Author: "Dietsche, B." - Searchworks@Jio Institute Digital Library Search Results

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

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

2. Umfassendes Qualitätsmanagement in einem Hausarztnetz — ein Werkstattbericht

Author: Niebling, Wilhelm, Unteregger, E., Böckmann, H., Dietsche, B., Mühlbacher, A., and Nübling, M.
Published: 2003
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3. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group

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

4. The genetic architecture of the human cerebral cortex

Author: Grasby, K.L., Jahanshad, N., Painter, J.N., Colodro-Conde, L., Bralten, J., Hibar, D.P., Lind, P.A., Pizzagalli, F., Ching, C.R.K., McMahon, M.A.B., Shatokhina, N., Zsembik, L.C.P., Thomopoulos, S.I., Zhu, A.H., Strike, L.T., Agartz, I., Alhusaini, S., Almeida, M.A.A., Alnæs, D., Amlien, I.K., Andersson, M., Ard, T., Armstrong, N.J., Ashley-Koch, A., Atkins, J.R., Bernard, M., Brouwer, R.M., Buimer, E.E.L., Bülow, R., Bürger, C., Cannon, D.M., Chakravarty, M.M., Chen, Q., Cheung, J.W., Couvy-Duchesne, B., Dale, A.M., Dalvie, S., de Araujo, T.K., de Zubicaray, G.I., de Zwarte, S.M.C., den Braber, A., Doan, N.T., Dohm, K., Ehrlich, S., Engelbrecht, H-R, Erk, S., Fan, C.C., Fedko, I.O., Foley, S.F., Ford, J.M., Fukunaga, M., Garrett, M.E., Ge, T., Giddaluru, S., Goldman, A.L., Green, M.J., Groenewold, N.A., Grotegerd, D., Gurholt, T.P., Gutman, B.A., Hansell, N.K., Harris, M.A., Harrison, M.B., Haswell, C.C., Hauser, M., Herms, S., Heslenfeld, D.J., Ho, N.F., Hoehn, D., Hoffmann, P., Holleran, L., Hoogman, M., Hottenga, J-J, Ikeda, M., Janowitz, D., Jansen, I.E., Jia, T., Jockwitz, C., Kanai, R., Karama, S., Kasperaviciute, D., Kaufmann, T., Kelly, S., Kikuchi, M., Klein, M., Knapp, M., Knodt, A.R., Krämer, B., Lam, M., Lancaster, T.M., Lee, P.H., Lett, T.A., Lewis, L.B., Lopes-Cendes, I., Luciano, M., Macciardi, F., Marquand, A.F., Mathias, S.R., Melzer, T.R., Milaneschi, Y., Mirza-Schreiber, N., Moreira, J.C.V., Mühleisen, T.W., Müller-Myhsok, B., Najt, P., Nakahara, S., Nho, K., Olde Loohuis, L.M., Orfanos, D.P., Pearson, J.F., Pitcher, T.L., Pütz, B., Quidé, Y., Ragothaman, A., Rashid, F.M., Reay, W.R., Redlich, R., Reinbold, C.S., Repple, J., Richard, G., Riedel, B.C., Risacher, S.L., Rocha, C.S., Mota, N.R., Salminen, L., Saremi, A., Saykin, A.J., Schlag, F., Schmaal, L., Schofield, P.R., Secolin, R., Shapland, C.Y., Shen, L., Shin, J., Shumskaya, E., Sønderby, I.E., Sprooten, E., Tansey, K.E., Teumer, A., Thalamuthu, A., Tordesillas-Gutierrez, D., Turner, J.A., Uhlmann, A., Vallerga, C.L., van der Meer, D., van Donkelaar, M.M.J., van Eijk, L., Van Erp, T.G.M., van Haren, N.E.M., Van Rooij, D., van Tol, M-J, Veldink, J.H., Verhoef, E., Walton, E., Wang, M., Wang, Y., Wardlaw, J.M., Wen, W., Westlye, L.T., Whelan, C.D., Witt, S.H., Wittfeld, K., Wolf, C., Wolfers, T., Wu, J.Q., Yasuda, C.L., Zaremba, D., Zhang, Z., Zwiers, M.P., Artiges, E., Assareh, A.A., Ayesa-Arriola, R., Belger, A., Brandt, C.L., Brown, G.G., Cichon, S., Curran, J.E., Davies, G.E., Degenhardt, F., Dennis, M.F., Dietsche, B., Djurovic, S., Doherty, C.P., Espiritu, R., Garijo, D., Gil, Y., Gowland, P.A., Green, R.C., Häusler, A.N., Heindel, W., Ho, B-C., Hoffmann, W.U., Holsboer, F., Homuth, G., Hosten, N., Jack, C.R., Jang, M., Jansen, A., Kimbrel, N.A., Kolskår, K., Koops, S., Krug, A., Lim, K.O., Luykx, J.J., Mathalon, D.H., Mather, K.A., Mattay, V.S., Matthews, S., Mayoral Van Son, J., McEwen, S.C., Melle, I., Morris, D.W., Mueller, B.A., Nauck, M., Nordvik, J.E., Nöthen, M.M., O’Leary, D.S., Opel, N., Martinot, M-L.P., Pike, G.B., Preda, A., Quinlan, E.B., Rasser, P.E., Ratnakar, V., Reppermund, S., Steen, V.M., Tooney, P.A., Torres, F.R., Veltman, D.J., Voyvodic, J.T., Whelan, R., White, T., Yamamori, H., Adams, H.H.H., Bis, J.C., Debette, S., DeCarli, C., Fornage, M., Gudnason, V., Hofer, E., Ikram, M.A., Launer, L., Longstreth, W.T., Lopez, O.L., Mazoyer, B., Mosley, T.H., Roshchupkin, G.V., Satizabal, C.L., Schmidt, R., Seshadri, S., Yang, Q., Alvim, M.K.M., Ames, D., Anderson, T.J., Andreassen, O.A., Arias-Vasquez, A., Bastin, M.E., Baune, B.T., Beckham, J.C., Blangero, J., Boomsma, D.I., Brodaty, H., Brunner, H.G., Buckner, R.L., Buitelaar, J.K., Bustillo, J.R., Cahn, W., Cairns, M.J., Calhoun, V., Carr, V.J., Caseras, X., Caspers, S., Cavalleri, G.L., Cendes, F., Corvin, A., Crespo-Facorro, B., Dalrymple-Alford, J.C., Dannlowski, U., de Geus, E.J.C., Deary, I.J., Delanty, N., Depondt, C., Desrivières, S., Donohoe, G., Espeseth, T., Fernández, G., Fisher, S.E., Flor, H., Forstner, A.J., Francks, C., Franke, B., Glahn, D.C., Gollub, R.L., Grabe, H.J., Gruber, O., Håberg, A.K., Hariri, A.R., Hartman, C.A., Hashimoto, R., Heinz, A., Henskens, F.A., Hillegers, M.H.J., Hoekstra, P.J., Holmes, A.J., Hong, L.E., Hopkins, W.D., Hulshoff Pol, H.E., Jernigan, T.L., Jönsson, E.G., Kahn, R.S., Kennedy, M.A., Kircher, T.T.J., Kochunov, P., Kwok, J.B.J., Le Hellard, S., Loughland, C.M., Martin, N.G., Martinot, J-L, McDonald, C., McMahon, K.L., Meyer-Lindenberg, A., Michie, P.T., Morey, R.A., Mowry, B., Nyberg, L., Oosterlaan, J., Ophoff, R.A., Pantelis, C., Paus, T., Pausova, Z., Penninx, B.W.J.H., Polderman, T.J.C., Posthuma, D., Rietschel, M., Roffman, J.L., Rowland, L.M., Sachdev, P.S., Sämann, P.G., Schall, U., Schumann, G., Scott, R.J., Sim, K., Sisodiya, S.M., Smoller, J.W., Sommer, I.E., St Pourcain, B., Stein, D.J., Toga, A.W., Trollor, J.N., van der Wee, N.J.A., van ’t Ent, D., Völzke, H., Walter, H., Weber, B., Weinberger, D.R., Wright, M.J., Zhou, J., Stein, J.L., Thompson, P.M., Medland, S.E., Grasby, K.L., Jahanshad, N., Painter, J.N., Colodro-Conde, L., Bralten, J., Hibar, D.P., Lind, P.A., Pizzagalli, F., Ching, C.R.K., McMahon, M.A.B., Shatokhina, N., Zsembik, L.C.P., Thomopoulos, S.I., Zhu, A.H., Strike, L.T., Agartz, I., Alhusaini, S., Almeida, M.A.A., Alnæs, D., Amlien, I.K., Andersson, M., Ard, T., Armstrong, N.J., Ashley-Koch, A., Atkins, J.R., Bernard, M., Brouwer, R.M., Buimer, E.E.L., Bülow, R., Bürger, C., Cannon, D.M., Chakravarty, M.M., Chen, Q., Cheung, J.W., Couvy-Duchesne, B., Dale, A.M., Dalvie, S., de Araujo, T.K., de Zubicaray, G.I., de Zwarte, S.M.C., den Braber, A., Doan, N.T., Dohm, K., Ehrlich, S., Engelbrecht, H-R, Erk, S., Fan, C.C., Fedko, I.O., Foley, S.F., Ford, J.M., Fukunaga, M., Garrett, M.E., Ge, T., Giddaluru, S., Goldman, A.L., Green, M.J., Groenewold, N.A., Grotegerd, D., Gurholt, T.P., Gutman, B.A., Hansell, N.K., Harris, M.A., Harrison, M.B., Haswell, C.C., Hauser, M., Herms, S., Heslenfeld, D.J., Ho, N.F., Hoehn, D., Hoffmann, P., Holleran, L., Hoogman, M., Hottenga, J-J, Ikeda, M., Janowitz, D., Jansen, I.E., Jia, T., Jockwitz, C., Kanai, R., Karama, S., Kasperaviciute, D., Kaufmann, T., Kelly, S., Kikuchi, M., Klein, M., Knapp, M., Knodt, A.R., Krämer, B., Lam, M., Lancaster, T.M., Lee, P.H., Lett, T.A., Lewis, L.B., Lopes-Cendes, I., Luciano, M., Macciardi, F., Marquand, A.F., Mathias, S.R., Melzer, T.R., Milaneschi, Y., Mirza-Schreiber, N., Moreira, J.C.V., Mühleisen, T.W., Müller-Myhsok, B., Najt, P., Nakahara, S., Nho, K., Olde Loohuis, L.M., Orfanos, D.P., Pearson, J.F., Pitcher, T.L., Pütz, B., Quidé, Y., Ragothaman, A., Rashid, F.M., Reay, W.R., Redlich, R., Reinbold, C.S., Repple, J., Richard, G., Riedel, B.C., Risacher, S.L., Rocha, C.S., Mota, N.R., Salminen, L., Saremi, A., Saykin, A.J., Schlag, F., Schmaal, L., Schofield, P.R., Secolin, R., Shapland, C.Y., Shen, L., Shin, J., Shumskaya, E., Sønderby, I.E., Sprooten, E., Tansey, K.E., Teumer, A., Thalamuthu, A., Tordesillas-Gutierrez, D., Turner, J.A., Uhlmann, A., Vallerga, C.L., van der Meer, D., van Donkelaar, M.M.J., van Eijk, L., Van Erp, T.G.M., van Haren, N.E.M., Van Rooij, D., van Tol, M-J, Veldink, J.H., Verhoef, E., Walton, E., Wang, M., Wang, Y., Wardlaw, J.M., Wen, W., Westlye, L.T., Whelan, C.D., Witt, S.H., Wittfeld, K., Wolf, C., Wolfers, T., Wu, J.Q., Yasuda, C.L., Zaremba, D., Zhang, Z., Zwiers, M.P., Artiges, E., Assareh, A.A., Ayesa-Arriola, R., Belger, A., Brandt, C.L., Brown, G.G., Cichon, S., Curran, J.E., Davies, G.E., Degenhardt, F., Dennis, M.F., Dietsche, B., Djurovic, S., Doherty, C.P., Espiritu, R., Garijo, D., Gil, Y., Gowland, P.A., Green, R.C., Häusler, A.N., Heindel, W., Ho, B-C., Hoffmann, W.U., Holsboer, F., Homuth, G., Hosten, N., Jack, C.R., Jang, M., Jansen, A., Kimbrel, N.A., Kolskår, K., Koops, S., Krug, A., Lim, K.O., Luykx, J.J., Mathalon, D.H., Mather, K.A., Mattay, V.S., Matthews, S., Mayoral Van Son, J., McEwen, S.C., Melle, I., Morris, D.W., Mueller, B.A., Nauck, M., Nordvik, J.E., Nöthen, M.M., O’Leary, D.S., Opel, N., Martinot, M-L.P., Pike, G.B., Preda, A., Quinlan, E.B., Rasser, P.E., Ratnakar, V., Reppermund, S., Steen, V.M., Tooney, P.A., Torres, F.R., Veltman, D.J., Voyvodic, J.T., Whelan, R., White, T., Yamamori, H., Adams, H.H.H., Bis, J.C., Debette, S., DeCarli, C., Fornage, M., Gudnason, V., Hofer, E., Ikram, M.A., Launer, L., Longstreth, W.T., Lopez, O.L., Mazoyer, B., Mosley, T.H., Roshchupkin, G.V., Satizabal, C.L., Schmidt, R., Seshadri, S., Yang, Q., Alvim, M.K.M., Ames, D., Anderson, T.J., Andreassen, O.A., Arias-Vasquez, A., Bastin, M.E., Baune, B.T., Beckham, J.C., Blangero, J., Boomsma, D.I., Brodaty, H., Brunner, H.G., Buckner, R.L., Buitelaar, J.K., Bustillo, J.R., Cahn, W., Cairns, M.J., Calhoun, V., Carr, V.J., Caseras, X., Caspers, S., Cavalleri, G.L., Cendes, F., Corvin, A., Crespo-Facorro, B., Dalrymple-Alford, J.C., Dannlowski, U., de Geus, E.J.C., Deary, I.J., Delanty, N., Depondt, C., Desrivières, S., Donohoe, G., Espeseth, T., Fernández, G., Fisher, S.E., Flor, H., Forstner, A.J., Francks, C., Franke, B., Glahn, D.C., Gollub, R.L., Grabe, H.J., Gruber, O., Håberg, A.K., Hariri, A.R., Hartman, C.A., Hashimoto, R., Heinz, A., Henskens, F.A., Hillegers, M.H.J., Hoekstra, P.J., Holmes, A.J., Hong, L.E., Hopkins, W.D., Hulshoff Pol, H.E., Jernigan, T.L., Jönsson, E.G., Kahn, R.S., Kennedy, M.A., Kircher, T.T.J., Kochunov, P., Kwok, J.B.J., Le Hellard, S., Loughland, C.M., Martin, N.G., Martinot, J-L, McDonald, C., McMahon, K.L., Meyer-Lindenberg, A., Michie, P.T., Morey, R.A., Mowry, B., Nyberg, L., Oosterlaan, J., Ophoff, R.A., Pantelis, C., Paus, T., Pausova, Z., Penninx, B.W.J.H., Polderman, T.J.C., Posthuma, D., Rietschel, M., Roffman, J.L., Rowland, L.M., Sachdev, P.S., Sämann, P.G., Schall, U., Schumann, G., Scott, R.J., Sim, K., Sisodiya, S.M., Smoller, J.W., Sommer, I.E., St Pourcain, B., Stein, D.J., Toga, A.W., Trollor, J.N., van der Wee, N.J.A., van ’t Ent, D., Völzke, H., Walter, H., Weber, B., Weinberger, D.R., Wright, M.J., Zhou, J., Stein, J.L., Thompson, P.M., and Medland, S.E.
Abstract: INTRODUCTION The cerebral cortex underlies our complex cognitive capabilities. Variations in human cortical surface area and thickness are associated with neurological, psychological, and behavioral traits and can be measured in vivo by magnetic resonance imaging (MRI). Studies in model organisms have identified genes that influence cortical structure, but little is known about common genetic variants that affect human cortical structure. RATIONALE To identify genetic variants associated with human cortical structure at both global and regional levels, we conducted a genome-wide association meta-analysis of brain MRI data from 51,665 individuals across 60 cohorts. We analyzed the surface area and average thickness of the whole cortex and 34 cortical regions with known functional specializations. RESULTS We identified 306 nominally genome-wide significant loci (P < 5 × 10−8) associated with cortical structure in a discovery sample of 33,992 participants of European ancestry. Of the 299 loci for which replication data were available, 241 loci influencing surface area and 14 influencing thickness remained significant after replication, with 199 loci passing multiple testing correction (P < 8.3 × 10−10; 187 influencing surface area and 12 influencing thickness). Common genetic variants explained 34% (SE = 3%) of the variation in total surface area and 26% (SE = 2%) in average thickness; surface area and thickness showed a negative genetic correlation (rG = −0.32, SE = 0.05, P = 6.5 × 10−12), which suggests that genetic influences have opposing effects on surface area and thickness. Bioinformatic analyses showed that total surface area is influenced by genetic variants that alter gene regulatory activity in neural progenitor cells during fetal development. By contrast, average thickness is influenced by active regulatory elements in adult brain samples, which may reflect processes that occur after mid-fetal development, such as myelination, branching, or pruning. When co
Published: 2020

5. The genetic architecture of the human cerebral cortex

Author: Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Ching, CRK, McMahon, MAB, Shatokhina, N, Zsembik, LCP, Thomopoulos, SI, Zhu, AH, Strike, LT, Agartz, I, Alhusaini, S, Almeida, MAA, Alnaes, D, Amlien, IK, Andersson, M, Ard, T, Armstrong, NJ, Ashley-Koch, A, Atkins, JR, Bernard, M, Brouwer, RM, Buimer, EEL, Bulow, R, Burger, C, Cannon, DM, Chakravarty, M, Chen, Q, Cheung, JW, Couvy-Duchesne, B, Dale, AM, Dalvie, S, de Araujo, TK, de Zubicaray, GI, de Zwarte, SMC, den Braber, A, Nhat, TD, Dohm, K, Ehrlich, S, Engelbrecht, H-R, Erk, S, Fan, CC, Fedko, IO, Foley, SF, Ford, JM, Fukunaga, M, Garrett, ME, Ge, T, Giddaluru, S, Goldman, AL, Green, MJ, Groenewold, NA, Grotegerd, D, Gurholt, TP, Gutman, BA, Hansell, NK, Harris, MA, Harrison, MB, Haswell, CC, Hauser, M, Herms, S, Heslenfeld, DJ, Ho, NF, Hoehn, D, Hoffmann, P, Holleran, L, Hoogman, M, Hottenga, J-J, Ikeda, M, Janowitz, D, Jansen, IE, Jia, T, Jockwitz, C, Kanai, R, Karama, S, Kasperaviciute, D, Kaufmann, T, Kelly, S, Kikuchi, M, Klein, M, Knapp, M, Knodt, AR, Kramer, B, Lam, M, Lancaster, TM, Lee, PH, Lett, TA, Lewis, LB, Lopes-Cendes, I, Luciano, M, Macciardi, F, Marquand, AF, Mathias, SR, Melzer, TR, Milaneschi, Y, Mirza-Schreiber, N, Moreira, JCV, Muhleisen, TW, Mueller-Myhsok, B, Najt, P, Nakahara, S, Nho, K, Loohuis, LMO, Orfanos, DP, Pearson, JF, Pitcher, TL, Putz, B, Quide, Y, Ragothaman, A, Rashid, FM, Reay, WR, Redlich, R, Reinbold, CS, Repple, J, Richard, G, Riedel, BC, Risacher, SL, Rocha, CS, Mota, NR, Salminen, L, Saremi, A, Saykin, AJ, Schlag, F, Schmaal, L, Schofield, PR, Secolin, R, Shapland, CY, Shen, L, Shin, J, Shumskaya, E, Sonderby, IE, Sprooten, E, Tansey, KE, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Turner, JA, Uhlmann, A, Vallerga, CL, van der Meer, D, van Donkelaar, MMJ, van Eijk, L, van Erp, TGM, van Haren, NEM, van Rooij, D, van Tol, M-J, Veldink, JH, Verhoef, E, Walton, E, Wang, M, Wang, Y, Wardlaw, JM, Wen, W, Westlye, LT, Whelan, CD, Witt, SH, Wittfeld, K, Wolf, C, Wolfers, T, Wu, JQ, Yasuda, CL, Zaremba, D, Zhang, Z, Zwiers, MP, Artiges, E, Assareh, AA, Ayesa-Arriola, R, Belger, A, Brandt, CL, Brown, GG, Cichon, S, Curran, JE, Davies, GE, Degenhardt, F, Dennis, MF, Dietsche, B, Djurovic, S, Doherty, CP, Espiritu, R, Garijo, D, Gil, Y, Gowland, PA, Green, RC, Hausler, AN, Heindel, W, Ho, B-C, Hoffmann, WU, Holsboer, F, Homuth, G, Hosten, N, Jack, CR, Jang, M, Jansen, A, Kimbrel, NA, Kolskar, K, Koops, S, Krug, A, Lim, KO, Luykx, JJ, Mathalon, DH, Mather, KA, Mattay, VS, Matthews, S, Van Son, JM, McEwen, SC, Melle, I, Morris, DW, Mueller, BA, Nauck, M, Nordvik, JE, Noethen, MM, O'Leary, DS, Opel, N, Martinot, M-LP, Pike, GB, Preda, A, Quinlan, EB, Rasser, PE, Ratnakar, V, Reppermund, S, Steen, VM, Tooney, PA, Torres, FR, Veltman, DJ, Voyvodic, JT, Whelan, R, White, T, Yamamori, H, Adams, HHH, Bis, JC, Debette, S, Decarli, C, Fornage, M, Gudnason, V, Hofer, E, Ikram, MA, Launer, L, Longstreth, WT, Lopez, OL, Mazoyer, B, Mosley, TH, Roshchupkin, GV, Satizabal, CL, Schmidt, R, Seshadri, S, Yang, Q, Alvim, MKM, Ames, D, Anderson, TJ, Andreassen, OA, Arias-Vasquez, A, Bastin, ME, Baune, BT, Beckham, JC, Blangero, J, Boomsma, DI, Brodaty, H, Brunner, HG, Buckner, RL, Buitelaar, JK, Bustillo, JR, Cahn, W, Cairns, MJ, Calhoun, V, Carr, VJ, Caseras, X, Caspers, S, Cavalleri, GL, Cendes, F, Corvin, A, Crespo-Facorro, B, Dalrymple-Alford, JC, Dannlowski, U, de Geus, EJC, Deary, IJ, Delanty, N, Depondt, C, Desrivieres, S, Donohoe, G, Espeseth, T, Fernandez, G, Fisher, SE, Flor, H, Forstner, AJ, Francks, C, Franke, B, Glahn, DC, Gollub, RL, Grabe, HJ, Gruber, O, Haberg, AK, Hariri, AR, Hartman, CA, Hashimoto, R, Heinz, A, Henskens, FA, Hillegers, MHJ, Hoekstra, PJ, Holmes, AJ, Hong, LE, Hopkins, WD, Pol, HEH, Jernigan, TL, Jonsson, EG, Kahn, RS, Kennedy, MA, Kircher, TTJ, Kochunov, P, Kwok, JBJ, Le Hellard, S, Loughland, CM, Martin, NG, Martinot, J-L, McDonald, C, McMahon, KL, Meyer-Lindenberg, A, Michie, PT, Morey, RA, Mowry, B, Nyberg, L, Oosterlaan, J, Ophoff, RA, Pantelis, C, Paus, T, Pausova, Z, Penninx, BWJH, Polderman, TJC, Posthuma, D, Rietschel, M, Roffman, JL, Rowland, LM, Sachdev, PS, Samann, PG, Schall, U, Schumann, G, Scott, RJ, Sim, K, Sisodiya, SM, Smoller, JW, Sommer, IE, St Pourcain, B, Stein, DJ, Toga, AW, Trollor, JN, Van der Wee, NJA, van't Ent, D, Volzke, H, Walter, H, Weber, B, Weinberger, DR, Wright, MJ, Zhou, J, Stein, JL, Thompson, PM, Medland, SE, Grasby, KL, Jahanshad, N, Painter, JN, Colodro-Conde, L, Bralten, J, Hibar, DP, Lind, PA, Pizzagalli, F, Ching, CRK, McMahon, MAB, Shatokhina, N, Zsembik, LCP, Thomopoulos, SI, Zhu, AH, Strike, LT, Agartz, I, Alhusaini, S, Almeida, MAA, Alnaes, D, Amlien, IK, Andersson, M, Ard, T, Armstrong, NJ, Ashley-Koch, A, Atkins, JR, Bernard, M, Brouwer, RM, Buimer, EEL, Bulow, R, Burger, C, Cannon, DM, Chakravarty, M, Chen, Q, Cheung, JW, Couvy-Duchesne, B, Dale, AM, Dalvie, S, de Araujo, TK, de Zubicaray, GI, de Zwarte, SMC, den Braber, A, Nhat, TD, Dohm, K, Ehrlich, S, Engelbrecht, H-R, Erk, S, Fan, CC, Fedko, IO, Foley, SF, Ford, JM, Fukunaga, M, Garrett, ME, Ge, T, Giddaluru, S, Goldman, AL, Green, MJ, Groenewold, NA, Grotegerd, D, Gurholt, TP, Gutman, BA, Hansell, NK, Harris, MA, Harrison, MB, Haswell, CC, Hauser, M, Herms, S, Heslenfeld, DJ, Ho, NF, Hoehn, D, Hoffmann, P, Holleran, L, Hoogman, M, Hottenga, J-J, Ikeda, M, Janowitz, D, Jansen, IE, Jia, T, Jockwitz, C, Kanai, R, Karama, S, Kasperaviciute, D, Kaufmann, T, Kelly, S, Kikuchi, M, Klein, M, Knapp, M, Knodt, AR, Kramer, B, Lam, M, Lancaster, TM, Lee, PH, Lett, TA, Lewis, LB, Lopes-Cendes, I, Luciano, M, Macciardi, F, Marquand, AF, Mathias, SR, Melzer, TR, Milaneschi, Y, Mirza-Schreiber, N, Moreira, JCV, Muhleisen, TW, Mueller-Myhsok, B, Najt, P, Nakahara, S, Nho, K, Loohuis, LMO, Orfanos, DP, Pearson, JF, Pitcher, TL, Putz, B, Quide, Y, Ragothaman, A, Rashid, FM, Reay, WR, Redlich, R, Reinbold, CS, Repple, J, Richard, G, Riedel, BC, Risacher, SL, Rocha, CS, Mota, NR, Salminen, L, Saremi, A, Saykin, AJ, Schlag, F, Schmaal, L, Schofield, PR, Secolin, R, Shapland, CY, Shen, L, Shin, J, Shumskaya, E, Sonderby, IE, Sprooten, E, Tansey, KE, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Turner, JA, Uhlmann, A, Vallerga, CL, van der Meer, D, van Donkelaar, MMJ, van Eijk, L, van Erp, TGM, van Haren, NEM, van Rooij, D, van Tol, M-J, Veldink, JH, Verhoef, E, Walton, E, Wang, M, Wang, Y, Wardlaw, JM, Wen, W, Westlye, LT, Whelan, CD, Witt, SH, Wittfeld, K, Wolf, C, Wolfers, T, Wu, JQ, Yasuda, CL, Zaremba, D, Zhang, Z, Zwiers, MP, Artiges, E, Assareh, AA, Ayesa-Arriola, R, Belger, A, Brandt, CL, Brown, GG, Cichon, S, Curran, JE, Davies, GE, Degenhardt, F, Dennis, MF, Dietsche, B, Djurovic, S, Doherty, CP, Espiritu, R, Garijo, D, Gil, Y, Gowland, PA, Green, RC, Hausler, AN, Heindel, W, Ho, B-C, Hoffmann, WU, Holsboer, F, Homuth, G, Hosten, N, Jack, CR, Jang, M, Jansen, A, Kimbrel, NA, Kolskar, K, Koops, S, Krug, A, Lim, KO, Luykx, JJ, Mathalon, DH, Mather, KA, Mattay, VS, Matthews, S, Van Son, JM, McEwen, SC, Melle, I, Morris, DW, Mueller, BA, Nauck, M, Nordvik, JE, Noethen, MM, O'Leary, DS, Opel, N, Martinot, M-LP, Pike, GB, Preda, A, Quinlan, EB, Rasser, PE, Ratnakar, V, Reppermund, S, Steen, VM, Tooney, PA, Torres, FR, Veltman, DJ, Voyvodic, JT, Whelan, R, White, T, Yamamori, H, Adams, HHH, Bis, JC, Debette, S, Decarli, C, Fornage, M, Gudnason, V, Hofer, E, Ikram, MA, Launer, L, Longstreth, WT, Lopez, OL, Mazoyer, B, Mosley, TH, Roshchupkin, GV, Satizabal, CL, Schmidt, R, Seshadri, S, Yang, Q, Alvim, MKM, Ames, D, Anderson, TJ, Andreassen, OA, Arias-Vasquez, A, Bastin, ME, Baune, BT, Beckham, JC, Blangero, J, Boomsma, DI, Brodaty, H, Brunner, HG, Buckner, RL, Buitelaar, JK, Bustillo, JR, Cahn, W, Cairns, MJ, Calhoun, V, Carr, VJ, Caseras, X, Caspers, S, Cavalleri, GL, Cendes, F, Corvin, A, Crespo-Facorro, B, Dalrymple-Alford, JC, Dannlowski, U, de Geus, EJC, Deary, IJ, Delanty, N, Depondt, C, Desrivieres, S, Donohoe, G, Espeseth, T, Fernandez, G, Fisher, SE, Flor, H, Forstner, AJ, Francks, C, Franke, B, Glahn, DC, Gollub, RL, Grabe, HJ, Gruber, O, Haberg, AK, Hariri, AR, Hartman, CA, Hashimoto, R, Heinz, A, Henskens, FA, Hillegers, MHJ, Hoekstra, PJ, Holmes, AJ, Hong, LE, Hopkins, WD, Pol, HEH, Jernigan, TL, Jonsson, EG, Kahn, RS, Kennedy, MA, Kircher, TTJ, Kochunov, P, Kwok, JBJ, Le Hellard, S, Loughland, CM, Martin, NG, Martinot, J-L, McDonald, C, McMahon, KL, Meyer-Lindenberg, A, Michie, PT, Morey, RA, Mowry, B, Nyberg, L, Oosterlaan, J, Ophoff, RA, Pantelis, C, Paus, T, Pausova, Z, Penninx, BWJH, Polderman, TJC, Posthuma, D, Rietschel, M, Roffman, JL, Rowland, LM, Sachdev, PS, Samann, PG, Schall, U, Schumann, G, Scott, RJ, Sim, K, Sisodiya, SM, Smoller, JW, Sommer, IE, St Pourcain, B, Stein, DJ, Toga, AW, Trollor, JN, Van der Wee, NJA, van't Ent, D, Volzke, H, Walter, H, Weber, B, Weinberger, DR, Wright, MJ, Zhou, J, Stein, JL, Thompson, PM, and Medland, SE
Abstract: The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.
Published: 2020

6. 10Kin1day: A Bottom-Up Neuroimaging Initiative

Author: Heuvel, M.P. van den, Scholtens, L.H., Burgh, H.K. van der, Agosta, F., Alloza, C., Arango, C., Auyeung, B., Baron-Cohen, S., Basaia, S., Benders, M., Beyer, F., Booij, L., Braun, K.P., Filho, G.B., Cahn, W., Cannon, D.M., Chaim-Avancini, T.M., Chan, S.S., Chen, E.Y.H., Crespo-Facorro, B., Crone, E.A.M., Dannlowski, U., Zwarte, S.M.C. de, Dietsche, B., Donohoe, G., Plessis, S.D., Durston, S., Diaz-Caneja, C.M., Diaz-Zuluaga, A.M., Emsley, R., Filippi, M., Frodl, T., Gorges, M., Graff, B., Grotegerd, D., Gasecki, D., Hall, J.M., Holleran, L., Holt, R., Hopman, H.J., Jansen, A, Janssen, J, Jodzio, K., Jancke, L., Kaleda, V.G., Kassubek, J., Masouleh, S.K., Kircher, T., Koevoets, M., Kostic, V.S., Krug, A., Lawrie, S.M., Lebedeva, I.S., Lee, E.H.M., Lett, T.A., Lewis, S.J., Liem, F., Lombardo, M.V., Lopez-Jaramillo, C., Margulies, D.S., Markett, S., Marques, P., Martinez-Zalacain, I., McDonald, C., McIntosh, A.M., McPhilemy, G., Meinert, S.L., Menchon, J.M., Montag, C., Moreira, P.S., Morgado, P., Mothersill, D.O., Merillat, S., Muller, H.P., Nabulsi, L., Najt, P., Narkiewicz, K., Naumczyk, P., Oranje, B., Foz, V. Ortiz-Garcia de, Peper, J.S., Pineda, J.A., Rasser, P.E., Redlich, R., Repple, J., Reuter, M, Rosa, P.G., Ruigrok, A.N., Sabisz, A., Schall, U., Seedat, S., Serpa, M.H., Skouras, S., Soriano-Mas, C., Sousa, N., Szurowska, E., Tomyshev, A.S., Tordesillas-Gutierrez, D., Valk, S.L., Berg, L.H. van den, Leeuwen, J.M.C. van, Zhang, R., Lange, S.C. de, Heuvel, M.P. van den, Scholtens, L.H., Burgh, H.K. van der, Agosta, F., Alloza, C., Arango, C., Auyeung, B., Baron-Cohen, S., Basaia, S., Benders, M., Beyer, F., Booij, L., Braun, K.P., Filho, G.B., Cahn, W., Cannon, D.M., Chaim-Avancini, T.M., Chan, S.S., Chen, E.Y.H., Crespo-Facorro, B., Crone, E.A.M., Dannlowski, U., Zwarte, S.M.C. de, Dietsche, B., Donohoe, G., Plessis, S.D., Durston, S., Diaz-Caneja, C.M., Diaz-Zuluaga, A.M., Emsley, R., Filippi, M., Frodl, T., Gorges, M., Graff, B., Grotegerd, D., Gasecki, D., Hall, J.M., Holleran, L., Holt, R., Hopman, H.J., Jansen, A, Janssen, J, Jodzio, K., Jancke, L., Kaleda, V.G., Kassubek, J., Masouleh, S.K., Kircher, T., Koevoets, M., Kostic, V.S., Krug, A., Lawrie, S.M., Lebedeva, I.S., Lee, E.H.M., Lett, T.A., Lewis, S.J., Liem, F., Lombardo, M.V., Lopez-Jaramillo, C., Margulies, D.S., Markett, S., Marques, P., Martinez-Zalacain, I., McDonald, C., McIntosh, A.M., McPhilemy, G., Meinert, S.L., Menchon, J.M., Montag, C., Moreira, P.S., Morgado, P., Mothersill, D.O., Merillat, S., Muller, H.P., Nabulsi, L., Najt, P., Narkiewicz, K., Naumczyk, P., Oranje, B., Foz, V. Ortiz-Garcia de, Peper, J.S., Pineda, J.A., Rasser, P.E., Redlich, R., Repple, J., Reuter, M, Rosa, P.G., Ruigrok, A.N., Sabisz, A., Schall, U., Seedat, S., Serpa, M.H., Skouras, S., Soriano-Mas, C., Sousa, N., Szurowska, E., Tomyshev, A.S., Tordesillas-Gutierrez, D., Valk, S.L., Berg, L.H. van den, Leeuwen, J.M.C. van, Zhang, R., and Lange, S.C. de
Abstract: Contains fulltext : 208767.pdf (publisher's version ) (Open Access), We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.
Published: 2019

7. 10kin1day: A bottom-up neuroimaging initiative

Author: Heuvel, M. (Martijn) van den, Scholtens, L.H. (Lianne H.), Van Der Burgh, H.K. (Hannelore K.), Agosta, F. (Federica), Alloza, C. (Clara), Arango, C. (Celso), Auyeung, B. (Bonnie), Baron-Cohen, S. (Simon), Basaia, S. (Silvia), Benders, J. (Jos), Beyer, F. (Frauke), Booij, L. (Linda), Braun, K.P.J. (Kees P.J.), Filho, G.B. (Geraldo Busatto), Cahn, W. (Wiepke), Cannon, D.M. (Dara), Chaim-Avancini, T.M. (Tiffany M.), Chan, S.S.M. (Sandra S.M.), Chen, E.Y.H. (Eric Y.H.), Crespo-Facorro, B. (Benedicto), Crone, E.A. (Eveline), Dannlowski, U. (Udo), De Zwarte, S.M.C. (Sonja M.C.), Dietsche, B. (Bruno), Donohoe, D.J. (Dennis), Plessis, S.D. (Stefan Du), Durston, S. (Sarah), Díaz-Caneja, C.M. (Covadonga M.), Díaz-Zuluaga, A.M. (Ana M.), Emsley, R. (Robin), Filippi, M. (Massimo), Frodl, T. (Thomas), Gorges, M. (Martin), Graff, B. (Beata), Grotegerd, D. (Dominik), Gąsecki, D. (Dariusz), Hall, J.M. (Julie M.), Holleran, L. (Laurena), Holt, R. (Rosemary), Hopman, H.J. (Helene J.), Jansen, A. (Andreas), Janssen, J. (Joost), Jodzio, K. (Krzysztof), Jäncke, L. (Lutz), Kaleda, V.G. (Vasiliy G.), Kassubek, J. (Jan), Masouleh, S.K. (Shahrzad Kharabian), Kircher, T. (Tilo), Koevoets, M.G.J.C. (Martijn G.J.C.), Kostic, V.S. (Vladimir S.), Krug, A. (Axel), Lawrie, S. (Stephen), Lebedeva, I.S. (Irina S.), Lee, E.H.M. (Edwin H.M.), Lett, T.A. (Tristram A.), Lewis, S.J.G. (Simon J.G.), Liem, F. (Franziskus), Lombardo, M.V. (Michael V.), Lopez-Jaramillo, C. (Carlos), Margulies, D.S. (Daniel S.), Markett, S. (Sebastian), Marques, P. (Paulo), Martínez-Zalacaín, I. (Ignacio), McDonald, C. (Colm), McIntosh, A.M. (Andrew), McPhilemy, G. (Genevieve), Meinert, S.L. (Susanne L.), Menchón, J.M. (José M.), Montag, C. (Christian), Moreira, P.S. (Pedro S.), Morgado, P. (Pedro), Mothersill, D.O. (David O.), Mérillat, S. (Susan), Müller, H.-P. (Hans-Peter), Nabulsi, L. (Leila), Najt, P. (Pablo), Narkiewicz, K. (Krzysztof), Naumczyk, P. (Patrycja), Oranje, B. (Bob), De la Foz, V.O.-G. (Victor Ortiz-Garcia), Peper, J.S. (Jiska S.), Pineda, J.A. (Julian A.), Rasser, P.E. (Paul E.), Redlich, R. (Ronny), Repple, J. (Jonathan), Reuter, M. (Martin), Rosa, P.G.P. (Pedro G.P.), Ruigrok, A.N.V. (Amber N.V.), Sabisz, A. (Agnieszka), Schall, U. (Ulrich), Seedat, S. (Soraya), Serpa, M.H. (Mauricio H.), Skouras, S. (Stavros), Soriano-Mas, C. (Carles), Sousa, N. (Nuno), Szurowska, E. (Edyta), Tomyshev, A.S. (Alexander S.), Tordesillas-Gutierrez, D. (Diana), Valk, S.L. (Sofie L.), Berg, L.H. (Leonard) van den, Erp, T.G.M. (Theo G.) van, Van Haren, N.E.M. (Neeltje E.M.), Van Leeuwen, J.M.C. (Judith M.C.), Villringer, A. (Arno), Vinkers, C.H., Vollmar, C. (Christian), Waller, L. (Lea), Walter, H. (Henrik), Whalley, H.C. (Heather C.), Witkowska, M. (Marta), Witte, A.V. (A. Veronica), Zanetti, M.V. (Marcus V.), Zhang, R. (Rui), De Lange, S.C. (Siemon C.), Heuvel, M. (Martijn) van den, Scholtens, L.H. (Lianne H.), Van Der Burgh, H.K. (Hannelore K.), Agosta, F. (Federica), Alloza, C. (Clara), Arango, C. (Celso), Auyeung, B. (Bonnie), Baron-Cohen, S. (Simon), Basaia, S. (Silvia), Benders, J. (Jos), Beyer, F. (Frauke), Booij, L. (Linda), Braun, K.P.J. (Kees P.J.), Filho, G.B. (Geraldo Busatto), Cahn, W. (Wiepke), Cannon, D.M. (Dara), Chaim-Avancini, T.M. (Tiffany M.), Chan, S.S.M. (Sandra S.M.), Chen, E.Y.H. (Eric Y.H.), Crespo-Facorro, B. (Benedicto), Crone, E.A. (Eveline), Dannlowski, U. (Udo), De Zwarte, S.M.C. (Sonja M.C.), Dietsche, B. (Bruno), Donohoe, D.J. (Dennis), Plessis, S.D. (Stefan Du), Durston, S. (Sarah), Díaz-Caneja, C.M. (Covadonga M.), Díaz-Zuluaga, A.M. (Ana M.), Emsley, R. (Robin), Filippi, M. (Massimo), Frodl, T. (Thomas), Gorges, M. (Martin), Graff, B. (Beata), Grotegerd, D. (Dominik), Gąsecki, D. (Dariusz), Hall, J.M. (Julie M.), Holleran, L. (Laurena), Holt, R. (Rosemary), Hopman, H.J. (Helene J.), Jansen, A. (Andreas), Janssen, J. (Joost), Jodzio, K. (Krzysztof), Jäncke, L. (Lutz), Kaleda, V.G. (Vasiliy G.), Kassubek, J. (Jan), Masouleh, S.K. (Shahrzad Kharabian), Kircher, T. (Tilo), Koevoets, M.G.J.C. (Martijn G.J.C.), Kostic, V.S. (Vladimir S.), Krug, A. (Axel), Lawrie, S. (Stephen), Lebedeva, I.S. (Irina S.), Lee, E.H.M. (Edwin H.M.), Lett, T.A. (Tristram A.), Lewis, S.J.G. (Simon J.G.), Liem, F. (Franziskus), Lombardo, M.V. (Michael V.), Lopez-Jaramillo, C. (Carlos), Margulies, D.S. (Daniel S.), Markett, S. (Sebastian), Marques, P. (Paulo), Martínez-Zalacaín, I. (Ignacio), McDonald, C. (Colm), McIntosh, A.M. (Andrew), McPhilemy, G. (Genevieve), Meinert, S.L. (Susanne L.), Menchón, J.M. (José M.), Montag, C. (Christian), Moreira, P.S. (Pedro S.), Morgado, P. (Pedro), Mothersill, D.O. (David O.), Mérillat, S. (Susan), Müller, H.-P. (Hans-Peter), Nabulsi, L. (Leila), Najt, P. (Pablo), Narkiewicz, K. (Krzysztof), Naumczyk, P. (Patrycja), Oranje, B. (Bob), De la Foz, V.O.-G. (Victor Ortiz-Garcia), Peper, J.S. (Jiska S.), Pineda, J.A. (Julian A.), Rasser, P.E. (Paul E.), Redlich, R. (Ronny), Repple, J. (Jonathan), Reuter, M. (Martin), Rosa, P.G.P. (Pedro G.P.), Ruigrok, A.N.V. (Amber N.V.), Sabisz, A. (Agnieszka), Schall, U. (Ulrich), Seedat, S. (Soraya), Serpa, M.H. (Mauricio H.), Skouras, S. (Stavros), Soriano-Mas, C. (Carles), Sousa, N. (Nuno), Szurowska, E. (Edyta), Tomyshev, A.S. (Alexander S.), Tordesillas-Gutierrez, D. (Diana), Valk, S.L. (Sofie L.), Berg, L.H. (Leonard) van den, Erp, T.G.M. (Theo G.) van, Van Haren, N.E.M. (Neeltje E.M.), Van Leeuwen, J.M.C. (Judith M.C.), Villringer, A. (Arno), Vinkers, C.H., Vollmar, C. (Christian), Waller, L. (Lea), Walter, H. (Henrik), Whalley, H.C. (Heather C.), Witkowska, M. (Marta), Witte, A.V. (A. Veronica), Zanetti, M.V. (Marcus V.), Zhang, R. (Rui), and De Lange, S.C. (Siemon C.)
Abstract: We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain. Ongoing grand-scale projects like the European Human Brain Project (1), the US Brain Initiative (2), the Human Connectome Project (3), the Chinese Brainnetome (4) and exciting world-wide neuroimaging collaborations such as ENIGMA (5) herald the new era of big neuroscience. In conjunction with these major undertakings, there is an emerging trend for bottom-up initiatives, starting with small-scale projects built upon existing collaborations and infrastructures. As described by Mainen et al. (6), these initiatives are centralized around self-organized groups of researchers working on the same challenges and sharing interests and specialized expertise. These projects could scale and open up to a larger audience and other disciplines over time, eventually lining up and merging their findings with other programs to make the bigger picture.
Published: 2019
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8. Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA consortium

Author: Kong, XZ, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H ; https://orcid.org/0000-0001-9487-6617, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Canive, JM, Cannon, DM, Caparelli, EC, Castellanos, FX, Cavalleri, GL, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dale, A, Dannlowski, U, De Bruttopilo, SA, De Zeeuw, P, Deary, IJ, Delanty, N, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, J ; https://orcid.org/0000-0003-4014-4490, Garavan, H, Garcia, DDS, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, Hernández, MDCV, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Roberts, Gloria ; https://orcid.org/0000-0002-1966-5120, Lenroot, Rhoshel ; https://orcid.org/0000-0002-0949-5121, Sachdev, Perminder ; https://orcid.org/0000-0002-9595-3220, Wen, Wei ; https://orcid.org/0000-0003-2753-3870, Fisher, Simon, Kong, XZ, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H ; https://orcid.org/0000-0001-9487-6617, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Canive, JM, Cannon, DM, Caparelli, EC, Castellanos, FX, Cavalleri, GL, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dale, A, Dannlowski, U, De Bruttopilo, SA, De Zeeuw, P, Deary, IJ, Delanty, N, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, J ; https://orcid.org/0000-0003-4014-4490, Garavan, H, Garcia, DDS, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, Hernández, MDCV, Mitchell, Philip ; https://orcid.org/0000-0002-7954-5235, Roberts, Gloria ; https://orcid.org/0000-0002-1966-5120, Lenroot, Rhoshel ; https://orcid.org/0000-0002-0949-5121, Sachdev, Perminder ; https://orcid.org/0000-0002-9595-3220, Wen, Wei ; https://orcid.org/0000-0003-2753-3870, and Fisher, Simon
Abstract: Hemispheric asymmetry is a cardinal feature of human brain organization. Altered brain asymmetry has also been linked to some cognitive and neuropsychiatric disorders. Here, the ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Consortium presents the largest-ever analysis of cerebral cortical asymmetry and its variability across individuals. Cortical thickness and surface area were assessed in MRI scans of 17,141 healthy individuals from 99 datasets worldwide. Results revealed widespread asymmetries at both hemispheric and regional levels, with a generally thicker cortex but smaller surface area in the left hemisphere relative to the right. Regionally, asymmetries of cortical thickness and/or surface area were found in the inferior frontal gyrus, transverse temporal gyrus, parahippocampal gyrus, and entorhinal cortex. These regions are involved in lateralized functions, including language and visuospatial processing. In addition to population-level asymmetries, variability in brain asymmetry was related to sex, age, and intracranial volume. Interestingly, we did not find significant associations between asymmetries and handedness. Finally, with two independent pedigree datasets (n = 1,443 and 1,113, respectively), we found several asymmetries showing significant, replicable heritability. The structural asymmetries identified and their variabilities and heritability provide a reference resource for future studies on the genetic basis of brain asymmetry and altered laterality in cognitive, neurological, and psychiatric disorders.
Published: 2018

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

Author: Nunes, A. (Abraham), Schnack, H. (Hugo), Ching, C.R.K. (Christopher), Agartz, I. (Ingrid), Akudjedu, T.N. (Theophilus N.), Alda, M. (Martin), Alnæs, D. (Dag), Alonso-Lana, S. (Silvia), Bauer, J. (Jochen), Baune, B.T., Bøen, E. (Erlend), Bonnin, C.M. (Caterina del Mar), Busatto, G.F. (Geraldo F.), Canales-Rodríguez, E.J. (Erick J.), Cannon, D.M. (Dara), Caseras, X. (Xavier), Chaim-Avancini, T.M. (Tiffany M.), Dannlowski, U. (Udo), Díaz-Zuluaga, A.M. (Ana M.), Dietsche, B. (Bruno), Doan, N.T. (Nhat Trung), Duchesnay, E. (Edouard), Elvsåshagen, T. (Torbjørn), Emden, D. (Daniel), Eyler, L.T. (Lisa T.), Fatjó-Vilas, M. (Mar), Favre, P. (Pauline), Foley, S.F. (Sonya F.), Fullerton, J.M. (Janice M.), Glahn, D.C. (David), Goikolea, J.M. (Jose M.), Grotegerd, D. (Dominik), Hahn, T. (Tim), Henry, C. (C.), Hibar, D.P. (Derrek P.), Houenou, J. (Josselin), Howells, F.M. (Fleur M.), Jahanshad, N. (Neda), Kaufmann, T. (Tobias), Kenney, J. (Joanne), Kircher, T.T.J. (Tilo T. J.), Krug, A. (Axel), Lagerberg, T.V. (Trine V.), Lenroot, R.K. (Rhoshel), López-Jaramillo, C. (Carlos), Machado-Vieira, R. (Rodrigo), Malt, U.F. (Ulrik), McDonald, C. (Colm), Mitchell, P.B. (Philip B.), Mwangi, B. (Benson), Nabulsi, L. (Leila), Opel, N. (Nils), Overs, B.J. (Bronwyn J.), Pineda-Zapata, J.A. (Julian A.), Pomarol-Clotet, E. (Edith), Redlich, R. (Ronny), Roberts, G. (Gloria), Rosa, P.G. (Pedro G.), Salvador, R. (Raymond), Satterthwaite, T.D. (Theodore), Soares, J.C. (Jair C.), Stein, D.J. (Dan), Temmingh, H.S. (Henk S.), Trappenberg, T. (Thomas), Uhlmann, A. (Anne), van Haren, N.E.M. (Neeltje E. M.), Vieta, E. (Eduard), Westlye, L.T. (Lars), Wolf, D.H. (Daniel H.), Yüksel, D. (Dilara), Zanetti, M.V. (Marcus V.), Andreassen, O.A. (Ole), Thompson, P.M. (Paul), Hajek, T. (Tomas), Nunes, A. (Abraham), Schnack, H. (Hugo), Ching, C.R.K. (Christopher), Agartz, I. (Ingrid), Akudjedu, T.N. (Theophilus N.), Alda, M. (Martin), Alnæs, D. (Dag), Alonso-Lana, S. (Silvia), Bauer, J. (Jochen), Baune, B.T., Bøen, E. (Erlend), Bonnin, C.M. (Caterina del Mar), Busatto, G.F. (Geraldo F.), Canales-Rodríguez, E.J. (Erick J.), Cannon, D.M. (Dara), Caseras, X. (Xavier), Chaim-Avancini, T.M. (Tiffany M.), Dannlowski, U. (Udo), Díaz-Zuluaga, A.M. (Ana M.), Dietsche, B. (Bruno), Doan, N.T. (Nhat Trung), Duchesnay, E. (Edouard), Elvsåshagen, T. (Torbjørn), Emden, D. (Daniel), Eyler, L.T. (Lisa T.), Fatjó-Vilas, M. (Mar), Favre, P. (Pauline), Foley, S.F. (Sonya F.), Fullerton, J.M. (Janice M.), Glahn, D.C. (David), Goikolea, J.M. (Jose M.), Grotegerd, D. (Dominik), Hahn, T. (Tim), Henry, C. (C.), Hibar, D.P. (Derrek P.), Houenou, J. (Josselin), Howells, F.M. (Fleur M.), Jahanshad, N. (Neda), Kaufmann, T. (Tobias), Kenney, J. (Joanne), Kircher, T.T.J. (Tilo T. J.), Krug, A. (Axel), Lagerberg, T.V. (Trine V.), Lenroot, R.K. (Rhoshel), López-Jaramillo, C. (Carlos), Machado-Vieira, R. (Rodrigo), Malt, U.F. (Ulrik), McDonald, C. (Colm), Mitchell, P.B. (Philip B.), Mwangi, B. (Benson), Nabulsi, L. (Leila), Opel, N. (Nils), Overs, B.J. (Bronwyn J.), Pineda-Zapata, J.A. (Julian A.), Pomarol-Clotet, E. (Edith), Redlich, R. (Ronny), Roberts, G. (Gloria), Rosa, P.G. (Pedro G.), Salvador, R. (Raymond), Satterthwaite, T.D. (Theodore), Soares, J.C. (Jair C.), Stein, D.J. (Dan), Temmingh, H.S. (Henk S.), Trappenberg, T. (Thomas), Uhlmann, A. (Anne), van Haren, N.E.M. (Neeltje E. M.), Vieta, E. (Eduard), Westlye, L.T. (Lars), Wolf, D.H. (Daniel H.), Yüksel, D. (Dilara), Zanetti, M.V. (Marcus V.), Andreassen, O.A. (Ole), Thompson, P.M. (Paul), and Hajek, T. (Tomas)
Abstract: Bipolar disorders (BDs) are among the leading causes of morbidity and disability. Objective biological markers, such as those based on brain imaging, could aid in clinical management of BD. Machine learning (ML) brings neuroimaging analyses to individual subject level and may potentially allow for their diagnostic use. However, fair and optimal application of ML requires large, multi-site datasets. We applied ML (support vector machines) to MRI data (regional cortical thickness, surface area, subcortical volumes) from 853 BD and 2167 control participants from 13 cohorts in the ENIGMA consortium. We attempted to differentiate BD from control participants, investigated different data handling strategies and studied the neuroimaging/clinical features most important for classification. Individual site accuracies ranged from 45.23% to 81.07%. Aggregate subject-level analyses yielded the highest accuracy (65.23%, 95% CI = 63.47–67.00, ROC-AUC = 71.49%, 95% CI = 69.39–73.59), followed by leave-one-site-out cross-validation (accuracy = 58.67%, 95% CI = 56.70–60.63). Meta-analysis of individual site accuracies did not provide above chance results. There was substantial agreement between the regions that contributed to identification of BD participants in the best performing site and in the aggregate dataset (Cohen’s Kappa = 0.83, 95% CI = 0.829–0.831). Treatment with anticonvulsants and age were associated with greater odds of correct classification. Although short of the 80% clinically relevant accuracy threshold, the resul
Published: 2018
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10. L'HÉRITAGE LITTÉRAIRE DE DIDYME L'AVEUGLE

Author: Dietsche, B.
Published: 1941

11. REMOVED: PB 12 Neural correlates of psychopathological symptoms in patients with affective and psychotic disorders

Author: Bröhl, H., primary, Engelen, J., additional, Meier, F., additional, Sauder, T., additional, Dietsche, B., additional, Dannlowski, U., additional, Krug, A., additional, and Kircher, T., additional
Published: 2017
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12. Structural and metabolic changes in the anterior cingulate cortex (ACC) after treatment with repetitive transcranial magnetic stimulation (rTMS) in patients with treatment-resistant unipolar depression (TRD)

Author: Zöllner, R, additional, Bopp, M, additional, Dietsche, P, additional, Rekate, H, additional, Dietsche, B, additional, Krug, A, additional, Hanewald, B, additional, Steinsträter, O, additional, Sommer, J, additional, and Zavorotnyy, M, additional
Published: 2017
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13. The Impact of Polygenic Risk for Schizophrenia on Memory-related Activation in the Anterior Cingulate Cortex (ACC)

Author: Schmitt, S, additional, Sauder, T, additional, Meier, F, additional, Engelen, J, additional, Bröhl, H, additional, Dietsche, B, additional, Heinen, J, additional, Yüksel, D, additional, Zaremba, D, additional, Meinert, S, additional, Dohm, K, additional, Förster, K, additional, Bürger, C, additional, Redlich, R, additional, Dannlowski, U, additional, Kircher, T, additional, Krug, A, additional, and Nenadić, I, additional
Published: 2017
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14. The Impact of a Polygenic Risk for Bipolar Disorder on Memory-related Activation in the Precuneus

Author: Sauder, T, additional, Schmitt, S, additional, Meier, F, additional, Engelen, J, additional, Bröhl, H, additional, Yüksel, D, additional, Heinen, J, additional, Dietsche, B, additional, Zaremba, D, additional, Meinert, S, additional, Bürger, C, additional, Dohm, K, additional, Förster, K, additional, Redlich, R, additional, Dannlowski, U, additional, Kircher, T, additional, Krug, A, additional, and Nenadić, I, additional
Published: 2017
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15. Literaturauswertung Lebenslanges Lernen und Literaturnachweis zur Literaturauswertung Lebenslanges Lernen:Anhang 3 und Anhang 4 zur Strategie für Lebenslanges Lernen in der Bundesrepublik Deutschland

Author: Dietsche, B. (Barbara), Meyer, H.H. (Heinz), and Universitäts- und Landesbibliothek Münster
Subjects: ddc:370, Education
Abstract: Diese Literaturauswertung wurde vom DIE im Auftrag des BMBF im Zeitraum September 2003 bis Juli 2004 im Zusammenhang mit der BLK-Veröffentlichung „Strategie für Lebenslanges Lernen in der Bundesrepublik Deutschland“ (http://www.blk-bonn.de/papers/heft115.pdf) der BLK Ad-hoc-AG vorgenommen. Sie stellt Literatur zum Lernen in unterschiedlichen Lebensphasen (Kinder, Jugendliche, junge Erwachsene, Erwachsene und Ältere) und zu Entwicklungsschwerpunkten lebenslangen Lernens (Einbeziehung informellen Lernens, Selbststeuerung, Kompetenzentwicklung, Vernetzung, Modularisierung, Lernberatung, Neue Lernkultur/Popularisierung des Lernens und chancengerechter Zugang) zusammen. Ergänzt wird die Darstellung durch Informationen zur Entwicklung lebenslangen Lernens im bildungspolitischen und erziehungswissenschaftlichen Diskurs und durch die Dokumentation bildungspolitischer Dokumente des Europarats, der OECD, der UNESCO, der Europäischen Union und der Weltbank. Zur Auswertung gehört ein 23-seitiger Literaturnachweis
Published: 2005

16. P.1.h.026 Advanced paternal age as a risk factor for social deficits: from rats to humans

Author: Seffer, D., primary, Krug, A., additional, Rippberger, H., additional, Dietsche, B., additional, Backes, H., additional, Schwarting, W., additional, Kircher, T., additional, and Wöhr, M., additional
Published: 2014
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17. Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

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

18. 10Kin1day: A Bottom-Up Neuroimaging Initiative

Author: Martijn P. van den Heuvel, Lianne H. Scholtens, Hannelore K. van der Burgh, Federica Agosta, Clara Alloza, Celso Arango, Bonnie Auyeung, Simon Baron-Cohen, Silvia Basaia, Manon J. N. L. Benders, Frauke Beyer, Linda Booij, Kees P. J. Braun, Geraldo Busatto Filho, Wiepke Cahn, Dara M. Cannon, Tiffany M. Chaim-Avancini, Sandra S. M. Chan, Eric Y. H. Chen, Benedicto Crespo-Facorro, Eveline A. Crone, Udo Dannlowski, Sonja M. C. de Zwarte, Bruno Dietsche, Gary Donohoe, Stefan Du Plessis, Sarah Durston, Covadonga M. Díaz-Caneja, Ana M. Díaz-Zuluaga, Robin Emsley, Massimo Filippi, Thomas Frodl, Martin Gorges, Beata Graff, Dominik Grotegerd, Dariusz Gąsecki, Julie M. Hall, Laurena Holleran, Rosemary Holt, Helene J. Hopman, Andreas Jansen, Joost Janssen, Krzysztof Jodzio, Lutz Jäncke, Vasiliy G. Kaleda, Jan Kassubek, Shahrzad Kharabian Masouleh, Tilo Kircher, Martijn G. J. C. Koevoets, Vladimir S. Kostic, Axel Krug, Stephen M. Lawrie, Irina S. Lebedeva, Edwin H. M. Lee, Tristram A. Lett, Simon J. G. Lewis, Franziskus Liem, Michael V. Lombardo, Carlos Lopez-Jaramillo, Daniel S. Margulies, Sebastian Markett, Paulo Marques, Ignacio Martínez-Zalacaín, Colm McDonald, Andrew M. McIntosh, Genevieve McPhilemy, Susanne L. Meinert, José M. Menchón, Christian Montag, Pedro S. Moreira, Pedro Morgado, David O. Mothersill, Susan Mérillat, Hans-Peter Müller, Leila Nabulsi, Pablo Najt, Krzysztof Narkiewicz, Patrycja Naumczyk, Bob Oranje, Victor Ortiz-Garcia de la Foz, Jiska S. Peper, Julian A. Pineda, Paul E. Rasser, Ronny Redlich, Jonathan Repple, Martin Reuter, Pedro G. P. Rosa, Amber N. V. Ruigrok, Agnieszka Sabisz, Ulrich Schall, Soraya Seedat, Mauricio H. Serpa, Stavros Skouras, Carles Soriano-Mas, Nuno Sousa, Edyta Szurowska, Alexander S. Tomyshev, Diana Tordesillas-Gutierrez, Sofie L. Valk, Leonard H. van den Berg, Theo G. M. van Erp, Neeltje E. M. van Haren, Judith M. C. van Leeuwen, Arno Villringer, Christiaan H. Vinkers, Christian Vollmar, Lea Waller, Henrik Walter, Heather C. Whalley, Marta Witkowska, A. Veronica Witte, Marcus V. Zanetti, Rui Zhang, Siemon C. de Lange, University Medical Center [Utrecht], Center for Nanotechnology Innovation, @NEST (CNI), National Enterprise for nanoScience and nanoTechnology (NEST), Scuola Normale Superiore di Pisa (SNS)-Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)-Istituto Italiano di Tecnologia (IIT)-Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA)-Scuola Normale Superiore di Pisa (SNS)-Scuola Universitaria Superiore Sant'Anna [Pisa] (SSSUP)-Istituto Italiano di Tecnologia (IIT)-Consiglio Nazionale delle Ricerche [Pisa] (CNR PISA), Psychiatry Department, Adolescent Unit, Hospital General Universitario Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental, CIBERSAM, University of Edinburgh, University of Cambridge [UK] (CAM), Laboratoire Jacques-Louis Lions (LJLL), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Department of Psychiatry, Icahn School of Medicine at Mount Sinai [New York] (MSSM), National University of Ireland [Galway] (NUI Galway), Centro de Investigación Biomédica en Red Salud Mental [Madrid] (CIBER-SAM), Trinity College Dublin-St. James's Hospital, University Hospital San Raffaele, Psychiatry and Psychotherapy, Universität Zürich [Zürich] = University of Zurich (UZH), Department of Neurology [Ulm], Universität Ulm - Ulm University [Ulm, Allemagne], Max-Planck-Institut für Mathematik in den Naturwissenschaften (MPI-MiS), Max-Planck-Gesellschaft, Dept. of Psychiatry, University of Marburg, Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences [Leipzig] (IMPNSC), Department of Psychology, Laboratory of Neurogenetics, sans affiliation, Division of Psychiatry, University of Edinburgh-Royal Edinburgh Hospital, Centro de Quimica Estrutural (CQE), Instituto Superior Técnico, Universidade Técnica de Lisboa (IST), Humboldt-Universität zu Berlin, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital [Boston]-Harvard Medical School [Boston] (HMS), Instituto Superior Técnico, Universidade Técnica de Lisboa, Schizophrenia Research Institute [Sydney], Magnetic Resonance Imaging, Universidade do Minho, Metacohorts Consortium, Heinrich Heine Universität Düsseldorf = Heinrich Heine University [Düsseldorf], Department of Psychiatry and Human Behavior [Irvine], University of California [Irvine] (UCI), University of California-University of California, Charité - UniversitätsMedizin = Charité - University Hospital [Berlin], Berlin School of Mind and Brain [Berlin], Department of Chemistry, Centre for Molecular Simulation, University of Calgary, Child and Adolescent Psychiatry / Psychology, Utrecht University, Wellcome Trust, Medical Research Council (UK), Canadian Institutes of Health Research, European Research Council, European Commission, German Research Foundation, Science Foundation Ireland, Russian Foundation for Basic Research, Fundação para a Ciência e a Tecnologia (Portugal), Instituto de Salud Carlos III, National Institutes of Health (US), Van Den Heuvel, M. P., Scholtens, L. H., Van Der Burgh, H. K., Agosta, F., Alloza, C., Arango, C., Auyeung, B., Baron-Cohen, S., Basaia, S., Benders, M. J. N. L., Beyer, F., Booij, L., Braun, K. P. J., Filho, G. B., Cahn, W., Cannon, D. M., Chaim-Avancini, T. M., Chan, S. S. M., Chen, E. Y. H., Crespo-Facorro, B., Crone, E. A., Dannlowski, U., De Zwarte, S. M. C., Dietsche, B., Donohoe, G., Plessis, S. D., Durston, S., Diaz-Caneja, C. M., Diaz-Zuluaga, A. M., Emsley, R., Filippi, M., Frodl, T., Gorges, M., Graff, B., Grotegerd, D., Gasecki, D., Hall, J. M., Holleran, L., Holt, R., Hopman, H. J., Jansen, A., Janssen, J., Jodzio, K., Jancke, L., Kaleda, V. G., Kassubek, J., Masouleh, S. K., Kircher, T., Koevoets, M. G. J. C., Kostic, V. S., Krug, A., Lawrie, S. M., Lebedeva, I. S., Lee, E. H. M., Lett, T. A., Lewis, S. J. G., Liem, F., Lombardo, M. V., Lopez-Jaramillo, C., Margulies, D. S., Markett, S., Marques, P., Martinez-Zalacain, I., Mcdonald, C., Mcintosh, A. M., Mcphilemy, G., Meinert, S. L., Menchon, J. M., Montag, C., Moreira, P. S., Morgado, P., Mothersill, D. O., Merillat, S., Muller, H. -P., Nabulsi, L., Najt, P., Narkiewicz, K., Naumczyk, P., Oranje, B., De la Foz, V. O. -G., Peper, J. S., Pineda, J. A., Rasser, P. E., Redlich, R., Repple, J., Reuter, M., Rosa, P. G. P., Ruigrok, A. N. V., Sabisz, A., Schall, U., Seedat, S., Serpa, M. H., Skouras, S., Soriano-Mas, C., Sousa, N., Szurowska, E., Tomyshev, A. S., Tordesillas-Gutierrez, D., Valk, S. L., Van Den Berg, L. H., Van Erp, T. G. M., Van Haren, N. E. M., Van Leeuwen, J. M. C., Villringer, A., Vinkers, C. H., Vollmar, C., Waller, L., Walter, H., Whalley, H. C., Witkowska, M., Witte, A. V., Zanetti, M. V., Zhang, R., De Lange, S. C., Baron-Cohen, Simon [0000-0001-9217-2544], Ruigrok, Amber [0000-0001-7711-8056], and Apollo - University of Cambridge Repository
Subjects: Computer science, diffusion weighted MRI, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], Network, Brain mapping, lcsh:RC346-429, HUMAN CONNECTOME, Diffusion, 0302 clinical medicine, Medicine and Health Sciences, yttria mould coating, Cervell, Anàlisi, ComputingMilieux_MISCELLANEOUS, Brain network, 0303 health sciences, Event (computing), Brain, Human Connectome, Top-down and bottom-up design, 3. Good health, Neurology, investment casting, Perspective, Connectome, Difusió, PROJECT, MRI, Connectome analysis, AZ91D-1 wt% CaO, brain, Clinical Neurology, 03 medical and health sciences, SDG 17 - Partnerships for the Goals, Neuroimaging, Journal Article, ddc:610, Diffusion weighted MRI, lcsh:Neurology. Diseases of the nervous system, 030304 developmental biology, Connectome analysi, Science & Technology, Assaying, [SCCO.NEUR]Cognitive science/Neuroscience, mould–metal interaction, Biology and Life Sciences, Data science, Clinical neurology, network, Neurology (clinical), HUMAN CEREBRAL-CORTEX, 030217 neurology & neurosurgery
Abstract: We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain. Ongoing grand-scale projects like the European Human Brain Project (1), the US Brain Initiative (2), the Human Connectome Project (3), the Chinese Brainnetome (4) and exciting world-wide neuroimaging collaborations such as ENIGMA (5) herald the new era of big neuroscience. In conjunction with these major undertakings, there is an emerging trend for bottom-up initiatives, starting with small-scale projects built upon existing collaborations and infrastructures. As described by Mainen et al. (6), these initiatives are centralized around self-organized groups of researchers working on the same challenges and sharing interests and specialized expertise. These projects could scale and open up to a larger audience and other disciplines over time, eventually lining up and merging their findings with other programs to make the bigger picture., The 10Kin1day workshop was generously sponsored by the Neuroscience and Cognition program Utrecht (NCU) of the Utrecht University (https://www.uu.nl/en/research/ neuroscience-and-cognition-utrecht), the ENIGMA consortium (http://enigma.ini.usc.edu), and personal grants: MvdH: NWOVIDI (452-16-015), MQ Fellowship; SB-C: the Wellcome Trust; Medical Research Council UK; NIHR CLAHRC for Cambridgeshire and Peterborough Foundation National Health Services Trust; Autism Research Trust; LB: New Investigator Award, Canadian Institutes of Health Research; Dara Cannon: Health Research Board (HRB), Ireland (grant code HRA-POR2013-324); SC: Research Grant Council (Hong Kong)-GRF 14101714; Eveline Crone: ERC-2010-StG-263234; UD: DFG, grant FOR2107 DA1151/5-1, DA1151/5-2, SFB-TRR58, Project C09, IZKF, grant Dan3/012/17; SD: MRC-RFA-UFSP-012013 (Shared Roots MRC Flagship grant); TF: Marie Curie Programme, International Training Programme, r’Birth; DG: National Science Centre (UMO-2011/02/A/NZ5/00329); BG: National Science Centre (UMO-2011/02/A/NZ5/00329); JH: Western Sydney University Postgraduate Research Award; LH: Science Foundation Ireland, ERC; HH: Research Grant Council (Hong Kong)-GRF 14101714; LJ: Velux Stiftung, grant 369 & UZH University Research Priority Program Dynamics of Healthy Aging; AJ: DFG, grant FOR2107 JA 1890/7-1; KJ: National Science Centre (UMO-2013/09/N/HS6/02634); VK: The Russian Foundation for Basic Research (grant code 15-06-05758A); TK: DFG, grant FOR2107 KI 588/14-1, DFG, grant FOR2107 KI 588/15-1; AK: DFG, grant FOR2107 KO 4291/4-1, DFG, grant FOR2107 KO 4291/3-1; IL: The Russian Foundation for Basic Research (grant code 15-06-05758A); EL: Health and Medical Research Fund - 11121271; SiL: NHMRC-ARC Dementia Fellowship 1110414, NHMRC Dementia Research Team Grant 1095127, NHMRC Project Grant 1062319; CL-J: 537-2011, 2014849; AM: Wellcome Trust Strategic Award (104036/Z/14/Z), MRC Grant MC_PC_17209; CM: Heisenberg-Grant, German Research Foundation, DFG MO 2363/3-2; PM: Foundation for Science and Technology, Portugal - PDE/BDE/113601/2015; KN: National Science Centre (UMO-2011/02/A/NZ5/00329); PN: National Science Centre (UMO-2013/09/N/HS6/02634); JiP: NWO-Veni 451-10-007; PaR: PER and US would like to thank the Schizophrenia Research Institute and the Chief-Investigators of the Australian Schizophrenia Research Bank V. Carr, U. Schall, R. Scott, A. Jablensky, B. Mowry, P. Michie, S. Catts, F. Henskens, and C. Pantelis; AS: National Science Centre (UMO-2011/02/A/NZ5/00329); SS: European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 707730; CS-M: Carlos III Health Institute (PI13/01958), Carlos III Health Institute (PI16/00889), Carlos III Health Institute (CPII16/00048); ES: National Science Centre (UMO-2011/02/A/NZ5/00329); AT: The Russian Foundation for Basic Research (grant code 1506-05758A); DT-G: PI14/00918, PI14/00639; Leonardo Tozzi: Marie Curie Programme, International Training Programme, r’Birth; SV: IMPRS Neurocom stipend; TvE: National Center for Research Resources at the National Institutes of Health (grant numbers: NIH 1 U24 RR021992 (Function Biomedical Informatics Research Network), NIH 1 U24 RR025736-01 (Biomedical Informatics Research Network Coordinating Center; http://www.birncommunity.org) and the NIH Big Data to Knowledge (BD2K) award (U54 EB020403 to Paul Thompson). NvH: NWO-VIDI (452-11-014); MW: National Science Centre (UMO-2011/02/A/NZ5/00329); Veronica O’Keane: Meath Foundation; AV and AW: CRC Obesity Mechanism (SFB 1052) Project A1 funded by DFG. The funding sources had no role in the study design, data collection, analysis, and interpretation of the data.
Published: 2019
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19. Using structural MRI to identify bipolar disorders - 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group.

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

Author: Krug A, Wöhr M, Seffer D, Rippberger H, Sungur AÖ, Dietsche B, Stein F, Sivalingam S, Forstner AJ, Witt SH, Dukal H, Streit F, Maaser A, Heilmann-Heimbach S, Andlauer TFM, Herms S, Hoffmann P, Rietschel M, Nöthen MM, Lackinger M, Schratt G, Koch M, Schwarting RKW, and Kircher T
Subjects: Adult, Age Factors, Animals, Anxiety psychology, Behavior, Animal, CpG Islands genetics, DNA Methylation genetics, Diffusion Tensor Imaging, Female, Gene Expression Regulation, Hippocampus diagnostic imaging, Hippocampus pathology, Humans, Male, MicroRNAs genetics, MicroRNAs metabolism, Neurodevelopmental Disorders genetics, Neurodevelopmental Disorders psychology, Neuronal Plasticity, Rats, Wistar, Risk Factors, Social Behavior, Stereotyped Behavior, Neurodevelopmental Disorders epidemiology, Parents, Translational Research, Biomedical
Abstract: Advanced paternal age (APA) is a risk factor for several neurodevelopmental disorders, including autism and schizophrenia. The potential mechanisms conferring this risk are poorly understood. Here, we show that the personality traits schizotypy and neuroticism correlated with paternal age in healthy subjects (N = 677). Paternal age was further positively associated with gray matter volume (VBM, N = 342) in the right prefrontal and the right medial temporal cortex. The integrity of fiber tracts (DTI, N = 222) connecting these two areas correlated positively with paternal age. Genome-wide methylation analysis in humans showed differential methylation in APA individuals, linking APA to epigenetic mechanisms. A corresponding phenotype was obtained in our rat model. APA rats displayed social-communication deficits and emitted fewer pro-social ultrasonic vocalizations compared to controls. They further showed repetitive and stereotyped patterns of behavior, together with higher anxiety during early development. At the neurobiological level, microRNAs miR-132 and miR-134 were both differentially regulated in rats and humans depending on APA. This study demonstrates associations between APA and social behaviors across species. They might be driven by changes in the expression of microRNAs and/or epigenetic changes regulating neuronal plasticity, leading to brain morphological changes and fronto-hippocampal connectivity, a network which has been implicated in social interaction.
Published: 2020
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21. The genetic architecture of the human cerebral cortex.

Author: Grasby KL, Jahanshad N, Painter JN, Colodro-Conde L, Bralten J, Hibar DP, Lind PA, Pizzagalli F, Ching CRK, McMahon MAB, Shatokhina N, Zsembik LCP, Thomopoulos SI, Zhu AH, Strike LT, Agartz I, Alhusaini S, Almeida MAA, Alnæs D, Amlien IK, Andersson M, Ard T, Armstrong NJ, Ashley-Koch A, Atkins JR, Bernard M, Brouwer RM, Buimer EEL, Bülow R, Bürger C, Cannon DM, Chakravarty M, Chen Q, Cheung JW, Couvy-Duchesne B, Dale AM, Dalvie S, de Araujo TK, de Zubicaray GI, de Zwarte SMC, den Braber A, Doan NT, Dohm K, Ehrlich S, Engelbrecht HR, Erk S, Fan CC, Fedko IO, Foley SF, Ford JM, Fukunaga M, Garrett ME, Ge T, Giddaluru S, Goldman AL, Green MJ, Groenewold NA, Grotegerd D, Gurholt TP, Gutman BA, Hansell NK, Harris MA, Harrison MB, Haswell CC, Hauser M, Herms S, Heslenfeld DJ, Ho NF, Hoehn D, Hoffmann P, Holleran L, Hoogman M, Hottenga JJ, Ikeda M, Janowitz D, Jansen IE, Jia T, Jockwitz C, Kanai R, Karama S, Kasperaviciute D, Kaufmann T, Kelly S, Kikuchi M, Klein M, Knapp M, Knodt AR, Krämer B, Lam M, Lancaster TM, Lee PH, Lett TA, Lewis LB, Lopes-Cendes I, Luciano M, Macciardi F, Marquand AF, Mathias SR, Melzer TR, Milaneschi Y, Mirza-Schreiber N, Moreira JCV, Mühleisen TW, Müller-Myhsok B, Najt P, Nakahara S, Nho K, Olde Loohuis LM, Orfanos DP, Pearson JF, Pitcher TL, Pütz B, Quidé Y, Ragothaman A, Rashid FM, Reay WR, Redlich R, Reinbold CS, Repple J, Richard G, Riedel BC, Risacher SL, Rocha CS, Mota NR, Salminen L, Saremi A, Saykin AJ, Schlag F, Schmaal L, Schofield PR, Secolin R, Shapland CY, Shen L, Shin J, Shumskaya E, Sønderby IE, Sprooten E, Tansey KE, Teumer A, Thalamuthu A, Tordesillas-Gutiérrez D, Turner JA, Uhlmann A, Vallerga CL, van der Meer D, van Donkelaar MMJ, van Eijk L, van Erp TGM, van Haren NEM, van Rooij D, van Tol MJ, Veldink JH, Verhoef E, Walton E, Wang M, Wang Y, Wardlaw JM, Wen W, Westlye LT, Whelan CD, Witt SH, Wittfeld K, Wolf C, Wolfers T, Wu JQ, Yasuda CL, Zaremba D, Zhang Z, Zwiers MP, Artiges E, Assareh AA, Ayesa-Arriola R, Belger A, Brandt CL, Brown GG, Cichon S, Curran JE, Davies GE, Degenhardt F, Dennis MF, Dietsche B, Djurovic S, Doherty CP, Espiritu R, Garijo D, Gil Y, Gowland PA, Green RC, Häusler AN, Heindel W, Ho BC, Hoffmann WU, Holsboer F, Homuth G, Hosten N, Jack CR Jr, Jang M, Jansen A, Kimbrel NA, Kolskår K, Koops S, Krug A, Lim KO, Luykx JJ, Mathalon DH, Mather KA, Mattay VS, Matthews S, Mayoral Van Son J, McEwen SC, Melle I, Morris DW, Mueller BA, Nauck M, Nordvik JE, Nöthen MM, O'Leary DS, Opel N, Martinot MP, Pike GB, Preda A, Quinlan EB, Rasser PE, Ratnakar V, Reppermund S, Steen VM, Tooney PA, Torres FR, Veltman DJ, Voyvodic JT, Whelan R, White T, Yamamori H, Adams HHH, Bis JC, Debette S, Decarli C, Fornage M, Gudnason V, Hofer E, Ikram MA, Launer L, Longstreth WT, Lopez OL, Mazoyer B, Mosley TH, Roshchupkin GV, Satizabal CL, Schmidt R, Seshadri S, Yang Q, Alvim MKM, Ames D, Anderson TJ, Andreassen OA, Arias-Vasquez A, Bastin ME, Baune BT, Beckham JC, Blangero J, Boomsma DI, Brodaty H, Brunner HG, Buckner RL, Buitelaar JK, Bustillo JR, Cahn W, Cairns MJ, Calhoun V, Carr VJ, Caseras X, Caspers S, Cavalleri GL, Cendes F, Corvin A, Crespo-Facorro B, Dalrymple-Alford JC, Dannlowski U, de Geus EJC, Deary IJ, Delanty N, Depondt C, Desrivières S, Donohoe G, Espeseth T, Fernández G, Fisher SE, Flor H, Forstner AJ, Francks C, Franke B, Glahn DC, Gollub RL, Grabe HJ, Gruber O, Håberg AK, Hariri AR, Hartman CA, Hashimoto R, Heinz A, Henskens FA, Hillegers MHJ, Hoekstra PJ, Holmes AJ, Hong LE, Hopkins WD, Hulshoff Pol HE, Jernigan TL, Jönsson EG, Kahn RS, Kennedy MA, Kircher TTJ, Kochunov P, Kwok JBJ, Le Hellard S, Loughland CM, Martin NG, Martinot JL, McDonald C, McMahon KL, Meyer-Lindenberg A, Michie PT, Morey RA, Mowry B, Nyberg L, Oosterlaan J, Ophoff RA, Pantelis C, Paus T, Pausova Z, Penninx BWJH, Polderman TJC, Posthuma D, Rietschel M, Roffman JL, Rowland LM, Sachdev PS, Sämann PG, Schall U, Schumann G, Scott RJ, Sim K, Sisodiya SM, Smoller JW, Sommer IE, St Pourcain B, Stein DJ, Toga AW, Trollor JN, Van der Wee NJA, van 't Ent D, Völzke H, Walter H, Weber B, Weinberger DR, Wright MJ, Zhou J, Stein JL, Thompson PM, and Medland SE
Subjects: Attention Deficit Disorder with Hyperactivity genetics, Brain Mapping, Cognition, Genetic Loci, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Organ Size genetics, Parkinson Disease genetics, Cerebral Cortex anatomy & histology, Genetic Variation
Abstract: The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder., (Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.)
Published: 2020
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22. A resting state fMRI analysis pipeline for pooling inference across diverse cohorts: an ENIGMA rs-fMRI protocol.

Author: Adhikari BM, Jahanshad N, Shukla D, Turner J, Grotegerd D, Dannlowski U, Kugel H, Engelen J, Dietsche B, Krug A, Kircher T, Fieremans E, Veraart J, Novikov DS, Boedhoe PSW, van der Werf YD, van den Heuvel OA, Ipser J, Uhlmann A, Stein DJ, Dickie E, Voineskos AN, Malhotra AK, Pizzagalli F, Calhoun VD, Waller L, Veer IM, Walter H, Buchanan RW, Glahn DC, Hong LE, Thompson PM, and Kochunov P
Subjects: Adult, Aged, Artifacts, Female, Functional Neuroimaging, Humans, Male, Middle Aged, Signal-To-Noise Ratio, Young Adult, Brain diagnostic imaging, Brain Mapping methods, Image Processing, Computer-Assisted, Magnetic Resonance Imaging methods
Abstract: Large-scale consortium efforts such as Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) and other collaborative efforts show that combining statistical data from multiple independent studies can boost statistical power and achieve more accurate estimates of effect sizes, contributing to more reliable and reproducible research. A meta- analysis would pool effects from studies conducted in a similar manner, yet to date, no such harmonized protocol exists for resting state fMRI (rsfMRI) data. Here, we propose an initial pipeline for multi-site rsfMRI analysis to allow research groups around the world to analyze scans in a harmonized way, and to perform coordinated statistical tests. The challenge lies in the fact that resting state fMRI measurements collected by researchers over the last decade vary widely, with variable quality and differing spatial or temporal signal-to-noise ratio (tSNR). An effective harmonization must provide optimal measures for all quality data. Here we used rsfMRI data from twenty-two independent studies with approximately fifty corresponding T1-weighted and rsfMRI datasets each, to (A) review and aggregate the state of existing rsfMRI data, (B) demonstrate utility of principal component analysis (PCA)-based denoising and (C) develop a deformable ENIGMA EPI template based on the representative anatomy that incorporates spatial distortion patterns from various protocols and populations.
Published: 2019
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23. Evidence of brain network aberration in healthy subjects with urban upbringing - A multimodal DTI and VBM study.

Author: Lammeyer S, Dietsche B, Dannlowski U, Kircher T, and Krug A
Subjects: Adult, Brain growth & development, Diffusion Tensor Imaging, Female, Healthy Volunteers, Humans, Image Processing, Computer-Assisted, Male, Multimodal Imaging, Neural Pathways diagnostic imaging, Neural Pathways growth & development, Urban Population, Brain diagnostic imaging
Abstract: City living represents not only the allegory of modern life, but also - due to attractive living conditions, employment and infrastructure - a crucial reality for a growing portion of the global society. Regarding the remarkable increase of the schizophrenia incidence in individuals exposed to an urban environment during upbringing the understanding of responsible pathogenetic mechanisms is important. Schizophrenia has been conceptualized as a disorder of brain dysconnectivity. We investigated the association between urban upbringing and gray matter as well as white matter in a large sample of healthy subjects (n = 290). Voxelwise analyses revealed a strong inverse correlation of early life urbanicity and gray matter volume of the bilateral dorsolateral prefrontal cortices (DLPFC) and the right inferior parietal lobe (IPL) as well as the white matter characteristics in the left superior longitudinal fasciculus (SLF). A positive correlation was found for the gray matter volume of the left precuneus. These results may point to an altered brain development associated with urban upbringing, which not only affects single brain regions but a fronto-parietal network. Considering a DLPFC susceptibility to stress, our findings support the hypothesis of the pathogenetic role of social stress in an urban environment., (Copyright © 2019. Published by Elsevier B.V.)
Published: 2019
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24. 10Kin1day: A Bottom-Up Neuroimaging Initiative.

Author: van den Heuvel MP, Scholtens LH, van der Burgh HK, Agosta F, Alloza C, Arango C, Auyeung B, Baron-Cohen S, Basaia S, Benders MJNL, Beyer F, Booij L, Braun KPJ, Filho GB, Cahn W, Cannon DM, Chaim-Avancini TM, Chan SSM, Chen EYH, Crespo-Facorro B, Crone EA, Dannlowski U, de Zwarte SMC, Dietsche B, Donohoe G, Plessis SD, Durston S, Díaz-Caneja CM, Díaz-Zuluaga AM, Emsley R, Filippi M, Frodl T, Gorges M, Graff B, Grotegerd D, Gąsecki D, Hall JM, Holleran L, Holt R, Hopman HJ, Jansen A, Janssen J, Jodzio K, Jäncke L, Kaleda VG, Kassubek J, Masouleh SK, Kircher T, Koevoets MGJC, Kostic VS, Krug A, Lawrie SM, Lebedeva IS, Lee EHM, Lett TA, Lewis SJG, Liem F, Lombardo MV, Lopez-Jaramillo C, Margulies DS, Markett S, Marques P, Martínez-Zalacaín I, McDonald C, McIntosh AM, McPhilemy G, Meinert SL, Menchón JM, Montag C, Moreira PS, Morgado P, Mothersill DO, Mérillat S, Müller HP, Nabulsi L, Najt P, Narkiewicz K, Naumczyk P, Oranje B, Ortiz-Garcia de la Foz V, Peper JS, Pineda JA, Rasser PE, Redlich R, Repple J, Reuter M, Rosa PGP, Ruigrok ANV, Sabisz A, Schall U, Seedat S, Serpa MH, Skouras S, Soriano-Mas C, Sousa N, Szurowska E, Tomyshev AS, Tordesillas-Gutierrez D, Valk SL, van den Berg LH, van Erp TGM, van Haren NEM, van Leeuwen JMC, Villringer A, Vinkers CH, Vollmar C, Waller L, Walter H, Whalley HC, Witkowska M, Witte AV, Zanetti MV, Zhang R, and de Lange SC
Abstract: We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.
Published: 2019
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25. Longitudinal brain volume changes in major depressive disorder.

Author: Yüksel D, Engelen J, Schuster V, Dietsche B, Konrad C, Jansen A, Dannlowski U, Kircher T, and Krug A
Subjects: Adolescent, Adult, Amygdala diagnostic imaging, Amygdala pathology, Antidepressive Agents therapeutic use, Brain diagnostic imaging, Depressive Disorder, Major diagnostic imaging, Depressive Disorder, Major drug therapy, Depressive Disorder, Major psychology, Disease Progression, Female, Follow-Up Studies, Gray Matter diagnostic imaging, Hippocampus diagnostic imaging, Hippocampus pathology, Humans, Interview, Psychological, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Organ Size, Phenotype, Severity of Illness Index, Thalamus diagnostic imaging, Thalamus pathology, Time Factors, Young Adult, Brain pathology, Depressive Disorder, Major pathology, Gray Matter pathology
Abstract: Patients with major depressive disorder (MDD) exhibit gray matter volume (GMV) reductions in limbic regions. Clinical variables-such as the number of depressive episodes-seem to affect volume alterations. It is unclear whether the observed cross-sectional GMV abnormalities in MDD change over time, and whether there is a longitudinal relationship between GMV changes and the course of disorder. We investigated T1 structural MRI images of 54 healthy control (HC) and 37 MDD patients in a 3-Tesla-MRI with a follow-up interval of 3 years. The Cat12 toolbox was used to analyze longitudinal data (p < 0.05, FWE-corrected, whole-brain analysis; flexible factorial design). Interaction effects indicated increasing GMV in MDD in the bilateral amygdala, and decreasing GMV in the right thalamus between T1 and T2. Further analyses comparing patients with a mild course of disorder (MCD; 0-1 depressive episode during the follow-up) to patients with a severe course of disorder (SCD; > 1 depressive episode during the follow-up) revealed increasing amygdalar volume in MCD. Our study confirms structural alterations in limbic regions in MDD patients and an association between these impairments and the course of disorder. Thus, we assume that the reported volumetric alterations in the left amygdala (i.e. volumetric normalization) are reversible and apparently driven by the clinical phenotype. Hence, these results support the assumption that the severity and progression of disease influences amygdalar GMV changes in MDD or vice versa.
Published: 2018
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26. Effects of cumulative illness severity on hippocampal gray matter volume in major depression: a voxel-based morphometry study.

Author: Zaremba D, Enneking V, Meinert S, Förster K, Bürger C, Dohm K, Grotegerd D, Redlich R, Dietsche B, Krug A, Kircher T, Kugel H, Heindel W, Baune BT, Arolt V, and Dannlowski U
Subjects: Adolescent, Adult, Depressive Disorder, Major diagnostic imaging, Female, Gray Matter diagnostic imaging, Hippocampus diagnostic imaging, Humans, Male, Middle Aged, Young Adult, Depressive Disorder, Major pathology, Depressive Disorder, Major physiopathology, Gray Matter pathology, Hippocampus pathology, Image Processing, Computer-Assisted methods, Magnetic Resonance Imaging methods, Severity of Illness Index
Abstract: Background: Patients with major depression show reduced hippocampal volume compared to healthy controls. However, the contribution of patients' cumulative illness severity to hippocampal volume has rarely been investigated. It was the aim of our study to find a composite score of cumulative illness severity that is associated with hippocampal volume in depression., Methods: We estimated hippocampal gray matter volume using 3-tesla brain magnetic resonance imaging in 213 inpatients with acute major depression according to DSM-IV criteria (employing the SCID interview) and 213 healthy controls. Patients' cumulative illness severity was ascertained by six clinical variables via structured clinical interviews. A principal component analysis was conducted to identify components reflecting cumulative illness severity. Regression analyses and a voxel-based morphometry approach were used to investigate the influence of patients' individual component scores on hippocampal volume., Results: Principal component analysis yielded two main components of cumulative illness severity: Hospitalization and Duration of Illness. While the component Hospitalization incorporated information from the intensity of inpatient treatment, the component Duration of Illness was based on the duration and frequency of illness episodes. We could demonstrate a significant inverse association of patients' Hospitalization component scores with bilateral hippocampal gray matter volume. This relationship was not found for Duration of Illness component scores., Conclusions: Variables associated with patients' history of psychiatric hospitalization seem to be accurate predictors of hippocampal volume in major depression and reliable estimators of patients' cumulative illness severity. Future studies should pay attention to these measures when investigating hippocampal volume changes in major depression.
Published: 2018
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27. Polygenic risk for schizophrenia affects working memory and its neural correlates in healthy subjects.

Author: Krug A, Dietsche B, Zöllner R, Yüksel D, Nöthen MM, Forstner AJ, Rietschel M, Dannlowski U, Baune BT, Maier R, Witt SH, and Kircher T
Subjects: Adult, Female, Genome-Wide Association Study, Humans, Magnetic Resonance Imaging, Male, Prefrontal Cortex diagnostic imaging, Risk, Schizophrenia diagnostic imaging, Memory, Short-Term physiology, Multifactorial Inheritance genetics, Prefrontal Cortex physiopathology, Schizophrenia genetics, Schizophrenia physiopathology
Abstract: Schizophrenia is a disorder with a high heritability. Patients as well as their first degree relatives display lower levels of performance in a number of cognitive domains compared to subjects without genetic risk. Several studies could link these aberrations to single genetic variants, however, only recently, polygenic risk scores as proxies for genetic risk have been associated with cognitive domains and their neural correlates. In the present study, a sample of healthy subjects (n=137) performed a letter version of the n-back task while scanned with 3-T fMRI. All subjects were genotyped with the PsychChip and polygenic risk scores were calculated based on the PGC2 schizophrenia GWAS results. Polygenic risk for schizophrenia was associated with a lower degree of brain activation in prefrontal areas during the 3-back compared to the 0-back baseline condition. Furthermore, polygenic risk was associated with lower levels of brain activation in the right inferior frontal gyrus during the 3-back compared to a 2-back condition. Polygenic risk leads to a shift in the underlying activation pattern to the left side, thus resembling results reported in patients with schizophrenia. The data may point to polygenic risk for schizophrenia being associated with brain function in a cognitive task known to be impaired in patients and their relatives., (Copyright © 2018 Elsevier B.V. All rights reserved.)
Published: 2018
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28. Neural correlates of working memory in first episode and recurrent depression: An fMRI study.

Author: Yüksel D, Dietsche B, Konrad C, Dannlowski U, Kircher T, and Krug A
Subjects: Adult, Brain diagnostic imaging, Brain Mapping, Cerebrovascular Circulation physiology, Depressive Disorder, Major diagnostic imaging, Depressive Disorder, Major psychology, Female, Humans, Magnetic Resonance Imaging, Male, Oxygen blood, Recurrence, Brain physiopathology, Depressive Disorder, Major physiopathology, Memory, Short-Term physiology
Abstract: Background: Patients suffering from major depressive disorder (MDD) show deficits in working memory (WM) performance accompanied by bilateral fronto-parietal BOLD signal changes. It is unclear whether patients with a first depressive episode (FDE) exhibit the same signal changes as patients with recurrent depressive episodes (RDE)., Methods: We investigated seventy-four MDD inpatients (48 RDE, 26 FDE) and 74 healthy control (HC) subjects performing an n-back WM task (0-back, 2-back, 3-back condition) in a 3T-fMRI., Results: FMRI analyses revealed deviating BOLD signal in MDD in the thalamus (0-back vs. 2-back), the angular gyrus (0-back vs. 3-back), and the superior frontal gyrus (2-back vs. 3-back). Further effects were observed between RDE vs. FDE. Thus, RDE displayed differing neural activation in the middle frontal gyrus (2-back vs. 3-back), the inferior frontal gyrus, and the precentral gyrus (0-back vs. 2-back). In addition, both HC and FDE indicated a linear activation trend depending on task complexity., Conclusions: Although we failed to find behavioral differences between the groups, results suggest differing BOLD signal in fronto-parietal brain regions in MDD vs. HC, and in RDE vs. FDE. Moreover, both HC and FDE show similar trends in activation shapes. This indicates a link between levels of complexity-dependent activation in fronto-parietal brain regions and the stage of MDD. We therefore assume that load-dependent BOLD signal during WM is impaired in MDD, and that it is particularly affected in RDE. We also suspect neurobiological compensatory mechanisms of the reported brain regions in (working) memory functioning., (Copyright © 2018 Elsevier Inc. All rights reserved.)
Published: 2018
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29. Polygenic risk for depression and the neural correlates of working memory in healthy subjects.

Author: Yüksel D, Dietsche B, Forstner AJ, Witt SH, Maier R, Rietschel M, Konrad C, Nöthen MM, Dannlowski U, Baune BT, Kircher T, and Krug A
Subjects: Adult, Brain diagnostic imaging, Brain Mapping, Female, Genome-Wide Association Study, Genotyping Techniques, Humans, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Regression Analysis, Brain physiology, Depressive Disorder, Major genetics, Genetic Predisposition to Disease, Memory, Short-Term physiology, Multifactorial Inheritance
Abstract: Introduction: Major depressive disorder (MDD) patients show impairments of cognitive functioning such as working memory (WM), and furthermore alterations during WM-fMRI tasks especially in frontal and parietal brain regions. The calculation of a polygenic risk score (PRS) can be used to describe the genetic influence on MDD, hence imaging genetic studies aspire to combine both genetics and neuroimaging data to identify the influence of genetic factors on brain functioning. We aimed to detect the effect of MDD-PRS on brain activation during a WM task measured with fMRI and expect healthy individuals with a higher PRS to be more resembling to MDD patients., Method: In total, n=137 (80 men, 57 women, aged 34.5, SD=10.4years) healthy subjects performed a WM n-back task [0-back (baseline), 2-back and 3-back condition] in a 3T-MRI-tomograph. The sample was genotyped using the Infinium PsychArray BeadChip and a polygenic risk score was calculated for MDD using PGC MDD GWAS results., Results: A lower MDD risk score was associated with increased activation in the bilateral middle occipital gyri (MOG), the bilateral middle frontal gyri (MFG) and the right precentral gyrus (PCG) during the 2-back vs. baseline condition. Moreover, a lower PRS was associated with increased brain activation during the 3-back vs. baseline condition in the bilateral cerebellum, the right MFG and the left inferior parietal lobule. A higher polygenic risk score was associated with hyperactivation in brain regions comprising the right MFG and the right supplementary motor area during the 3-back vs. 2-back condition., Discussion: The results suggest that part of the WM-related brain activation patterns might be explained by genetic variants captured by the MDD-PRS. Furthermore we were able to detect MDD-associated activation patterns in healthy individuals depending on the MDD-PRS and the task complexity. Additional gene loci could contribute to these task-dependent brain activation patterns., (Copyright © 2017 Elsevier Inc. All rights reserved.)
Published: 2017
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30. White matter integrity and symptom dimensions of schizophrenia: A diffusion tensor imaging study.

Author: Bopp MHA, Zöllner R, Jansen A, Dietsche B, Krug A, and Kircher TTJ
Subjects: Adult, Female, Hallucinations etiology, Hallucinations physiopathology, Humans, Male, Middle Aged, Schizophrenia complications, Thinking physiology, Young Adult, Diffusion Tensor Imaging methods, Schizophrenia diagnostic imaging, Schizophrenia physiopathology, White Matter diagnostic imaging
Abstract: Impaired fiber bundle connectivity between brain regions is a key neuropathological finding in schizophrenia. Symptom dimensions in schizophrenia can be clustered into factor models. Single syndromes have been related to grey and white matter brain structure alterations. We associated all core syndromes of schizophrenia in a single patient group with changes in white matter integrity. Diffusion weighted images (3T MRI) and SAPS/SANS scores were measured in 26 male patients and 26 healthy controls. First, group differences in fractional anisotropy (FA) were calculated with TBSS. Second, core symptom dimensions of schizophrenia were correlated with FA within these altered tracts. We found differences between groups in nine white matter tracts. Hallucinations were positively correlated with FA in the left uncinate fasciculus and left corticospinal tract. Ego-disturbances (passivity phenomena) showed a positive correlation with FA in the right anterior thalamic radiation. Positive formal thought disorders (FTD) corresponded negatively with FA in the right cingulum bundle. Negative symptoms were positively associated with the right anterior thalamic radiation and negatively with the right ventral cingulum bundle. For the first time, we analyzed the whole range of psychopathological factors in one schizophrenia patient group. We could validate our novel results for positive FTD and passivity phenomena by replicating findings for hallucinations and negative symptoms. Only those brain circuits which are most vulnerable at a given time during neurodevelopment are affected by a particular pathological impact (genetic, environmental). This scenario could explain the predominance of particular psychopathological syndromes related to specific white matter anomalies., (Copyright © 2016 Elsevier B.V. All rights reserved.)
Published: 2017
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31. Structural brain changes in schizophrenia at different stages of the illness: A selective review of longitudinal magnetic resonance imaging studies.

Author: Dietsche B, Kircher T, and Falkenberg I
Subjects: Humans, Disease Progression, Gray Matter diagnostic imaging, Magnetic Resonance Imaging methods, Psychotic Disorders diagnostic imaging, Schizophrenia diagnostic imaging
Abstract: Objective: Schizophrenia is a devastating mental disorder accompanied by aberrant structural brain connectivity. The question whether schizophrenia is a progressive brain disorder is yet to be resolved. Thus, it is not clear when these structural alterations occur and how they develop over time., Methods: In our selective review, we summarized recent findings from longitudinal magnetic resonance imaging studies investigating structural brain alterations and its impact on clinical outcome at different stages of the illness: (1) subjects at ultra-high risk of developing psychosis, (2) patients with a first episode psychosis, and (3) chronically ill patients. Moreover, we reviewed studies examining the longitudinal effects of medication on brain structure in patients with schizophrenia., Results: (1) Studies from pre-clinical stages to conversion showed a more pronounced cortical gray matter loss (i.e. superior temporal and inferior frontal regions) in those individuals who later made transition to psychosis. (2) Studies investigating patients with a first episode psychosis revealed a decline in multiple gray matter regions (i.e. frontal regions and thalamus) over time as well as progressive cortical thinning in the superior and inferior frontal cortex. (3) Studies focusing on patients with chronic schizophrenia showed that gray matter decreased to a greater extent (i.e. frontal and temporal areas, thalamus, and cingulate cortices)-especially in poor-outcome patients. Very few studies reported effects on white matter microstructure in the longitudinal course of the illness., Conclusion: There is adequate evidence to suggest that schizophrenia is associated with progressive gray matter abnormalities particularly during the initial stages of illness. However, causal relationships between structural changes and illness course-especially in chronically ill patients-should be interpreted with caution. Findings might be confounded by longer periods of treatment and higher doses of antipsychotics or epiphenomena related to the illness.
Published: 2017
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32. Effects of Long-Term Mindfulness Meditation on Brain's White Matter Microstructure and its Aging.

Author: Laneri D, Schuster V, Dietsche B, Jansen A, Ott U, and Sommer J
Abstract: Although research on the effects of mindfulness meditation (MM) is increasing, still very little has been done to address its influence on the white matter (WM) of the brain. We hypothesized that the practice of MM might affect the WM microstructure adjacent to five brain regions of interest associated with mindfulness. Diffusion tensor imaging was employed on samples of meditators and non-meditators (n = 64) in order to investigate the effects of MM on group difference and aging. Tract-Based Spatial Statistics was used to estimate the fractional anisotrophy of the WM connected to the thalamus, insula, amygdala, hippocampus, and anterior cingulate cortex. The subsequent generalized linear model analysis revealed group differences and a group-by-age interaction in all five selected regions. These data provide preliminary indications that the practice of MM might result in WM connectivity change and might provide evidence on its ability to help diminish age-related WM degeneration in key regions which participate in processes of mindfulness.
Published: 2016
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33. A genome-wide supported psychiatric risk variant in NCAN influences brain function and cognitive performance in healthy subjects.

Author: Raum H, Dietsche B, Nagels A, Witt SH, Rietschel M, Kircher T, and Krug A
Subjects: Adult, Brain blood supply, Female, Genome-Wide Association Study, Genotype, Healthy Volunteers, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neurocan, Neuropsychological Tests, Oxygen blood, Schizophrenia, Verbal Learning, Young Adult, Brain physiology, Brain Mapping, Chondroitin Sulfate Proteoglycans genetics, Cognition physiology, Lectins, C-Type genetics, Nerve Tissue Proteins genetics, Polymorphism, Single Nucleotide genetics
Abstract: The A allele of the single nucleotide polymorphism (SNP) rs1064395 in the NCAN gene has recently been identified as a susceptibility factor for bipolar disorder and schizophrenia. NCAN encodes neurocan, a brain-specific chondroitin sulfate proteoglycan that is thought to influence neuronal adhesion and migration. Several lines of research suggest an impact of NCAN on neurocognitive functioning. In the present study, we investigated the effects of rs1064395 genotype on neural processing and cognitive performance in healthy subjects. Brain activity was measured with functional magnetic resonance imaging (fMRI) during an overt semantic verbal fluency task in 110 healthy subjects who were genotyped for the NCAN SNP rs1064395. Participants additionally underwent comprehensive neuropsychological testing. Whole brain analyses revealed that NCAN risk status, defined as AA or AG genotype, was associated with a lack of task-related deactivation in a large left lateral temporal cluster extending from the middle temporal gyrus to the temporal pole. Regarding neuropsychological measures, risk allele carriers demonstrated poorer immediate and delayed verbal memory performance when compared to subjects with GG genotype. Better verbal memory performance was significantly associated with greater deactivation of the left temporal cluster during the fMRI task in subjects with GG genotype. The current data demonstrate that common genetic variation in NCAN influences both neural processing and cognitive performance in healthy subjects. Our study provides new evidence for a specific genetic influence on human brain function., (© 2014 Wiley Periodicals, Inc.)
Published: 2015
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34. Increased neural activity during overt and continuous semantic verbal fluency in major depression: mainly a failure to deactivate.

Author: Backes H, Dietsche B, Nagels A, Stratmann M, Konrad C, Kircher T, and Krug A
Subjects: Adult, Brain blood supply, Case-Control Studies, Female, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Oxygen blood, Verbal Behavior, Young Adult, Brain pathology, Brain Mapping, Depressive Disorder, Major complications, Language Disorders etiology, Language Disorders pathology, Semantics
Abstract: Major depression is associated with impairments in semantic verbal fluency (VF). However, the neural correlates underlying dysfunctional cognitive processing in depressed subjects during the production of semantic category members still remain unclear. In the current study, an overt and continuous semantic VF paradigm was used to examine these mechanisms in a representative sample of 33 patients diagnosed with a current episode of unipolar depression and 33 statistically matched healthy controls. Subjects articulated words in response to semantic category cues while brain activity was measured with functional magnetic resonance imaging (fMRI). Compared to controls, patients showed poorer task performance. On the neural level, a group by condition interaction analysis, corrected for task performance, revealed a reduced task-related deactivation in patients in the right parahippocampal gyrus, the right fusiform gyrus, and the right supplementary motor area. An additional and an increased task-related activation in patients were observed in the right precentral gyrus and the left cerebellum, respectively. These results indicate that a failure to suppress potentially interfering activity from inferior temporal regions involved in default-mode network functions and visual imagery, accompanied by an enhanced recruitment of areas implicated in speech initiation and higher-order language processes, may underlie dysfunctional cognitive processing during semantic VF in depression. The finding that patients with depression demonstrated both decreased performance and aberrant brain activation during the current semantic VF task demonstrates that this paradigm is a sensitive tool for assessing brain dysfunctions in clinical populations.
Published: 2014
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35. Altered neural function during episodic memory encoding and retrieval in major depression.

Author: Dietsche B, Backes H, Stratmann M, Konrad C, Kircher T, and Krug A
Subjects: Adult, Brain Mapping, Face, Female, Humans, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Pattern Recognition, Visual physiology, Photic Stimulation, Recognition, Psychology physiology, Regression Analysis, Brain physiopathology, Depressive Disorder, Major physiopathology, Memory, Episodic
Abstract: Memory impairments are common in major depression. Neural processing during non-emotional episodic memory in depressed patients has only sparsely been investigated, since the majority of studies have focused on emotional stimuli. The aim of this study was to explore neural correlates of episodic memory in depressive patients and to assess brain regions related to subsequent memory performance. Forty-six participants (23 depressed patients) performed a non-emotional episodic memory encoding and retrieval task while brain activation was measured with functional magnetic resonance imaging. Patients with depression showed decreased activation in the right prefrontal cortex and right cingulate cortex during memory encoding, but increased activation in the right inferior frontal gyrus (IFG) during recognition memory. While a strong association between hippocampal and parahippocampal activation during memory encoding with subsequent memory performance became evident in healthy controls, this relationship was absent in patients with depression. Taken together, these findings demonstrate that memory related brain regions are affected in their appropriate functioning during memory encoding in depressed patients. Therefore, patients with depression may rely to a greater degree on other brain regions such as the IFG during episodic memory retrieval., (Copyright © 2014 Wiley Periodicals, Inc.)
Published: 2014
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36. Genetic variation in CACNA1C affects neural processing in major depression.

Author: Backes H, Dietsche B, Nagels A, Konrad C, Witt SH, Rietschel M, Kircher T, and Krug A
Subjects: Adult, Analysis of Variance, Brain blood supply, Brain Mapping, Case-Control Studies, DNA Mutational Analysis, Depressive Disorder, Major complications, Female, Genotype, Germany, Humans, Image Processing, Computer-Assisted, Learning Disabilities etiology, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Oxygen, Semantics, Verbal Learning physiology, Young Adult, Brain pathology, Calcium Channels, L-Type genetics, Depressive Disorder, Major genetics, Depressive Disorder, Major pathology, Polymorphism, Single Nucleotide genetics
Abstract: Genetic studies found the A allele of the single nucleotide polymorphism rs1006737 in the CACNA1C gene, which encodes for the alpha 1C subunit of the voltage-dependent, L-type calcium ion channel Cav1.2, to be overrepresented in patients with major depressive disorder (MDD). Altered prefrontal brain functioning and impaired semantic verbal fluency (SVF) are robust findings in these patients. A recent functional magnetic resonance imaging (fMRI) study found the A allele to be associated with poorer performance and increased left inferior frontal gyrus (IFG) activation during SVF tasks in healthy subjects. In the present study, we investigated the effects of rs1006737 on neural processing during SVF in MDD. In response to semantic category cues, 40 patients with MDD and 40 matched controls overtly generated words while brain activity was measured with fMRI. As revealed by whole brain analyses, genotype significantly affected brain activity in patients. Compared to patients with GG genotype, patients with A allele demonstrated increased task-related activation in the left middle/inferior frontal gyrus and the bilateral cerebellum. Patients with A allele also showed enhanced functional coupling between left middle/inferior and right superior/middle frontal gyri. No differential effects of genotype on SVF performance or brain activation were found between diagnostic groups. The current data provide further evidence for an impact of rs1006737 on the left IFG and demonstrate that genetic variation in CACNA1C modulates neural responses in patients with MDD. The observed functional alterations in prefrontal and cerebellar areas might represent a mechanism by which rs1006737 influences susceptibility to MDD., (Copyright © 2014 Elsevier Ltd. All rights reserved.)
Published: 2014
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37. The impact of a CACNA1C gene polymorphism on learning and hippocampal formation in healthy individuals: a diffusion tensor imaging study.

Author: Dietsche B, Backes H, Laneri D, Weikert T, Witt SH, Rietschel M, Sommer J, Kircher T, and Krug A
Subjects: Adolescent, Adult, Diffusion Tensor Imaging, Female, Humans, Male, Middle Aged, Polymorphism, Genetic, Young Adult, Calcium Channels, L-Type genetics, Hippocampus physiology, Memory physiology, Verbal Learning physiology
Abstract: Background: Genome-wide association studies have identified the CACNA1C single nucleotide polymorphism (SNP) rs1006737 as one of the most consistent genetic findings as susceptibility locus for major psychiatric disorders. Furthermore, animal and genetic imaging studies have reported strong functional evidence for the association of CACNA1C with learning, memory, neural plasticity, and its association with the hippocampal formation. In the present study we investigated the impact of the CACNA1C SNP rs1006737 on the fractional anisotropy (FA) in the hippocampal formation as well as on verbal learning and memory in healthy individuals., Methods: 118 healthy individuals (72 males, 46 females, age 18-56years) initially underwent diffusion tensor imaging (DTI), 100 of them were included in the final analysis. We used Tract-Based Spatial Statistics (TBSS) to examine the impact of the CACNA1C SNP rs1006737 on the hippocampal formation as predefined region of interest (ROI). Furthermore, all participants completed the Verbal Learning and Memory Test (VLMT)., Results: In the VLMT genotype was significantly associated with learning performance. Bonferroni corrected post-hoc tests indicated a diminished performance at the beginning of the learning curve in risk allele carriers compared to non-risk allele carriers. The TBSS ROI analysis revealed one cluster of reduced FA in risk allele carriers compared to non-risk allele carriers located in the right hippocampal formation. Moreover, an association between the initial learning performance and FA values was found., Discussion: These findings demonstrate that genetic variation in the CACNA1C SNP rs1006737 is associated with FA reduction in the hippocampal formation as well as with differences in learning performance in healthy individuals., (Copyright © 2013 Elsevier Inc. All rights reserved.)
Published: 2014
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38. A genome-wide supported variant in CACNA1C influences hippocampal activation during episodic memory encoding and retrieval.

Author: Krug A, Witt SH, Backes H, Dietsche B, Nieratschker V, Shah NJ, Nöthen MM, Rietschel M, and Kircher T
Subjects: Adult, Analysis of Variance, Discrimination, Psychological, Echo-Planar Imaging, Female, Genome-Wide Association Study, Hippocampus blood supply, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Neuropsychological Tests, Oxygen blood, Young Adult, Calcium Channels, L-Type genetics, Genetic Variation genetics, Hippocampus physiology, Memory, Episodic, Mental Recall physiology
Abstract: The alpha 1C subunit of the L-type voltage-gated calcium channel (CACNA1C) gene is one of the best replicated susceptibility loci for bipolar disorder, schizophrenia and major depression. It is involved in learning, memory and brain plasticity. Genetic studies using functional magnetic resonance imaging (fMRI) reported evidence of association with the CACNA1C single nucleotide polymorphism rs1006737 with functional correlates of episodic memory encoding and retrieval, especially activations in the hippocampus. These results, however, are inconsistent with regard to the magnitude and directionality of effect. In the present study, brain activation was measured with fMRI during an episodic memory encoding and retrieval task using neutral faces in two independent samples of 94 and 111 healthy subjects, respectively. Within whole brain analyses, a main effect of genotype emerged mainly in the right hippocampus during encoding as well as retrieval within the first sample: Carriers of the minor allele (A) exhibited lower activations compared to G/G allele carriers. This effect could be replicated within the second sample, however, only for the retrieval condition. The results strengthen findings that rs1006737 is associated with neural systems related to memory processes in hippocampal regions which are detectable in healthy subjects.
Published: 2014
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39. Neural processing of overt word generation in healthy individuals: the effect of age and word knowledge.

Author: Nagels A, Kircher T, Dietsche B, Backes H, Marquetand J, and Krug A
Subjects: Adult, Cognition physiology, Female, Humans, Knowledge, Magnetic Resonance Imaging, Male, Middle Aged, Young Adult, Aging physiology, Brain physiology, Brain Mapping, Intelligence physiology, Neuropsychological Tests, Speech physiology
Abstract: Verbal fluency is a classical and widely used neuropsychological instrument to assess cognitive abilities. Results of previous studies indicate an influence on verbal fluency performance of both, age and word knowledge. So far, no imaging study has investigated the neural mechanisms underlying an age and word knowledge related decline on the quantitative verbal output in a highly demanding overt and continuous semantic fluency task. Fifty healthy volunteers (age 22-56 years, verbal IQ 95-143) overtly and continuously articulated words in response to ten visually presented semantic categories while BOLD signal was measured with fMRI. Verbal responses were recorded with an MRI compatible microphone and transcribed after the scanning session. The number of produced words as well as age, word knowledge and level of education was implemented in the design matrix enabling a separate analysis of these factors on both, neural responses and behavioral differences. There was a significant correlation of level of education and number of generated words, but no significant correlations of generated words and age or word knowledge were observed. On the neural level, a widespread network was found for the word production task as contrasted with the resting condition, encompassing the bilateral superior temporal gyri, the cerebellum and the SMA. An age related positive correlation was found in the bilateral inferior and middle frontal gyri, the anterior cingulate gyrus, the left precentral gyrus and the right insula. A lower word knowledge resulted in enhanced BOLD responses in the right superior temporal gyrus and the left superior frontal gyrus. Results are interpreted in terms of compensation mechanisms countervailing potential age and word knowledge related effects., (Copyright © 2012 Elsevier Inc. All rights reserved.)
Published: 2012
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40. Decentralization of nursing authority.

Author: Mahowald JF, Freeman JF, and Dietsche B
Subjects: Hospital Units, Interprofessional Relations, Leadership, Nurse-Patient Relations, Nursing, Nursing Service, Hospital, Nursing Staff, Hospital, Nursing, Supervisory, Organization and Administration, Personnel Management
Published: 1974
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