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

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

2. Widespread intra-axonal signal fraction abnormalities in bipolar disorder from multicompartment diffusion MRI: Sensitivity to diagnosis, association with clinical features and pharmacologic treatment

Author: Universitat Rovira i Virgili, Canales-Rodríguez EJ; Verdolini N; Alonso-Lana S; Torres ML; Panicalli F; Argila-Plaza I; Rodriguez-Cano E; Montoro I; Garcia-Ruiz B; Jimenez E; Varo C; Lluch A; del Mar Bonnin C; Maluf S; Pujol M; Guarner NJ; Sarró S; Vieta E; Vilella E; Salvador R; Pomarol-Clotet E, Universitat Rovira i Virgili, and Canales-Rodríguez EJ; Verdolini N; Alonso-Lana S; Torres ML; Panicalli F; Argila-Plaza I; Rodriguez-Cano E; Montoro I; Garcia-Ruiz B; Jimenez E; Varo C; Lluch A; del Mar Bonnin C; Maluf S; Pujol M; Guarner NJ; Sarró S; Vieta E; Vilella E; Salvador R; Pomarol-Clotet E
Abstract: Despite diffusion tensor imaging (DTI) evidence for widespread fractional anisotropy (FA) reductions in the brain white matter of patients with bipolar disorder, questions remain regarding the specificity and sensitivity of FA abnormalities as opposed to other diffusion metrics in the disorder. We conducted a whole-brain voxel-based multicompartment diffusion MRI study on 316 participants (i.e., 158 patients and 158 matched healthy controls) employing four diffusion metrics: the mean diffusivity (MD) and FA estimated from DTI, and the intra-axonal signal fraction (IASF) and microscopic axonal parallel diffusivity (Dpar) derived from the spherical mean technique. Our findings provide novel evidence about widespread abnormalities in other diffusion metrics in BD. An extensive overlap between the FA and IASF results suggests that the lower FA in patients may be caused by a reduced intra-axonal volume fraction or a higher macromolecular content in the intra-axonal water. We also found a diffuse alteration in MD involving white and grey matter tissue and more localised changes in Dpar. A Machine Learning analysis revealed that FA, followed by IASF, were the most helpful metric for the automatic diagnosis of BD patients, reaching an accuracy of 72%. Number of mood episodes, age of onset/duration of illness, psychotic symptoms, and current treatment with lithium, antipsychotics, antidepressants, and antiepileptics were all significantly associated with microstructure abnormalities. Lithium treatment was associated with less microstructure abnormality.© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
Published: 2023

3. 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, Michael, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, Michael, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M
Published: 2022

4. 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

5. 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

6. 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

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

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

8. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author: Ching, C.R., Hibar, D.P., Gurholt, T.P., Nunes, A., Thomopoulos, S.I., Abé, C., Agartz, I., Brouwer, R.M., Cannon, D.M., Zwarte, S.M.C. de, Eyler, L.T., Favre, P., Hajek, T., Haukvik, U.K., Houenou, J., Landén, M., Lett, T.A., McDonald, C., Nabulsi, L., Patel, Y., Pauling, M.E., Paus, T., Radua, J., Soeiro-de-Souza, M.G., Tronchin, G., Haren, N.E.M. van, Vieta, E., Walter, H., Zeng, L.L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M, Baune, B.T., Bearden, C.E., Bellani, M., Benedetti, F. De, Berk, M., Bilderbeck, A.C., Blumberg, H.P., Bøen, E., Bollettini, I., Bonnin, C. Del Mar, Brambilla, P., Canales-Rodríguez, E.J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Dima, D., Duchesnay, É., Elvsåshagen, T., Fears, S.C., Frangou, S., Fullerton, J.M., Glahn, D.C., Goikolea, J.M., Green, M.J., Grotegerd, D., Gruber, O., Haarman, B.C.M., Henry, C., Howells, F.M., Ives-Deliperi, V., Jansen, Andreas, Kircher, T.T.J., Knöchel, C., Kramer, B., Lafer, B., López-Jaramillo, C., Machado-Vieira, R., MacIntosh, B.J., Melloni, E.M.T., Mitchell, P.B., Nenadic, I., Nery, F., Nugent, A.C., Oertel, V., Ophoff, R.A., Ota, M., Overs, B.J., Pham, D.L., Phillips, M.L., Pineda-Zapata, J.A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quidé, Y., Rive, M.M., Roberts, G., Ruhe, H.G., Salvador, R., Sarró, S., Satterthwaite, T.D., Schene, A.H., Sim, K., Thompson, P.M., Andreassen, O.A., Ching, C.R., Hibar, D.P., Gurholt, T.P., Nunes, A., Thomopoulos, S.I., Abé, C., Agartz, I., Brouwer, R.M., Cannon, D.M., Zwarte, S.M.C. de, Eyler, L.T., Favre, P., Hajek, T., Haukvik, U.K., Houenou, J., Landén, M., Lett, T.A., McDonald, C., Nabulsi, L., Patel, Y., Pauling, M.E., Paus, T., Radua, J., Soeiro-de-Souza, M.G., Tronchin, G., Haren, N.E.M. van, Vieta, E., Walter, H., Zeng, L.L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M, Baune, B.T., Bearden, C.E., Bellani, M., Benedetti, F. De, Berk, M., Bilderbeck, A.C., Blumberg, H.P., Bøen, E., Bollettini, I., Bonnin, C. Del Mar, Brambilla, P., Canales-Rodríguez, E.J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Díaz-Zuluaga, A.M., Dima, D., Duchesnay, É., Elvsåshagen, T., Fears, S.C., Frangou, S., Fullerton, J.M., Glahn, D.C., Goikolea, J.M., Green, M.J., Grotegerd, D., Gruber, O., Haarman, B.C.M., Henry, C., Howells, F.M., Ives-Deliperi, V., Jansen, Andreas, Kircher, T.T.J., Knöchel, C., Kramer, B., Lafer, B., López-Jaramillo, C., Machado-Vieira, R., MacIntosh, B.J., Melloni, E.M.T., Mitchell, P.B., Nenadic, I., Nery, F., Nugent, A.C., Oertel, V., Ophoff, R.A., Ota, M., Overs, B.J., Pham, D.L., Phillips, M.L., Pineda-Zapata, J.A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quidé, Y., Rive, M.M., Roberts, G., Ruhe, H.G., Salvador, R., Sarró, S., Satterthwaite, T.D., Schene, A.H., Sim, K., Thompson, P.M., and Andreassen, O.A.
Abstract: Contains fulltext : 252204.pdf (Publisher’s version ) (Open Access), 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

9. Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder

Author: Amann, B. L., Canales-Rodríguez, E. J., Madre, M., Radua, J., Monte, G., Alonso-Lana, S., Landin-Romero, R., Moreno-Alcázar, A., Bonnin, C. M., Sarró, S., Ortiz-Gil, J., Gomar, J. J., Moro, N., Fernandez-Corcuera, P., Goikolea, J. M., Blanch, J., Salvador, R., Vieta, E., McKenna, P. J., and Pomarol-Clotet, E.
Published: 2016
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10. Clinical performance of an antibody-free assay for plasma Aβ42/Aβ40 to detect early alterations of Alzheimer's disease in individuals with subjective cognitive decline.

Author: Pascual-Lucas, María, Allué, José Antonio, Sarasa, Leticia, Fandos, Noelia, Castillo, Sergio, Terencio, Jose, Sarasa, Manuel, Tartari, Juan Pablo, Sanabria, Ángela, Tárraga, Lluís, Ruíz, Agustín, Marquié, Marta, Seo, Sang Won, Jang, Hyemin, Boada, Mercè, on behalf of the FACEHBI study group, Aguilera, N., Alarcón-Martín, E., Alegret, M., and Alonso-Lana, S.
Subjects: ALZHEIMER'S disease, COGNITION disorders, RECEIVER operating characteristic curves, EPISODIC memory, CEREBRAL atrophy, PATHOLOGICAL physiology, MILD cognitive impairment
Abstract: Background: Accessible and cost-effective diagnostic tools are urgently needed to accurately quantify blood biomarkers to support early diagnosis of Alzheimer's disease (AD). In this study, we investigated the ability of plasma amyloid-beta (Aβ)42/Aβ40 ratio measured by an antibody-free mass-spectrometric (MS) method, ABtest-MS, to detect early pathological changes of AD. Methods: This cohort study included data from the baseline and 2-year follow-up visits from the Fundació ACE Healthy Brain Initiative (FACEHBI) study. Plasma Aβ42/Aβ40 was measured with ABtest-MS and compared to 18F-Florbetaben PET as the reference standard (cutoff for early amyloid deposition of 13.5 centiloids). Cross-validation was performed in an independent DPUK-Korean cohort. Additionally, associations of plasma Aβ42/Aβ40 with episodic memory performance and brain atrophy were assessed. Results: The FACEHBI cohort at baseline included 200 healthy individuals with subjective cognitive decline (SCD), of which 36 (18%) were Aβ-PET positive. Plasma Aβ42/Aβ40 levels were significantly lower in Aβ-PET positive individuals (median [interquartile range, IQR], 0.215 [0.203–0.236]) versus Aβ-PET negative subjects (median [IQR], 0.261 [0.244–0.279]) (P <.001). Plasma Aβ42/Aβ40 was significantly correlated with Aβ-PET levels (rho = −0.390; P <.001) and identified Aβ-PET status with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI], 0.80–0.93). A cutoff for the Aβ42/Aβ40 ratio of 0.241 (maximum Youden index) yielded a sensitivity of 86.1% and a specificity of 80.5%. These findings were cross-validated in an independent DPUK-Korean cohort (AUC 0.86 [95% CI 0.77–0.95]). Lower plasma Aβ42/Aβ40 ratio was associated with worse episodic memory performance and increased brain atrophy. Plasma Aβ42/Aβ40 at baseline predicted clinical conversion to mild cognitive impairment and longitudinal changes in amyloid deposition and brain atrophy at 2-year follow-up. Conclusions: This study suggests that plasma Aβ42/Aβ40, as determined by this MS-based assay, has potential value as an accurate and cost-effective tool to identify individuals in the earliest stages of AD, supporting its implementation in clinical trials, preventative strategies and clinical practice. [ABSTRACT FROM AUTHOR]
Published: 2023
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11. Metabolic syndrome impact on cognitive composites domain scores and on white matter hyperintensities in subjective cognitive decline: The FACEHBI Cohort

Author: Ortega, Gemma, primary, Espinosa, Ana, additional, Alegret, Montserrat, additional, Monté‐Rubio, Gemma, additional, Sotolongo‐Grau, Oscar, additional, Sanabria, Angela, additional, Tartari, Juan Pablo, additional, Rodriguez‐Gomez, Octavio, additional, Marquié, Marta, additional, Vivas, Assumpta, additional, Gómez‐Chiari, M, additional, Alarcón‐Martín, Emilio, additional, Pérez‐Cordón, Alba, additional, Roberto, Natalia, additional, Hernandez, Isabel, additional, Rosende‐Roca, Maitee, additional, Vargas, Liliana, additional, Mauleon, Ana, additional, Abdelnour, Carla, additional, Antonio, Ester Esteban‐De, additional, López‐Cuevas, Rogelio, additional, Alonso‐Lana, S, additional, Moreno‐Grau, Sonia, additional, de Rojas, Itziar, additional, Orellana, Adelina, additional, Montrreal, Laura, additional, Tarraga, Lluis, additional, Ruiz, Agustin, additional, Boada, Mercè, additional, and Valero, Sergi, additional
Published: 2021
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12. Altered brain responses to specific negative emotions in schizophrenia

Author: Garcia-Leon MA, Fuentes-Claramonte P, Valiente-Gómez A, Natividad C, Salgado-Pineda P, Gomar JJ, Guerrero-Pedraza A, Portillo F, Ortiz-Gil J, Alonso-Lana S, Maristany M, Raduà J, Salvador R, Sarró S, and Pomarol-Clotet E
Subjects: fMRI, Scenic stimuli, Schizophrenia, Emotions, IAPS, behavioral disciplines and activities
Abstract: Deficits in emotion processing are a core feature of schizophrenia, but their neurobiological bases are poorly understood. Previous research, mainly focused on emotional face processing and emotion recognition deficits, has shown controverted results. Furthermore, the use of faces has been questioned for not entailing an appropriate stimulus to study emotional processing. This highlights the importance of investigating emotional processing abnormalities using evocative stimuli. For the first time, we have studied the brain responses to scenic stimuli in patients with schizophrenia. We selected scenes from the IAPS that elicit fear, disgust, happiness, and sadness. Twenty-six patients with schizophrenia and thirty age-, sex- and premorbid IQ-matched healthy controls were included. Behavioral task results show that patients tended to misclassify disgust and sadness as fear. Brain responses in patients were different from controls in images eliciting disgust and fear. In response to disgust images, patients hyperactivated the right temporal cortex, which was not activated by the controls. With fear images, hyperactivation was observed in brain regions involved in fear processing, including midline regions from the medial frontal cortex to the anterior cingulate cortex, the superior frontal gyrus, inferior and superior temporal cortex, and visual areas. These results suggest that schizophrenia is characterized by hyper-responsivity to stimuli evoking high-arousal, negative emotions, and a bias towards fear in emotion recognition.
Published: 2021

13. 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, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, J-K, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, J-K, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M
Published: 2021

14. Virtual histology of cortical thickness and shared neurobiology in 6 psychiatric disorders

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abé, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargalló, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, Del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bülow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodríguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjó-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Silk, Timothy, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abé, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargalló, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, Del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bülow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodríguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjó-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, and Silk, Timothy
Published: 2021

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

Author: Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., Paus, T., Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., and Paus, T.
Abstract: Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls. Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (exce
Published: 2021
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16. Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals (Neuropsychopharmacology, (2019), 44, 13, (2285-2293), 10.1038/s41386-019-0485-6)

Author: Favre P., Pauling M., Stout J., Hozer F., Sarrazin S., Abe C., Alda M., Alloza C., Alonso-Lana S., Andreassen O. A., Baune B. T., Benedetti F., Busatto G. F., Canales-Rodriguez E. J., Caseras X., Chaim-Avancini T. M., Ching C. R. K., Dannlowski U., Deppe M., Eyler L. T., Fatjo-Vilas M., Foley S. F., Grotegerd D., Hajek T., Haukvik U. K., Howells F. M., Jahanshad N., Kugel H., Lagerberg T. V., Lawrie S. M., Linke J. O., McIntosh A., Melloni E. M. T., Mitchell P. B., Polosan M., Pomarol-Clotet E., Repple J., Roberts G., Roos A., Rosa P. G. P., Salvador R., Sarro S., Schofield P. R., Serpa M. H., Sim K., Stein D. J., Sussmann J. E., Temmingh H. S., Thompson P. M., Verdolini N., Vieta E., Wessa M., Whalley H. C., Zanetti M. V., Leboyer M., Mangin J. -F., Henry C., Duchesnay E., Houenou J., Favre, P., Pauling, M., Stout, J., Hozer, F., Sarrazin, S., Abe, C., Alda, M., Alloza, C., Alonso-Lana, S., Andreassen, O. A., Baune, B. T., Benedetti, F., Busatto, G. F., Canales-Rodriguez, E. J., Caseras, X., Chaim-Avancini, T. M., Ching, C. R. K., Dannlowski, U., Deppe, M., Eyler, L. T., Fatjo-Vilas, M., Foley, S. F., Grotegerd, D., Hajek, T., Haukvik, U. K., Howells, F. M., Jahanshad, N., Kugel, H., Lagerberg, T. V., Lawrie, S. M., Linke, J. O., Mcintosh, A., Melloni, E. M. T., Mitchell, P. B., Polosan, M., Pomarol-Clotet, E., Repple, J., Roberts, G., Roos, A., Rosa, P. G. P., Salvador, R., Sarro, S., Schofield, P. R., Serpa, M. H., Sim, K., Stein, D. J., Sussmann, J. E., Temmingh, H. S., Thompson, P. M., Verdolini, N., Vieta, E., Wessa, M., Whalley, H. C., Zanetti, M. V., Leboyer, M., Mangin, J. -F., Henry, C., Duchesnay, E., and Houenou, J.
Abstract: This Article was originally published under NPG's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.
Published: 2019

17. Structural abnormality in schizophrenia versus bipolar disorder: A whole brain cortical thickness, surface area, volume and gyrification analyses

Author: Madre M, Canales-Rodríguez EJ, Fuentes-Claramonte P, Alonso-Lana S, Salgado-Pineda P, Guerrero-Pedraza A, Moro N, Bosque C, Gomar JJ, Ortíz-Gil J, Goikolea JM, Bonnin CM, Vieta E, Sarró S, Maristany M, McKenna PJ, Salvador R, and Pomarol-Clotet E
Subjects: Cortical thickness, Neuroimaging, mental disorders, Schizophrenia, Surface-based morphometry, Bipolar disorder, Surface area, Gyrification index
Abstract: OBJECTIVES: The profiles of cortical abnormalities in schizophrenia and bipolar disorder, and how far they resemble each other, have only been studied to a limited extent. The aim of this study was to identify and compare the changes in cortical morphology associated with these pathologies. METHODS: A total of 384 subjects, including 128 patients with schizophrenia, 128 patients with bipolar disorder and 127 sex-age-matched healthy subjects, were examined using cortical surface-based morphology. Four cortical structural measures were studied: cortical volume (CV), cortical thickness (CT), surface area (SA) and gyrification index (GI). Group comparisons for each separate cortical measure were conducted. RESULTS: At a threshold of P = 0.05 corrected, both patient groups showed significant widespread CV and CT reductions in similar areas compared to healthy subjects. However, the changes in schizophrenia were more pronounced. While CV decrease in bipolar disorder was exclusively explained by cortical thinning, in schizophrenia it was driven by changes in CT and partially by SA. Reduced GI was only found in schizophrenia. The direct comparison between both disorders showed significant reductions in all measures in patients with schizophrenia. CONCLUSIONS: Cortical volume and cortical thickness deficits are shared between patients with schizophrenia and bipolar disorder, suggesting that both pathologies may be affected by similar environmental and neurodegenerative factors. However, the exclusive alteration in schizophrenia of metrics related to the geometry and curvature of the brain cortical surface (SA, GI) suggests that this group is influenced by additional neurodevelopmental and genetic factors.
Published: 2020

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

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

19. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author: Ching, CRK, Hibar, DP, Gurholt, TP, Nunes, A, Thomopoulos, SI, Abé, C, Agartz, I, Brouwer, RM, Cannon, DM, de Zwarte, SMC, Eyler, LT, Favre, P, Hajek, T, Haukvik, UK, Houenou, J, Landén, 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, LL, Alda, M, Almeida, J, Alnæs, D, Alonso-Lana, S, Altimus, C, Bauer, M, Baune, BT, Bearden, CE, Bellani, M, Benedetti, F, Berk, M, Bilderbeck, AC, Blumberg, HP, Bøen, E, Bollettini, I, del Mar Bonnin, C, Brambilla, P, Canales-Rodríguez, EJ, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Díaz-Zuluaga, AM, Dima, D, Duchesnay, É, Elvsåshagen, 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, Knöchel, C, Kramer, B, Lafer, B, López-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, Quidé, Y, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarró, S, Satterthwaite, TD, Schene, AH, Sim, K, Ching, CRK, Hibar, DP, Gurholt, TP, Nunes, A, Thomopoulos, SI, Abé, C, Agartz, I, Brouwer, RM, Cannon, DM, de Zwarte, SMC, Eyler, LT, Favre, P, Hajek, T, Haukvik, UK, Houenou, J, Landén, 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, LL, Alda, M, Almeida, J, Alnæs, D, Alonso-Lana, S, Altimus, C, Bauer, M, Baune, BT, Bearden, CE, Bellani, M, Benedetti, F, Berk, M, Bilderbeck, AC, Blumberg, HP, Bøen, E, Bollettini, I, del Mar Bonnin, C, Brambilla, P, Canales-Rodríguez, EJ, Caseras, X, Dandash, O, Dannlowski, U, Delvecchio, G, Díaz-Zuluaga, AM, Dima, D, Duchesnay, É, Elvsåshagen, 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, Knöchel, C, Kramer, B, Lafer, B, López-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, Quidé, Y, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarró, S, Satterthwaite, TD, Schene, AH, and Sim, K
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: 2020

20. What we learn about bipolar disorder from large-scale neuroimaging: Findings and future directions from the ENIGMA Bipolar Disorder Working Group

Author: Ching, C.R.K. (Christopher), Hibar, D.P. (Derrek P.), Gurholt, T.P. (Tiril P.), Nunes, A. (Abraham), Thomopoulos, S.I. (Sophia I.), Abé, C. (Christoph), Agartz, I. (Ingrid), Brouwer, R.M. (Rachel), Cannon, D.M. (Dara), de Zwarte, S.M.C. (Sonja M. C.), Eyler, L.T. (Lisa T.), Favre, P. (Pauline), Hajek, T. (Tomas), Haukvik, U.K. (Unn), Houenou, J. (Josselin), Landén, M. (Mikael), Lett, T.A. (Tristram A.), McDonald, C. (Colm), Nabulsi, L. (Leila), Patel, Y. (Yash), Pauling, M.E. (Melissa E.), Paus, T. (Tomas), Radua, J. (Joaquim), Soeiro-de-Souza, M.G. (Marcio G.), Tronchin, G. (Giulia), van Haren, N.E.M. (Neeltje E. M.), Vieta, E. (Eduard), Walter, H.J. (Henrik), Zeng, L.-L. (Ling-Li), Alda, M. (Martin), Almeida, J. (Jorge), Alnæs, D. (Dag), Alonso-Lana, S. (Silvia), Altimus, C. (Cara), Bauer, M. (Michael), Baune, B.T., Bearden, C.E. (Carrie), Bellani, M. (Marcella), Benedetti, F. (Francesco), Berk, M. (Michael), Bilderbeck, A.C. (Amy C.), Blumberg, H.P. (Hilary P.), Bøen, E. (Erlend), Bollettini, I. (Irene), del Mar Bonnin, C. (Caterina), Brambilla, P. (Paolo), Canales-Rodríguez, E.J. (Erick J.), Caseras, X. (Xavier), Dandash, O. (Orwa), Dannlowski, U. (Udo), Delvecchio, G. (Giuseppe), Díaz-Zuluaga, A.M. (Ana M.), Dima, D. (Danai), Duchesnay, É. (Édouard), Elvsåshagen, T. (Torbjørn), Fears, S. (Scott), Frangou, S. (Sophia), Fullerton, J.M. (Janice M.), Glahn, D.C. (David), Goikolea, J.M. (Jose M.), Green, M.J. (Melissa J.), Grotegerd, D. (Dominik), Gruber, O. (Oliver), Haarman, B.C.M. (Benno), Henry, C. (C.), Howells, F.M. (Fleur M.), Ives-Deliperi, V. (Victoria), Jansen, A. (Andreas), Kircher, T.T.J. (Tilo T. J.), Knöchel, C. (Christian), Kramer, B. (Bernd), Lafer, B. (Beny), López-Jaramillo, C. (Carlos), Machado-Vieira, R. (Rodrigo), MacIntosh, B.J. (Bradley J), Melloni, E.M.T. (Elisa M. T.), Mitchell, P.B. (Philip B.), Nenadic, I. (Igor), Nery, F. (Fabiano), Nugent, A.C. (Allison), Oertel, V. (Viola), Ophoff, R.A. (Roel), Ota, M. (Miho), Overs, B.J. (Bronwyn J.), Pham, D.L. (Daniel L.), Phillips, M.L. (Mary L.), Pineda-Zapata, J.A. (Julian A.), Poletti, S. (Sara), Polosan, M. (Mircea), Pomarol-Clotet, E. (Edith), Pouchon, A. (Arnaud), Quidé, Y. (Yann), Rive, M.M. (Maria M.), Roberts, G. (Gloria), Ruhé, H.G. (Henricus G.Eric), Salvador, R. (Raymond), Sarró, S. (Salvador), Satterthwaite, T.D. (Theodore), Schene, A.H. (Aart), Sim, K. (Kang), Soares, J.C. (Jair C.), Stäblein, M. (Michael), Stein, D.J. (Dan J.), Tamnes, C.K. (Christian K.), Thomaidis, G.V. (Georgios V.), Upegui, C.V. (Cristian Vargas), Veltman, D.J. (Dick), Wessa, M. (Michèle), Westlye, L.T. (Lars), Whalley, H.C. (Heather C.), Wolf, D.H. (Daniel H.), Wu, M.-J. (Mon-Ju), Yatham, L.N. (Lakshmi N.), Zarate, C.A. (Carlos A.), Thompson, P.M. (Paul), Andreassen, O.A. (Ole), Ching, C.R.K. (Christopher), Hibar, D.P. (Derrek P.), Gurholt, T.P. (Tiril P.), Nunes, A. (Abraham), Thomopoulos, S.I. (Sophia I.), Abé, C. (Christoph), Agartz, I. (Ingrid), Brouwer, R.M. (Rachel), Cannon, D.M. (Dara), de Zwarte, S.M.C. (Sonja M. C.), Eyler, L.T. (Lisa T.), Favre, P. (Pauline), Hajek, T. (Tomas), Haukvik, U.K. (Unn), Houenou, J. (Josselin), Landén, M. (Mikael), Lett, T.A. (Tristram A.), McDonald, C. (Colm), Nabulsi, L. (Leila), Patel, Y. (Yash), Pauling, M.E. (Melissa E.), Paus, T. (Tomas), Radua, J. (Joaquim), Soeiro-de-Souza, M.G. (Marcio G.), Tronchin, G. (Giulia), van Haren, N.E.M. (Neeltje E. M.), Vieta, E. (Eduard), Walter, H.J. (Henrik), Zeng, L.-L. (Ling-Li), Alda, M. (Martin), Almeida, J. (Jorge), Alnæs, D. (Dag), Alonso-Lana, S. (Silvia), Altimus, C. (Cara), Bauer, M. (Michael), Baune, B.T., Bearden, C.E. (Carrie), Bellani, M. (Marcella), Benedetti, F. (Francesco), Berk, M. (Michael), Bilderbeck, A.C. (Amy C.), Blumberg, H.P. (Hilary P.), Bøen, E. (Erlend), Bollettini, I. (Irene), del Mar Bonnin, C. (Caterina), Brambilla, P. (Paolo), Canales-Rodríguez, E.J. (Erick J.), Caseras, X. (Xavier), Dandash, O. (Orwa), Dannlowski, U. (Udo), Delvecchio, G. (Giuseppe), Díaz-Zuluaga, A.M. (Ana M.), Dima, D. (Danai), Duchesnay, É. (Édouard), Elvsåshagen, T. (Torbjørn), Fears, S. (Scott), Frangou, S. (Sophia), Fullerton, J.M. (Janice M.), Glahn, D.C. (David), Goikolea, J.M. (Jose M.), Green, M.J. (Melissa J.), Grotegerd, D. (Dominik), Gruber, O. (Oliver), Haarman, B.C.M. (Benno), Henry, C. (C.), Howells, F.M. (Fleur M.), Ives-Deliperi, V. (Victoria), Jansen, A. (Andreas), Kircher, T.T.J. (Tilo T. J.), Knöchel, C. (Christian), Kramer, B. (Bernd), Lafer, B. (Beny), López-Jaramillo, C. (Carlos), Machado-Vieira, R. (Rodrigo), MacIntosh, B.J. (Bradley J), Melloni, E.M.T. (Elisa M. T.), Mitchell, P.B. (Philip B.), Nenadic, I. (Igor), Nery, F. (Fabiano), Nugent, A.C. (Allison), Oertel, V. (Viola), Ophoff, R.A. (Roel), Ota, M. (Miho), Overs, B.J. (Bronwyn J.), Pham, D.L. (Daniel L.), Phillips, M.L. (Mary L.), Pineda-Zapata, J.A. (Julian A.), Poletti, S. (Sara), Polosan, M. (Mircea), Pomarol-Clotet, E. (Edith), Pouchon, A. (Arnaud), Quidé, Y. (Yann), Rive, M.M. (Maria M.), Roberts, G. (Gloria), Ruhé, H.G. (Henricus G.Eric), Salvador, R. (Raymond), Sarró, S. (Salvador), Satterthwaite, T.D. (Theodore), Schene, A.H. (Aart), Sim, K. (Kang), Soares, J.C. (Jair C.), Stäblein, M. (Michael), Stein, D.J. (Dan J.), Tamnes, C.K. (Christian K.), Thomaidis, G.V. (Georgios V.), Upegui, C.V. (Cristian Vargas), Veltman, D.J. (Dick), Wessa, M. (Michèle), Westlye, L.T. (Lars), Whalley, H.C. (Heather C.), Wolf, D.H. (Daniel H.), Wu, M.-J. (Mon-Ju), Yatham, L.N. (Lakshmi N.), Zarate, C.A. (Carlos A.), Thompson, P.M. (Paul), and Andreassen, O.A. (Ole)
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 studi
Published: 2020
Full Text: View/download PDF

21. Correction: Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals (Neuropsychopharmacology, (2019), 44, 13, (2285-2293), 10.1038/s41386-019-0485-6)

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, and Houenou, J
Abstract: This Article was originally published under NPG's License to Publish, but has now been made available under a [CC BY 4.0] license. The PDF and HTML versions of the Article have been modified accordingly.
Published: 2019

22. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Author: Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, Houenou, J, Favre, P, Pauling, M, Stout, J, Hozer, F, Sarrazin, S, Abé, C, Alda, M, Alloza, C, Alonso-Lana, S, Andreassen, OA, Baune, BT, Benedetti, F, Busatto, GF, Canales-Rodríguez, EJ, Caseras, X, Chaim-Avancini, TM, Ching, CRK, Dannlowski, U, Deppe, M, Eyler, LT, Fatjo-Vilas, M, Foley, SF, Grotegerd, D, Hajek, T, Haukvik, UK, Howells, FM, Jahanshad, N, Kugel, H, Lagerberg, TV, Lawrie, SM, Linke, JO, McIntosh, A, Melloni, EMT, Mitchell, PB, Polosan, M, Pomarol-Clotet, E, Repple, J, Roberts, G, Roos, A, Rosa, PGP, Salvador, R, Sarró, S, Schofield, PR, Serpa, MH, Sim, K, Stein, DJ, Sussmann, JE, Temmingh, HS, Thompson, PM, Verdolini, N, Vieta, E, Wessa, M, Whalley, HC, Zanetti, MV, Leboyer, M, Mangin, JF, Henry, C, Duchesnay, E, and Houenou, J
Abstract: Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD); however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD. These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2019

23. P.328 Exploring the correlation between functioning and cognition in bipolar disorder: A fMRI study using the n-back working memory task

Author: Verdolini, N., primary, Simon, G.D., additional, Alonso-Lana, S., additional, Salgado-Pineda, P., additional, Albacete, A., additional, Fuentes-Claramonte, P., additional, Sarró, S., additional, Goikolea, J.M., additional, Bonnin, C.M., additional, Vieta, E., additional, and Pomarol-Clotet, E., additional
Published: 2019
Full Text: View/download PDF

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

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

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

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

Author: Rodriguez-Cano, E, Alonso-Lana, S, Sarro, S, Fernandez-Corcuera, P, Goikolea, JM, Vieta, E, Maristany, T, Salvador, R, McKenna, PJ, Pomarol-Clotet, E, Rodriguez-Cano, E, Alonso-Lana, S, Sarro, S, Fernandez-Corcuera, P, Goikolea, JM, Vieta, E, Maristany, T, Salvador, R, McKenna, PJ, and Pomarol-Clotet, E
Abstract: OBJECTIVES: Neuroimaging studies have revealed evidence of brain functional abnormalities in bipolar depressive disorder (BDD) and major depressive disorder (MDD). However, few studies to date have compared these two mood disorders directly. METHODS: Matched groups of 26 BDD type I patients, 26 MDD patients and 26 healthy controls underwent functional magnetic resonance imaging (fMRI) while performing the n-back working memory task. A whole-brain ANOVA was used to compare the three groups and clusters of significant difference were examined further using region-of-interest (ROI) analysis. RESULTS: The whole-brain ANOVA revealed a single cluster of significant difference in the medial frontal cortex. The BDD and MDD patients both showed failure to deactivate in this area compared to the controls. The BDD patients showed significantly greater failure of deactivation than the MDD patients, which was not accounted for by differences in severity or chronicity of illness between them. CONCLUSIONS: Failure of deactivation, considered to reflect default mode network dysfunction, is present to a greater extent in bipolar than unipolar depression. The study of this network may be useful in the search for brain markers that distinguish the two disorders.
Published: 2017

27. Structural and Functional Brain Correlates of Cognitive Impairment in Euthymic Patients with Bipolar Disorder

Author: Alonso-Lana, S., Goikolea, J.M., Bonnin, C.M., Sarró, S., Segura, B., Amann, B.L., Monté, G.C., Moro, N., Fernandez-Corcuera, P., Maristany M, Salvador, R., Vieta, E., Pomarol-Clotet, E., and McKenna, P.J.
Abstract: Cognitive impairment in the euthymic phase is a well-established finding in bipolar disorder. However, its brain structural and/or functional correlates are uncertain.
Published: 2016
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28. Brain correlates of impaired insight and social cognition in schizophrenia

Author: Martin-Subero, M., primary, Salgado-Pineda, P., additional, Salvador, R., additional, Fuentes-Claramonte, P., additional, Alonso-Lana, S., additional, Sarró, S., additional, Pomarol-Clotet, E., additional, and Mckenna, P., additional
Published: 2017
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29. Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder

Author: Amann, BL, Canales-Rodriguez, J, Madre, M, Radua, J, Monte, G, Alonso-Lana, S, Landin-Romero, R, Moreno-Alcazar, A, Bonnin, CM, Sarro, S, Ortiz-Gil, J, Gomar, JJ, Moro, N, Fernandez-Corcuera, P, Goikolea, JM, Blanch, J, Salvador, R, Vieta, E, McKenna, PJ, Pomarol-Clotet, E, Amann, BL, Canales-Rodriguez, J, Madre, M, Radua, J, Monte, G, Alonso-Lana, S, Landin-Romero, R, Moreno-Alcazar, A, Bonnin, CM, Sarro, S, Ortiz-Gil, J, Gomar, JJ, Moro, N, Fernandez-Corcuera, P, Goikolea, JM, Blanch, J, Salvador, R, Vieta, E, McKenna, PJ, and Pomarol-Clotet, E
Abstract: OBJECTIVE: Brain structural changes in schizoaffective disorder, and how far they resemble those seen in schizophrenia and bipolar disorder, have only been studied to a limited extent. METHOD: Forty-five patients meeting DSM-IV and RDC criteria for schizoaffective disorder, groups of patients with 45 matched schizophrenia and bipolar disorder, and 45 matched healthy controls were examined using voxel-based morphometry (VBM). RESULTS: Analyses comparing each patient group with the healthy control subjects found that the patients with schizoaffective disorder and the patients with schizophrenia showed widespread and overlapping areas of significant volume reduction, but the patients with bipolar disorder did not. A subsequent analysis compared the combined group of patients with the controls followed by extraction of clusters. In regions where the patients differed significantly from the controls, no significant differences in mean volume between patients with schizoaffective disorder and patients with schizophrenia in any of five regions of volume reduction were found, but mean volumes in the patients with bipolar disorder were significantly smaller in three of five. CONCLUSION: The findings provide evidence that, in terms of structural gray matter brain abnormality, schizoaffective disorder resembles schizophrenia more than bipolar disorder.
Published: 2016

30. Structural and Functional Brain Correlates of Cognitive Impairment in Euthymic Patients with Bipolar Disorder

Author: Walss-Bass, C, Alonso-Lana, S, Goikolea, JM, Bonnin, CM, Sarro, S, Segura, B, Amann, BL, Monte, GC, Moro, N, Fernandez-Corcuera, P, Maristany, T, Salvador, R, Vieta, E, Pomarol-Clotet, E, McKenna, PJ, Walss-Bass, C, Alonso-Lana, S, Goikolea, JM, Bonnin, CM, Sarro, S, Segura, B, Amann, BL, Monte, GC, Moro, N, Fernandez-Corcuera, P, Maristany, T, Salvador, R, Vieta, E, Pomarol-Clotet, E, and McKenna, PJ
Abstract: INTRODUCTION: Cognitive impairment in the euthymic phase is a well-established finding in bipolar disorder. However, its brain structural and/or functional correlates are uncertain. METHODS: Thirty-three euthymic bipolar patients with preserved memory and executive function and 28 euthymic bipolar patients with significant memory and/or executive impairment, as defined using two test batteries, the Rivermead Behavioural Memory Test (RBMT) and the Behavioural Assessment of the Dysexecutive Syndrome (BADS), plus 28 healthy controls underwent structural MRI using voxel-based morphometry (VBM). Twenty-seven of the cognitively preserved patients, 23 of the cognitively impaired patients and 28 controls also underwent fMRI during performance of the n-back working memory task. RESULTS: No clusters of grey or white matter volume difference were found between the two patient groups. During n-back performance, the cognitively impaired patients showed hypoactivation compared to the cognitively preserved patients in a circumscribed region in the right dorsolateral prefrontal cortex. Both patient groups showed failure of de-activation in the medial frontal cortex compared to the healthy controls. CONCLUSIONS: Cognitive impairment in euthymic bipolar patients appears from this study to be unrelated to structural brain abnormality, but there was some evidence for an association with altered prefrontal function.
Published: 2016

31. Adolescent cannabis use: what is the evidence for functional brain alteration?

Author: Lorenzetti, Valentina, Alonso-Lana, S, Youssef, George J, Verdejo-Garcia, Antonio, Suo, Chao, Cousijn, Janna, Takagi, Michael J, Yücel, Murat, Solowij, Nadia, Lorenzetti, Valentina, Alonso-Lana, S, Youssef, George J, Verdejo-Garcia, Antonio, Suo, Chao, Cousijn, Janna, Takagi, Michael J, Yücel, Murat, and Solowij, Nadia
Abstract: Background: Cannabis use typically commences during adolescence, a period during which the brain undergoes profound remodeling in areas that are high in cannabinoid receptors and that mediate cognitive control and emotion regulation. It is therefore important to determine the impact of adolescent cannabis use on brain function. Objective: We investigate the impact of adolescent cannabis use on brain function by reviewing the functional magnetic resonance imaging studies in adolescent samples. Method: We systematically reviewed the literature and identified 13 functional neuroimaging studies in adolescent cannabis users (aged 13 to 18 years) performing working memory, inhibition and reward processing tasks. Results: The majority of the studies found altered brain function, but intact Behav task performance in adolescent cannabis users versus controls. The most consistently reported differences were in the frontal-parietal network, which mediates cognitive control. Heavier use was associated with abnormal brain function in most samples. A minority of studies controlled for the influence of confounders that can also undermine brain function, such as tobacco and alcohol use, psychopathology symptoms and family history of psychiatric disorders and substance use. Conclusion: Emerging evidence shows abnormal frontal-parietal network activity in adolescent cannabis users, particularly in heavier users. Brain functional alterations may reflect a compensatory neural mechanism that enables normal Behav performance. It remains unclear if cannabis exposure drives these alterations, as substance use and mental health confounders have not been systematically examined.
Published: 2016

32. Testing theories of default mode function and its dysfunction in schizophrenia

Author: Martin-Subero, M., primary, Salgado- Pineda, P., additional, Fuentes, P., additional, Alonso-Lana, S., additional, Salavert, J., additional, Arévalo, A., additional, Salvador, R., additional, Pomarol-Clotet, E., additional, and McKenna, P., additional
Published: 2016
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33. Brain functional changes in first-degree relatives of patients with bipolar disorder: evidence for default mode network dysfunction

Author: Alonso-Lana, S., primary, Valentí, M., additional, Romaguera, A., additional, Sarri, C., additional, Sarró, S., additional, Rodríguez-Martínez, A., additional, Goikolea, J. M., additional, Amann, B. L., additional, Maristany, T., additional, Salvador, R., additional, Vieta, E., additional, McKenna, P. J., additional, and Pomarol-Clotet, E., additional
Published: 2016
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34. Brain structural changes in schizoaffective disorder compared to schizophrenia and bipolar disorder

Author: Amann, B. L., primary, Canales‐Rodríguez, E. J., additional, Madre, M., additional, Radua, J., additional, Monte, G., additional, Alonso‐Lana, S., additional, Landin‐Romero, R., additional, Moreno‐Alcázar, A., additional, Bonnin, C. M., additional, Sarró, S., additional, Ortiz‐Gil, J., additional, Gomar, J. J., additional, Moro, N., additional, Fernandez‐Corcuera, P., additional, Goikolea, J. M., additional, Blanch, J., additional, Salvador, R., additional, Vieta, E., additional, McKenna, P. J., additional, and Pomarol‐Clotet, E., additional
Published: 2015
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35. P.1.i.031 - Brain correlates of impaired insight and social cognition in schizophrenia

Author: Martin-Subero, M., Salgado-Pineda, P., Salvador, R., Fuentes-Claramonte, P., Alonso-Lana, S., Sarró, S., Pomarol-Clotet, E., and Mckenna, P.
Published: 2017
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36. P.1.i.038 - Testing theories of default mode function and its dysfunction in schizophrenia

Author: Martin-Subero, M., Salgado- Pineda, P., Fuentes, P., Alonso-Lana, S., Salavert, J., Arévalo, A., Salvador, R., Pomarol-Clotet, E., and McKenna, P.
Published: 2016
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37. Brain functional changes across the different phases of bipolar disorder

Author: Pomarol-Clotet E, Alonso-Lana S, Moro N, Sarró S, Mc, Bonnin, Jm, Goikolea, Fernández-Corcuera P, Benedikt L Amann, Romaguera A, Vieta E, Blanch J, Pj, Mckenna, and Salvador R

38. Longitudinal brain functional changes between mania and euthymia in bipolar disorder

Author: Alonso-Lana S, Moro N, Pj, Mckenna, Sarró S, Romaguera A, Gc, Monté, Maristany T, Jm, Goikolea, Eduard Vieta, Salvador R, and Pomarol-Clotet E
Subjects: fMRI, bipolar disorder, working memory, mental disorders, follow-up, default-mode network, behavioral disciplines and activities, psychological phenomena and processes
Abstract: OBJECTIVES: While widespread cortical and subcortical brain functional abnormalities have been found in bipolar disorder, the changes that take place between illness phases and recovery are less clearly documented. Only a small number of longitudinal studies of manic patients, in particular, have been carried out. METHODS: Twenty-six bipolar patients underwent fMRI during performance of the n-back working memory task when manic and again after recovery. Twenty-six matched healthy controls were also scanned on two occasions. Task-related activations and de-activations were examined. RESULTS: When manic, the patients showed clusters of significantly reduced activation in the left dorsolateral prefrontal cortex (DLPFC)/precentral cortex and the parietal cortex/superior precuneus bilaterally. They also showed failure of de-activation in the ventromedial frontal cortex (vmPFC). After recovery, activation in the left DLPFC/precentral cortex and in the bilateral parietal cortex/superior precuneus clusters increased significantly. However, failure of de-activation remained present in the vmPFC. CONCLUSIONS: Recovery from mania is associated with normalization of DLPFC and parietal hypoactivation, but not with vmPFC failure of de-activation, which accordingly appears to represent a trait abnormality in the disorder.

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

Author: Abe, C., Ching, C.R.K., Liberg, B., Lebedev, A.V., Agartz, I., Akudjedu, Theophilus. N., Alda, M., Alnæs, D., Alonso-Lana, S., Benedetti, F., Berk, M., Bøen, E., Bonnin, C.D.M., Breuer, F., Brosch, K., Brouwer, R.M., Canales-Rodríguez, E.J., Cannon, D.M., Chye, Y., Dahl, A., Dandash, O., Dannlowski, U., Dohm, K., Elvsåshagen, T., Fisch, L., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Haatveit, B., Hahn, T., Hajek, T., Heindel, W., Ingvar, M., Sim, K., Kircher, T.T.J., Lenroot, R.K., Malt, U.F., McDonald, C., McWhinney, S.R., Melle, I., Meller, T., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Opel, N., Overs, B.J., Panicalli, F., Pfarr, J.K., Poletti, S., Pomarol-Clotet, E., Radua, J., Repple, J., Ringwald, K.G., Roberts, G., Rodriguez-Cano, E., Salvador, R., Sarink, K., Sarró, S., Schmitt, S., Stein, F., Suo, C., Thomopoulos, S.I., Tronchin, G., Vieta, E., Westlye, L.T., White, A.G., Yatham, L.N., Zak, N., Thompson, P.M., Andreassen, O.A., Landen, M., Abe, C., Ching, C.R.K., Liberg, B., Lebedev, A.V., Agartz, I., Akudjedu, Theophilus. N., Alda, M., Alnæs, D., Alonso-Lana, S., Benedetti, F., Berk, M., Bøen, E., Bonnin, C.D.M., Breuer, F., Brosch, K., Brouwer, R.M., Canales-Rodríguez, E.J., Cannon, D.M., Chye, Y., Dahl, A., Dandash, O., Dannlowski, U., Dohm, K., Elvsåshagen, T., Fisch, L., Fullerton, J.M., Goikolea, J.M., Grotegerd, D., Haatveit, B., Hahn, T., Hajek, T., Heindel, W., Ingvar, M., Sim, K., Kircher, T.T.J., Lenroot, R.K., Malt, U.F., McDonald, C., McWhinney, S.R., Melle, I., Meller, T., Melloni, E.M.T., Mitchell, P.B., Nabulsi, L., Nenadić, I., Opel, N., Overs, B.J., Panicalli, F., Pfarr, J.K., Poletti, S., Pomarol-Clotet, E., Radua, J., Repple, J., Ringwald, K.G., Roberts, G., Rodriguez-Cano, E., Salvador, R., Sarink, K., Sarró, S., Schmitt, S., Stein, F., Suo, C., Thomopoulos, S.I., Tronchin, G., Vieta, E., Westlye, L.T., White, A.G., Yatham, L.N., Zak, N., Thompson, P.M., Andreassen, O.A., and Landen, 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.

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

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

41. What we learn about bipolar disorder from large-scale neuroimaging

Author: Christian K. Tamnes, Bartholomeus C M Haarman, Jair C. Soares, Ole A. Andreassen, Viola Oertel, Theodore D. Satterthwaite, G. Tronchin, Michael Stäblein, Bradley J. MacIntosh, Melissa Pauling, Christopher R.K. Ching, Daniel H. Wolf, Dick J. Veltman, Ingrid Agartz, Bernhard T. Baune, Salvador Sarró, Mon-Ju Wu, Scott C Fears, Eduard Vieta, Melissa J. Green, Neeltje E.M. van Haren, Yann Quidé, Erlend Bøen, Yash Patel, Igor Nenadic, Martin Alda, Lisa T. Eyler, Arnaud Pouchon, Danai Dima, Tomáš Paus, Irene Bollettini, Torbjørn Elvsåshagen, Rachel M. Brouwer, Lakshmi N. Yatham, Michael Bauer, Caterina del Mar Bonnín, C. McDonald, Udo Dannlowski, Bronwyn Overs, Edith Pomarol-Clotet, Cristian Vargas Upegui, Oliver Gruber, Henricus G. Ruhé, Márcio Gerhardt Soeiro-de-Souza, Edouard Duchesnay, Hilary P. Blumberg, Tilo Kircher, Miho Ota, Michael Berk, Christoph Abé, Andreas Jansen, Kang Sim, Heather C. Whalley, Derrek P. Hibar, Roel A. Ophoff, Georgios V Thomaidis, Henrik Walter, Sophia Frangou, Michèle Wessa, Dara M. Cannon, Cara M. Altimus, Allison C. Nugent, Rodrigo Machado-Vieira, Orwa Dandash, Marcella Bellani, Unn K. Haukvik, Philip B. Mitchell, Ling-Li Zeng, Christian Knöchel, Jose Manuel Goikolea, Sonja M C de Zwarte, Francesco Benedetti, Sara Poletti, Janice M. Fullerton, Carlos A. Zarate, Aart H. Schene, Dan J. Stein, Chantal Henry, Tristram A. Lett, Mikael Landén, Daniel L Pham, Paolo Brambilla, Silvia Alonso-Lana, Sophia I. Thomopoulos, Carlos López-Jaramillo, Tomas Hajek, Bernd Kramer, G. Delvecchio, Maria M. Rive, Lars T. Westlye, Erick J. Canales-Rodríguez, Victoria L. Ives-Deliperi, Dominik Grotegerd, Beny Lafer, Abraham Nunes, Carrie E. Bearden, Raymond Salvador, Joaquim Radua, Amy C Bilderbeck, Xavier Caseras, Paul M. Thompson, Jorge R. C. Almeida, Pauline Favre, Gloria Roberts, David C. Glahn, Dag Alnæs, Julian A Pineda-Zapata, Tiril P. Gurholt, Mircea Polosan, Josselin Houenou, Fabiano G. Nery, Leila Nabulsi, Mary L. Phillips, Fleur M. Howells, Ana M. Díaz-Zuluaga, Elisa M T Melloni, Ching, C. R. K., Hibar, D. P., Gurholt, T. P., Nunes, A., Thomopoulos, S. I., Abe, C., Agartz, I., Brouwer, R. M., Cannon, D. M., de Zwarte, S. M. C., Eyler, L. T., Favre, P., Hajek, T., Haukvik, U. K., Houenou, J., Landen, M., Lett, T. A., Mcdonald, C., Nabulsi, L., Patel, Y., Pauling, M. E., Paus, T., Radua, J., Soeiro-de-Souza, M. G., Tronchin, G., van Haren, N. E. M., Vieta, E., Walter, H., Zeng, L. -L., Alda, M., Almeida, J., Alnaes, D., Alonso-Lana, S., Altimus, C., Bauer, M., Baune, B. T., Bearden, C. E., Bellani, M., Benedetti, F., Berk, M., Bilderbeck, A. C., Blumberg, H. P., Boen, E., Bollettini, I., del Mar Bonnin, C., Brambilla, P., Canales-Rodriguez, E. J., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Diaz-Zuluaga, A. M., Dima, D., Duchesnay, E., Elvsashagen, T., Fears, S. C., Frangou, S., Fullerton, J. M., Glahn, D. C., Goikolea, J. M., Green, M. J., Grotegerd, D., Gruber, O., Haarman, B. C. M., Henry, C., Howells, F. M., Ives-Deliperi, V., Jansen, A., Kircher, T. T. J., Knochel, C., Kramer, B., Lafer, B., Lopez-Jaramillo, C., Machado-Vieira, R., Macintosh, B. J., Melloni, E. M. T., Mitchell, P. B., Nenadic, I., Nery, F., Nugent, A. C., Oertel, V., Ophoff, R. A., Ota, M., Overs, B. J., Pham, D. L., Phillips, M. L., Pineda-Zapata, J. A., Poletti, S., Polosan, M., Pomarol-Clotet, E., Pouchon, A., Quide, Y., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarro, S., Satterthwaite, T. D., Schene, A. H., Sim, K., Soares, J. C., Stablein, M., Stein, D. J., Tamnes, C. K., Thomaidis, G. V., Upegui, C. V., Veltman, D. J., Wessa, M., Westlye, L. T., Whalley, H. C., Wolf, D. H., Wu, M. -J., Yatham, L. N., Zarate, C. A., Thompson, P. M., and Andreassen, O. A.
Subjects: mega-analysis, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], cortical surface area, Review Article, 0302 clinical medicine, Manic-depressive illness, Multicenter Studies as Topic, Spectrum disorder, Review Articles, bipolar disorder, Cerebral Cortex, Trastorn bipolar, neuroimaging, Radiological and Ultrasound Technology, 05 social sciences, ENIGMA, HUMAN BRAIN, Magnetic Resonance Imaging, psychiatry, 3. Good health, Neurology, Meta-analysis, Scale (social sciences), Anatomy, Psychology, Clinical risk factor, Clinical psychology, MRI, MAJOR PSYCHIATRIC-DISORDERS, Schizoaffective disorder, 050105 experimental psychology, 03 medical and health sciences, Magnetic resonance imaging, Neuroimaging, Meta-Analysis as Topic, SDG 3 - Good Health and Well-being, Imatges per ressonància magnètica, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Bipolar disorder, HIPPOCAMPAL VOLUMES, mega‐analysis, GRAY-MATTER VOLUME, SPECTRUM DISORDER, volume, DIABETES-MELLITUS, cortical thickness, COGNITIVE IMPAIRMENT, medicine.disease, Mental illness, meta-analysis, meta‐analysis, RC0321, Neurology (clinical), SCHIZOAFFECTIVE DISORDER, PSYCHOTIC FEATURES, 030217 neurology & neurosurgery
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., This review discusses the major challenges facing neuroimaging research of bipolar disorder and highlights the major accomplishments, ongoing challenges and future goals of the ENIGMA Bipolar Disorder Working Group.
Published: 2022
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42. Longitudinal structural brain changes in bipolar disorder: A multicenter neuroimaging study of 1232 individuals by the ENIGMA Bipolar Disorder Working Group

Author: Theophilus N. Akudjedu, Frederike Stein, Edith Pomarol-Clotet, Lars T. Westlye, Ulrik Fredrik Malt, Erlend Bøen, Fabian Breuer, Chao Suo, Tina Meller, Tim Hahn, Francesco Benedetti, Jose Manuel Goikolea, Silvia Alonso-Lana, Adam George White, Dag Alnæs, Julia-Katharina Pfarr, Beathe Haatveit, Sara Poletti, Kai Ringwald, Nathalia Zak, Benny Liberg, Kelvin Sarink, Giulia Tronchin, Yann Chye, Janice M. Fullerton, Orwa Dandash, Igor Nenadic, Caterina del Mar Bonnín, Elisa M T Melloni, Udo Dannlowski, Michael Berk, Dominik Grotegerd, Christopher R.K. Ching, Lukas Fisch, Torbjørn Elvsåshagen, Andreas Dahl, Martin Alda, Francesco Panicalli, Ingrid Agartz, Martin Ingvar, Bronwyn Overs, Joaquim Radua, Katharina Brosch, Alexander V. Lebedev, Kang Sim, Tilo Kircher, Leila Nabulsi, Dara M. Cannon, Erick J. Canales-Rodríguez, Paul M. Thompson, Nils Opel, Jonathan Repple, R. Salvador, Katharina Dohm, Philip B. Mitchell, Colm McDonald, Salvador Sarró, Rachel M. Brouwer, Ole A. Andreassen, Tomas Hajek, Mikael Landén, Simon Schmitt, Sophia I. Thomopoulos, Elena Rodriguez-Cano, Eduard Vieta, Ingrid Melle, Rhoshel K. Lenroot, Lakshmi N. Yatham, Sean R. McWhinney, Gloria Roberts, Christoph Abé, Walter Heindel, Abe, C., Ching, C. R. K., Liberg, B., Lebedev, A. V., Agartz, I., Akudjedu, T. N., Alda, M., Alnaes, D., Alonso-Lana, S., Benedetti, F., Berk, M., Boen, E., Bonnin, C. D. M., Breuer, F., Brosch, K., Brouwer, R. M., Canales-Rodriguez, E. J., Cannon, D. M., Chye, Y., Dahl, A., Dandash, O., Dannlowski, U., Dohm, K., Elvsashagen, T., Fisch, L., Fullerton, J. M., Goikolea, J. M., Grotegerd, D., Haatveit, B., Hahn, T., Hajek, T., Heindel, W., Ingvar, M., Sim, K., Kircher, T. T. J., Lenroot, R. K., Malt, U. F., Mcdonald, C., Mcwhinney, S. R., Melle, I., Meller, T., Melloni, E. M. T., Mitchell, P. B., Nabulsi, L., Nenadic, I., Opel, N., Overs, B. J., Panicalli, F., Pfarr, J. -K., Poletti, S., Pomarol-Clotet, E., Radua, J., Repple, J., Ringwald, K. G., Roberts, G., Rodriguez-Cano, E., Salvador, R., Sarink, K., Sarro, S., Schmitt, S., Stein, F., Suo, C., Thomopoulos, S. I., Tronchin, G., Vieta, E., Westlye, L. T., White, A. G., Yatham, L. N., Zak, N., Thompson, P. M., Andreassen, O. A., Landen, M., Complex Trait Genetics, and Amsterdam Neuroscience - Complex Trait Genetics
Subjects: Adult, Male, Longitudinal study, medicine.medical_specialty, Bipolar disorder, Neuroimaging, volume changes, surface-based analysis, Young Adult, gray-matter, Cortex (anatomy), Internal medicine, medicine, Humans, Multicenter Studies as Topic, Biological Psychiatry, mri, human cerebral-cortex, Psychiatry, medicine.diagnostic_test, business.industry, ENIGMA, Brain, Magnetic resonance imaging, Cerebral Cortical Thinning, Middle Aged, cortical thickness, medicine.disease, Magnetic Resonance Imaging, Neuroprogression, Mania, genetic influences, medicine.anatomical_structure, Mood, Meta-analysis, Cardiology, lithium treatment, Female, medicine.symptom, i disorder, business, metaanalysis
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
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43. In vivo hippocampal subfield volumes in bipolar disorder-A mega-analysis from The Enhancing Neuro Imaging Genetics throughMeta-AnalysisBipolar Disorder Working Group

Author: Sophia I. Thomopoulos, Julian A Pineda-Zapata, Ronny Redlich, Bartholomeus C M Haarman, Mathew A. Harris, Orwa Dandash, Ulrik Fredrik Malt, Lauren E. Salminen, Michael Stäblein, Theo G.M. van Erp, Gloria Roberts, Michael Berk, Jochen Bauer, Edith Pomarol-Clotet, Carlos López-Jaramillo, Dominik Grotegerd, Tomas Hajek, Paul M. Thompson, Philipp G. Sämann, Francesco Benedetti, Tilo Kircher, Brian Hallahan, Jonathan Repple, Lena Waltemate, Maria M. Rive, Heather C. Whalley, Caterina del Mar Bonnín, Oliver Gruber, Igor Nenadic, Udo Dannlowski, Henricus G. Ruhé, Raymond Salvador, Bronwyn Overs, Torbjørn Elvsåshagen, Márcio Gerhardt Soeiro-de-Souza, Ana M. Díaz-Zuluaga, Katharina Förster, Jose Manuel Goikolea, Emma L. Hawkins, Vera Lonning, Silvia Alonso-Lana, Dan J. Stein, Theophilus N. Akudjedu, Elisa M T Melloni, Dag Alnæs, Nils Opel, Martin Alda, Rayus Kuplicki, Erlend Bøen, Salvador Sarró, Unn K. Haukvik, Philip B. Mitchell, Kang Sim, Lisa Rauer, Ole A. Andreassen, Colm McDonald, Eduard Vieta, Erick J. Canales-Rodríguez, Axel Krug, Viola Oertel, Frederike Stein, Xavier Caseras, Christopher R.K. Ching, Lucio Oldani, Dara M. Cannon, Andrew M. McIntosh, Kjetil Nordbø Jørgensen, Ingrid Melle, Rhoshel K. Lenroot, Lars T. Westlye, Giuseppe Delvecchio, Dick J. Veltman, Mar Fatjó-Vilas, Trine Vik Lagerberg, Leila Nabulsi, Henk Temmingh, Carina Hülsmann, Francesco Bettella, Paolo Brambilla, Dennis van der Meer, Sonya Foley, Tiril P. Gurholt, Fleur M. Howells, Joaquim Radua, Thomas M. Lancaster, Christian K. Tamnes, Maria Cg Otaduy, Jonathan Savitz, Stener Nerland, Genevieve McPhilemy, Janice M. Fullerton, Aart H. Schene, Neda Jahanshad, Ingrid Agartz, Bernhard T. Baune, Beathe Haatveit, Bernd Krämer, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, Haukvik, U. K., Gurholt, T. P., Nerland, S., Elvsashagen, T., Akudjedu, T. N., Alda, M., Alnaes, D., Alonso-Lana, S., Bauer, J., Baune, B. T., Benedetti, F., Berk, M., Bettella, F., Boen, E., Bonnin, C. M., Brambilla, P., Canales-Rodriguez, E. J., Cannon, D. M., Caseras, X., Dandash, O., Dannlowski, U., Delvecchio, G., Diaz-Zuluaga, A. M., van Erp, T. G. M., Fatjo-Vilas, M., Foley, S. F., Forster, K., Fullerton, J. M., Goikolea, J. M., Grotegerd, D., Gruber, O., Haarman, B. C. M., Haatveit, B., Hajek, T., Hallahan, B., Harris, M., Hawkins, E. L., Howells, F. M., Hulsmann, C., Jahanshad, N., Jorgensen, K. N., Kircher, T., Kramer, B., Krug, A., Kuplicki, R., Lagerberg, T. V., Lancaster, T. M., Lenroot, R. K., Lonning, V., Lopez-Jaramillo, C., Malt, U. F., Mcdonald, C., Mcintosh, A. M., Mcphilemy, G., van der Meer, D., Melle, I., Melloni, E. M. T., Mitchell, P. B., Nabulsi, L., Nenadic, I., Oertel, V., Oldani, L., Opel, N., Otaduy, M. C. G., Overs, B. J., Pineda-Zapata, J. A., Pomarol-Clotet, E., Radua, J., Rauer, L., Redlich, R., Repple, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salminen, L. E., Salvador, R., Sarro, S., Savitz, J., Schene, A. H., Sim, K., Soeiro-de-Souza, M. G., Stablein, M., Stein, D. J., Stein, F., Tamnes, C. K., Temmingh, H. S., Thomopoulos, S. I., Veltman, D. J., Vieta, E., Waltemate, L., Westlye, L. T., Whalley, H. C., Samann, P. G., Thompson, P. M., Ching, C. R. K., Andreassen, O. A., Agartz, I., Clinical Cognitive Neuropsychiatry Research Program (CCNP), Psychiatry, Anatomy and neurosciences, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, and Adult Psychiatry
Subjects: structural brain MRI, Bipolar Disorder, HALOPERIDOL, hippocampus, Stress-related disorders Donders Center for Medical Neuroscience [Radboudumc 13], SEGMENTATION, Hippocampus, Hippocampal formation, 0302 clinical medicine, SCHIZOPHRENIA, Manic-depressive illness, psychosis, BRAIN, Research Articles, Trastorn bipolar, Radiological and Ultrasound Technology, 05 social sciences, Subiculum, ATLAS, Magnetic Resonance Imaging, Liti, 3. Good health, medicine.anatomical_structure, Neurology, Schizophrenia, lithium, Anatomy, Hippocampus (Brain), Research Article, MRI, INTERNEURONS, Psychosis, Hipocamp (Cervell), Neuroimaging, Amygdala, 050105 experimental psychology, CELL-PROLIFERATION, 03 medical and health sciences, Genetics, medicine, Humans, 0501 psychology and cognitive sciences, Radiology, Nuclear Medicine and imaging, Bipolar disorder, large‐scale, LITHIUM-TREATED PATIENTS, business.industry, Dentate gyrus, medicine.disease, nervous system, DENTATE GYRUS, large-scale, bipolar disorder subtype, Neurology (clinical), business, Neuroscience, 030217 neurology & neurosurgery
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., The hippocampus consists of anatomically and functionally distinct subfields that may be differentially involved in the pathophysiology of bipolar disorder.In the largest study of hippocampal subfields in bipolar disorder to date, from 23 sites worldwide, we report widespread reductions in nine of 12 subfields.The lack of differences between lithium users and healthy controls supports a possible protective role of lithium in bipolar disorder.
Published: 2022
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44. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Author: Committee, Writing, Disorder, Autism Spectrum, French, Leon, Grevet, Eugenio H, Groenewold, Nynke A, Grotegerd, Dominik, Gruber, Oliver, Gruner, Patricia, Guerrero-Pedraza, Amalia, Gur, Raquel E, Gur, Ruben C, Haar, Shlomi, Haarman, Bartholomeus C M, Thomopoulos, Sophia I, Haavik, Jan, Hahn, Tim, Hajek, Tomas, Harrison, Benjamin J, Harrison, Neil A, Hartman, Catharina A, Whalley, Heather C, Heslenfeld, Dirk J, Hibar, Derrek P, Hilland, Eva, Pozzi, Elena, Hirano, Yoshiyuki, Ho, Tiffany C, Hoekstra, Pieter J, Hoekstra, Liesbeth, Hohmann, Sarah, Hong, L. E., Höschl, Cyril, Høvik, Marie F, Howells, Fleur M, Nenadic, Igor, Abe, Yoshinari, Jalbrzikowski, Maria, James, Anthony C, Janssen, Joost, Jaspers-Fayer, Fern, Xu, Jian, Jonassen, Rune, Karkashadze, Georgii, King, Joseph A, Kircher, Tilo, Kirschner, Matthias, Abé, Christoph, Koch, Kathrin, Kochunov, Peter, Kohls, Gregor, Konrad, Kerstin, Krämer, Bernd, Krug, Axel, Kuntsi, Jonna, Kwon, Jun Soo, Landén, Mikael, Landrø, Nils I, Anticevic, Alan, Lazaro, Luisa, Lebedeva, Irina S, Leehr, Elisabeth J, Lera-Miguel, Sara, Lesch, Klaus-Peter, Lochner, Christine, Louza, Mario R, Luna, Beatriz, Lundervold, Astri J, MacMaster, Frank P, Alda, Martin, Maglanoc, Luigi A, Malpas, Charles B, Portella, Maria J, Marsh, Rachel, Martyn, Fiona M, Mataix-Cols, David, Mathalon, Daniel H, McCarthy, Hazel, McDonald, Colm, McPhilemy, Genevieve, Aleman, Andre, Meinert, Susanne, Menchón, José M, Minuzzi, Luciano, Mitchell, Philip B, Moreno, Carmen, Morgado, Pedro, Muratori, Filippo, Murphy, Clodagh M, Murphy, Declan, Mwangi, Benson, Alloza, Clara, Nabulsi, Leila, Nakagawa, Akiko, Nakamae, Takashi, Namazova, Leyla, Narayanaswamy, Janardhanan, Jahanshad, Neda, Nguyen, Danai D, Nicolau, Rosa, O'Gorman Tuura, Ruth L, O'Hearn, Kirsten, Alonso-Lana, Silvia, Oosterlaan, Jaap, Opel, Nils, Ophoff, Roel A, Oranje, Bob, García de la Foz, Victor Ortiz, Overs, Bronwyn J, Paloyelis, Yannis, Pantelis, Christos, Parellada, Mara, Pauli, Paul, Disorder, Bipolar, Ameis, Stephanie H, Picó-Pérez, Maria, Picon, Felipe A, Piras, Fabrizio, Piras, Federica, Plessen, Kerstin J, Pomarol-Clotet, Edith, Preda, Adrian, Puig, Olga, Quidé, Yann, Radua, Joaquim, Anagnostou, Evdokia, Ramos-Quiroga, J Antoni, Rasser, Paul E, Rauer, Lisa, Reddy, Janardhan, Redlich, Ronny, Reif, Andreas, Reneman, Liesbeth, Repple, Jonathan, Retico, Alessandra, Richarte, Vanesa, McIntosh, Andrew A, Richter, Anja, Rosa, Pedro G P, Rubia, Katya K, Hashimoto, Ryota, Sacchet, Matthew D, Salvador, Raymond, Santonja, Javier, Sarink, Kelvin, Sarró, Salvador, Satterthwaite, Theodore D, Arango, Celso, Sawa, Akira, Schall, Ulrich, Schofield, Peter R, Schrantee, Anouk, Seitz, Jochen, Serpa, Mauricio H, Setién-Suero, Esther, Shaw, Philip, Shook, Devon, Silk, Tim J, Arnold, Paul D, Sim, Kang, Simon, Schmitt, Simpson, Helen Blair, Singh, Aditya, Skoch, Antonin, Skokauskas, Norbert, Soares, Jair C, Soreni, Noam, Soriano-Mas, Carles, Spalletta, Gianfranco, Asherson, Philip, Spaniel, Filip, Lawrie, Stephen M, Stern, Emily R, Stewart, S Evelyn, Takayanagi, Yoichiro, Temmingh, Henk S, Tolin, David F, Tomecek, David, Tordesillas-Gutiérrez, Diana, Tosetti, Michela, Assogna, Francesca, Uhlmann, Anne, van Amelsvoort, Therese, van der Wee, Nic J A, van der Werff, Steven J A, van Haren, Neeltje E M, van Wingen, Guido A, Vance, Alasdair, Vázquez-Bourgon, Javier, Vecchio, Daniela, Venkatasubramanian, Ganesan, Auzias, Guillaume, Vieta, Eduard, Vilarroya, Oscar, Vives-Gilabert, Yolanda, Voineskos, Aristotle N, Völzke, Henry, von Polier, Georg G, Walton, Esther, Weickert, Thomas W, Weickert, Cynthia Shannon, Weideman, Andrea S, Ayesa-Arriola, Rosa, Wittfeld, Katharina, Wolf, Daniel H, Wu, Mon-Ju, Yang, T. T., Yang, Sikun, Yoncheva, Yuliya, Yun, Je-Yeon, Cheng, Yuqi, Zanetti, Marcus V, Ziegler, Georg C, Bakker, Geor, Franke, Barbara, Hoogman, Martine, Buitelaar, Jan K, van Rooij, Daan, Andreassen, Ole A, Ching, Christopher R K, Veltman, Dick J, Schmaal, Lianne, Stein, Dan J, van den Heuvel, Odile A, Disorder, Major Depressive, Banaj, Nerisa, Turner, Jessica A, van Erp, Theo G M, Pausova, Zdenka, Thompson, Paul M, Paus, Tomáš, Attention-Deficit/Hyperactivity Disorder, Banaschewski, Tobias, Bandeira, Cibele E, Baranov, Alexandr, Bargalló, Núria, Bau, Claiton H D, Baumeister, Sarah, Baune, Bernhard T, Bellgrove, Mark A, Benedetti, Francesco, Disorder, Obsessive-Compulsive, Bertolino, Alessandro, Boedhoe, Premika S W, Boks, Marco, Bollettini, Irene, Del Mar Bonnin, Caterina, Borgers, Tiana, Borgwardt, Stefan, Brandeis, Daniel, Brennan, Brian P, Bruggemann, Jason M, Groups, Schizophrenia ENIGMA Working, Bülow, Robin, Busatto, Geraldo F, Calderoni, Sara, Calhoun, Vince D, Calvo, Rosa, Canales-Rodríguez, Erick J, Cannon, Dara M, Carr, Vaughan J, Cascella, Nicola, Cercignani, Mara, Patel, Yash, Chaim-Avancini, Tiffany M, Christakou, Anastasia, Coghill, David, Conzelmann, Annette, Crespo-Facorro, Benedicto, Cubillo, Ana I, Cullen, Kathryn R, Cupertino, Renata B, Daly, Eileen, Dannlowski, Udo, Parker, Nadine, Davey, Christopher G, Denys, Damiaan, Deruelle, Christine, Di Giorgio, Annabella, Dickie, Erin W, Dima, Danai, Dohm, Katharina, Ehrlich, Stefan, Ely, Benjamin A, Erwin-Grabner, Tracy, Shin, Jean, Ethofer, Thomas, Fair, Damien A, Fallgatter, Andreas, Faraone, Stephen V, Fatjó-Vilas, Mar, Fedor, Jennifer M, Fitzgerald, Kate D, Ford, Judith M, Frodl, Thomas, Fu, Cynthia H Y, Howard, Derek, Fullerton, Janice M, Gabel, Matt C, Glahn, David C, Roberts, Gloria, Gogberashvili, Tinatin, Goikolea, Jose M, Gotlib, Ian H, Goya-Maldonado, Roberto, Grabe, Hans, Green, Melissa J, Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S. I., Pozzi, E., Abe, Y., Abe, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S. H., Anagnostou, E., Mcintosh, A. A., Arango, C., Arnold, P. D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C. E., Baranov, A., Bargallo, N., Bau, C. H. D., Baumeister, S., Baune, B. T., Bellgrove, M. A., Benedetti, F., Bertolino, A., Boedhoe, P. S. W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B. P., Bruggemann, J. M., Bulow, R., Busatto, G. F., Calderoni, S., Calhoun, V. D., Calvo, R., Canales-Rodriguez, E. J., Cannon, D. M., Carr, V. J., Cascella, N., Cercignani, M., Chaim-Avancini, T. M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A. I., Cullen, K. R., Cupertino, R. B., Daly, E., Dannlowski, U., Davey, C. G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E. W., Dima, D., Dohm, K., Ehrlich, S., Ely, B. A., Erwin-Grabner, T., Ethofer, T., Fair, D. A., Fallgatter, A. J., Faraone, S. V., Fatjo-Vilas, M., Fedor, J. M., Fitzgerald, K. D., Ford, J. M., Frodl, T., Fu, C. H. Y., Fullerton, J. M., Gabel, M. C., Glahn, D. C., Roberts, G., Gogberashvili, T., Goikolea, J. M., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Green, M. J., Grevet, E. H., Groenewold, N. A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R. E., Gur, R. C., Haar, S., Haarman, B. C. M., Haavik, J., Hahn, T., Hajek, T., Harrison, B. J., Harrison, N. A., Hartman, C. A., Whalley, H. C., Heslenfeld, D. J., Hibar, D. P., Hilland, E., Hirano, Y., Ho, T. C., Hoekstra, P. J., Hoekstra, L., Hohmann, S., Hong, L. E., Hoschl, C., Hovik, M. F., Howells, F. M., Nenadic, I., Jalbrzikowski, M., James, A. C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J. A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Kramer, B., Krug, A., Kuntsi, J., Kwon, J. S., Landen, M., Landro, N. I., Lazaro, L., Lebedeva, I. S., Leehr, E. J., Lera-Miguel, S., Lesch, K. -P., Lochner, C., Louza, M. R., Luna, B., Lundervold, A. J., Macmaster, F. P., Maglanoc, L. A., Malpas, C. B., Portella, M. J., Marsh, R., Martyn, F. M., Mataix-Cols, D., Mathalon, D. H., Mccarthy, H., Mcdonald, C., Mcphilemy, G., Meinert, S., Menchon, J. M., Minuzzi, L., Mitchell, P. B., Moreno, C., Morgado, P., Muratori, F., Murphy, C. M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D. D., Nicolau, R., O'Gorman Tuura, R. L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R. A., Oranje, B., Garcia De La Foz, V. O., Overs, B. J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Pico-Perez, M., Picon, F. A., Piras, F., Plessen, K. J., Pomarol-Clotet, E., Preda, A., Puig, O., Quide, Y., Radua, J., Ramos-Quiroga, J. A., Rasser, P. E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P. G. P., Rubia, K. K., Hashimoto, R., Sacchet, M. D., Salvador, R., Santonja, J., Sarink, K., Sarro, S., Satterthwaite, T. D., Sawa, A., Schall, U., Schofield, P. R., Schrantee, A., Seitz, J., Serpa, M. H., Setien-Suero, E., Shaw, P., Shook, D., Silk, T. J., Sim, K., Simon, S., Simpson, H. B., Singh, A., Skoch, A., Skokauskas, N., Soares, J. C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S. M., Stern, E. R., Stewart, S. E., Takayanagi, Y., Temmingh, H. S., Tolin, D. F., Tomecek, D., Tordesillas-Gutierrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N. J. A., Van Der Werff, S. J. A., Van Haren, N. E. M., Van Wingen, G. A., Vance, A., Vazquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A. N., Volzke, H., Von Polier, G. G., Walton, E., Weickert, T. W., Weickert, C. S., Weideman, A. S., Wittfeld, K., Wolf, D. H., Wu, M. -J., Yang, T. T., Yang, K., Yoncheva, Y., Yun, J. -Y., Cheng, Y., Zanetti, M. V., Ziegler, G. C., Franke, B., Hoogman, M., Buitelaar, J. K., Van Rooij, D., Andreassen, O. A., Ching, C. R. K., Veltman, D. J., Schmaal, L., Stein, D. J., Van Den Heuvel, O. A., Turner, J. A., Van Erp, T. G. M., Pausova, Z., Thompson, P. M., Paus, T., Institut de Neurosciences de la Timone (INT), Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Pediatric surgery, Radiology and nuclear medicine, Anatomy and neurosciences, Psychiatry, Amsterdam Neuroscience - Brain Imaging, Amsterdam Neuroscience - Compulsivity, Impulsivity & Attention, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Amsterdam Neuroscience - Neurodegeneration, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Med Staf Spec Psychiatrie (9), Adult Psychiatry, ANS - Compulsivity, Impulsivity & Attention, General Paediatrics, ARD - Amsterdam Reproduction and Development, Radiology and Nuclear Medicine, APH - Personalized Medicine, ANS - Brain Imaging, ANS - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, University of Zurich, Clinical Cognitive Neuropsychiatry Research Program (CCNP), Clinical Neuropsychology, Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Child and Adolescent Psychiatry / Psychology, IBBA, and Cognitive Psychology
Subjects: Male, Obsessive-Compulsive Disorder, Bipolar Disorder, Autism Spectrum Disorder, Autism, [SDV]Life Sciences [q-bio], Gene Expression, cytology [Cerebral Cortex], Cohort Studies, Fetal Development, physiology [Gene Expression], 2738 Psychiatry and Mental Health, 0302 clinical medicine, diagnostic imaging [Cerebral Cortex], SCHIZOPHRENIA, BRAIN, Child, Obsessive-compulsive disorder (OCD), Original Investigation, Aged, 80 and over, Cerebral Cortex, 0303 health sciences, pathology [Depressive Disorder, Major], Principal Component Analysis, Adolescent psychiatry, 10058 Department of Child and Adolescent Psychiatry, Middle Aged, diagnostic imaging [Obsessive-Compulsive Disorder], REGIONS, Magnetic Resonance Imaging, 3. Good health, FALSE DISCOVERY RATE, Psychiatry and Mental health, Autism spectrum disorder, Schizophrenia, growth & development [Cerebral Cortex], Child, Preschool, Major depressive disorder, diagnostic imaging [Schizophrenia], Esquizofrènia, Female, Psiquiatria infantil, Psiquiatria de l'adolescència, diagnostic imaging [Autism Spectrum Disorder], Adult, medicine.medical_specialty, Adolescent, Human Development, 610 Medicine & health, diagnostic imaging [Bipolar Disorder], pathology [Autism Spectrum Disorder], diagnostic imaging [Depressive Disorder, Major], 03 medical and health sciences, Young Adult, All institutes and research themes of the Radboud University Medical Center, Neuroimaging, SDG 3 - Good Health and Well-being, CEREBRAL-CORTEX, Child psychiatry, medicine, Attention deficit hyperactivity disorder, Humans, Bipolar disorder, ddc:610, Psychiatry, pathology [Schizophrenia], 030304 developmental biology, Aged, Depressive Disorder, Major, Neurodevelopmental disorders Donders Center for Medical Neuroscience [Radboudumc 7], business.industry, DENDRITE, Computational Biology, Correction, pathology [Attention Deficit Disorder with Hyperactivity], physiology [Fetal Development], medicine.disease, PATHOLOGY, pathology [Bipolar Disorder], pathology [Obsessive-Compulsive Disorder], 10036 Medical Clinic, Attention Deficit Disorder with Hyperactivity, 10054 Clinic for Psychiatry, Psychotherapy, and Psychosomatics, Case-Control Studies, DENSITY, ORIGINS, HIPPOCAMPUS, diagnostic imaging [Attention Deficit Disorder with Hyperactivity], pathology [Cerebral Cortex], Autisme, business, Neuroscience, 030217 neurology & neurosurgery, physiology [Human Development]
Abstract: [Importance] Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood., [Objective] To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia., [Design, Setting, and Participants] Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244., [Main Outcomes and Measures] Interregional profiles of group difference in cortical thickness between cases and controls., [Results] A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (except for OCD); collectively, gene-expression profiles of the 3 cell types explain between 25% and 54% of variance in interregional profiles of group differences in cortical thickness. Principal component analysis revealed a shared profile of difference in cortical thickness across the 6 disorders (48% variance explained); interregional profile of this principal component 1 was associated with that of the pyramidal-cell gene expression (explaining 56% of interregional variation). Coexpression analyses of these genes revealed 2 clusters: (1) a prenatal cluster enriched with genes involved in neurodevelopmental (axon guidance) processes and (2) a postnatal cluster enriched with genes involved in synaptic activity and plasticity-related processes. These clusters were enriched with genes associated with all 6 psychiatric disorders., [Conclusions and Relevance] In this study, shared neurobiologic processes were associated with differences in cortical thickness across multiple psychiatric disorders. These processes implicate a common role of prenatal development and postnatal functioning of the cerebral cortex in these disorders.
Published: 2021
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45. Widespread white matter microstructural abnormalities in bipolar disorder: evidence from mega- and meta-analyses across 3033 individuals

Author: Jess E. Sussmann, Unn K. Haukvik, Michèle Wessa, Pedro G.P. Rosa, Philip B. Mitchell, Trine Vik Lagerberg, Henk Temmingh, Christoph Abé, Tomas Hajek, Edith Pomarol-Clotet, Sonya Foley, Chantal Henry, Neda Jahanshad, Martin Alda, Franz Hozer, Harald Kugel, Mircea Polosan, Jacques Stout, Erick J. Canales-Rodríguez, Pauline Favre, Peter R. Schofield, Josselin Houenou, Michael Deppe, Gloria Roberts, Heather C. Whalley, Tiffany M. Chaim-Avancini, Norma Verdolini, Clara Alloza, Ole A. Andreassen, Marcus V. Zanetti, Salvador Sarró, Mauricio H. Serpa, Melissa Pauling, Jonathan Repple, R. Salvador, Geraldo F. Busatto, Annerine Roos, Christopher R.K. Ching, Dominik Grotegerd, Marion Leboyer, Udo Dannlowski, Lisa T. Eyler, Xavier Caseras, Francesco Benedetti, Kang Sim, Silvia Alonso-Lana, Samuel Sarrazin, Julia Linke, Bernhard T. Baune, Jean-François Mangin, Andrew M. McIntosh, Mar Fatjó-Vilas, Edouard Duchesnay, Eduard Vieta, Dan J. Stein, Stephen M. Lawrie, Paul M. Thompson, Fleur M. Howells, Elisa M T Melloni, Favre, P., Pauling, M., Stout, J., Hozer, F., Sarrazin, S., Abe, C., Alda, M., Alloza, C., Alonso-Lana, S., Andreassen, O. A., Baune, B. T., Benedetti, F., Busatto, G. F., Canales-Rodriguez, E. J., Caseras, X., Chaim-Avancini, T. M., Ching, C. R. K., Dannlowski, U., Deppe, M., Eyler, L. T., Fatjo-Vilas, M., Foley, S. F., Grotegerd, D., Hajek, T., Haukvik, U. K., Howells, F. M., Jahanshad, N., Kugel, H., Lagerberg, T. V., Lawrie, S. M., Linke, J. O., Mcintosh, A., Melloni, E. M. T., Mitchell, P. B., Polosan, M., Pomarol-Clotet, E., Repple, J., Roberts, G., Roos, A., Rosa, P. G. P., Salvador, R., Sarro, S., Schofield, P. R., Serpa, M. H., Sim, K., Stein, D. J., Sussmann, J. E., Temmingh, H. S., Thompson, P. M., Verdolini, N., Vieta, E., Wessa, M., Whalley, H. C., Zanetti, M. V., Leboyer, M., Mangin, J. -F., Henry, C., Duchesnay, E., and Houenou, J.
Subjects: Pathology, medicine.medical_specialty, Corpus callosum, Article, White matter, 03 medical and health sciences, 0302 clinical medicine, Fractional anisotropy, Cingulum (brain), Medicine, Manic-depressive illness, Bipolar disorder, Pharmacology, Trastorn bipolar, business.industry, Diagnostic markers, Anisotropia, Translational research, medicine.disease, 030227 psychiatry, Psychiatry and Mental health, medicine.anatomical_structure, Meta-analysis, Anisotropy, business, 030217 neurology & neurosurgery, Diffusion MRI, Tractography
Abstract: Fronto-limbic white matter (WM) abnormalities are assumed to lie at the heart of the pathophysiology of bipolar disorder (BD);\ud however, diffusion tensor imaging (DTI) studies have reported heterogeneous results and it is not clear how the clinical\ud heterogeneity is related to the observed differences. This study aimed to identify WM abnormalities that differentiate patients with\ud BD from healthy controls (HC) in the largest DTI dataset of patients with BD to date, collected via the ENIGMA network. We gathered\ud individual tensor-derived regional metrics from 26 cohorts leading to a sample size of N = 3033 (1482 BD and 1551 HC). Mean\ud fractional anisotropy (FA) from 43 regions of interest (ROI) and average whole-brain FA were entered into univariate mega- and\ud meta-analyses to differentiate patients with BD from HC. Mega-analysis revealed significantly lower FA in patients with BD\ud compared with HC in 29 regions, with the highest effect sizes observed within the corpus callosum (R2 = 0.041, Pcorr < 0.001) and\ud cingulum (right: R2 = 0.041, left: R2 = 0.040, Pcorr < 0.001). Lithium medication, later onset and short disease duration were related to\ud higher FA along multiple ROIs. Results of the meta-analysis showed similar effects. We demonstrated widespread WM abnormalities\ud in BD and highlighted that altered WM connectivity within the corpus callosum and the cingulum are strongly associated with BD.\ud These brain abnormalities could represent a biomarker for use in the diagnosis of BD. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.
Published: 2019
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46. Associations of altered leukocyte DDR1 promoter methylation and childhood trauma with bipolar disorder and suicidal behavior in euthymic patients.

Author: Garcia-Ruiz B, Jiménez E, Aranda S, Verdolini N, Gutiérrez-Zotes A, Sáez C, Losantos E, Alonso-Lana S, Fatjó-Vilas M, Sarró S, Torres L, Panicalli F, Bonnin CDM, Pomarol-Clotet E, Vieta E, and Vilella E
Subjects: Humans, Male, Female, Adult, Middle Aged, Adverse Childhood Experiences, Risk Factors, Case-Control Studies, Suicidal Ideation, DNA Methylation genetics, Bipolar Disorder genetics, Bipolar Disorder metabolism, Promoter Regions, Genetic genetics, Discoidin Domain Receptor 1 genetics, Discoidin Domain Receptor 1 metabolism, Leukocytes metabolism
Abstract: Altered DNA methylation (DNAm) patterns of discoidin domain receptor 1 (DDR1) have been found in the blood and brain of patients with schizophrenia (SCZ) and the brain of patients with bipolar disorder (BD). Childhood trauma (CT) is associated with changes in DNAm that in turn are related to suicidal behavior (SB) in patients with several psychiatric disorders. Here, using MassARRAY® technology, we studied 128 patients diagnosed with BD in remission and 141 healthy controls (HCs) to compare leukocyte DDR1 promoter DNAm patterns between patients and HCs and between patients with and without SB. Additionally, we investigated whether CT was associated with DDR1 DNAm and mediated SB. We found hypermethylation at DDR1 cg19215110 and cg23953820 sites and hypomethylation at cg14279856 and cg03270204 sites in patients with BD compared to HCs. Logistic regression models showed that hypermethylation of DDR1 cg23953820 but not cg19215110 and CT were risk factors for BD, while cg14279856 and cg03270204 hypomethylation were protective factors. In patients, CT was a risk factor for SB, but DDR1 DNAm, although associated with CT, did not mediate the association of CT with SB. This is the first study demonstrating altered leukocyte DDR1 promoter DNAm in euthymic patients with BD. We conclude that altered DDR1 DNAm may be related to immune and inflammatory mechanisms and could be a potential blood biomarker for the diagnosis and stratification of psychiatric patients., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2024
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47. Verbal Learning and Memory Deficits across Neurological and Neuropsychiatric Disorders: Insights from an ENIGMA Mega Analysis.

Author: Kennedy E, Liebel SW, Lindsey HM, Vadlamani S, Lei PW, Adamson MM, Alda M, Alonso-Lana S, Anderson TJ, Arango C, Asarnow RF, Avram M, Ayesa-Arriola R, Babikian T, Banaj N, Bird LJ, Borgwardt S, Brodtmann A, Brosch K, Caeyenberghs K, Calhoun VD, Chiaravalloti ND, Cifu DX, Crespo-Facorro B, Dalrymple-Alford JC, Dams-O'Connor K, Dannlowski U, Darby D, Davenport N, DeLuca J, Diaz-Caneja CM, Disner SG, Dobryakova E, Ehrlich S, Esopenko C, Ferrarelli F, Frank LE, Franz CE, Fuentes-Claramonte P, Genova H, Giza CC, Goltermann J, Grotegerd D, Gruber M, Gutierrez-Zotes A, Ha M, Haavik J, Hinkin C, Hoskinson KR, Hubl D, Irimia A, Jansen A, Kaess M, Kang X, Kenney K, Keřková B, Khlif MS, Kim M, Kindler J, Kircher T, Knížková K, Kolskår KK, Krch D, Kremen WS, Kuhn T, Kumari V, Kwon J, Langella R, Laskowitz S, Lee J, Lengenfelder J, Liou-Johnson V, Lippa SM, Løvstad M, Lundervold AJ, Marotta C, Marquardt CA, Mattos P, Mayeli A, McDonald CR, Meinert S, Melzer TR, Merchán-Naranjo J, Michel C, Morey RA, Mwangi B, Myall DJ, Nenadić I, Newsome MR, Nunes A, O'Brien T, Oertel V, Ollinger J, Olsen A, Ortiz García de la Foz V, Ozmen M, Pardoe H, Parent M, Piras F, Piras F, Pomarol-Clotet E, Repple J, Richard G, Rodriguez J, Rodriguez M, Rootes-Murdy K, Rowland J, Ryan NP, Salvador R, Sanders AM, Schmidt A, Soares JC, Spalleta G, Španiel F, Sponheim SR, Stasenko A, Stein F, Straube B, Thames A, Thomas-Odenthal F, Thomopoulos SI, Tone EB, Torres I, Troyanskaya M, Turner JA, Ulrichsen KM, Umpierrez G, Vecchio D, Vilella E, Vivash L, Walker WC, Werden E, Westlye LT, Wild K, Wroblewski A, Wu MJ, Wylie GR, Yatham LN, Zunta-Soares GB, Thompson PM, Pugh MJ, Tate DF, Hillary FG, Wilde EA, and Dennis EL
Abstract: Deficits in memory performance have been linked to a wide range of neurological and neuropsychiatric conditions. While many studies have assessed the memory impacts of individual conditions, this study considers a broader perspective by evaluating how memory recall is differentially associated with nine common neuropsychiatric conditions using data drawn from 55 international studies, aggregating 15,883 unique participants aged 15-90. The effects of dementia, mild cognitive impairment, Parkinson's disease, traumatic brain injury, stroke, depression, attention-deficit/hyperactivity disorder (ADHD), schizophrenia, and bipolar disorder on immediate, short-, and long-delay verbal learning and memory (VLM) scores were estimated relative to matched healthy individuals. Random forest models identified age, years of education, and site as important VLM covariates. A Bayesian harmonization approach was used to isolate and remove site effects. Regression estimated the adjusted association of each clinical group with VLM scores. Memory deficits were strongly associated with dementia and schizophrenia ( p < 0.001), while neither depression nor ADHD showed consistent associations with VLM scores ( p > 0.05). Differences associated with clinical conditions were larger for longer delayed recall duration items. By comparing VLM across clinical conditions, this study provides a foundation for enhanced diagnostic precision and offers new insights into disease management of comorbid disorders.
Published: 2024
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48. Improved estimation of the risk of manic relapse by combining clinical and brain scan data.

Author: Palau P, Solanes A, Madre M, Saez-Francas N, Sarró S, Moro N, Verdolini N, Sanchez M, Alonso-Lana S, Amann BL, Romaguera A, Martin-Subero M, Fortea L, Fuentes-Claramonte P, García-León MA, Munuera J, Canales-Rodríguez EJ, Fernández-Corcuera P, Brambilla P, Vieta E, Pomarol-Clotet E, and Radua J
Subjects: Humans, Mania, Recurrence, Brain, Bipolar Disorder diagnostic imaging, Psychotic Disorders diagnosis
Abstract: Introduction: Estimating the risk of manic relapse could help the psychiatrist individually adjust the treatment to the risk. Some authors have attempted to estimate this risk from baseline clinical data. Still, no studies have assessed whether the estimation could improve by adding structural magnetic resonance imaging (MRI) data. We aimed to evaluate it., Material and Methods: We followed a cohort of 78 patients with a manic episode without mixed symptoms (bipolar type I or schizoaffective disorder) at 2-4-6-9-12-15-18 months and up to 10 years. Within a cross-validation scheme, we created and evaluated a Cox lasso model to estimate the risk of manic relapse using both clinical and MRI data., Results: The model successfully estimated the risk of manic relapse (Cox regression of the time to relapse as a function of the estimated risk: hazard ratio (HR)=2.35, p=0.027; area under the curve (AUC)=0.65, expected calibration error (ECE)<0.2). The most relevant variables included in the model were the diagnosis of schizoaffective disorder, poor impulse control, unusual thought content, and cerebellum volume decrease. The estimations were poorer when we used clinical or MRI data separately., Conclusion: Combining clinical and MRI data may improve the risk of manic relapse estimation after a manic episode. We provide a website that estimates the risk according to the model to facilitate replication by independent groups before translation to clinical settings., (Copyright © 2023 The Author(s). Published by Elsevier España S.L.U. All rights reserved.)
Published: 2023
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49. Widespread intra-axonal signal fraction abnormalities in bipolar disorder from multicompartment diffusion MRI: Sensitivity to diagnosis, association with clinical features and pharmacologic treatment.

Author: Canales-Rodríguez EJ, Verdolini N, Alonso-Lana S, Torres ML, Panicalli F, Argila-Plaza I, Rodriguez-Cano E, Montoro I, Garcia-Ruiz B, Jimenez E, Varo C, Lluch A, Del Mar Bonnin C, Maluf S, Pujol M, Guarner NJ, Sarró S, Vieta E, Vilella E, Salvador R, and Pomarol-Clotet E
Subjects: Humans, Diffusion Tensor Imaging methods, Diffusion Magnetic Resonance Imaging, Bipolar Disorder diagnostic imaging, Bipolar Disorder drug therapy, White Matter diagnostic imaging, Antipsychotic Agents pharmacology, Antipsychotic Agents therapeutic use
Abstract: Despite diffusion tensor imaging (DTI) evidence for widespread fractional anisotropy (FA) reductions in the brain white matter of patients with bipolar disorder, questions remain regarding the specificity and sensitivity of FA abnormalities as opposed to other diffusion metrics in the disorder. We conducted a whole-brain voxel-based multicompartment diffusion MRI study on 316 participants (i.e., 158 patients and 158 matched healthy controls) employing four diffusion metrics: the mean diffusivity (MD) and FA estimated from DTI, and the intra-axonal signal fraction (IASF) and microscopic axonal parallel diffusivity (Dpar) derived from the spherical mean technique. Our findings provide novel evidence about widespread abnormalities in other diffusion metrics in BD. An extensive overlap between the FA and IASF results suggests that the lower FA in patients may be caused by a reduced intra-axonal volume fraction or a higher macromolecular content in the intra-axonal water. We also found a diffuse alteration in MD involving white and grey matter tissue and more localised changes in Dpar. A Machine Learning analysis revealed that FA, followed by IASF, were the most helpful metric for the automatic diagnosis of BD patients, reaching an accuracy of 72%. Number of mood episodes, age of onset/duration of illness, psychotic symptoms, and current treatment with lithium, antipsychotics, antidepressants, and antiepileptics were all significantly associated with microstructure abnormalities. Lithium treatment was associated with less microstructure abnormality., (© 2023 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)
Published: 2023
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50. Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium.

Author: Kennedy E, Vadlamani S, Lindsey HM, Lei PW, Jo-Pugh M, Adamson M, Alda M, Alonso-Lana S, Ambrogi S, Anderson TJ, Arango C, Asarnow RF, Avram M, Ayesa-Arriola R, Babikian T, Banaj N, Bird LJ, Borgwardt S, Brodtmann A, Brosch K, Caeyenberghs K, Calhoun VD, Chiaravalloti ND, Cifu DX, Crespo-Facorro B, Dalrymple-Alford JC, Dams-O'Connor K, Dannlowski U, Darby D, Davenport N, DeLuca J, Diaz-Caneja CM, Disner SG, Dobryakova E, Ehrlich S, Esopenko C, Ferrarelli F, Frank LE, Franz C, Fuentes-Claramonte P, Genova H, Giza CC, Goltermann J, Grotegerd D, Gruber M, Gutierrez-Zotes A, Ha M, Haavik J, Hinkin C, Hoskinson KR, Hubl D, Irimia A, Jansen A, Kaess M, Kang X, Kenney K, Keřková B, Khlif MS, Kim M, Kindler J, Kircher T, Knížková K, Kolskår KK, Krch D, Kremen WS, Kuhn T, Kumari V, Kwon JS, Langella R, Laskowitz S, Lee J, Lengenfelder J, Liebel SW, Liou-Johnson V, Lippa SM, Løvstad M, Lundervold A, Marotta C, Marquardt CA, Mattos P, Mayeli A, McDonald CR, Meinert S, Melzer TR, Merchán-Naranjo J, Michel C, Morey RA, Mwangi B, Myall DJ, Nenadić I, Newsome MR, Nunes A, O'Brien T, Oertel V, Ollinger J, Olsen A, de la Foz VOG, Ozmen M, Pardoe H, Parent M, Piras F, Piras F, Pomarol-Clotet E, Repple J, Richard G, Rodriguez J, Rodriguez M, Rootes-Murdy K, Rowland J, Ryan NP, Salvador R, Sanders AM, Schmidt A, Soares JC, Spalleta G, Španiel F, Stasenko A, Stein F, Straube B, Thames A, Thomas-Odenthal F, Thomopoulos SI, Tone E, Torres I, Troyanskaya M, Turner JA, Ulrichsen KM, Umpierrez G, Vilella E, Vivash L, Walker WC, Werden E, Westlye LT, Wild K, Wroblewski A, Wu MJ, Wylie GR, Yatham LN, Zunta-Soares GB, Thompson PM, Tate DF, Hillary FG, Dennis EL, and Wilde EA
Abstract: Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences., Competing Interests: Competing Interest Statement: Dr. Arango has been a consultant to or has received honoraria or grants from Acadia, Angelini, Biogen, Boehringer, Gedeon Richter, Janssen Cilag, Lundbeck, Medscape, Menarini, Minerva, Otsuka, Pfizer, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. Dr. Brodtmann serves on the editorial boards of Neurology and International Journal of Stroke. Dr. Diaz-Caneja has received honoraria from Exeltis and Angelinii. Dr. Giza: consultant for NBA, NFL, NHLPA, Los Angeles Lakers; Advisory Board: Highmark Interactive, Novartis, MLS, NBA, USSF; Medicolegal 1–2 cases annually. Dr. Soares: ALKERMES (Research Grant), ALLERGAN (Research Grant), ASOFARMA (Consultant), ATAI (Stock), BOEHRINGER Ingelheim (Consultant), COMPASS (Research Grant), JOHNSON & JOHNSON (Consultant), LIVANOVA (Consultant), PFIZER (Consultant), PULVINAR NEURO LLC (Consultant), RELMADA (Consultant), SANOFI (Consultant), SUNOVIAN (Consultant). Dr. Thompson received partial research support from Biogen, Inc., for research unrelated to this manuscript. Dr. Yatham has been on speaker or advisory boards for, or has received research grants from, Alkermes, Abbvie, Canadian Institutes of Health Research, Sumitomo Dainippon Pharma, GlaxoSmithKline, Intracellular Therapies, Merck, Sanofi, Sequiris, Servier, and Sunovion, over the past 3 years, all outside this work. The collection of this cohort was partially supported by an investigator-initiated research grant from Biogen (US). Biogen had no role in the analysis or writing of this manuscript. Eisai (JP) and Life Molecular Imaging for research unrelated to this manuscript. Dr. Wylie has received research support from the NJ Commission for brain injury research, from the Dept of Veterans’ Affairs, from Biogen, from Bristol, Myers, Squibb, from Genetech, and has served on advisory boards for the CDMRP and the VA. All of these activities are unrelated to this research. The views expressed in this article are those of the author(s) and do not reflect the official policy of the Department of Army/Navy/Air Force, Department of Defense, or U.S. Government.
Published: 2023
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