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    Virtual Ontogeny of Cortical Growth Preceding Mental Illness
    Patel, Y ; Shin, J ; Abe, C ; Agartz, I ; Alloza, C ; Alnaes, D ; Ambrogi, S ; Antonucci, LA ; Arango, C ; Arolt, V ; Auzias, G ; Ayesa-Arriola, R ; Banaj, N ; Banaschewski, T ; Bandeira, C ; Basgoze, Z ; Cupertino, RB ; Bau, CHD ; Bauer, J ; Baumeister, S ; Bernardoni, F ; Bertolino, A ; del Mar Bonnin, C ; Brandeis, D ; Brem, S ; Bruggemann, J ; Bulow, R ; Bustillo, JR ; Calderoni, S ; Calvo, R ; Canales-Rodriguez, EJ ; Cannon, DM ; Carmona, S ; Carr, VJ ; Catts, SV ; Chenji, S ; Chew, QH ; Coghill, D ; Connolly, CG ; Conzelmann, A ; Craven, AR ; Crespo-Facorro, B ; Cullen, K ; Dahl, A ; Dannlowski, U ; Davey, CG ; Deruelle, C ; Diaz-Caneja, CM ; Dohm, K ; Ehrlich, S ; Epstein, J ; Erwin-Grabner, T ; Eyler, LT ; Fedor, J ; Fitzgerald, J ; Foran, W ; Ford, JM ; Fortea, L ; Fuentes-Claramonte, P ; Fullerton, J ; Furlong, L ; Gallagher, L ; Gao, B ; Gao, S ; Goikolea, JM ; Gotlib, I ; Goya-Maldonado, R ; Grabe, HJ ; Green, M ; Grevet, EH ; Groenewold, NA ; Grotegerd, D ; Gruber, O ; Haavik, J ; Hahn, T ; Harrison, BJ ; Heindel, W ; Henskens, F ; Heslenfeld, DJ ; Hilland, E ; Hoekstra, PJ ; Hohmann, S ; Holz, N ; Howells, FM ; Ipser, JC ; Jahanshad, N ; Jakobi, B ; Jansen, A ; Janssen, J ; Jonassen, R ; Kaiser, A ; Kaleda, V ; Karantonis, J ; King, JA ; Kircher, T ; Kochunov, P ; Koopowitz, S-M ; Landen, M ; Landro, NI ; Lawrie, S ; Lebedeva, I ; Luna, B ; Lundervold, AJ ; MacMaster, FP ; Maglanoc, LA ; Mathalon, DH ; McDonald, C ; McIntosh, A ; Meinert, S ; Michie, PT ; Mitchell, P ; Moreno-Alcazar, A ; Mowry, B ; Muratori, F ; Nabulsi, L ; Nenadic, I ; Tuura, RO ; Oosterlaan, J ; Overs, B ; Pantelis, C ; Parellada, M ; Pariente, JC ; Pauli, P ; Pergola, G ; Piarulli, FM ; Picon, F ; Piras, F ; Pomarol-Clotet, E ; Pretus, C ; Quide, Y ; Radua, J ; Ramos-Quiroga, JA ; Rasser, PE ; Reif, A ; Retico, A ; Roberts, G ; Rossell, S ; Rovaris, DL ; Rubia, K ; Sacchet, M ; Salavert, J ; Salvador, R ; Sarro, S ; Sawa, A ; Schall, U ; Scott, R ; Selvaggi, P ; Silk, T ; Sim, K ; Skoch, A ; Spalletta, G ; Spaniel, F ; Stein, DJ ; Steinstrater, O ; Stolicyn, A ; Takayanagi, Y ; Tamm, L ; Tavares, M ; Teumer, A ; Thiel, K ; Thomopoulos, SI ; Tomecek, D ; Tomyshev, AS ; Tordesillas-Gutierrez, D ; Tosetti, M ; Uhlmann, A ; Van Rheenen, T ; Vazquez-Bourgon, J ; Vernooij, MW ; Vieta, E ; Vilarroya, O ; Weickert, C ; Weickert, T ; Westlye, LT ; Whalley, H ; Willinger, D ; Winter, A ; Wittfeld, K ; Yang, TT ; Yoncheva, Y ; Zijlmans, JL ; Hoogman, M ; Franke, B ; van Rooij, D ; Buitelaar, J ; Ching, CRK ; Andreassen, OA ; Pozzi, E ; Veltman, D ; Schmaal, L ; van Erp, TGM ; Turner, J ; Castellanos, FX ; Pausova, Z ; Thompson, P ; Paus, T (ELSEVIER SCIENCE INC, 2022-08-15)
    BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.
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    Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium
    van Velzen, LS ; Dauvermann, MR ; Colic, L ; Villa, LM ; Savage, HS ; Toenders, YJ ; Zhu, AH ; Bright, JK ; Campos, A ; Salminen, LE ; Ambrogi, S ; Ayesa-Arriola, R ; Banaj, N ; Basgoze, Z ; Bauer, J ; Blair, K ; Blair, RJ ; Brosch, K ; Cheng, Y ; Colle, R ; Connolly, CG ; Corruble, E ; Couvy-Duchesne, B ; Crespo-Facorro, B ; Cullen, KR ; Dannlowski, U ; Davey, CG ; Dohm, K ; Fullerton, JM ; Gonul, AS ; Gotlib, IH ; Grotegerd, D ; Hahn, T ; Harrison, BJ ; He, M ; Hickie, IB ; Ho, TC ; Iorfino, F ; Jansen, A ; Jollant, F ; Kircher, T ; Klimes-Dougan, B ; Klug, M ; Leehr, EJ ; Lippard, ETC ; McLaughlin, KA ; Meinert, S ; Miller, AB ; Mitchell, PB ; Mwangi, B ; Nenadic, I ; Ojha, A ; Overs, BJ ; Pfarr, J-K ; Piras, F ; Ringwald, KG ; Roberts, G ; Romer, G ; Sanches, M ; Sheridan, MA ; Soares, JC ; Spalletta, G ; Stein, F ; Teresi, G ; Tordesillas-Gutierrez, D ; Uyar-Demir, A ; van der Wee, NJA ; van der Werff, SJ ; Vermeiren, RRJM ; Winter, A ; Wu, M-J ; Yang, TT ; Thompson, PM ; Renteria, ME ; Jahanshad, N ; Blumberg, HP ; Van Harmelen, A-L ; Schmaal, L (SPRINGERNATURE, 2022-11)
    Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; Nā€‰=ā€‰519), clinical controls with a mood disorder but without STBs (CC; Nā€‰=ā€‰246) and young people with current suicidal ideation (Nā€‰=ā€‰223). In separate analyses, MRI metrics were compared among HCs (Nā€‰=ā€‰253), CCs (Nā€‰=ā€‰217), and suicide attempters (Nā€‰=ā€‰64). Third, in a larger transdiagnostic sample with various assessment instruments (HCā€‰=ā€‰606; CCā€‰=ā€‰419; Ideationā€‰=ā€‰289; HCā€‰=ā€‰253; CCā€‰=ā€‰432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (Nā€‰=ā€‰163) than those without a lifetime suicide attempt (Nā€‰=ā€‰323; FDR-pā€‰=ā€‰0.035, Cohen's dā€‰=ā€‰0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.
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    Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts
    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 (ELSEVIER SCIENCE INC, 2021-08-15)
    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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    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
    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 (SPRINGERNATURE, 2021-09)
    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 (nā€‰=ā€‰6420) and genetic data (nā€‰=ā€‰3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMIā€‰>ā€‰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 CohenĀ“s d (left fusiform gyrus)ā€‰=ā€‰-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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    Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders (May, 2020, 10.1038/s41380-020-0774-9)
    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 (SPRINGERNATURE, 2021-12)
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    Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years
    Frangou, S ; Modabbernia, A ; Williams, SCR ; Papachristou, E ; Doucet, GE ; Agartz, I ; Aghajani, M ; Akudjedu, TN ; Albajes-Eizagirre, A ; Alnaes, D ; Alpert, K ; Andersson, M ; Andreasen, NC ; Andreassen, OA ; Asherson, P ; Banaschewski, T ; Bargallo, N ; Baumeister, S ; Baur-Streubel, R ; Bertolino, A ; Bonvino, A ; Boomsma, D ; Borgwardt, S ; Bourque, J ; Brandeis, D ; Breier, A ; Brodaty, H ; Brouwer, RM ; Buitelaar, JK ; Busatto, GF ; Buckner, RL ; Calhoun, V ; Canales-Rodriguez, EJ ; Cannon, DM ; Caseras, X ; Castellanos, FX ; Cervenka, S ; Chaim-Avancini, TM ; Ching, CRK ; Chubar, V ; Clark, VP ; Conrod, P ; Conzelmann, A ; Crespo-Facorro, B ; Crivello, F ; Crone, EA ; Dale, AM ; Davey, C ; de Geus, EJC ; de Haan, L ; de Zubicaray, G ; den Braber, A ; Dickie, EW ; Di Giorgio, A ; Nhat, TD ; Dorum, ES ; Ehrlich, S ; Erk, S ; Espeseth, T ; Fatouros-Bergman, H ; Fisher, SE ; Fouche, J-P ; Franke, B ; Frodl, T ; Fuentes-Claramonte, P ; Glahn, DC ; Gotlib, IH ; Grabe, H-J ; Grimm, O ; Groenewold, NA ; Grotegerd, D ; Gruber, O ; Gruner, P ; Gur, RE ; Gur, RC ; Harrison, BJ ; Hartman, CA ; Hatton, SN ; Heinz, A ; Heslenfeld, DJ ; Hibar, DP ; Hickie, IB ; Ho, B-C ; Hoekstra, PJ ; Hohmann, S ; Holmes, AJ ; Hoogman, M ; Hosten, N ; Howells, FM ; Pol, HEH ; Huyser, C ; Jahanshad, N ; James, A ; Jernigan, TL ; Jiang, J ; Jonsson, EG ; Joska, JA ; Kahn, R ; Kalnin, A ; Kanai, R ; Klein, M ; Klyushnik, TP ; Koenders, L ; Koops, S ; Kraemer, B ; Kuntsi, J ; Lagopoulos, J ; Lazaro, L ; Lebedeva, I ; Lee, WH ; Lesch, K-P ; Lochner, C ; Machielsen, MWJ ; Maingault, S ; Martin, NG ; Martinez-Zalacain, I ; Mataix-Cols, D ; Mazoyer, B ; McDonald, C ; McDonald, BC ; McIntosh, AM ; McMahon, KL ; McPhilemy, G ; Menchon, JM ; Medland, SE ; Meyer-Lindenberg, A ; Naaijen, J ; Najt, P ; Nakao, T ; Nordvik, JE ; Nyberg, L ; Oosterlaan, J ; de la Foz, VO-G ; Paloyelis, Y ; Pauli, P ; Pergola, G ; Pomarol-Clotet, E ; Portella, MJ ; Potkin, SG ; Radua, J ; Reif, A ; Rinker, DA ; Roffman, JL ; Rosa, PGP ; Sacchet, MD ; Sachdev, PS ; Salvador, R ; Sanchez-Juan, P ; Sarro, S ; Satterthwaite, TD ; Saykin, AJ ; Serpa, MH ; Schmaal, L ; Schnell, K ; Schumann, G ; Sim, K ; Smoller, JW ; Sommer, I ; Soriano-Mas, C ; Stein, DJ ; Strike, LT ; Swagerman, SC ; Tamnes, CK ; Temmingh, HS ; Thomopoulos, S ; Tomyshev, AS ; Tordesillas-Gutierrez, D ; Trollor, JN ; Turner, JA ; Uhlmann, A ; van den Heuvel, OA ; van den Meer, D ; van der Wee, NJA ; van Haren, NEM ; van't Ent, D ; van Erp, TGM ; Veer, IM ; Veltman, DJ ; Voineskos, A ; Voelzke, H ; Walter, H ; Walton, E ; Wang, L ; Wang, Y ; Wassink, TH ; Weber, B ; Wen, W ; West, JD ; Westlye, LT ; Whalley, H ; Wierenga, LM ; Wittfeld, K ; Wolf, DH ; Worker, A ; Wright, MJ ; Yang, K ; Yoncheva, Y ; Zanetti, M ; Ziegler, GC ; Thompson, PM ; Dima, D (WILEY, 2022-01)
    Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90ā€‰years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
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    Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years
    Dima, D ; Modabbernia, A ; Papachristou, E ; Doucet, GE ; Agartz, I ; Aghajani, M ; Akudjedu, TN ; Albajes-Eizagirre, A ; Alnaes, D ; Alpert, K ; Andersson, M ; Andreasen, NC ; Andreassen, OA ; Asherson, P ; Banaschewski, T ; Bargallo, N ; Baumeister, S ; Baur-Streubel, R ; Bertolino, A ; Bonvino, A ; Boomsma, D ; Borgwardt, S ; Bourque, J ; Brandeis, D ; Breier, A ; Brodaty, H ; Brouwer, RM ; Buitelaar, JK ; Busatto, GF ; Buckner, RL ; Calhoun, V ; Canales-Rodriguez, EJ ; Cannon, DM ; Caseras, X ; Castellanos, FX ; Cervenka, S ; Chaim-Avancini, TM ; Ching, CRK ; Chubar, V ; Clark, VP ; Conrod, P ; Conzelmann, A ; Crespo-Facorro, B ; Crivello, F ; Crone, EA ; Dale, AM ; Davey, C ; de Geus, EJC ; de Haan, L ; de Zubicaray, G ; den Braber, A ; Dickie, EW ; Di Giorgio, A ; Nhat, TD ; Dorum, ES ; Ehrlich, S ; Erk, S ; Espeseth, T ; Fatouros-Bergman, H ; Fisher, SE ; Fouche, J-P ; Franke, B ; Frodl, T ; Fuentes-Claramonte, P ; Glahn, DC ; Gotlib, IH ; Grabe, H-J ; Grimm, O ; Groenewold, NA ; Grotegerd, D ; Gruber, O ; Gruner, P ; Gur, RE ; Gur, RC ; Harrison, BJ ; Hartman, CA ; Hatton, SN ; Heinz, A ; Heslenfeld, DJ ; Hibar, DP ; Hickie, IB ; Ho, B-C ; Hoekstra, PJ ; Hohmann, S ; Holmes, AJ ; Hoogman, M ; Hosten, N ; Howells, FM ; Pol, HEH ; Huyser, C ; Jahanshad, N ; James, A ; Jernigan, TL ; Jiang, J ; Jonsson, EG ; Joska, JA ; Kahn, R ; Kalnin, A ; Kanai, R ; Klein, M ; Klyushnik, TP ; Koenders, L ; Koops, S ; Kraemer, B ; Kuntsi, J ; Lagopoulos, J ; Lazaro, L ; Lebedeva, I ; Lee, WH ; Lesch, K-P ; Lochner, C ; Machielsen, MWJ ; Maingault, S ; Martin, NG ; Martinez-Zalacain, I ; Mataix-Cols, D ; Mazoyer, B ; McDonald, C ; McDonald, BC ; McIntosh, AM ; McMahon, KL ; McPhilemy, G ; Menchon, JM ; Medland, SE ; Meyer-Lindenberg, A ; Naaijen, J ; Najt, P ; Nakao, T ; Nordvik, JE ; Nyberg, L ; Oosterlaan, J ; Ortiz-Garcia De la Foz, V ; Paloyelis, Y ; Pauli, P ; Pergola, G ; Pomarol-Clotet, E ; Portella, MJ ; Potkin, SG ; Radua, J ; Reif, A ; Rinker, DA ; Roffman, JL ; Rosa, PGP ; Sacchet, MD ; Sachdev, PS ; Salvador, R ; Sanchez-Juan, P ; Sarro, S ; Satterthwaite, TD ; Saykin, AJ ; Serpa, MH ; Schmaal, L ; Schnell, K ; Schumann, G ; Sim, K ; Smoller, JW ; Sommer, I ; Soriano-Mas, C ; Stein, DJ ; Strike, LT ; Swagerman, SC ; Tamnes, CK ; Temmingh, HS ; Thomopoulos, S ; Tomyshev, AS ; Tordesillas-Gutierrez, D ; Trollor, JN ; Turner, JA ; Uhlmann, A ; van den Heuvel, OA ; van den Meer, D ; van der Wee, NJA ; van Haren, NEM ; Van't Ent, D ; van Erp, TGM ; Veer, IM ; Veltman, DJ ; Voineskos, A ; Voelzke, H ; Walter, H ; Walton, E ; Wang, L ; Wang, Y ; Wassink, TH ; Weber, B ; Wen, W ; West, JD ; Westlye, LT ; Whalley, H ; Wierenga, LM ; Williams, SCR ; Wittfeld, K ; Wolf, DH ; Worker, A ; Wright, MJ ; Yang, K ; Yoncheva, Y ; Zanetti, M ; Ziegler, GC ; Thompson, PM ; Frangou, S (WILEY, 2022-01)
    Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90ā€‰years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
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    Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders
    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 ; 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 (AMER MEDICAL ASSOC, 2021-01)
    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-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders. CONCLUSIONS AND RELEVANCE: In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
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    ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing
    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 (SPRINGERNATURE, 2020-05-29)
    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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    Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
    Han, LKM ; Dinga, R ; Hahn, T ; Ching, CRK ; Eyler, LT ; Aftanas, L ; Aghajani, M ; Aleman, A ; Baune, BT ; Berger, K ; Brak, I ; Busatto Filho, G ; Carballedo, A ; Connolly, CG ; Couvy-Duchesne, B ; Cullen, KR ; Dannlowski, U ; Davey, CG ; Dima, D ; Duran, FLS ; Enneking, V ; Filimonova, E ; Frenzel, S ; Frodl, T ; Fu, CHY ; Godlewska, BR ; Gotlib, IH ; Grabe, HJ ; Groenewold, NA ; Grotegerd, D ; Gruber, O ; Hall, GB ; Harrison, BJ ; Hatton, SN ; Hermesdorf, M ; Hickie, IB ; Ho, TC ; Hosten, N ; Jansen, A ; Kaehler, C ; Kircher, T ; Klimes-Dougan, B ; Kraemer, B ; Krug, A ; Lagopoulos, J ; Leenings, R ; MacMaster, FP ; MacQueen, G ; McIntosh, A ; McLellan, Q ; McMahon, KL ; Medland, SE ; Mueller, BA ; Mwangi, B ; Osipov, E ; Portella, MJ ; Pozzi, E ; Reneman, L ; Repple, J ; Rosa, PGP ; Sacchet, MD ; Saemann, PG ; Schnell, K ; Schrantee, A ; Simulionyte, E ; Soares, JC ; Sommer, J ; Stein, DJ ; Steinstraeter, O ; Strike, LT ; Thomopoulos, SI ; van Tol, M-J ; Veer, IM ; Vermeiren, RRJM ; Walter, H ; van der Wee, NJA ; van der Werff, SJA ; Whalley, H ; Winter, NR ; Wittfeld, K ; Wright, MJ ; Wu, M-J ; Voelzke, H ; Yang, TT ; Zannias, V ; de Zubicaray, GI ; Zunta-Soares, GB ; Abe, C ; Alda, M ; Andreassen, OA ; Boen, E ; Bonnin, CM ; Canales-Rodriguez, EJ ; Cannon, D ; Caseras, X ; Chaim-Avancini, TM ; Elvsashagen, T ; Favre, P ; Foley, SF ; Fullerton, JM ; Goikolea, JM ; Haarman, BCM ; Hajek, T ; Henry, C ; Houenou, J ; Howells, FM ; Ingvar, M ; Kuplicki, R ; Lafer, B ; Landen, M ; Machado-Vieira, R ; Malt, UF ; McDonald, C ; Mitchell, PB ; Nabulsi, L ; Otaduy, MCG ; Overs, BJ ; Polosan, M ; Pomarol-Clotet, E ; Radua, J ; Rive, MM ; Roberts, G ; Ruhe, HG ; Salvador, R ; Sarro, S ; Satterthwaite, TD ; Savitz, J ; Schene, AH ; Schofield, PR ; Serpa, MH ; Sim, K ; Soeiro-de-Souza, MG ; Sutherland, AN ; Temmingh, HS ; Timmons, GM ; Uhlmann, A ; Vieta, E ; Wolf, DH ; Zanetti, MV ; Jahanshad, N ; Thompson, PM ; Veltman, DJ ; Penninx, BWJH ; Marquand, AF ; Cole, JH ; Schmaal, L (SPRINGERNATURE, 2021-09)
    Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's dā€‰=ā€‰0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.