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3. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm.

Author

Jiang, Y, Luo, C, Wang, J, Palaniyappan, L, Chang, X, Xiang, S, Zhang, J, Duan, M, Huang, H, Gaser, C, Nemoto, K, Miura, K, Hashimoto, R, Westlye, LT, Richard, G, Fernandez-Cabello, S, Parker, N, Andreassen, OA, Kircher, T, Nenadić, I, Stein, F, Thomas-Odenthal, F, Teutenberg, L, Usemann, P, Dannlowski, U, Hahn, T, Grotegerd, D, Meinert, S, Lencer, R, Tang, Y, Zhang, T, Li, C, Yue, W, Zhang, Y, Yu, X, Zhou, E, Lin, C-P, Tsai, S-J, Rodrigue, AL, Glahn, D, Pearlson, G, Blangero, J, Karuk, A, Pomarol-Clotet, E, Salvador, R, Fuentes-Claramonte, P, Garcia-León, MÁ, Spalletta, G, Piras, F, Vecchio, D, Banaj, N, Cheng, J, Liu, Z, Yang, J, Gonul, AS, Uslu, O, Burhanoglu, BB, Uyar Demir, A, Rootes-Murdy, K, Calhoun, VD, Sim, K, Green, M, Quidé, Y, Chung, YC, Kim, W-S, Sponheim, SR, Demro, C, Ramsay, IS, Iasevoli, F, de Bartolomeis, A, Barone, A, Ciccarelli, M, Brunetti, A, Cocozza, S, Pontillo, G, Tranfa, M, Park, MTM, Kirschner, M, Georgiadis, F, Kaiser, S, Van Rheenen, TE, Rossell, SL, Hughes, M, Woods, W, Carruthers, SP, Sumner, P, Ringin, E, Spaniel, F, Skoch, A, Tomecek, D, Homan, P, Homan, S, Omlor, W, Cecere, G, Nguyen, DD, Preda, A, Thomopoulos, SI, Jahanshad, N, Cui, L-B, Yao, D, Thompson, PM, Turner, JA, van Erp, TGM, Cheng, W, ENIGMA Schizophrenia Consortium, Feng, J, ZIB Consortium, Jiang, Y, Luo, C, Wang, J, Palaniyappan, L, Chang, X, Xiang, S, Zhang, J, Duan, M, Huang, H, Gaser, C, Nemoto, K, Miura, K, Hashimoto, R, Westlye, LT, Richard, G, Fernandez-Cabello, S, Parker, N, Andreassen, OA, Kircher, T, Nenadić, I, Stein, F, Thomas-Odenthal, F, Teutenberg, L, Usemann, P, Dannlowski, U, Hahn, T, Grotegerd, D, Meinert, S, Lencer, R, Tang, Y, Zhang, T, Li, C, Yue, W, Zhang, Y, Yu, X, Zhou, E, Lin, C-P, Tsai, S-J, Rodrigue, AL, Glahn, D, Pearlson, G, Blangero, J, Karuk, A, Pomarol-Clotet, E, Salvador, R, Fuentes-Claramonte, P, Garcia-León, MÁ, Spalletta, G, Piras, F, Vecchio, D, Banaj, N, Cheng, J, Liu, Z, Yang, J, Gonul, AS, Uslu, O, Burhanoglu, BB, Uyar Demir, A, Rootes-Murdy, K, Calhoun, VD, Sim, K, Green, M, Quidé, Y, Chung, YC, Kim, W-S, Sponheim, SR, Demro, C, Ramsay, IS, Iasevoli, F, de Bartolomeis, A, Barone, A, Ciccarelli, M, Brunetti, A, Cocozza, S, Pontillo, G, Tranfa, M, Park, MTM, Kirschner, M, Georgiadis, F, Kaiser, S, Van Rheenen, TE, Rossell, SL, Hughes, M, Woods, W, Carruthers, SP, Sumner, P, Ringin, E, Spaniel, F, Skoch, A, Tomecek, D, Homan, P, Homan, S, Omlor, W, Cecere, G, Nguyen, DD, Preda, A, Thomopoulos, SI, Jahanshad, N, Cui, L-B, Yao, D, Thompson, PM, Turner, JA, van Erp, TGM, Cheng, W, ENIGMA Schizophrenia Consortium, Feng, J, and ZIB Consortium

Abstract

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Published
2024

4. Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Author

McWhinney, SR, Hlinka, J, Bakstein, E, Dietze, LMF, Corkum, ELV, Abé, C, Alda, M, Alexander, N, Benedetti, F, Berk, M, Bøen, E, Bonnekoh, LM, Boye, B, Brosch, K, Canales-Rodríguez, EJ, Cannon, DM, Dannlowski, U, Demro, C, Diaz-Zuluaga, A, Elvsåshagen, T, Eyler, LT, Fortea, L, Fullerton, JM, Goltermann, J, Gotlib, IH, Grotegerd, D, Haarman, B, Hahn, T, Howells, FM, Jamalabadi, H, Jansen, A, Kircher, T, Klahn, AL, Kuplicki, R, Lahud, E, Landén, M, Leehr, EJ, Lopez-Jaramillo, C, Mackey, S, Malt, U, Martyn, F, Mazza, E, McDonald, C, McPhilemy, G, Meier, S, Meinert, S, Melloni, E, Mitchell, PB, Nabulsi, L, Nenadić, I, Nitsch, R, Opel, N, Ophoff, RA, Ortuño, M, Overs, BJ, Pineda-Zapata, J, Pomarol-Clotet, E, Radua, J, Repple, J, Roberts, G, Rodriguez-Cano, E, Sacchet, MD, Salvador, R, Savitz, J, Scheffler, F, Schofield, PR, Schürmeyer, N, Shen, C, Sim, K, Sponheim, SR, Stein, DJ, Stein, F, Straube, B, Suo, C, Temmingh, H, Teutenberg, L, Thomas-Odenthal, F, Thomopoulos, SI, Urosevic, S, Usemann, P, van Haren, NEM, Vargas, C, Vieta, E, Vilajosana, E, Vreeker, A, Winter, NR, Yatham, LN, Thompson, PM, Andreassen, OA, Ching, CRK, Hajek, T, McWhinney, SR, Hlinka, J, Bakstein, E, Dietze, LMF, Corkum, ELV, Abé, C, Alda, M, Alexander, N, Benedetti, F, Berk, M, Bøen, E, Bonnekoh, LM, Boye, B, Brosch, K, Canales-Rodríguez, EJ, Cannon, DM, Dannlowski, U, Demro, C, Diaz-Zuluaga, A, Elvsåshagen, T, Eyler, LT, Fortea, L, Fullerton, JM, Goltermann, J, Gotlib, IH, Grotegerd, D, Haarman, B, Hahn, T, Howells, FM, Jamalabadi, H, Jansen, A, Kircher, T, Klahn, AL, Kuplicki, R, Lahud, E, Landén, M, Leehr, EJ, Lopez-Jaramillo, C, Mackey, S, Malt, U, Martyn, F, Mazza, E, McDonald, C, McPhilemy, G, Meier, S, Meinert, S, Melloni, E, Mitchell, PB, Nabulsi, L, Nenadić, I, Nitsch, R, Opel, N, Ophoff, RA, Ortuño, M, Overs, BJ, Pineda-Zapata, J, Pomarol-Clotet, E, Radua, J, Repple, J, Roberts, G, Rodriguez-Cano, E, Sacchet, MD, Salvador, R, Savitz, J, Scheffler, F, Schofield, PR, Schürmeyer, N, Shen, C, Sim, K, Sponheim, SR, Stein, DJ, Stein, F, Straube, B, Suo, C, Temmingh, H, Teutenberg, L, Thomas-Odenthal, F, Thomopoulos, SI, Urosevic, S, Usemann, P, van Haren, NEM, Vargas, C, Vieta, E, Vilajosana, E, Vreeker, A, Winter, NR, Yatham, LN, Thompson, PM, Andreassen, OA, Ching, CRK, and Hajek, T

Abstract

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associati

Published
2024

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

Author

Groenewold, NA, Bas-Hoogendam, JM, Amod, AR, Laansma, MA, Van Velzen, LS, Aghajani, M, Hilbert, K, Oh, H, Salas, R, Jackowski, AP, Pan, PM, Salum, GA, Blair, JR, Blair, KS, Hirsch, J, Pantazatos, SP, Schneier, FR, Talati, A, Roelofs, K, Volman, I, Blanco-Hinojo, L, Cardoner, N, Pujol, J, Beesdo-Baum, K, Ching, CRK, Thomopoulos, SI, Jansen, A, Kircher, T, Krug, A, Nenadić, I, Stein, F, Dannlowski, U, Grotegerd, D, Lemke, H, Meinert, S, Winter, A, Erb, M, Kreifelts, B, Gong, Q, Lui, S, Zhu, F, Mwangi, B, Soares, JC, Wu, M-J, Bayram, A, Canli, M, Tükel, R, Westenberg, PM, Heeren, A, Cremers, HR, Hofmann, D, Straube, T, Doruyter, AGG, Lochner, C, Peterburs, J, Van Tol, M-J, Gur, RE, Kaczkurkin, AN, Larsen, B, Satterthwaite, TD, Filippi, CA, Gold, AL, Harrewijn, A, Zugman, A, Bülow, R, Grabe, HJ, Völzke, H, Wittfeld, K, Böhnlein, J, Dohm, K, Kugel, H, Schrammen, E, Zwanzger, P, Leehr, EJ, Sindermann, L, Ball, TM, Fonzo, GA, Paulus, MP, Simmons, A, Stein, MB, Klumpp, H, Phan, KL, Furmark, T, Månsson, KNT, Manzouri, A, Avery, SN, Blackford, JU, Clauss, JA, Feola, B, Harper, JC, Sylvester, CM, Lueken, U, Veltman, DJ, Winkler, AM, Jahanshad, N, Pine, DS, Thompson, PM, Stein, DJ, Van der Wee, NJA, Groenewold, NA, Bas-Hoogendam, JM, Amod, AR, Laansma, MA, Van Velzen, LS, Aghajani, M, Hilbert, K, Oh, H, Salas, R, Jackowski, AP, Pan, PM, Salum, GA, Blair, JR, Blair, KS, Hirsch, J, Pantazatos, SP, Schneier, FR, Talati, A, Roelofs, K, Volman, I, Blanco-Hinojo, L, Cardoner, N, Pujol, J, Beesdo-Baum, K, Ching, CRK, Thomopoulos, SI, Jansen, A, Kircher, T, Krug, A, Nenadić, I, Stein, F, Dannlowski, U, Grotegerd, D, Lemke, H, Meinert, S, Winter, A, Erb, M, Kreifelts, B, Gong, Q, Lui, S, Zhu, F, Mwangi, B, Soares, JC, Wu, M-J, Bayram, A, Canli, M, Tükel, R, Westenberg, PM, Heeren, A, Cremers, HR, Hofmann, D, Straube, T, Doruyter, AGG, Lochner, C, Peterburs, J, Van Tol, M-J, Gur, RE, Kaczkurkin, AN, Larsen, B, Satterthwaite, TD, Filippi, CA, Gold, AL, Harrewijn, A, Zugman, A, Bülow, R, Grabe, HJ, Völzke, H, Wittfeld, K, Böhnlein, J, Dohm, K, Kugel, H, Schrammen, E, Zwanzger, P, Leehr, EJ, Sindermann, L, Ball, TM, Fonzo, GA, Paulus, MP, Simmons, A, Stein, MB, Klumpp, H, Phan, KL, Furmark, T, Månsson, KNT, Manzouri, A, Avery, SN, Blackford, JU, Clauss, JA, Feola, B, Harper, JC, Sylvester, CM, Lueken, U, Veltman, DJ, Winkler, AM, Jahanshad, N, Pine, DS, Thompson, PM, Stein, DJ, and Van der Wee, NJA

Abstract

There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, pFWE = 0.037; right: d = -0.104, pFWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, pFWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, pFWE < 0.001; right: d = -0.158, pFWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, pFWE = 0.006; right: d = 0.099, pFWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood.

Published
2023

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

Author

Schijven, Dick, Postema, M.C., Fukunaga, M., Matsumoto, J., Miura, K., Zwarte, S.M.C. de, Haren, N.E.M. van, Cahn, W., Hulshoff Pol, H.E., Kahn, R.S., Ayesa-Arriola, R., Ortoz-García de la Foz, V., Tordesillas-Gutierrez, D., Vázquez-Bourgon, J., Crespo-Facorro, B., Alnæs, D., Dahl, A., Westlye, L.T., Agartz, I., Andreassen, O.A., Jönsson, E.G., Kochunov, P., Bruggemann, J.M., Catts, S.V., Michie, P.T., Mowry, B.J., Quidé, Y., Rasser, P.E., Schall, U., Scott, R.J., Carr, V.J., Green, M.J., Henskens, F.A., Loughland, C.M., Pantelis, C., Weickert, C.S., Weickert, T.W., Haan, L. de, Brosch, K., Pfarr, J.K., Ringwald, K.G., Stein, F., Jansen, Andreas, Kircher, T.T.J., Nenadić, I., Krämer, Bernd, Gruber, O., Satterthwaite, T.D., Bustillo, J., Mathalon, D.H., Preda, A., Calhoun, V.D., Ford, J.M., Potkin, S.G., Chen, Jingxu, Tan, Yunlong, Wang, Zhiren, Xiang, Hong, Fan, Fengmei, Bernardoni, F., Ehrlich, S., Fuentes-Claramonte, P., Garcia-Leon, M.A., Guerrero-Pedraza, A., Salvador, R., Sarró, S., Pomarol-Clotet, E., Ciullo, V., Piras, F., Vecchio, D., Banaj, N., Spalletta, G., Michielse, S., Amelsvoort, T. van, Dickie, E.W., Voineskos, A.N., Sim, K., Ciufolini, S., Dazzan, P., Murray, R.M., Kim, W.S., Chung, Y.C., Andreou, C., Schmidt, A, Borgwardt, S., McIntosh, A.M., Whalley, H.C., Lawrie, S.M., Plessis, S. du, Luckhoff, H.K., Scheffler, F., Emsley, R., Grotegerd, D., Lencer, R., Dannlowski, U., Edmond, J.T., Rootes-Murdy, K., Stephen, J.M., Mayer, A.R., Antonucci, L.A., Fazio, L., Pergola, G., Bertolino, A., Díaz-Caneja, C.M., Janssen, J, Lois, N.G., Arango, C., Tomyshev, A.S., Lebedeva, I., Cervenka, S., Sellgren, C.M., Georgiadis, F., Kirschner, M., Kaiser, S., Hajek, T., Skoch, A., Spaniel, F., Kim, M., Kwak, Y.B., Oh, S., Kwon, J.S., James, A., Bakker, G., Knöchel, C., Stäblein, M., Oertel, V., Uhlmann, A., Howells, F.M., Stein, D.J., Temmingh, H.S., Diaz-Zuluaga, A.M., Pineda-Zapata, J.A., López-Jaramillo, C., Homan, S., Ji, E., Surbeck, W., Homan, P., Fisher, S.E., Franke, B., Glahn, D.C., Gur, R.C., Hashimoto, R., Jahanshad, N., Luders, E., Medland, S.E., Thompson, P.M., Turner, J.A., Erp, T.G. van, Francks, C., Schijven, Dick, Postema, M.C., Fukunaga, M., Matsumoto, J., Miura, K., Zwarte, S.M.C. de, Haren, N.E.M. van, Cahn, W., Hulshoff Pol, H.E., Kahn, R.S., Ayesa-Arriola, R., Ortoz-García de la Foz, V., Tordesillas-Gutierrez, D., Vázquez-Bourgon, J., Crespo-Facorro, B., Alnæs, D., Dahl, A., Westlye, L.T., Agartz, I., Andreassen, O.A., Jönsson, E.G., Kochunov, P., Bruggemann, J.M., Catts, S.V., Michie, P.T., Mowry, B.J., Quidé, Y., Rasser, P.E., Schall, U., Scott, R.J., Carr, V.J., Green, M.J., Henskens, F.A., Loughland, C.M., Pantelis, C., Weickert, C.S., Weickert, T.W., Haan, L. de, Brosch, K., Pfarr, J.K., Ringwald, K.G., Stein, F., Jansen, Andreas, Kircher, T.T.J., Nenadić, I., Krämer, Bernd, Gruber, O., Satterthwaite, T.D., Bustillo, J., Mathalon, D.H., Preda, A., Calhoun, V.D., Ford, J.M., Potkin, S.G., Chen, Jingxu, Tan, Yunlong, Wang, Zhiren, Xiang, Hong, Fan, Fengmei, Bernardoni, F., Ehrlich, S., Fuentes-Claramonte, P., Garcia-Leon, M.A., Guerrero-Pedraza, A., Salvador, R., Sarró, S., Pomarol-Clotet, E., Ciullo, V., Piras, F., Vecchio, D., Banaj, N., Spalletta, G., Michielse, S., Amelsvoort, T. van, Dickie, E.W., Voineskos, A.N., Sim, K., Ciufolini, S., Dazzan, P., Murray, R.M., Kim, W.S., Chung, Y.C., Andreou, C., Schmidt, A, Borgwardt, S., McIntosh, A.M., Whalley, H.C., Lawrie, S.M., Plessis, S. du, Luckhoff, H.K., Scheffler, F., Emsley, R., Grotegerd, D., Lencer, R., Dannlowski, U., Edmond, J.T., Rootes-Murdy, K., Stephen, J.M., Mayer, A.R., Antonucci, L.A., Fazio, L., Pergola, G., Bertolino, A., Díaz-Caneja, C.M., Janssen, J, Lois, N.G., Arango, C., Tomyshev, A.S., Lebedeva, I., Cervenka, S., Sellgren, C.M., Georgiadis, F., Kirschner, M., Kaiser, S., Hajek, T., Skoch, A., Spaniel, F., Kim, M., Kwak, Y.B., Oh, S., Kwon, J.S., James, A., Bakker, G., Knöchel, C., Stäblein, M., Oertel, V., Uhlmann, A., Howells, F.M., Stein, D.J., Temmingh, H.S., Diaz-Zuluaga, A.M., Pineda-Zapata, J.A., López-Jaramillo, C., Homan, S., Ji, E., Surbeck, W., Homan, P., Fisher, S.E., Franke, B., Glahn, D.C., Gur, R.C., Hashimoto, R., Jahanshad, N., Luders, E., Medland, S.E., Thompson, P.M., Turner, J.A., Erp, T.G. van, and Francks, C.

Abstract

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

Published
2023

9. Social support in major depression: association with cognitive performance, whiter matter integrity, and disease course

Author

Flinkenflügel, K., primary, Meinert, S., additional, Thiel, K., additional, Winter, A., additional, Goltermann, J., additional, Brosch, K., additional, Stein, F., additional, Thomas-Odenthal, F., additional, Evermann, U., additional, Wroblewski, A., additional, Usemann, P., additional, Grotegerd, D., additional, Hahn, T., additional, Leehr, E.J., additional, Dohm, K., additional, Bauer, J., additional, Jamalabadi, H., additional, Straube, B., additional, Alexander, N., additional, Jansen, A., additional, Nenadić, I., additional, Kircher, T., additional, and Dannlowski, U., additional

Published
2023
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10. The impact of cognitive reserve on cognition, connectome pathology, and disease course in depression

Author

Gruber, M., primary, Klein, H., additional, Mauritz, M., additional, De Lange, S.C., additional, Grumbach, P., additional, Goltermann, J., additional, Winter, N.R., additional, Thiel, K., additional, Winter, A., additional, Flinkenflügel, K., additional, Borgers, T., additional, Enneking, V., additional, Klug, M., additional, Stein, F., additional, Brosch, K., additional, Usemann, P., additional, Thomas-Odenthal, F., additional, Wroblewski, A., additional, Steinsträter, O., additional, Pfarr, J.K., additional, Evermann, U., additional, Meinert, S., additional, Grotegerd, D., additional, Opel, N., additional, Hahn, T., additional, Leehr, E.J., additional, Bauer, J., additional, Reif, A., additional, Jansen, A., additional, Krug, A., additional, Nenadić, I., additional, Kircher, T., additional, Van den Heuvel, M.P., additional, Dannlowski, U., additional, and Repple, J., additional

Published
2023
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11. Trait, state or scar: brain structural differences in major depressive disorder using a converter sample

Author

Kraus, A., primary, Meinert, S., additional, Winter, A., additional, Thiel, K., additional, Flinkenflügel, K., additional, Grotegerd, D., additional, Goltermann, J., additional, Leehr, E.J., additional, Hahn, T., additional, Alexander, N., additional, Stein, F., additional, Brosch, K., additional, Usemann, P., additional, Teutenberg, L., additional, Thomas-Odenthal, F., additional, Jansen, A., additional, Nenadić, I., additional, Kircher, T., additional, Dohm, K., additional, and Dannlowski, U., additional

Published
2023
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12. Fiber microstructural differences in bipolar disorder types I and II: association with disease course and polygenic risk

Author

Thiel, K., primary, Lemke, H., additional, Winter, A., additional, Flinkenflügel, K., additional, Meinert, S., additional, Grotegerd, D., additional, Goltermann, J., additional, Leehr, E.J., additional, Dohm, K., additional, Kraus, A., additional, Hahn, T., additional, Brosch, K., additional, Evermann, U., additional, Pfarr, J.K., additional, Ringwald, K.G., additional, Stein, F., additional, Straube, B., additional, Teutenberg, L., additional, Thomas-Odenthal, F., additional, Usemann, P., additional, Wroblewski, A., additional, Alexander, N., additional, Jansen, A., additional, David, F., additional, Forstner, A., additional, Nenadić, I., additional, Kircher, T., additional, and Dannlowski, U., additional

Published
2023
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18. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author

Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, Michael, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, Michael, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M

Published
2022

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

Author

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

Published
2022

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

Author

Haukvik, U.K., Gurholt, T.P., Nerland, S., Elvsåshagen, T., Akudjedu, T.N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B.T., Benedetti, F. De, Berk, M., Bettella, F., Bøen, E., Bonnín, C.M., Brambilla, P., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Erp, T.G. van, Fatjó-Vilas, M., Foley, S.F., Förster, K., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Gruber, O., Haarman, B.C.M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E.L., Howells, F.M., Hülsmann, C., Jahanshad, N., Jørgensen, K.N., Kircher, T., Krämer, B., Krug, A., Kuplicki, R., Lagerberg, T.V., Lancaster, T.M., Lenroot, R.K., Lonning, V., López-Jaramillo, C., Malt, U.F., McDonald, C., McIntosh, A.M., McPhilemy, G., Meer, D. van der, Melle, I., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M.C.G., Overs, B.J., Pineda-Zapata, J.A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M.M., Roberts, G., Ruhe, H.G., Salminen, L.E., Salvador, R., Sarró, S., Savitz, J., Schene, A.H., Sim, K., Soeiro-de-Souza, M.G., Stäblein, M., Stein, D.J., Stein, F., Tamnes, C.K., Temmingh, H.S., Thomopoulos, S.I., Veltman, D.J., Vieta, E., Waltemate, L., Westlye, L.T., Whalley, H.C., Sämann, P.G., Thompson, P.M., Ching, C.R., Andreassen, O.A., Agartz, I., Haukvik, U.K., Gurholt, T.P., Nerland, S., Elvsåshagen, T., Akudjedu, T.N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B.T., Benedetti, F. De, Berk, M., Bettella, F., Bøen, E., Bonnín, C.M., Brambilla, P., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Erp, T.G. van, Fatjó-Vilas, M., Foley, S.F., Förster, K., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Gruber, O., Haarman, B.C.M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E.L., Howells, F.M., Hülsmann, C., Jahanshad, N., Jørgensen, K.N., Kircher, T., Krämer, B., Krug, A., Kuplicki, R., Lagerberg, T.V., Lancaster, T.M., Lenroot, R.K., Lonning, V., López-Jaramillo, C., Malt, U.F., McDonald, C., McIntosh, A.M., McPhilemy, G., Meer, D. van der, Melle, I., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M.C.G., Overs, B.J., Pineda-Zapata, J.A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M.M., Roberts, G., Ruhe, H.G., Salminen, L.E., Salvador, R., Sarró, S., Savitz, J., Schene, A.H., Sim, K., Soeiro-de-Souza, M.G., Stäblein, M., Stein, D.J., Stein, F., Tamnes, C.K., Temmingh, H.S., Thomopoulos, S.I., Veltman, D.J., Vieta, E., Waltemate, L., Westlye, L.T., Whalley, H.C., Sämann, P.G., Thompson, P.M., Ching, C.R., Andreassen, O.A., and Agartz, I.

Abstract

Contains fulltext : 252169.pdf (Publisher’s version ) (Open Access), The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder (BD). Here we, the Enhancing NeuroImaging Genetics through Meta-Analysis Bipolar Disorder workinggroup, study hippocampal subfield volumetry in BD. T1-weighted magnetic resonance imaging scans from 4,698 individuals (BD = 1,472, healthy controls [HC] = 3,226) from 23 sites worldwide were processed with FreeSurfer. We used linear mixed-effects models and mega-analysis to investigate differences in hippocampal subfield volumes between BD and HC, followed by analyses of clinical characteristics and medication use. BD showed significantly smaller volumes of the whole hippocampus (Cohen's d = -0.20), cornu ammonis (CA)1 (d = -0.18), CA2/3 (d = -0.11), CA4 (d = -0.19), molecular layer (d = -0.21), granule cell layer of dentate gyrus (d = -0.21), hippocampal tail (d = -0.10), subiculum (d = -0.15), presubiculum (d = -0.18), and hippocampal amygdala transition area (d = -0.17) compared to HC. Lithium users did not show volume differences compared to HC, while non-users did. Antipsychotics or antiepileptic use was associated with smaller volumes. In this largest study of hippocampal subfields in BD to date, we show widespread reductions in nine of 12 subfields studied. The associations were modulated by medication use and specifically the lack of differences between lithium users and HC supports a possible protective role of lithium in BD.

Published
2022

21. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A., Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.-M., Landén, M., Landrø, N.I., Lawrie, S., Lebedeva, I., Luna, B., Lundervold, A.J., MacMaster, F.P., Maglanoc, L.A., Mathalon, D.H., McDonald, C., McIntosh, A., Meinert, S., Michie, P.T., Mitchell, P., Moreno-Alcázar, A., Mowry, B., Muratori, F., Nabulsi, L., Nenadić, I., O'Gorman Tuura, R., Oosterlaan, J., Overs, B., Pantelis, C., Parellada, M., Pariente, J.C., Pauli, P., Pergola, G., Piarulli, F.M., Picon, F., Piras, F., Pomarol-Clotet, E., Pretus, C., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Reif, A., Retico, A., Roberts, G., Rossell, S., Rovaris, D.L., Rubia, K., Sacchet, M., Salavert, J., Salvador, R., Sarró, S., Sawa, A., Schall, U., Scott, R., Selvaggi, P., Silk, T., Sim, K., Skoch, A., Spalletta, G., Spaniel, F., Stein, D.J., Steinsträter, O., Stolicyn, A., Takayanagi, Y., Tamm, L., Tavares, M., Teumer, A., Thiel, K., Thomopoulos, S.I., Tomecek, D., Tomyshev, A.S., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Rheenen, T., Vazquez-Bourgón, J., Vernooij, M.W., Vieta, E., Vilarroya, O., Weickert, C., Weickert, T., Westlye, L.T., Whalley, H., Willinger, D., Winter, A., Wittfeld, K., Yang, T.T., Yoncheva, Y., Zijlmans, J.L., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J., Ching, C.R.K., Andreassen, O.A., Pozzi, E., Veltman, D., Schmaal, L., van Erp, T.G.M., Turner, J., Castellanos, F.X., Pausova, Z., Thompson, P., Paus, T., Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A., Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.-M., Landén, M., Landrø, N.I., Lawrie, S., Lebedeva, I., Luna, B., Lundervold, A.J., MacMaster, F.P., Maglanoc, L.A., Mathalon, D.H., McDonald, C., McIntosh, A., Meinert, S., Michie, P.T., Mitchell, P., Moreno-Alcázar, A., Mowry, B., Muratori, F., Nabulsi, L., Nenadić, I., O'Gorman Tuura, R., Oosterlaan, J., Overs, B., Pantelis, C., Parellada, M., Pariente, J.C., Pauli, P., Pergola, G., Piarulli, F.M., Picon, F., Piras, F., Pomarol-Clotet, E., Pretus, C., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Reif, A., Retico, A., Roberts, G., Rossell, S., Rovaris, D.L., Rubia, K., Sacchet, M., Salavert, J., Salvador, R., Sarró, S., Sawa, A., Schall, U., Scott, R., Selvaggi, P., Silk, T., Sim, K., Skoch, A., Spalletta, G., Spaniel, F., Stein, D.J., Steinsträter, O., Stolicyn, A., Takayanagi, Y., Tamm, L., Tavares, M., Teumer, A., Thiel, K., Thomopoulos, S.I., Tomecek, D., Tomyshev, A.S., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Rheenen, T., Vazquez-Bourgón, J., Vernooij, M.W., Vieta, E., Vilarroya, O., Weickert, C., Weickert, T., Westlye, L.T., Whalley, H., Willinger, D., Winter, A., Wittfeld, K., Yang, T.T., Yoncheva, Y., Zijlmans, J.L., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J., Ching, C.R.K., Andreassen, O.A., Pozzi, E., Veltman, D., Schmaal, L., van Erp, T.G.M., Turner, J., Castellanos, F.X., Pausova, Z., Thompson, P., and Paus, T.

Abstract

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

Published
2022
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22. CROATIA. Critical junctures in the media transformation process

Author

Peruško, Z., Vozab, D., and Nenadić, I.

Abstract

The present study details the critical junctures in the transformations of risks and opportunities in the four domains of media systems – the Legal and ethical environment, Journalism, Media usage, and Media-related competencies domain – that are expected to contribute to or deter from deliberative communication. Study includes a background chapter on social and political changes that influenced the four key domains Croatia. The study is based on the literature and other data sources identified in Case study 1 “Risks and Opportunities Related to Media and Journalism Studies (2000–2020). Case Study on National Research and Monitoring Capabilities”, but goes beyond it by offering an in-depth analyses of changes within each domain and identifying the actors behind them. Legal framework in Croatia is in most respects in accordance with European standards, but a degree of conflicting legislation exists regarding defamation offences. Frequent legislative changes (although most without a change of direction) show that a coherent policy-led system has not yet materialized. Evidence of hybridity of the media system is seen in media and related practices, which take place in a diverse yet highly concentrated media system, most similar to the Mediterranean polarized pluralist media system model from the Hallin and Mancini (2004) typology. Media-related competencies and media literacy appear to be higher in some areas and population groups than in others. Journalism market is diverse although subject to economic constrictions as well as pressures on journalists in the form of many SLAPP lawsuits.

Published
2022

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

Author

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

Published
2022
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26. Cognitive performance and brain structural connectome alterations in major depressive disorder

Author

Gruber, M., Mauritz, M., Meinert, S., Grotegerd, D., de Lange, S.C., Grumbach, P., Goltermann, J., Winter, N.R., Waltemate, L., Lemke, H., Thiel, K., Winter, A., Breuer, F., Borgers, T., Enneking, V., Klug, M., Brosch, K., Meller, T., Pfarr, J.K., Ringwald, K.G., Stein, F., Opel, N., Redlich, R., Hahn, T., Leehr, E.J., Bauer, J., Nenadic, I., Kircher, T., van den Heuvel, M.P., Dannlowski, U., and Repple, J.

Published
2022
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27. P.0277 Mood state effects on fractional anisotropy in bipolar disorder

Author

Thiel, K., primary, Meinert, S., additional, Winter, A., additional, Lemke, H., additional, Waltemate, L., additional, Brosch, K., additional, Meller, T., additional, Pfarr, J.K., additional, Ringwald, K.G., additional, Schmitt, S., additional, Stein, F., additional, Nenadić, I., additional, Kircher, T., additional, and Dannlowski, U., additional

Published
2021
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28. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author

Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, J-K, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, J-K, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M

Published
2021

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

Author

Radua, J, Vieta, E, Shinohara, R, Kochunov, P, Quidé, Y, Green, MJ, Weickert, CS, Weickert, T, Bruggemann, J, Kircher, T, Nenadić, I, Cairns, MJ, Seal, M, Schall, U, Henskens, F, Fullerton, JM, Mowry, B, Pantelis, C, Lenroot, R, Cropley, V, Loughland, C, Scott, R, Wolf, D, Satterthwaite, TD, Tan, Y, Sim, K, Piras, F, Spalletta, G, Banaj, N, Pomarol-Clotet, E, Solanes, A, Albajes-Eizagirre, A, Canales-Rodríguez, EJ, Sarro, S, Di Giorgio, A, Bertolino, A, Stäblein, M, Oertel, V, Knöchel, C, Borgwardt, S, du Plessis, S, Yun, JY, Kwon, JS, Dannlowski, U, Hahn, T, Grotegerd, D, Alloza, C, Arango, C, Janssen, J, Díaz-Caneja, C, Jiang, W, Calhoun, V, Ehrlich, S, Yang, K, Cascella, NG, Takayanagi, Y, Sawa, A, Tomyshev, A, Lebedeva, I, Kaleda, V, Kirschner, M, Hoschl, C, Tomecek, D, Skoch, A, van Amelsvoort, T, Bakker, G, James, A, Preda, A, Weideman, A, Stein, DJ, Howells, F, Uhlmann, A, Temmingh, H, López-Jaramillo, C, Díaz-Zuluaga, A, Fortea, L, Martinez-Heras, E, Solana, E, Llufriu, S, Jahanshad, N, Thompson, P, Turner, J, van Erp, T, Glahn, D, Pearlson, G, Hong, E, Krug, A, Carr, V, Tooney, P, Cooper, G, Rasser, P, Michie, P, Catts, S, Gur, R, Yang, F, Fan, F, Chen, J, Guo, H, Tan, S, Radua, J, Vieta, E, Shinohara, R, Kochunov, P, Quidé, Y, Green, MJ, Weickert, CS, Weickert, T, Bruggemann, J, Kircher, T, Nenadić, I, Cairns, MJ, Seal, M, Schall, U, Henskens, F, Fullerton, JM, Mowry, B, Pantelis, C, Lenroot, R, Cropley, V, Loughland, C, Scott, R, Wolf, D, Satterthwaite, TD, Tan, Y, Sim, K, Piras, F, Spalletta, G, Banaj, N, Pomarol-Clotet, E, Solanes, A, Albajes-Eizagirre, A, Canales-Rodríguez, EJ, Sarro, S, Di Giorgio, A, Bertolino, A, Stäblein, M, Oertel, V, Knöchel, C, Borgwardt, S, du Plessis, S, Yun, JY, Kwon, JS, Dannlowski, U, Hahn, T, Grotegerd, D, Alloza, C, Arango, C, Janssen, J, Díaz-Caneja, C, Jiang, W, Calhoun, V, Ehrlich, S, Yang, K, Cascella, NG, Takayanagi, Y, Sawa, A, Tomyshev, A, Lebedeva, I, Kaleda, V, Kirschner, M, Hoschl, C, Tomecek, D, Skoch, A, van Amelsvoort, T, Bakker, G, James, A, Preda, A, Weideman, A, Stein, DJ, Howells, F, Uhlmann, A, Temmingh, H, López-Jaramillo, C, Díaz-Zuluaga, A, Fortea, L, Martinez-Heras, E, Solana, E, Llufriu, S, Jahanshad, N, Thompson, P, Turner, J, van Erp, T, Glahn, D, Pearlson, G, Hong, E, Krug, A, Carr, V, Tooney, P, Cooper, G, Rasser, P, Michie, P, Catts, S, Gur, R, Yang, F, Fan, F, Chen, J, Guo, H, and Tan, S

Abstract

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

Published
2020

34. P.328 Replication of effects of cumulative illness severity on hippocampal gray matter volume in the FOR2107 cohort

Author

Lemke, H., Förster, K., Waltemate, L., Meinert, S., Stein, F., Brosch, K., Fingas, S., Romankiewicz, L., Grotegerd, D., Redlich, R., Koch, K., Leehr, E., Böhnlein, J., Goltermann, J., Winter, N., Enneking, V., Opel, N., Emden, D., Repple, J., Leenings, R., Kaehler, C., Hahn, T., Schmitt, S., Meller, T., Jansen, A., Krug, A., Kircher, T., Nenadic, I., Baune, B.T., and Dannlowski, U.

Published
2020
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36. The Impact of Polygenic Risk for Schizophrenia on Memory-related Activation in the Anterior Cingulate Cortex (ACC)

Author

Schmitt, S, additional, Sauder, T, additional, Meier, F, additional, Engelen, J, additional, Bröhl, H, additional, Dietsche, B, additional, Heinen, J, additional, Yüksel, D, additional, Zaremba, D, additional, Meinert, S, additional, Dohm, K, additional, Förster, K, additional, Bürger, C, additional, Redlich, R, additional, Dannlowski, U, additional, Kircher, T, additional, Krug, A, additional, and Nenadić, I, additional

Published
2017
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37. The Impact of a Polygenic Risk for Bipolar Disorder on Memory-related Activation in the Precuneus

Author

Sauder, T, additional, Schmitt, S, additional, Meier, F, additional, Engelen, J, additional, Bröhl, H, additional, Yüksel, D, additional, Heinen, J, additional, Dietsche, B, additional, Zaremba, D, additional, Meinert, S, additional, Bürger, C, additional, Dohm, K, additional, Förster, K, additional, Redlich, R, additional, Dannlowski, U, additional, Kircher, T, additional, Krug, A, additional, and Nenadić, I, additional

Published
2017
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44. Duplications in RB1CC1 are associated with schizophrenia; identification in large European sample sets

Author

Degenhardt, F, Priebe, L, Meier, S, Lennertz, L, Streit, F, Witt, S H, Hofmann, A, Becker, T, Mössner, R, Maier, W, Nenadic, I, Sauer, H, Mattheisen, M, Buizer-Voskamp, J, Ophoff, R A, Rujescu, D, Giegling, I, Ingason, A, Wagner, M, Delobel, B, Andrieux, J, Meyer-Lindenberg, A, Heinz, A, Walter, H, Moebus, S, Corvin, A, Kahn, René S, Linszen, Don H, van Os, Jim, Wiersma, Durk, Bruggeman, Richard, Cahn, Wiepke, de Haan, Lieuwe, Krabbendam, Lydia, Myin-Germeys, Inez, Rietschel, M, Nöthen, M M, and Cichon, S

Subjects
exome-sequencing, intellectual disability, schizoaffective disorder
Abstract

Schizophrenia (SCZ) is a severe and debilitating neuropsychiatric disorder with an estimated heritability of ~80%. Recently, de novo mutations, identified by next-generation sequencing (NGS) technology, have been suggested to contribute to the risk of developing SCZ. Although these studies show an overall excess of de novo mutations among patients compared with controls, it is not easy to pinpoint specific genes hit by de novo mutations as actually involved in the disease process. Importantly, support for a specific gene can be provided by the identification of additional alterations in several independent patients. We took advantage of existing genome-wide single-nucleotide polymorphism data sets to screen for deletions or duplications (copy number variations, CNVs) in genes previously implicated by NGS studies. Our approach was based on the observation that CNVs constitute part of the mutational spectrum in many human disease-associated genes. In a discovery step, we investigated whether CNVs in 55 candidate genes, suggested from NGS studies, were more frequent among 1637 patients compared with 1627 controls. Duplications in RB1CC1 were overrepresented among patients. This finding was followed-up in large, independent European sample sets. In the combined analysis, totaling 8461 patients and 112 871 controls, duplications in RB1CC1 were found to be associated with SCZ (P=1.29 × 10−5; odds ratio=8.58). Our study provides evidence for rare duplications in RB1CC1 as a risk factor for SCZ.

Published
2013
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46. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author

Abe, C., Ching, C.R.K., Liberg, B., Lebedev, A.V., Agartz, I., Akudjedu, Theophilus. N., Alda, M., Alnæs, D., Alonso-Lana, S., Benedetti, F., Berk, M., Bøen, E., Bonnin, C.D.M., Breuer, F., Brosch, K., Brouwer, R.M., Canales-Rodríguez, E.J., Cannon, D.M., Chye, Y., Dahl, A., Dandash, O., Dannlowski, U., Dohm, K., Elvsåshagen, T., Fisch, L., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Haatveit, B., Hahn, T., Hajek, T., Heindel, W., Ingvar, M., Sim, K., Kircher, T.T.J., Lenroot, R.K., Malt, U.F., McDonald, C., McWhinney, S.R., Melle, I., Meller, T., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Opel, N., Overs, B.J., Panicalli, F., Pfarr, J.K., Poletti, S., Pomarol-Clotet, E., Radua, J., Repple, J., Ringwald, K.G., Roberts, G., Rodriguez-Cano, E., Salvador, R., Sarink, K., Sarró, S., Schmitt, S., Stein, F., Suo, C., Thomopoulos, S.I., Tronchin, G., Vieta, E., Westlye, L.T., White, A.G., Yatham, L.N., Zak, N., Thompson, P.M., Andreassen, O.A., Landen, M., Abe, C., Ching, C.R.K., Liberg, B., Lebedev, A.V., Agartz, I., Akudjedu, Theophilus. N., Alda, M., Alnæs, D., Alonso-Lana, S., Benedetti, F., Berk, M., Bøen, E., Bonnin, C.D.M., Breuer, F., Brosch, K., Brouwer, R.M., Canales-Rodríguez, E.J., Cannon, D.M., Chye, Y., Dahl, A., Dandash, O., Dannlowski, U., Dohm, K., Elvsåshagen, T., Fisch, L., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Haatveit, B., Hahn, T., Hajek, T., Heindel, W., Ingvar, M., Sim, K., Kircher, T.T.J., Lenroot, R.K., Malt, U.F., McDonald, C., McWhinney, S.R., Melle, I., Meller, T., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Opel, N., Overs, B.J., Panicalli, F., Pfarr, J.K., Poletti, S., Pomarol-Clotet, E., Radua, J., Repple, J., Ringwald, K.G., Roberts, G., Rodriguez-Cano, E., Salvador, R., Sarink, K., Sarró, S., Schmitt, S., Stein, F., Suo, C., Thomopoulos, S.I., Tronchin, G., Vieta, E., Westlye, L.T., White, A.G., Yatham, L.N., Zak, N., Thompson, P.M., Andreassen, O.A., and Landen, M.

Abstract

Background: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. Methods: Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. Results: Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18 < d < 0.22). More (hypo)manic episodes were associated with faster cortical thinning, primarily in the prefrontal cortex. Conclusions: In the hitherto largest longitudinal MRI study on BD, we did not detect accelerated cortical thinning but noted faster ventricular enlargements in BD. However, abnormal frontocortical thinning was observed in association with frequent manic episodes. Our study yields insights into disease progression in BD and highlights the importance of mania prevention in BD treatment.

50. White matter microstructure in obesity and bipolar disorders: an ENIGMA bipolar disorder working group study in 2186 individuals.

Author

Dietze LMF, McWhinney SR, Favre P, Abé C, Alexander N, Barkhau C, Benedetti F, Berk M, Bøen E, Boye B, Brosch K, Canales-Rodríguez EJ, Cannon DM, Carruthers SP, Corkum ELV, Dannlowski U, Díaz-Zuluaga AM, Dohm K, Elvsåshagen T, Flinkenflügel K, Fortea L, Furlong LS, Goldstein BI, Grotegerd D, Gruber M, Haarman BCM, Howells FM, Jahanshad N, Jamalabadi H, Jansen A, Karantonis JA, Kennedy KG, Kircher TTJ, Klahn AL, Kochunov P, Kraus A, Landén M, López-Jaramillo C, MacIntosh BJ, Mazza E, McDonald C, McIntosh AM, Meinert H, Meinert S, Melloni EMT, Mitchell PB, Nenadić I, Opel N, Phillips M, Piguet C, Polosan M, Pomarol-Clotet E, Pouchon A, Radua J, Roberts G, Ross AJ, Rossell SL, Salvador R, Sim K, Soares JC, Zunta-Soares GB, Stein F, Straube B, Suo C, Teutenberg L, Thomas-Odenthal F, Thomopoulos SI, Usemann P, Van Rheenen TE, Versace A, Vieta E, Vilajosana E, Mwangi B, Wen W, Whalley HC, Wu MJ, Andreassen OA, Ching CRK, Thompson PM, Houenou J, and Hajek T

Abstract

Although specific risk factors for brain alterations in bipolar disorders (BD) are currently unknown, obesity impacts the brain and is highly prevalent in BD. Gray matter correlates of obesity in BD have been well documented, but we know much less about brain white matter abnormalities in people who have both obesity and BD. We obtained body mass index (BMI) and diffusion tensor imaging derived fractional anisotropy (FA) from 22 white matter tracts in 899 individuals with BD, and 1287 control individuals from 20 cohorts in the ENIGMA-BD working group. In a mega-analysis, we investigated the associations between BMI, diagnosis or medication and FA. Lower FA was associated with both BD and BMI in six white matter tracts, including the corpus callosum and thalamic radiation. Higher BMI or BD were uniquely associated with lower FA in three and six white matter tracts, respectively. People not receiving lithium treatment had a greater negative association between FA and BMI than people treated with lithium in the posterior thalamic radiation and sagittal stratum. In three tracts BMI accounted for 10.5 to 17% of the negative association between the number of medication classes other than lithium and FA. Both overweight/obesity and BD demonstrated lower FA in some of the same regions. People prescribed lithium had a weaker association between BMI and FA than people not on lithium. In contrast, greater weight contributed to the negative associations between medications and FA. Obesity may add to brain alterations in BD and may play a role in effects of medications on the brain., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

Published
2024
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