303 results on '"Opel, N."'
Search Results
2. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group
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Schmaal, L, Hibar, DP, Sämann, PG, Hall, GB, Baune, BT, Jahanshad, N, Cheung, JW, van Erp, TGM, Bos, D, Ikram, MA, Vernooij, MW, Niessen, WJ, Tiemeier, H, Hofman, A, Wittfeld, K, Grabe, HJ, Janowitz, D, Bülow, R, Selonke, M, Völzke, H, Grotegerd, D, Dannlowski, U, Arolt, V, Opel, N, Heindel, W, Kugel, H, Hoehn, D, Czisch, M, Couvy-Duchesne, B, Rentería, ME, Strike, LT, Wright, MJ, Mills, NT, de Zubicaray, GI, McMahon, KL, Medland, SE, Martin, NG, Gillespie, NA, Goya-Maldonado, R, Gruber, O, Krämer, B, Hatton, SN, Lagopoulos, J, Hickie, IB, Frodl, T, Carballedo, A, Frey, EM, van Velzen, LS, Penninx, BWJH, van Tol, M-J, van der Wee, NJ, Davey, CG, Harrison, BJ, Mwangi, B, Cao, B, Soares, JC, Veer, IM, Walter, H, Schoepf, D, Zurowski, B, Konrad, C, Schramm, E, Normann, C, Schnell, K, Sacchet, MD, Gotlib, IH, MacQueen, GM, Godlewska, BR, Nickson, T, McIntosh, AM, Papmeyer, M, Whalley, HC, Hall, J, Sussmann, JE, Li, M, Walter, M, Aftanas, L, Brack, I, Bokhan, NA, Thompson, PM, and Veltman, DJ
- Subjects
Biological Psychology ,Biomedical and Clinical Sciences ,Clinical Sciences ,Psychology ,Major Depressive Disorder ,Serious Mental Illness ,Neurosciences ,Biomedical Imaging ,Depression ,Basic Behavioral and Social Science ,Mental Health ,Brain Disorders ,Clinical Research ,Pediatric ,Behavioral and Social Science ,2.3 Psychological ,social and economic factors ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Mental health ,Adolescent ,Adult ,Brain ,Cerebral Cortex ,Depressive Disorder ,Major ,Female ,Frontal Lobe ,Gray Matter ,Gyrus Cinguli ,Humans ,Magnetic Resonance Imaging ,Male ,Neuroimaging ,Prefrontal Cortex ,Temporal Lobe ,Biological Sciences ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Psychiatry ,Clinical sciences ,Biological psychology ,Clinical and health psychology - Abstract
The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.
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- 2017
3. Performance Analysis of Vehicle to Infrastructure Network
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Mbanzabugabo, Opel N., primary, Kabiri, Charles, additional, Jayavel, Kayalvizhi, additional, and Sibomana, Louis, additional
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- 2023
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4. Using cross-validation for accurate estimation of effect size in mass-univariate VBM analysis
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Goltermann, J., primary, Winter, N.R., additional, Gruber, M., additional, Lukas, F., additional, Richter, M., additional, Grotegerd, D., additional, Dohm, K., additional, Meinert, S., additional, Berger, K., additional, Jansen, A., additional, Nenadić, I., additional, Kircher, T., additional, and Opel, N., additional
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- 2023
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5. Associations between SARS-CoV-2 Infection, burden of the pandemic and mental health in the German population-based cohort for digital health research
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Steinmann, L.A., primary, Opel, N., additional, Massag, J., additional, Diexer, S., additional, Klee, B., additional, Costa, D., additional, Gottschick, C., additional, Broda, A., additional, Purschke, O., additional, Binder, M., additional, Sedding, D., additional, Frese, T., additional, Girndt, M., additional, Hoell, J., additional, Moor, I., additional, Rosendahl, J., additional, Gekle, M., additional, and Mikolajczyk, R., additional
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- 2023
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6. Cortical thickness of the posterior cingulate cortex is associated with the ketamine-induced altered sense of self
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Danyeli, L., primary, Sen, Z., additional, Colic, L., additional, Opel, N., additional, Refisch, A., additional, Blekic, N., additional, Macharadze, T., additional, Kretzschmar, M., additional, Munk, M., additional, Gaser, C., additional, Speck, O., additional, Walter, M., additional, and Li, M., additional
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- 2023
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7. The impact of cognitive reserve on cognition, connectome pathology, and disease course in depression
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Gruber, M., primary, Klein, H., additional, Mauritz, M., additional, De Lange, S.C., additional, Grumbach, P., additional, Goltermann, J., additional, Winter, N.R., additional, Thiel, K., additional, Winter, A., additional, Flinkenflügel, K., additional, Borgers, T., additional, Enneking, V., additional, Klug, M., additional, Stein, F., additional, Brosch, K., additional, Usemann, P., additional, Thomas-Odenthal, F., additional, Wroblewski, A., additional, Steinsträter, O., additional, Pfarr, J.K., additional, Evermann, U., additional, Meinert, S., additional, Grotegerd, D., additional, Opel, N., additional, Hahn, T., additional, Leehr, E.J., additional, Bauer, J., additional, Reif, A., additional, Jansen, A., additional, Krug, A., additional, Nenadić, I., additional, Kircher, T., additional, Van den Heuvel, M.P., additional, Dannlowski, U., additional, and Repple, J., additional
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- 2023
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8. Post-treatment narcissism predicts higher rates of depression recurrence one year after inpatient treatment in a real-world clinical sample
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Richter, M., primary, Bratek, R., additional, and Opel, N., additional
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- 2023
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9. Elevated CYP2C19 expression is associated with depressive symptoms and hippocampal homeostasis impairment
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Jukić, M M, Opel, N, Ström, J, Carrillo-Roa, T, Miksys, S, Novalen, M, Renblom, A, Sim, S C, Peñas-Lledó, E M, Courtet, P, Llerena, A, Baune, B T, de Quervain, D J, Papassotiropoulos, A, Tyndale, R F, Binder, E B, Dannlowski, U, and Ingelman-Sundberg, M
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- 2017
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10. Prefrontal gray matter volume mediates genetic risks for obesity
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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
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- 2017
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11. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group
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Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, Michael, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, Michael, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M
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- 2022
12. In vivo hippocampal subfield volumes in bipolar disorder—A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group
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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
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- 2022
13. Association Between Genetic Risk for Type 2 Diabetes and Structural Brain Connectivity in Major Depressive Disorder.
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Repple, J, König, 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, Mehler, DMA, Holstein, V, Gruber, M, Nenadic, I, Krug, A, Brosch, K, Schmitt, S, Stein, F, Meller, T, Jansen, A, Steinsträter, O, Amare, AT, Kircher, T, Baune, BT, van den Heuvel, MP, Dannlowski, U, Repple, J, König, 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, Mehler, DMA, Holstein, V, Gruber, M, Nenadic, I, Krug, A, Brosch, K, Schmitt, S, Stein, F, Meller, T, Jansen, A, Steinsträter, 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.
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- 2022
14. Genetic variants associated with longitudinal changes in brain structure across the lifespan
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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.
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- 2022
15. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics through Meta-Analysis Bipolar Disorder Working Group
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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.
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- 2022
16. Local molecular and global connectomic contributions to cross-disorder cortical abnormalities.
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Hansen, JY, Shafiei, G, Vogel, JW, Smart, K, Bearden, CE, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, McDonald, CR, Sisodiya, SM, Schmaal, L, Veltman, DJ, van den Heuvel, OA, Stein, DJ, van Erp, TGM, Ching, CRK, Andreassen, OA, Hajek, T, Opel, N, Modinos, G, Aleman, A, van der Werf, Y, Jahanshad, N, Thomopoulos, SI, Thompson, PM, Carson, RE, Dagher, A, Misic, B, Hansen, JY, Shafiei, G, Vogel, JW, Smart, K, Bearden, CE, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, McDonald, CR, Sisodiya, SM, Schmaal, L, Veltman, DJ, van den Heuvel, OA, Stein, DJ, van Erp, TGM, Ching, CRK, Andreassen, OA, Hajek, T, Opel, N, Modinos, G, Aleman, A, van der Werf, Y, Jahanshad, N, Thomopoulos, SI, Thompson, PM, Carson, RE, Dagher, A, and Misic, B
- Abstract
Numerous brain disorders demonstrate structural brain abnormalities, which are thought to arise from molecular perturbations or connectome miswiring. The unique and shared contributions of these molecular and connectomic vulnerabilities to brain disorders remain unknown, and has yet to be studied in a single multi-disorder framework. Using MRI morphometry from the ENIGMA consortium, we construct maps of cortical abnormalities for thirteen neurodevelopmental, neurological, and psychiatric disorders from N = 21,000 participants and N = 26,000 controls, collected using a harmonised processing protocol. We systematically compare cortical maps to multiple micro-architectural measures, including gene expression, neurotransmitter density, metabolism, and myelination (molecular vulnerability), as well as global connectomic measures including number of connections, centrality, and connection diversity (connectomic vulnerability). We find a relationship between molecular vulnerability and white-matter architecture that drives cortical disorder profiles. Local attributes, particularly neurotransmitter receptor profiles, constitute the best predictors of both disorder-specific cortical morphology and cross-disorder similarity. Finally, we find that cross-disorder abnormalities are consistently subtended by a small subset of network epicentres in bilateral sensory-motor, inferior temporal lobe, precuneus, and superior parietal cortex. Collectively, our results highlight how local molecular attributes and global connectivity jointly shape cross-disorder cortical abnormalities.
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- 2022
17. Correction to: Biological sex classification with structural MRI data shows increased misclassification in transgender women.
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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
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- 2022
18. The Role of Educational Attainment and Brain Morphology in Major Depressive Disorder: Findings From the ENIGMA Major Depressive Disorder Consortium
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Whittle, S, Rakesh, D, Schmaal, L, Veltman, DJ, Thompson, PM, Singh, A, Gonul, AS, Aleman, A, Demir, AU, Krug, A, Mwangi, B, Kramer, B, Baune, BT, Stein, DJ, Grotegerd, D, Pomarol-Clotet, E, Rodriguez-Cano, E, Melloni, E, Benedetti, F, Stein, F, Grabe, HJ, Volzke, H, Gotlib, IH, Nenadic, I, Soares, JC, Repple, J, Sim, K, Brosch, K, Wittfeld, K, Berger, K, Hermesdorf, M, Portella, MJ, Sacchet, MD, Wu, M-J, Opel, N, Groenewold, NA, Gruber, O, Fuentes-Claramonte, P, Salvador, R, Goya-Maldonado, R, Sarro, S, Poletti, S, Meinert, SL, Kircher, T, Dannlowski, U, Pozzi, E, Whittle, S, Rakesh, D, Schmaal, L, Veltman, DJ, Thompson, PM, Singh, A, Gonul, AS, Aleman, A, Demir, AU, Krug, A, Mwangi, B, Kramer, B, Baune, BT, Stein, DJ, Grotegerd, D, Pomarol-Clotet, E, Rodriguez-Cano, E, Melloni, E, Benedetti, F, Stein, F, Grabe, HJ, Volzke, H, Gotlib, IH, Nenadic, I, Soares, JC, Repple, J, Sim, K, Brosch, K, Wittfeld, K, Berger, K, Hermesdorf, M, Portella, MJ, Sacchet, MD, Wu, M-J, Opel, N, Groenewold, NA, Gruber, O, Fuentes-Claramonte, P, Salvador, R, Goya-Maldonado, R, Sarro, S, Poletti, S, Meinert, SL, Kircher, T, Dannlowski, U, and Pozzi, E
- Abstract
Brain structural abnormalities and low educational attainment are consistently associated with major depressive disorder (MDD), yet there has been little research investigating the complex interaction of these factors. Brain structural alterations may represent a vulnerability or differential susceptibility marker, and in the context of low educational attainment, predict MDD. We tested this moderation model in a large multisite sample of 1958 adults with MDD and 2921 controls (aged 18 to 86) from the ENIGMA MDD working group. Using generalized linear mixed models and within-sample split-half replication, we tested whether brain structure interacted with educational attainment to predict MDD status. Analyses revealed that cortical thickness in a number of occipital, parietal, and frontal regions significantly interacted with education to predict MDD. For the majority of regions, models suggested a differential susceptibility effect, whereby thicker cortex was more likely to predict MDD in individuals with low educational attainment, but less likely to predict MDD in individuals with high educational attainment. Findings suggest that greater thickness of brain regions subserving visuomotor and social-cognitive functions confers susceptibility to MDD, dependent on level of educational attainment. Longitudinal work, however, is ultimately needed to establish whether cortical thickness represents a preexisting susceptibility marker. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
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- 2022
19. Effects of electroconvulsive therapy on amygdala function in major depression – a longitudinal functional magnetic resonance imaging study
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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.
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- 2017
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20. TNF receptors 1 and 2 exert distinct region‐specific effects on striatal and hippocampal grey matter volumes (VBM) in healthy adults
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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.
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- 2017
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21. Multimodal imaging of a tescalcin (TESC)-regulating polymorphism (rs7294919)-specific effects on hippocampal gray matter structure
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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
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- 2015
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22. Gray matter correlates of childhood maltreatment: investigation of robustness and replicability in a multi-cohort voxel-based analysis of 2952 adults
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Goltermann, J., Winter, N., Waltemate, L., Schrammen, E., Meinert, S., Grotegerd, D., Dohm, K., Thiel, K., Lemke, H., Breuer, F., Gruber, M., Repple, J., Teismann, H., Hermesdorf, M., Berger, K., Jansen, A., Nenadić, I., Kircher, T., Opel, N., and Dannlowski, U.
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- 2022
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23. Self-reported childhood emotional neglect and inhibitory neurometabolite levels in the pregenual anterior cingulate cortex in humans
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Herrmann, L., Ade, J., Kühnel, A., Widmann, A., Demenescu, L.R., Li, M., Opel, N., Speck, O., Walter, M., and Colic, L.
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- 2022
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24. Cognitive performance and brain structural connectome alterations in major depressive disorder
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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.
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- 2022
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25. P.0677 Fronto-limbic functional connectivity associated with childhood maltreatment in adults with depression
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Goltermann, J., primary, Winter, N., additional, Meinert, S., additional, Sindermann, L., additional, Lemke, H., additional, Leehr, E.J., additional, Grotegerd, D., additional, Winter, A., additional, Thiel, K., additional, Teckentrup, V., additional, Opel, N., additional, Hahn, T., additional, and Dannlowski, U., additional
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- 2021
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26. Differing brain structural correlates of familial and environmental risk for major depressive disorder revealed by a combined VBM/pattern recognition approach
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Opel, N., Zwanzger, P., Redlich, R., Grotegerd, D., Dohm, K., Arolt, V., Heindel, W., Kugel, H., and Dannlowski, U.
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- 2016
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27. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group
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Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, J-K, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, J-K, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M
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- 2021
28. Genome-wide interaction study with major depression identifies novel variants associated with cognitive function
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Thalamuthu, A, Mills, NT, Berger, K, Minnerup, H, Grotegerd, D, Dannlowski, U, Meinert, S, Opel, N, Repple, J, Gruber, M, Stein, F, Brosch, K, Meller, T, Pfarr, J-K, Forstner, AJ, Hoffmann, P, Nothen, MM, Witt, S, Rietschel, M, Kircher, T, Adams, M, McIntosh, AM, Porteous, DJ, Deary, IJ, Hayward, C, Campbell, A, Grabe, HJ, Teumer, A, Homuth, G, Van der Auwera-Palitschka, S, Schubert, KO, Baune, BT, Thalamuthu, A, Mills, NT, Berger, K, Minnerup, H, Grotegerd, D, Dannlowski, U, Meinert, S, Opel, N, Repple, J, Gruber, M, Stein, F, Brosch, K, Meller, T, Pfarr, J-K, Forstner, AJ, Hoffmann, P, Nothen, MM, Witt, S, Rietschel, M, Kircher, T, Adams, M, McIntosh, AM, Porteous, DJ, Deary, IJ, Hayward, C, Campbell, A, Grabe, HJ, Teumer, A, Homuth, G, Van der Auwera-Palitschka, S, Schubert, KO, and Baune, BT
- Abstract
Major Depressive Disorder (MDD) often is associated with significant cognitive dysfunction. We conducted a meta-analysis of genome-wide interaction of MDD and cognitive function using data from four large European cohorts in a total of 3510 MDD cases and 6057 controls. In addition, we conducted analyses using polygenic risk scores (PRS) based on data from the Psychiatric Genomics Consortium (PGC) on the traits of MDD, Bipolar disorder (BD), Schizophrenia (SCZ), and mood instability (MIN). Functional exploration contained gene expression analyses and Ingenuity Pathway Analysis (IPA®). We identified a set of significantly interacting single nucleotide polymorphisms (SNPs) between MDD and the genome-wide association study (GWAS) of cognitive domains of executive function, processing speed, and global cognition. Several of these SNPs are located in genes expressed in brain, with important roles such as neuronal development (REST), oligodendrocyte maturation (TNFRSF21), and myelination (ARFGEF1). IPA® identified a set of core genes from our dataset that mapped to a wide range of canonical pathways and biological functions (MPO, FOXO1, PDE3A, TSLP, NLRP9, ADAMTS5, ROBO1, REST). Furthermore, IPA® identified upstream regulator molecules and causal networks impacting on the expression of dataset genes, providing a genetic basis for further clinical exploration (vitamin D receptor, beta-estradiol, tadalafil). PRS of MIN and meta-PRS of MDD, MIN and SCZ were significantly associated with all cognitive domains. Our results suggest several genes involved in physiological processes for the development and maintenance of cognition in MDD, as well as potential novel therapeutic agents that could be explored in patients with MDD associated cognitive dysfunction.
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- 2021
29. Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts
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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.
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- 2021
30. A genome-wide association study of the longitudinal course of executive functions
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Wendel, B, Papiol, S, Andlauer, TFM, Zimmermann, J, Wiltfang, J, Spitzer, C, Senner, F, Schulte, EC, Schmauss, M, Schaupp, SK, Repple, J, Reininghaus, E, Reimer, J, Reich-Erkelenz, D, Opel, N, Meinert, S, Konrad, C, Kloehn-Saghatolislam, F, Kircher, T, Kalman, JL, Juckel, G, Jansen, A, Jaeger, M, Heilbronner, M, von Hagen, M, Gade, K, Figge, C, Fallgatter, AJ, Dietrich, DE, Dannlowski, U, Comes, AL, Budde, M, Baune, BT, Arolt, V, Anghelescu, I-G, Anderson-Schmidt, H, Adorjan, K, Falkai, P, Schulze, TG, Bickeboeller, H, Heilbronner, U, Wendel, B, Papiol, S, Andlauer, TFM, Zimmermann, J, Wiltfang, J, Spitzer, C, Senner, F, Schulte, EC, Schmauss, M, Schaupp, SK, Repple, J, Reininghaus, E, Reimer, J, Reich-Erkelenz, D, Opel, N, Meinert, S, Konrad, C, Kloehn-Saghatolislam, F, Kircher, T, Kalman, JL, Juckel, G, Jansen, A, Jaeger, M, Heilbronner, M, von Hagen, M, Gade, K, Figge, C, Fallgatter, AJ, Dietrich, DE, Dannlowski, U, Comes, AL, Budde, M, Baune, BT, Arolt, V, Anghelescu, I-G, Anderson-Schmidt, H, Adorjan, K, Falkai, P, Schulze, TG, Bickeboeller, H, and Heilbronner, U
- Abstract
Executive functions are metacognitive capabilities that control and coordinate mental processes. In the transdiagnostic PsyCourse Study, comprising patients of the affective-to-psychotic spectrum and controls, we investigated the genetic basis of the time course of two core executive subfunctions: set-shifting (Trail Making Test, part B (TMT-B)) and updating (Verbal Digit Span backwards) in 1338 genotyped individuals. Time course was assessed with four measurement points, each 6 months apart. Compared to the initial assessment, executive performance improved across diagnostic groups. We performed a genome-wide association study to identify single nucleotide polymorphisms (SNPs) associated with performance change over time by testing for SNP-by-time interactions using linear mixed models. We identified nine genome-wide significant SNPs for TMT-B in strong linkage disequilibrium with each other on chromosome 5. These were associated with decreased performance on the continuous TMT-B score across time. Variant rs150547358 had the lowest P value = 7.2 × 10-10 with effect estimate beta = 1.16 (95% c.i.: 1.11, 1.22). Implementing data of the FOR2107 consortium (1795 individuals), we replicated these findings for the SNP rs150547358 (P value = 0.015), analyzing the difference of the two available measurement points two years apart. In the replication study, rs150547358 exhibited a similar effect estimate beta = 0.85 (95% c.i.: 0.74, 0.97). Our study demonstrates that longitudinally measured phenotypes have the potential to unmask novel associations, adding time as a dimension to the effects of genomics.
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- 2021
31. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders (May, 2020, 10.1038/s41380-020-0774-9)
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Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U
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- 2021
32. Systematic misestimation of machine learning performance in neuroimaging studies of depression
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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.
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- 2021
33. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders
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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
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- 2021
34. Design and Implementation of an Informatics Infrastructure for Standardized Data Acquisition, Transfer, Storage, and Export in Psychiatric Clinical Routine: Feasibility Study
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Blitz, R, Storck, M, Baune, BT, Dugas, M, Opel, N, Blitz, R, Storck, M, Baune, BT, Dugas, M, and Opel, N
- Abstract
BACKGROUND: Empirically driven personalized diagnostic applications and treatment stratification is widely perceived as a major hallmark in psychiatry. However, databased personalized decision making requires standardized data acquisition and data access, which are currently absent in psychiatric clinical routine. OBJECTIVE: Here, we describe the informatics infrastructure implemented at the psychiatric Münster University Hospital, which allows standardized acquisition, transfer, storage, and export of clinical data for future real-time predictive modelling in psychiatric routine. METHODS: We designed and implemented a technical architecture that includes an extension of the electronic health record (EHR) via scalable standardized data collection and data transfer between EHRs and research databases, thus allowing the pooling of EHRs and research data in a unified database and technical solutions for the visual presentation of collected data and analyses results in the EHR. The Single-source Metadata ARchitecture Transformation (SMA:T) was used as the software architecture. SMA:T is an extension of the EHR system and uses module-driven engineering to generate standardized applications and interfaces. The operational data model was used as the standard. Standardized data were entered on iPads via the Mobile Patient Survey (MoPat) and the web application Mopat@home, and the standardized transmission, processing, display, and export of data were realized via SMA:T. RESULTS: The technical feasibility of the informatics infrastructure was demonstrated in the course of this study. We created 19 standardized documentation forms with 241 items. For 317 patients, 6451 instances were automatically transferred to the EHR system without errors. Moreover, 96,323 instances were automatically transferred from the EHR system to the research database for further analyses. CONCLUSIONS: In this study, we present the successful implementation of the informatics infrastructure enabling
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- 2021
35. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders
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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
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- 2021
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36. P.305 Inferior frontal gyrus activity as a possible neural marker of depression with comorbid anxiety compared to depression
- Author
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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
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- 2021
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- View/download PDF
37. Using structural MRI to identify bipolar disorders – 13 site machine learning study in 3020 individuals from the ENIGMA Bipolar Disorders Working Group
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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.
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- 2020
38. The genetic architecture of the human cerebral cortex
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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
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- 2020
39. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
- Author
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Thompson, P.M. (Paul), Jahanshad, N. (Neda), Ching, C.R.K. (Christopher), Salminen, L.E. (Lauren E.), Thomopoulos, S.I. (Sophia I.), Bright, J. (Joanna), Baune, B.T., Bertolín, S. (Sara), Bralten, L.B.C. (Linda), Bruin, W.B. (Willem B.), Bülow, R. (Robin), Chen, J. (Jian), Chye, Y. (Yann), Dannlowski, U. (Udo), de Kovel, C.G.F. (Carolien G F), Donohoe, D.J. (Dennis), Eyler, L.T. (Lisa T.), Faraone, S.V. (Stephen), Favre, P. (Pauline), Filippi, C.A. (Courtney A.), Frodl, T. (Thomas), Garijo, D. (Daniel), Gil, Y. (Yolanda), Grabe, H.J. (Hans Jörgen), Grasby, K.L. (Katrina L.), Hajek, T. (Tomas), Han, L.K.M. (Laura K M), Hatton, W., Hilbert, K. (Kevin), Ho, T.C. (Tiffany C.), Holleran, L. (Laurena), Homuth, G. (Georg), Hosten, N. (Norbert), Houenou, J. (Josselin), Ivanov, I. (Iliyan), Jia, T. (Tianye), Kelly, S. (Sinead), Klein, M. (Marieke), Kwon, J.S. (Jun Soo), Laansma, M.A. (Max A.), Leerssen, J. (Jeanne), Lueken, U. (Ulrike), Nunes, A. (Abraham), Neill, J.O. (Joseph O'), Opel, N. (Nils), Piras, F. (Fabrizio), Piras, F. (Federica), Postema, M.C. (Merel C.), Pozzi, E. (Elena), Shatokhina, N. (Natalia), Soriano-Mas, C. (Carles), Spalletta, G. (Gianfranco), Sun, D. (Daqiang), Teumer, A. (Alexander), Tilot, A.K. (Amanda K.), Tozzi, L. (Leonardo), van der Merwe, C. (Celia), Someren, E.J.W. (Eus) van, van Wingen, G.A. (Guido A.), Völzke, H. (Henry), Walton, E. (Esther), Wang, L. (Lei), Winkler, A.M. (Anderson), Wittfeld, K. (Katharina), Wright, M.J. (Margaret), Yun, J.-Y. (Je-Yeon), Zhang, G. (Guohao), Zhang-James, Y. (Yanli), Adhikari, B.M. (Bhim M.), Agartz, I. (Ingrid), Aghajani, M. (Moji), Aleman, A. (André), Althoff, R.R. (Robert R.), Altmann, A. (A.), Andreassen, O.A. (Ole), Baron, D.A. (David A.), Bartnik-Olson, B.L. (Brenda L.), Marie Bas-Hoogendam, J. (Janna), Baskin-Sommers, A.R. (Arielle R.), Bearden, C.E. (Carrie), Berner, L.A. (Laura A.), Boedhoe, P.S.W. (Premika S W), Brouwer, R.M. (Rachel), Buitelaar, J.K. (Jan), Caeyenberghs, K. (Karen), Cecil, C.A.M. (Charlotte), Cohen, R.A. (Ronald A.), Cole, J.H. (James H.), Conrod, P. (Patricia), De Brito, S.A. (Stephane A.), de Zwarte, S.M.C. (Sonja M C), Dennis, E.L. (Emily L.), Desrivieres, S. (Sylvane), Dima, D. (Danai), Ehrlich, S.M. (Stefan), Esopenko, C. (Carrie), Fairchild, G. (Graeme), Fisher, S.E. (Simon), Fouche, J.-P. (Jean-Paul), Francks, C. (Clyde), Frangou, S. (Sophia), Franke, B. (Barbara), Garavan, H.P. (Hugh P.), Glahn, D.C. (David), Groenewold, N.A. (Nynke A.), Gurholt, T.P. (Tiril P.), Gutman, B.A. (Boris A.), Hahn, T. (Tim), Harding, I.H. (Ian H.), Hernaus, D. (Dennis), Hibar, D.P. (Derrek P.), Hillary, F.G. (Frank G.), Hoogman, M. (Martine), Hulshoff Pol, H.E. (Hilleke E.), Jalbrzikowski, M. (Maria), Karkashadze, G.A. (George A.), Klapwijk, E.T. (Eduard T.), Knickmeyer, R.C. (Rebecca C.), Kochunov, P. (Peter), Koerte, I.K. (Inga K.), Kong, X.-Z. (Xiang-Zhen), Liew, S.-L. (Sook-Lei), Lin, A.P. (Alexander P.), Logue, M.W. (Mark W.), Luders, E. (Eileen), Macciardi, F. (Fabio), Mackey, S. (Scott), Mayer, A.R. (Andrew R.), McDonald, C.R. (Carrie R.), McMahon, A.B. (Agnes B.), Medland, S.E. (Sarah), Modinos, G. (Gemma), Morey, R.A. (Rajendra A.), Mueller, S.C. (Sven C.), Mukherjee, P. (Pratik), Namazova-Baranova, L. (L.), Nir, T.M. (Talia M.), Olsen, A. (Alexander), Paschou, P. (Peristera), Pine, D.S. (Daniel S.), Pizzagalli, F. (Fabrizio), Rentería, M.E. (Miguel), Rohrer, J.D. (Jonathan D.), Sämann, P.G. (Philipp), Schmaal, L. (Lianne), Schumann, G. (Gunter), Shiroishi, M.S. (Mark S.), Sisodiya, S.M. (Sanjay), Smit, D.J.A. (Dirk J A), Sønderby, I.E. (Ida E.), Stein, D.J. (Dan J.), Stein, J.L., Tahmasian, M. (Masoud), Tate, D.F. (David F.), Turner, J. (Jessica), Heuvel, O.A. (Odile A.), Wee, N.J. (Nic) van der, van der Werf, Y.D. (Ysbrand), Erp, T.G.M. (Theo G.) van, van Haren, N.E.M. (Neeltje E M), van Rooij, D. (Daan), Van Velzen, L.S., Veer, I.M. (Ilya), Veltman, D.J. (Dick), Villalon-Reina, J.E. (Julio E.), Walter, H.J. (Henrik), Whelan, C.D. (Christopher), Wilde, E.A. (Elisabeth A.), Zarei, M. (Mojtaba), Zelman, V. (Vladimir), Thompson, P.M. (Paul), Jahanshad, N. (Neda), Ching, C.R.K. (Christopher), Salminen, L.E. (Lauren E.), Thomopoulos, S.I. (Sophia I.), Bright, J. (Joanna), Baune, B.T., Bertolín, S. (Sara), Bralten, L.B.C. (Linda), Bruin, W.B. (Willem B.), Bülow, R. (Robin), Chen, J. (Jian), Chye, Y. (Yann), Dannlowski, U. (Udo), de Kovel, C.G.F. (Carolien G F), Donohoe, D.J. (Dennis), Eyler, L.T. (Lisa T.), Faraone, S.V. (Stephen), Favre, P. (Pauline), Filippi, C.A. (Courtney A.), Frodl, T. (Thomas), Garijo, D. (Daniel), Gil, Y. (Yolanda), Grabe, H.J. (Hans Jörgen), Grasby, K.L. (Katrina L.), Hajek, T. (Tomas), Han, L.K.M. (Laura K M), Hatton, W., Hilbert, K. (Kevin), Ho, T.C. (Tiffany C.), Holleran, L. (Laurena), Homuth, G. (Georg), Hosten, N. (Norbert), Houenou, J. (Josselin), Ivanov, I. (Iliyan), Jia, T. (Tianye), Kelly, S. (Sinead), Klein, M. (Marieke), Kwon, J.S. (Jun Soo), Laansma, M.A. (Max A.), Leerssen, J. (Jeanne), Lueken, U. (Ulrike), Nunes, A. (Abraham), Neill, J.O. (Joseph O'), Opel, N. (Nils), Piras, F. (Fabrizio), Piras, F. (Federica), Postema, M.C. (Merel C.), Pozzi, E. (Elena), Shatokhina, N. (Natalia), Soriano-Mas, C. (Carles), Spalletta, G. (Gianfranco), Sun, D. (Daqiang), Teumer, A. (Alexander), Tilot, A.K. (Amanda K.), Tozzi, L. (Leonardo), van der Merwe, C. (Celia), Someren, E.J.W. (Eus) van, van Wingen, G.A. (Guido A.), Völzke, H. (Henry), Walton, E. (Esther), Wang, L. (Lei), Winkler, A.M. (Anderson), Wittfeld, K. (Katharina), Wright, M.J. (Margaret), Yun, J.-Y. (Je-Yeon), Zhang, G. (Guohao), Zhang-James, Y. (Yanli), Adhikari, B.M. (Bhim M.), Agartz, I. (Ingrid), Aghajani, M. (Moji), Aleman, A. (André), Althoff, R.R. (Robert R.), Altmann, A. (A.), Andreassen, O.A. (Ole), Baron, D.A. (David A.), Bartnik-Olson, B.L. (Brenda L.), Marie Bas-Hoogendam, J. (Janna), Baskin-Sommers, A.R. (Arielle R.), Bearden, C.E. (Carrie), Berner, L.A. (Laura A.), Boedhoe, P.S.W. (Premika S W), Brouwer, R.M. (Rachel), Buitelaar, J.K. (Jan), Caeyenberghs, K. (Karen), Cecil, C.A.M. (Charlotte), Cohen, R.A. (Ronald A.), Cole, J.H. (James H.), Conrod, P. (Patricia), De Brito, S.A. (Stephane A.), de Zwarte, S.M.C. (Sonja M C), Dennis, E.L. (Emily L.), Desrivieres, S. (Sylvane), Dima, D. (Danai), Ehrlich, S.M. (Stefan), Esopenko, C. (Carrie), Fairchild, G. (Graeme), Fisher, S.E. (Simon), Fouche, J.-P. (Jean-Paul), Francks, C. (Clyde), Frangou, S. (Sophia), Franke, B. (Barbara), Garavan, H.P. (Hugh P.), Glahn, D.C. (David), Groenewold, N.A. (Nynke A.), Gurholt, T.P. (Tiril P.), Gutman, B.A. (Boris A.), Hahn, T. (Tim), Harding, I.H. (Ian H.), Hernaus, D. (Dennis), Hibar, D.P. (Derrek P.), Hillary, F.G. (Frank G.), Hoogman, M. (Martine), Hulshoff Pol, H.E. (Hilleke E.), Jalbrzikowski, M. (Maria), Karkashadze, G.A. (George A.), Klapwijk, E.T. (Eduard T.), Knickmeyer, R.C. (Rebecca C.), Kochunov, P. (Peter), Koerte, I.K. (Inga K.), Kong, X.-Z. (Xiang-Zhen), Liew, S.-L. (Sook-Lei), Lin, A.P. (Alexander P.), Logue, M.W. (Mark W.), Luders, E. (Eileen), Macciardi, F. (Fabio), Mackey, S. (Scott), Mayer, A.R. (Andrew R.), McDonald, C.R. (Carrie R.), McMahon, A.B. (Agnes B.), Medland, S.E. (Sarah), Modinos, G. (Gemma), Morey, R.A. (Rajendra A.), Mueller, S.C. (Sven C.), Mukherjee, P. (Pratik), Namazova-Baranova, L. (L.), Nir, T.M. (Talia M.), Olsen, A. (Alexander), Paschou, P. (Peristera), Pine, D.S. (Daniel S.), Pizzagalli, F. (Fabrizio), Rentería, M.E. (Miguel), Rohrer, J.D. (Jonathan D.), Sämann, P.G. (Philipp), Schmaal, L. (Lianne), Schumann, G. (Gunter), Shiroishi, M.S. (Mark S.), Sisodiya, S.M. (Sanjay), Smit, D.J.A. (Dirk J A), Sønderby, I.E. (Ida E.), Stein, D.J. (Dan J.), Stein, J.L., Tahmasian, M. (Masoud), Tate, D.F. (David F.), Turner, J. (Jessica), Heuvel, O.A. (Odile A.), Wee, N.J. (Nic) van der, van der Werf, Y.D. (Ysbrand), Erp, T.G.M. (Theo G.) van, van Haren, N.E.M. (Neeltje E M), van Rooij, D. (Daan), Van Velzen, L.S., Veer, I.M. (Ilya), Veltman, D.J. (Dick), Villalon-Reina, J.E. (Julio E.), Walter, H.J. (Henrik), Whelan, C.D. (Christopher), Wilde, E.A. (Elisabeth A.), Zarei, M. (Mojtaba), and Zelman, V. (Vladimir)
- Abstract
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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- 2020
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40. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries
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Thompson, PM, Jahanshad, N, Ching, CRK, Salminen, LE, Thomopoulos, SI, Bright, J, Baune, BT, Bertolin, S, Bralten, J, Bruin, WB, Buelow, R, Chen, J, Chye, Y, Dannlowski, U, de Kovel, CGF, Donohoe, G, Eyler, LT, Faraone, SV, Favre, P, Filippi, CA, Frodl, T, Garijo, D, Gil, Y, Grabe, HJ, Grasby, KL, Hajek, T, Han, LKM, Hatton, SN, Hilbert, K, Ho, TC, Holleran, L, Homuth, G, Hosten, N, Houenou, J, Ivanov, I, Jia, T, Kelly, S, Klein, M, Kwon, JS, Laansma, MA, Leerssen, J, Lueken, U, Nunes, A, Neill, JO, Opel, N, Piras, F, Postema, MC, Pozzi, E, Shatokhina, N, Soriano-Mas, C, Spalletta, G, Sun, D, Teumer, A, Tilot, AK, Tozzi, L, van der Merwe, C, Van Someren, EJW, van Wingen, GA, Voelzke, H, Walton, E, Wang, L, Winkler, AM, Wittfeld, K, Wright, MJ, Yun, J-Y, Zhang, G, Zhang-James, Y, Adhikari, BM, Agartz, I, Aghajani, M, Aleman, A, Althoff, RR, Altmann, A, Andreassen, OA, Baron, DA, Bartnik-Olson, BL, Bas-Hoogendam, J, Baskin-Sommers, AR, Bearden, CE, Berner, LA, Boedhoe, PSW, Brouwer, RM, Buitelaar, JK, Caeyenberghs, K, Cecil, CAM, Cohen, RA, Cole, JH, Conrod, PJ, De Brito, SA, de Zwarte, SMC, Dennis, EL, Desrivieres, S, Dima, D, Ehrlich, S, Esopenko, C, Fairchild, G, Fisher, SE, Fouche, J-P, Francks, C, Frangou, S, Franke, B, Garavan, HP, Glahn, DC, Groenewold, NA, Gurholt, TP, Gutman, BA, Hahn, T, Harding, IH, Hernaus, D, Hibar, DP, Hillary, FG, Hoogman, M, Pol, HE, Jalbrzikowski, M, Karkashadze, GA, Klapwijk, ET, Knickmeyer, RC, Kochunov, P, Koerte, IK, Kong, X-Z, Liew, S-L, Lin, AP, Logue, MW, Luders, E, Macciardi, F, Mackey, S, Mayer, AR, McDonald, CR, McMahon, AB, Medland, SE, Modinos, G, Morey, RA, Mueller, SC, Mukherjee, P, Namazova-Baranova, L, Nir, TM, Olsen, A, Paschou, P, Pine, DS, Pizzagalli, F, Renteria, ME, Rohrer, JD, Saemann, PG, Schmaal, L, Schumann, G, Shiroishi, MS, Sisodiya, SM, Smit, DJA, Sonderby, IE, Stein, DJ, Stein, JL, Tahmasian, M, Tate, DF, Turner, JA, van den Heuvel, OA, van der Wee, NJA, van der Werf, YD, van Erp, TGM, van Haren, NEM, van Rooij, D, van Velzen, LS, Veer, IM, Veltman, DJ, Villalon-Reina, JE, Walter, H, Whelan, CD, Wilde, EA, Zarei, M, Zelman, V, Thompson, PM, Jahanshad, N, Ching, CRK, Salminen, LE, Thomopoulos, SI, Bright, J, Baune, BT, Bertolin, S, Bralten, J, Bruin, WB, Buelow, R, Chen, J, Chye, Y, Dannlowski, U, de Kovel, CGF, Donohoe, G, Eyler, LT, Faraone, SV, Favre, P, Filippi, CA, Frodl, T, Garijo, D, Gil, Y, Grabe, HJ, Grasby, KL, Hajek, T, Han, LKM, Hatton, SN, Hilbert, K, Ho, TC, Holleran, L, Homuth, G, Hosten, N, Houenou, J, Ivanov, I, Jia, T, Kelly, S, Klein, M, Kwon, JS, Laansma, MA, Leerssen, J, Lueken, U, Nunes, A, Neill, JO, Opel, N, Piras, F, Postema, MC, Pozzi, E, Shatokhina, N, Soriano-Mas, C, Spalletta, G, Sun, D, Teumer, A, Tilot, AK, Tozzi, L, van der Merwe, C, Van Someren, EJW, van Wingen, GA, Voelzke, H, Walton, E, Wang, L, Winkler, AM, Wittfeld, K, Wright, MJ, Yun, J-Y, Zhang, G, Zhang-James, Y, Adhikari, BM, Agartz, I, Aghajani, M, Aleman, A, Althoff, RR, Altmann, A, Andreassen, OA, Baron, DA, Bartnik-Olson, BL, Bas-Hoogendam, J, Baskin-Sommers, AR, Bearden, CE, Berner, LA, Boedhoe, PSW, Brouwer, RM, Buitelaar, JK, Caeyenberghs, K, Cecil, CAM, Cohen, RA, Cole, JH, Conrod, PJ, De Brito, SA, de Zwarte, SMC, Dennis, EL, Desrivieres, S, Dima, D, Ehrlich, S, Esopenko, C, Fairchild, G, Fisher, SE, Fouche, J-P, Francks, C, Frangou, S, Franke, B, Garavan, HP, Glahn, DC, Groenewold, NA, Gurholt, TP, Gutman, BA, Hahn, T, Harding, IH, Hernaus, D, Hibar, DP, Hillary, FG, Hoogman, M, Pol, HE, Jalbrzikowski, M, Karkashadze, GA, Klapwijk, ET, Knickmeyer, RC, Kochunov, P, Koerte, IK, Kong, X-Z, Liew, S-L, Lin, AP, Logue, MW, Luders, E, Macciardi, F, Mackey, S, Mayer, AR, McDonald, CR, McMahon, AB, Medland, SE, Modinos, G, Morey, RA, Mueller, SC, Mukherjee, P, Namazova-Baranova, L, Nir, TM, Olsen, A, Paschou, P, Pine, DS, Pizzagalli, F, Renteria, ME, Rohrer, JD, Saemann, PG, Schmaal, L, Schumann, G, Shiroishi, MS, Sisodiya, SM, Smit, DJA, Sonderby, IE, Stein, DJ, Stein, JL, Tahmasian, M, Tate, DF, Turner, JA, van den Heuvel, OA, van der Wee, NJA, van der Werf, YD, van Erp, TGM, van Haren, NEM, van Rooij, D, van Velzen, LS, Veer, IM, Veltman, DJ, Villalon-Reina, JE, Walter, H, Whelan, CD, Wilde, EA, Zarei, M, and Zelman, V
- Abstract
This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
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- 2020
41. Repeated Digitized Assessment of Risk and Symptom Profiles During Inpatient Treatment of Affective Disorder: Observational Study
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Richter, MF, Storck, M, Blitz, R, Goltermann, J, Seipp, J, Dannlowski, U, Baune, BT, Dugas, M, Opel, N, Richter, MF, Storck, M, Blitz, R, Goltermann, J, Seipp, J, Dannlowski, U, Baune, BT, Dugas, M, and Opel, N
- Abstract
BACKGROUND: Predictive models have revealed promising results for the individual prognosis of treatment response and relapse risk as well as for differential diagnosis in affective disorders. Yet, in order to translate personalized predictive modeling from research contexts to psychiatric clinical routine, standardized collection of information of sufficient detail and temporal resolution in day-to-day clinical care is needed. Digital collection of self-report measures by patients is a time- and cost-efficient approach to gain such data throughout treatment. OBJECTIVE: The objective of this study was to investigate whether patients with severe affective disorders were willing and able to participate in such efforts, whether the feasibility of such systems might vary depending on individual patient characteristics, and if digitally acquired assessments were of sufficient diagnostic validity. METHODS: We implemented a system for longitudinal digital collection of risk and symptom profiles based on repeated self-reports via tablet computers throughout inpatient treatment of affective disorders at the Department of Psychiatry at the University of Münster. Tablet-handling competency and the speed of data entry were assessed. Depression severity was additionally assessed by a clinical interviewer at baseline and before discharge. RESULTS: Of 364 affective disorder patients who were approached, 242 (66.5%) participated in the study; 88.8% of participants (215/242) were diagnosed with major depressive disorder, and 27 (11.2%) had bipolar disorder. During the duration of inpatient treatment, 79% of expected assessments were completed, with an average of 4 completed assessments per participant; 4 participants (4/242, 1.6%) dropped out of the study prematurely. During data entry, 89.3% of participants (216/242) did not require additional support. Needing support with tablet handling and slower data entry pace were predicted by older age, whereas depression severity at baseline
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- 2020
42. Severity of current depression and remission status are associated with structural connectome alterations in major depressive disorder
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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.
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- 2020
43. ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing
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Schmaal, L, Pozzi, E, Ho, TC, van Velzen, LS, Veer, IM, Opel, N, Van Someren, EJW, Han, LKM, Aftanas, L, Aleman, A, Baune, BT, Berger, K, Blanken, TF, Capitao, L, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, C, Erwin-Grabner, T, Evans, J, Frodl, T, Fu, CHY, Godlewska, B, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gutman, BA, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Hilland, E, Irungu, B, Jonassen, R, Kelly, S, Kircher, T, Klimes-Dougan, B, Krug, A, Landro, NI, Lagopoulos, J, Leerssen, J, Li, M, Linden, DEJ, MacMaster, FP, McIntosh, AM, Mehler, DMA, Nenadic, I, Penninx, BWJH, Portella, MJ, Reneman, L, Renteria, ME, Sacchet, MD, Saemann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Tozzi, L, van Der Wee, NJA, van Tol, M-J, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, Whalley, HC, Wittfeld, K, Whittle, S, Wright, MJ, Yang, TT, Zarate, C, Thomopoulos, SI, Jahanshad, N, Thompson, PM, Veltman, DJ, Schmaal, L, Pozzi, E, Ho, TC, van Velzen, LS, Veer, IM, Opel, N, Van Someren, EJW, Han, LKM, Aftanas, L, Aleman, A, Baune, BT, Berger, K, Blanken, TF, Capitao, L, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, C, Erwin-Grabner, T, Evans, J, Frodl, T, Fu, CHY, Godlewska, B, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gutman, BA, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Hilland, E, Irungu, B, Jonassen, R, Kelly, S, Kircher, T, Klimes-Dougan, B, Krug, A, Landro, NI, Lagopoulos, J, Leerssen, J, Li, M, Linden, DEJ, MacMaster, FP, McIntosh, AM, Mehler, DMA, Nenadic, I, Penninx, BWJH, Portella, MJ, Reneman, L, Renteria, ME, Sacchet, MD, Saemann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Tozzi, L, van Der Wee, NJA, van Tol, M-J, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, Whalley, HC, Wittfeld, K, Whittle, S, Wright, MJ, Yang, TT, Zarate, C, Thomopoulos, SI, Jahanshad, N, Thompson, PM, and Veltman, DJ
- Abstract
A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.
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- 2020
44. Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort
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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.
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- 2020
45. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group
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Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U
- Abstract
Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.
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- 2020
46. The genetic architecture of the human cerebral cortex
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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.
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- 2020
47. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics throughMeta-AnalysisBipolar Disorder Working Group
- Author
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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.
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- 2020
48. Brain functional effects of electroconvulsive therapy during emotional processing in major depressive disorder
- Author
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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.
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- 2020
49. Biological sex classification with structural MRI data shows increased misclassification in transgender women
- Author
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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.
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- 2020
50. Sleep duration is associated with white matter microstructure and cognitive performance in healthy adults
- Author
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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.
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- 2020
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