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2. Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Author

Belov, V, Erwin-Grabner, T, Aghajani, M, Aleman, A, Amod, AR, Basgoze, Z, Benedetti, F, Besteher, B, Bülow, R, Ching, CRK, Connolly, CG, Cullen, K, Davey, CG, Dima, D, Dols, A, Evans, JW, Fu, CHY, Gonul, AS, Gotlib, IH, Grabe, HJ, Groenewold, N, Hamilton, JP, Harrison, BJ, Ho, TC, Mwangi, B, Jaworska, N, Jahanshad, N, Klimes-Dougan, B, Koopowitz, S-M, Lancaster, T, Li, M, Linden, DEJ, MacMaster, FP, Mehler, DMA, Melloni, E, Mueller, BA, Ojha, A, Oudega, ML, Penninx, BWJH, Poletti, S, Pomarol-Clotet, E, Portella, MJ, Pozzi, E, Reneman, L, Sacchet, MD, Sämann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Thomopoulos, SI, Uyar-Demir, A, van der Wee, NJA, van der Werff, SJA, Völzke, H, Whittle, S, Wittfeld, K, Wright, MJ, Wu, M-J, Yang, TT, Zarate, C, Veltman, DJ, Schmaal, L, Thompson, PM, Goya-Maldonado, R, ENIGMA Major Depressive Disorder working group, Belov, V, Erwin-Grabner, T, Aghajani, M, Aleman, A, Amod, AR, Basgoze, Z, Benedetti, F, Besteher, B, Bülow, R, Ching, CRK, Connolly, CG, Cullen, K, Davey, CG, Dima, D, Dols, A, Evans, JW, Fu, CHY, Gonul, AS, Gotlib, IH, Grabe, HJ, Groenewold, N, Hamilton, JP, Harrison, BJ, Ho, TC, Mwangi, B, Jaworska, N, Jahanshad, N, Klimes-Dougan, B, Koopowitz, S-M, Lancaster, T, Li, M, Linden, DEJ, MacMaster, FP, Mehler, DMA, Melloni, E, Mueller, BA, Ojha, A, Oudega, ML, Penninx, BWJH, Poletti, S, Pomarol-Clotet, E, Portella, MJ, Pozzi, E, Reneman, L, Sacchet, MD, Sämann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Thomopoulos, SI, Uyar-Demir, A, van der Wee, NJA, van der Werff, SJA, Völzke, H, Whittle, S, Wittfeld, K, Wright, MJ, Wu, M-J, Yang, TT, Zarate, C, Veltman, DJ, Schmaal, L, Thompson, PM, Goya-Maldonado, R, and ENIGMA Major Depressive Disorder working group

Abstract

Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects.

Published
2024

3. Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data: Secondary Analysis of a Randomized Clinical Trial

Author

Poirot, M.G., Ruhé, H.G., Mutsaerts, H.M.M., Maximov, II, Groote, I.R., Bjørnerud, A., Marquering, H.A., Reneman, L., Caan, M.W., Poirot, M.G., Ruhé, H.G., Mutsaerts, H.M.M., Maximov, II, Groote, I.R., Bjørnerud, A., Marquering, H.A., Reneman, L., and Caan, M.W.

Abstract

Contains fulltext : 305051.pdf (Publisher’s version ) (Closed access), OBJECTIVE: Response to antidepressant treatment in major depressive disorder varies substantially between individuals, which lengthens the process of finding effective treatment. The authors sought to determine whether a multimodal machine learning approach could predict early sertraline response in patients with major depressive disorder. They assessed the predictive contribution of MR neuroimaging and clinical assessments at baseline and after 1 week of treatment. METHODS: This was a preregistered secondary analysis of data from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a multisite double-blind, placebo-controlled randomized clinical trial that included 296 adult outpatients with unmedicated recurrent or chronic major depressive disorder. MR neuroimaging and clinical data were collected before and after 1 week of treatment. Performance in predicting response and remission, collected after 8 weeks, was quantified using balanced accuracy (bAcc) and area under the receiver operating characteristic curve (AUROC) scores. RESULTS: A total of 229 patients were included in the analyses (mean age, 38 years [SD=13]; 66% female). Internal cross-validation performance in predicting response to sertraline (bAcc=68% [SD=10], AUROC=0.73 [SD=0.03]) was significantly better than chance. External cross-validation on data from placebo nonresponders (bAcc=62%, AUROC=0.66) and placebo nonresponders who were switched to sertraline (bAcc=65%, AUROC=0.68) resulted in differences that suggest specificity for sertraline treatment compared with placebo treatment. Finally, multimodal models outperformed unimodal models. CONCLUSIONS: The study results confirm that early sertraline treatment response can be predicted; that the models are sertraline specific compared with placebo; that prediction benefits from integrating multimodal MRI data with clinical data; and that perfusion imaging contributes most to these predictions. Using

Published
2024

8. Effects of stimulant medication on symptom interrelations in attention-deficit/hyperactivity disorder

Author

Van Der Pal, Z., primary, Geurts, H.M., additional, Haslbeck, J., additional, Van Keeken, A., additional, Bruijn, A.M., additional, Borsboom, D., additional, Douw, L., additional, Van Rooij, D., additional, Franke, B., additional, Buitelaar, J., additional, Lambregt-Rommelse, N., additional, Hartman, C., additional, Oosterlaan, J., additional, Marjolein, L., additional, Reneman, L., additional, Hoekstra, P.J., additional, Blanken, T.F., additional, and Schrantee, A., additional

Published
2023
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17. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure

Author

Hoogman, M., Rooij, D. van, Klein, M., Boedhoe, P., Ilioska, I., Li, T., Patel, Y., Postema, M.C., Zhang-James, Y., Anagnostou, E., Arango, C., Auzias, G., Banaschewski, T., Bau, C.H.D., Behrmann, M., Bellgrove, Mark A., Brandeis, D., Brem, S., Busatto, G.F., Calderoni, S., Calvo, R., Castellanos, F.X., Coghill, D., Conzelmann, A., Daly, E., Deruelle, C., Dinstein, I., Durston, S., Ecker, C., Ehrlich, S., Epstein, J.N., Fair, D.A., Fitzgerald, J., Freitag, C.M., Frodl, T., Gallagher, L., Grevet, E.H., Haavik, J., Hoekstra, P.J., Janssen, J., Karkashadze, G., King, J.A., Konrad, K., Kuntsi, J., Lazaro, L., Lerch, J.P., Lesch, K.P., Louza, M.R., Luna, B., Mattos, P., McGrath, J., Muratori, F., Murphy, C., Nigg, J.T., Oberwelland-Weiss, E., Tuura, R.L. O'Gorman, O'Hearn, K., Oosterlaan, J., Parellada, M., Pauli, P., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Retico, A., Rosa, P.G., Rubia, K., Shaw, P., Silk, T.J., Tamm, L., Vilarroya, O., Walitza, S., Jahanshad, N., Faraone, S.V, Francks, C., Heuvel, O.A. van den, Paus, T., Thompson, P.M., Buitelaar, J.K., Franke, B., Hoogman, M., Rooij, D. van, Klein, M., Boedhoe, P., Ilioska, I., Li, T., Patel, Y., Postema, M.C., Zhang-James, Y., Anagnostou, E., Arango, C., Auzias, G., Banaschewski, T., Bau, C.H.D., Behrmann, M., Bellgrove, Mark A., Brandeis, D., Brem, S., Busatto, G.F., Calderoni, S., Calvo, R., Castellanos, F.X., Coghill, D., Conzelmann, A., Daly, E., Deruelle, C., Dinstein, I., Durston, S., Ecker, C., Ehrlich, S., Epstein, J.N., Fair, D.A., Fitzgerald, J., Freitag, C.M., Frodl, T., Gallagher, L., Grevet, E.H., Haavik, J., Hoekstra, P.J., Janssen, J., Karkashadze, G., King, J.A., Konrad, K., Kuntsi, J., Lazaro, L., Lerch, J.P., Lesch, K.P., Louza, M.R., Luna, B., Mattos, P., McGrath, J., Muratori, F., Murphy, C., Nigg, J.T., Oberwelland-Weiss, E., Tuura, R.L. O'Gorman, O'Hearn, K., Oosterlaan, J., Parellada, M., Pauli, P., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Retico, A., Rosa, P.G., Rubia, K., Shaw, P., Silk, T.J., Tamm, L., Vilarroya, O., Walitza, S., Jahanshad, N., Faraone, S.V, Francks, C., Heuvel, O.A. van den, Paus, T., Thompson, P.M., Buitelaar, J.K., and Franke, B.

Abstract

Contains fulltext : 248364.pdf (Publisher’s version ) (Open Access), 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

18. 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

23. A randomized controlled trial on the effects of a 12-Week high- vs. low-intensity exercise intervention on hippocampal structure and function in healthy, young adults

Author

Kaiser, A., Reneman, L., Solleveld, M.M., Coolen, B.F., Scherder, E.J.A., Knutsson, L., Bjornerud, A., Osch, M.J.P. van, Wijnen, J.P., Lucassen, P.J., and Schrantee, A.

Subjects
angiogenesis, vasculature, exercise, hippocampus, neuro-metabolites, multimodal, perfusion, MRI
Abstract

Physical exercise affects hippocampal structure and function, but the underlying neural mechanisms and the effects of exercise intensity remain incompletely understood. Therefore, we undertook a comprehensive, multi-modal 3T and 7T MRI randomized controlled trial (Netherlands Trial Register - NL5847) in which we randomized 52 young, non-athletic volunteers to a 12-week low- or high-intensity exercise program. Using state-of-the-art methods, we investigated changes in hippocampal volume, as well as changes in vasculature, neuro-metabolites, and peripheral growth factors as potential underpinnings. Cardiorespiratory fitness improved over time (p < 0.001), but no interaction with exercise intensity was found (p = 0.48). Accordingly, we did not observe significant interactions between exercise condition and time on MRI measures (all p > 0.06). However, we found a significant decrease in right hippocampal volume (p < 0.01), an increase in left hippocampal glutathione (p < 0.01), and a decrease of left hippocampal cerebral blood volume (p = 0.01) over time, regardless of exercise condition. Additional exploratory analyses showed that changes in brain-derived neurotrophic factor (p = 0.01), insulin-like growth-factor (p = 0.03), and dorsal anterior cingulate cortex N-acetyl-aspartate levels (p = 0.01) were positively associated with cardiorespiratory fitness changes. Furthermore, a trend toward a positive association of fitness and gray-matter cerebral blood flow (p = 0.06) was found. Our results do not provide evidence for differential effects between high-intensity (aerobic) and low-intensity (toning) exercise on hippocampal structure and function in young adults. However, we show small but significant effects of exercise on hippocampal volume, neurometabolism and vasculature across exercise conditions. Moreover, our exploratory results suggest that exercise might not specifically only benefit hippocampal structure and function, but rather has a more widespread effect. These findings suggest that, in agreement with previous MRI studies demonstrating moderate to strong effects in elderly and diseased populations, but none to only mild effects in young healthy cohorts, the benefits of exercise on the studied brain measures may be age-dependent and restorative rather than stimulatory. Our study highlights the importance of a multi-modal, whole-brain approach to assess macroscopic and microscopic changes underlying exercise-induced brain changes, to better understand the role of exercise as a potential non-pharmacological intervention.

Published
2022

29. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., Schmaal, L., Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., and Schmaal, L.

Abstract

Item does not contain fulltext, Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

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

Author

Postema, M.C., Hoogman, M., Ambrosino, S., Asherson, P., Banaschewski, T., Bandeira, C.E., Baranov, A., Bau, C.H.D., Baumeister, S., Baur-Streubel, R., Bellgrove, Mark A., Biederman, J., Bralten, J.B., Brandeis, D., Brem, S., Buitelaar, J.K., Busatto, G.F., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Cupertino, R.B., Zeeuw, P. de, Doyle, A.E., Durston, S., Earl, E.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Frodl, T., Gabel, M.C., Gogberashvili, T., Grevet, E.H., Haavik, J., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hoekstra, P.J., Hohmann, S., Høvik, M.F., Jernigan, T.L., Kardatzki, B., Karkashadze, G., Kelly, C., Kohls, G., Konrad, K., Kuntsi, J., Lazaro, L., Lera-Miguel, S., Lesch, K.P., Louza, M.R., Lundervold, A.J., Malpas, C.B., Mattos, P., McCarthy, H., Namazova-Baranova, L., Nicolau, R., Nigg, J.T., Novotny, S.E., Weiss, E. Oberwelland, Tuura, R.L. O'Gorman, Oosterlaan, J., Oranje, B., Paloyelis, Y., Pauli, P., Picon, F.A., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Rosa, P.G., Rubia, K., Schrantee, A., Schweren, L.J., Seitz, J., Shaw, P., Silk, T.J., Skokauskas, N., Vila, J.C. Soliva, Stevens, M.C., Sudre, G., Tamm, L., Tovar-Moll, F., Erp, T.G. van, Vance, A., Vilarroya, O., Vives-Gilabert, Y., Polier, G.G. von, Walitza, S., Yoncheva, Y.N., Zanetti, M.V., Ziegler, G.C., Glahn, D.C., Fisher, S.E., Franke, B., Francks, C., Postema, M.C., Hoogman, M., Ambrosino, S., Asherson, P., Banaschewski, T., Bandeira, C.E., Baranov, A., Bau, C.H.D., Baumeister, S., Baur-Streubel, R., Bellgrove, Mark A., Biederman, J., Bralten, J.B., Brandeis, D., Brem, S., Buitelaar, J.K., Busatto, G.F., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Cupertino, R.B., Zeeuw, P. de, Doyle, A.E., Durston, S., Earl, E.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Frodl, T., Gabel, M.C., Gogberashvili, T., Grevet, E.H., Haavik, J., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hoekstra, P.J., Hohmann, S., Høvik, M.F., Jernigan, T.L., Kardatzki, B., Karkashadze, G., Kelly, C., Kohls, G., Konrad, K., Kuntsi, J., Lazaro, L., Lera-Miguel, S., Lesch, K.P., Louza, M.R., Lundervold, A.J., Malpas, C.B., Mattos, P., McCarthy, H., Namazova-Baranova, L., Nicolau, R., Nigg, J.T., Novotny, S.E., Weiss, E. Oberwelland, Tuura, R.L. O'Gorman, Oosterlaan, J., Oranje, B., Paloyelis, Y., Pauli, P., Picon, F.A., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Rosa, P.G., Rubia, K., Schrantee, A., Schweren, L.J., Seitz, J., Shaw, P., Silk, T.J., Skokauskas, N., Vila, J.C. Soliva, Stevens, M.C., Sudre, G., Tamm, L., Tovar-Moll, F., Erp, T.G. van, Vance, A., Vilarroya, O., Vives-Gilabert, Y., Polier, G.G. von, Walitza, S., Yoncheva, Y.N., Zanetti, M.V., Ziegler, G.C., Glahn, D.C., Fisher, S.E., Franke, B., and Francks, C.

Abstract

Item does not contain fulltext, 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

31. ENIGMA-Sleep: Challenges, opportunities, and the road map

Author

Tahmasian, M., Aleman, A., Andreassen, O.A., Arab, Z., Baillet, M., Benedetti, F. De, Bresser, T., Bright, J., Chee, M.W.L., Chylinski, D., Cheng, W., Deantoni, M., Dresler, M., Eickhoff, S.B., Eickhoff, C.R., Elvsåshagen, T., Feng, J., Foster-Dingley, J.C., Ganjgahi, H., Grabe, H.J., Groenewold, N.A., Ho, T.C., Hong, S., Houenou, J., Irungu, B., Jahanshad, N., Khazaie, H., Kim, H., Koshmanova, E., Kocevska, D., Kochunov, P., Lakbila-Kamal, O., Leerssen, J., Li, M., Luik, A.I., Muto, V., Narbutas, J., Nilsonne, G., O'Callaghan, V.S., Olsen, A., Osorio, R.S., Poletti, S., Poudel, G., Reesen, J.E., Reneman, L., Reyt, M., Riemann, D., Rosenzweig, I., Rostampour, M., Saberi, A., Schiel, J., Schmidt, C., Schrantee, A., Sciberras, E., Silk, T.J., Sim, K., Smevik, H., Soares, J.C., Spiegelhalder, K., Stein, D.J., Talwar, P., Tamm, S., Teresi, G.L., Valk, S.L., Someren, E. van, Vandewalle, G., Egroo, M. Van, Völzke, H., Walter, M., Wassing, R., Weber, F.D., Weihs, A., Westlye, L.T., Wright, M.J., Wu, M.J., Zak, N., Zarei, M., Tahmasian, M., Aleman, A., Andreassen, O.A., Arab, Z., Baillet, M., Benedetti, F. De, Bresser, T., Bright, J., Chee, M.W.L., Chylinski, D., Cheng, W., Deantoni, M., Dresler, M., Eickhoff, S.B., Eickhoff, C.R., Elvsåshagen, T., Feng, J., Foster-Dingley, J.C., Ganjgahi, H., Grabe, H.J., Groenewold, N.A., Ho, T.C., Hong, S., Houenou, J., Irungu, B., Jahanshad, N., Khazaie, H., Kim, H., Koshmanova, E., Kocevska, D., Kochunov, P., Lakbila-Kamal, O., Leerssen, J., Li, M., Luik, A.I., Muto, V., Narbutas, J., Nilsonne, G., O'Callaghan, V.S., Olsen, A., Osorio, R.S., Poletti, S., Poudel, G., Reesen, J.E., Reneman, L., Reyt, M., Riemann, D., Rosenzweig, I., Rostampour, M., Saberi, A., Schiel, J., Schmidt, C., Schrantee, A., Sciberras, E., Silk, T.J., Sim, K., Smevik, H., Soares, J.C., Spiegelhalder, K., Stein, D.J., Talwar, P., Tamm, S., Teresi, G.L., Valk, S.L., Someren, E. van, Vandewalle, G., Egroo, M. Van, Völzke, H., Walter, M., Wassing, R., Weber, F.D., Weihs, A., Westlye, L.T., Wright, M.J., Wu, M.J., Zak, N., and Zarei, M.

Abstract

Item does not contain fulltext, Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

Published
2021

32. 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

33. 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

34. 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

35. Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts

Author

Campos, A, Thompson, PM, Veltman, DJ, Pozzi, E, van Veltzen, LS, Jahanshad, N, Adams, MJ, Baune, BT, Berger, K, Brosch, K, Bulow, R, Connolly, CG, Dannlowski, U, Davey, CG, de Zubicaray, G, Dima, D, Erwin-Grabner, T, Evans, JW, Fu, CHY, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Grotegerd, D, Harris, MA, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, McMahon, K, MacMaster, FP, Martin, NG, McIntosh, AM, Medland, SE, Meinert, S, Meller, T, Nenadic, I, Opel, N, Redlich, R, Reneman, L, Repple, J, Sacchet, MD, Schmitt, S, Schrantee, A, Sim, K, Singh, A, Stein, F, Strike, LT, van Der Wee, NJA, van Der Werff, SJA, Volzke, H, Waltemate, L, Whalley, HC, Wittfeld, K, Wright, MJ, Yang, TT, Zarate, CA, Schmaal, L, Renteria, ME, Campos, A, Thompson, PM, Veltman, DJ, Pozzi, E, van Veltzen, LS, Jahanshad, N, Adams, MJ, Baune, BT, Berger, K, Brosch, K, Bulow, R, Connolly, CG, Dannlowski, U, Davey, CG, de Zubicaray, G, Dima, D, Erwin-Grabner, T, Evans, JW, Fu, CHY, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Grotegerd, D, Harris, MA, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, McMahon, K, MacMaster, FP, Martin, NG, McIntosh, AM, Medland, SE, Meinert, S, Meller, T, Nenadic, I, Opel, N, Redlich, R, Reneman, L, Repple, J, Sacchet, MD, Schmitt, S, Schrantee, A, Sim, K, Singh, A, Stein, F, Strike, LT, van Der Wee, NJA, van Der Werff, SJA, Volzke, H, Waltemate, L, Whalley, HC, Wittfeld, K, Wright, MJ, Yang, TT, Zarate, CA, Schmaal, L, and Renteria, ME

Abstract

BACKGROUND: Neuroimaging studies of suicidal behavior have so far been conducted in small samples, prone to biases and false-positive associations, yielding inconsistent results. The ENIGMA-MDD Working Group aims to address the issues of poor replicability and comparability by coordinating harmonized analyses across neuroimaging studies of major depressive disorder and related phenotypes, including suicidal behavior. METHODS: Here, we pooled data from 18 international cohorts with neuroimaging and clinical measurements in 18,925 participants (12,477 healthy control subjects and 6448 people with depression, of whom 694 had attempted suicide). We compared regional cortical thickness and surface area and measures of subcortical, lateral ventricular, and intracranial volumes between suicide attempters, clinical control subjects (nonattempters with depression), and healthy control subjects. RESULTS: We identified 25 regions of interest with statistically significant (false discovery rate < .05) differences between groups. Post hoc examinations identified neuroimaging markers associated with suicide attempt including smaller volumes of the left and right thalamus and the right pallidum and lower surface area of the left inferior parietal lobe. CONCLUSIONS: This study addresses the lack of replicability and consistency in several previously published neuroimaging studies of suicide attempt and further demonstrates the need for well-powered samples and collaborative efforts. Our results highlight the potential involvement of the thalamus, a structure viewed historically as a passive gateway in the brain, and the pallidum, a region linked to reward response and positive affect. Future functional and connectivity studies of suicidal behaviors may focus on understanding how these regions relate to the neurobiological mechanisms of suicide attempt risk.

Published
2021

36. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders (May, 2020, 10.1038/s41380-020-0774-9)

Author

Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U

Published
2021

37. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group

Author

Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U

Abstract

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

Published
2021

38. 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

39. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group

Author

Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, Schmaal, L, Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, and Schmaal, L

Abstract

Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.

Published
2021

40. ENIGMA-Sleep: Challenges, opportunities, and the road map

Author

Tahmasian, M, Aleman, A, Andreassen, OA, Arab, Z, Baillet, M, Benedetti, F, Bresser, T, Bright, J, Chee, MWL, Chylinski, D, Cheng, W, Deantoni, M, Dresler, M, Eickhoff, SB, Eickhoff, CR, Elvsashagen, T, Feng, J, Foster-Dingley, JC, Ganjgahi, H, Grabe, HJ, Groenewold, NA, Ho, TC, Hong, SB, Houenou, J, Irungu, B, Jahanshad, N, Khazaie, H, Kim, H, Koshmanova, E, Kocevska, D, Kochunov, P, Lakbila-Kamal, O, Leerssen, J, Li, M, Luik, A, Muto, V, Narbutas, J, Nilsonne, G, O'Callaghan, VS, Olsen, A, Osorio, RS, Poletti, S, Poudel, G, Reesen, JE, Reneman, L, Reyt, M, Riemann, D, Rosenzweig, I, Rostampour, M, Saberi, A, Schiel, J, Schmidt, C, Schrantee, A, Sciberras, E, Silk, TJ, Sim, K, Smevik, H, Soares, JC, Spiegelhalder, K, Stein, DJ, Talwar, P, Tamm, S, Teresi, GL, Valk, SL, Van Someren, E, Vandewalle, G, Van Egroo, M, Volzke, H, Walter, M, Wassing, R, Weber, FD, Weihs, A, Westlye, LT, Wright, MJ, Wu, M-J, Zak, N, Zarei, M, Tahmasian, M, Aleman, A, Andreassen, OA, Arab, Z, Baillet, M, Benedetti, F, Bresser, T, Bright, J, Chee, MWL, Chylinski, D, Cheng, W, Deantoni, M, Dresler, M, Eickhoff, SB, Eickhoff, CR, Elvsashagen, T, Feng, J, Foster-Dingley, JC, Ganjgahi, H, Grabe, HJ, Groenewold, NA, Ho, TC, Hong, SB, Houenou, J, Irungu, B, Jahanshad, N, Khazaie, H, Kim, H, Koshmanova, E, Kocevska, D, Kochunov, P, Lakbila-Kamal, O, Leerssen, J, Li, M, Luik, A, Muto, V, Narbutas, J, Nilsonne, G, O'Callaghan, VS, Olsen, A, Osorio, RS, Poletti, S, Poudel, G, Reesen, JE, Reneman, L, Reyt, M, Riemann, D, Rosenzweig, I, Rostampour, M, Saberi, A, Schiel, J, Schmidt, C, Schrantee, A, Sciberras, E, Silk, TJ, Sim, K, Smevik, H, Soares, JC, Spiegelhalder, K, Stein, DJ, Talwar, P, Tamm, S, Teresi, GL, Valk, SL, Van Someren, E, Vandewalle, G, Van Egroo, M, Volzke, H, Walter, M, Wassing, R, Weber, FD, Weihs, A, Westlye, LT, Wright, MJ, Wu, M-J, Zak, N, and Zarei, M

Abstract

Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.

Published
2021

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

Author

Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., Paus, T., Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., 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 (exce

Published
2021
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43. The association between stress-induced changes in prefrontal GABA levels and heart rate variability: a 7T 1H-MRS study

Author

Kaiser, A., Reneman, L., Lucassen, P. J., Kaag, A. M., Van der Zwaag, W., Jurhar, T., Kirschbaum, C., Van den Heuvel, O. A., Hermans, E. J., Tan, H. L., Medical Microbiology and Infection Control, Radiology and nuclear medicine, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Neurodegeneration, Physiology, and ACS - Heart failure & arrhythmias

Published
2020

44. Ultrahigh-resolution MRI reveals structural brain differences in serotonin transporter knockout rats after sucrose and cocaine self-administration

Author

Karel, P.G., Toorn, A. van der, Vanderschuren, L., Guo, C., Sadighi Alvandi, M., Reneman, L., Dijkhuizen, R., Verheij, M.M.M., Homberg, J.R., Karel, P.G., Toorn, A. van der, Vanderschuren, L., Guo, C., Sadighi Alvandi, M., Reneman, L., Dijkhuizen, R., Verheij, M.M.M., and Homberg, J.R.

Abstract

Contains fulltext : 220583.pdf (Publisher’s version ) (Open Access), Excessive use of cocaine is known to induce changes in brain white and gray matter. It is unknown whether the extent of these changes is related to individual differences in vulnerability to cocaine addiction. One factor increasing vulnerability involves reduced expression of the serotonin transporter (5-HTT). Human studies have shown that inherited 5-HTT downregulation is associated with structural changes in the brain. These genotype-related structural changes may contribute to risk for cocaine addiction. Here, we tested this idea by using ultrahigh-resolution structural magnetic resonance imaging (MRI) on postmortem tissue of 5-HTT(-/-) and wild-type (5-HTT(+/+) ) rats with a history of long access to cocaine or sucrose (control) self-administration. We found that 5-HTT(-/-) rats, compared with wild-type control animals, self-administered more cocaine, but not sucrose, under long-access conditions. Ultrahigh-resolution structural MRI subsequently revealed that, independent of sucrose or cocaine self-administration, 5-HTT(-/-) rats had a smaller amygdala. Moreover, we found an interaction between genotype and type of reward for dorsal raphe nucleus volume. The data point to an important but differential role of the amygdala and dorsal raphe nucleus in 5-HTT genotype-dependent vulnerability to cocaine addiction.

Published
2020

45. ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

Author

Schmaal, L, Pozzi, E, Ho, TC, van Velzen, LS, Veer, IM, Opel, N, Van Someren, EJW, Han, LKM, Aftanas, L, Aleman, A, Baune, BT, Berger, K, Blanken, TF, Capitao, L, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, C, Erwin-Grabner, T, Evans, J, Frodl, T, Fu, CHY, Godlewska, B, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gutman, BA, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Hilland, E, Irungu, B, Jonassen, R, Kelly, S, Kircher, T, Klimes-Dougan, B, Krug, A, Landro, NI, Lagopoulos, J, Leerssen, J, Li, M, Linden, DEJ, MacMaster, FP, McIntosh, AM, Mehler, DMA, Nenadic, I, Penninx, BWJH, Portella, MJ, Reneman, L, Renteria, ME, Sacchet, MD, Saemann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Tozzi, L, van Der Wee, NJA, van Tol, M-J, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, Whalley, HC, Wittfeld, K, Whittle, S, Wright, MJ, Yang, TT, Zarate, C, Thomopoulos, SI, Jahanshad, N, Thompson, PM, Veltman, DJ, Schmaal, L, Pozzi, E, Ho, TC, van Velzen, LS, Veer, IM, Opel, N, Van Someren, EJW, Han, LKM, Aftanas, L, Aleman, A, Baune, BT, Berger, K, Blanken, TF, Capitao, L, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, C, Erwin-Grabner, T, Evans, J, Frodl, T, Fu, CHY, Godlewska, B, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gutman, BA, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Hilland, E, Irungu, B, Jonassen, R, Kelly, S, Kircher, T, Klimes-Dougan, B, Krug, A, Landro, NI, Lagopoulos, J, Leerssen, J, Li, M, Linden, DEJ, MacMaster, FP, McIntosh, AM, Mehler, DMA, Nenadic, I, Penninx, BWJH, Portella, MJ, Reneman, L, Renteria, ME, Sacchet, MD, Saemann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Tozzi, L, van Der Wee, NJA, van Tol, M-J, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, Whalley, HC, Wittfeld, K, Whittle, S, Wright, MJ, Yang, TT, Zarate, C, Thomopoulos, SI, Jahanshad, N, Thompson, PM, and Veltman, DJ

Abstract

A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.

Published
2020

46. 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

47. Subcortical surface morphometry in substance dependence: An ENIGMA addiction working group study

Author

Chye, Y, Mackey, S, Gutman, BA, Ching, CRK, Batalla, A, Blaine, S, Brooks, S, Caparelli, EC, Cousijn, J, Dagher, A, Foxe, JJ, Goudriaan, AE, Hester, R, Hutchison, K, Jahanshad, N, Kaag, AM, Korucuoglu, O, Li, C-SR, London, ED, Lorenzetti, V, Luijten, M, Martin-Santos, R, Meda, SA, Momenan, R, Morales, A, Orr, C, Paulus, MP, Pearlson, G, Reneman, L, Schmaal, L, Sinha, R, Solowij, N, Stein, DJ, Stein, EA, Tang, D, Uhlmann, A, van Holst, R, Veltman, DJ, Verdejo-Garcia, A, Wiers, RW, Yuecel, M, Thompson, PM, Conrod, P, Garavan, H, Chye, Y, Mackey, S, Gutman, BA, Ching, CRK, Batalla, A, Blaine, S, Brooks, S, Caparelli, EC, Cousijn, J, Dagher, A, Foxe, JJ, Goudriaan, AE, Hester, R, Hutchison, K, Jahanshad, N, Kaag, AM, Korucuoglu, O, Li, C-SR, London, ED, Lorenzetti, V, Luijten, M, Martin-Santos, R, Meda, SA, Momenan, R, Morales, A, Orr, C, Paulus, MP, Pearlson, G, Reneman, L, Schmaal, L, Sinha, R, Solowij, N, Stein, DJ, Stein, EA, Tang, D, Uhlmann, A, van Holst, R, Veltman, DJ, Verdejo-Garcia, A, Wiers, RW, Yuecel, M, Thompson, PM, Conrod, P, and Garavan, H

Abstract

While imaging studies have demonstrated volumetric differences in subcortical structures associated with dependence on various abused substances, findings to date have not been wholly consistent. Moreover, most studies have not compared brain morphology across those dependent on different substances of abuse to identify substance-specific and substance-general dependence effects. By pooling large multinational datasets from 33 imaging sites, this study examined subcortical surface morphology in 1628 nondependent controls and 2277 individuals with dependence on alcohol, nicotine, cocaine, methamphetamine, and/or cannabis. Subcortical structures were defined by FreeSurfer segmentation and converted to a mesh surface to extract two vertex-level metrics-the radial distance (RD) of the structure surface from a medial curve and the log of the Jacobian determinant (JD)-that, respectively, describe local thickness and surface area dilation/contraction. Mega-analyses were performed on measures of RD and JD to test for the main effect of substance dependence, controlling for age, sex, intracranial volume, and imaging site. Widespread differences between dependent users and nondependent controls were found across subcortical structures, driven primarily by users dependent on alcohol. Alcohol dependence was associated with localized lower RD and JD across most structures, with the strongest effects in the hippocampus, thalamus, putamen, and amygdala. Meanwhile, nicotine use was associated with greater RD and JD relative to nonsmokers in multiple regions, with the strongest effects in the bilateral hippocampus and right nucleus accumbens. By demonstrating subcortical morphological differences unique to alcohol and nicotine use, rather than dependence across all substances, results suggest substance-specific relationships with subcortical brain structures.

Published
2020

48. ExploreASL: an image processing pipeline for multi-center ASL perfusion MRI studies

Author

Mutsaerts, H. J., (0000-0002-3201-6002) Petr, J., Groot, P. F., Vandemaele, P., Ingala, S., Robertson, A. D., Vaclavu, L., Groote, I., Kuijf, H., Zelaya, F., O'Daly, O., Hilal, S., Wink, A. M., Kant, I., Caan, M., Morgan, C., Bresser, J., Lysvik, E., Schrantee, A., Bjornebekk, A., Clement, P., Shirzadi, Z., Kuijer, J., Anazodo, U., Pajkrt, D., Richard, E., Bokkers, R., Reneman, L., Masellis, M., Guenther, M., Macintosh, B., Achten, E., Chappell, M., Osch, M., Golay, X., Thomas, D., Vita, E., Bjornerud, A., Nederveen, A., Hendrikse, J., Asllani, I., Barkhof, F., Mutsaerts, H. J., (0000-0002-3201-6002) Petr, J., Groot, P. F., Vandemaele, P., Ingala, S., Robertson, A. D., Vaclavu, L., Groote, I., Kuijf, H., Zelaya, F., O'Daly, O., Hilal, S., Wink, A. M., Kant, I., Caan, M., Morgan, C., Bresser, J., Lysvik, E., Schrantee, A., Bjornebekk, A., Clement, P., Shirzadi, Z., Kuijer, J., Anazodo, U., Pajkrt, D., Richard, E., Bokkers, R., Reneman, L., Masellis, M., Guenther, M., Macintosh, B., Achten, E., Chappell, M., Osch, M., Golay, X., Thomas, D., Vita, E., Bjornerud, A., Nederveen, A., Hendrikse, J., Asllani, I., and Barkhof, F.

Abstract

Arterial spin labeling (ASL) has undergone significant development since its inception, with a focus on improving standardization and reproducibility of its acquisition and quantification. In a community-wide effort towards robust and reproducible clinical ASL image processing, we developed the software package ExploreASL, allowing standardized analyses across centers and scanners. The procedures used in ExploreASL capitalize on published image processing advancements and address the challenges of multi-center datasets with scanner-specific processing and artifact reduction to limit patient exclusion. ExploreASL is self-contained, written in MATLAB and based on Statistical Parameter Mapping (SPM) and runs on multiple operating systems. The toolbox adheres to previously defined international standards for data structure, provenance, and best analysis practice. ExploreASL was iteratively refined and tested in the analysis of >10,000 ASL scans using different pulse-sequences in a variety of clinical populations, resulting in four processing modules: Import, Structural, ASL, and Population that perform tasks, respectively, for data curation, structural and ASL image processing and quality control, and finally preparing the results for statistical analyses on both single-subject and group level. We illustrate ExploreASL processing results from three cohorts: perinatally HIV-infected children, healthy adults, and elderly at risk for neurodegenerative disease. We show the reproducibility for each cohort when processed at different centers with different operating systems and MATLAB versions, and its effects on the quantification of gray matter cerebral blood flow. ExploreASL facilitates the standardization of image processing and quality control, allowing the pooling of cohorts to increase statistical power and discover between-group perfusion differences. Ultimately, this workflow may advance ASL for wider adoption in clinical studies, trials, and practice.

Published
2020

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