Janssen, J, Jaspers-Fayer, F, Jernigan, TL, Kapilushniy, D, Kardatzki, B, Karkashadze, G, Kathmann, N, Kaufmann, C, Kelly, C, Khadka, S, King, JA, Koch, K, Kohls, G, Konrad, K, Kuno, M, Kuntsi, J, Kvale, G, Kwon, JS, Lazaro, L, Lera-Miguel, S, Lesch, K-P, Hoekstra, L, Liu, Y, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, Malpas, CB, Marques, P, Marsh, R, Martinez-Zalacain, I, Mataix-Cols, D, Mattos, P, McCarthy, H, McGrath, J, Mehta, MA, Menchon, JM, Mennes, M, Martinho, MM, Moreira, PS, Morer, A, Morgado, P, Muratori, F, Murphy, CM, Murphy, DGM, Nakagawa, A, Nakamae, T, Nakao, T, Namazova-Baranova, L, Narayanaswamy, JC, Nicolau, R, Nigg, JT, Novotny, SE, Nurmi, EL, Weiss, EO, Tuura, RLO, O'Hearn, K, O'Neill, J, Oosterlaan, J, Oranje, B, Paloyelis, Y, Parellada, M, Pauli, P, Perriello, C, Piacentini, J, Piras, F, Plessen, KJ, Puig, O, Ramos-Quiroga, JA, Reddy, YCJ, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Rus, OG, Sakai, Y, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Shook, D, Silk, TJ, Simpson, HB, Skokauskas, N, Vila, JCS, Solovieva, A, Soreni, N, Soriano-Mas, C, Spalletta, G, Stern, ER, Stevens, MC, Stewart, SE, Sudre, G, Szeszko, PR, Tamm, L, Taylor, MJ, Tolin, DF, Tosetti, M, Tovar-Moll, F, Tsuchiyagaito, A, van Erp, TGM, van Wingen, GA, Vance, A, Venkatasubramanian, G, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Wallace, GL, Wang, Z, Wolfers, T, Yoncheva, YN, Yun, J-Y, Zanetti, M, Zhou, F, Ziegler, GC, Zierhut, KC, Zwiers, MP, Thompson, PM, Stein, DJ, Buitelaar, J, Franke, B, van den Heuvel, OA, Boedhoe, PSW, van Rooij, D, Hoogman, M, Twisk, JWR, Schmaal, L, Abe, Y, Alonso, P, Ameis, SH, Anikin, A, Anticevic, A, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Banaschewski, T, Baranov, A, Batistuzzo, MC, Baumeister, S, Baur-Streubel, R, Behrmann, M, Bellgrove, MA, Benedetti, F, Beucke, JC, Biederman, J, Bollettini, I, Bose, A, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Brennan, BP, Busatto, GF, Calderoni, S, Calvo, A, Calvo, R, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Cheng, Y, Cho, KIK, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, A, Dale, AM, Dallaspezia, S, Daly, E, Denys, D, Deruelle, C, Di Martino, A, Dinstein, I, Doyle, AE, Durston, S, Earl, EA, Ecker, C, Ehrlich, S, Ely, BA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, S, Fedor, J, Feng, X, Feusner, JD, Fitzgerald, J, Fitzgerald, KD, Fouche, J-P, Freitag, CM, Fridgeirsson, EA, Frodl, T, Gabel, MC, Gallagher, L, Gogberashvili, T, Gori, I, Gruner, P, Gursel, DA, Haar, S, Haavik, J, Hall, GB, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hirano, Y, Hoekstra, PJ, Hoexter, MQ, Hohmann, S, Hovik, MF, Hu, H, Huyser, C, Jahanshad, N, Jalbrzikowski, M, James, A, Janssen, J, Jaspers-Fayer, F, Jernigan, TL, Kapilushniy, D, Kardatzki, B, Karkashadze, G, Kathmann, N, Kaufmann, C, Kelly, C, Khadka, S, King, JA, Koch, K, Kohls, G, Konrad, K, Kuno, M, Kuntsi, J, Kvale, G, Kwon, JS, Lazaro, L, Lera-Miguel, S, Lesch, K-P, Hoekstra, L, Liu, Y, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, Malpas, CB, Marques, P, Marsh, R, Martinez-Zalacain, I, Mataix-Cols, D, Mattos, P, McCarthy, H, McGrath, J, Mehta, MA, Menchon, JM, Mennes, M, Martinho, MM, Moreira, PS, Morer, A, Morgado, P, Muratori, F, Murphy, CM, Murphy, DGM, Nakagawa, A, Nakamae, T, Nakao, T, Namazova-Baranova, L, Narayanaswamy, JC, Nicolau, R, Nigg, JT, Novotny, SE, Nurmi, EL, Weiss, EO, Tuura, RLO, O'Hearn, K, O'Neill, J, Oosterlaan, J, Oranje, B, Paloyelis, Y, Parellada, M, Pauli, P, Perriello, C, Piacentini, J, Piras, F, Plessen, KJ, Puig, O, Ramos-Quiroga, JA, Reddy, YCJ, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Rus, OG, Sakai, Y, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Shook, D, Silk, TJ, Simpson, HB, Skokauskas, N, Vila, JCS, Solovieva, A, Soreni, N, Soriano-Mas, C, Spalletta, G, Stern, ER, Stevens, MC, Stewart, SE, Sudre, G, Szeszko, PR, Tamm, L, Taylor, MJ, Tolin, DF, Tosetti, M, Tovar-Moll, F, Tsuchiyagaito, A, van Erp, TGM, van Wingen, GA, Vance, A, Venkatasubramanian, G, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Wallace, GL, Wang, Z, Wolfers, T, Yoncheva, YN, Yun, J-Y, Zanetti, M, Zhou, F, Ziegler, GC, Zierhut, KC, Zwiers, MP, Thompson, PM, Stein, DJ, Buitelaar, J, Franke, B, and van den Heuvel, OA
Abstract: Objective: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. Methods: Structural T1-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). Results: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. Conclusions: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.
Published: 2020

14. Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals (Neuropsychopharmacology, (2019), 44, 13, (2285-2293), 10.1038/s41386-019-0485-6)

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR ; https://orcid.org/0000-0003-2967-9662, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR ; https://orcid.org/0000-0003-2967-9662, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, and Houenou, J
Abstract: This Article was originally published under NPG's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.
Published: 2019

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

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR ; https://orcid.org/0000-0003-2967-9662, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR ; https://orcid.org/0000-0003-2967-9662, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, and Houenou, J
Abstract: Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2019

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

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abe, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodriguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarro, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, J-F, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abe, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodriguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarro, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, J-F, Henry, C, Duchesnay, E, and Houenou, J
Abstract: Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2019

17. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group.

Author: Hibar, DP, Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, CB, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsåshagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, Lawrence, NS, Hibar, DP, Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, CB, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsåshagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, and Lawrence, NS
Abstract: Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

18. Cortical abnormalities in bipolar disorder: An MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

Author: Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B ; https://orcid.org/0000-0002-7138-5556, Hartberg, CB, Abe, C, Dima, D, Grotegerd, D, Sprooten, E, Ben, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, Van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsashagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM ; https://orcid.org/0000-0003-4014-4490, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-De-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, Lawrence, NS, Schofield, Peter ; https://orcid.org/0000-0003-2967-9662, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Lenroot, Rhoshel ; https://orcid.org/0000-0002-0949-5121, Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B ; https://orcid.org/0000-0002-7138-5556, Hartberg, CB, Abe, C, Dima, D, Grotegerd, D, Sprooten, E, Ben, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, Van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsashagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM ; https://orcid.org/0000-0003-4014-4490, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-De-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, Lawrence, NS, Schofield, Peter ; https://orcid.org/0000-0003-2967-9662, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, and Lenroot, Rhoshel ; https://orcid.org/0000-0002-0949-5121
Abstract: Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d='0.293; P=1.71 × 10 '21), left fusiform gyrus (d='0.288; P=8.25 × 10 '21) and left rostral middle frontal cortex (d='0.276; P=2.99 × 10 '19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

19. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

Author: van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, W, Glahn, DC, Pearlson, GD, Yao, N, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Pol, HEH, Kahn, RS, Ophoff, RA, van Haren, NEM, Andreassen, OA, Dale, AM, Nhat, TD, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jorgensen, KN, Lagerberg, T, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santianez, R, Tordesillas-Gutierrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quide, Y, Schall, U, Scott, RJ, Cairns, MJ, Seal, M, Tooney, PA, Rasser, PE, Cooper, G, Weickert, CS, Weickert, TW, Morris, DW, Hong, E, Kochunov, P, Beard, LM, Gur, RE, Gur, RC, Satterthwaite, TD, Wolf, DH, Belger, A, Brown, GG, Ford, JM, Macciardi, F, Mathalon, DH, O'Leary, DS, Potkin, SG, Preda, A, Voyvodic, J, Lim, KO, McEwen, S, Yang, F, Tan, Y, Tan, S, Wang, Z, Fan, F, Chen, J, Xiang, H, Tang, S, Guo, H, Wan, P, Wei, D, Bockholt, HJ, Ehrlich, S, Wolthusen, RPF, King, MD, Shoemaker, JM, Sponheim, SR, De Haan, L, Koenders, L, Machielsen, MW, van Amelsvoort, T, Veltman, DJ, Assogna, F, Banaj, N, de Rossi, P, Iorio, M, Piras, F, Spalletta, G, McKenna, PJ, Pomarol-Clotet, E, Salvador, R, Corvin, A, Donohoe, G, Kelly, S, Whelan, CD, Dickie, EW, Rotenberg, D, Voineskos, AN, Ciufolini, S, Radua, J, Dazzan, P, Murray, R, Marques, TR, Simmons, A, Borgwardt, S, Egloff, L, Harrisberger, F, Riecher-Roessler, A, Smieskova, R, Alpert, K, Wang, L, Jonsson, EG, Koops, S, Sommer, IEC, Bertolino, A, Bonvino, A, Di Giorgio, A, Neilson, E, Mayer, AR, Stephen, JM, Kwon, JS, Yun, J-Y, Cannon, DM, McDonald, C, Lebedeva, I, Tomyshev, AS, Akhadov, T, Kaleda, V, Fatouros-Bergman, H, Flyckt, L, Busatto, GF, Rosa, PGP, Serpa, MH, Zanetti, M, Hoschl, C, Skoch, A, Spaniel, F, Tomecek, D, Hagenaars, SP, McIntosh, AM, Whalley, HC, Lawrie, SM, Knoechel, C, Oertel-Knoechel, V, Staeblein, M, Howells, FM, Stein, DJ, Temmingh, HS, Uhlmann, A, Lopez-Jaramillo, C, Dima, D, McMahon, A, Faskowitz, J, Gutman, BA, Jahanshad, N, Thompson, PM, Turner, JA, van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, W, Glahn, DC, Pearlson, GD, Yao, N, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Pol, HEH, Kahn, RS, Ophoff, RA, van Haren, NEM, Andreassen, OA, Dale, AM, Nhat, TD, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jorgensen, KN, Lagerberg, T, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santianez, R, Tordesillas-Gutierrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quide, Y, Schall, U, Scott, RJ, Cairns, MJ, Seal, M, Tooney, PA, Rasser, PE, Cooper, G, Weickert, CS, Weickert, TW, Morris, DW, Hong, E, Kochunov, P, Beard, LM, Gur, RE, Gur, RC, Satterthwaite, TD, Wolf, DH, Belger, A, Brown, GG, Ford, JM, Macciardi, F, Mathalon, DH, O'Leary, DS, Potkin, SG, Preda, A, Voyvodic, J, Lim, KO, McEwen, S, Yang, F, Tan, Y, Tan, S, Wang, Z, Fan, F, Chen, J, Xiang, H, Tang, S, Guo, H, Wan, P, Wei, D, Bockholt, HJ, Ehrlich, S, Wolthusen, RPF, King, MD, Shoemaker, JM, Sponheim, SR, De Haan, L, Koenders, L, Machielsen, MW, van Amelsvoort, T, Veltman, DJ, Assogna, F, Banaj, N, de Rossi, P, Iorio, M, Piras, F, Spalletta, G, McKenna, PJ, Pomarol-Clotet, E, Salvador, R, Corvin, A, Donohoe, G, Kelly, S, Whelan, CD, Dickie, EW, Rotenberg, D, Voineskos, AN, Ciufolini, S, Radua, J, Dazzan, P, Murray, R, Marques, TR, Simmons, A, Borgwardt, S, Egloff, L, Harrisberger, F, Riecher-Roessler, A, Smieskova, R, Alpert, K, Wang, L, Jonsson, EG, Koops, S, Sommer, IEC, Bertolino, A, Bonvino, A, Di Giorgio, A, Neilson, E, Mayer, AR, Stephen, JM, Kwon, JS, Yun, J-Y, Cannon, DM, McDonald, C, Lebedeva, I, Tomyshev, AS, Akhadov, T, Kaleda, V, Fatouros-Bergman, H, Flyckt, L, Busatto, GF, Rosa, PGP, Serpa, MH, Zanetti, M, Hoschl, C, Skoch, A, Spaniel, F, Tomecek, D, Hagenaars, SP, McIntosh, AM, Whalley, HC, Lawrie, SM, Knoechel, C, Oertel-Knoechel, V, Staeblein, M, Howells, FM, Stein, DJ, Temmingh, HS, Uhlmann, A, Lopez-Jaramillo, C, Dima, D, McMahon, A, Faskowitz, J, Gutman, BA, Jahanshad, N, Thompson, PM, and Turner, JA
Abstract: BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.
Published: 2018

20. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

Author: Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Kraemer, B, Overs, B, Hartberg, CB, Abe, C, Dima, D, Grotegerd, D, Sprooten, E, Boen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsashagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjo-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landen, M, Lawrence, NS, van Haren, NEM, Horn, NR, Freimer, NB, Gruber, O, Schofield, PR, Mitchell, PB, Kahn, RS, Lenroot, R, Machado-Vieira, R, Ophoff, RA, Sarro, S, Frangou, S, Satterthwaite, TD, Hajek, T, Dannlowski, U, Malt, UF, Arolt, V, Gattaz, WF, Drevets, WC, Caseras, X, Agartz, I, Thompson, PM, Andreassen, OA, Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Kraemer, B, Overs, B, Hartberg, CB, Abe, C, Dima, D, Grotegerd, D, Sprooten, E, Boen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsashagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjo-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landen, M, Lawrence, NS, van Haren, NEM, Horn, NR, Freimer, NB, Gruber, O, Schofield, PR, Mitchell, PB, Kahn, RS, Lenroot, R, Machado-Vieira, R, Ophoff, RA, Sarro, S, Frangou, S, Satterthwaite, TD, Hajek, T, Dannlowski, U, Malt, UF, Arolt, V, Gattaz, WF, Drevets, WC, Caseras, X, Agartz, I, Thompson, PM, and Andreassen, OA
Abstract: Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

21. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group.

Author: Hibar, DP, Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, CB, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsåshagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, Lawrence, NS, Hibar, DP, Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, CB, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsåshagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, and Lawrence, NS
Abstract: Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

22. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

Author: van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, WH, Glahn, DC, Pearlson, GD, Yao, NL, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Pol, HEH, Kahn, RS, Ophoff, RA, van Haren, Neeltje, Andreassen, OA, Dale, AM, Doan, NT, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jorgensen, KN, Lagerberg, TV, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santianez, R, Tordesillas-Gutierrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quide, Y, Schall, U, Scott, RJ, Cairns, MJ, Seal, M, Tooney, PA, Rasser, PE, Cooper, G, Weickert, CS, Weickert, TW, Morris, DW, Hong, E, Kochunov, P, Beard, LM, Gur, RE, Gur, RC, Satterthwaite, TD, Wolf, DH, Belger, A, Brown, GG, Ford, JM, Macciardi, F, Mathalon, DH, O'Leary, DS, Potkin, SG, Preda, A, Voyvodic, J, Lim, KO, McEwen, S, Yang, FD, Tan, YL, Tan, SP, Wang, ZR, Fan, FM, Chen, JX, Xiang, H, Tang, SY, Guo, H, Wan, P, Wei, D, Bockholt, HJ, Ehrlich, S, Wolthusen, RPF, King, MD, Shoemaker, JM, Sponheim, SR, de Haan, L, Koenders, L, Machielsen, MW, van Amelsvoort, T, Veltman, DJ, Assogna, F, Banaj, N, Rossi, P, De Iorio, M, Piras, F, Spalletta, G, McKenna, PJ, Pomarol-Clotet, E, Salvador, R, Corvin, A, Donohoe, G, Kelly, S, Whelan, CD, Dickie, EW, Rotenberg, D, Voineskos, AN, Ciufolini, S, Radua, J, Dazzan, P, Murray, R, Marques, TR, Simmons, A, Borgwardt, S, Egloff, L, Harrisberger, F, Riecher-Rossler, A, Smieskova, R, Alpert, KI, Wang, L (Lei), Jonsson, EG, Koops, S, Sommer, IEC, Bertolino, A, Bonvino, A, Di Giorgio, A, Neilson, E, Mayer, AR, Stephen, JM, Kwon, JS, Yun, JY, Cannon, DM, McDonald, C, Lebedeva, I, Tomyshev, AS, Akhadov, T, Kaleda, V, Fatouros-Bergman, H, Flyckt, L, Busatto, GF, Rosa, PGP, Serpa, MH, Zanetti, MV, Hoschl, C, Skoch, A, Spaniel, F, Tomecek, D, Hagenaars, SP, McIntosh, AM, Whalley, HC, Lawrie, SM, Knochel, C, Oertel-Knochel, V, Stablein, M, Howells, FM, Stein, DJ, Temmingh, HS, Uhlmann, A, Lopez-Jaramillo, C, Dima, D, McMahon, A, Faskowitz, JI, Gutman, B A, Jahanshad, N, Thompson, PM, Turner, JA, van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, WH, Glahn, DC, Pearlson, GD, Yao, NL, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Pol, HEH, Kahn, RS, Ophoff, RA, van Haren, Neeltje, Andreassen, OA, Dale, AM, Doan, NT, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jorgensen, KN, Lagerberg, TV, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santianez, R, Tordesillas-Gutierrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quide, Y, Schall, U, Scott, RJ, Cairns, MJ, Seal, M, Tooney, PA, Rasser, PE, Cooper, G, Weickert, CS, Weickert, TW, Morris, DW, Hong, E, Kochunov, P, Beard, LM, Gur, RE, Gur, RC, Satterthwaite, TD, Wolf, DH, Belger, A, Brown, GG, Ford, JM, Macciardi, F, Mathalon, DH, O'Leary, DS, Potkin, SG, Preda, A, Voyvodic, J, Lim, KO, McEwen, S, Yang, FD, Tan, YL, Tan, SP, Wang, ZR, Fan, FM, Chen, JX, Xiang, H, Tang, SY, Guo, H, Wan, P, Wei, D, Bockholt, HJ, Ehrlich, S, Wolthusen, RPF, King, MD, Shoemaker, JM, Sponheim, SR, de Haan, L, Koenders, L, Machielsen, MW, van Amelsvoort, T, Veltman, DJ, Assogna, F, Banaj, N, Rossi, P, De Iorio, M, Piras, F, Spalletta, G, McKenna, PJ, Pomarol-Clotet, E, Salvador, R, Corvin, A, Donohoe, G, Kelly, S, Whelan, CD, Dickie, EW, Rotenberg, D, Voineskos, AN, Ciufolini, S, Radua, J, Dazzan, P, Murray, R, Marques, TR, Simmons, A, Borgwardt, S, Egloff, L, Harrisberger, F, Riecher-Rossler, A, Smieskova, R, Alpert, KI, Wang, L (Lei), Jonsson, EG, Koops, S, Sommer, IEC, Bertolino, A, Bonvino, A, Di Giorgio, A, Neilson, E, Mayer, AR, Stephen, JM, Kwon, JS, Yun, JY, Cannon, DM, McDonald, C, Lebedeva, I, Tomyshev, AS, Akhadov, T, Kaleda, V, Fatouros-Bergman, H, Flyckt, L, Busatto, GF, Rosa, PGP, Serpa, MH, Zanetti, MV, Hoschl, C, Skoch, A, Spaniel, F, Tomecek, D, Hagenaars, SP, McIntosh, AM, Whalley, HC, Lawrie, SM, Knochel, C, Oertel-Knochel, V, Stablein, M, Howells, FM, Stein, DJ, Temmingh, HS, Uhlmann, A, Lopez-Jaramillo, C, Dima, D, McMahon, A, Faskowitz, JI, Gutman, B A, Jahanshad, N, Thompson, PM, and Turner, JA
Published: 2018

23. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

Author: Nieuwenhuis, M, Schnack, HG, van Haren, NE, Kahn, RS, Lappin, J ; https://orcid.org/0000-0001-5946-2144, Dazzan, P, Morgan, C, Reinders, AA, Gutierrez-Tordesillas, D, Roiz-Santiañez, R, Crespo-Facorro, B, Schaufelberger, MS, Rosa, PG, Zanetti, MV, Busatto, GF, McGorry, PD, Velakoulis, D, Pantelis, C, Wood, SJ, Mourao-Miranda, J, Nieuwenhuis, M, Schnack, HG, van Haren, NE, Kahn, RS, Lappin, J ; https://orcid.org/0000-0001-5946-2144, Dazzan, P, Morgan, C, Reinders, AA, Gutierrez-Tordesillas, D, Roiz-Santiañez, R, Crespo-Facorro, B, Schaufelberger, MS, Rosa, PG, Zanetti, MV, Busatto, GF, McGorry, PD, Velakoulis, D, Pantelis, C, Wood, SJ, and Mourao-Miranda, J
Abstract: Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n = 67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n = 97); University of São Paulo (Brazil) (n = 64); University of Cantabria, Santander (Spain) (n = 107); and University of Melbourne (Australia) (n = 54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7 years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either “continuous” (n = 94) or “remitting” (n = 118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p < 0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classificatio
Published: 2017

24. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

Author: Nieuwenhuis, M, Schnack, HG, van Haren, NE, Kahn, RS, Lappin, J, Dazzan, P, Morgan, C, Reinders, AA, Gutierrez-Tordesillas, D, Roiz-Santiañez, R, Crespo-Facorro, B, Schaufelberger, MS, Rosa, PG, Zanetti, MV, Busatto, GF, McGorry, PD, Velakoulis, D, Pantelis, C, Wood, SJ, Mourao-Miranda, J, Nieuwenhuis, M, Schnack, HG, van Haren, NE, Kahn, RS, Lappin, J, Dazzan, P, Morgan, C, Reinders, AA, Gutierrez-Tordesillas, D, Roiz-Santiañez, R, Crespo-Facorro, B, Schaufelberger, MS, Rosa, PG, Zanetti, MV, Busatto, GF, McGorry, PD, Velakoulis, D, Pantelis, C, Wood, SJ, and Mourao-Miranda, J
Abstract: Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n = 67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n = 97); University of São Paulo (Brazil) (n = 64); University of Cantabria, Santander (Spain) (n = 107); and University of Melbourne (Australia) (n = 54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7 years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either “continuous” (n = 94) or “remitting” (n = 118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p < 0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classificatio
Published: 2017

25. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

Author: Nieuwenhuis, M, Schnack, HG, van Haren, NE, Lappin, J, Morgan, C, Reinders, AA, Gutierrez-Tordesillas, D, Roiz-Santianez, R, Schaufelberger, MS, Rosa, PG, Zanetti, MV, Busatto, GF, Crespo-Facorro, B, McGorry, PD, Velakoulis, D, Pantelis, C, Wood, SJ, Kahn, RS, Mourao-Miranda, J, Dazzan, P, Nieuwenhuis, M, Schnack, HG, van Haren, NE, Lappin, J, Morgan, C, Reinders, AA, Gutierrez-Tordesillas, D, Roiz-Santianez, R, Schaufelberger, MS, Rosa, PG, Zanetti, MV, Busatto, GF, Crespo-Facorro, B, McGorry, PD, Velakoulis, D, Pantelis, C, Wood, SJ, Kahn, RS, Mourao-Miranda, J, and Dazzan, P
Abstract: Structural Magnetic Resonance Imaging (MRI) studies have attempted to use brain measures obtained at the first-episode of psychosis to predict subsequent outcome, with inconsistent results. Thus, there is a real need to validate the utility of brain measures in the prediction of outcome using large datasets, from independent samples, obtained with different protocols and from different MRI scanners. This study had three main aims: 1) to investigate whether structural MRI data from multiple centers can be combined to create a machine-learning model able to predict a strong biological variable like sex; 2) to replicate our previous finding that an MRI scan obtained at first episode significantly predicts subsequent illness course in other independent datasets; and finally, 3) to test whether these datasets can be combined to generate multicenter models with better accuracy in the prediction of illness course. The multi-center sample included brain structural MRI scans from 256 males and 133 females patients with first episode psychosis, acquired in five centers: University Medical Center Utrecht (The Netherlands) (n=67); Institute of Psychiatry, Psychology and Neuroscience, London (United Kingdom) (n=97); University of São Paulo (Brazil) (n=64); University of Cantabria, Santander (Spain) (n=107); and University of Melbourne (Australia) (n=54). All images were acquired on 1.5-Tesla scanners and all centers provided information on illness course during a follow-up period ranging 3 to 7years. We only included in the analyses of outcome prediction patients for whom illness course was categorized as either "continuous" (n=94) or "remitting" (n=118). Using structural brain scans from all centers, sex was predicted with significant accuracy (89%; p<0.001). In the single- or multi-center models, illness course could not be predicted with significant accuracy. However, when reducing heterogeneity by restricting the analyses to male patients only, classification accuracy improv
Published: 2017

26. Patterns of regional gray matter loss at different stages of schizophrenia: A multisite, cross-sectional VBM study in first-episode and chronic illness.

Author: Torres, US, Duran, FLS, Schaufelberger, MS, Crippa, JAS, Louzã, MR, Sallet, PC, Kanegusuku, CYO, Elkis, H, Gattaz, WF, Bassitt, DP, Zuardi, AW, Hallak, JEC, Leite, CC, Castro, CC, Santos, AC, Murray, RM, Busatto, GF, Torres, US, Duran, FLS, Schaufelberger, MS, Crippa, JAS, Louzã, MR, Sallet, PC, Kanegusuku, CYO, Elkis, H, Gattaz, WF, Bassitt, DP, Zuardi, AW, Hallak, JEC, Leite, CC, Castro, CC, Santos, AC, Murray, RM, and Busatto, GF
Abstract: BACKGROUND: Structural brain abnormalities in schizophrenia have been repeatedly demonstrated in magnetic resonance imaging (MRI) studies, but it remains unclear whether these are static or progressive in nature. While longitudinal MRI studies have been traditionally used to assess the issue of progression of brain abnormalities in schizophrenia, information from cross-sectional neuroimaging studies directly comparing first-episode and chronic schizophrenia patients to healthy controls may also be useful to further clarify this issue. With the recent interest in multisite mega-analyses combining structural MRI data from multiple centers aiming at increased statistical power, the present multisite voxel-based morphometry (VBM) study was carried out to examine patterns of brain structural changes according to the different stages of illness and to ascertain which (if any) of such structural abnormalities would be specifically correlated to potential clinical moderators, including cumulative exposure to antipsychotics, age of onset, illness duration and overall illness severity. METHODS: We gathered a large sample of schizophrenia patients (161, being 99 chronic and 62 first-episode) and controls (151) from four previous morphometric MRI studies (1.5 T) carried out in the same geographical region of Brazil. Image processing and analyses were conducted using Statistical Parametric Mapping (SPM8) software with the diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) algorithm. Group effects on regional gray matter (GM) volumes were investigated through whole-brain voxel-wise comparisons using General Linear Model Analysis of Co-variance (ANCOVA), always including total GM volume, scan protocol, age and gender as nuisance variables. Finally, correlation analyses were performed between the aforementioned clinical moderators and regional and global brain volumes. RESULTS: First-episode schizophrenia subjects displayed subtle volumetric deficits r
Published: 2016

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26 results on '"Busatto, GF"'

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

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

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

4. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

5. Virtual histology of cortical thickness and shared neurobiology in 6 psychiatric disorders

6. Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes

7. Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis

8. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

9. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets

10. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

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

12. Using structural MRI to identify bipolar disorders-13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

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

14. Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals (Neuropsychopharmacology, (2019), 44, 13, (2285-2293), 10.1038/s41386-019-0485-6)

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

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

17. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group.

18. Cortical abnormalities in bipolar disorder: An MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

19. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

20. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group

21. Cortical abnormalities in bipolar disorder: an MRI analysis of 6503 individuals from the ENIGMA Bipolar Disorder Working Group.

22. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

23. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

24. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

25. Multi-center MRI prediction models: Predicting sex and illness course in first episode psychosis patients

26. Patterns of regional gray matter loss at different stages of schizophrenia: A multisite, cross-sectional VBM study in first-episode and chronic illness.

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26 results on '"Busatto, GF"'

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