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

Author: Hibar, DP, Westlye, LT, Doan, NT, Jahanshad, N, Cheung, JW, Ching, CRK, Versace, A, Bilderbeck, AC, Uhlmann, A, Mwangi, B, Krämer, B, Overs, B, Hartberg, CB, Abé, C, Dima, D, Grotegerd, D, Sprooten, E, Bøen, E, Jimenez, E, Howells, FM, Delvecchio, G, Temmingh, H, Starke, J, Almeida, JRC, Goikolea, JM, Houenou, J, Beard, LM, Rauer, L, Abramovic, L, Bonnin, M, Ponteduro, MF, Keil, M, Rive, MM, Yao, N, Yalin, N, Najt, P, Rosa, PG, Redlich, R, Trost, S, Hagenaars, S, Fears, SC, Alonso-Lana, S, van Erp, TGM, Nickson, T, Chaim-Avancini, TM, Meier, TB, Elvsåshagen, T, Haukvik, UK, Lee, WH, Schene, AH, Lloyd, AJ, Young, AH, Nugent, A, Dale, AM, Pfennig, A, McIntosh, AM, Lafer, B, Baune, BT, Ekman, CJ, Zarate, CA, Bearden, CE, Henry, C, Simhandl, C, McDonald, C, Bourne, C, Stein, DJ, Wolf, DH, Cannon, DM, Glahn, DC, Veltman, DJ, Pomarol-Clotet, E, Vieta, E, Canales-Rodriguez, EJ, Nery, FG, Duran, FLS, Busatto, GF, Roberts, G, Pearlson, GD, Goodwin, GM, Kugel, H, Whalley, HC, Ruhe, HG, Soares, JC, Fullerton, JM, Rybakowski, JK, Savitz, J, Chaim, KT, Fatjó-Vilas, M, Soeiro-de-Souza, MG, Boks, MP, Zanetti, MV, Otaduy, MCG, Schaufelberger, MS, Alda, M, Ingvar, M, Phillips, ML, Kempton, MJ, Bauer, M, Landén, M, and Lawrence, NS
Subjects: Brain, Cerebral Cortex, Frontal Lobe, Prefrontal Cortex, Temporal Lobe, Humans, Magnetic Resonance Imaging, Case-Control Studies, Bipolar Disorder, Psychotic Disorders, Age Factors, Sex Factors, Adolescent, Adult, Middle Aged, Female, Male, Young Adult, Neuroimaging, Gray Matter, Clinical Research, Serious Mental Illness, Biomedical Imaging, Brain Disorders, Mental Health, Neurosciences, 2.1 Biological and endogenous factors, Aetiology, Mental health, Neurological, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 × 10-21), left fusiform gyrus (d=-0.288; P=8.25 × 10-21) and left rostral middle frontal cortex (d=-0.276; P=2.99 × 10-19). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

2. Sex-specifics of ECT outcome

Author: Blanken, M. A. J. T., Oudega, M. L., Hoogendoorn, A. W., Sonnenberg, C. S., Rhebergen, D., Klumpers, U. M. H., van Diermen, L., Birkenhager, T., Schrijvers, D., Redlich, R., Dannlowski, U., Heindel, W., Coenjaerts, M., Nordanskog, P., Oltedal, L., Kessler, U., Frid, L. M., Takamiya, A., Kishimoto, T., Jorgensen, M. B., Jorgensen, A., Bolwig, T., Emsell, L., Sienaert, P., Bouckaert, F., Abbott, C. C., Péran, P., Arbus, C., Yrondi, A., Kiebs, M., Philipsen, A., van Waarde, J. A., Prinsen, E., van Verseveld, M., van Wingen, G., ten Doesschate, F., Camprodon, J. A., Kritzer, M., Barbour, T., Argyelan, M., Cardoner, N., Urretavizcaya, M., Soriano-Mas, C., Narr, K. L., Espinoza, R. T., Prudic, J., Rowny, S., van Eijndhoven, Ph., Tendolkar, I., Dols, A., Psychiatry, APH - Aging & Later Life, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, APH - Methodology, IOO, Neurology, Amsterdam Neuroscience - Neurodegeneration, Adult Psychiatry, ANS - Brain Imaging, and ANS - Compulsivity, Impulsivity & Attention
Subjects: Psychiatry and Mental health, Clinical Psychology, All institutes and research themes of the Radboud University Medical Center, Phenotype, SDG 3 - Good Health and Well-being, Electroconvulsive therapy, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], ECT, Sex, Human medicine, Major depressive disorder, Sex-specific, Predictor
Abstract: Objective: Electroconvulsive therapy (ECT) is the most effective treatment for patients with severe major depressive disorder (MDD). Given the known sex differences in MDD, improved knowledge may provide more sex-specific recommendations in clinical guidelines and improve outcome. In the present study we examine sex differences in ECT outcome and its predictors. Methods: Clinical data from 20 independent sites participating in the Global ECT-MRI Research Collaboration (GEMRIC) were obtained for analysis, totaling 500 patients with MDD (58.6 % women) with a mean age of 54.8 years. Severity of depression before and after ECT was assessed with validated depression scales. Remission was defined as a HAM-D score of 7 points or below after ECT. Variables associated with remission were selected based on literature (i.e. depression severity at baseline, age, duration of index episode, and presence of psychotic symptoms). Results: Remission rates of ECT were independent of sex, 48.0 % in women and 45.7 % in men (X2(1) = 0.2, p = 0.70). In the logistic regression analyses, a shorter index duration was identified as a sex-specific predictor for ECT outcome in women (X2(1) = 7.05, p = 0.01). The corresponding predictive margins did show overlapping confidence intervals for men and women. Conclusion: The evidence provided by our study suggests that ECT as a biological treatment for MDD is equally effective in women and men. A shorter duration of index episode was an additional sex- specific predictor for remission in women. Future research should establish whether the confidence intervals for the corresponding predictive margins are overlapping, as we find, or not.
Published: 2023

3. Sex-specifics of ECT outcome

Author: Blanken, M. A.J.T., Oudega, M. L., Hoogendoorn, A. W., Sonnenberg, C. S., Rhebergen, D., Klumpers, U. M.H., Van Diermen, L., Birkenhager, T., Schrijvers, D., Redlich, R., Dannlowski, U., Heindel, W., Coenjaerts, M., Nordanskog, P., Oltedal, L., Kessler, U., Frid, L. M., Takamiya, A., Kishimoto, T., Jorgensen, M. B., Jorgensen, A., Bolwig, T., Emsell, L., Sienaert, P., Bouckaert, F., Abbott, C. C., Péran, P., Arbus, C., Yrondi, A., Kiebs, M., Philipsen, A., van Waarde, J. A., Prinsen, E., van Verseveld, M., Van Wingen, G., ten Doesschate, F., Camprodon, J. A., Kritzer, M., Barbour, T., Argyelan, M., Cardoner, N., Urretavizcaya, M., Soriano-Mas, C., Narr, K. L., Espinoza, R. T., Prudic, J., Rowny, S., van Eijndhoven, Ph, Tendolkar, I., Dols, A., Blanken, M. A.J.T., Oudega, M. L., Hoogendoorn, A. W., Sonnenberg, C. S., Rhebergen, D., Klumpers, U. M.H., Van Diermen, L., Birkenhager, T., Schrijvers, D., Redlich, R., Dannlowski, U., Heindel, W., Coenjaerts, M., Nordanskog, P., Oltedal, L., Kessler, U., Frid, L. M., Takamiya, A., Kishimoto, T., Jorgensen, M. B., Jorgensen, A., Bolwig, T., Emsell, L., Sienaert, P., Bouckaert, F., Abbott, C. C., Péran, P., Arbus, C., Yrondi, A., Kiebs, M., Philipsen, A., van Waarde, J. A., Prinsen, E., van Verseveld, M., Van Wingen, G., ten Doesschate, F., Camprodon, J. A., Kritzer, M., Barbour, T., Argyelan, M., Cardoner, N., Urretavizcaya, M., Soriano-Mas, C., Narr, K. L., Espinoza, R. T., Prudic, J., Rowny, S., van Eijndhoven, Ph, Tendolkar, I., and Dols, A.
Abstract: Objective: Electroconvulsive therapy (ECT) is the most effective treatment for patients with severe major depressive disorder (MDD). Given the known sex differences in MDD, improved knowledge may provide more sex-specific recommendations in clinical guidelines and improve outcome. In the present study we examine sex differences in ECT outcome and its predictors. Methods: Clinical data from 20 independent sites participating in the Global ECT-MRI Research Collaboration (GEMRIC) were obtained for analysis, totaling 500 patients with MDD (58.6 % women) with a mean age of 54.8 years. Severity of depression before and after ECT was assessed with validated depression scales. Remission was defined as a HAM-D score of 7 points or below after ECT. Variables associated with remission were selected based on literature (i.e. depression severity at baseline, age, duration of index episode, and presence of psychotic symptoms). Results: Remission rates of ECT were independent of sex, 48.0 % in women and 45.7 % in men (X2(1) = 0.2, p = 0.70). In the logistic regression analyses, a shorter index duration was identified as a sex-specific predictor for ECT outcome in women (X2(1) = 7.05, p = 0.01). The corresponding predictive margins did show overlapping confidence intervals for men and women. Conclusion: The evidence provided by our study suggests that ECT as a biological treatment for MDD is equally effective in women and men. A shorter duration of index episode was an additional sex- specific predictor for remission in women. Future research should establish whether the confidence intervals for the corresponding predictive margins are overlapping, as we find, or not.
Published: 2023

4. Prefrontal gray matter volume mediates genetic risks for obesity

Author: Opel, N, Redlich, R, Kaehler, C, Grotegerd, D, Dohm, K, Heindel, W, Kugel, H, Thalamuthu, A, Koutsouleris, N, Arolt, V, Teuber, A, Wersching, H, Baune, B T, Berger, K, and Dannlowski, U
Published: 2017
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5. In vivo hippocampal subfield volumes in bipolar disorder—A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group

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

6. Association Between Genetic Risk for Type 2 Diabetes and Structural Brain Connectivity in Major Depressive Disorder

Author: Repple, J, Koenig, A, de Lange, SC, Opel, N, Redlich, R, Meinert, S, Grotegerd, D, Mauritz, M, Hahn, T, Borgers, T, Leehr, EJ, Winter, N, Goltermann, J, Enneking, V, Fingas, SM, Lemke, H, Waltemate, L, Dohm, K, Richter, M, Holstein, V, Gruber, M, Nenadic, I, Krug, A, Brosch, K, Schmitt, S, Stein, F, Meller, T, Jansen, A, Steinstraeter, O, Amare, AT, Kircher, T, Baune, BT, van den Heuvel, MP, Dannlowski, U, Repple, J, Koenig, A, de Lange, SC, Opel, N, Redlich, R, Meinert, S, Grotegerd, D, Mauritz, M, Hahn, T, Borgers, T, Leehr, EJ, Winter, N, Goltermann, J, Enneking, V, Fingas, SM, Lemke, H, Waltemate, L, Dohm, K, Richter, M, Holstein, V, Gruber, M, Nenadic, I, Krug, A, Brosch, K, Schmitt, S, Stein, F, Meller, T, Jansen, A, Steinstraeter, O, Amare, AT, Kircher, T, Baune, BT, van den Heuvel, MP, and Dannlowski, U
Abstract: BACKGROUND: Major depressive disorder (MDD) and type 2 diabetes mellitus (T2D) are known to share clinical comorbidity and to have genetic overlap. Besides their shared genetics, both diseases seem to be associated with alterations in brain structural connectivity and impaired cognitive performance, but little is known about the mechanisms by which genetic risk of T2D might affect brain structure and function and if they do, how these effects could contribute to the disease course of MDD. METHODS: This study explores the association of polygenic risk for T2D with structural brain connectome topology and cognitive performance in 434 nondiabetic patients with MDD and 539 healthy control subjects. RESULTS: Polygenic risk score for T2D across MDD patients and healthy control subjects was found to be associated with reduced global fractional anisotropy, a marker of white matter microstructure, an effect found to be predominantly present in MDD-related fronto-temporo-parietal connections. A mediation analysis further suggests that this fractional anisotropy variation may mediate the association between polygenic risk score and cognitive performance. CONCLUSIONS: Our findings provide preliminary evidence of a polygenic risk for T2D to be linked to brain structural connectivity and cognition in patients with MDD and healthy control subjects, even in the absence of a direct T2D diagnosis. This suggests an effect of T2D genetic risk on white matter integrity, which may mediate an association of genetic risk for diabetes and cognitive impairments.
Published: 2022

7. Genetic variants associated with longitudinal changes in brain structure across the lifespan

Author: Brouwer, RM, Klein, M, Grasby, KL, Schnack, HG, Jahanshad, N, Teeuw, J, Thomopoulos, SI, Sprooten, E, Franz, CE, Gogtay, N, Kremen, WS, Panizzon, MS, Olde Loohuis, LM, Whelan, CD, Aghajani, M, Alloza, C, Alanaes, D, Artiges, E, Ayesa-Arriola, R, Barker, GJ, Bastin, ME, Blok, E, Boen, E, Breukelaar, IA, Bright, JK, Buimer, EEL, Bulow, R, Cannon, DM, Ciufolini, S, Crossley, NA, Damatac, CG, Dazzan, P, de Mol, CL, de Zwarte, SMC, Desrivieres, S, Diaz-Caneja, CM, Doan, NT, Dohm, K, Froehner, JH, Goltermann, J, Grigis, A, Grotegerd, D, Han, LKM, Harris, MA, Hartman, CA, Heany, SJ, Heindel, W, Heslenfeld, DJ, Hohmann, S, Ittermann, B, Jansen, PR, Janssen, J, Jia, T, Jiang, J, Jockwitz, C, Karali, T, Keeser, D, Koevoets, MGJC, Lenroot, RK, Malchow, B, Mandl, RCW, Medel, V, Meinert, S, Morgan, CA, Muehleisen, TW, Nabulsi, L, Opel, N, de la Foz, VO-G, Overs, BJ, Paillere Martinot, M-L, Redlich, R, Marques, TR, Repple, J, Roberts, G, Roshchupkin, GV, Setiaman, N, Shumskaya, E, Stein, F, Sudre, G, Takahashi, S, Thalamuthu, A, Tordesillas-Gutierrez, D, van der Lugt, A, van Haren, NEM, Wardlaw, JM, Wen, W, Westeneng, H-J, Wittfeld, K, Zhu, AH, Zugman, A, Armstrong, NJ, Bonfiglio, G, Bralten, J, Dalvie, S, Davies, G, Di Forti, M, Ding, L, Donohoe, G, Forstner, AJ, Gonzalez-Penas, J, Guimaraes, JPOFT, Homuth, G, Hottenga, J-J, Knol, MJ, Kwok, JBJ, Le Hellard, S, Mather, KA, Milaneschi, Y, Morris, DW, Noethen, MM, Papiol, S, Rietschel, M, Santoro, ML, Steen, VM, Stein, JL, Streit, F, Tankard, RM, Teumer, A, van 't Ent, D, van der Meer, D, van Eijk, KR, Vassos, E, Vazquez-Bourgon, J, Witt, SH, Adams, HHH, Agartz, I, Ames, D, Amunts, K, Andreassen, OA, Arango, C, Banaschewski, T, Baune, BT, Belangero, SI, Bokde, ALW, Boomsma, DI, Bressan, RA, Brodaty, H, Buitelaar, JK, Cahn, W, Caspers, S, Cichon, S, Crespo-Facorro, B, Cox, SR, Dannlowski, U, Elvsashagen, T, Espeseth, T, Falkai, PG, Fisher, SE, Flor, H, Fullerton, JM, Garavan, H, Gowland, PA, Grabe, HJ, Hahn, T, Heinz, A, Hillegers, M, Hoare, J, Hoekstra, PJ, Ikram, MA, Jackowski, AP, Jansen, A, Jonsson, EG, Kahn, RS, Kircher, T, Korgaonkar, MS, Krug, A, Lemaitre, H, Malt, UF, Martinot, J-L, McDonald, C, Mitchell, PB, Muetzel, RL, Murray, RM, Nees, F, Nenadic, I, Oosterlaan, J, Ophoff, RA, Pan, PM, Penninx, BWJH, Poustka, L, Sachdev, PS, Salum, GA, Schofield, PR, Schumann, G, Shaw, P, Sim, K, Smolka, MN, Stein, DJ, Trollor, JN, van den Berg, LH, Veldink, JH, Walter, H, Westlye, LT, Whelan, R, White, T, Wright, MJ, Medland, SE, Franke, B, Thompson, PM, Hulshoff Pol, HE, Brouwer, RM, Klein, M, Grasby, KL, Schnack, HG, Jahanshad, N, Teeuw, J, Thomopoulos, SI, Sprooten, E, Franz, CE, Gogtay, N, Kremen, WS, Panizzon, MS, Olde Loohuis, LM, Whelan, CD, Aghajani, M, Alloza, C, Alanaes, D, Artiges, E, Ayesa-Arriola, R, Barker, GJ, Bastin, ME, Blok, E, Boen, E, Breukelaar, IA, Bright, JK, Buimer, EEL, Bulow, R, Cannon, DM, Ciufolini, S, Crossley, NA, Damatac, CG, Dazzan, P, de Mol, CL, de Zwarte, SMC, Desrivieres, S, Diaz-Caneja, CM, Doan, NT, Dohm, K, Froehner, JH, Goltermann, J, Grigis, A, Grotegerd, D, Han, LKM, Harris, MA, Hartman, CA, Heany, SJ, Heindel, W, Heslenfeld, DJ, Hohmann, S, Ittermann, B, Jansen, PR, Janssen, J, Jia, T, Jiang, J, Jockwitz, C, Karali, T, Keeser, D, Koevoets, MGJC, Lenroot, RK, Malchow, B, Mandl, RCW, Medel, V, Meinert, S, Morgan, CA, Muehleisen, TW, Nabulsi, L, Opel, N, de la Foz, VO-G, Overs, BJ, Paillere Martinot, M-L, Redlich, R, Marques, TR, Repple, J, Roberts, G, Roshchupkin, GV, Setiaman, N, Shumskaya, E, Stein, F, Sudre, G, Takahashi, S, Thalamuthu, A, Tordesillas-Gutierrez, D, van der Lugt, A, van Haren, NEM, Wardlaw, JM, Wen, W, Westeneng, H-J, Wittfeld, K, Zhu, AH, Zugman, A, Armstrong, NJ, Bonfiglio, G, Bralten, J, Dalvie, S, Davies, G, Di Forti, M, Ding, L, Donohoe, G, Forstner, AJ, Gonzalez-Penas, J, Guimaraes, JPOFT, Homuth, G, Hottenga, J-J, Knol, MJ, Kwok, JBJ, Le Hellard, S, Mather, KA, Milaneschi, Y, Morris, DW, Noethen, MM, Papiol, S, Rietschel, M, Santoro, ML, Steen, VM, Stein, JL, Streit, F, Tankard, RM, Teumer, A, van 't Ent, D, van der Meer, D, van Eijk, KR, Vassos, E, Vazquez-Bourgon, J, Witt, SH, Adams, HHH, Agartz, I, Ames, D, Amunts, K, Andreassen, OA, Arango, C, Banaschewski, T, Baune, BT, Belangero, SI, Bokde, ALW, Boomsma, DI, Bressan, RA, Brodaty, H, Buitelaar, JK, Cahn, W, Caspers, S, Cichon, S, Crespo-Facorro, B, Cox, SR, Dannlowski, U, Elvsashagen, T, Espeseth, T, Falkai, PG, Fisher, SE, Flor, H, Fullerton, JM, Garavan, H, Gowland, PA, Grabe, HJ, Hahn, T, Heinz, A, Hillegers, M, Hoare, J, Hoekstra, PJ, Ikram, MA, Jackowski, AP, Jansen, A, Jonsson, EG, Kahn, RS, Kircher, T, Korgaonkar, MS, Krug, A, Lemaitre, H, Malt, UF, Martinot, J-L, McDonald, C, Mitchell, PB, Muetzel, RL, Murray, RM, Nees, F, Nenadic, I, Oosterlaan, J, Ophoff, RA, Pan, PM, Penninx, BWJH, Poustka, L, Sachdev, PS, Salum, GA, Schofield, PR, Schumann, G, Shaw, P, Sim, K, Smolka, MN, Stein, DJ, Trollor, JN, van den Berg, LH, Veldink, JH, Walter, H, Westlye, LT, Whelan, R, White, T, Wright, MJ, Medland, SE, Franke, B, Thompson, PM, and Hulshoff Pol, HE
Abstract: Human brain structure changes throughout the lifespan. Altered brain growth or rates of decline are implicated in a vast range of psychiatric, developmental and neurodegenerative diseases. In this study, we identified common genetic variants that affect rates of brain growth or atrophy in what is, to our knowledge, the first genome-wide association meta-analysis of changes in brain morphology across the lifespan. Longitudinal magnetic resonance imaging data from 15,640 individuals were used to compute rates of change for 15 brain structures. The most robustly identified genes GPR139, DACH1 and APOE are associated with metabolic processes. We demonstrate global genetic overlap with depression, schizophrenia, cognitive functioning, insomnia, height, body mass index and smoking. Gene set findings implicate both early brain development and neurodegenerative processes in the rates of brain changes. Identifying variants involved in structural brain changes may help to determine biological pathways underlying optimal and dysfunctional brain development and aging.
Published: 2022

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

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

9. Subcortical shape alterations in major depressive disorder: Findings from the ENIGMA major depressive disorder working group

Author: Ho, TC, Gutman, B, Pozzi, E, Grabe, HJ, Hosten, N, Wittfeld, K, Voelzke, H, Baune, B, Dannlowski, U, Foerster, K, Grotegerd, D, Redlich, R, Jansen, A, Kircher, T, Krug, A, Meinert, S, Nenadic, I, Opel, N, Dinga, R, Veltman, DJ, Schnell, K, Veer, I, Walter, H, Gotlib, IH, Sacchet, MD, Aleman, A, Groenewold, NA, Stein, DJ, Li, M, Walter, M, Ching, CRK, Jahanshad, N, Ragothaman, A, Isaev, D, Zavaliangos-Petropulu, A, Thompson, PM, Saemann, PG, Schmaal, L, Ho, TC, Gutman, B, Pozzi, E, Grabe, HJ, Hosten, N, Wittfeld, K, Voelzke, H, Baune, B, Dannlowski, U, Foerster, K, Grotegerd, D, Redlich, R, Jansen, A, Kircher, T, Krug, A, Meinert, S, Nenadic, I, Opel, N, Dinga, R, Veltman, DJ, Schnell, K, Veer, I, Walter, H, Gotlib, IH, Sacchet, MD, Aleman, A, Groenewold, NA, Stein, DJ, Li, M, Walter, M, Ching, CRK, Jahanshad, N, Ragothaman, A, Isaev, D, Zavaliangos-Petropulu, A, Thompson, PM, Saemann, PG, and Schmaal, L
Abstract: Alterations in regional subcortical brain volumes have been investigated as part of the efforts of an international consortium, ENIGMA, to identify reliable neural correlates of major depressive disorder (MDD). Given that subcortical structures are comprised of distinct subfields, we sought to build significantly from prior work by precisely mapping localized MDD-related differences in subcortical regions using shape analysis. In this meta-analysis of subcortical shape from the ENIGMA-MDD working group, we compared 1,781 patients with MDD and 2,953 healthy controls (CTL) on individual measures of shape metrics (thickness and surface area) on the surface of seven bilateral subcortical structures: nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Harmonized data processing and statistical analyses were conducted locally at each site, and findings were aggregated by meta-analysis. Relative to CTL, patients with adolescent-onset MDD (≤ 21 years) had lower thickness and surface area of the subiculum, cornu ammonis (CA) 1 of the hippocampus and basolateral amygdala (Cohen's d = -0.164 to -0.180). Relative to first-episode MDD, recurrent MDD patients had lower thickness and surface area in the CA1 of the hippocampus and the basolateral amygdala (Cohen's d = -0.173 to -0.184). Our results suggest that previously reported MDD-associated volumetric differences may be localized to specific subfields of these structures that have been shown to be sensitive to the effects of stress, with important implications for mapping treatments to patients based on specific neural targets and key clinical features.
Published: 2022

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

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

11. Correction to: Biological sex classification with structural MRI data shows increased misclassification in transgender women.

Author: Flint, C, Förster, K, Koser, SA, Konrad, C, Zwitserlood, P, Berger, K, Hermesdorf, M, Kircher, T, Nenadic, I, Krug, A, Baune, BT, Dohm, K, Redlich, R, Opel, N, Arolt, V, Hahn, T, Jiang, X, Dannlowski, U, Grotegerd, D, Flint, C, Förster, K, Koser, SA, Konrad, C, Zwitserlood, P, Berger, K, Hermesdorf, M, Kircher, T, Nenadic, I, Krug, A, Baune, BT, Dohm, K, Redlich, R, Opel, N, Arolt, V, Hahn, T, Jiang, X, Dannlowski, U, and Grotegerd, D
Published: 2022

12. Effects of electroconvulsive therapy on amygdala function in major depression – a longitudinal functional magnetic resonance imaging study

Author: Redlich, R., Bürger, C., Dohm, K., Grotegerd, D., Opel, N., Zaremba, D., Meinert, S., Förster, K., Repple, J., Schnelle, R., Wagenknecht, C., Zavorotnyy, M., Heindel, W., Kugel, H., Gerbaulet, M., Alferink, J., Arolt, V., Zwanzger, P., and Dannlowski, U.
Published: 2017
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13. TNF receptors 1 and 2 exert distinct region‐specific effects on striatal and hippocampal grey matter volumes (VBM) in healthy adults

Author: Stacey, D., Redlich, R., Büschel, A., Opel, N., Grotegerd, D., Zaremba, D., Dohm, K., Bürger, C., Meinert, S. L., Förster, K., Repple, J., Kaufmann, C., Kugel, H., Heindel, W., Arolt, V., Dannlowski, U., and Baune, B. T.
Published: 2017
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14. Multimodal imaging of a tescalcin (TESC)-regulating polymorphism (rs7294919)-specific effects on hippocampal gray matter structure

Author: Dannlowski, U, Grabe, H J, Wittfeld, K, Klaus, J, Konrad, C, Grotegerd, D, Redlich, R, Suslow, T, Opel, N, Ohrmann, P, Bauer, J, Zwanzger, P, Laeger, I, Hohoff, C, Arolt, V, Heindel, W, Deppe, M, Domschke, K, Hegenscheid, K, Völzke, H, Stacey, D, Meyer zu Schwabedissen, H, Kugel, H, and Baune, B T
Published: 2015
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15. Effective in-patient treatment is associated with an increase in structural brain connectivity in severely depressed patients

Author: Repple, J., Grumbach, P., Gruber, M., Mauritz, M., Dannlowski, U., and Redlich, R.
Published: 2022
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16. Cognitive performance and brain structural connectome alterations in major depressive disorder

Author: Gruber, M., Mauritz, M., Meinert, S., Grotegerd, D., de Lange, S.C., Grumbach, P., Goltermann, J., Winter, N.R., Waltemate, L., Lemke, H., Thiel, K., Winter, A., Breuer, F., Borgers, T., Enneking, V., Klug, M., Brosch, K., Meller, T., Pfarr, J.K., Ringwald, K.G., Stein, F., Opel, N., Redlich, R., Hahn, T., Leehr, E.J., Bauer, J., Nenadic, I., Kircher, T., van den Heuvel, M.P., Dannlowski, U., and Repple, J.
Published: 2022
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17. Effects of electroconvulsive therapy on brain structure in major depression over two years

Author: Borgers, T., Enneking, V., Klug, M., Meinert, H., Garbe, J., Wulle, M., Dannlowski, U., and Redlich, R.
Published: 2022
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18. P.0820 Association of resilience with limbic activity during negative emotional face processing in individuals who experienced childhood maltreatment

Author: Borgers, T., primary, Enneking, V., additional, Klug, M., additional, Dannlowski, U., additional, and Redlich, R., additional
Published: 2021
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19. Differing brain structural correlates of familial and environmental risk for major depressive disorder revealed by a combined VBM/pattern recognition approach

Author: Opel, N., Zwanzger, P., Redlich, R., Grotegerd, D., Dohm, K., Arolt, V., Heindel, W., Kugel, H., and Dannlowski, U.
Published: 2016
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20. Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts

Author: Campos, A, Thompson, PM, Veltman, DJ, Pozzi, E, van Veltzen, LS, Jahanshad, N, Adams, MJ, Baune, BT, Berger, K, Brosch, K, Bulow, R, Connolly, CG, Dannlowski, U, Davey, CG, de Zubicaray, G, Dima, D, Erwin-Grabner, T, Evans, JW, Fu, CHY, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Grotegerd, D, Harris, MA, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, McMahon, K, MacMaster, FP, Martin, NG, McIntosh, AM, Medland, SE, Meinert, S, Meller, T, Nenadic, I, Opel, N, Redlich, R, Reneman, L, Repple, J, Sacchet, MD, Schmitt, S, Schrantee, A, Sim, K, Singh, A, Stein, F, Strike, LT, van Der Wee, NJA, van Der Werff, SJA, Volzke, H, Waltemate, L, Whalley, HC, Wittfeld, K, Wright, MJ, Yang, TT, Zarate, CA, Schmaal, L, Renteria, ME, Campos, A, Thompson, PM, Veltman, DJ, Pozzi, E, van Veltzen, LS, Jahanshad, N, Adams, MJ, Baune, BT, Berger, K, Brosch, K, Bulow, R, Connolly, CG, Dannlowski, U, Davey, CG, de Zubicaray, G, Dima, D, Erwin-Grabner, T, Evans, JW, Fu, CHY, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Grotegerd, D, Harris, MA, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, McMahon, K, MacMaster, FP, Martin, NG, McIntosh, AM, Medland, SE, Meinert, S, Meller, T, Nenadic, I, Opel, N, Redlich, R, Reneman, L, Repple, J, Sacchet, MD, Schmitt, S, Schrantee, A, Sim, K, Singh, A, Stein, F, Strike, LT, van Der Wee, NJA, van Der Werff, SJA, Volzke, H, Waltemate, L, Whalley, HC, Wittfeld, K, Wright, MJ, Yang, TT, Zarate, CA, Schmaal, L, and Renteria, ME
Abstract: BACKGROUND: Neuroimaging studies of suicidal behavior have so far been conducted in small samples, prone to biases and false-positive associations, yielding inconsistent results. The ENIGMA-MDD Working Group aims to address the issues of poor replicability and comparability by coordinating harmonized analyses across neuroimaging studies of major depressive disorder and related phenotypes, including suicidal behavior. METHODS: Here, we pooled data from 18 international cohorts with neuroimaging and clinical measurements in 18,925 participants (12,477 healthy control subjects and 6448 people with depression, of whom 694 had attempted suicide). We compared regional cortical thickness and surface area and measures of subcortical, lateral ventricular, and intracranial volumes between suicide attempters, clinical control subjects (nonattempters with depression), and healthy control subjects. RESULTS: We identified 25 regions of interest with statistically significant (false discovery rate < .05) differences between groups. Post hoc examinations identified neuroimaging markers associated with suicide attempt including smaller volumes of the left and right thalamus and the right pallidum and lower surface area of the left inferior parietal lobe. CONCLUSIONS: This study addresses the lack of replicability and consistency in several previously published neuroimaging studies of suicide attempt and further demonstrates the need for well-powered samples and collaborative efforts. Our results highlight the potential involvement of the thalamus, a structure viewed historically as a passive gateway in the brain, and the pallidum, a region linked to reward response and positive affect. Future functional and connectivity studies of suicidal behaviors may focus on understanding how these regions relate to the neurobiological mechanisms of suicide attempt risk.
Published: 2021

21. Systematic misestimation of machine learning performance in neuroimaging studies of depression

Author: Flint, C, Cearns, M, Opel, N, Redlich, R, Mehler, DMA, Emden, D, Winter, NR, Leenings, R, Eickhoff, SB, Kircher, T, Krug, A, Nenadic, I, Arolt, V, Clark, S, Baune, BT, Jiang, X, Dannlowski, U, Hahn, T, Flint, C, Cearns, M, Opel, N, Redlich, R, Mehler, DMA, Emden, D, Winter, NR, Leenings, R, Eickhoff, SB, Kircher, T, Krug, A, Nenadic, I, Arolt, V, Clark, S, Baune, BT, Jiang, X, Dannlowski, U, and Hahn, T
Abstract: We currently observe a disconcerting phenomenon in machine learning studies in psychiatry: While we would expect larger samples to yield better results due to the availability of more data, larger machine learning studies consistently show much weaker performance than the numerous small-scale studies. Here, we systematically investigated this effect focusing on one of the most heavily studied questions in the field, namely the classification of patients suffering from Major Depressive Disorder (MDD) and healthy controls based on neuroimaging data. Drawing upon structural MRI data from a balanced sample of N = 1868 MDD patients and healthy controls from our recent international Predictive Analytics Competition (PAC), we first trained and tested a classification model on the full dataset which yielded an accuracy of 61%. Next, we mimicked the process by which researchers would draw samples of various sizes (N = 4 to N = 150) from the population and showed a strong risk of misestimation. Specifically, for small sample sizes (N = 20), we observe accuracies of up to 95%. For medium sample sizes (N = 100) accuracies up to 75% were found. Importantly, further investigation showed that sufficiently large test sets effectively protect against performance misestimation whereas larger datasets per se do not. While these results question the validity of a substantial part of the current literature, we outline the relatively low-cost remedy of larger test sets, which is readily available in most cases.
Published: 2021

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

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

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

Author: Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., Paus, T., Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., and Paus, T.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls. Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (exce
Published: 2021
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24. P.305 Inferior frontal gyrus activity as a possible neural marker of depression with comorbid anxiety compared to depression

Author: Sindermann, L., primary, Leehr, E.J., additional, Redlich, R., additional, Meinert, S., additional, Böhnlein, J., additional, Grotegerd, D., additional, Pollack, D., additional, Reppen, M., additional, Waltemate, L., additional, Fingas, S., additional, Lemke, H., additional, Enneking, V., additional, Opel, N., additional, Repple, J., additional, Goltermann, J., additional, and Dannlowski, U., additional
Published: 2021
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25. Brain structural correlates of alexithymia in patients with major depressive disorder

Author: Förster, K. (Katharina), Enneking, V. (Verena), Dohm, K. (Katharina), Redlich, R. (Ronny), Meinert, S. (Susanne), Geisler, A.I. (Adina), Leehr, E.J. (Elisabeth), Kugel, H. (Harald), Baune, B.T. (Bernhard), Arolt, V. (Volker), Zwitserlood, P. (Pienie), Grotegerd, D. (Dominik), Dannlowski, U. (Udo), and Universitäts- und Landesbibliothek Münster
Subjects: Medicine and health, ddc:610, behavioral disciplines and activities
Abstract: BACKGROUND: Alexithymia is a risk factor for major depressive disorder (MDD) and has been associated with diminished treatment response. Neuroimaging studies have revealed structural aberrations of the anterior cingulate cortex and the fusiform gyrus in healthy controls with high levels of alexithymia. The present study tried to corroborate and extend these results to patients with MDD compared with healthy controls. METHODS: We investigated the relationship between alexithymia, depression and grey matter volume in 63 patients with MDD (mean age ± standard deviation = 42.43 yr ± 11.91; 33 female) and 46 healthy controls (45.35 yr ± 8.37; 22 female). We assessed alexithymia using the Toronto Alexithymia Scale. We conducted an alexithymia × group analysis of covariance; we used a region-of-interest approach, including the fusiform gyrus and anterior cingulate cortex, and conducted whole brain analysis using voxelbased morphometry. RESULTS: Our analysis revealed a significant alexithymia × group interaction in the fusiform gyrus (left, pFWE = 0.031; right, pFWE = 0.010). Higher alexithymia scores were associated with decreased grey matter volume in patients with MDD (pFWE = 0.009), but with increased grey matter volume of the fusiform gyrus in healthy controls (pFWE = 0.044). We found no significant main effects in the region-of-interest analysis. LIMITATIONS: Owing to the naturalistic nature of our study, patients with MDD and healthy controls differed significantly in their alexithymia scores. CONCLUSION: Our results showed the fusiform gyrus as a correlate of alexithymia. We also found differences related to alexithymia between patients with MDD and healthy controls in the fusiform gyrus. Our study encourages research related to the transition from risk to MDD in people with alexithymia.
Published: 2020

26. Structural changes induced by electroconvulsive therapy are associated with clinical outcome

Author: Mulders, P.C.R., Llera, A., Beckmann, C.F., Vandenbulcke, M., Stek, M., Sienaert, P., Redlich, R., Petrides, G., Oudega, M.L., Oltedal, L., Oedegaard, K.J., Narr, K.L., Magnusson, P.O., Kessler, U., Jorgensen, A., Espinoza, R., Enneking, V., Emsell, L., Dols, A., Dannlowski, U., Bolwig, T.G., Bartsch, H., Argyelan, M., Anand, A., Abbott, C.C., Eijndhoven, P.F.P. van, Tendolkar, I., Mulders, P.C.R., Llera, A., Beckmann, C.F., Vandenbulcke, M., Stek, M., Sienaert, P., Redlich, R., Petrides, G., Oudega, M.L., Oltedal, L., Oedegaard, K.J., Narr, K.L., Magnusson, P.O., Kessler, U., Jorgensen, A., Espinoza, R., Enneking, V., Emsell, L., Dols, A., Dannlowski, U., Bolwig, T.G., Bartsch, H., Argyelan, M., Anand, A., Abbott, C.C., Eijndhoven, P.F.P. van, and Tendolkar, I.
Abstract: Contains fulltext : 220550.pdf (Publisher’s version ) (Open Access), BACKGROUND: Electroconvulsive therapy (ECT) is the most effective treatment option for major depressive disorder, so understanding whether its clinical effect relates to structural brain changes is vital for current and future antidepressant research. OBJECTIVE: To determine whether clinical response to ECT is related to structural volumetric changes in the brain as measured by structural magnetic resonance imaging (MRI) and, if so, which regions are related to this clinical effect. We also determine whether a similar model can be used to identify regions associated with electrode placement (unilateral versus bilateral ECT). METHODS: Longitudinal MRI and clinical data (Hamilton Depression Rating Scale) was collected from 10 sites as part of the Global ECT-MRI research collaboration (GEMRIC). From 192 subjects, relative changes in 80 (sub)cortical areas were used as potential features for classifying treatment response. We used recursive feature elimination to extract relevant features, which were subsequently used to train a linear classifier. As a validation, the same was done for electrode placement. We report accuracy as well as the structural coefficients of regions included in the discriminative spatial patterns obtained. RESULTS: A pattern of structural changes in cortical midline, striatal and lateral prefrontal areas discriminates responders from non-responders (75% accuracy, p < 0.001) while left-sided mediotemporal changes discriminate unilateral from bilateral electrode placement (81% accuracy, p < 0.001). CONCLUSIONS: The identification of a multivariate discriminative pattern shows that structural change is relevant for clinical response to ECT, but this pattern does not include mediotemporal regions that have been the focus of electroconvulsive therapy research so far.
Published: 2020

27. International Consortium on the Genetics of Electroconvulsive Therapy and Severe Depressive Disorders (Gen-ECT-ic)

Author: Soda, T, McLoughlin, DM, Clark, SR, Oltedal, L, Kessler, U, Haavik, J, Bousman, C, Smith, DJ, Bioque, M, Clements, CC, Loo, C, Vila-Rodriguez, F, Minelli, A, Mickey, BJ, Milev, R, Docherty, AR, Langan Martin, J, Achtyes, ED, Arolt, V, Redlich, R, Dannlowski, U, Cardoner, N, Clare, E, Craddock, N, Di Florio, A, Dmitrzak-Weglarz, M, Forty, L, Gordon-Smith, K, Husain, M, Ingram, WM, Jones, L, Jones, I, Juruena, M, Kirov, G, Landén, M, Müller, DJ, Nordensköld, A, Pålsson, E, Paul, M, Permoda, A, Pliszka, B, Rea, J, Schubert, KO, Sonnen, JA, Soria, V, Stageman, W, Takamiya, A, Urretavizacaya, M, Watson, S, Zavorotny, M, Young, AH, Vieta, E, Rybakowski, JK, Gennarelli, M, Zandi, PP, Sullivan, PF, Baune, BT, Soda, T, McLoughlin, DM, Clark, SR, Oltedal, L, Kessler, U, Haavik, J, Bousman, C, Smith, DJ, Bioque, M, Clements, CC, Loo, C, Vila-Rodriguez, F, Minelli, A, Mickey, BJ, Milev, R, Docherty, AR, Langan Martin, J, Achtyes, ED, Arolt, V, Redlich, R, Dannlowski, U, Cardoner, N, Clare, E, Craddock, N, Di Florio, A, Dmitrzak-Weglarz, M, Forty, L, Gordon-Smith, K, Husain, M, Ingram, WM, Jones, L, Jones, I, Juruena, M, Kirov, G, Landén, M, Müller, DJ, Nordensköld, A, Pålsson, E, Paul, M, Permoda, A, Pliszka, B, Rea, J, Schubert, KO, Sonnen, JA, Soria, V, Stageman, W, Takamiya, A, Urretavizacaya, M, Watson, S, Zavorotny, M, Young, AH, Vieta, E, Rybakowski, JK, Gennarelli, M, Zandi, PP, Sullivan, PF, and Baune, BT
Abstract: Recent genome-wide association studies have demonstrated that the genetic burden associated with depression correlates with depression severity. Therefore, conducting genetic studies of patients at the most severe end of the depressive disorder spectrum, those with treatment-resistant depression and who are prescribed electroconvulsive therapy (ECT), could lead to a better understanding of the genetic underpinnings of depression. Despite ECT being one of the most effective forms of treatment for severe depressive disorders, it is usually placed at the end of treatment algorithms of current guidelines. This is perhaps because ECT has controlled risk and logistical demands including use of general anaesthesia and muscle relaxants and side-effects such as short-term memory impairment. Better understanding of the genetics and biology of ECT response and of cognitive side-effects could lead to more personalized treatment decisions. To enhance the understanding of the genomics of severe depression and ECT response, researchers and ECT providers from around the world and from various depression or ECT networks, but not limited to, such as the Psychiatric Genomics Consortium, the Clinical Alliance and Research in ECT, and the National Network of Depression Centers have formed the Genetics of ECT International Consortium (Gen-ECT-ic). Gen-ECT-ic will organize the largest clinical and genetic collection to date to study the genomics of severe depressive disorders and response to ECT, aiming for 30,000 patients worldwide using a GWAS approach. At this stage it will be the largest genomic study on treatment response in depression. Retrospective data abstraction and prospective data collection will be facilitated by a uniform data collection approach that is flexible and will incorporate data from many clinical practices. Gen-ECT-ic invites all ECT providers and researchers to join its efforts.
Published: 2020

28. 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, 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, 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
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

29. 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

30. Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder

Author: Repple, J, Mauritz, M, Meinert, S, de Lange, SC, Grotegerd, D, Opel, N, Redlich, R, Hahn, T, Foerster, K, Leehr, EJ, Winter, N, Goltermann, J, Enneking, V, Fingas, SM, Lemke, H, Waltemate, L, Nenadic, I, Krug, A, Brosch, K, Schmitt, S, Stein, F, Meller, T, Jansen, A, Steinstraeter, O, Baune, BT, Kircher, T, Dannlowski, U, van den Heuvel, MP, Repple, J, Mauritz, M, Meinert, S, de Lange, SC, Grotegerd, D, Opel, N, Redlich, R, Hahn, T, Foerster, K, Leehr, EJ, Winter, N, Goltermann, J, Enneking, V, Fingas, SM, Lemke, H, Waltemate, L, Nenadic, I, Krug, A, Brosch, K, Schmitt, S, Stein, F, Meller, T, Jansen, A, Steinstraeter, O, Baune, BT, Kircher, T, Dannlowski, U, and van den Heuvel, MP
Abstract: Major depressive disorder (MDD) is associated to affected brain wiring. Little is known whether these changes are stable over time and hence might represent a biological predisposition, or whether these are state markers of current disease severity and recovery after a depressive episode. Human white matter network ("connectome") analysis via network science is a suitable tool to investigate the association between affected brain connectivity and MDD. This study examines structural connectome topology in 464 MDD patients (mean age: 36.6 years) and 432 healthy controls (35.6 years). MDD patients were stratified categorially by current disease status (acute vs. partial remission vs. full remission) based on DSM-IV criteria. Current symptom severity was assessed continuously via the Hamilton Depression Rating Scale (HAMD). Connectome matrices were created via a combination of T1-weighted magnetic resonance imaging (MRI) and tractography methods based on diffusion-weighted imaging. Global tract-based metrics were not found to show significant differences between disease status groups, suggesting conserved global brain connectivity in MDD. In contrast, reduced global fractional anisotropy (FA) was observed specifically in acute depressed patients compared to fully remitted patients and healthy controls. Within the MDD patients, FA in a subnetwork including frontal, temporal, insular, and parietal nodes was negatively associated with HAMD, an effect remaining when correcting for lifetime disease severity. Therefore, our findings provide new evidence of MDD to be associated with structural, yet dynamic, state-dependent connectome alterations, which covary with current disease severity and remission status after a depressive episode.
Published: 2020

31. Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort

Author: Tozzi, L, Garczarek, L, Janowitz, D, Stein, DJ, Wittfeld, K, Dobrowolny, H, Lagopoulos, J, Hatton, SN, Hickie, IB, Carballedo, A, Brooks, SJ, Vuletic, D, Uhlmann, A, Veer, IM, Walter, H, Buelow, R, Voelzke, H, Klinger-Koenig, J, Schnell, K, Schoepf, D, Grotegerd, D, Opel, N, Dannlowski, U, Kugel, H, Schramm, E, Konrad, C, Kircher, T, Jueksel, DI, Nenadic, I, Krug, A, Hahn, T, Steinstraeter, O, Redlich, R, Zaremba, D, Zurowski, B, Fu, CHY, Dima, D, Cole, J, Grabe, HJ, Connolly, CG, Yang, TT, Ho, TC, Lewinn, KZ, Li, M, Groenewold, NA, Salminen, LE, Walter, M, Simmons, AN, van Erp, TGM, Jahanshad, N, Baune, BT, van der Wee, NJA, van Tol, M-J, Penninx, BWJH, Hibar, DP, Thompson, PM, Veltman, DJ, Schmaal, L, Frodl, T, Tozzi, L, Garczarek, L, Janowitz, D, Stein, DJ, Wittfeld, K, Dobrowolny, H, Lagopoulos, J, Hatton, SN, Hickie, IB, Carballedo, A, Brooks, SJ, Vuletic, D, Uhlmann, A, Veer, IM, Walter, H, Buelow, R, Voelzke, H, Klinger-Koenig, J, Schnell, K, Schoepf, D, Grotegerd, D, Opel, N, Dannlowski, U, Kugel, H, Schramm, E, Konrad, C, Kircher, T, Jueksel, DI, Nenadic, I, Krug, A, Hahn, T, Steinstraeter, O, Redlich, R, Zaremba, D, Zurowski, B, Fu, CHY, Dima, D, Cole, J, Grabe, HJ, Connolly, CG, Yang, TT, Ho, TC, Lewinn, KZ, Li, M, Groenewold, NA, Salminen, LE, Walter, M, Simmons, AN, van Erp, TGM, Jahanshad, N, Baune, BT, van der Wee, NJA, van Tol, M-J, Penninx, BWJH, Hibar, DP, Thompson, PM, Veltman, DJ, Schmaal, L, and Frodl, T
Abstract: BACKGROUND: Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age. METHODS: Within the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer. RESULTS: CM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions. CONCLUSIONS: Severity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.
Published: 2020

32. The role of BDNF methylation and Val66Met in amygdala reactivity during emotion processing

Author: Redlich, R, Schneider, I, Kerkenberg, N, Opel, N, Bauhaus, J, Enneking, V, Repple, J, Leehr, EJ, Grotegerd, D, Kaehler, C, Foerster, K, Dohm, K, Meinert, S, Hahn, T, Kugel, H, Schwarte, K, Schettler, C, Domschke, K, Arolt, V, Heindel, W, Baune, BT, Zhang, W, Hohoff, C, Dannlowski, U, Redlich, R, Schneider, I, Kerkenberg, N, Opel, N, Bauhaus, J, Enneking, V, Repple, J, Leehr, EJ, Grotegerd, D, Kaehler, C, Foerster, K, Dohm, K, Meinert, S, Hahn, T, Kugel, H, Schwarte, K, Schettler, C, Domschke, K, Arolt, V, Heindel, W, Baune, BT, Zhang, W, Hohoff, C, and Dannlowski, U
Abstract: Epigenetic alterations of the brain-derived neurotrophic factor (BDNF) gene have been associated with psychiatric disorders in humans and with differences in amygdala BDNF mRNA levels in rodents. This human study aimed to investigate the relationship between the functional BDNF-Val66 Met polymorphism, its surrounding DNA methylation in BDNF exon IX, amygdala reactivity to emotional faces, and personality traits. Healthy controls (HC, n = 189) underwent functional MRI during an emotional face-matching task. Harm avoidance, novelty seeking and reward dependence were measured using the Tridimensional Personality Questionnaire (TPQ). Individual BDNF methylation profiles were ascertained and associated with several BDNF single nucleotide polymorphisms surrounding the BDNF-Val66 Met, amygdala reactivity, novelty seeking and harm avoidance. Higher BDNF methylation was associated with higher amygdala reactivity (x = 34, y = 0, z = -26, t(166) = 3.00, TFCE = 42.39, p(FWE) = .045), whereby the BDNF-Val66 Met genotype per se did not show any significant association with brain function. Furthermore, novelty seeking was negatively associated with BDNF methylation (r = -.19, p = .015) and amygdala reactivity (r = -.17, p = .028), while harm avoidance showed a trend for a positive association with BDNF methylation (r = .14, p = .066). The study provides first insights into the relationship among BDNF methylation, BDNF genotype, amygdala reactivity and personality traits in humans, highlighting the multidimensional relations among genetics, epigenetics, and neuronal functions. The present study suggests a possible involvement of epigenetic BDNF modifications in psychiatric disorders and related brain functions, whereby high BDNF methylation might reduce BDNF mRNA expression and upregulate amygdala reactivity.
Published: 2020

33. Brain structural correlates of alexithymia in patients with major depressive disorder

Author: Foerster, K, Enneking, V, Dohm, K, Redlich, R, Meinert, S, Geisler, AI, Leehr, EJ, Kugel, H, Baune, BT, Arolt, V, Zwitserlood, P, Grotegerd, D, Dannlowski, U, Foerster, K, Enneking, V, Dohm, K, Redlich, R, Meinert, S, Geisler, AI, Leehr, EJ, Kugel, H, Baune, BT, Arolt, V, Zwitserlood, P, Grotegerd, D, and Dannlowski, U
Abstract: BACKGROUND: Alexithymia is a risk factor for major depressive disorder (MDD) and has been associated with diminished treatment response. Neuroimaging studies have revealed structural aberrations of the anterior cingulate cortex and the fusiform gyrus in healthy controls with high levels of alexithymia. The present study tried to corroborate and extend these results to patients with MDD compared with healthy controls. METHODS: We investigated the relationship between alexithymia, depression and grey matter volume in 63 patients with MDD (mean age ± standard deviation = 42.43 yr ± 11.91; 33 female) and 46 healthy controls (45.35 yr ± 8.37; 22 female). We assessed alexithymia using the Toronto Alexithymia Scale. We conducted an alexithymia × group analysis of covariance; we used a region-of-interest approach, including the fusiform gyrus and anterior cingulate cortex, and conducted whole brain analysis using voxelbased morphometry. RESULTS: Our analysis revealed a significant alexithymia × group interaction in the fusiform gyrus (left, pFWE = 0.031; right, pFWE = 0.010). Higher alexithymia scores were associated with decreased grey matter volume in patients with MDD (pFWE = 0.009), but with increased grey matter volume of the fusiform gyrus in healthy controls (pFWE = 0.044). We found no significant main effects in the region-of-interest analysis. LIMITATIONS: Owing to the naturalistic nature of our study, patients with MDD and healthy controls differed significantly in their alexithymia scores. CONCLUSION: Our results showed the fusiform gyrus as a correlate of alexithymia. We also found differences related to alexithymia between patients with MDD and healthy controls in the fusiform gyrus. Our study encourages research related to the transition from risk to MDD in people with alexithymia.
Published: 2020

34. 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

35. Brain functional effects of electroconvulsive therapy during emotional processing in major depressive disorder

Author: Enneking, V, Dzvonyar, F, Dueck, K, Dohm, K, Grotegerd, D, Foerster, K, Meinert, S, Lemke, H, Klug, M, Waltemate, L, Goltermann, J, Huelsmann, C, Borgers, T, Boehnlein, J, Sindermann, L, Richter, M, Leehr, EJ, Repple, J, Opel, N, Baune, BT, Dannlowski, U, Redlich, R, Enneking, V, Dzvonyar, F, Dueck, K, Dohm, K, Grotegerd, D, Foerster, K, Meinert, S, Lemke, H, Klug, M, Waltemate, L, Goltermann, J, Huelsmann, C, Borgers, T, Boehnlein, J, Sindermann, L, Richter, M, Leehr, EJ, Repple, J, Opel, N, Baune, BT, Dannlowski, U, and Redlich, R
Abstract: BACKGROUND: In treatment-resistant major depressive disorder (MDD), electroconvulsive therapy (ECT) is a treatment with high efficacy. While knowledge regarding changes in brain structure following ECT is growing, the effects of ECT on brain function during emotional processing are largely unknown. OBJECTIVE: We investigated the effects of ECT on the activity of the anterior cingulate cortex (ACC) and amygdala during negative emotional stimuli processing and its association with clinical response. METHODS: In this non-randomized longitudinal study, patients with MDD (n = 37) were assessed before and after treatment with ECT. Healthy controls (n = 37) were matched regarding age and gender. Functional magnetic resonance imaging (fMRI) was obtained twice, at baseline and after six weeks using a supraliminal face-matching paradigm. In order to evaluate effects of clinical response, additional post-hoc analyses were performed comparing responders to non-responders. RESULTS: After ECT, patients with MDD showed a statistically significant increase in ACC activity during processing of negative emotional stimuli (pFWE = .039). This effect was driven by responders (pFWE = .023), while non-responders showed no increase. Responders also had lower pre-treatment ACC activity compared to non-responders (pFWE = .025). No significant effects in the amygdala could be observed. CONCLUSIONS: ECT leads to brain functional changes in the ACC, a relevant region for emotional regulation during processing of negative stimuli. Furthermore, baseline ACC activity might serve as a biomarker for treatment response. Findings are in accordance with recent studies highlighting properties of pre-treatment ACC to be associated with general antidepressive treatment response.
Published: 2020

36. Brain structural correlates of insomnia severity in 1053 individuals with major depressive disorder: results from the ENIGMA MDD Working Group

Author: Leerssen, J, Blanken, TF, Pozzi, E, Jahanshad, N, Aftanas, L, Andreassen, OA, Baune, BT, Brack, I, Carballedo, A, Ching, CRK, Dannlowski, U, Dohm, K, Enneking, V, Filimonova, E, Fingas, SM, Frodl, T, Godlewska, BR, Goltermann, J, Gotlib, IH, Grotegerd, D, Gruber, O, Harris, MA, Hatton, SN, Hawkins, E, Hickie, IB, Jaworska, N, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, Li, M, MacMaster, FP, McIntosh, AM, McLellan, Q, Meinert, S, Mwangi, B, Nenadic, I, Osipov, E, Portella, MJ, Redlich, R, Repple, J, Sacchet, MD, Saemann, PG, Simulionyte, E, Soares, JC, Walter, M, Watanabe, N, Whalley, HC, Yueksel, D, Veltman, DJ, Thompson, PM, Schmaal, L, Van Someren, EJW, Leerssen, J, Blanken, TF, Pozzi, E, Jahanshad, N, Aftanas, L, Andreassen, OA, Baune, BT, Brack, I, Carballedo, A, Ching, CRK, Dannlowski, U, Dohm, K, Enneking, V, Filimonova, E, Fingas, SM, Frodl, T, Godlewska, BR, Goltermann, J, Gotlib, IH, Grotegerd, D, Gruber, O, Harris, MA, Hatton, SN, Hawkins, E, Hickie, IB, Jaworska, N, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, Li, M, MacMaster, FP, McIntosh, AM, McLellan, Q, Meinert, S, Mwangi, B, Nenadic, I, Osipov, E, Portella, MJ, Redlich, R, Repple, J, Sacchet, MD, Saemann, PG, Simulionyte, E, Soares, JC, Walter, M, Watanabe, N, Whalley, HC, Yueksel, D, Veltman, DJ, Thompson, PM, Schmaal, L, and Van Someren, EJW
Abstract: It has been difficult to find robust brain structural correlates of the overall severity of major depressive disorder (MDD). We hypothesized that specific symptoms may better reveal correlates and investigated this for the severity of insomnia, both a key symptom and a modifiable major risk factor of MDD. Cortical thickness, surface area and subcortical volumes were assessed from T1-weighted brain magnetic resonance imaging (MRI) scans of 1053 MDD patients (age range 13-79 years) from 15 cohorts within the ENIGMA MDD Working Group. Insomnia severity was measured by summing the insomnia items of the Hamilton Depression Rating Scale (HDRS). Symptom specificity was evaluated with correlates of overall depression severity. Disease specificity was evaluated in two independent samples comprising 2108 healthy controls, and in 260 clinical controls with bipolar disorder. Results showed that MDD patients with more severe insomnia had a smaller cortical surface area, mostly driven by the right insula, left inferior frontal gyrus pars triangularis, left frontal pole, right superior parietal cortex, right medial orbitofrontal cortex, and right supramarginal gyrus. Associations were specific for insomnia severity, and were not found for overall depression severity. Associations were also specific to MDD; healthy controls and clinical controls showed differential insomnia severity association profiles. The findings indicate that MDD patients with more severe insomnia show smaller surfaces in several frontoparietal cortical areas. While explained variance remains small, symptom-specific associations could bring us closer to clues on underlying biological phenomena of MDD.
Published: 2020

37. Biological sex classification with structural MRI data shows increased misclassification in transgender women

Author: Flint, C, Foerster, K, Koser, SA, Konrad, C, Zwitserlood, P, Berger, K, Hermesdorf, M, Kircher, T, Krug, A, Baune, BT, Dohm, K, Redlich, R, Opel, N, Arolt, V, Hahn, T, Jiang, X, Dannlowski, U, Grotegerd, D, Nenadic, I, Flint, C, Foerster, K, Koser, SA, Konrad, C, Zwitserlood, P, Berger, K, Hermesdorf, M, Kircher, T, Krug, A, Baune, BT, Dohm, K, Redlich, R, Opel, N, Arolt, V, Hahn, T, Jiang, X, Dannlowski, U, Grotegerd, D, and Nenadic, I
Abstract: Transgender individuals (TIs) show brain-structural alterations that differ from their biological sex as well as their perceived gender. To substantiate evidence that the brain structure of TIs differs from male and female, we use a combined multivariate and univariate approach. Gray matter segments resulting from voxel-based morphometry preprocessing of N = 1753 cisgender (CG) healthy participants were used to train (N = 1402) and validate (20% holdout N = 351) a support-vector machine classifying the biological sex. As a second validation, we classified N = 1104 patients with depression. A third validation was performed using the matched CG sample of the transgender women (TW) application sample. Subsequently, the classifier was applied to N = 26 TW. Finally, we compared brain volumes of CG-men, women, and TW-pre/post treatment cross-sex hormone treatment (CHT) in a univariate analysis controlling for sexual orientation, age, and total brain volume. The application of our biological sex classifier to the transgender sample resulted in a significantly lower true positive rate (TPR-male = 56.0%). The TPR did not differ between CG-individuals with (TPR-male = 86.9%) and without depression (TPR-male = 88.5%). The univariate analysis of the transgender application-sample revealed that TW-pre/post treatment show brain-structural differences from CG-women and CG-men in the putamen and insula, as well as the whole-brain analysis. Our results support the hypothesis that brain structure in TW differs from brain structure of their biological sex (male) as well as their perceived gender (female). This finding substantiates evidence that TIs show specific brain-structural alterations leading to a different pattern of brain structure than CG-individuals.
Published: 2020

38. Sleep duration is associated with white matter microstructure and cognitive performance in healthy adults

Author: Grumbach, P, Opel, N, Martin, S, Meinert, S, Leehr, EJ, Redlich, R, Enneking, V, Goltermann, J, Baune, BT, Dannlowski, U, Repple, J, Grumbach, P, Opel, N, Martin, S, Meinert, S, Leehr, EJ, Redlich, R, Enneking, V, Goltermann, J, Baune, BT, Dannlowski, U, and Repple, J
Abstract: Reduced sleep duration and sleep deprivation have been associated with cognitive impairment as well as decreased white matter integrity as reported by experimental studies. However, it is largely unknown whether differences in sleep duration and sleep quality might affect microstructural white matter and cognition. Therefore, the present study aims to examine the cross-sectional relationship between sleep duration, sleep quality, and cognitive performance in a naturalistic study design, by focusing on the association with white matter integrity in a large sample of healthy, young adults. To address this, 1,065 participants, taken from the publicly available sample of the Human Connectome Project, underwent diffusion tensor imaging. Moreover, broad cognitive performance measures (NIH Cognition Toolbox) and sleep duration and quality (Pittsburgh Sleep Quality Index) were assessed. The results revealed a significant positive association between sleep duration and overall cognitive performance. Shorter sleep duration significantly correlated with fractional anisotropy (FA) reductions in the left superior longitudinal fasciculus (SLF). In turn, FA in this tract was related to measures of cognitive performance and was shown to significantly mediate the association of sleep duration and cognition. For cognition only, associations shift to a negative association of sleep duration and cognition for participants sleeping more than 8 hr a day. Investigations into subjective sleep quality showed no such associations. The present study showed that real-world differences in sleep duration, but not subjective sleep quality are related to cognitive performance measures and white matter integrity in the SLF in healthy, young adults.
Published: 2020

39. P.222 Brain functional correlates of emotional face processing in body dysmorphic disorder

Author: Borgers, T., primary, Enneking, V., additional, Dannlowski, U., additional, and Redlich, R., additional
Published: 2020
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40. P.242 Transdiagnostic review of brain imaging results: depression, anxiety disorders and their co-occurrence

Author: Sindermann, L., primary, Redlich, R., additional, Böhnlein, J., additional, Dannlowski, U., additional, and Leehr, E., additional
Published: 2020
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41. The influence of recent stressful life events on brain structure

Author: Ringwald, K, additional, Meller, T, additional, Brosch, K, additional, Schmitt, S, additional, Stein, F, additional, Pfarr, J, additional, Waltemate, L, additional, Meinert, S, additional, Lemke, H, additional, Fingas, S, additional, Redlich, R, additional, Dannlowski, U, additional, Nenadic, I, additional, and Kirch, T, additional
Published: 2020
Full Text: View/download PDF

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

Author: Lemke, H., primary, Förster, K., additional, Waltemate, L., additional, Meinert, S., additional, Stein, F., additional, Brosch, K., additional, Fingas, S., additional, Romankiewicz, L., additional, Grotegerd, D., additional, Redlich, R., additional, Koch, K., additional, Leehr, E., additional, Böhnlein, J., additional, Goltermann, J., additional, Winter, N., additional, Enneking, V., additional, Opel, N., additional, Emden, D., additional, Repple, J., additional, Leenings, R., additional, Kaehler, C., additional, Hahn, T., additional, Schmitt, S., additional, Meller, T., additional, Jansen, A., additional, Krug, A., additional, Kircher, T., additional, Nenadic, I., additional, Baune, B.T., additional, and Dannlowski, U., additional
Published: 2020
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43. 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

44. 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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45. Electroconvulsive therapy modulates gray matter increase in a hub of an affect processing network

Author: Camilleri, Julia, Hoffstaedter, Felix, Eickhoff, Simon, Nickl-Jockschat, Thomas, Zavorotny, M., Wolf, C., Thomann, P., Redlich, R., Dannlowski, U., Groezinger, M., Demirakca, T., and Sartorius, A.
Published: 2018

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

Author: Hibar, D.P., Westlye, L.T., Doan, N.T., Jahanshad, N., Cheung, J.W., Ching, C.R., Versace, A., Bilderbeck, A.C., Uhlmann, A., Mwangi, B., Kramer, B., Overs, B., Hartberg, C.B., Abe, C., Dima, D., Grotegerd, D., Sprooten, E., Boen, E., Jimenez, E., Howells, F.M., Delvecchio, G., Temmingh, H., Starke, J., Almeida, J.R. de, Goikolea, J.M., Houenou, J., Beard, L.M., Rauer, L., Abramovic, L., Bonnin, M., Ponteduro, M.F., Keil, M., Rive, M.M., Yao, N., Yalin, N., Najt, P., Rosa, P.G., Redlich, R., Trost, S., Hagenaars, S., Fears, S.C., Alonso-Lana, S., Erp, T.G. van, Nickson, T., Chaim-Avancini, T.M., Meier, T.B., Elvsashagen, T., Haukvik, U.K., Lee, W.H., Schene, A.H., Lloyd, A.J., Young, A.H., Nugent, A., Dale, A.M., Pfennig, A., McIntosh, A.M., Lafer, B., Baune, B.T., Ekman, C.J., Zarate, C.A., Bearden, C.E., Henry, C., Simhandl, C., McDonald, C., Bourne, C., Stein, D.J., Wolf, D.H., Cannon, D.M., Glahn, D.C., Veltman, D.J., Pomarol-Clotet, E., Vieta, E., Canales-Rodriguez, E.J., Nery, F.G., Duran, F.L.S., Busatto, G.F., Roberts, G., Pearlson, G.D., Goodwin, G.M., Kugel, H., Whalley, H.C., Ruhe, H.G., Soares, J.C., Fullerton, J.M., Rybakowski, J.K., Savitz, J., Chaim, K.T., Fatjo-Vilas, M., Soeiro-de-Souza, M.G., Boks, M.P., Zanetti, M.V., Otaduy, M.C.G., Schaufelberger, M.S., Alda, M., Ingvar, M., Phillips, M.L., Kempton, M.J., Bauer, M., Landen, M., Lawrence, N.S., Hibar, D.P., Westlye, L.T., Doan, N.T., Jahanshad, N., Cheung, J.W., Ching, C.R., Versace, A., Bilderbeck, A.C., Uhlmann, A., Mwangi, B., Kramer, B., Overs, B., Hartberg, C.B., Abe, C., Dima, D., Grotegerd, D., Sprooten, E., Boen, E., Jimenez, E., Howells, F.M., Delvecchio, G., Temmingh, H., Starke, J., Almeida, J.R. de, Goikolea, J.M., Houenou, J., Beard, L.M., Rauer, L., Abramovic, L., Bonnin, M., Ponteduro, M.F., Keil, M., Rive, M.M., Yao, N., Yalin, N., Najt, P., Rosa, P.G., Redlich, R., Trost, S., Hagenaars, S., Fears, S.C., Alonso-Lana, S., Erp, T.G. van, Nickson, T., Chaim-Avancini, T.M., Meier, T.B., Elvsashagen, T., Haukvik, U.K., Lee, W.H., Schene, A.H., Lloyd, A.J., Young, A.H., Nugent, A., Dale, A.M., Pfennig, A., McIntosh, A.M., Lafer, B., Baune, B.T., Ekman, C.J., Zarate, C.A., Bearden, C.E., Henry, C., Simhandl, C., McDonald, C., Bourne, C., Stein, D.J., Wolf, D.H., Cannon, D.M., Glahn, D.C., Veltman, D.J., Pomarol-Clotet, E., Vieta, E., Canales-Rodriguez, E.J., Nery, F.G., Duran, F.L.S., Busatto, G.F., Roberts, G., Pearlson, G.D., Goodwin, G.M., Kugel, H., Whalley, H.C., Ruhe, H.G., Soares, J.C., Fullerton, J.M., Rybakowski, J.K., Savitz, J., Chaim, K.T., Fatjo-Vilas, M., Soeiro-de-Souza, M.G., Boks, M.P., Zanetti, M.V., Otaduy, M.C.G., Schaufelberger, M.S., Alda, M., Ingvar, M., Phillips, M.L., Kempton, M.J., Bauer, M., Landen, M., and Lawrence, N.S.
Abstract: Contains fulltext : 191289.pdf (publisher's version ) (Open Access), Despite decades of research, the pathophysiology of bipolar disorder (BD) is still not well understood. Structural brain differences have been associated with BD, but results from neuroimaging studies have been inconsistent. To address this, we performed the largest study to date of cortical gray matter thickness and surface area measures from brain magnetic resonance imaging scans of 6503 individuals including 1837 unrelated adults with BD and 2582 unrelated healthy controls for group differences while also examining the effects of commonly prescribed medications, age of illness onset, history of psychosis, mood state, age and sex differences on cortical regions. In BD, cortical gray matter was thinner in frontal, temporal and parietal regions of both brain hemispheres. BD had the strongest effects on left pars opercularis (Cohen's d=-0.293; P=1.71 x 10(-21)), left fusiform gyrus (d=-0.288; P=8.25 x 10(-21)) and left rostral middle frontal cortex (d=-0.276; P=2.99 x 10(-19)). Longer duration of illness (after accounting for age at the time of scanning) was associated with reduced cortical thickness in frontal, medial parietal and occipital regions. We found that several commonly prescribed medications, including lithium, antiepileptic and antipsychotic treatment showed significant associations with cortical thickness and surface area, even after accounting for patients who received multiple medications. We found evidence of reduced cortical surface area associated with a history of psychosis but no associations with mood state at the time of scanning. Our analysis revealed previously undetected associations and provides an extensive analysis of potential confounding variables in neuroimaging studies of BD.
Published: 2018

47. Volume of the Human Hippocampus and Clinical Response Following Electroconvulsive Therapy

Author: Oltedal, L., Narr, K.L., Abbott, C., Anand, A., Argyelan, M., Bartsch, H., Dannlowski, U., Dols, A., Eijndhoven, P.F. van, Emsell, L., Erchinger, V.J., Espinoza, R., Hahn, T., Hanson, L.G., Hellemann, G., Jorgensen, M.B., Kessler, U., Oudega, M.L., Paulson, O.B., Redlich, R., Sienaert, P., Stek, M.L., Tendolkar, I., Vandenbulcke, M., Oedegaard, K.J., Dale, A.M., Oltedal, L., Narr, K.L., Abbott, C., Anand, A., Argyelan, M., Bartsch, H., Dannlowski, U., Dols, A., Eijndhoven, P.F. van, Emsell, L., Erchinger, V.J., Espinoza, R., Hahn, T., Hanson, L.G., Hellemann, G., Jorgensen, M.B., Kessler, U., Oudega, M.L., Paulson, O.B., Redlich, R., Sienaert, P., Stek, M.L., Tendolkar, I., Vandenbulcke, M., Oedegaard, K.J., and Dale, A.M.
Abstract: Contains fulltext : 196725.pdf (publisher's version ) (Open Access), BACKGROUND: Hippocampal enlargements are commonly reported after electroconvulsive therapy (ECT). To clarify mechanisms, we examined if ECT-induced hippocampal volume change relates to dose (number of ECT sessions and electrode placement) and acts as a biomarker of clinical outcome. METHODS: Longitudinal neuroimaging and clinical data from 10 independent sites participating in the Global ECT-Magnetic Resonance Imaging Research Collaboration (GEMRIC) were obtained for mega-analysis. Hippocampal volumes were extracted from structural magnetic resonance images, acquired before and after patients (n = 281) experiencing a major depressive episode completed an ECT treatment series using right unilateral and bilateral stimulation. Untreated nondepressed control subjects (n = 95) were scanned twice. RESULTS: The linear component of hippocampal volume change was 0.28% (SE 0.08) per ECT session (p < .001). Volume change varied by electrode placement in the left hippocampus (bilateral, 3.3 +/- 2.2%, d = 1.5; right unilateral, 1.6 +/- 2.1%, d = 0.8; p < .0001) but not the right hippocampus (bilateral, 3.0 +/- 1.7%, d = 1.8; right unilateral, 2.7 +/- 2.0%, d = 1.4; p = .36). Volume change for electrode placement per ECT session varied similarly by hemisphere. Individuals with greater treatment-related volume increases had poorer outcomes (Montgomery-Asberg Depression Rating Scale change -1.0 [SE 0.35], per 1% volume increase, p = .005), although the effects were not significant after controlling for ECT number (slope -0.69 [SE 0.38], p = .069). CONCLUSIONS: The number of ECT sessions and electrode placement impacts the extent and laterality of hippocampal enlargement, but volume change is not positively associated with clinical outcome. The results suggest that the high efficacy of ECT is not explained by hippocampal enlargement, which alone might not serve as a viable biomarker for treatment outcome.
Published: 2018

48. 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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49. The Global ECT-MRI Research Collaboration (GEMRIC): Establishing a multi-site investigation of the neural mechanisms underlying response to electroconvulsive therapy

Author: Oltedal, L., Bartsch, H., Sorhaug, O.J., Kessler, U., Abbott, C., Dols, A., Stek, M.L., Ersland, L., Emsell, L., Eijndhoven, P.F. van, Argyelan, M., Tendolkar, I., Nordanskog, P., Hamilton, P., Jorgensen, M.B., Sommer, I.E., Heringa, S.M., Draganski, B., Redlich, R., Dannlowski, U., Kugel, H., Bouckaert, F., Sienaert, P., Anand, A., Espinoza, R., Narr, K.L., Holland, D., Dale, A.M., Oedegaard, K.J., Oltedal, L., Bartsch, H., Sorhaug, O.J., Kessler, U., Abbott, C., Dols, A., Stek, M.L., Ersland, L., Emsell, L., Eijndhoven, P.F. van, Argyelan, M., Tendolkar, I., Nordanskog, P., Hamilton, P., Jorgensen, M.B., Sommer, I.E., Heringa, S.M., Draganski, B., Redlich, R., Dannlowski, U., Kugel, H., Bouckaert, F., Sienaert, P., Anand, A., Espinoza, R., Narr, K.L., Holland, D., Dale, A.M., and Oedegaard, K.J.
Abstract: Contains fulltext : 173051.pdf (publisher's version ) (Open Access), Major depression, currently the world's primary cause of disability, leads to profound personal suffering and increased risk of suicide. Unfortunately, the success of antidepressant treatment varies amongst individuals and can take weeks to months in those who respond. Electroconvulsive therapy (ECT), generally prescribed for the most severely depressed and when standard treatments fail, produces a more rapid response and remains the most effective intervention for severe depression. Exploring the neurobiological effects of ECT is thus an ideal approach to better understand the mechanisms of successful therapeutic response. Though several recent neuroimaging studies show structural and functional changes associated with ECT, not all brain changes associate with clinical outcome. Larger studies that can address individual differences in clinical and treatment parameters may better target biological factors relating to or predictive of ECT-related therapeutic response. We have thus formed the Global ECT-MRI Research Collaboration (GEMRIC) that aims to combine longitudinal neuroimaging as well as clinical, behavioral and other physiological data across multiple independent sites. Here, we summarize the ECT sample characteristics from currently participating sites, and the common data-repository and standardized image analysis pipeline developed for this initiative. This includes data harmonization across sites and MRI platforms, and a method for obtaining unbiased estimates of structural change based on longitudinal measurements with serial MRI scans. The optimized analysis pipeline, together with the large and heterogeneous combined GEMRIC dataset, will provide new opportunities to elucidate the mechanisms of ECT response and the factors mediating and predictive of clinical outcomes, which may ultimately lead to more effective personalized treatment approaches.
Published: 2017

50. 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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