Search

Your search keyword '"Radua, J"' showing total 651 results
Start Over Author "Radua, J"
651 results on '"Radua, J"'

3. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis

Author

Wise, T, Radua, J, Via, E, Cardoner, N, Abe, O, Adams, TM, Amico, F, Cheng, Y, Cole, JH, de Azevedo Marques Périco, C, Dickstein, DP, Farrow, TFD, Frodl, T, Wagner, G, Gotlib, IH, Gruber, O, Ham, BJ, Job, DE, Kempton, MJ, Kim, MJ, Koolschijn, PCMP, Malhi, GS, Mataix-Cols, D, McIntosh, AM, Nugent, AC, O'Brien, JT, Pezzoli, S, Phillips, ML, Sachdev, PS, Salvadore, G, Selvaraj, S, Stanfield, AC, Thomas, AJ, van Tol, MJ, van der Wee, NJA, Veltman, DJ, Young, AH, Fu, CH, Cleare, AJ, and Arnone, D

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Biomedical Imaging, Brain Disorders, Neurosciences, Mental Health, Serious Mental Illness, Major Depressive Disorder, Depression, Mental health, Adult, Bipolar Disorder, Brain, Case-Control Studies, Depressive Disorder, Major, Female, Gray Matter, Humans, Magnetic Resonance Imaging, Male, Neuroimaging, Prefrontal Cortex, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

Finding robust brain substrates of mood disorders is an important target for research. The degree to which major depression (MDD) and bipolar disorder (BD) are associated with common and/or distinct patterns of volumetric changes is nevertheless unclear. Furthermore, the extant literature is heterogeneous with respect to the nature of these changes. We report a meta-analysis of voxel-based morphometry (VBM) studies in MDD and BD. We identified studies published up to January 2015 that compared grey matter in MDD (50 data sets including 4101 individuals) and BD (36 data sets including 2407 individuals) using whole-brain VBM. We used statistical maps from the studies included where available and reported peak coordinates otherwise. Group comparisons and conjunction analyses identified regions in which the disorders showed common and distinct patterns of volumetric alteration. Both disorders were associated with lower grey-matter volume relative to healthy individuals in a number of areas. Conjunction analysis showed smaller volumes in both disorders in clusters in the dorsomedial and ventromedial prefrontal cortex, including the anterior cingulate cortex and bilateral insula. Group comparisons indicated that findings of smaller grey-matter volumes relative to controls in the right dorsolateral prefrontal cortex and left hippocampus, along with cerebellar, temporal and parietal regions were more substantial in major depression. These results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes. This combination of differences and similarities has the potential to inform the development of diagnostic biomarkers for these conditions.

Published
2017

5. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Author

Georgiadis, F, Larivière, S, Glahn, D, Hong, LE, Kochunov, P, Mowry, B, Loughland, C, Pantelis, C, Henskens, FA, Green, MJ ; https://orcid.org/0000-0002-9361-4874, Cairns, MJ, Michie, PT, Rasser, PE, Catts, S, Tooney, P, Scott, RJ, Schall, U, Carr, V ; https://orcid.org/0000-0002-8907-5804, Quidé, Y, Krug, A, Stein, F, Nenadić, I, Brosch, K, Kircher, T, Gur, R, Satterthwaite, TD, Karuk, A, Pomarol- Clotet, E, Radua, J, Fuentes-Claramonte, P, Salvador, R, Spalletta, G, Voineskos, A, Sim, K, Crespo-Facorro, B, Tordesillas Gutiérrez, D, Ehrlich, S, Crossley, N, Grotegerd, D, Repple, J, Lencer, R, Dannlowski, U, Calhoun, V, Rootes-Murdy, K, Demro, C, Ramsay, IS, Sponheim, SR, Schmidt, A, Borgwardt, S, Tomyshev, A, Lebedeva, I, Höschl, C, Spaniel, F, Preda, A, Nguyen, D, Uhlmann, A, Stein, DJ, Howells, F, Temmingh, HS, Diaz Zuluaga, AM, López Jaramillo, C, Iasevoli, F, Ji, E, Homan, S, Omlor, W, Homan, P, Kaiser, S, Seifritz, E, Misic, B, Valk, SL, Thompson, P, van Erp, TGM, Turner, JA, Bernhardt, B, Kirschner, M, Quide, Yann ; https://orcid.org/0000-0002-8569-7139, Georgiadis, F, Larivière, S, Glahn, D, Hong, LE, Kochunov, P, Mowry, B, Loughland, C, Pantelis, C, Henskens, FA, Green, MJ ; https://orcid.org/0000-0002-9361-4874, Cairns, MJ, Michie, PT, Rasser, PE, Catts, S, Tooney, P, Scott, RJ, Schall, U, Carr, V ; https://orcid.org/0000-0002-8907-5804, Quidé, Y, Krug, A, Stein, F, Nenadić, I, Brosch, K, Kircher, T, Gur, R, Satterthwaite, TD, Karuk, A, Pomarol- Clotet, E, Radua, J, Fuentes-Claramonte, P, Salvador, R, Spalletta, G, Voineskos, A, Sim, K, Crespo-Facorro, B, Tordesillas Gutiérrez, D, Ehrlich, S, Crossley, N, Grotegerd, D, Repple, J, Lencer, R, Dannlowski, U, Calhoun, V, Rootes-Murdy, K, Demro, C, Ramsay, IS, Sponheim, SR, Schmidt, A, Borgwardt, S, Tomyshev, A, Lebedeva, I, Höschl, C, Spaniel, F, Preda, A, Nguyen, D, Uhlmann, A, Stein, DJ, Howells, F, Temmingh, HS, Diaz Zuluaga, AM, López Jaramillo, C, Iasevoli, F, Ji, E, Homan, S, Omlor, W, Homan, P, Kaiser, S, Seifritz, E, Misic, B, Valk, SL, Thompson, P, van Erp, TGM, Turner, JA, Bernhardt, B, Kirschner, M, and Quide, Yann ; https://orcid.org/0000-0002-8569-7139

Abstract

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia’s alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network ar

Published
2024

6. Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity.

Author

McWhinney, SR, Hlinka, J, Bakstein, E, Dietze, LMF, Corkum, ELV, Abé, C, Alda, M, Alexander, N, Benedetti, F, Berk, M, Bøen, E, Bonnekoh, LM, Boye, B, Brosch, K, Canales-Rodríguez, EJ, Cannon, DM, Dannlowski, U, Demro, C, Diaz-Zuluaga, A, Elvsåshagen, T, Eyler, LT, Fortea, L, Fullerton, JM, Goltermann, J, Gotlib, IH, Grotegerd, D, Haarman, B, Hahn, T, Howells, FM, Jamalabadi, H, Jansen, A, Kircher, T, Klahn, AL, Kuplicki, R, Lahud, E, Landén, M, Leehr, EJ, Lopez-Jaramillo, C, Mackey, S, Malt, U, Martyn, F, Mazza, E, McDonald, C, McPhilemy, G, Meier, S, Meinert, S, Melloni, E, Mitchell, PB, Nabulsi, L, Nenadić, I, Nitsch, R, Opel, N, Ophoff, RA, Ortuño, M, Overs, BJ, Pineda-Zapata, J, Pomarol-Clotet, E, Radua, J, Repple, J, Roberts, G, Rodriguez-Cano, E, Sacchet, MD, Salvador, R, Savitz, J, Scheffler, F, Schofield, PR, Schürmeyer, N, Shen, C, Sim, K, Sponheim, SR, Stein, DJ, Stein, F, Straube, B, Suo, C, Temmingh, H, Teutenberg, L, Thomas-Odenthal, F, Thomopoulos, SI, Urosevic, S, Usemann, P, van Haren, NEM, Vargas, C, Vieta, E, Vilajosana, E, Vreeker, A, Winter, NR, Yatham, LN, Thompson, PM, Andreassen, OA, Ching, CRK, Hajek, T, McWhinney, SR, Hlinka, J, Bakstein, E, Dietze, LMF, Corkum, ELV, Abé, C, Alda, M, Alexander, N, Benedetti, F, Berk, M, Bøen, E, Bonnekoh, LM, Boye, B, Brosch, K, Canales-Rodríguez, EJ, Cannon, DM, Dannlowski, U, Demro, C, Diaz-Zuluaga, A, Elvsåshagen, T, Eyler, LT, Fortea, L, Fullerton, JM, Goltermann, J, Gotlib, IH, Grotegerd, D, Haarman, B, Hahn, T, Howells, FM, Jamalabadi, H, Jansen, A, Kircher, T, Klahn, AL, Kuplicki, R, Lahud, E, Landén, M, Leehr, EJ, Lopez-Jaramillo, C, Mackey, S, Malt, U, Martyn, F, Mazza, E, McDonald, C, McPhilemy, G, Meier, S, Meinert, S, Melloni, E, Mitchell, PB, Nabulsi, L, Nenadić, I, Nitsch, R, Opel, N, Ophoff, RA, Ortuño, M, Overs, BJ, Pineda-Zapata, J, Pomarol-Clotet, E, Radua, J, Repple, J, Roberts, G, Rodriguez-Cano, E, Sacchet, MD, Salvador, R, Savitz, J, Scheffler, F, Schofield, PR, Schürmeyer, N, Shen, C, Sim, K, Sponheim, SR, Stein, DJ, Stein, F, Straube, B, Suo, C, Temmingh, H, Teutenberg, L, Thomas-Odenthal, F, Thomopoulos, SI, Urosevic, S, Usemann, P, van Haren, NEM, Vargas, C, Vieta, E, Vilajosana, E, Vreeker, A, Winter, NR, Yatham, LN, Thompson, PM, Andreassen, OA, Ching, CRK, and Hajek, T

Abstract

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associati

Published
2024

9. Effectiveness of treatment with nebulized colistin in patients with COPD

Author

Bruguera-Avila N, Marín A, Garcia-Olive I, Radua J, Prat C, Gil M, and Ruiz-Manzano J

Subjects
Bronchiectasis, Colistin, COPD, nebulised antibiotics, Diseases of the respiratory system, RC705-779
Abstract

Nuria Bruguera-Avila,1–3 Alicia Marin,3–5 Ignasi Garcia-Olive,3–5 Joaquim Radua,6–8 Cristina Prat,4,9,10 Montserrat Gil,3 Juan Ruiz-Manzano2–5 1Department of Medicine, Hospital Sant Jaume de Calella, Calella, Barcelona, Spain; 2Department of Medicine, Universitat Autònoma de Barcelona, Bellatera, Spain; 3Department of Pulmonary Medicine, Hospital Universitari Germans Trias i Pujol, Carretera del Canyet sn, Badalona, Barcelona, Spain; 4Ciber de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain; 5Fundació Institut d’Investigació en Ciències de la Salut Germans Trias i Pujol, Carretera del Canyet sn, Badalona, Barcelona, Spain; 6Department of Statistics, FIDMAG Germanes Hospitalaries Research Unit, Sant Boi de Llobregat, Barcelona, Spain; 7CiberSam – Ciber de Salud Mental, Madrid, Spain; 8Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden; 9Department of Microbiology, Hospital Universitari Germans Trias i Pujol, Carretera del Canyet sn, Badalona, Barcelona, Spain; 10Department of Genetics and Microbiology of Universitat Autònoma de Barcelona, Bellatera, Spain Objectives: To analyze whether the introduction of nebulized colistin in patients with chronic obstructive pulmonary disease (COPD) and infection with Pseudomonas aeruginosa (PA) is associated with a decrease of the number and duration of severe exacerbations.Materials and methods: Thirty six patients with COPD and infection with PA treated with nebulized colistin attending a day hospital during a 5-year (January 2010–December 2014) period were prospectively included. Repeated-measures t-tests were used to assess whether the introduction of colistin was associated with changes in the number of exacerbations or the length of the hospitalizations, comparing for each patient the year prior to the introduction of colistin with the year after.Results: After the introduction of colistin, the number of admissions decreased from 2.0 to 0.9 per individual year (P=0.0007), and hospitalizations were shorter (23.3 vs 10.9 days, P=0.00005). These results persisted when patients with and without bronchiectasis or with and without persistence of Pseudomonas were separately analyzed. No pre–post differences were detected in the number of exacerbations not requiring admission.Conclusion: Nebulized colistin seems associated with a strong decrease in the number and duration of hospitalizations due to exacerbation in patients with COPD and infection with PA. Clinical trials with a larger number of patients are needed in order to confirm these results. Keywords: bronchiectasis, colistin, COPD, nebulized antibiotics

Published
2017

10. Corrigendum to “Resilience and mental health during the COVID-19 pandemic” [J. Affect. Disord. 2021 Mar 15;283:156–164]

Author

Verdolini, N., primary, Amoretti, S., additional, Montejo, L., additional, García-Rizo, C., additional, Hogg, B., additional, Mezquida, G., additional, Rabelo-da-Ponte, F.D., additional, Vallespir, C., additional, Radua, J., additional, Martinez-Aran, A., additional, Pacchiarotti, I., additional, Rosa, A.R., additional, Bernardo, M., additional, Vieta, E., additional, Torrent, C., additional, and Solé, B., additional

Published
2023
Full Text
View/download PDF

15. Correlation between emotion dysregulation and mood symptoms of bipolar disorder: A systematic review and meta-analysis.

Author

Oliva, V., Prisco, M. De, Fico, G., Possidente, C., Fortea, L., Montejo, L., Anmella, G., Hidalgo-Mazzei, D., Grande, I., Murru, A., Fornaro, M., Bartolomeis, A. de, Dodd, A., Fanelli, G., Fabbri, C., Serretti, A., Vieta, E., Radua, J., Oliva, V., Prisco, M. De, Fico, G., Possidente, C., Fortea, L., Montejo, L., Anmella, G., Hidalgo-Mazzei, D., Grande, I., Murru, A., Fornaro, M., Bartolomeis, A. de, Dodd, A., Fanelli, G., Fabbri, C., Serretti, A., Vieta, E., and Radua, J.

Abstract

Contains fulltext : 299975.pdf (Publisher’s version ) (Open Access), BACKGROUND: Emotion dysregulation (ED) is a transdiagnostic construct characterized by difficulties regulating intense emotions. People with bipolar disorder (BD) are more likely to show ED and use maladaptive emotion regulation strategies than adaptive ones. However, little is known about whether ED in BD is a trait or it is rather an epiphenomenon of mood symptoms. METHODS: We conducted a systematic review and meta-analysis of the evidence across major literature databases reporting correlations between measures of emotion regulation (overall ED and different emotion regulation strategies) and measures of depressive and (hypo)manic symptoms in BD from inception until April 12th, 2022. RESULTS: Fourteen studies involving 1371 individuals with BD were included in the qualitative synthesis, of which 11 reported quantitative information and were included in the meta-analysis. ED and maladaptive strategies were significantly higher during periods with more severe mood symptoms, especially depressive ones, while adaptive strategies were lower. CONCLUSION: ED significantly correlates with BD symptomatology, and it mainly occurs during mood alterations. ED may be a target for specific psychotherapeutic and pharmacological treatments, according to precision psychiatry. However, further studies are needed, including patients with mood episodes and longitudinal design, to provide more robust evidence and explore the causal direction of the associations., 01 december 2023

Published
2023

16. What emotional regulation strategies are most related to the affective symptoms of bipolar disorder? A systematic review and network meta-analysis

Author

Oliva, V., primary, De Prisco, M., additional, Fico, G., additional, Possidente, C., additional, Fortea, L., additional, Montejo, L., additional, Anmella, G., additional, Hidalgo-Mazzei, D., additional, Grande, I., additional, Murru, A., additional, Fornaro, M., additional, De Bartolomeis, A., additional, Fanelli, G., additional, Fabbri, C., additional, Serretti, A., additional, Vieta, E., additional, and Radua, J., additional

Published
2023
Full Text
View/download PDF

25. Global case fatality rate of coronavirus disease 2019 (COVID‐19) by continents and national income: a meta‐analysis

Author

Ghayda RA, Lee KH, Han YJ, Ryu S, Hong SH, Yoon S, Jeong GH, Yang JW, Lee HJ, Lee J, Lee JY, Effenberger M, Eisenhut M, Kronbichler A, Solmi M, Li H, Jacob L., Koyanagi A, Radua J, Park MB, Aghayeva S, Ahmed MLCB, Serouri AA, Al-Shamsi HO, Amir-Behghadami M, Baatarkhuu O, Bashour H, Bondarenko A, Camacho-Ortiz A, Castro F, Cox H, Davtyan H, Douglas K, Dragioti E, Ebrahim S, Ferioli M, Harapan H, Mallah SI, Ikram A, Inoue S, Jankovic S, Jayarajah U, Jesenak M, Kakodkar P, Kebede Y, Kifle M, Koh D, Males VK, Kotfis K, Lakoh S, Ling L, Llibre-Guerra J, Machida M, Makurumidze R, Mamun M, Masic I, Van Minh H, Moiseev S, Nadasdy T, Nahshon C, Ñamendys-Silva SA, Yongsi BN, Nielsen HB, Nodjikouambaye ZA, Ohnmar O, Oksanen A, Owopetu O, Parperis K, Perez GE, Pongpirul K, Rademaker M, Rosa S, Sah R, Sallam D, Schober P, Singhal T, Tafaj S, Torres I, Smith Torres-Roman J, Tsartsalis D, Tsolmon J, Tuychiev L, Vukcevic B, Wanghi G, Wollina U, Xu RH, Yang L, Zaidi Z, Smith L, and Shin JI

Subjects
continents, COVID-19, proportion meta-analysis, case fatality rate (CFR)
Abstract

The aim of this study is to provide a more accurate representation of COVID-19's CFR by performing meta-analyses by continents and income, and by comparing the result with pooled estimates. We used multiple worldwide data sources on COVID-19 for every country reporting COVID-19 cases. Based on the data, we performed random and fixed meta-analyses for CFR of COVID-19 by continents and income according to each individual calendar date. CFR were estimated based on the different geographical regions and level of income using three models: pooled estimates, fixed- and random-model. In Asia, all three types of CFR initially remained approximately between 2.0% and 3.0%. In the case of pooled estimates and the fixed model results, CFR increased to 4.0%, by then gradually decreasing, while in the case of random-model, CFR remained under 2.0%. Similarly, in Europe, initially the two types of CFR peaked at 9.0% and 10.0%, respectively. The random-model results showed an increase near 5.0%. In high income countries, pooled estimates and fixed-model showed gradually increasing trends with a final pooled estimates and random-model reached about 8.0% and 4.0%, respectively. In middle-income, the pooled estimates and fixed-model have gradually increased reaching up to 4.5%. in low-income countries, CFRs remained similar between 1.5% and 3.0%. Our study emphasizes that COVID-19 CFR is not a fixed or static value. Rather, it is a dynamic estimate that changes with time, population, socioeconomic factors and the mitigatory efforts of individuals countries. This article is protected by copyright. All rights reserved.

Published
2022

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

Author

Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM ; https://orcid.org/0000-0003-4014-4490, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, Landén, M, Abé, C, Ching, CRK, Liberg, B, Lebedev, AV, Agartz, I, Akudjedu, TN, Alda, M, Alnæs, D, Alonso-Lana, S, Benedetti, F, Berk, M, Bøen, E, Bonnin, CDM, Breuer, F, Brosch, K, Brouwer, RM, Canales-Rodríguez, EJ, Cannon, DM, Chye, Y, Dahl, A, Dandash, O, Dannlowski, U, Dohm, K, Elvsåshagen, T, Fisch, L, Fullerton, JM ; https://orcid.org/0000-0003-4014-4490, Goikolea, JM, Grotegerd, D, Haatveit, B, Hahn, T, Hajek, T, Heindel, W, Ingvar, M, Sim, K, Kircher, TTJ, Lenroot, RK, Malt, UF, McDonald, C, McWhinney, SR, Melle, I, Meller, T, Melloni, EMT, Mitchell, PB ; https://orcid.org/0000-0002-7954-5235, Nabulsi, L, Nenadić, I, Opel, N, Overs, BJ, Panicalli, F, Pfarr, JK, Poletti, S, Pomarol-Clotet, E, Radua, J, Repple, J, Ringwald, KG, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Rodriguez-Cano, E, Salvador, R, Sarink, K, Sarró, S, Schmitt, S, Stein, F, Suo, C, Thomopoulos, SI, Tronchin, G, Vieta, E, Westlye, LT, White, AG, Yatham, LN, Zak, N, Thompson, PM, Andreassen, OA, and Landén, M

Abstract

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

Published
2022

30. 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 ; https://orcid.org/0000-0003-4014-4490, Glahn, DC, Goikolea, JM, Green, MJ ; https://orcid.org/0000-0002-9361-4874, 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 ; https://orcid.org/0000-0002-7954-5235, Nenadic, I, Nery, F, Nugent, AC, Oertel, V, Ophoff, RA, Ota, M, Overs, BJ ; https://orcid.org/0000-0002-7138-5556, Pham, DL, Phillips, ML, Pineda-Zapata, JA, Poletti, S, Polosan, M, Pomarol-Clotet, E, Pouchon, A, Quidé, Y, Rive, MM, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Ruhe, HG, Salvador, R, Sarró, S, Satterthwaite, TD, Schene, AH, Sim, K, Quide, Yann ; https://orcid.org/0000-0002-8569-7139, 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 ; https://orcid.org/0000-0003-4014-4490, Glahn, DC, Goikolea, JM, Green, MJ ; https://orcid.org/0000-0002-9361-4874, 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 ; https://orcid.org/0000-0002-7954-5235, Nenadic, I, Nery, F, Nugent, AC, Oertel, V, Ophoff, RA, Ota, M, Overs, BJ ; https://orcid.org/0000-0002-7138-5556, Pham, DL, Phillips, ML, Pineda-Zapata, JA, Poletti, S, Polosan, M, Pomarol-Clotet, E, Pouchon, A, Quidé, Y, Rive, MM, Roberts, G ; https://orcid.org/0000-0002-1966-5120, Ruhe, HG, Salvador, R, Sarró, S, Satterthwaite, TD, Schene, AH, Sim, K, and Quide, Yann ; https://orcid.org/0000-0002-8569-7139

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

31. Physical and mental health impact of COVID-19 on children, adolescents, and their families: The Collaborative Outcomes study on Health and Functioning during Infection Times - Children and Adolescents (COH-FIT-C&A)

Author

Solmi, M, Estradé, A, Thompson, T, Agorastos, A, Radua, J, Cortese, S, Dragioti, E, Leisch, F, Vancampfort, D, Thygesen, LC, Aschauer, H, Schloegelhofer, M, Akimova, E, Schneeberger, A, Huber, CG, Hasler, G, Conus, P, Cuénod, KQD, von Känel, R, Arrondo, G, Fusar-Poli, P, Gorwood, P, Llorca, PM, Krebs, MO, Scanferla, E, Kishimoto, T, Rabbani, G, Skonieczna-Żydecka, K, Brambilla, P, Favaro, A, Takamiya, A, Zoccante, L, Colizzi, M, Bourgin, J, Kamiński, K, Moghadasin, M, Seedat, S, Matthews, E, Wells, J, Vassilopoulou, E, Gadelha, A, Su, KP, Kwon, JS, Kim, M, Lee, TY, Papsuev, O, Manková, D, Boscutti, A, Gerunda, C, Saccon, D, Righi, E, Monaco, F, Croatto, G, Cereda, G, Demurtas, J, Brondino, N, Veronese, N, Enrico, P, Politi, P, Ciappolino, V, Pfennig, A, Bechdolf, A, Meyer-Lindenberg, A, Kahl, KG, Domschke, K, Bauer, M, Koutsouleris, N, Winter, S, Borgwardt, S, Bitter, I, Balazs, J, Czobor, P, Unoka, Z, Mavridis, D, Tsamakis, K, Bozikas, VP, Tunvirachaisakul, C, Maes, M, Rungnirundorn, T, Supasitthumrong, T, Haque, A, Brunoni, AR, Costardi, CG, Schuch, FB, Polanczyk, G, Luiz, JM, Fonseca, L, Aparicio, LV, Valvassori, SS, Nordentoft, M, Vendsborg, P, Hoffmann, SH, Sehli, J, Sartorius, N, Heuss, S, Guinart, D, Hamilton, J, Kane, J, Rubio, J, Sand, M, Marx, Wolf, Solmi, M, Estradé, A, Thompson, T, Agorastos, A, Radua, J, Cortese, S, Dragioti, E, Leisch, F, Vancampfort, D, Thygesen, LC, Aschauer, H, Schloegelhofer, M, Akimova, E, Schneeberger, A, Huber, CG, Hasler, G, Conus, P, Cuénod, KQD, von Känel, R, Arrondo, G, Fusar-Poli, P, Gorwood, P, Llorca, PM, Krebs, MO, Scanferla, E, Kishimoto, T, Rabbani, G, Skonieczna-Żydecka, K, Brambilla, P, Favaro, A, Takamiya, A, Zoccante, L, Colizzi, M, Bourgin, J, Kamiński, K, Moghadasin, M, Seedat, S, Matthews, E, Wells, J, Vassilopoulou, E, Gadelha, A, Su, KP, Kwon, JS, Kim, M, Lee, TY, Papsuev, O, Manková, D, Boscutti, A, Gerunda, C, Saccon, D, Righi, E, Monaco, F, Croatto, G, Cereda, G, Demurtas, J, Brondino, N, Veronese, N, Enrico, P, Politi, P, Ciappolino, V, Pfennig, A, Bechdolf, A, Meyer-Lindenberg, A, Kahl, KG, Domschke, K, Bauer, M, Koutsouleris, N, Winter, S, Borgwardt, S, Bitter, I, Balazs, J, Czobor, P, Unoka, Z, Mavridis, D, Tsamakis, K, Bozikas, VP, Tunvirachaisakul, C, Maes, M, Rungnirundorn, T, Supasitthumrong, T, Haque, A, Brunoni, AR, Costardi, CG, Schuch, FB, Polanczyk, G, Luiz, JM, Fonseca, L, Aparicio, LV, Valvassori, SS, Nordentoft, M, Vendsborg, P, Hoffmann, SH, Sehli, J, Sartorius, N, Heuss, S, Guinart, D, Hamilton, J, Kane, J, Rubio, J, Sand, M, and Marx, Wolf

Published
2022

32. The collaborative outcomes study on health and functioning during infection times in adults (COH-FIT-Adults): Design and methods of an international online survey targeting physical and mental health effects of the COVID-19 pandemic

Author

Solmi, M, Estradé, A, Thompson, T, Agorastos, A, Radua, J, Cortese, S, Dragioti, E, Leisch, F, Vancampfort, D, Thygesen, LC, Aschauer, H, Schloegelhofer, M, Akimova, E, Schneeberger, A, Huber, CG, Hasler, G, Conus, P, Cuénod, KQD, von Känel, R, Arrondo, G, Fusar-Poli, P, Gorwood, P, Llorca, PM, Krebs, MO, Scanferla, E, Kishimoto, T, Rabbani, G, Skonieczna-Żydecka, K, Brambilla, P, Favaro, A, Takamiya, A, Zoccante, L, Colizzi, M, Bourgin, J, Kamiński, K, Moghadasin, M, Seedat, S, Matthews, E, Wells, J, Vassilopoulou, E, Gadelha, A, Su, KP, Kwon, JS, Kim, M, Lee, TY, Papsuev, O, Manková, D, Boscutti, A, Gerunda, C, Saccon, D, Righi, E, Monaco, F, Croatto, G, Cereda, G, Demurtas, J, Brondino, N, Veronese, N, Enrico, P, Politi, P, Ciappolino, V, Pfennig, A, Bechdolf, A, Meyer-Lindenberg, A, Kahl, KG, Domschke, K, Bauer, M, Koutsouleris, N, Winter, S, Borgwardt, S, Bitter, I, Balazs, J, Czobor, P, Unoka, Z, Mavridis, D, Tsamakis, K, Bozikas, VP, Tunvirachaisakul, C, Maes, M, Rungnirundorn, T, Supasitthumrong, T, Haque, A, Brunoni, AR, Costardi, CG, Schuch, FB, Polanczyk, G, Luiz, JM, Fonseca, L, Aparicio, LV, Valvassori, SS, Nordentoft, M, Vendsborg, P, Hoffmann, SH, Sehli, J, Sartorius, N, Heuss, S, Guinart, D, Hamilton, J, Kane, J, Rubio, J, Sand, M, Berk, Michael, Solmi, M, Estradé, A, Thompson, T, Agorastos, A, Radua, J, Cortese, S, Dragioti, E, Leisch, F, Vancampfort, D, Thygesen, LC, Aschauer, H, Schloegelhofer, M, Akimova, E, Schneeberger, A, Huber, CG, Hasler, G, Conus, P, Cuénod, KQD, von Känel, R, Arrondo, G, Fusar-Poli, P, Gorwood, P, Llorca, PM, Krebs, MO, Scanferla, E, Kishimoto, T, Rabbani, G, Skonieczna-Żydecka, K, Brambilla, P, Favaro, A, Takamiya, A, Zoccante, L, Colizzi, M, Bourgin, J, Kamiński, K, Moghadasin, M, Seedat, S, Matthews, E, Wells, J, Vassilopoulou, E, Gadelha, A, Su, KP, Kwon, JS, Kim, M, Lee, TY, Papsuev, O, Manková, D, Boscutti, A, Gerunda, C, Saccon, D, Righi, E, Monaco, F, Croatto, G, Cereda, G, Demurtas, J, Brondino, N, Veronese, N, Enrico, P, Politi, P, Ciappolino, V, Pfennig, A, Bechdolf, A, Meyer-Lindenberg, A, Kahl, KG, Domschke, K, Bauer, M, Koutsouleris, N, Winter, S, Borgwardt, S, Bitter, I, Balazs, J, Czobor, P, Unoka, Z, Mavridis, D, Tsamakis, K, Bozikas, VP, Tunvirachaisakul, C, Maes, M, Rungnirundorn, T, Supasitthumrong, T, Haque, A, Brunoni, AR, Costardi, CG, Schuch, FB, Polanczyk, G, Luiz, JM, Fonseca, L, Aparicio, LV, Valvassori, SS, Nordentoft, M, Vendsborg, P, Hoffmann, SH, Sehli, J, Sartorius, N, Heuss, S, Guinart, D, Hamilton, J, Kane, J, Rubio, J, Sand, M, and Berk, Michael

Published
2022

33. 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

34. 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

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

Author

Wierenga, LM, Doucet, GE, Dima, D, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andreassen, OA, Anticevic, A, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, den Braber, A, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Calhoun, VD, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Chaim-Avancini, TM, Ching, CRK, Clark, VP, Conrod, PJ, Conzelmann, A, Crivello, F, Davey, CG, Dickie, EW, Ehrlich, S, Van't Ent, D, Fisher, SE, Fouche, J-P, Franke, B, Fuentes-Claramonte, P, de Geus, EJC, Di Giorgio, A, Glahn, DC, Gotlib, IH, Grabe, HJ, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Gurholt, TP, de Haan, L, Haatveit, B, Harrison, BJ, Hartman, CA, Hatton, SN, Heslenfeld, DJ, van den Heuvel, OA, Hickie, IB, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, AC, Jiang, J, Jonsson, EG, Joska, JA, Kalnin, AJ, Klein, M, Koenders, L, Kolskar, KK, Kramer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, IS, Lee, PH, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, BC, McDonald, C, McIntosh, AM, McMahon, KL, McPhilemy, G, van der Meer, D, Menchon, JM, Naaijen, J, Nyberg, L, Oosterlaan, J, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Radua, J, Reif, A, Richard, G, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Sim, K, Simmons, A, Smoller, JW, Sommer, IE, Soriano-Mas, C, Stein, DJ, Strike, LT, Szeszko, PR, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Trollor, JN, Uhlmann, A, Veer, IM, Veltman, DJ, Voineskos, A, Volzke, H, Walter, H, Wang, L, Wang, Y, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, HC, Williams, SCR, Wittfeld, K, Wolf, DH, Wright, MJ, Yoncheva, YN, Zanetti, M, Ziegler, GC, de Zubicaray, G, Thompson, PM, Crone, EA, Frangou, S, Tamnes, CK, Wierenga, LM, Doucet, GE, Dima, D, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andreassen, OA, Anticevic, A, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, den Braber, A, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Calhoun, VD, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Chaim-Avancini, TM, Ching, CRK, Clark, VP, Conrod, PJ, Conzelmann, A, Crivello, F, Davey, CG, Dickie, EW, Ehrlich, S, Van't Ent, D, Fisher, SE, Fouche, J-P, Franke, B, Fuentes-Claramonte, P, de Geus, EJC, Di Giorgio, A, Glahn, DC, Gotlib, IH, Grabe, HJ, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Gurholt, TP, de Haan, L, Haatveit, B, Harrison, BJ, Hartman, CA, Hatton, SN, Heslenfeld, DJ, van den Heuvel, OA, Hickie, IB, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, AC, Jiang, J, Jonsson, EG, Joska, JA, Kalnin, AJ, Klein, M, Koenders, L, Kolskar, KK, Kramer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, IS, Lee, PH, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, BC, McDonald, C, McIntosh, AM, McMahon, KL, McPhilemy, G, van der Meer, D, Menchon, JM, Naaijen, J, Nyberg, L, Oosterlaan, J, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Radua, J, Reif, A, Richard, G, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Sim, K, Simmons, A, Smoller, JW, Sommer, IE, Soriano-Mas, C, Stein, DJ, Strike, LT, Szeszko, PR, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Trollor, JN, Uhlmann, A, Veer, IM, Veltman, DJ, Voineskos, A, Volzke, H, Walter, H, Wang, L, Wang, Y, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, HC, Williams, SCR, Wittfeld, K, Wolf, DH, Wright, MJ, Yoncheva, YN, Zanetti, M, Ziegler, GC, de Zubicaray, G, Thompson, PM, Crone, EA, Frangou, S, and Tamnes, CK

Abstract

For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Published
2022

36. 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

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

Author

Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Frangou, S, Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Frangou, S

Abstract

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.

Published
2022

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

Author

Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Dima, D, Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Dima, D

Abstract

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.

Published
2022

39. 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

40. 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

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

Author

Baldwin, H, Radua, J, Antoniades, M, Haas, SS, Frangou, S, Agartz, I, Allen, P, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Bartholomeusz, CF, Chee, MWL, Colibazzi, T, Cooper, RE, Corcoran, CM, Cropley, VL, Ebdrup, BH, Fortea, A, Glenthoj, LB, Hamilton, HK, Haut, KM, Hayes, RA, He, Y, Heekeren, K, Kaess, M, Kasai, K, Katagiri, N, Kim, M, Kindler, J, Klaunig, MJ, Koike, S, Koppel, A, Kristensen, TD, Bin Kwak, Y, Kwon, JS, Lawrie, SM, Lebedeva, I, Lee, J, Lin, A, Loewy, RL, Mathalon, DH, Michel, C, Mizrahi, R, Moller, P, Nelson, B, Nemoto, T, Nordholm, D, Omelchenko, MA, Pantelis, C, Raghava, JM, Rossberg, J, Roessler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Smigielski, L, Sugranyes, G, Suzuki, M, Takahashi, T, Tamnes, CK, Tang, J, Theodoridou, A, Thomopoulos, S, Tomyshev, AS, Uhlhaas, PJ, Vaernes, TG, van Amelsvoort, TAMJ, Van Erp, TGM, Waltz, JA, Westlye, LT, Wood, SJ, Zhou, JH, McGuire, P, Thompson, PM, Jalbrzikowski, M, Hernaus, D, Fusar-Poli, P, Baldwin, H, Radua, J, Antoniades, M, Haas, SS, Frangou, S, Agartz, I, Allen, P, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Bartholomeusz, CF, Chee, MWL, Colibazzi, T, Cooper, RE, Corcoran, CM, Cropley, VL, Ebdrup, BH, Fortea, A, Glenthoj, LB, Hamilton, HK, Haut, KM, Hayes, RA, He, Y, Heekeren, K, Kaess, M, Kasai, K, Katagiri, N, Kim, M, Kindler, J, Klaunig, MJ, Koike, S, Koppel, A, Kristensen, TD, Bin Kwak, Y, Kwon, JS, Lawrie, SM, Lebedeva, I, Lee, J, Lin, A, Loewy, RL, Mathalon, DH, Michel, C, Mizrahi, R, Moller, P, Nelson, B, Nemoto, T, Nordholm, D, Omelchenko, MA, Pantelis, C, Raghava, JM, Rossberg, J, Roessler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Smigielski, L, Sugranyes, G, Suzuki, M, Takahashi, T, Tamnes, CK, Tang, J, Theodoridou, A, Thomopoulos, S, Tomyshev, AS, Uhlhaas, PJ, Vaernes, TG, van Amelsvoort, TAMJ, Van Erp, TGM, Waltz, JA, Westlye, LT, Wood, SJ, Zhou, JH, McGuire, P, Thompson, PM, Jalbrzikowski, M, Hernaus, D, and Fusar-Poli, P

Abstract

Individuals at Clinical High Risk for Psychosis (CHR-P) demonstrate heterogeneity in clinical profiles and outcome features. However, the extent of neuroanatomical heterogeneity in the CHR-P state is largely undetermined. We aimed to quantify the neuroanatomical heterogeneity in structural magnetic resonance imaging measures of cortical surface area (SA), cortical thickness (CT), subcortical volume (SV), and intracranial volume (ICV) in CHR-P individuals compared with healthy controls (HC), and in relation to subsequent transition to a first episode of psychosis. The ENIGMA CHR-P consortium applied a harmonised analysis to neuroimaging data across 29 international sites, including 1579 CHR-P individuals and 1243 HC, offering the largest pooled CHR-P neuroimaging dataset to date. Regional heterogeneity was indexed with the Variability Ratio (VR) and Coefficient of Variation (CV) ratio applied at the group level. Personalised estimates of heterogeneity of SA, CT and SV brain profiles were indexed with the novel Person-Based Similarity Index (PBSI), with two complementary applications. First, to assess the extent of within-diagnosis similarity or divergence of neuroanatomical profiles between individuals. Second, using a normative modelling approach, to assess the 'normativeness' of neuroanatomical profiles in individuals at CHR-P. CHR-P individuals demonstrated no greater regional heterogeneity after applying FDR corrections. However, PBSI scores indicated significantly greater neuroanatomical divergence in global SA, CT and SV profiles in CHR-P individuals compared with HC. Normative PBSI analysis identified 11 CHR-P individuals (0.70%) with marked deviation (>1.5 SD) in SA, 118 (7.47%) in CT and 161 (10.20%) in SV. Psychosis transition was not significantly associated with any measure of heterogeneity. Overall, our examination of neuroanatomical heterogeneity within the CHR-P state indicated greater divergence in neuroanatomical profiles at an individual level, irre

Published
2022

42. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Y, Shin, J, Abe, C, Agartz, I, Alloza, C, Alnaes, D, Ambrogi, S, Antonucci, LA, Arango, C, Arolt, V, Auzias, G, Ayesa-Arriola, R, Banaj, N, Banaschewski, T, Bandeira, C, Basgoze, Z, Cupertino, RB, Bau, CHD, Bauer, J, Baumeister, S, Bernardoni, F, Bertolino, A, del Mar Bonnin, C, Brandeis, D, Brem, S, Bruggemann, J, Bulow, R, Bustillo, JR, Calderoni, S, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carmona, S, Carr, VJ, Catts, SV, Chenji, S, Chew, QH, Coghill, D, Connolly, CG, Conzelmann, A, Craven, AR, Crespo-Facorro, B, Cullen, K, Dahl, A, Dannlowski, U, Davey, CG, Deruelle, C, Diaz-Caneja, CM, Dohm, K, Ehrlich, S, Epstein, J, Erwin-Grabner, T, Eyler, LT, Fedor, J, Fitzgerald, J, Foran, W, Ford, JM, Fortea, L, Fuentes-Claramonte, P, Fullerton, J, Furlong, L, Gallagher, L, Gao, B, Gao, S, Goikolea, JM, Gotlib, I, Goya-Maldonado, R, Grabe, HJ, Green, M, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Haavik, J, Hahn, T, Harrison, BJ, Heindel, W, Henskens, F, Heslenfeld, DJ, Hilland, E, Hoekstra, PJ, Hohmann, S, Holz, N, Howells, FM, Ipser, JC, Jahanshad, N, Jakobi, B, Jansen, A, Janssen, J, Jonassen, R, Kaiser, A, Kaleda, V, Karantonis, J, King, JA, Kircher, T, Kochunov, P, Koopowitz, S-M, Landen, M, Landro, NI, Lawrie, S, Lebedeva, I, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Mathalon, DH, McDonald, C, McIntosh, A, Meinert, S, Michie, PT, Mitchell, P, Moreno-Alcazar, A, Mowry, B, Muratori, F, Nabulsi, L, Nenadic, I, Tuura, RO, Oosterlaan, J, Overs, B, Pantelis, C, Parellada, M, Pariente, JC, Pauli, P, Pergola, G, Piarulli, FM, Picon, F, Piras, F, Pomarol-Clotet, E, Pretus, C, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Reif, A, Retico, A, Roberts, G, Rossell, S, Rovaris, DL, Rubia, K, Sacchet, M, Salavert, J, Salvador, R, Sarro, S, Sawa, A, Schall, U, Scott, R, Selvaggi, P, Silk, T, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Stein, DJ, Steinstrater, O, Stolicyn, A, Takayanagi, Y, Tamm, L, Tavares, M, Teumer, A, Thiel, K, Thomopoulos, SI, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, Van Rheenen, T, Vazquez-Bourgon, J, Vernooij, MW, Vieta, E, Vilarroya, O, Weickert, C, Weickert, T, Westlye, LT, Whalley, H, Willinger, D, Winter, A, Wittfeld, K, Yang, TT, Yoncheva, Y, Zijlmans, JL, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, Ching, CRK, Andreassen, OA, Pozzi, E, Veltman, D, Schmaal, L, van Erp, TGM, Turner, J, Castellanos, FX, Pausova, Z, Thompson, P, Paus, T, Patel, Y, Shin, J, Abe, C, Agartz, I, Alloza, C, Alnaes, D, Ambrogi, S, Antonucci, LA, Arango, C, Arolt, V, Auzias, G, Ayesa-Arriola, R, Banaj, N, Banaschewski, T, Bandeira, C, Basgoze, Z, Cupertino, RB, Bau, CHD, Bauer, J, Baumeister, S, Bernardoni, F, Bertolino, A, del Mar Bonnin, C, Brandeis, D, Brem, S, Bruggemann, J, Bulow, R, Bustillo, JR, Calderoni, S, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carmona, S, Carr, VJ, Catts, SV, Chenji, S, Chew, QH, Coghill, D, Connolly, CG, Conzelmann, A, Craven, AR, Crespo-Facorro, B, Cullen, K, Dahl, A, Dannlowski, U, Davey, CG, Deruelle, C, Diaz-Caneja, CM, Dohm, K, Ehrlich, S, Epstein, J, Erwin-Grabner, T, Eyler, LT, Fedor, J, Fitzgerald, J, Foran, W, Ford, JM, Fortea, L, Fuentes-Claramonte, P, Fullerton, J, Furlong, L, Gallagher, L, Gao, B, Gao, S, Goikolea, JM, Gotlib, I, Goya-Maldonado, R, Grabe, HJ, Green, M, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Haavik, J, Hahn, T, Harrison, BJ, Heindel, W, Henskens, F, Heslenfeld, DJ, Hilland, E, Hoekstra, PJ, Hohmann, S, Holz, N, Howells, FM, Ipser, JC, Jahanshad, N, Jakobi, B, Jansen, A, Janssen, J, Jonassen, R, Kaiser, A, Kaleda, V, Karantonis, J, King, JA, Kircher, T, Kochunov, P, Koopowitz, S-M, Landen, M, Landro, NI, Lawrie, S, Lebedeva, I, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Mathalon, DH, McDonald, C, McIntosh, A, Meinert, S, Michie, PT, Mitchell, P, Moreno-Alcazar, A, Mowry, B, Muratori, F, Nabulsi, L, Nenadic, I, Tuura, RO, Oosterlaan, J, Overs, B, Pantelis, C, Parellada, M, Pariente, JC, Pauli, P, Pergola, G, Piarulli, FM, Picon, F, Piras, F, Pomarol-Clotet, E, Pretus, C, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Reif, A, Retico, A, Roberts, G, Rossell, S, Rovaris, DL, Rubia, K, Sacchet, M, Salavert, J, Salvador, R, Sarro, S, Sawa, A, Schall, U, Scott, R, Selvaggi, P, Silk, T, Sim, K, Skoch, A, Spalletta, G, Spaniel, F, Stein, DJ, Steinstrater, O, Stolicyn, A, Takayanagi, Y, Tamm, L, Tavares, M, Teumer, A, Thiel, K, Thomopoulos, SI, Tomecek, D, Tomyshev, AS, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, Van Rheenen, T, Vazquez-Bourgon, J, Vernooij, MW, Vieta, E, Vilarroya, O, Weickert, C, Weickert, T, Westlye, LT, Whalley, H, Willinger, D, Winter, A, Wittfeld, K, Yang, TT, Yoncheva, Y, Zijlmans, JL, Hoogman, M, Franke, B, van Rooij, D, Buitelaar, J, Ching, CRK, Andreassen, OA, Pozzi, E, Veltman, D, Schmaal, L, van Erp, TGM, Turner, J, Castellanos, FX, Pausova, Z, Thompson, P, and Paus, T

Abstract

BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from t

Published
2022

43. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A., Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.-M., Landén, M., Landrø, N.I., Lawrie, S., Lebedeva, I., Luna, B., Lundervold, A.J., MacMaster, F.P., Maglanoc, L.A., Mathalon, D.H., McDonald, C., McIntosh, A., Meinert, S., Michie, P.T., Mitchell, P., Moreno-Alcázar, A., Mowry, B., Muratori, F., Nabulsi, L., Nenadić, I., O'Gorman Tuura, R., Oosterlaan, J., Overs, B., Pantelis, C., Parellada, M., Pariente, J.C., Pauli, P., Pergola, G., Piarulli, F.M., Picon, F., Piras, F., Pomarol-Clotet, E., Pretus, C., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Reif, A., Retico, A., Roberts, G., Rossell, S., Rovaris, D.L., Rubia, K., Sacchet, M., Salavert, J., Salvador, R., Sarró, S., Sawa, A., Schall, U., Scott, R., Selvaggi, P., Silk, T., Sim, K., Skoch, A., Spalletta, G., Spaniel, F., Stein, D.J., Steinsträter, O., Stolicyn, A., Takayanagi, Y., Tamm, L., Tavares, M., Teumer, A., Thiel, K., Thomopoulos, S.I., Tomecek, D., Tomyshev, A.S., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Rheenen, T., Vazquez-Bourgón, J., Vernooij, M.W., Vieta, E., Vilarroya, O., Weickert, C., Weickert, T., Westlye, L.T., Whalley, H., Willinger, D., Winter, A., Wittfeld, K., Yang, T.T., Yoncheva, Y., Zijlmans, J.L., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J., Ching, C.R.K., Andreassen, O.A., Pozzi, E., Veltman, D., Schmaal, L., van Erp, T.G.M., Turner, J., Castellanos, F.X., Pausova, Z., Thompson, P., Paus, T., Patel, Y., Shin, J., Abé, C., Agartz, I., Alloza, C., Alnæs, D., Ambrogi, S., Antonucci, L.A., Arango, C., Arolt, V., Auzias, G., Ayesa-Arriola, R., Banaj, N., Banaschewski, T., Bandeira, C., Başgöze, Z., Cupertino, R.B., Bau, C.H.D., Bauer, J., Baumeister, S., Bernardoni, F., Bertolino, A., Bonnin, C.D.M., Brandeis, D., Brem, S., Bruggemann, J., Bülow, R., Bustillo, J.R., Calderoni, S., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carmona, S., Carr, V.J., Catts, S.V., Chenji, S., Chew, Q.H., Coghill, D., Connolly, C.G., Conzelmann, A., Craven, A.R., Crespo-Facorro, B., Cullen, K., Dahl, A., Dannlowski, U., Davey, C.G., Deruelle, C., Díaz-Caneja, C.M., Dohm, K., Ehrlich, S., Epstein, J., Erwin-Grabner, T., Eyler, L.T., Fedor, J., Fitzgerald, J., Foran, W., Ford, J.M., Fortea, L., Fuentes-Claramonte, P., Fullerton, J., Furlong, L., Gallagher, L., Gao, B., Gao, S., Goikolea, J.M., Gotlib, I., Goya-Maldonado, R., Grabe, H.J., Green, M., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Haavik, J., Hahn, T., Harrison, B.J., Heindel, W., Henskens, F., Heslenfeld, D.J., Hilland, E., Hoekstra, P.J., Hohmann, S., Holz, N., Howells, F.M., Ipser, J.C., Jahanshad, N., Jakobi, B., Jansen, A., Janssen, J., Jonassen, R., Kaiser, A., Kaleda, V., Karantonis, J., King, J.A., Kircher, T., Kochunov, P., Koopowitz, S.-M., Landén, M., Landrø, N.I., Lawrie, S., Lebedeva, I., Luna, B., Lundervold, A.J., MacMaster, F.P., Maglanoc, L.A., Mathalon, D.H., McDonald, C., McIntosh, A., Meinert, S., Michie, P.T., Mitchell, P., Moreno-Alcázar, A., Mowry, B., Muratori, F., Nabulsi, L., Nenadić, I., O'Gorman Tuura, R., Oosterlaan, J., Overs, B., Pantelis, C., Parellada, M., Pariente, J.C., Pauli, P., Pergola, G., Piarulli, F.M., Picon, F., Piras, F., Pomarol-Clotet, E., Pretus, C., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Reif, A., Retico, A., Roberts, G., Rossell, S., Rovaris, D.L., Rubia, K., Sacchet, M., Salavert, J., Salvador, R., Sarró, S., Sawa, A., Schall, U., Scott, R., Selvaggi, P., Silk, T., Sim, K., Skoch, A., Spalletta, G., Spaniel, F., Stein, D.J., Steinsträter, O., Stolicyn, A., Takayanagi, Y., Tamm, L., Tavares, M., Teumer, A., Thiel, K., Thomopoulos, S.I., Tomecek, D., Tomyshev, A.S., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Rheenen, T., Vazquez-Bourgón, J., Vernooij, M.W., Vieta, E., Vilarroya, O., Weickert, C., Weickert, T., Westlye, L.T., Whalley, H., Willinger, D., Winter, A., Wittfeld, K., Yang, T.T., Yoncheva, Y., Zijlmans, J.L., Hoogman, M., Franke, B., van Rooij, D., Buitelaar, J., Ching, C.R.K., Andreassen, O.A., Pozzi, E., Veltman, D., Schmaal, L., van Erp, T.G.M., Turner, J., Castellanos, F.X., Pausova, Z., Thompson, P., and Paus, T.

Abstract

Background: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. Methods: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. Results: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. Conclusions: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from t

Published
2022
Full Text
View/download PDF

47. Concurrent antiepileptic and antipsychotic use moderates lithium’s effects on regional brain volumes: a mega-analysis from the ENIGMA-Bipolar Disorder Working Group

Author

King, S., Tronchin, G., Nabulsi, L., Thomopoulos, S.I., Fontana, E., Radua, J., Sim, K., Gruber, O., Yatham, L., Dannlowski, U., Kircher, T., Nenadic, I., Stein, F., Brosch, K., Howells, F., Haarman, B.C.M., Pomarol-Clotet, E., Vieta, E., Landen, M., Cannon, D., Alnæs, D., Westlye, L.T., Jaramillo, C. López, Soeiro-de-Souza, M. Gerhardt, Berk, M., Elvsåshagen, T., Roberts, G., Mitchell, P.B., Fullerton, J.M., Green, M.J., Quidé, Y., Hermesdorf, M., Berger, K., Soares, J., Satterthwaite, T., Savitz, J., Benedetti, F., Glahn, D., Hajek, T., Kuplicki, R., Gotlib, I.H., Amoretti, S., Sacchet, M., Favre, P., Van Rheenen, T., Karantonis, J. Anthony, Furlong, L., Forte, F., Rossell, S., Goldstein, B., Kennedy, K., Canales-Rodriguez, E., Lahud, E., Mwangi, B., Rodriguez-Cano, E., Salvador, R., Wu, M.-J., Houenou, J., Rodrigue, A., Melloni, E.M.T., Sponheim, S., Urosevic, S., Demro, C., Goya-Maldonado, R., Eyler, L., Thompson, P.M., Andreassan, O.A., Ching, C.R.K., and McDonald, C.

Published
2022
Full Text
View/download PDF

49. The global burden of sudden infant death syndrome from 1990 to 2019: a systematic analysis from the Global Burden of Disease study 2019

Author

Park, S, primary, Han, J H, additional, Hwang, J, additional, Yon, D K, additional, Lee, S W, additional, Kim, J H, additional, Koyanagi, A, additional, Jacob, L, additional, Oh, H, additional, Kostev, K, additional, Dragioti, E, additional, Radua, J, additional, Eun, H S, additional, Shin, J I, additional, and Smith, L, additional

Published
2022
Full Text
View/download PDF

50. Differential expression of MicroRNAs in Alzheimer's disease: a systematic review and meta-analysis

Author

Yoon S, Kim SE, Ko Y, Jeong GH, Lee KH, Lee J, Solmi M, Jacob L., Smith L, Stickley A, Carvalho AF, Dragioti E, Kronbichler A, Koyanagi A, Hong SH, Thompson T, Hans Oh, Salazar de Pablo G, Radua J, Shin JI, and Fusar-Poli P

Abstract

Alzheimer's disease (AD) results in progressive cognitive decline owing to the accumulation of amyloid plaques and hyperphosphorylated tau. MicroRNAs (miRNAs) have attracted attention as a putative diagnostic and therapeutic target for neurodegenerative diseases. However, existing meta-analyses on AD and its association with miRNAs have produced inconsistent results. The primary objective of this study is to evaluate the magnitude and consistency of differences in miRNA levels between AD patients, mild cognitive impairment (MCI) patients and healthy controls (HC). Articles investigating miRNA levels in blood, brain tissue, or cerebrospinal fluid (CSF) of AD and MCI patients versus HC were systematically searched in PubMed/Medline from inception to February 16(th), 2021. Fixed- and random-effects meta-analyses were complemented with the I(2) statistic to measure the heterogeneity, assessment of publication bias, sensitivity subgroup analyses (AD severity, brain region, post-mortem versus ante-mortem specimen for CSF and type of analysis used to quantify miRNA) and functional enrichment pathway analysis. Of the 1512 miRNAs included in 61 articles, 425 meta-analyses were performed on 334 miRNAs. Fifty-six miRNAs were significantly upregulated (n = 40) or downregulated (n = 16) in AD versus HC and all five miRNAs were significantly upregulated in MCI versus HC. Functional enrichment analysis confirmed that pathways related to apoptosis, immune response and inflammation were statistically enriched with upregulated pathways in participants with AD relative to HC. This study confirms that miRNAs' expression is altered in AD and MCI compared to HC. These findings open new diagnostic and therapeutic perspectives for this disorder.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results