Author: "Westlye, LT" - Searchworks@Jio Institute Digital Library Search Results

Your search keyword '"Westlye, LT"' showing total 496 results

Start Over Author "Westlye, LT"

496 results on '"Westlye, LT"'

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

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

2. Prefrontal cortical thinning links to negative symptoms in schizophrenia via the ENIGMA consortium.

Author: Walton, E, Hibar, DP, van Erp, TGM, Potkin, SG, Roiz-Santiañez, R, Crespo-Facorro, B, Suarez-Pinilla, P, van Haren, NEM, de Zwarte, SMC, Kahn, RS, Cahn, W, Doan, NT, Jørgensen, KN, Gurholt, TP, Agartz, I, Andreassen, OA, Westlye, LT, Melle, I, Berg, AO, Morch-Johnsen, L, Færden, A, Flyckt, L, Fatouros-Bergman, H, Karolinska Schizophrenia Project Consortium (KaSP), Jönsson, EG, Hashimoto, R, Yamamori, H, Fukunaga, M, Jahanshad, N, De Rossi, P, Piras, F, Banaj, N, Spalletta, G, Gur, RE, Gur, RC, Wolf, DH, Satterthwaite, TD, Beard, LM, Sommer, IE, Koops, S, Gruber, O, Richter, A, Krämer, B, Kelly, S, Donohoe, G, McDonald, C, Cannon, DM, Corvin, A, Gill, M, Di Giorgio, A, Bertolino, A, Lawrie, S, Nickson, T, Whalley, HC, Neilson, E, Calhoun, VD, Thompson, PM, Turner, JA, and Ehrlich, S
Subjects: Karolinska Schizophrenia Project Consortium, Prefrontal Cortex, Humans, Magnetic Resonance Imaging, Linear Models, Schizophrenia, Psychiatric Status Rating Scales, Schizophrenic Psychology, Internationality, Image Processing, Computer-Assisted, Adult, Female, Male, Functional Laterality, Cortical thickness, ENIGMA, FreeSurfer, MRI, PANSS, SANS, medial orbitofrontal cortex, negative symptoms, schizophrenia, Image Processing, Computer-Assisted, Psychiatry, Psychology, Public Health and Health Services, Neurosciences
Abstract: BackgroundOur understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.MethodsThis study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).ResultsMeta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.ConclusionsUsing an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.
Published: 2018

3. Positive symptoms associate with cortical thinning in the superior temporal gyrus via the ENIGMA Schizophrenia consortium

Author: Walton, E, Hibar, DP, Erp, TGM, Potkin, SG, Roiz‐Santiañez, R, Crespo‐Facorro, B, Suarez‐Pinilla, P, Van Haren, NEM, Zwarte, SMC, Kahn, RS, Cahn, W, Doan, NT, Jørgensen, KN, Gurholt, TP, Agartz, I, Andreassen, OA, Westlye, LT, Melle, I, Berg, AO, Mørch‐Johnsen, L, Færden, A, Flyckt, L, Fatouros‐Bergman, H, Consortium, Karolinska Schizophrenia Project, Jönsson, EG, Hashimoto, R, Yamamori, H, Fukunaga, M, Preda, A, De Rossi, P, Piras, F, Banaj, N, Ciullo, V, Spalletta, G, Gur, RE, Gur, RC, Wolf, DH, Satterthwaite, TD, Beard, LM, Sommer, IE, Koops, S, Gruber, O, Richter, A, Krämer, B, Kelly, S, Donohoe, G, McDonald, C, Cannon, DM, Corvin, A, Gill, M, Di Giorgio, A, Bertolino, A, Lawrie, S, Nickson, T, Whalley, HC, Neilson, E, Calhoun, VD, Thompson, PM, Turner, JA, and Ehrlich, S
Subjects: Schizophrenia, Mental Health, Brain Disorders, Mental health, Good Health and Well Being, Adult, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Male, Prospective Studies, Psychiatric Status Rating Scales, Schizophrenic Psychology, Temporal Lobe, schizophrenia, positive symptoms, superior temporal gyrus, cortical thickness, ENIGMA, FreeSurfer, MRI, scale for the assessment of positive symptoms, positive and negative syndrome scale, Karolinska Schizophrenia Project Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: ObjectiveBased on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia.MethodThis prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness.ResultsPositive symptom severity was negatively related to STG thickness in both hemispheres (left: βstd = -0.052; P = 0.021; right: βstd = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness.ConclusionOur findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.
Published: 2017

4. Subcortical volumetric abnormalities in bipolar disorder.

Author: Hibar, DP, Westlye, LT, van Erp, TGM, Rasmussen, J, Leonardo, CD, Faskowitz, J, Haukvik, UK, Hartberg, CB, Doan, NT, Agartz, I, Dale, AM, Gruber, O, Krämer, B, Trost, S, Liberg, B, Abé, C, Ekman, CJ, Ingvar, M, Landén, M, Fears, SC, Freimer, NB, Bearden, CE, Costa Rica/Colombia Consortium for Genetic Investigation of Bipolar Endophenotypes, Sprooten, E, Glahn, DC, Pearlson, GD, Emsell, L, Kenney, J, Scanlon, C, McDonald, C, Cannon, DM, Almeida, J, Versace, A, Caseras, X, Lawrence, NS, Phillips, ML, Dima, D, Delvecchio, G, Frangou, S, Satterthwaite, TD, Wolf, D, Houenou, J, Henry, C, Malt, UF, Bøen, E, Elvsåshagen, T, Young, AH, Lloyd, AJ, Goodwin, GM, Mackay, CE, Bourne, C, Bilderbeck, A, Abramovic, L, Boks, MP, van Haren, NEM, Ophoff, RA, Kahn, RS, Bauer, M, Pfennig, A, Alda, M, Hajek, T, Mwangi, B, Soares, JC, Nickson, T, Dimitrova, R, Sussmann, JE, Hagenaars, S, Whalley, HC, McIntosh, AM, Thompson, PM, and Andreassen, OA
Subjects: Costa Rica/Colombia Consortium for Genetic Investigation of Bipolar Endophenotypes, Brain, Humans, Magnetic Resonance Imaging, Organ Size, Case-Control Studies, Retrospective Studies, Bipolar Disorder, Adult, Middle Aged, Female, Male, Clinical Research, Mental Health, Brain Disorders, Serious Mental Illness, Neurosciences, Aetiology, 2.1 Biological and endogenous factors, Mental health, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract: Considerable uncertainty exists about the defining brain changes associated with bipolar disorder (BD). Understanding and quantifying the sources of uncertainty can help generate novel clinical hypotheses about etiology and assist in the development of biomarkers for indexing disease progression and prognosis. Here we were interested in quantifying case-control differences in intracranial volume (ICV) and each of eight subcortical brain measures: nucleus accumbens, amygdala, caudate, hippocampus, globus pallidus, putamen, thalamus, lateral ventricles. In a large study of 1710 BD patients and 2594 healthy controls, we found consistent volumetric reductions in BD patients for mean hippocampus (Cohen's d=-0.232; P=3.50 × 10-7) and thalamus (d=-0.148; P=4.27 × 10-3) and enlarged lateral ventricles (d=-0.260; P=3.93 × 10-5) in patients. No significant effect of age at illness onset was detected. Stratifying patients based on clinical subtype (BD type I or type II) revealed that BDI patients had significantly larger lateral ventricles and smaller hippocampus and amygdala than controls. However, when comparing BDI and BDII patients directly, we did not detect any significant differences in brain volume. This likely represents similar etiology between BD subtype classifications. Exploratory analyses revealed significantly larger thalamic volumes in patients taking lithium compared with patients not taking lithium. We detected no significant differences between BDII patients and controls in the largest such comparison to date. Findings in this study should be interpreted with caution and with careful consideration of the limitations inherent to meta-analyzed neuroimaging comparisons.
Published: 2016

5. Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

Author: van Erp, TGM, Hibar, DP, Rasmussen, JM, Glahn, DC, Pearlson, GD, Andreassen, OA, Agartz, I, Westlye, LT, Haukvik, UK, Dale, AM, Melle, I, Hartberg, CB, Gruber, O, Kraemer, B, Zilles, D, Donohoe, G, Kelly, S, McDonald, C, Morris, DW, Cannon, DM, Corvin, A, Machielsen, MWJ, Koenders, L, de Haan, L, Veltman, DJ, Satterthwaite, TD, Wolf, DH, Gur, RC, Gur, RE, Potkin, SG, Mathalon, DH, Mueller, BA, Preda, A, Macciardi, F, Ehrlich, S, Walton, E, Hass, J, Calhoun, VD, Bockholt, HJ, Sponheim, SR, Shoemaker, JM, van Haren, NEM, Pol, HEH, Ophoff, RA, Kahn, RS, Roiz-Santiañez, R, Crespo-Facorro, B, Wang, L, Alpert, KI, Jönsson, EG, Dimitrova, R, Bois, C, Whalley, HC, McIntosh, AM, Lawrie, SM, Hashimoto, R, Thompson, PM, and Turner, JA
Subjects: Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Serious Mental Illness, Brain Disorders, Schizophrenia, Clinical Research, Neurosciences, Mental Health, Biomedical Imaging, Rare Diseases, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Adult, Brain, Brain Mapping, Case-Control Studies, Female, Functional Laterality, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Prospective Studies, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract: The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.
Published: 2016

6. Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm

Author: Jiang, Y, Luo, C, Wang, J, Palaniyappan, L, Chang, X, Xiang, S, Zhang, J, Duan, M, Huang, H, Gaser, C, Nemoto, K, Miura, K, Hashimoto, R, Westlye, LT, Richard, G, Fernandez-Cabello, S, Parker, N, Andreassen, OA, Kircher, T, Nenadić, I, Stein, F, Thomas-Odenthal, F, Teutenberg, L, Usemann, P, Dannlowski, U, Hahn, T, Grotegerd, D, Meinert, S, Lencer, R, Tang, Y, Zhang, T, Li, C, Yue, W, Zhang, Y, Yu, X, Zhou, E, Lin, CP, Tsai, SJ, Rodrigue, AL, Glahn, D, Pearlson, G, Blangero, J, Karuk, A, Pomarol-Clotet, E, Salvador, R, Fuentes-Claramonte, P, Garcia-León, MÁ, Spalletta, G, Piras, F, Vecchio, D, Banaj, N, Cheng, J, Liu, Z, Yang, J, Gonul, AS, Uslu, O, Burhanoglu, BB, Uyar Demir, A, Rootes-Murdy, K, Calhoun, VD, Sim, K, Green, M ; https://orcid.org/0000-0002-9361-4874, Quidé, Y, Chung, YC, Kim, WS, Sponheim, SR, Demro, C, Ramsay, IS, Iasevoli, F, de Bartolomeis, A, Barone, A, Ciccarelli, M, Brunetti, A, Cocozza, S, Pontillo, G, Tranfa, M, Park, MTM, Kirschner, M, Georgiadis, F, Kaiser, S, Van Rheenen, TE, Rossell, SL, Hughes, M, Woods, W, Carruthers, SP, Sumner, P, Ringin, E, Spaniel, F, Skoch, A, Tomecek, D, Homan, P, Homan, S, Omlor, W, Cecere, G, Nguyen, DD, Preda, A, Thomopoulos, SI, Jahanshad, N, Cui, LB, Yao, D, Quide, Yann ; https://orcid.org/0000-0002-8569-7139, Jiang, Y, Luo, C, Wang, J, Palaniyappan, L, Chang, X, Xiang, S, Zhang, J, Duan, M, Huang, H, Gaser, C, Nemoto, K, Miura, K, Hashimoto, R, Westlye, LT, Richard, G, Fernandez-Cabello, S, Parker, N, Andreassen, OA, Kircher, T, Nenadić, I, Stein, F, Thomas-Odenthal, F, Teutenberg, L, Usemann, P, Dannlowski, U, Hahn, T, Grotegerd, D, Meinert, S, Lencer, R, Tang, Y, Zhang, T, Li, C, Yue, W, Zhang, Y, Yu, X, Zhou, E, Lin, CP, Tsai, SJ, Rodrigue, AL, Glahn, D, Pearlson, G, Blangero, J, Karuk, A, Pomarol-Clotet, E, Salvador, R, Fuentes-Claramonte, P, Garcia-León, MÁ, Spalletta, G, Piras, F, Vecchio, D, Banaj, N, Cheng, J, Liu, Z, Yang, J, Gonul, AS, Uslu, O, Burhanoglu, BB, Uyar Demir, A, Rootes-Murdy, K, Calhoun, VD, Sim, K, Green, M ; https://orcid.org/0000-0002-9361-4874, Quidé, Y, Chung, YC, Kim, WS, Sponheim, SR, Demro, C, Ramsay, IS, Iasevoli, F, de Bartolomeis, A, Barone, A, Ciccarelli, M, Brunetti, A, Cocozza, S, Pontillo, G, Tranfa, M, Park, MTM, Kirschner, M, Georgiadis, F, Kaiser, S, Van Rheenen, TE, Rossell, SL, Hughes, M, Woods, W, Carruthers, SP, Sumner, P, Ringin, E, Spaniel, F, Skoch, A, Tomecek, D, Homan, P, Homan, S, Omlor, W, Cecere, G, Nguyen, DD, Preda, A, Thomopoulos, SI, Jahanshad, N, Cui, LB, Yao, D, and Quide, Yann ; https://orcid.org/0000-0002-8569-7139
Abstract: Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal ‘trajectory’ of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.
Published: 2024

7. Normative Modeling of Brain Morphometry in Clinical High Risk for Psychosis

Author: Haas, SS, Ge, R, Agartz, I, Amminger, GP, Andreassen, OA, Bachman, P, Baeza, I, Choi, S, Colibazzi, T, Cropley, VL, de la Fuente-Sandoval, C, Ebdrup, BH, Fortea, A, Fusar-Poli, P, Glenthoj, BY, Glenthoj, LB, Haut, KM, Hayes, RA, Heekeren, K, Hooker, CI, Hwang, WJ, Jahanshad, N, Kaess, M, Kasai, K, Katagiri, N, Kim, M, Kindler, J, Koike, S, Kristensen, TD, Kwon, JS, Lawrie, SM, Lebedeva, I, Lee, J, Lemmers-Jansen, ILJ, Lin, A, Ma, X, Mathalon, DH, McGuire, P, Michel, C, Mizrahi, R, Mizuno, M, Moller, P, Mora-Duran, R, Nelson, B, Nemoto, T, Nordentoft, M, Nordholm, D, Omelchenko, MA, Pantelis, C, Pariente, JC, Raghava, J, Reyes-Madrigal, F, Rossberg, JI, Rossler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Smigielski, L, Sugranyes, G, Suzuki, M, Takahashi, T, Tamnes, CK, Theodoridou, A, Thomopoulos, SI, Thompson, PM, Tomyshev, AS, Uhlhaas, PJ, Vaernes, TG, van Amelsvoort, TAMJ, van Erp, TGM, Waltz, JA, Wenneberg, C, Westlye, LT, Wood, SJ, Zhou, JH, Hernaus, D, Jalbrzikowski, M, Kahn, RS, Corcoran, CM, Frangou, S, Haas, SS, Ge, R, Agartz, I, Amminger, GP, Andreassen, OA, Bachman, P, Baeza, I, Choi, S, Colibazzi, T, Cropley, VL, de la Fuente-Sandoval, C, Ebdrup, BH, Fortea, A, Fusar-Poli, P, Glenthoj, BY, Glenthoj, LB, Haut, KM, Hayes, RA, Heekeren, K, Hooker, CI, Hwang, WJ, Jahanshad, N, Kaess, M, Kasai, K, Katagiri, N, Kim, M, Kindler, J, Koike, S, Kristensen, TD, Kwon, JS, Lawrie, SM, Lebedeva, I, Lee, J, Lemmers-Jansen, ILJ, Lin, A, Ma, X, Mathalon, DH, McGuire, P, Michel, C, Mizrahi, R, Mizuno, M, Moller, P, Mora-Duran, R, Nelson, B, Nemoto, T, Nordentoft, M, Nordholm, D, Omelchenko, MA, Pantelis, C, Pariente, JC, Raghava, J, Reyes-Madrigal, F, Rossberg, JI, Rossler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Smigielski, L, Sugranyes, G, Suzuki, M, Takahashi, T, Tamnes, CK, Theodoridou, A, Thomopoulos, SI, Thompson, PM, Tomyshev, AS, Uhlhaas, PJ, Vaernes, TG, van Amelsvoort, TAMJ, van Erp, TGM, Waltz, JA, Wenneberg, C, Westlye, LT, Wood, SJ, Zhou, JH, Hernaus, D, Jalbrzikowski, M, Kahn, RS, Corcoran, CM, and Frangou, S
Abstract: IMPORTANCE: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals. OBJECTIVE: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. DESIGN, SETTING, AND PARTICIPANTS: This case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022. MAIN OUTCOMES AND MEASURES: For each regional morphometric measure, deviation scores were computed as z scores indexing the degree of deviation from their normative means from a healthy reference population. Average deviation scores (ADS) were also calculated for regional CT, SA, and SV measures and globally across all measures. Regression analyses quantified the association of deviation scores with clinical severity and cognition, and 2-proportion z tests identified case-control differences in the proportion of individuals with infranormal (z < -1.96) or supranormal (z > 1.96) scores. RESULTS: Among 1340 individuals with CHR-P, 709 (52.91%) were male, and the mean (SD) age was 20.75 (4.74) years. Among 1237 healthy individuals, 684 (55.30%) were male, and the mean (SD
Published: 2024

8. Beyond the Global Brain Differences: Intraindividual Variability Differences in 1q21.1 Distal and 15q11.2 BP1-BP2 Deletion Carriers

Author: Boen, R, Kaufmann, T, van der Meer, D, Frei, O, Agartz, I, Ames, D, Andersson, M, Armstrong, NJ, Artiges, E, Atkins, JR, Bauer, J, Benedetti, F, Boomsma, DI, Brodaty, H, Brosch, K, Buckner, RL, Cairns, MJ, Calhoun, V, Caspers, S, Cichon, S, Corvin, AP, Crespo-Facorro, B, Dannlowski, U, David, FS, de Geus, EJC, de Zubicaray, GI, Desrivieres, S, Doherty, JL, Donohoe, G, Ehrlich, S, Eising, E, Espeseth, T, Fisher, SE, Forstner, AJ, Fortaner-Uya, L, Frouin, V, Fukunaga, M, Ge, T, Glahn, DC, Goltermann, J, Grabe, HJ, Green, MJ, Groenewold, NA, Grotegerd, D, Grontvedt, GR, Hahn, T, Hashimoto, R, Hehir-Kwa, JY, Henskens, FA, Holmes, AJ, Haberg, AK, Haavik, J, Jacquemont, S, Jansen, A, Jockwitz, C, Joensson, EG, Kikuchi, M, Kircher, T, Kumar, K, Le Hellard, S, Leu, C, Linden, DE, Liu, J, Loughnan, R, Mather, KA, Mcmahon, KL, Mcrae, AF, Medland, SE, Meinert, S, Moreau, CA, Morris, DW, Mowry, BJ, Muehleisen, TW, Nenadic, I, Noethen, MM, Nyberg, L, Ophoff, RA, Owen, MJ, Pantelis, C, Paolini, M, Paus, T, Pausova, Z, Persson, K, Quide, Y, Marques, TR, Sachdev, PS, Sando, SB, Schall, U, Scott, RJ, Selbaek, G, Shumskaya, E, Silva, AI, Sisodiya, SM, Stein, F, Stein, DJ, Straube, B, Streit, F, Strike, LT, Teumer, A, Teutenberg, L, Thalamuthu, A, Tooney, PA, Tordesillas-Gutierrez, D, Trollor, JN, Van't Ent, D, van den Bree, MBM, van Haren, NEM, Vazquez-Bourgon, J, Voelzke, H, Wen, W, Wittfeld, K, Ching, CRK, Westlye, LT, Thompson, PM, Bearden, CE, Selmer, KK, Alnaes, D, Andreassen, OA, Sonderby, IE, Boen, R, Kaufmann, T, van der Meer, D, Frei, O, Agartz, I, Ames, D, Andersson, M, Armstrong, NJ, Artiges, E, Atkins, JR, Bauer, J, Benedetti, F, Boomsma, DI, Brodaty, H, Brosch, K, Buckner, RL, Cairns, MJ, Calhoun, V, Caspers, S, Cichon, S, Corvin, AP, Crespo-Facorro, B, Dannlowski, U, David, FS, de Geus, EJC, de Zubicaray, GI, Desrivieres, S, Doherty, JL, Donohoe, G, Ehrlich, S, Eising, E, Espeseth, T, Fisher, SE, Forstner, AJ, Fortaner-Uya, L, Frouin, V, Fukunaga, M, Ge, T, Glahn, DC, Goltermann, J, Grabe, HJ, Green, MJ, Groenewold, NA, Grotegerd, D, Grontvedt, GR, Hahn, T, Hashimoto, R, Hehir-Kwa, JY, Henskens, FA, Holmes, AJ, Haberg, AK, Haavik, J, Jacquemont, S, Jansen, A, Jockwitz, C, Joensson, EG, Kikuchi, M, Kircher, T, Kumar, K, Le Hellard, S, Leu, C, Linden, DE, Liu, J, Loughnan, R, Mather, KA, Mcmahon, KL, Mcrae, AF, Medland, SE, Meinert, S, Moreau, CA, Morris, DW, Mowry, BJ, Muehleisen, TW, Nenadic, I, Noethen, MM, Nyberg, L, Ophoff, RA, Owen, MJ, Pantelis, C, Paolini, M, Paus, T, Pausova, Z, Persson, K, Quide, Y, Marques, TR, Sachdev, PS, Sando, SB, Schall, U, Scott, RJ, Selbaek, G, Shumskaya, E, Silva, AI, Sisodiya, SM, Stein, F, Stein, DJ, Straube, B, Streit, F, Strike, LT, Teumer, A, Teutenberg, L, Thalamuthu, A, Tooney, PA, Tordesillas-Gutierrez, D, Trollor, JN, Van't Ent, D, van den Bree, MBM, van Haren, NEM, Vazquez-Bourgon, J, Voelzke, H, Wen, W, Wittfeld, K, Ching, CRK, Westlye, LT, Thompson, PM, Bearden, CE, Selmer, KK, Alnaes, D, Andreassen, OA, and Sonderby, IE
Abstract: BACKGROUND: Carriers of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants exhibit regional and global brain differences compared with noncarriers. However, interpreting regional differences is challenging if a global difference drives the regional brain differences. Intraindividual variability measures can be used to test for regional differences beyond global differences in brain structure. METHODS: Magnetic resonance imaging data were used to obtain regional brain values for 1q21.1 distal deletion (n = 30) and duplication (n = 27) and 15q11.2 BP1-BP2 deletion (n = 170) and duplication (n = 243) carriers and matched noncarriers (n = 2350). Regional intra-deviation scores, i.e., the standardized difference between an individual's regional difference and global difference, were used to test for regional differences that diverge from the global difference. RESULTS: For the 1q21.1 distal deletion carriers, cortical surface area for regions in the medial visual cortex, posterior cingulate, and temporal pole differed less and regions in the prefrontal and superior temporal cortex differed more than the global difference in cortical surface area. For the 15q11.2 BP1-BP2 deletion carriers, cortical thickness in regions in the medial visual cortex, auditory cortex, and temporal pole differed less and the prefrontal and somatosensory cortex differed more than the global difference in cortical thickness. CONCLUSIONS: We find evidence for regional effects beyond differences in global brain measures in 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants. The results provide new insight into brain profiling of the 1q21.1 distal and 15q11.2 BP1-BP2 copy number variants, with the potential to increase understanding of the mechanisms involved in altered neurodevelopment.
Published: 2024

9. Large-scale analysis of structural brain asymmetries in schizophrenia via the ENIGMA consortium

Author: Schijven, D, Postema, MC, Fukunaga, M, Matsumoto, J, Miura, K, de Zwarte, SMC, van Haren, NEM, Cahn, W, Hulshoff Pol, HE, Kahn, RS, Ayesa-Arriola, R, Ortiz-García de la Foz, V, Tordesillas-Gutierrez, D, Vázquez-Bourgon, J, Crespo-Facorro, B, Alnæs, D, Dahl, A, Westlye, LT, Agartz, I, Andreassen, OA, Jönsson, EG, Kochunov, P, Bruggemann, JM, Catts, SV, Michie, PT, Mowry, BJ, Quidé, Y, Rasser, PE, Schall, U, Scott, RJ, Carr, VJ ; https://orcid.org/0000-0002-8907-5804, Green, MJ ; https://orcid.org/0000-0002-9361-4874, Henskens, FA, Loughland, CM, Pantelis, C, Weickert, CS ; https://orcid.org/0000-0002-4560-0259, Weickert, TW, de Haan, L, Brosch, K, Pfarr, JK, Ringwald, KG, Stein, F, Jansen, A, Kircher, TTJ, Nenadić, I, Krämer, B, Gruber, O, Satterthwaite, TD, Bustillo, J, Mathalon, DH, Preda, A, Calhoun, VD, Ford, JM, Potkin, SG, Chen, J, Tan, Y, Wang, Z, Xiang, H, Fan, F, Bernardoni, F, Ehrlich, S, Fuentes-Claramonte, P, Garcia-Leon, MA, Guerrero-Pedraza, A, Salvador, R, Sarró, S, Pomarol-Clotet, E, Ciullo, V, Piras, F, Vecchio, D, Banaj, N, Spalletta, G, Michielse, S, van Amelsvoort, T, Dickie, EW, Voineskos, AN, Sim, K, Ciufolini, S, Dazzan, P, Murray, RM, Kim, WS, Chung, YC, Andreou, C, Schmidt, A, Borgwardt, S, McIntosh, AM, Whalley, HC, Lawrie, SM, du Plessis, S, Luckhoff, HK, Scheffler, F, Emsley, R, Grotegerd, D, Lencer, R, Dannlowski, U, Edmond, JT, Rootes-Murdy, K, Stephen, JM, Mayer, AR, Antonucci, LA, Quide, Yann ; https://orcid.org/0000-0002-8569-7139, Schijven, D, Postema, MC, Fukunaga, M, Matsumoto, J, Miura, K, de Zwarte, SMC, van Haren, NEM, Cahn, W, Hulshoff Pol, HE, Kahn, RS, Ayesa-Arriola, R, Ortiz-García de la Foz, V, Tordesillas-Gutierrez, D, Vázquez-Bourgon, J, Crespo-Facorro, B, Alnæs, D, Dahl, A, Westlye, LT, Agartz, I, Andreassen, OA, Jönsson, EG, Kochunov, P, Bruggemann, JM, Catts, SV, Michie, PT, Mowry, BJ, Quidé, Y, Rasser, PE, Schall, U, Scott, RJ, Carr, VJ ; https://orcid.org/0000-0002-8907-5804, Green, MJ ; https://orcid.org/0000-0002-9361-4874, Henskens, FA, Loughland, CM, Pantelis, C, Weickert, CS ; https://orcid.org/0000-0002-4560-0259, Weickert, TW, de Haan, L, Brosch, K, Pfarr, JK, Ringwald, KG, Stein, F, Jansen, A, Kircher, TTJ, Nenadić, I, Krämer, B, Gruber, O, Satterthwaite, TD, Bustillo, J, Mathalon, DH, Preda, A, Calhoun, VD, Ford, JM, Potkin, SG, Chen, J, Tan, Y, Wang, Z, Xiang, H, Fan, F, Bernardoni, F, Ehrlich, S, Fuentes-Claramonte, P, Garcia-Leon, MA, Guerrero-Pedraza, A, Salvador, R, Sarró, S, Pomarol-Clotet, E, Ciullo, V, Piras, F, Vecchio, D, Banaj, N, Spalletta, G, Michielse, S, van Amelsvoort, T, Dickie, EW, Voineskos, AN, Sim, K, Ciufolini, S, Dazzan, P, Murray, RM, Kim, WS, Chung, YC, Andreou, C, Schmidt, A, Borgwardt, S, McIntosh, AM, Whalley, HC, Lawrie, SM, du Plessis, S, Luckhoff, HK, Scheffler, F, Emsley, R, Grotegerd, D, Lencer, R, Dannlowski, U, Edmond, JT, Rootes-Murdy, K, Stephen, JM, Mayer, AR, Antonucci, LA, and Quide, Yann ; https://orcid.org/0000-0002-8569-7139
Abstract: Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.
Published: 2023

10. Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders

Author: Segal, A, Parkes, L, Aquino, K, Kia, SM, Wolfers, T, Franke, B, Hoogman, M, Beckmann, CF, Westlye, LT, Andreassen, OA, Zalesky, A, Harrison, BJ, Davey, CG, Soriano-Mas, C, Cardoner, N, Tiego, J, Yucel, M, Braganza, L, Suo, C, Berk, M, Cotton, S, Bellgrove, MA, Marquand, AF, Fornito, A, Segal, A, Parkes, L, Aquino, K, Kia, SM, Wolfers, T, Franke, B, Hoogman, M, Beckmann, CF, Westlye, LT, Andreassen, OA, Zalesky, A, Harrison, BJ, Davey, CG, Soriano-Mas, C, Cardoner, N, Tiego, J, Yucel, M, Braganza, L, Suo, C, Berk, M, Cotton, S, Bellgrove, MA, Marquand, AF, and Fornito, A
Abstract: The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.
Published: 2023

11. Longitudinal Structural Brain Changes in Bipolar Disorder: A Multicenter Neuroimaging Study of 1232 Individuals by the ENIGMA Bipolar Disorder Working Group

Author: 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 ; https://orcid.org/0000-0003-4014-4490, 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 ; https://orcid.org/0000-0002-7954-5235, 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 ; https://orcid.org/0000-0002-1966-5120, 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 ; https://orcid.org/0000-0003-4014-4490, 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 ; https://orcid.org/0000-0002-7954-5235, 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 ; https://orcid.org/0000-0002-1966-5120, 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
Abstract: Background: Bipolar disorder (BD) is associated with cortical and subcortical structural brain abnormalities. It is unclear whether such alterations progressively change over time, and how this is related to the number of mood episodes. To address this question, we analyzed a large and diverse international sample with longitudinal magnetic resonance imaging (MRI) and clinical data to examine structural brain changes over time in BD. Methods: Longitudinal structural MRI and clinical data from the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) BD Working Group, including 307 patients with BD and 925 healthy control subjects, were collected from 14 sites worldwide. Male and female participants, aged 40 ± 17 years, underwent MRI at 2 time points. Cortical thickness, surface area, and subcortical volumes were estimated using FreeSurfer. Annualized change rates for each imaging phenotype were compared between patients with BD and healthy control subjects. Within patients, we related brain change rates to the number of mood episodes between time points and tested for effects of demographic and clinical variables. Results: Compared with healthy control subjects, patients with BD showed faster enlargement of ventricular volumes and slower thinning of the fusiform and parahippocampal cortex (0.18 < d < 0.22). More (hypo)manic episodes were associated with faster cortical thinning, primarily in the prefrontal cortex. Conclusions: In the hitherto largest longitudinal MRI study on BD, we did not detect accelerated cortical thinning but noted faster ventricular enlargements in BD. However, abnormal frontocortical thinning was observed in association with frequent manic episodes. Our study yields insights into disease progression in BD and highlights the importance of mania prevention in BD treatment.
Published: 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

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

13. Mind the gap: Performance metric evaluation in brain-age prediction

Author: de Lange, A-MG, Anaturk, M, Rokicki, J, Han, LKM, Franke, K, Alnaes, D, Ebmeier, KP, Draganski, B, Kaufmann, T, Westlye, LT, Hahn, T, Cole, JH, de Lange, A-MG, Anaturk, M, Rokicki, J, Han, LKM, Franke, K, Alnaes, D, Ebmeier, KP, Draganski, B, Kaufmann, T, Westlye, LT, Hahn, T, and Cole, JH
Abstract: Estimating age based on neuroimaging-derived data has become a popular approach to developing markers for brain integrity and health. While a variety of machine-learning algorithms can provide accurate predictions of age based on brain characteristics, there is significant variation in model accuracy reported across studies. We predicted age in two population-based datasets, and assessed the effects of age range, sample size and age-bias correction on the model performance metrics Pearson's correlation coefficient (r), the coefficient of determination (R2 ), Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE). The results showed that these metrics vary considerably depending on cohort age range; r and R2 values are lower when measured in samples with a narrower age range. RMSE and MAE are also lower in samples with a narrower age range due to smaller errors/brain age delta values when predictions are closer to the mean age of the group. Across subsets with different age ranges, performance metrics improve with increasing sample size. Performance metrics further vary depending on prediction variance as well as mean age difference between training and test sets, and age-bias corrected metrics indicate high accuracy-also for models showing poor initial performance. In conclusion, performance metrics used for evaluating age prediction models depend on cohort and study-specific data characteristics, and cannot be directly compared across different studies. Since age-bias corrected metrics generally indicate high accuracy, even for poorly performing models, inspection of uncorrected model results provides important information about underlying model attributes such as prediction variance.
Published: 2022

14. Charting brain growth and aging at high spatial precision

Author: Rutherford, S, Fraza, C, Dinga, R, Kia, SM, Wolfers, T, Zabihi, M, Berthet, P, Worker, A, Verdi, S, Andrews, D, Han, LK, Bayer, JM, Dazzan, P, McGuire, P, Mocking, RT, Schene, A, Sripada, C, Tso, IF, Duval, ER, Chang, S-E, Penninx, BW, Heitzeg, MM, Burt, SA, Hyde, LW, Amaral, D, Nordahl, CW, Andreasssen, OA, Westlye, LT, Zahn, R, Ruhe, HG, Beckmann, C, Marquand, AF, Rutherford, S, Fraza, C, Dinga, R, Kia, SM, Wolfers, T, Zabihi, M, Berthet, P, Worker, A, Verdi, S, Andrews, D, Han, LK, Bayer, JM, Dazzan, P, McGuire, P, Mocking, RT, Schene, A, Sripada, C, Tso, IF, Duval, ER, Chang, S-E, Penninx, BW, Heitzeg, MM, Burt, SA, Hyde, LW, Amaral, D, Nordahl, CW, Andreasssen, OA, Westlye, LT, Zahn, R, Ruhe, HG, Beckmann, C, and Marquand, AF
Abstract: Defining reference models for population variation, and the ability to study individual deviations is essential for understanding inter-individual variability and its relation to the onset and progression of medical conditions. In this work, we assembled a reference cohort of neuroimaging data from 82 sites (N=58,836; ages 2-100) and used normative modeling to characterize lifespan trajectories of cortical thickness and subcortical volume. Models are validated against a manually quality checked subset (N=24,354) and we provide an interface for transferring to new data sources. We showcase the clinical value by applying the models to a transdiagnostic psychiatric sample (N=1985), showing they can be used to quantify variability underlying multiple disorders whilst also refining case-control inferences. These models will be augmented with additional samples and imaging modalities as they become available. This provides a common reference platform to bind results from different studies and ultimately paves the way for personalized clinical decision-making.
Published: 2022

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

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

16. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from theENIGMABipolar Disorder Working Group

Author: Ching, CRK, Hibar, DP, Gurholt, TP, Nunes, A, Thomopoulos, SI, Abe, C, Agartz, I, Brouwer, RM, Cannon, DM, de Zwarte, SMC, Eyler, LT, Favre, P, Hajek, T, Haukvik, UK, Houenou, J, Landen, M, Lett, TA, McDonald, C, Nabulsi, L, Patel, Y, Pauling, ME, Paus, T, Radua, J, Soeiro-de-Souza, MG, Tronchin, G, van Haren, NEM, Vieta, E, Walter, H, Zeng, L-L, Alda, M, Almeida, J, Alnaes, D, Alonso-Lana, S, Altimus, C, Bauer, M, Baune, BT, Bearden, CE, Bellani, M, Benedetti, F, Berk, M, Bilderbeck, AC, Blumberg, HP, Boen, E, Bollettini, I, del Mar Bonnin, C, Brambilla, P, Canales-Rodriguez, EJ, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Diaz-Zuluaga, AM, Dima, D, Duchesnay, E, Elvsashagen, T, Fears, SC, Frangou, S, Fullerton, JM, Glahn, DC, Goikolea, JM, Green, MJ, Grotegerd, D, Gruber, O, Haarman, BCM, Henry, C, Howells, FM, Ives-Deliperi, V, Jansen, A, Kircher, TTJ, Knoechel, C, Kramer, B, Lafer, B, Lopez-Jaramillo, C, Machado-Vieira, R, MacIntosh, BJ, Melloni, EMT, Mitchell, PB, Nenadic, I, Nery, F, Nugent, AC, Oertel, V, Ophoff, RA, Ota, M, Overs, BJ, Pham, DL, Phillips, ML, Pineda-Zapata, JA, Poletti, S, Polosan, M, Pomarol-Clotet, E, Pouchon, A, Quide, Y, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Schene, AH, Sim, K, Soares, JC, Staeblein, M, Stein, DJ, Tamnes, CK, Thomaidis, GV, Upegui, CV, Veltman, DJ, Wessa, M, Westlye, LT, Whalley, HC, Wolf, DH, Wu, M-J, Yatham, LN, Zarate, CA, Thompson, PM, Andreassen, OA, Ching, CRK, Hibar, DP, Gurholt, TP, Nunes, A, Thomopoulos, SI, Abe, C, Agartz, I, Brouwer, RM, Cannon, DM, de Zwarte, SMC, Eyler, LT, Favre, P, Hajek, T, Haukvik, UK, Houenou, J, Landen, M, Lett, TA, McDonald, C, Nabulsi, L, Patel, Y, Pauling, ME, Paus, T, Radua, J, Soeiro-de-Souza, MG, Tronchin, G, van Haren, NEM, Vieta, E, Walter, H, Zeng, L-L, Alda, M, Almeida, J, Alnaes, D, Alonso-Lana, S, Altimus, C, Bauer, M, Baune, BT, Bearden, CE, Bellani, M, Benedetti, F, Berk, M, Bilderbeck, AC, Blumberg, HP, Boen, E, Bollettini, I, del Mar Bonnin, C, Brambilla, P, Canales-Rodriguez, EJ, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Diaz-Zuluaga, AM, Dima, D, Duchesnay, E, Elvsashagen, T, Fears, SC, Frangou, S, Fullerton, JM, Glahn, DC, Goikolea, JM, Green, MJ, Grotegerd, D, Gruber, O, Haarman, BCM, Henry, C, Howells, FM, Ives-Deliperi, V, Jansen, A, Kircher, TTJ, Knoechel, C, Kramer, B, Lafer, B, Lopez-Jaramillo, C, Machado-Vieira, R, MacIntosh, BJ, Melloni, EMT, Mitchell, PB, Nenadic, I, Nery, F, Nugent, AC, Oertel, V, Ophoff, RA, Ota, M, Overs, BJ, Pham, DL, Phillips, ML, Pineda-Zapata, JA, Poletti, S, Polosan, M, Pomarol-Clotet, E, Pouchon, A, Quide, Y, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Schene, AH, Sim, K, Soares, JC, Staeblein, M, Stein, DJ, Tamnes, CK, Thomaidis, GV, Upegui, CV, Veltman, DJ, Wessa, M, Westlye, LT, Whalley, HC, Wolf, DH, Wu, M-J, Yatham, LN, Zarate, CA, Thompson, PM, and Andreassen, OA
Abstract: MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.
Published: 2022

17. Greater male than female variability in regional brain structure across the lifespan

Author: Wierenga, LM, Doucet, GE, Dima, D, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andreassen, OA, Anticevic, A, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, den Braber, A, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Calhoun, VD, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Chaim-Avancini, TM, Ching, CRK, Clark, VP, Conrod, PJ, Conzelmann, A, Crivello, F, Davey, CG, Dickie, EW, Ehrlich, S, Van't Ent, D, Fisher, SE, Fouche, J-P, Franke, B, Fuentes-Claramonte, P, de Geus, EJC, Di Giorgio, A, Glahn, DC, Gotlib, IH, Grabe, HJ, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Gurholt, TP, de Haan, L, Haatveit, B, Harrison, BJ, Hartman, CA, Hatton, SN, Heslenfeld, DJ, van den Heuvel, OA, Hickie, IB, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, AC, Jiang, J, Jonsson, EG, Joska, JA, Kalnin, AJ, Klein, M, Koenders, L, Kolskar, KK, Kramer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, IS, Lee, PH, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, BC, McDonald, C, McIntosh, AM, McMahon, KL, McPhilemy, G, van der Meer, D, Menchon, JM, Naaijen, J, Nyberg, L, Oosterlaan, J, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Radua, J, Reif, A, Richard, G, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Sim, K, Simmons, A, Smoller, JW, Sommer, IE, Soriano-Mas, C, Stein, DJ, Strike, LT, Szeszko, PR, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Trollor, JN, Uhlmann, A, Veer, IM, Veltman, DJ, Voineskos, A, Volzke, H, Walter, H, Wang, L, Wang, Y, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, HC, Williams, SCR, Wittfeld, K, Wolf, DH, Wright, MJ, Yoncheva, YN, Zanetti, M, Ziegler, GC, de Zubicaray, G, Thompson, PM, Crone, EA, Frangou, S, Tamnes, CK, Wierenga, LM, Doucet, GE, Dima, D, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andreassen, OA, Anticevic, A, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, den Braber, A, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Calhoun, VD, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Chaim-Avancini, TM, Ching, CRK, Clark, VP, Conrod, PJ, Conzelmann, A, Crivello, F, Davey, CG, Dickie, EW, Ehrlich, S, Van't Ent, D, Fisher, SE, Fouche, J-P, Franke, B, Fuentes-Claramonte, P, de Geus, EJC, Di Giorgio, A, Glahn, DC, Gotlib, IH, Grabe, HJ, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Gurholt, TP, de Haan, L, Haatveit, B, Harrison, BJ, Hartman, CA, Hatton, SN, Heslenfeld, DJ, van den Heuvel, OA, Hickie, IB, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, AC, Jiang, J, Jonsson, EG, Joska, JA, Kalnin, AJ, Klein, M, Koenders, L, Kolskar, KK, Kramer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, IS, Lee, PH, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, BC, McDonald, C, McIntosh, AM, McMahon, KL, McPhilemy, G, van der Meer, D, Menchon, JM, Naaijen, J, Nyberg, L, Oosterlaan, J, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Radua, J, Reif, A, Richard, G, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Sim, K, Simmons, A, Smoller, JW, Sommer, IE, Soriano-Mas, C, Stein, DJ, Strike, LT, Szeszko, PR, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Trollor, JN, Uhlmann, A, Veer, IM, Veltman, DJ, Voineskos, A, Volzke, H, Walter, H, Wang, L, Wang, Y, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, HC, Williams, SCR, Wittfeld, K, Wolf, DH, Wright, MJ, Yoncheva, YN, Zanetti, M, Ziegler, GC, de Zubicaray, G, Thompson, PM, Crone, EA, Frangou, S, and Tamnes, CK
Abstract: For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.
Published: 2022

18. The ENIGMA Stroke Recovery Working Group: Big data neuroimaging to study brain-behavior relationships after stroke

Author: Liew, S-L, Zavaliangos-Petropulu, A, Jahanshad, N, Lang, CE, Hayward, KS, Lohse, KR, Juliano, JM, Assogna, F, Baugh, LA, Bhattacharya, AK, Bigjahan, B, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Byblow, WD, Cassidy, JM, Conforto, AB, Craddock, RC, Dimyan, MA, Dula, AN, Ermer, E, Etherton, MR, Fercho, KA, Gregory, CM, Hadidchi, S, Holguin, JA, Hwang, DH, Jung, S, Kautz, SA, Khlif, MS, Khoshab, N, Kim, B, Kim, H, Kuceyeski, A, Lotze, M, MacIntosh, BJ, Margetis, JL, Mohamed, FB, Piras, F, Ramos-Murguialday, A, Richard, G, Roberts, P, Robertson, AD, Rondina, JM, Rost, NS, Sanossian, N, Schweighofer, N, Seo, NJ, Shiroishi, MS, Soekadar, SR, Spalletta, G, Stinear, CM, Suri, A, Tang, WKW, Thielman, GT, Vecchio, D, Villringer, A, Ward, NS, Werden, E, Westlye, LT, Winstein, C, Wittenberg, GF, Wong, KA, Yu, C, Cramer, SC, Thompson, PM, Liew, S-L, Zavaliangos-Petropulu, A, Jahanshad, N, Lang, CE, Hayward, KS, Lohse, KR, Juliano, JM, Assogna, F, Baugh, LA, Bhattacharya, AK, Bigjahan, B, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Byblow, WD, Cassidy, JM, Conforto, AB, Craddock, RC, Dimyan, MA, Dula, AN, Ermer, E, Etherton, MR, Fercho, KA, Gregory, CM, Hadidchi, S, Holguin, JA, Hwang, DH, Jung, S, Kautz, SA, Khlif, MS, Khoshab, N, Kim, B, Kim, H, Kuceyeski, A, Lotze, M, MacIntosh, BJ, Margetis, JL, Mohamed, FB, Piras, F, Ramos-Murguialday, A, Richard, G, Roberts, P, Robertson, AD, Rondina, JM, Rost, NS, Sanossian, N, Schweighofer, N, Seo, NJ, Shiroishi, MS, Soekadar, SR, Spalletta, G, Stinear, CM, Suri, A, Tang, WKW, Thielman, GT, Vecchio, D, Villringer, A, Ward, NS, Werden, E, Westlye, LT, Winstein, C, Wittenberg, GF, Wong, KA, Yu, C, Cramer, SC, and Thompson, PM
Abstract: The goal of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Stroke Recovery working group is to understand brain and behavior relationships using well-powered meta- and mega-analytic approaches. ENIGMA Stroke Recovery has data from over 2,100 stroke patients collected across 39 research studies and 10 countries around the world, comprising the largest multisite retrospective stroke data collaboration to date. This article outlines the efforts taken by the ENIGMA Stroke Recovery working group to develop neuroinformatics protocols and methods to manage multisite stroke brain magnetic resonance imaging, behavioral and demographics data. Specifically, the processes for scalable data intake and preprocessing, multisite data harmonization, and large-scale stroke lesion analysis are described, and challenges unique to this type of big data collaboration in stroke research are discussed. Finally, future directions and limitations, as well as recommendations for improved data harmonization through prospective data collection and data management, are provided.
Published: 2022

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

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

20. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years

Author: 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, 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, and Frangou, S
Abstract: 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 3-90 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.
Published: 2022

21. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years

Author: 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, 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, and Dima, D
Abstract: 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 3-90 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.
Published: 2022

22. Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

Author: Baldwin, H, Radua, J, Antoniades, M, Haas, SS, Frangou, S, Agartz, I, Allen, P, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Bartholomeusz, CF, Chee, MWL, Colibazzi, T, Cooper, RE, Corcoran, CM, Cropley, VL, Ebdrup, BH, Fortea, A, Glenthoj, LB, Hamilton, HK, Haut, KM, Hayes, RA, He, Y, Heekeren, K, Kaess, M, Kasai, K, Katagiri, N, Kim, M, Kindler, J, Klaunig, MJ, Koike, S, Koppel, A, Kristensen, TD, Bin Kwak, Y, Kwon, JS, Lawrie, SM, Lebedeva, I, Lee, J, Lin, A, Loewy, RL, Mathalon, DH, Michel, C, Mizrahi, R, Moller, P, Nelson, B, Nemoto, T, Nordholm, D, Omelchenko, MA, Pantelis, C, Raghava, JM, Rossberg, J, Roessler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Smigielski, L, Sugranyes, G, Suzuki, M, Takahashi, T, Tamnes, CK, Tang, J, Theodoridou, A, Thomopoulos, S, Tomyshev, AS, Uhlhaas, PJ, Vaernes, TG, van Amelsvoort, TAMJ, Van Erp, TGM, Waltz, JA, Westlye, LT, Wood, SJ, Zhou, JH, McGuire, P, Thompson, PM, Jalbrzikowski, M, Hernaus, D, Fusar-Poli, P, Baldwin, H, Radua, J, Antoniades, M, Haas, SS, Frangou, S, Agartz, I, Allen, P, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Bartholomeusz, CF, Chee, MWL, Colibazzi, T, Cooper, RE, Corcoran, CM, Cropley, VL, Ebdrup, BH, Fortea, A, Glenthoj, LB, Hamilton, HK, Haut, KM, Hayes, RA, He, Y, Heekeren, K, Kaess, M, Kasai, K, Katagiri, N, Kim, M, Kindler, J, Klaunig, MJ, Koike, S, Koppel, A, Kristensen, TD, Bin Kwak, Y, Kwon, JS, Lawrie, SM, Lebedeva, I, Lee, J, Lin, A, Loewy, RL, Mathalon, DH, Michel, C, Mizrahi, R, Moller, P, Nelson, B, Nemoto, T, Nordholm, D, Omelchenko, MA, Pantelis, C, Raghava, JM, Rossberg, J, Roessler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Smigielski, L, Sugranyes, G, Suzuki, M, Takahashi, T, Tamnes, CK, Tang, J, Theodoridou, A, Thomopoulos, S, Tomyshev, AS, Uhlhaas, PJ, Vaernes, TG, van Amelsvoort, TAMJ, Van Erp, TGM, Waltz, JA, Westlye, LT, Wood, SJ, Zhou, JH, McGuire, P, Thompson, PM, Jalbrzikowski, M, Hernaus, D, and Fusar-Poli, P
Abstract: Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the 'normativeness' of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irre
Published: 2022

23. A large, curated, open-source stroke neuroimaging dataset to improve lesion segmentation algorithms

Author: Liew, S-L, Lo, BP, Donnelly, MR, Zavaliangos-Petropulu, A, Jeong, JN, Barisano, G, Hutton, A, Simon, JP, Juliano, JM, Suri, A, Wang, Z, Abdullah, A, Kim, J, Ard, T, Banaj, N, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Cao, L, Cassidy, JM, Ciullo, V, Conforto, AB, Cramer, SC, Dacosta-Aguayo, R, de la Rosa, E, Domin, M, Dula, AN, Feng, W, Franco, AR, Geranmayeh, F, Gramfort, A, Gregory, CM, Hanlon, CA, Hordacre, BG, Kautz, SA, Khlif, MS, Kim, H, Kirschke, JS, Liu, J, Lotze, M, MacIntosh, BJ, Mataro, M, Mohamed, FB, Nordvik, JE, Park, G, Pienta, A, Piras, F, Redman, SM, Revill, KP, Reyes, M, Robertson, AD, Seo, NJ, Soekadar, SR, Spalletta, G, Sweet, A, Telenczuk, M, Thielman, G, Westlye, LT, Winstein, CJ, Wittenberg, GF, Wong, KA, Yu, C, Liew, S-L, Lo, BP, Donnelly, MR, Zavaliangos-Petropulu, A, Jeong, JN, Barisano, G, Hutton, A, Simon, JP, Juliano, JM, Suri, A, Wang, Z, Abdullah, A, Kim, J, Ard, T, Banaj, N, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Cao, L, Cassidy, JM, Ciullo, V, Conforto, AB, Cramer, SC, Dacosta-Aguayo, R, de la Rosa, E, Domin, M, Dula, AN, Feng, W, Franco, AR, Geranmayeh, F, Gramfort, A, Gregory, CM, Hanlon, CA, Hordacre, BG, Kautz, SA, Khlif, MS, Kim, H, Kirschke, JS, Liu, J, Lotze, M, MacIntosh, BJ, Mataro, M, Mohamed, FB, Nordvik, JE, Park, G, Pienta, A, Piras, F, Redman, SM, Revill, KP, Reyes, M, Robertson, AD, Seo, NJ, Soekadar, SR, Spalletta, G, Sweet, A, Telenczuk, M, Thielman, G, Westlye, LT, Winstein, CJ, Wittenberg, GF, Wong, KA, and Yu, C
Abstract: Accurate lesion segmentation is critical in stroke rehabilitation research for the quantification of lesion burden and accurate image processing. Current automated lesion segmentation methods for T1-weighted (T1w) MRIs, commonly used in stroke research, lack accuracy and reliability. Manual segmentation remains the gold standard, but it is time-consuming, subjective, and requires neuroanatomical expertise. We previously released an open-source dataset of stroke T1w MRIs and manually-segmented lesion masks (ATLAS v1.2, N = 304) to encourage the development of better algorithms. However, many methods developed with ATLAS v1.2 report low accuracy, are not publicly accessible or are improperly validated, limiting their utility to the field. Here we present ATLAS v2.0 (N = 1271), a larger dataset of T1w MRIs and manually segmented lesion masks that includes training (n = 655), test (hidden masks, n = 300), and generalizability (hidden MRIs and masks, n = 316) datasets. Algorithm development using this larger sample should lead to more robust solutions; the hidden datasets allow for unbiased performance evaluation via segmentation challenges. We anticipate that ATLAS v2.0 will lead to improved algorithms, facilitating large-scale stroke research.
Published: 2022

24. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author: 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, 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, and Paus, T
Abstract: 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 t
Published: 2022

25. Chronic stroke sensorimotor impairment is related to smaller hippocampal volumes: An ENIGMA analysis

Author: Zavaliangos-Petropulu, A, primary, Lo, B, additional, Donnelly, MR, additional, Schweighofer, N, additional, Lohse, Keith, additional, Jahanshad, Neda, additional, Barisano, G, additional, Banaj, N, additional, Borich, MR, additional, Boyd, LA, additional, Buetefisch, CM, additional, Byblow, WD, additional, Cassidy, JM, additional, Charalambous, CC, additional, Conforto, AB, additional, DiCarlo, JA, additional, Dula, AN, additional, Egorova-Brumley, N, additional, Etherton, MR, additional, Feng, W, additional, Fercho, KA, additional, Geranmayeh, F, additional, Hanlon, CA, additional, Hayward, KS, additional, Hordacre, B, additional, Kautz, SA, additional, Khlif, MS, additional, Kim, H, additional, Kuceyeski, A, additional, Lin, DJ, additional, Lotze, M, additional, Liu, J, additional, MacIntosh, BJ, additional, Margetis, JL, additional, Piras, F, additional, Ramos-Murguialday, A, additional, Revill, KP, additional, Roberts, PS, additional, Robertson, AD, additional, Schambra, HM, additional, Seo, NJ, additional, Shiroishi, MS, additional, Soekadar, SR, additional, Spalletta, G, additional, Taga, M, additional, Tang, WK, additional, Thielman, GT, additional, Vecchio, D, additional, Ward, NS, additional, Westlye, LT, additional, Werden, E, additional, Winstein, C, additional, Wittenberg, GF, additional, Wolf, SL, additional, Wong, KA, additional, Yu, C, additional, Brodtmann, A, additional, Cramer, SC, additional, Thompson, PM, additional, and Liew, S-L, additional
Published: 2021
Full Text: View/download PDF

26. Association of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis: An ENIGMA Working Group Mega-analysis

Author: ENIGMA Clinical High Risk for Psychosis Working Group, Jalbrzikowski M, Hayes RA, Wood SJ, Nordholm D, Zhou JH, Fusar-Poli P, Uhlhaas PJ, Takahashi T, Sugranyes G, Kwak YB, Mathalon DH, Katagiri N, Hooker CI, Smigielski L, Colibazzi T, Esther Via Virgili, Tang J, Koike S, Rasser PE, Michel C, Lebedeva I, Hegelstad WTV, de la Fuente-Sandoval C, Waltz JA, Mizrahi R, Corcoran CM, Resch F, Tamnes CK, Haas SS, Lemmers-Jansen ILJ, Agartz I, Allen P, Amminger GP, Andreassen OA, Atkinson K, Bachman P, Baeza I, Baldwin H, Bartholomeusz CF, Borgwardt S, Catalano S, Chee MWL, Chen X, Cho KIK, Cooper RE, Cropley VL, Dolz M, Ebdrup BH, Fortea A, Glenthøj LB, Glenthøj BY, de Haan L, Hamilton HK, Harris MA, Haut KM, He Y, Heekeren K, Heinz A, Hubl D, Hwang WJ, Kaess M, Kasai K, Kim M, Kindler J, Klaunig MJ, Koppel A, Kristensen TD, Kwon JS, Lawrie SM, Lee J, León-Ortiz P, Lin A, Loewy RL, Ma X, McGorry P, McGuire P, Mizuno M, Møller P, Moncada-Habib T, Muñoz Samons D, Nelson B, Nemoto T, Nordentoft M, Omelchenko MA, Oppedal K, Ouyang L, Pantelis C, Pariente JC, Raghava JM, Reyes-Madrigal F, Roach BJ, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Schall U, Schiffman J, Schlagenhauf F, Schmidt A, Sørensen ME, Suzuki M, Theodoridou A, Tomyshev AS, Tor J, Værnes TG, Velakoulis D, Venegoni GD, Vinogradov S, Wenneberg C, Westlye LT, Yamasue H, Yuan L, Yung AR, van Amelsvoort TAMJ, Turner JA, van Erp TGM, Thompson PM, and Hernaus D
Abstract: IMPORTANCE: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. OBJECTIVE: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. MAIN OUTCOMES AND MEASURES: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). RESULTS: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (? = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (? = 0.43; 95% CI, 0.20 to 0.61; P = .001). CONCLUSIONS AND RELEVANCE: This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.
Published: 2021

27. Toward a global and reproducible science for brain imaging in neurotrauma: the ENIGMA adult moderate/severe traumatic brain injury working group

Author: Olsen, A, Babikian, T, Bigler, ED, Caeyenberghs, Karen, Conde, V, Dams-O’Connor, K, Dobryakova, E, Genova, H, Grafman, J, Håberg, AK, Heggland, I, Hellstrøm, T, Hodges, CB, Irimia, A, Jha, RM, Johnson, PK, Koliatsos, VE, Levin, H, Li, LM, Lindsey, HM, Livny, A, Løvstad, M, Medaglia, J, Menon, DK, Mondello, S, Monti, MM, Newcombe, VFJ, Petroni, A, Ponsford, J, Sharp, D, Spitz, G, Westlye, LT, Thompson, PM, Dennis, EL, Tate, DF, Wilde, EA, Hillary, FG, Olsen, A, Babikian, T, Bigler, ED, Caeyenberghs, Karen, Conde, V, Dams-O’Connor, K, Dobryakova, E, Genova, H, Grafman, J, Håberg, AK, Heggland, I, Hellstrøm, T, Hodges, CB, Irimia, A, Jha, RM, Johnson, PK, Koliatsos, VE, Levin, H, Li, LM, Lindsey, HM, Livny, A, Løvstad, M, Medaglia, J, Menon, DK, Mondello, S, Monti, MM, Newcombe, VFJ, Petroni, A, Ponsford, J, Sharp, D, Spitz, G, Westlye, LT, Thompson, PM, Dennis, EL, Tate, DF, Wilde, EA, and Hillary, FG
Abstract: AbstractThe global burden of mortality and morbidity caused by traumatic brain injury (TBI) is significant, and the heterogeneity of TBI patients and the relatively small sample sizes of most current neuroimaging studies is a major challenge for scientific advances and clinical translation. The ENIGMA (Enhancing NeuroImaging Genetics through Meta-Analysis) Adult moderate/severe TBI (AMS-TBI) working group aims to be a driving force for new discoveries in AMS-TBI by providing researchers world-wide with an effective framework and platform for large-scale cross-border collaboration and data sharing. Based on the principles of transparency, rigor, reproducibility and collaboration, we will facilitate the development and dissemination of multiscale and big data analysis pipelines for harmonized analyses in AMS-TBI using structural and functional neuroimaging in combination with non-imaging biomarkers, genetics, as well as clinical and behavioral measures. Ultimately, we will offer investigators an unprecedented opportunity to test important hypotheses about recovery and morbidity in AMS-TBI by taking advantage of our robust methods for large-scale neuroimaging data analysis. In this consensus statement we outline the working group’s short-term, intermediate, and long-term goals.
Published: 2021

28. Identifying multimodal signatures underlying the somatic comorbidity of psychosis: the COMMITMENT roadmap

Author: Schwarz, E, Alnaes, D, Andreassen, OA, Cao, H, Chen, J, Degenhardt, F, Doncevic, D, Dwyer, D, Eils, R, Erdmann, J, Herrmann, C, Hofmann-Apitius, M, Kaufmann, T, Koutsouleris, N, Kodamullil, AT, Khuntia, A, Mucha, S, Noethen, MM, Paul, R, Pedersen, ML, Quintero, A, Schunkert, H, Sharma, A, Tost, H, Westlye, LT, Zhang, Y, Meyer-Lindenberg, A, Schwarz, E, Alnaes, D, Andreassen, OA, Cao, H, Chen, J, Degenhardt, F, Doncevic, D, Dwyer, D, Eils, R, Erdmann, J, Herrmann, C, Hofmann-Apitius, M, Kaufmann, T, Koutsouleris, N, Kodamullil, AT, Khuntia, A, Mucha, S, Noethen, MM, Paul, R, Pedersen, ML, Quintero, A, Schunkert, H, Sharma, A, Tost, H, Westlye, LT, Zhang, Y, and Meyer-Lindenberg, A
Published: 2021

29. 1q21.1 distal copy number variants are associated with cerebral and cognitive alterations in humans

Author: Sonderby, IE, van der Meer, D, Moreau, C, Kaufmann, T, Walters, GB, Ellegaard, M, Abdellaoui, A, Ames, D, Amunts, K, Andersson, M, Armstrong, NJ, Bernard, M, Blackburn, NB, Blangero, J, Boomsma, DI, Brodaty, H, Brouwer, RM, Buelow, R, Boen, R, Cahn, W, Calhoun, VD, Caspers, S, Ching, CRK, Cichon, S, Ciufolini, S, Crespo-Facorro, B, Curran, JE, Dale, AM, Dalvie, S, Dazzan, P, de Geus, EJC, de Zubicaray, GI, de Zwarte, SMC, Desrivieres, S, Doherty, JL, Donohoe, G, Draganski, B, Ehrlich, S, Eising, E, Espeseth, T, Fejgin, K, Fisher, SE, Fladby, T, Frei, O, Frouin, V, Fukunaga, M, Gareau, T, Ge, T, Glahn, DC, Grabe, HJ, Groenewold, NA, Gustafsson, O, Haavik, J, Haberg, AK, Hall, J, Hashimoto, R, Hehir-Kwa, JY, Hibar, DP, Hillegers, MHJ, Hoffmann, P, Holleran, L, Holmes, AJ, Homuth, G, Hottenga, J-J, Hulshoff Pol, HE, Ikeda, M, Jahanshad, N, Jockwitz, C, Johansson, S, Joensson, EG, Jorgensen, NR, Kikuchi, M, Knowles, EEM, Kumar, K, Le Hellard, S, Leu, C, Linden, DEJ, Liu, J, Lundervold, A, Lundervold, AJ, Maillard, AM, Martin, NG, Martin-Brevet, S, Mather, KA, Mathias, SR, McMahon, KL, McRae, AF, Medland, SE, Meyer-Lindenberg, A, Moberget, T, Modenato, C, Sanchez, JM, Morris, DW, Muehleisen, TW, Murray, RM, Nielsen, J, Nordvik, JE, Nyberg, L, Loohuis, LMO, Ophoff, RA, Owen, MJ, Paus, T, Pausova, Z, Peralta, JM, Pike, GB, Prieto, C, Quinlan, EB, Reinbold, CS, Marques, TR, Rucker, JJH, Sachdev, PS, Sando, SB, Schofield, PR, Schork, AJ, Schumann, G, Shin, J, Shumskaya, E, Silva, AI, Sisodiya, SM, Steen, VM, Stein, DJ, Strike, LT, Suzuki, IK, Tamnes, CK, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Uhlmann, A, Ulfarsson, MO, van 't Ent, D, van den Bree, MBM, Vanderhaeghen, P, Vassos, E, Wen, W, Wittfeld, K, Wright, MJ, Agartz, I, Djurovic, S, Westlye, LT, Stefansson, H, Stefansson, K, Jacquemont, S, Thompson, PM, Andreassen, OA, Sonderby, IE, van der Meer, D, Moreau, C, Kaufmann, T, Walters, GB, Ellegaard, M, Abdellaoui, A, Ames, D, Amunts, K, Andersson, M, Armstrong, NJ, Bernard, M, Blackburn, NB, Blangero, J, Boomsma, DI, Brodaty, H, Brouwer, RM, Buelow, R, Boen, R, Cahn, W, Calhoun, VD, Caspers, S, Ching, CRK, Cichon, S, Ciufolini, S, Crespo-Facorro, B, Curran, JE, Dale, AM, Dalvie, S, Dazzan, P, de Geus, EJC, de Zubicaray, GI, de Zwarte, SMC, Desrivieres, S, Doherty, JL, Donohoe, G, Draganski, B, Ehrlich, S, Eising, E, Espeseth, T, Fejgin, K, Fisher, SE, Fladby, T, Frei, O, Frouin, V, Fukunaga, M, Gareau, T, Ge, T, Glahn, DC, Grabe, HJ, Groenewold, NA, Gustafsson, O, Haavik, J, Haberg, AK, Hall, J, Hashimoto, R, Hehir-Kwa, JY, Hibar, DP, Hillegers, MHJ, Hoffmann, P, Holleran, L, Holmes, AJ, Homuth, G, Hottenga, J-J, Hulshoff Pol, HE, Ikeda, M, Jahanshad, N, Jockwitz, C, Johansson, S, Joensson, EG, Jorgensen, NR, Kikuchi, M, Knowles, EEM, Kumar, K, Le Hellard, S, Leu, C, Linden, DEJ, Liu, J, Lundervold, A, Lundervold, AJ, Maillard, AM, Martin, NG, Martin-Brevet, S, Mather, KA, Mathias, SR, McMahon, KL, McRae, AF, Medland, SE, Meyer-Lindenberg, A, Moberget, T, Modenato, C, Sanchez, JM, Morris, DW, Muehleisen, TW, Murray, RM, Nielsen, J, Nordvik, JE, Nyberg, L, Loohuis, LMO, Ophoff, RA, Owen, MJ, Paus, T, Pausova, Z, Peralta, JM, Pike, GB, Prieto, C, Quinlan, EB, Reinbold, CS, Marques, TR, Rucker, JJH, Sachdev, PS, Sando, SB, Schofield, PR, Schork, AJ, Schumann, G, Shin, J, Shumskaya, E, Silva, AI, Sisodiya, SM, Steen, VM, Stein, DJ, Strike, LT, Suzuki, IK, Tamnes, CK, Teumer, A, Thalamuthu, A, Tordesillas-Gutierrez, D, Uhlmann, A, Ulfarsson, MO, van 't Ent, D, van den Bree, MBM, Vanderhaeghen, P, Vassos, E, Wen, W, Wittfeld, K, Wright, MJ, Agartz, I, Djurovic, S, Westlye, LT, Stefansson, H, Stefansson, K, Jacquemont, S, Thompson, PM, and Andreassen, OA
Abstract: Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.
Published: 2021

30. Association of Structural Magnetic Resonance Imaging Measures With Psychosis Onset in Individuals at Clinical High Risk for Developing Psychosis An ENIGMA Working Group Mega-analysis

Author: Jalbrzikowski, M, Hayes, RA, Wood, SJ, Nordholm, D, Zhou, JH, Fusar-Poli, P, Uhlhaas, PJ, Takahashi, T, Sugranyes, G, Kwak, YB, Mathalon, DH, Katagiri, N, Hooker, CI, Smigielski, L, Colibazzi, T, Via, E, Tang, J, Koike, S, Rasser, PE, Michel, C, Lebedeva, I, Hegelstad, WTV, de la Fuente-Sandoval, C, Waltz, JA, Mizrahi, R, Corcoran, CM, Resch, F, Tamnes, CK, Haas, SS, Lemmers-Jansen, ILJ, Agartz, I, Allen, P, Amminger, GP, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Baldwin, H, Bartholomeusz, CF, Borgwardt, S, Catalano, S, Chee, MWL, Chen, X, Cho, KIK, Cooper, RE, Cropley, VL, Dolz, M, Ebdrup, BH, Fortea, A, Glenthoj, LB, Glenthoj, BY, de Haan, L, Hamilton, HK, Harris, MA, Haut, KM, He, Y, Heekeren, K, Heinz, A, Hubl, D, Hwang, WJ, Kaess, M, Kasai, K, Kim, M, Kindler, J, Klaunig, MJ, Koppel, A, Kristensen, TD, Kwon, JS, Lawrie, SM, Lee, J, Leon-Ortiz, P, Lin, A, Loewy, RL, Ma, X, McGorry, P, McGuire, P, Mizuno, M, Moller, P, Moncada-Habib, T, Munoz-Samons, D, Nelson, B, Nemoto, T, Nordentoft, M, Omelchenko, MA, Oppedal, K, Ouyang, L, Pantelis, C, Pariente, JC, Raghava, JM, Reyes-Madrigal, F, Roach, BJ, Rossberg, JI, Rossler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Schiffman, J, Schlagenhauf, F, Schmidt, A, Sorensen, ME, Suzuki, M, Theodoridou, A, Tomyshev, AS, Tor, J, Vaernes, TG, Velakoulis, D, Venegoni, GD, Vinogradov, S, Wenneberg, C, Westlye, LT, Yamasue, H, Yuan, L, Yung, AR, van Amelsvoort, TAMJ, Turner, JA, van Erp, TGM, Thompson, PM, Hernaus, D, Jalbrzikowski, M, Hayes, RA, Wood, SJ, Nordholm, D, Zhou, JH, Fusar-Poli, P, Uhlhaas, PJ, Takahashi, T, Sugranyes, G, Kwak, YB, Mathalon, DH, Katagiri, N, Hooker, CI, Smigielski, L, Colibazzi, T, Via, E, Tang, J, Koike, S, Rasser, PE, Michel, C, Lebedeva, I, Hegelstad, WTV, de la Fuente-Sandoval, C, Waltz, JA, Mizrahi, R, Corcoran, CM, Resch, F, Tamnes, CK, Haas, SS, Lemmers-Jansen, ILJ, Agartz, I, Allen, P, Amminger, GP, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Baldwin, H, Bartholomeusz, CF, Borgwardt, S, Catalano, S, Chee, MWL, Chen, X, Cho, KIK, Cooper, RE, Cropley, VL, Dolz, M, Ebdrup, BH, Fortea, A, Glenthoj, LB, Glenthoj, BY, de Haan, L, Hamilton, HK, Harris, MA, Haut, KM, He, Y, Heekeren, K, Heinz, A, Hubl, D, Hwang, WJ, Kaess, M, Kasai, K, Kim, M, Kindler, J, Klaunig, MJ, Koppel, A, Kristensen, TD, Kwon, JS, Lawrie, SM, Lee, J, Leon-Ortiz, P, Lin, A, Loewy, RL, Ma, X, McGorry, P, McGuire, P, Mizuno, M, Moller, P, Moncada-Habib, T, Munoz-Samons, D, Nelson, B, Nemoto, T, Nordentoft, M, Omelchenko, MA, Oppedal, K, Ouyang, L, Pantelis, C, Pariente, JC, Raghava, JM, Reyes-Madrigal, F, Roach, BJ, Rossberg, JI, Rossler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Schiffman, J, Schlagenhauf, F, Schmidt, A, Sorensen, ME, Suzuki, M, Theodoridou, A, Tomyshev, AS, Tor, J, Vaernes, TG, Velakoulis, D, Venegoni, GD, Vinogradov, S, Wenneberg, C, Westlye, LT, Yamasue, H, Yuan, L, Yung, AR, van Amelsvoort, TAMJ, Turner, JA, van Erp, TGM, Thompson, PM, and Hernaus, D
Abstract: IMPORTANCE: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. OBJECTIVE: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. MAIN OUTCOMES AND MEASURES: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). RESULTS: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with t
Published: 2021

31. Frequency drift in MR spectroscopy at 3T

Author: Hui, SCN, Mikkelsen, M, Zollner, HJ, Ahluwalia, V, Alcauter, S, Baltusis, L, Barany, DA, Barlow, LR, Becker, R, Berman, J, Berrington, A, Bhattacharyya, PK, Blicher, JU, Bogner, W, Brown, MS, Calhoun, VD, Castillo, R, Cecil, KM, Choi, YB, Chu, WCW, Clarke, WT, Craven, AR, Cuypers, K, Dacko, M, de la Fuente-Sandoval, C, Desmond, P, Domagalik, A, Dumont, J, Duncan, NW, Dydak, U, Dyke, K, Edmondson, DA, Ende, G, Ersland, L, Evans, CJ, Fermin, ASR, Ferretti, A, Fillmer, A, Gong, T, Greenhouse, I, Grist, JT, Gu, M, Harris, AD, Hatz, K, Heba, S, Heckova, E, Hegarty, JP, Heise, K-F, Honda, S, Jacobson, A, Jansen, JFA, Jenkins, CW, Johnston, SJ, Juchem, C, Kangarlu, A, Kerr, AB, Landheer, K, Lange, T, Lee, P, Levendovszky, SR, Limperopoulos, C, Liu, F, Lloyd, W, Lythgoe, DJ, Machizawa, MG, MacMillan, EL, Maddock, RJ, Manzhurtsev, A, Martinez-Gudino, ML, Miller, JJ, Mirzakhanian, H, Moreno-Ortega, M, Mullins, PG, Nakajima, S, Near, J, Noeske, R, Nordhoy, W, Oeltzschner, G, Osorio-Duran, R, Otaduy, MCG, Pasaye, EH, Peeters, R, Peltier, SJ, Pilatus, U, Polomac, N, Porges, EC, Pradhan, S, Prisciandaro, JJ, Puts, NA, Rae, CD, Reyes-Madrigal, F, Roberts, TPL, Robertson, CE, Rosenberg, JT, Rotaru, D-G, Tuura, RLO, Saleh, MG, Sandberg, K, Sangill, R, Schembri, K, Schrantee, A, Semenova, NA, Singel, D, Sitnikov, R, Smith, J, Song, Y, Stark, C, Stoffers, D, Swinnen, SP, Tain, R, Tanase, C, Tapper, S, Tegenthoff, M, Thiel, T, Thioux, M, Truong, P, van Dijk, P, Vella, N, Vidyasagar, R, Vovk, A, Wang, G, Westlye, LT, Wilbur, TK, Willoughby, WR, Wilson, M, Wittsack, H-J, Woods, AJ, Wu, Y-C, Xu, J, Lopez, MY, Yeung, DKW, Zhao, Q, Zhou, X, Zupan, G, Edden, RAE, Hui, SCN, Mikkelsen, M, Zollner, HJ, Ahluwalia, V, Alcauter, S, Baltusis, L, Barany, DA, Barlow, LR, Becker, R, Berman, J, Berrington, A, Bhattacharyya, PK, Blicher, JU, Bogner, W, Brown, MS, Calhoun, VD, Castillo, R, Cecil, KM, Choi, YB, Chu, WCW, Clarke, WT, Craven, AR, Cuypers, K, Dacko, M, de la Fuente-Sandoval, C, Desmond, P, Domagalik, A, Dumont, J, Duncan, NW, Dydak, U, Dyke, K, Edmondson, DA, Ende, G, Ersland, L, Evans, CJ, Fermin, ASR, Ferretti, A, Fillmer, A, Gong, T, Greenhouse, I, Grist, JT, Gu, M, Harris, AD, Hatz, K, Heba, S, Heckova, E, Hegarty, JP, Heise, K-F, Honda, S, Jacobson, A, Jansen, JFA, Jenkins, CW, Johnston, SJ, Juchem, C, Kangarlu, A, Kerr, AB, Landheer, K, Lange, T, Lee, P, Levendovszky, SR, Limperopoulos, C, Liu, F, Lloyd, W, Lythgoe, DJ, Machizawa, MG, MacMillan, EL, Maddock, RJ, Manzhurtsev, A, Martinez-Gudino, ML, Miller, JJ, Mirzakhanian, H, Moreno-Ortega, M, Mullins, PG, Nakajima, S, Near, J, Noeske, R, Nordhoy, W, Oeltzschner, G, Osorio-Duran, R, Otaduy, MCG, Pasaye, EH, Peeters, R, Peltier, SJ, Pilatus, U, Polomac, N, Porges, EC, Pradhan, S, Prisciandaro, JJ, Puts, NA, Rae, CD, Reyes-Madrigal, F, Roberts, TPL, Robertson, CE, Rosenberg, JT, Rotaru, D-G, Tuura, RLO, Saleh, MG, Sandberg, K, Sangill, R, Schembri, K, Schrantee, A, Semenova, NA, Singel, D, Sitnikov, R, Smith, J, Song, Y, Stark, C, Stoffers, D, Swinnen, SP, Tain, R, Tanase, C, Tapper, S, Tegenthoff, M, Thiel, T, Thioux, M, Truong, P, van Dijk, P, Vella, N, Vidyasagar, R, Vovk, A, Wang, G, Westlye, LT, Wilbur, TK, Willoughby, WR, Wilson, M, Wittsack, H-J, Woods, AJ, Wu, Y-C, Xu, J, Lopez, MY, Yeung, DKW, Zhao, Q, Zhou, X, Zupan, G, and Edden, RAE
Abstract: PURPOSE: Heating of gradient coils and passive shim components is a common cause of instability in the B0 field, especially when gradient intensive sequences are used. The aim of the study was to set a benchmark for typical drift encountered during MR spectroscopy (MRS) to assess the need for real-time field-frequency locking on MRI scanners by comparing field drift data from a large number of sites. METHOD: A standardized protocol was developed for 80 participating sites using 99 3T MR scanners from 3 major vendors. Phantom water signals were acquired before and after an EPI sequence. The protocol consisted of: minimal preparatory imaging; a short pre-fMRI PRESS; a ten-minute fMRI acquisition; and a long post-fMRI PRESS acquisition. Both pre- and post-fMRI PRESS were non-water suppressed. Real-time frequency stabilization/adjustment was switched off when appropriate. Sixty scanners repeated the protocol for a second dataset. In addition, a three-hour post-fMRI MRS acquisition was performed at one site to observe change of gradient temperature and drift rate. Spectral analysis was performed using MATLAB. Frequency drift in pre-fMRI PRESS data were compared with the first 5:20 minutes and the full 30:00 minutes of data after fMRI. Median (interquartile range) drifts were measured and showed in violin plot. Paired t-tests were performed to compare frequency drift pre- and post-fMRI. A simulated in vivo spectrum was generated using FID-A to visualize the effect of the observed frequency drifts. The simulated spectrum was convolved with the frequency trace for the most extreme cases. Impacts of frequency drifts on NAA and GABA were also simulated as a function of linear drift. Data from the repeated protocol were compared with the corresponding first dataset using Pearson's and intraclass correlation coefficients (ICC). RESULTS: Of the data collected from 99 scanners, 4 were excluded due to various reasons. Thus, data from 95 scanners were ultimately analyzed. For the f
Published: 2021

32. Smaller spared subcortical nuclei are associated with worse post-stroke sensorimotor outcomes in 28 cohorts worldwide

Author: Liew, S-L, Zavaliangos-Petropulu, A, Schweighofer, N, Jahanshad, N, Lang, CE, Lohse, KR, Banaj, N, Barisano, G, Baugh, LA, Bhattacharya, AK, Bigjahan, B, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Byblow, WD, Cassidy, JM, Charalambous, CC, Ciullo, V, Conforto, AB, Craddock, RC, Dula, AN, Egorova, N, Feng, W, Fercho, KA, Gregory, CM, Hanlon, CA, Hayward, KS, Holguin, JA, Hordacre, B, Hwang, DH, Kautz, SA, Khlif, MS, Kim, B, Kim, H, Kuceyeski, A, Lo, B, Liu, J, Lin, D, Lotze, M, MacIntosh, BJ, Margetis, JL, Mohamed, FB, Nordvik, JE, Petoe, MA, Piras, F, Raju, S, Ramos-Murguialday, A, Revill, KP, Roberts, P, Robertson, AD, Schambra, HM, Seo, NJ, Shiroishi, MS, Soekadar, SR, Spalletta, G, Stinear, CM, Suri, A, Tang, WK, Thielman, GT, Thijs, VN, Vecchio, D, Ward, NS, Westlye, LT, Winstein, CJ, Wittenberg, GF, Wong, KA, Yu, C, Wolf, SL, Cramer, SC, Thompson, PM, Liew, S-L, Zavaliangos-Petropulu, A, Schweighofer, N, Jahanshad, N, Lang, CE, Lohse, KR, Banaj, N, Barisano, G, Baugh, LA, Bhattacharya, AK, Bigjahan, B, Borich, MR, Boyd, LA, Brodtmann, A, Buetefisch, CM, Byblow, WD, Cassidy, JM, Charalambous, CC, Ciullo, V, Conforto, AB, Craddock, RC, Dula, AN, Egorova, N, Feng, W, Fercho, KA, Gregory, CM, Hanlon, CA, Hayward, KS, Holguin, JA, Hordacre, B, Hwang, DH, Kautz, SA, Khlif, MS, Kim, B, Kim, H, Kuceyeski, A, Lo, B, Liu, J, Lin, D, Lotze, M, MacIntosh, BJ, Margetis, JL, Mohamed, FB, Nordvik, JE, Petoe, MA, Piras, F, Raju, S, Ramos-Murguialday, A, Revill, KP, Roberts, P, Robertson, AD, Schambra, HM, Seo, NJ, Shiroishi, MS, Soekadar, SR, Spalletta, G, Stinear, CM, Suri, A, Tang, WK, Thielman, GT, Thijs, VN, Vecchio, D, Ward, NS, Westlye, LT, Winstein, CJ, Wittenberg, GF, Wong, KA, Yu, C, Wolf, SL, Cramer, SC, and Thompson, PM
Abstract: Up to two-thirds of stroke survivors experience persistent sensorimotor impairments. Recovery relies on the integrity of spared brain areas to compensate for damaged tissue. Deep grey matter structures play a critical role in the control and regulation of sensorimotor circuits. The goal of this work is to identify associations between volumes of spared subcortical nuclei and sensorimotor behaviour at different timepoints after stroke. We pooled high-resolution T1-weighted MRI brain scans and behavioural data in 828 individuals with unilateral stroke from 28 cohorts worldwide. Cross-sectional analyses using linear mixed-effects models related post-stroke sensorimotor behaviour to non-lesioned subcortical volumes (Bonferroni-corrected, P < 0.004). We tested subacute (≤90 days) and chronic (≥180 days) stroke subgroups separately, with exploratory analyses in early stroke (≤21 days) and across all time. Sub-analyses in chronic stroke were also performed based on class of sensorimotor deficits (impairment, activity limitations) and side of lesioned hemisphere. Worse sensorimotor behaviour was associated with a smaller ipsilesional thalamic volume in both early (n = 179; d = 0.68) and subacute (n = 274, d = 0.46) stroke. In chronic stroke (n = 404), worse sensorimotor behaviour was associated with smaller ipsilesional putamen (d = 0.52) and nucleus accumbens (d = 0.39) volumes, and a larger ipsilesional lateral ventricle (d = -0.42). Worse chronic sensorimotor impairment specifically (measured by the Fugl-Meyer Assessment; n = 256) was associated with smaller ipsilesional putamen (d = 0.72) and larger lateral ventricle (d = -0.41) volumes, while several measures of activity limitations (n = 116) showed no significant relationships. In the full cohort across all time (n = 828), sensorimotor behaviour was associated with the volumes of the ipsilesional nucleus accumbens (d = 0.23), putamen (d = 0.33), thalamus (d = 0.33) and lateral ventricle (d = -0.23). We demonstrate sig
Published: 2021

33. Cortical thickness and resting-state cardiac function across the lifespan: A cross-sectional pooled mega-analysis

Author: Koenig, J, Abler, B, Agartz, I, akerstedt, T, Andreassen, OA, Anthony, M, Baer, K-J, Bertsch, K, Brown, RC, Brunner, R, Carnevali, L, Critchley, HD, Cullen, KR, de Geus, EJC, de la Cruz, F, Dziobek, I, Ferger, MD, Fischer, H, Flor, H, Gaebler, M, Gianaros, PJ, Giummarra, MJ, Greening, SG, Guendelman, S, Heathers, JAJ, Herpertz, SC, Hu, MX, Jentschke, S, Kaess, M, Kaufmann, T, Klimes-Dougan, B, Koelsch, S, Krauch, M, Kumral, D, Lamers, F, Lee, T-H, Lekander, M, Lin, F, Lotze, M, Makovac, E, Mancini, M, Mancke, F, Mansson, KNT, Manuck, SB, Mather, M, Meeten, F, Min, J, Mueller, B, Muench, V, Nees, F, Nga, L, Nilsonne, G, Ordonez Acuna, D, Osnes, B, Ottaviani, C, Penninx, BWJH, Ponzio, A, Poudel, GR, Reinelt, J, Ren, P, Sakaki, M, Schumann, A, Sorensen, L, Specht, K, Straub, J, Tamm, S, Thai, M, Thayer, JF, Ubani, B, van Der Mee, DJ, van Velzen, LS, Ventura-Bort, C, Villringer, A, Watson, DR, Wei, L, Wendt, J, Schreiner, MW, Westlye, LT, Weymar, M, Winkelmann, T, Wu, G-R, Yoo, HJ, Quintana, DS, Koenig, J, Abler, B, Agartz, I, akerstedt, T, Andreassen, OA, Anthony, M, Baer, K-J, Bertsch, K, Brown, RC, Brunner, R, Carnevali, L, Critchley, HD, Cullen, KR, de Geus, EJC, de la Cruz, F, Dziobek, I, Ferger, MD, Fischer, H, Flor, H, Gaebler, M, Gianaros, PJ, Giummarra, MJ, Greening, SG, Guendelman, S, Heathers, JAJ, Herpertz, SC, Hu, MX, Jentschke, S, Kaess, M, Kaufmann, T, Klimes-Dougan, B, Koelsch, S, Krauch, M, Kumral, D, Lamers, F, Lee, T-H, Lekander, M, Lin, F, Lotze, M, Makovac, E, Mancini, M, Mancke, F, Mansson, KNT, Manuck, SB, Mather, M, Meeten, F, Min, J, Mueller, B, Muench, V, Nees, F, Nga, L, Nilsonne, G, Ordonez Acuna, D, Osnes, B, Ottaviani, C, Penninx, BWJH, Ponzio, A, Poudel, GR, Reinelt, J, Ren, P, Sakaki, M, Schumann, A, Sorensen, L, Specht, K, Straub, J, Tamm, S, Thai, M, Thayer, JF, Ubani, B, van Der Mee, DJ, van Velzen, LS, Ventura-Bort, C, Villringer, A, Watson, DR, Wei, L, Wendt, J, Schreiner, MW, Westlye, LT, Weymar, M, Winkelmann, T, Wu, G-R, Yoo, HJ, and Quintana, DS
Abstract: Understanding the association between autonomic nervous system [ANS] function and brain morphology across the lifespan provides important insights into neurovisceral mechanisms underlying health and disease. Resting-state ANS activity, indexed by measures of heart rate [HR] and its variability [HRV] has been associated with brain morphology, particularly cortical thickness [CT]. While findings have been mixed regarding the anatomical distribution and direction of the associations, these inconsistencies may be due to sex and age differences in HR/HRV and CT. Previous studies have been limited by small sample sizes, which impede the assessment of sex differences and aging effects on the association between ANS function and CT. To overcome these limitations, 20 groups worldwide contributed data collected under similar protocols of CT assessment and HR/HRV recording to be pooled in a mega-analysis (N = 1,218 (50.5% female), mean age 36.7 years (range: 12-87)). Findings suggest a decline in HRV as well as CT with increasing age. CT, particularly in the orbitofrontal cortex, explained additional variance in HRV, beyond the effects of aging. This pattern of results may suggest that the decline in HRV with increasing age is related to a decline in orbitofrontal CT. These effects were independent of sex and specific to HRV; with no significant association between CT and HR. Greater CT across the adult lifespan may be vital for the maintenance of healthy cardiac regulation via the ANS-or greater cardiac vagal activity as indirectly reflected in HRV may slow brain atrophy. Findings reveal an important association between CT and cardiac parasympathetic activity with implications for healthy aging and longevity that should be studied further in longitudinal research.
Published: 2021

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

Author: Tahmasian, M, Aleman, A, Andreassen, OA, Arab, Z, Baillet, M, Benedetti, F, Bresser, T, Bright, J, Chee, MWL, Chylinski, D, Cheng, W, Deantoni, M, Dresler, M, Eickhoff, SB, Eickhoff, CR, Elvsashagen, T, Feng, J, Foster-Dingley, JC, Ganjgahi, H, Grabe, HJ, Groenewold, NA, Ho, TC, Hong, SB, Houenou, J, Irungu, B, Jahanshad, N, Khazaie, H, Kim, H, Koshmanova, E, Kocevska, D, Kochunov, P, Lakbila-Kamal, O, Leerssen, J, Li, M, Luik, A, Muto, V, Narbutas, J, Nilsonne, G, O'Callaghan, VS, Olsen, A, Osorio, RS, Poletti, S, Poudel, G, Reesen, JE, Reneman, L, Reyt, M, Riemann, D, Rosenzweig, I, Rostampour, M, Saberi, A, Schiel, J, Schmidt, C, Schrantee, A, Sciberras, E, Silk, TJ, Sim, K, Smevik, H, Soares, JC, Spiegelhalder, K, Stein, DJ, Talwar, P, Tamm, S, Teresi, GL, Valk, SL, Van Someren, E, Vandewalle, G, Van Egroo, M, Volzke, H, Walter, M, Wassing, R, Weber, FD, Weihs, A, Westlye, LT, Wright, MJ, Wu, M-J, Zak, N, Zarei, M, Tahmasian, M, Aleman, A, Andreassen, OA, Arab, Z, Baillet, M, Benedetti, F, Bresser, T, Bright, J, Chee, MWL, Chylinski, D, Cheng, W, Deantoni, M, Dresler, M, Eickhoff, SB, Eickhoff, CR, Elvsashagen, T, Feng, J, Foster-Dingley, JC, Ganjgahi, H, Grabe, HJ, Groenewold, NA, Ho, TC, Hong, SB, Houenou, J, Irungu, B, Jahanshad, N, Khazaie, H, Kim, H, Koshmanova, E, Kocevska, D, Kochunov, P, Lakbila-Kamal, O, Leerssen, J, Li, M, Luik, A, Muto, V, Narbutas, J, Nilsonne, G, O'Callaghan, VS, Olsen, A, Osorio, RS, Poletti, S, Poudel, G, Reesen, JE, Reneman, L, Reyt, M, Riemann, D, Rosenzweig, I, Rostampour, M, Saberi, A, Schiel, J, Schmidt, C, Schrantee, A, Sciberras, E, Silk, TJ, Sim, K, Smevik, H, Soares, JC, Spiegelhalder, K, Stein, DJ, Talwar, P, Tamm, S, Teresi, GL, Valk, SL, Van Someren, E, Vandewalle, G, Van Egroo, M, Volzke, H, Walter, M, Wassing, R, Weber, FD, Weihs, A, Westlye, LT, Wright, MJ, Wu, M-J, Zak, N, and Zarei, M
Abstract: Neuroimaging and genetics studies have advanced our understanding of the neurobiology of sleep and its disorders. However, individual studies usually have limitations to identifying consistent and reproducible effects, including modest sample sizes, heterogeneous clinical characteristics and varied methodologies. These issues call for a large-scale multi-centre effort in sleep research, in order to increase the number of samples, and harmonize the methods of data collection, preprocessing and analysis using pre-registered well-established protocols. The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) consortium provides a powerful collaborative framework for combining datasets across individual sites. Recently, we have launched the ENIGMA-Sleep working group with the collaboration of several institutes from 15 countries to perform large-scale worldwide neuroimaging and genetics studies for better understanding the neurobiology of impaired sleep quality in population-based healthy individuals, the neural consequences of sleep deprivation, pathophysiology of sleep disorders, as well as neural correlates of sleep disturbances across various neuropsychiatric disorders. In this introductory review, we describe the details of our currently available datasets and our ongoing projects in the ENIGMA-Sleep group, and discuss both the potential challenges and opportunities of a collaborative initiative in sleep medicine.
Published: 2021

35. Widespread reduced axial diffusivity in left frontotemporal white matter and corpus callosum in adults with bipolar II disorder: RC12

Author: Elvsåshagen, T, Westlye, LT, Bøen, E, Courivau, F, Hol, PK, Rasmussen, I, Andersson, S, Boye, B, Andreassen, OA, and Malt, UF
Published: 2011

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

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

37. The genetic architecture of the human cerebral cortex

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

38. Cortical Brain Abnormalities in 4474 Individuals With Schizophrenia and 5098 Control Subjects via the Enhancing Neuro Imaging Genetics Through Meta Analysis (ENIGMA) Consortium

Author: van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, W, Glahn, DC, Pearlson, GD, Yao, N, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Hulshoff Pol, HE, Kahn, RS, Ophoff, RA, van Haren, NEM, Andreassen, OA, Dale, AM, Doan, NT, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jørgensen, KN, Lagerberg, TV, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santiañez, R, Tordesillas-Gutiérrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quidé, Y, Schall, U, and Scott, RJ
Abstract: © 2018 Society of Biological Psychiatry Background: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. Methods: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11–78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10–87 years; 53% male) assessed with standardized methods at 39 centers worldwide. Results: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = −0.530/−0.516) and smaller surface area (left/right hemisphere: Cohen's d = −0.251/−0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. Conclusions: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.
Published: 2018
Full Text: View/download PDF

39. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group

Author: Kelly, S, Jahanshad, N, Zalesky, A, Kochunov, P, Agartz, I, Alloza, C, Andreassen, OA, Arango, C, Banaj, N, Bouix, S, Bousman, CA, Brouwer, RM, Bruggemann, J, Bustillo, J, Cahn, W, Calhoun, V, Cannon, D, Carr, V, Catts, S, Chen, J, Chen, J-X, Chen, X, Chiapponi, C, Cho, KK, Ciullo, V, Corvin, AS, Crespo-Facorro, B, Cropley, V, De Rossi, P, Diaz-Caneja, CM, Dickie, EW, Ehrlich, S, Fan, F-M, Faskowitz, J, Fatouros-Bergman, H, Flyckt, L, Ford, JM, Fouche, J-P, Fukunaga, M, Gill, M, Glahn, DC, Gollub, R, Goudzwaard, ED, Guo, H, Gur, RE, Gur, RC, Gurholt, TP, Hashimoto, R, Hatton, SN, Henskens, FA, Hibar, DP, Hickie, IB, Hong, LE, Horacek, J, Howells, FM, Pol, HEH, Hyde, CL, Isaev, D, Jablensky, A, Jansen, PR, Janssen, J, Jonsson, EG, Jung, LA, Kahn, RS, Kikinis, Z, Liu, K, Klauser, P, Knoechel, C, Kubicki, M, Lagopoulos, J, Langen, C, Lawrie, S, Lenroot, RK, Lim, KO, Lopez-Jaramillo, C, Lyall, A, Magnotta, V, Mandl, RCW, Mathalon, DH, McCarley, RW, McCarthy-Jones, S, McDonald, C, McEwen, S, McIntosh, A, Melicher, T, Mesholam-Gately, R, Michie, PT, Mowry, B, Mueller, BA, Newell, DT, O'Donnell, P, Oertel-Knoechel, V, Oestreich, L, Paciga, SA, Pantelis, C, Pasternak, O, Pearlson, G, Pellicano, GR, Pereira, A, Zapata, JP, Piras, F, Potkin, SG, Preda, A, Rasser, PE, Roalf, DR, Roiz, R, Roos, A, Rotenberg, D, Satterthwaite, TD, Savadjiev, P, Schall, U, Scott, RJ, Seal, ML, Seidman, LJ, Weickert, CS, Whelan, CD, Shenton, ME, Kwon, JS, Spalletta, G, Spaniel, F, Sprooten, E, Stablein, M, Stein, DJ, Sundram, S, Tan, Y, Tan, S, Tang, S, Temmingh, HS, Westlye, LT, Tonnesen, S, Tordesillas-Gutierrez, D, Doan, NT, Vaidya, J, van Haren, NEM, Vargas, CD, Vecchio, D, Velakoulis, D, Voineskos, A, Voyvodic, JQ, Wang, Z, Wan, P, Wei, D, Weickert, TW, Whalley, H, White, T, Whitford, TJ, Wojcik, JD, Xiang, H, Xie, Z, Yamamori, H, Yang, F, Yao, N, Zhang, G, Zhao, J, van Erp, TGM, Turner, J, Thompson, PM, Donohoe, G, Kelly, S, Jahanshad, N, Zalesky, A, Kochunov, P, Agartz, I, Alloza, C, Andreassen, OA, Arango, C, Banaj, N, Bouix, S, Bousman, CA, Brouwer, RM, Bruggemann, J, Bustillo, J, Cahn, W, Calhoun, V, Cannon, D, Carr, V, Catts, S, Chen, J, Chen, J-X, Chen, X, Chiapponi, C, Cho, KK, Ciullo, V, Corvin, AS, Crespo-Facorro, B, Cropley, V, De Rossi, P, Diaz-Caneja, CM, Dickie, EW, Ehrlich, S, Fan, F-M, Faskowitz, J, Fatouros-Bergman, H, Flyckt, L, Ford, JM, Fouche, J-P, Fukunaga, M, Gill, M, Glahn, DC, Gollub, R, Goudzwaard, ED, Guo, H, Gur, RE, Gur, RC, Gurholt, TP, Hashimoto, R, Hatton, SN, Henskens, FA, Hibar, DP, Hickie, IB, Hong, LE, Horacek, J, Howells, FM, Pol, HEH, Hyde, CL, Isaev, D, Jablensky, A, Jansen, PR, Janssen, J, Jonsson, EG, Jung, LA, Kahn, RS, Kikinis, Z, Liu, K, Klauser, P, Knoechel, C, Kubicki, M, Lagopoulos, J, Langen, C, Lawrie, S, Lenroot, RK, Lim, KO, Lopez-Jaramillo, C, Lyall, A, Magnotta, V, Mandl, RCW, Mathalon, DH, McCarley, RW, McCarthy-Jones, S, McDonald, C, McEwen, S, McIntosh, A, Melicher, T, Mesholam-Gately, R, Michie, PT, Mowry, B, Mueller, BA, Newell, DT, O'Donnell, P, Oertel-Knoechel, V, Oestreich, L, Paciga, SA, Pantelis, C, Pasternak, O, Pearlson, G, Pellicano, GR, Pereira, A, Zapata, JP, Piras, F, Potkin, SG, Preda, A, Rasser, PE, Roalf, DR, Roiz, R, Roos, A, Rotenberg, D, Satterthwaite, TD, Savadjiev, P, Schall, U, Scott, RJ, Seal, ML, Seidman, LJ, Weickert, CS, Whelan, CD, Shenton, ME, Kwon, JS, Spalletta, G, Spaniel, F, Sprooten, E, Stablein, M, Stein, DJ, Sundram, S, Tan, Y, Tan, S, Tang, S, Temmingh, HS, Westlye, LT, Tonnesen, S, Tordesillas-Gutierrez, D, Doan, NT, Vaidya, J, van Haren, NEM, Vargas, CD, Vecchio, D, Velakoulis, D, Voineskos, A, Voyvodic, JQ, Wang, Z, Wan, P, Wei, D, Weickert, TW, Whalley, H, White, T, Whitford, TJ, Wojcik, JD, Xiang, H, Xie, Z, Yamamori, H, Yang, F, Yao, N, Zhang, G, Zhao, J, van Erp, TGM, Turner, J, Thompson, PM, and Donohoe, G
Abstract: The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2018

40. A common brain network links development, aging, and vulnerability to disease

Author: Douaud, G, Groves, AR, Tamnes, CK, Westlye, LT, Duff, EP, Engvig, A, Walhovd, KB, James, A, Gass, A, Monsch, AU, Matthews, PM, Fjell, AM, Smith, SM, and Johansen-Berg, H
Abstract: Several theories link processes of development and aging in humans. In neuroscience, one model posits for instance that healthy age-related brain degeneration mirrors development, with the areas of the brain thought to develop later also degenerating earlier. However, intrinsic evidence for such a link between healthy aging and development in brain structure remains elusive. Here, we show that a data-driven analysis of brain structural variation across 484 healthy participants (8-85 y) reveals a largely--but not only--transmodal network whose lifespan pattern of age-related change intrinsically supports this model of mirroring development and aging. We further demonstrate that this network of brain regions, which develops relatively late during adolescence and shows accelerated degeneration in old age compared with the rest of the brain, characterizes areas of heightened vulnerability to unhealthy developmental and aging processes, as exemplified by schizophrenia and Alzheimer's disease, respectively. Specifically, this network, while derived solely from healthy subjects, spatially recapitulates the pattern of brain abnormalities observed in both schizophrenia and Alzheimer's disease. This network is further associated in our large-scale healthy population with intellectual ability and episodic memory, whose impairment contributes to key symptoms of schizophrenia and Alzheimer's disease. Taken together, our results suggest that the common spatial pattern of abnormalities observed in these two disorders, which emerge at opposite ends of the life spectrum, might be influenced by the timing of their separate and distinct pathological processes in disrupting healthy cerebral development and aging, respectively.
Published: 2016
Full Text: View/download PDF

41. Erratum: Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium (Molecular Psychiatry (2015) DOI:10.1038/mp.2015.63)

Author: Van Erp, TGM, Hibar, DP, Rasmussen, JM, Glahn, DC, Pearlson, GD, Andreassen, OA, Agartz, I, Westlye, LT, Haukvik, UK, Dale, AM, Melle, I, Hartberg, CB, Gruber, O, Kraemer, B, Zilles, D, Donohoe, G, Kelly, S, Mcdonald, C, Morris, DW, Cannon, DM, Corvin, A, Machielsen, MWJ, Koenders, L, De Haan, L, Veltman, DJ, Satterthwaite, TD, Wolf, DH, Gur, RC, Gur, RE, Potkin, SG, Mathalon, DH, Mueller, BA, Preda, A, Macciardi, F, Ehrlich, S, Walton, E, Hass, J, Calhoun, VD, Bockholt, HJ, Sponheim, SR, Shoemaker, JM, Van Haren, NEM, Pol, HEH, Ophoff, RA, Kahn, RS, Roiz-Santiañez, R, Crespo-Facorro, B, Wang, L, Alpert, KI, Jönsson, EG, Dimitrova, R, Bois, C, Whalley, HC, Mcintosh, AM, Lawrie, SM, Hashimoto, R, Thompson, PM, and Turner, JA
Published: 2016
Full Text: View/download PDF

42. Large-scale genomics unveil polygenic architecture of human cortical surface area

Author: Chen, CH, Peng, Q, Schork, AJ, Lo, MT, Fan, CC, Wang, Y, Desikan, RS, Bettella, F, Hagler, DJ, Westlye, LT, Kremen, WS, Jernigan, TL, Le Hellard, S, Steen, VM, Espeseth, T, Huentelman, M, Håberg, AK, Agartz, I, Djurovic, S, Andreassen, OA, Schork, N, Dale, AM, McCabe, C, Chang, L, Akshoomoff, N, Newman, E, Ernst, T, Van Zijl, P, Kuperman, J, Murray, S, Bloss, C, Appelbaum, M, Gamst, A, Thompson, W, Bartsch, H, Weiner, M, Aisen, P, Petersen, R, Jack, CR, Jagust, W, Trojanowki, JQ, Toga, AW, Beckett, L, Green, RC, Saykin, AJ, Morris, J, Shaw, LM, Khachaturian, Z, Sorensen, G, Carrillo, M, Kuller, L, Raichle, M, Paul, S, Davies, P, Fillit, H, Hefti, F, Holtzman, D, Mesulman, MM, Potter, W, Snyder, PJ, Schwartz, A, Montine, T, Thomas, RG, Donohue, M, Walter, S, Gessert, D, Sather, T, Jiminez, G, Harvey, D, Bernstein, M, Fox, N, Thompson, P, Schuff, N, DeCarli, C, Borowski, B, Gunter, J, Senjem, M, Vemuri, P, Jones, D, Kantarci, K, Ward, C, Koeppe, RA, Foster, N, and Reiman, EM
Abstract: © 2015 Macmillan Publishers Limited. All rights reserved. Little is known about how genetic variation contributes to neuroanatomical variability, and whether particular genomic regions comprising genes or evolutionarily conserved elements are enriched for effects that influence brain morphology. Here, we examine brain imaging and single-nucleotide polymorphisms (SNPs) data from ∼ 2,700 individuals. We show that a substantial proportion of variation in cortical surface area is explained by additive effects of SNPs dispersed throughout the genome, with a larger heritable effect for visual and auditory sensory and insular cortices (h2 ∼ 0.45). Genome-wide SNPs collectively account for, on average, about half of twin heritability across cortical regions (N = 466 twins). We find enriched genetic effects in or near genes. We also observe that SNPs in evolutionarily more conserved regions contributed significantly to the heritability of cortical surface area, particularly, for medial and temporal cortical regions. SNPs in less conserved regions contributed more to occipital and dorsolateral prefrontal cortices.
Published: 2015
Full Text: View/download PDF

43. Common genetic variants influence human subcortical brain structures

Author: Hibar, DP, Stein, JL, Renteria, ME, Arias-Vasquez, A, Desrivières, S, Jahanshad, N, Toro, R, Wittfeld, K, Abramovic, L, Andersson, M, Aribisala, BS, Armstrong, NJ, Bernard, M, Bohlken, MM, Boks, MP, Bralten, J, Brown, AA, Mallar Chakravarty, M, Chen, Q, Ching, CRK, Cuellar-Partida, G, Den Braber, A, Giddaluru, S, Goldman, AL, Grimm, O, Guadalupe, T, Hass, J, Woldehawariat, G, Holmes, AJ, Hoogman, M, Janowitz, D, Jia, T, Kim, S, Klein, M, Kraemer, B, Lee, PH, Olde Loohuis, LM, Luciano, M, MacAre, C, Mather, KA, Mattheisen, M, Milaneschi, Y, Nho, K, Papmeyer, M, Ramasamy, A, Risacher, SL, Roiz-Santiañez, R, Rose, EJ, Salami, A, Sämann, PG, Schmaal, L, Schork, AJ, Shin, J, Strike, LT, Teumer, A, Van Donkelaar, MMJ, Van Eijk, KR, Walters, RK, Westlye, LT, and Whelan, CD
Abstract: ©2015 Macmillan Publishers Limited. All rights reserved. The highly complex structure of the human brain is strongly shaped by genetic influences. Subcortical brain regions form circuits with cortical areas to coordinate movement, learning, memory and motivation, and altered circuits can lead to abnormal behaviour and disease. To investigate how common genetic variants affect the structure of these brain regions, here we conduct genome-wide association studies of the volumes of seven subcortical regions and the intracranial volume derived from magnetic resonance images of 30,717 individuals from 50 cohorts. We identify five novel genetic variants influencing the volumes of the putamen and caudate nucleus. We also find stronger evidence for three loci with previously established influences on hippocampal volume and intracranial volume. These variants show specific volumetric effects on brain structures rather than global effects across structures. The strongest effects were found for the putamen, where a novel intergenic locus with replicable influence on volume (rs945270; P = 1.08×10 -33; 0.52% variance explained) showed evidence of altering the expression of the KTN1 gene in both brain and blood tissue. Variants influencing putamen volume clustered near developmental genes that regulate apoptosis, axon guidance and vesicle transport. Identification of these genetic variants provides insight into the causes of variability in human brain development, and may help to determine mechanisms of neuropsychiatric dysfunction.
Published: 2015
Full Text: View/download PDF

44. Human subcortical brain asymmetries in 15,847 people worldwide reveal effects of age and sex

Author: Guadalupe, T, Mathias, SR, vanErp, TGM, Whelan, CD, Zwiers, MP, Abe, Y, Abramovic, L, Agartz, I, Andreassen, OA, Arias-Vásquez, A, Aribisala, BS, Armstrong, NJ, Arolt, V, Artiges, E, Ayesa-Arriola, R, Baboyan, VG, Banaschewski, T, Barker, G, Bastin, ME, Baune, BT, Blangero, J, Bokde, ALW, Boedhoe, PSW, Bose, A, Brem, S, Brodaty, H ; https://orcid.org/0000-0001-9487-6617, Bromberg, U, Brooks, S, Büchel, C, Buitelaar, J, Calhoun, VD, Cannon, DM, Cattrell, A, Cheng, Y, Conrod, PJ, Conzelmann, A, Corvin, A, Crespo-Facorro, B, Crivello, F, Dannlowski, U, de Zubicaray, GI, de Zwarte, SMC, Deary, IJ, Desrivières, S, Doan, NT, Donohoe, G, Dørum, ES, Ehrlich, S, Espeseth, T, Fernández, G, Flor, H, Fouche, J-P, Frouin, V, Fukunaga, M, Gallinat, J, Garavan, H, Gill, M, Suarez, AG, Gowland, P, Grabe, HJ, Grotegerd, D, Gruber, O, Hagenaars, S, Hashimoto, R, Hauser, TU, Heinz, A, Hibar, DP, Hoekstra, PJ, Hoogman, M, Howells, FM, Hu, H, Hulshoff Pol, HE, Huyser, C, Ittermann, B, Jahanshad, N, Jönsson, EG, Jurk, S, Kahn, RS, Kelly, S, Kraemer, B, Kugel, H, Kwon, JS, Lemaitre, H, Lesch, K-P, Lochner, C, Luciano, M, Marquand, AF, Martin, NG, Martínez-Zalacaín, I, Martinot, J-L, Mataix-Cols, D, Mather, K ; https://orcid.org/0000-0003-4143-8941, McDonald, C, McMahon, KL, Medland, SE, Menchón, JM, Morris, DW, Mothersill, O, Maniega, SM, Mwangi, B, Nakamae, T, Nakao, T, Narayanaswaamy, JC, Nees, F, Nordvik, JE, Onnink, AMH, Opel, N, Ophoff, R, Paillère Martinot, M-L, Papadopoulos Orfanos, D, Pauli, P, Paus, T, Poustka, L, Reddy, JY, Renteria, ME, Roiz-Santiáñez, R, Roos, A, Royle, NA, Sachdev, P ; https://orcid.org/0000-0002-9595-3220, Sánchez-Juan, P, Schmaal, L, Schumann, G, Shumskaya, E, Smolka, MN, Soares, JC, Soriano-Mas, C, Stein, DJ, Strike, LT, Toro, R, Turner, JA, Tzourio-Mazoyer, N, Uhlmann, A, Hernández, MV, van den Heuvel, OA, van der Meer, D, van Haren, NEM, Veltman, DJ, Venkatasubramanian, G, Vetter, NC, Vuletic, D, Walitza, S, Walter, H, Walton, E, Wang, Z, Wardlaw, J, Wen, W ; https://orcid.org/0000-0003-2753-3870, Westlye, LT, Whelan, R, Wittfeld, K, Wolfers, T, Wright, MJ, Xu, J, Xu, X, Yun, J-Y, Zhao, J, Franke, B, Thompson, PM, Glahn, DC, Mazoyer, B, Fisher, SE, Francks, C, Guadalupe, T, Mathias, SR, vanErp, TGM, Whelan, CD, Zwiers, MP, Abe, Y, Abramovic, L, Agartz, I, Andreassen, OA, Arias-Vásquez, A, Aribisala, BS, Armstrong, NJ, Arolt, V, Artiges, E, Ayesa-Arriola, R, Baboyan, VG, Banaschewski, T, Barker, G, Bastin, ME, Baune, BT, Blangero, J, Bokde, ALW, Boedhoe, PSW, Bose, A, Brem, S, Brodaty, H ; https://orcid.org/0000-0001-9487-6617, Bromberg, U, Brooks, S, Büchel, C, Buitelaar, J, Calhoun, VD, Cannon, DM, Cattrell, A, Cheng, Y, Conrod, PJ, Conzelmann, A, Corvin, A, Crespo-Facorro, B, Crivello, F, Dannlowski, U, de Zubicaray, GI, de Zwarte, SMC, Deary, IJ, Desrivières, S, Doan, NT, Donohoe, G, Dørum, ES, Ehrlich, S, Espeseth, T, Fernández, G, Flor, H, Fouche, J-P, Frouin, V, Fukunaga, M, Gallinat, J, Garavan, H, Gill, M, Suarez, AG, Gowland, P, Grabe, HJ, Grotegerd, D, Gruber, O, Hagenaars, S, Hashimoto, R, Hauser, TU, Heinz, A, Hibar, DP, Hoekstra, PJ, Hoogman, M, Howells, FM, Hu, H, Hulshoff Pol, HE, Huyser, C, Ittermann, B, Jahanshad, N, Jönsson, EG, Jurk, S, Kahn, RS, Kelly, S, Kraemer, B, Kugel, H, Kwon, JS, Lemaitre, H, Lesch, K-P, Lochner, C, Luciano, M, Marquand, AF, Martin, NG, Martínez-Zalacaín, I, Martinot, J-L, Mataix-Cols, D, Mather, K ; https://orcid.org/0000-0003-4143-8941, McDonald, C, McMahon, KL, Medland, SE, Menchón, JM, Morris, DW, Mothersill, O, Maniega, SM, Mwangi, B, Nakamae, T, Nakao, T, Narayanaswaamy, JC, Nees, F, Nordvik, JE, Onnink, AMH, Opel, N, Ophoff, R, Paillère Martinot, M-L, Papadopoulos Orfanos, D, Pauli, P, Paus, T, Poustka, L, Reddy, JY, Renteria, ME, Roiz-Santiáñez, R, Roos, A, Royle, NA, Sachdev, P ; https://orcid.org/0000-0002-9595-3220, Sánchez-Juan, P, Schmaal, L, Schumann, G, Shumskaya, E, Smolka, MN, Soares, JC, Soriano-Mas, C, Stein, DJ, Strike, LT, Toro, R, Turner, JA, Tzourio-Mazoyer, N, Uhlmann, A, Hernández, MV, van den Heuvel, OA, van der Meer, D, van Haren, NEM, Veltman, DJ, Venkatasubramanian, G, Vetter, NC, Vuletic, D, Walitza, S, Walter, H, Walton, E, Wang, Z, Wardlaw, J, Wen, W ; https://orcid.org/0000-0003-2753-3870, Westlye, LT, Whelan, R, Wittfeld, K, Wolfers, T, Wright, MJ, Xu, J, Xu, X, Yun, J-Y, Zhao, J, Franke, B, Thompson, PM, Glahn, DC, Mazoyer, B, Fisher, SE, and Francks, C
Abstract: The two hemispheres of the human brain differ functionally and structurally. Despite over a century of research, the extent to which brain asymmetry is influenced by sex, handedness, age, and genetic factors is still controversial. Here we present the largest ever analysis of subcortical brain asymmetries, in a harmonized multi-site study using meta-analysis methods. Volumetric asymmetry of seven subcortical structures was assessed in 15,847 MRI scans from 52 datasets worldwide. There were sex differences in the asymmetry of the globus pallidus and putamen. Heritability estimates, derived from 1170 subjects belonging to 71 extended pedigrees, revealed that additive genetic factors influenced the asymmetry of these two structures and that of the hippocampus and thalamus. Handedness had no detectable effect on subcortical asymmetries, even in this unprecedented sample size, but the asymmetry of the putamen varied with age. Genetic drivers of asymmetry in the hippocampus, thalamus and basal ganglia may affect variability in human cognition, including susceptibility to psychiatric disorders.
Published: 2017

45. Novel genetic loci associated with hippocampal volume

Author: Hibar, DP, Adams, HHH, Jahanshad, N, Chauhan, G, Stein, JL, Hofer, E, Renteria, ME, Bis, JC, Arias-Vasquez, A, Ikram, MK, Desrivieres, S, Vernooij, MW, Abramovic, L, Alhusaini, S, Amin, N, Andersson, M, Arfanakis, K, Aribisala, BS, Armstrong, NJ, Athanasiu, L, Axelsson, T, Beecham, AH, Beiser, A, Bernard, M, Blanton, SH, Bohlken, MM, Boks, MP, Bralten, J, Brickman, AM, Carmichael, O, Chakravarty, MM, Chen, Q, Ching, CRK, Chouraki, V, Cuellar-Partida, G, Crivello, F, Den Braber, A, Nhat, TD, Ehrlich, S, Giddaluru, S, Goldman, AL, Gottesman, RF, Grimm, O, Griswold, ME, Guadalupe, T, Gutman, BA, Hass, J, Haukvik, UK, Hoehn, D, Holmes, AJ, Hoogman, M, Janowitz, D, Jia, T, Jorgensen, KN, Karbalai, N, Kasperaviciute, D, Kim, S, Klein, M, Kraemer, B, Lee, PH, Liewald, DCM, Lopez, LM, Luciano, M, Macare, C, Marquand, AF, Matarin, M, Mather, KA, Mattheisen, M, McKay, DR, Milaneschi, Y, Maniega, SM, Nho, K, Nugent, AC, Nyquist, P, Loohuis, LMO, Oosterlaan, J, Papmeyer, M, Pirpamer, L, Puetz, B, Ramasamy, A, Richards, JS, Risacher, SL, Roiz-Santianez, R, Rommelse, N, Ropele, S, Rose, EJ, Royle, NA, Rundek, T, Saemann, PG, Saremi, A, Satizabal, CL, Schmaal, L, Schork, AJ, Shen, L, Shin, J, Shumskaya, E, Smith, AV, Sprooten, E, Strike, LT, Teumer, A, Tordesillas-Gutierrez, D, Toro, R, Trabzuni, D, Trompet, S, Vaidya, D, Van der Grond, J, Van der Lee, SJ, Van der Meer, D, Van Donkelaar, MMJ, Van Eijk, KR, Van Erp, TGM, Van Rooij, D, Walton, E, Westlye, LT, Whelan, CD, Windham, BG, Winkler, AM, Wittfeld, K, Woldehawariat, G, Wolf, C, Wolfers, T, Yanek, LR, Yang, J, Zijdenbos, A, Zwiers, MP, Agartz, I, Almasy, L, Ames, D, Amouyel, P, Andreassen, OA, Arepalli, S, Assareh, AA, Barral, S, Bastin, ME, Becker, DM, Becker, JT, Bennett, DA, Blangero, J, van Bokhoven, H, Boomsma, DI, Brodaty, H, Brouwer, RM, Brunner, HG, Buckner, RL, Buitelaar, JK, Bulayeva, KB, Cahn, W, Calhoun, VD, Cannon, DM, Cavalleri, GL, Cheng, C-Y, Cichon, S, Cookson, MR, Corvin, A, Crespo-Facorro, B, Curran, JE, Czisch, M, Dale, AM, Davies, GE, De Craen, AJM, De Geus, EJC, De Jager, PL, De Zubicaray, GI, Deary, IJ, Debette, S, DeCarli, C, Delanty, N, Depondt, C, DeStefano, A, Dillman, A, Djurovic, S, Donohoe, G, Drevets, WC, Duggirala, R, Dyer, TD, Enzinger, C, Erk, S, Espeseth, T, Fedko, IO, Fernandez, G, Ferrucci, L, Fisher, SE, Fleischman, DA, Ford, I, Fornage, M, Foroud, TM, Fox, PT, Francks, C, Fukunaga, M, Gibbs, JR, Glahn, DC, Gollub, RL, Goring, HHH, Green, RC, Gruber, O, Gudnason, V, Guelfi, S, Haberg, AK, Hansell, NK, Hardy, J, Hartman, CA, Hashimoto, R, Hegenscheid, K, Heinz, A, Le Hellard, S, Hernandez, DG, Heslenfeld, DJ, Ho, B-C, Hoekstra, PJ, Hoffmann, W, Hofman, A, Holsboer, F, Homuth, G, Hosten, N, Hottenga, J-J, Huentelman, M, Pol, HEH, Ikeda, M, Jack, CR, Jenkinson, M, Johnson, R, Joensson, EG, Jukema, JW, Kahn, RS, Kanai, R, Kloszewska, I, Knopman, DS, Kochunov, P, Kwok, JB, Lawrie, SM, Lemaitre, H, Liu, X, Longo, DL, Lopez, OL, Lovestone, S, Martinez, O, Martinot, J-L, Mattay, VS, McDonald, C, McIntosh, AM, McMahon, FJ, McMahon, KL, Mecocci, P, Melle, I, Meyer-Lindenberg, A, Mohnke, S, Montgomery, GW, Morris, DW, Mosley, TH, Muhleisen, TW, Mueller-Myhsok, B, Nalls, MA, Nauck, M, Nichols, TE, Niessen, WJ, Nothen, MM, Nyberg, L, Ohi, K, Olvera, RL, Ophoff, RA, Pandolfo, M, Paus, T, Pausova, Z, Penninx, BWJH, Pike, GB, Potkin, SG, Psaty, BM, Reppermund, S, Rietschel, M, Roffman, JL, Romanczuk-Seiferth, N, Rotter, JI, Ryten, M, Sacco, RL, Sachdev, PS, Saykin, AJ, Schmidt, R, Schmidt, H, Schofield, PR, Sigursson, S, Simmons, A, Singleton, A, Sisodiya, SM, Smith, C, Smoller, JW, Soininen, H, Steen, VM, Stott, DJ, Sussmann, JE, Thalamuthu, A, Toga, AW, Traynor, BJ, Troncoso, J, Tsolaki, M, Tzourio, C, Uitterlinden, AG, Hernandez, MCV, Van der Brug, M, van der Lugt, A, van der Wee, NJA, Van Haren, NEM, van't Ent, D, Van Tol, M-J, Vardarajan, BN, Vellas, B, Veltman, DJ, Voelzke, H, Walter, H, Wardlaw, JM, Wassink, TH, Weale, ME, Weinberger, DR, Weiner, MW, Wen, W, Westman, E, White, T, Wong, TY, Wright, CB, Zielke, RH, Zonderman, AB, Martin, NG, Van Duijn, CM, Wright, MJ, Longstreth, WT, Schumann, G, Grabe, HJ, Franke, B, Launer, LJ, Medland, SE, Seshadri, S, Thompson, PM, Ikram, MA, Hibar, DP, Adams, HHH, Jahanshad, N, Chauhan, G, Stein, JL, Hofer, E, Renteria, ME, Bis, JC, Arias-Vasquez, A, Ikram, MK, Desrivieres, S, Vernooij, MW, Abramovic, L, Alhusaini, S, Amin, N, Andersson, M, Arfanakis, K, Aribisala, BS, Armstrong, NJ, Athanasiu, L, Axelsson, T, Beecham, AH, Beiser, A, Bernard, M, Blanton, SH, Bohlken, MM, Boks, MP, Bralten, J, Brickman, AM, Carmichael, O, Chakravarty, MM, Chen, Q, Ching, CRK, Chouraki, V, Cuellar-Partida, G, Crivello, F, Den Braber, A, Nhat, TD, Ehrlich, S, Giddaluru, S, Goldman, AL, Gottesman, RF, Grimm, O, Griswold, ME, Guadalupe, T, Gutman, BA, Hass, J, Haukvik, UK, Hoehn, D, Holmes, AJ, Hoogman, M, Janowitz, D, Jia, T, Jorgensen, KN, Karbalai, N, Kasperaviciute, D, Kim, S, Klein, M, Kraemer, B, Lee, PH, Liewald, DCM, Lopez, LM, Luciano, M, Macare, C, Marquand, AF, Matarin, M, Mather, KA, Mattheisen, M, McKay, DR, Milaneschi, Y, Maniega, SM, Nho, K, Nugent, AC, Nyquist, P, Loohuis, LMO, Oosterlaan, J, Papmeyer, M, Pirpamer, L, Puetz, B, Ramasamy, A, Richards, JS, Risacher, SL, Roiz-Santianez, R, Rommelse, N, Ropele, S, Rose, EJ, Royle, NA, Rundek, T, Saemann, PG, Saremi, A, Satizabal, CL, Schmaal, L, Schork, AJ, Shen, L, Shin, J, Shumskaya, E, Smith, AV, Sprooten, E, Strike, LT, Teumer, A, Tordesillas-Gutierrez, D, Toro, R, Trabzuni, D, Trompet, S, Vaidya, D, Van der Grond, J, Van der Lee, SJ, Van der Meer, D, Van Donkelaar, MMJ, Van Eijk, KR, Van Erp, TGM, Van Rooij, D, Walton, E, Westlye, LT, Whelan, CD, Windham, BG, Winkler, AM, Wittfeld, K, Woldehawariat, G, Wolf, C, Wolfers, T, Yanek, LR, Yang, J, Zijdenbos, A, Zwiers, MP, Agartz, I, Almasy, L, Ames, D, Amouyel, P, Andreassen, OA, Arepalli, S, Assareh, AA, Barral, S, Bastin, ME, Becker, DM, Becker, JT, Bennett, DA, Blangero, J, van Bokhoven, H, Boomsma, DI, Brodaty, H, Brouwer, RM, Brunner, HG, Buckner, RL, Buitelaar, JK, Bulayeva, KB, Cahn, W, Calhoun, VD, Cannon, DM, Cavalleri, GL, Cheng, C-Y, Cichon, S, Cookson, MR, Corvin, A, Crespo-Facorro, B, Curran, JE, Czisch, M, Dale, AM, Davies, GE, De Craen, AJM, De Geus, EJC, De Jager, PL, De Zubicaray, GI, Deary, IJ, Debette, S, DeCarli, C, Delanty, N, Depondt, C, DeStefano, A, Dillman, A, Djurovic, S, Donohoe, G, Drevets, WC, Duggirala, R, Dyer, TD, Enzinger, C, Erk, S, Espeseth, T, Fedko, IO, Fernandez, G, Ferrucci, L, Fisher, SE, Fleischman, DA, Ford, I, Fornage, M, Foroud, TM, Fox, PT, Francks, C, Fukunaga, M, Gibbs, JR, Glahn, DC, Gollub, RL, Goring, HHH, Green, RC, Gruber, O, Gudnason, V, Guelfi, S, Haberg, AK, Hansell, NK, Hardy, J, Hartman, CA, Hashimoto, R, Hegenscheid, K, Heinz, A, Le Hellard, S, Hernandez, DG, Heslenfeld, DJ, Ho, B-C, Hoekstra, PJ, Hoffmann, W, Hofman, A, Holsboer, F, Homuth, G, Hosten, N, Hottenga, J-J, Huentelman, M, Pol, HEH, Ikeda, M, Jack, CR, Jenkinson, M, Johnson, R, Joensson, EG, Jukema, JW, Kahn, RS, Kanai, R, Kloszewska, I, Knopman, DS, Kochunov, P, Kwok, JB, Lawrie, SM, Lemaitre, H, Liu, X, Longo, DL, Lopez, OL, Lovestone, S, Martinez, O, Martinot, J-L, Mattay, VS, McDonald, C, McIntosh, AM, McMahon, FJ, McMahon, KL, Mecocci, P, Melle, I, Meyer-Lindenberg, A, Mohnke, S, Montgomery, GW, Morris, DW, Mosley, TH, Muhleisen, TW, Mueller-Myhsok, B, Nalls, MA, Nauck, M, Nichols, TE, Niessen, WJ, Nothen, MM, Nyberg, L, Ohi, K, Olvera, RL, Ophoff, RA, Pandolfo, M, Paus, T, Pausova, Z, Penninx, BWJH, Pike, GB, Potkin, SG, Psaty, BM, Reppermund, S, Rietschel, M, Roffman, JL, Romanczuk-Seiferth, N, Rotter, JI, Ryten, M, Sacco, RL, Sachdev, PS, Saykin, AJ, Schmidt, R, Schmidt, H, Schofield, PR, Sigursson, S, Simmons, A, Singleton, A, Sisodiya, SM, Smith, C, Smoller, JW, Soininen, H, Steen, VM, Stott, DJ, Sussmann, JE, Thalamuthu, A, Toga, AW, Traynor, BJ, Troncoso, J, Tsolaki, M, Tzourio, C, Uitterlinden, AG, Hernandez, MCV, Van der Brug, M, van der Lugt, A, van der Wee, NJA, Van Haren, NEM, van't Ent, D, Van Tol, M-J, Vardarajan, BN, Vellas, B, Veltman, DJ, Voelzke, H, Walter, H, Wardlaw, JM, Wassink, TH, Weale, ME, Weinberger, DR, Weiner, MW, Wen, W, Westman, E, White, T, Wong, TY, Wright, CB, Zielke, RH, Zonderman, AB, Martin, NG, Van Duijn, CM, Wright, MJ, Longstreth, WT, Schumann, G, Grabe, HJ, Franke, B, Launer, LJ, Medland, SE, Seshadri, S, Thompson, PM, and Ikram, MA
Abstract: The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer's disease (rg=-0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness.
Published: 2017

46. Effects of cognitive training on gray matter volumes in memory clinic patients with subjective memory impairment

Author: Engvig A, Fjell AM, Westlye LT, Skaane NV, Dale AM, Holland D, Due-Txf8nnessen P, Sundseth O, and Walhovd KB.
Published: 2014

47. The ENIGMA Consortium: large-scale collaborative analyses of neuroimaging and genetic data

Author: Thompson, PM, Stein, JL, Medland, SE, Hibar, DP, Vasquez, AA, Renteria, ME, Toro, R, Jahanshad, N, Schumann, G, Franke, B, Wright, MJ, Martin, NG, Agartz, I, Alda, M, Alhusaini, S, Almasy, L, Almeida, J, Alpert, K, Andreasen, NC, Andreassen, OA, Apostolova, LG, Appel, K, Armstrong, NJ, Aribisala, B, Bastin, ME, Bauer, M, Bearden, CE, Bergmann, O, Binder, EB, Blangero, J, Bockholt, HJ, Boen, E, Bois, C, Boomsma, DI, Booth, T, Bowman, IJ, Bralten, J, Brouwer, RM, Brunner, HG, Brohawn, DG, Buckner, RL, Buitelaar, J, Bulayeva, K, Bustillo, JR, Calhoun, VD, Cannon, DM, Cantor, RM, Carless, MA, Caseras, X, Cavalleri, GL, Chakravarty, MM, Chang, KD, Ching, CRK, Christoforou, A, Cichon, S, Clark, VP, Conrod, P, Coppola, G, Crespo-Facorro, B, Curran, JE, Czisch, M, Deary, IJ, de Geus, EJC, den Braber, A, Delvecchio, G, Depondt, C, de Haan, L, de Zubicaray, GI, Dima, D, Dimitrova, R, Djurovic, S, Dong, H, Donohoe, G, Duggirala, R, Dyer, TD, Ehrlich, S, Ekman, CJ, Elvsashagen, T, Emsell, L, Erk, S, Espeseth, T, Fagerness, J, Fears, S, Fedko, I, Fernandez, G, Fisher, SE, Foroud, T, Fox, PT, Francks, C, Frangou, S, Frey, EM, Frodl, T, Frouin, V, Garavan, H, Giddaluru, S, Glahn, DC, Godlewska, B, Goldstein, RZ, Gollub, RL, Grabe, HJ, Grimm, O, Gruber, O, Guadalupe, T, Gur, RE, Gur, RC, Goering, HHH, Hagenaars, S, Hajek, T, Hall, GB, Hall, J, Hardy, J, Hartman, CA, Hass, J, Hatton, SN, Haukvik, UK, Hegenscheid, K, Heinz, A, Hickie, IB, Ho, B-C, Hoehn, D, Hoekstra, PJ, Hollinshead, M, Holmes, AJ, Homuth, G, Hoogman, M, Hong, LE, Hosten, N, Hottenga, J-J, Pol, HEH, Hwang, KS, Jack, CR, Jenkinson, M, Johnston, C, Joensson, EG, Kahn, RS, Kasperaviciute, D, Kelly, S, Kim, S, Kochunov, P, Koenders, L, Kraemer, B, Kwok, JBJ, Lagopoulos, J, Laje, G, Landen, M, Landman, BA, Lauriello, J, Lawrie, SM, Lee, PH, Le Hellard, S, Lemaitre, H, Leonardo, CD, Li, C-S, Liberg, B, Liewald, DC, Liu, X, Lopez, LM, Loth, E, Lourdusamy, A, Luciano, M, Macciardi, F, Machielsen, MWJ, MacQueen, GM, Malt, UF, Mandl, R, Manoach, DS, Martinot, J-L, Matarin, M, Mather, KA, Mattheisen, M, Mattingsdal, M, Meyer-Lindenberg, A, McDonald, C, McIntosh, AM, McMahon, FJ, McMahon, KL, Meisenzahl, E, Melle, I, Milaneschi, Y, Mohnke, S, Montgomery, GW, Morris, DW, Moses, EK, Mueller, BA, Munoz Maniega, S, Muehleisen, TW, Mueller-Myhsok, B, Mwangi, B, Nauck, M, Nho, K, Nichols, TE, Nilsson, L-G, Nugent, AC, Nyberg, L, Olvera, RL, Oosterlaan, J, Ophoff, RA, Pandolfo, M, Papalampropoulou-Tsiridou, M, Papmeyer, M, Paus, T, Pausova, Z, Pearlson, GD, Penninx, BW, Peterson, CP, Pfennig, A, Phillips, M, Pike, GB, Poline, J-B, Potkin, SG, Puetz, B, Ramasamy, A, Rasmussen, J, Rietschel, M, Rijpkema, M, Risacher, SL, Roffman, JL, Roiz-Santianez, R, Romanczuk-Seiferth, N, Rose, EJ, Royle, NA, Rujescu, D, Ryten, M, Sachdev, PS, Salami, A, Satterthwaite, TD, Savitz, J, Saykin, AJ, Scanlon, C, Schmaal, L, Schnack, HG, Schork, AJ, Schulz, SC, Schuer, R, Seidman, L, Shen, L, Shoemaker, JM, Simmons, A, Sisodiya, SM, Smith, C, Smoller, JW, Soares, JC, Sponheim, SR, Sprooten, E, Starr, JM, Steen, VM, Strakowski, S, Strike, L, Sussmann, J, Saemann, PG, Teumer, A, Toga, AW, Tordesillas-Gutierrez, D, Trabzuni, D, Trost, S, Turner, J, Van den Heuvel, M, van der Wee, NJ, van Eijk, K, van Erp, TGM, van Haren, NEM, van 't Ent, D, van Tol, M-J, Hernandez, MCV, Veltman, DJ, Versace, A, Voelzke, H, Walker, R, Walter, H, Wang, L, Wardlaw, JM, Weale, ME, Weiner, MW, Wen, W, Westlye, LT, Whalley, HC, Whelan, CD, White, T, Winkler, AM, Wittfeld, K, Woldehawariat, G, Wolf, C, Zilles, D, Zwiers, MP, Thalamuthu, A, Schofield, PR, Freimer, NB, Lawrence, NS, Drevets, W, Thompson, PM, Stein, JL, Medland, SE, Hibar, DP, Vasquez, AA, Renteria, ME, Toro, R, Jahanshad, N, Schumann, G, Franke, B, Wright, MJ, Martin, NG, Agartz, I, Alda, M, Alhusaini, S, Almasy, L, Almeida, J, Alpert, K, Andreasen, NC, Andreassen, OA, Apostolova, LG, Appel, K, Armstrong, NJ, Aribisala, B, Bastin, ME, Bauer, M, Bearden, CE, Bergmann, O, Binder, EB, Blangero, J, Bockholt, HJ, Boen, E, Bois, C, Boomsma, DI, Booth, T, Bowman, IJ, Bralten, J, Brouwer, RM, Brunner, HG, Brohawn, DG, Buckner, RL, Buitelaar, J, Bulayeva, K, Bustillo, JR, Calhoun, VD, Cannon, DM, Cantor, RM, Carless, MA, Caseras, X, Cavalleri, GL, Chakravarty, MM, Chang, KD, Ching, CRK, Christoforou, A, Cichon, S, Clark, VP, Conrod, P, Coppola, G, Crespo-Facorro, B, Curran, JE, Czisch, M, Deary, IJ, de Geus, EJC, den Braber, A, Delvecchio, G, Depondt, C, de Haan, L, de Zubicaray, GI, Dima, D, Dimitrova, R, Djurovic, S, Dong, H, Donohoe, G, Duggirala, R, Dyer, TD, Ehrlich, S, Ekman, CJ, Elvsashagen, T, Emsell, L, Erk, S, Espeseth, T, Fagerness, J, Fears, S, Fedko, I, Fernandez, G, Fisher, SE, Foroud, T, Fox, PT, Francks, C, Frangou, S, Frey, EM, Frodl, T, Frouin, V, Garavan, H, Giddaluru, S, Glahn, DC, Godlewska, B, Goldstein, RZ, Gollub, RL, Grabe, HJ, Grimm, O, Gruber, O, Guadalupe, T, Gur, RE, Gur, RC, Goering, HHH, Hagenaars, S, Hajek, T, Hall, GB, Hall, J, Hardy, J, Hartman, CA, Hass, J, Hatton, SN, Haukvik, UK, Hegenscheid, K, Heinz, A, Hickie, IB, Ho, B-C, Hoehn, D, Hoekstra, PJ, Hollinshead, M, Holmes, AJ, Homuth, G, Hoogman, M, Hong, LE, Hosten, N, Hottenga, J-J, Pol, HEH, Hwang, KS, Jack, CR, Jenkinson, M, Johnston, C, Joensson, EG, Kahn, RS, Kasperaviciute, D, Kelly, S, Kim, S, Kochunov, P, Koenders, L, Kraemer, B, Kwok, JBJ, Lagopoulos, J, Laje, G, Landen, M, Landman, BA, Lauriello, J, Lawrie, SM, Lee, PH, Le Hellard, S, Lemaitre, H, Leonardo, CD, Li, C-S, Liberg, B, Liewald, DC, Liu, X, Lopez, LM, Loth, E, Lourdusamy, A, Luciano, M, Macciardi, F, Machielsen, MWJ, MacQueen, GM, Malt, UF, Mandl, R, Manoach, DS, Martinot, J-L, Matarin, M, Mather, KA, Mattheisen, M, Mattingsdal, M, Meyer-Lindenberg, A, McDonald, C, McIntosh, AM, McMahon, FJ, McMahon, KL, Meisenzahl, E, Melle, I, Milaneschi, Y, Mohnke, S, Montgomery, GW, Morris, DW, Moses, EK, Mueller, BA, Munoz Maniega, S, Muehleisen, TW, Mueller-Myhsok, B, Mwangi, B, Nauck, M, Nho, K, Nichols, TE, Nilsson, L-G, Nugent, AC, Nyberg, L, Olvera, RL, Oosterlaan, J, Ophoff, RA, Pandolfo, M, Papalampropoulou-Tsiridou, M, Papmeyer, M, Paus, T, Pausova, Z, Pearlson, GD, Penninx, BW, Peterson, CP, Pfennig, A, Phillips, M, Pike, GB, Poline, J-B, Potkin, SG, Puetz, B, Ramasamy, A, Rasmussen, J, Rietschel, M, Rijpkema, M, Risacher, SL, Roffman, JL, Roiz-Santianez, R, Romanczuk-Seiferth, N, Rose, EJ, Royle, NA, Rujescu, D, Ryten, M, Sachdev, PS, Salami, A, Satterthwaite, TD, Savitz, J, Saykin, AJ, Scanlon, C, Schmaal, L, Schnack, HG, Schork, AJ, Schulz, SC, Schuer, R, Seidman, L, Shen, L, Shoemaker, JM, Simmons, A, Sisodiya, SM, Smith, C, Smoller, JW, Soares, JC, Sponheim, SR, Sprooten, E, Starr, JM, Steen, VM, Strakowski, S, Strike, L, Sussmann, J, Saemann, PG, Teumer, A, Toga, AW, Tordesillas-Gutierrez, D, Trabzuni, D, Trost, S, Turner, J, Van den Heuvel, M, van der Wee, NJ, van Eijk, K, van Erp, TGM, van Haren, NEM, van 't Ent, D, van Tol, M-J, Hernandez, MCV, Veltman, DJ, Versace, A, Voelzke, H, Walker, R, Walter, H, Wang, L, Wardlaw, JM, Weale, ME, Weiner, MW, Wen, W, Westlye, LT, Whalley, HC, Whelan, CD, White, T, Winkler, AM, Wittfeld, K, Woldehawariat, G, Wolf, C, Zilles, D, Zwiers, MP, Thalamuthu, A, Schofield, PR, Freimer, NB, Lawrence, NS, and Drevets, W
Abstract: The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA's first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.
Published: 2014

48. Effects of APOE on brain white matter microstructure in healthy adults.

Author: Westlye LT, Reinvang I, Rootwelt H, and Espeseth T
Published: 2012
Full Text: View/download PDF

49. Mini-Mental State Examination is sensitive to brain atrophy in Alzheimer's disease.

Author: Fjell AM, Amlien IK, Westlye LT, and Walhovd KB
Abstract: BACKGROUND/AIMS: Screening instruments such as the Mini-Mental State Examination (MMSE) are useful for the early identification of Alzheimer's disease (AD). We tested whether macrostructural differences in brain volume are related to the MMSE. METHODS: The MMSE was related to cortical thickness and the volume of 19 brain structures in 96 patients with mild to moderate AD. In addition, the patients were compared to 93 healthy elderly controls. RESULTS: The MMSE was related to the volume of the total brain, cerebral cortex, accumbens, cerebral white matter, inferior lateral ventricles and hippocampus. Positive correlations with cortical thickness were found for 41% of the brain surface, and 58% of this area was significantly thinner in AD. CONCLUSION: The MMSE is sensitive to macrostructural brain atrophy in AD, but also to morphometric variation not specifically related to AD. [ABSTRACT FROM AUTHOR]
Published: 2009
Full Text: View/download PDF

50. Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study.

Author: Omlor W, Rabe F, Fuchs S, Surbeck W, Cecere G, Huang GY, Homan S, Kallen N, Georgiadis F, Spiller T, Seifritz E, Weickert T, Bruggemann J, Weickert C, Potkin S, Hashimoto R, Sim K, Rootes-Murdy K, Quide Y, Houenou J, Banaj N, Vecchio D, Piras F, Piras F, Spalletta G, Salvador R, Karuk A, Pomarol-Clotet E, Rodrigue A, Pearlson G, Glahn D, Tomecek D, Spaniel F, Skoch A, Kirschner M, Kaiser S, Kochunov P, Fan FM, Andreassen OA, Westlye LT, Berthet P, Calhoun VD, Howells F, Uhlmann A, Scheffler F, Stein D, Iasevoli F, Cairns MJ, Carr VJ, Catts SV, Di Biase MA, Jablensky A, Green MJ, Henskens FA, Klauser P, Loughland C, Michie PT, Mowry B, Pantelis C, Rasser PE, Schall U, Scott R, Zalesky A, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Di Giorgio A, Thomopoulos SI, Jahanshad N, Thompson PM, van Erp T, Turner J, and Homan P
Abstract: Objective: The clinical diversity of schizophrenia is reflected by structural brain variability. It remains unclear how this variability manifests across different gray and white matter features. In this meta- and mega-analysis, the authors investigated how brain heterogeneity in schizophrenia is distributed across multimodal structural indicators., Methods: The authors used the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6,037 individuals for a given brain measure. Variability and mean values of cortical thickness, cortical surface area, cortical folding index, subcortical volume, and fractional anisotropy were examined in individuals with schizophrenia and healthy control subjects., Results: Individuals with schizophrenia showed greater variability in cortical thickness, cortical surface area, subcortical volume, and fractional anisotropy within the frontotemporal and subcortical network. This increased structural variability was mainly associated with psychopathological symptom domains, and the schizophrenia group frequently displayed lower mean values in the respective structural measures. Unexpectedly, folding patterns were more uniform in individuals with schizophrenia, particularly in the right caudal anterior cingulate region. The mean folding values of the right caudal anterior cingulate region did not differ between the schizophrenia and healthy control groups, and folding patterns in this region were not associated with disease-related parameters., Conclusions: In patients with schizophrenia, uniform folding patterns in the right caudal anterior cingulate region contrasted with the multimodal variability in the frontotemporal and subcortical network. While variability in the frontotemporal and subcortical network was associated with disease-related diversity, uniform folding may indicate a less flexible interplay between genetic and environmental factors during neurodevelopment., Competing Interests: Dr. Andreassen has served as a consultant for Cortechs.ai and has received speakers honoraria from Janssen, Lundbeck, and Sunovion. Dr. Seifritz has served as an adviser and provided educational lectures for Angelini, Janssen, Lundbeck, Mepha Pharma, Otsuka, Recordati, Sunovion, and Schwabe. Dr. P. Homan has received grants and honoraria from Boehringer Ingelheim, Janssen, Lundbeck, Mepha, Neurolite, and Novartis. The other authors report no financial relationships with commercial interests.
Published: 2025
Full Text: View/download PDF

Catalog

Books, media, physical & digital resources

See catalog results

Searchworks

Select search scope, currently: Articles Catalog books, media & more in Jio Institute collections Articles journal articles & other e-resources

Search

Search Constraints

Refine your results

Search Limiters

Topic

Publication Year Range

Language

Publication Type

Journal

Region

Database

Publisher

496 results on '"Westlye, LT"'

Search Results

Catalog

Select search scope, currently: Articles

Catalog

books, media & more in Jio Institute collections

Articles

journal articles & other e-resources