626 results on '"Frodl T"'
Search Results
2. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis
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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
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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.
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- 2017
3. Cortical abnormalities in adults and adolescents with major depression based on brain scans from 20 cohorts worldwide in the ENIGMA Major Depressive Disorder Working Group
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Schmaal, L, Hibar, DP, Sämann, PG, Hall, GB, Baune, BT, Jahanshad, N, Cheung, JW, van Erp, TGM, Bos, D, Ikram, MA, Vernooij, MW, Niessen, WJ, Tiemeier, H, Hofman, A, Wittfeld, K, Grabe, HJ, Janowitz, D, Bülow, R, Selonke, M, Völzke, H, Grotegerd, D, Dannlowski, U, Arolt, V, Opel, N, Heindel, W, Kugel, H, Hoehn, D, Czisch, M, Couvy-Duchesne, B, Rentería, ME, Strike, LT, Wright, MJ, Mills, NT, de Zubicaray, GI, McMahon, KL, Medland, SE, Martin, NG, Gillespie, NA, Goya-Maldonado, R, Gruber, O, Krämer, B, Hatton, SN, Lagopoulos, J, Hickie, IB, Frodl, T, Carballedo, A, Frey, EM, van Velzen, LS, Penninx, BWJH, van Tol, M-J, van der Wee, NJ, Davey, CG, Harrison, BJ, Mwangi, B, Cao, B, Soares, JC, Veer, IM, Walter, H, Schoepf, D, Zurowski, B, Konrad, C, Schramm, E, Normann, C, Schnell, K, Sacchet, MD, Gotlib, IH, MacQueen, GM, Godlewska, BR, Nickson, T, McIntosh, AM, Papmeyer, M, Whalley, HC, Hall, J, Sussmann, JE, Li, M, Walter, M, Aftanas, L, Brack, I, Bokhan, NA, Thompson, PM, and Veltman, DJ
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Biological Psychology ,Biomedical and Clinical Sciences ,Clinical Sciences ,Psychology ,Major Depressive Disorder ,Serious Mental Illness ,Neurosciences ,Biomedical Imaging ,Depression ,Basic Behavioral and Social Science ,Mental Health ,Brain Disorders ,Clinical Research ,Pediatric ,Behavioral and Social Science ,2.3 Psychological ,social and economic factors ,Aetiology ,2.1 Biological and endogenous factors ,Neurological ,Mental health ,Adolescent ,Adult ,Brain ,Cerebral Cortex ,Depressive Disorder ,Major ,Female ,Frontal Lobe ,Gray Matter ,Gyrus Cinguli ,Humans ,Magnetic Resonance Imaging ,Male ,Neuroimaging ,Prefrontal Cortex ,Temporal Lobe ,Biological Sciences ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Psychiatry ,Clinical sciences ,Biological psychology ,Clinical and health psychology - Abstract
The neuro-anatomical substrates of major depressive disorder (MDD) are still not well understood, despite many neuroimaging studies over the past few decades. Here we present the largest ever worldwide study by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Major Depressive Disorder Working Group on cortical structural alterations in MDD. Structural T1-weighted brain magnetic resonance imaging (MRI) scans from 2148 MDD patients and 7957 healthy controls were analysed with harmonized protocols at 20 sites around the world. To detect consistent effects of MDD and its modulators on cortical thickness and surface area estimates derived from MRI, statistical effects from sites were meta-analysed separately for adults and adolescents. Adults with MDD had thinner cortical gray matter than controls in the orbitofrontal cortex (OFC), anterior and posterior cingulate, insula and temporal lobes (Cohen's d effect sizes: -0.10 to -0.14). These effects were most pronounced in first episode and adult-onset patients (>21 years). Compared to matched controls, adolescents with MDD had lower total surface area (but no differences in cortical thickness) and regional reductions in frontal regions (medial OFC and superior frontal gyrus) and primary and higher-order visual, somatosensory and motor areas (d: -0.26 to -0.57). The strongest effects were found in recurrent adolescent patients. This highly powered global effort to identify consistent brain abnormalities showed widespread cortical alterations in MDD patients as compared to controls and suggests that MDD may impact brain structure in a highly dynamic way, with different patterns of alterations at different stages of life.
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- 2017
4. Real-world evidence from a European cohort study of patients with treatment resistant depression: Baseline patient characteristics
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Heerlein, K., Young, A.H., Otte, C., Frodl, T., Degraeve, G., Hagedoorn, W., Oliveira-Maia, A.J., Perez Sola, V., Rathod, S., Rosso, G., Sierra, P., Morrens, J., Van Dooren, G., Gali, Y., and Perugi, G.
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- 2021
- Full Text
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5. What do the teachers want? A targeted needs assessment survey for prospective didactic training of psychiatry medical educators
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Baessler, F, Zafar, A, Koelkebeck, K, Frodl, T, Signerski-Krieger, J, Pinilla, S, Barth, GM, Jannowitz, D, Speerforck, S, Roesch-Ely, D, Kluge, I, Aust, M, Utz, J, Kersten, GM, Spitzer, P, Baessler, F, Zafar, A, Koelkebeck, K, Frodl, T, Signerski-Krieger, J, Pinilla, S, Barth, GM, Jannowitz, D, Speerforck, S, Roesch-Ely, D, Kluge, I, Aust, M, Utz, J, Kersten, GM, and Spitzer, P
- Abstract
Objectives: Physicians and psychologists at psychiatric university hospitals are assigned teaching tasks from the first day of work without necessarily having the prerequisite training in teaching methods. This exploratory survey provides a needs-based analysis for the prospective didactic training of physicians and psychologists at psychiatric hospitals in Germany, Austria and Switzerland.Methods: An online questionnaire was distributed at medical schools via email in German-speaking countries in Europe. All physicians involved in teaching medical students at psychiatry faculties were eligible to participate in the survey. Participants were further requested to recruit eligible participants (snowball sampling). Responses were analyzed descriptively, and differences between groups were calculated using nonparametric Mann-Whitney U tests (p<.05).Results: Overall, 97 respondents (male=55, female=42; mean age= 40.6) from 19 medical schools completed the survey. The respondents consisted of 43 residents, 39 specialists, 6 chief physicians and 9 psychologists. Of the respondents, 97.6% rated didactic competence as either highly relevant or rather relevant for teaching medical students. The highest overall interest was shown for bedside teaching (mode=4; IQR: 2-4) and error culture (mode=3; IQR: 2-4). Respondents expressed the highest training needs for topics regarding presentation and communication (mode=3; IQR: 2-3). Resident physicians were significantly more interested in bedside teaching (U=362.0, p=0.004) and roleplay (U=425.0; p=0.036) than specialist physicians, who were more interested in examination didactics (U=415.0; p=0.022). Chief physicians displayed significantly deeper interest in group dynamics (U=51; p=0.023) than specialist physicians. In-person training was preferred by a majority of respondents, and 27.4% preferred online/web-based training.Conclusions: The majority of physicians and psychologists at psychiatric university hospitals considered profe, Zielsetzung: Ärzt*innen und Psycholog*innen an psychiatrischen Universitätskliniken werden vom ersten Arbeitstag an mit Lehraufgaben konfrontiert, ohne jedoch notwendigerweise die hierzu erforderliche didaktische Ausbildung erhalten zu haben. Diese Pilotstudie liefert eine bedarfsorientierte Untersuchung für die zukünftige didaktische Ausbildung an psychiatrischen Kliniken tätigen Ärzt*nnen und Psycholog*nnen in Deutschland, Österreich und der Schweiz.Methodik: Eine Onlineumfrage wurde per E-Mail an die Medizinischen Fakultäten in deutschsprachigen, europäischen Ländern verteilt. Alle an der studentischen Lehre beteiligten Ärzt*innen an psychiatrischen Kliniken waren teilnahmeberechtigt. Die Proband*innen wurden außerdem gebeten, qualifizierte Teilnehmer*innen zu rekrutieren (Schneeballverfahren). Die Rückmeldungen wurden deskriptiv ausgewertet, Gruppenunterschiede wurden mit nonparametrischen Mann-Whitney-U-Tests berechnet (p<.05)Ergebnisse: 97 Teilnehmende (männlich=55, weiblich=42; mittleres Alter=40,6 Jahre) von 19 Medizinischen Fakultäten schlossen die Umfrage ab. Diese setzten sich aus 43 Assistenzärzt*innen (AÄ), 39 Fachärzt*innen (FÄ), 6 Chefärzt*innen (CÄ) sowie 9 Psycholog*innen zusammen. 97,6% der Proband*innen empfanden didaktische Kompetenz als relevant, oder sehr relevant für die studentische Lehre. Das größte Interesse bestand an Bedside Teaching (Modus=4; IQA: 2-4) und Fehlerkultur (Modus=3; IQA: 2-4). Der größte Ausbildungsbedarf zeigte sich bei Themen um Präsentation und Kommunikation (Modus=3; IQA: 2-3). Assistenzärzt*innen waren signifikant interessierter an Bedside Teaching (U=362; p=0,004) und Rollenspielen (U=425; p=0,036) als Fachärzt*innen, welche Prüfungsdidaktik als relevanter einstuften (U=415; p=0,022). Chefärzt*innen waren signifikant mehr an Gruppendynamik (U=51; p=0,023) interessiert als Fachärzt*innen. Die Mehrheit der Teilnehmer*innen bevorzugte Präsenzangebote, 27,4% Onlineangebote. Schlussfolgerungen: Der Großteil der Ärzt*innen u
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- 2024
6. The role of carbon dioxide in electroconvulsive therapy: Assessing the necessity of forced hyperventilation
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Paetow, R., primary, Grözinger, M., additional, and Frodl, T., additional
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- 2024
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7. Breath gas markers in depression and their relationship with brain metabolism
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Keskin Gökcelli, D., primary, Itzhacki Sitton, J., additional, Kesik, J., additional, Henning, D., additional, Farrher, E., additional, Shah, N.J., additional, and Frodl, T., additional
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- 2024
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8. Effects of a cognitive bias modification training on resting state EEG oscillations in patients with major depressive disorder and healthy controls
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Kesik, J., primary, Kratochwil, Z., additional, Keskin-Gökcelli, D., additional, Heckelmann, J., additional, Müller, B., additional, and Frodl, T., additional
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- 2024
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9. Response to Dr Fried & Dr Kievit, and Dr Malhi et al.
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Schmaal, L, Veltman, DJ, van Erp, TGM, Sämann, PG, Frodl, T, Jahanshad, N, Loehrer, E, Vernooij, MW, Niessen, WJ, Ikram, MA, Wittfeld, K, Grabe, HJ, Block, A, Hegenscheid, K, Hoehn, D, Czisch, M, Lagopoulos, J, Hatton, SN, Hickie, IB, Goya-Maldonado, R, Krämer, B, Gruber, O, Couvy-Duchesne, B, Rentería, ME, Strike, LT, Wright, MJ, de Zubicaray, GI, McMahon, KL, Medland, SE, Gillespie, NA, Hall, GB, van Velzen, LS, van Tol, M-J, van der Wee, NJ, Veer, IM, Walter, H, Schramm, E, Normann, C, Schoepf, D, Konrad, C, Zurowski, B, McIntosh, AM, Whalley, HC, Sussmann, JE, Godlewska, BR, Fischer, FH, Penninx, BWJH, Thompson, PM, and Hibar, DP
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Biomedical and Clinical Sciences ,Biological Psychology ,Clinical and Health Psychology ,Clinical Sciences ,Psychology ,Biological Sciences ,Medical and Health Sciences ,Psychology and Cognitive Sciences ,Psychiatry ,Clinical sciences ,Biological psychology ,Clinical and health psychology - Published
- 2016
10. Subcortical brain alterations in major depressive disorder: findings from the ENIGMA Major Depressive Disorder working group.
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Schmaal, L, Veltman, DJ, van Erp, TGM, Sämann, PG, Frodl, T, Jahanshad, N, Loehrer, E, Tiemeier, H, Hofman, A, Niessen, WJ, Vernooij, MW, Ikram, MA, Wittfeld, K, Grabe, HJ, Block, A, Hegenscheid, K, Völzke, H, Hoehn, D, Czisch, M, Lagopoulos, J, Hatton, SN, Hickie, IB, Goya-Maldonado, R, Krämer, B, Gruber, O, Couvy-Duchesne, B, Rentería, ME, Strike, LT, Mills, NT, de Zubicaray, GI, McMahon, KL, Medland, SE, Martin, NG, Gillespie, NA, Wright, MJ, Hall, GB, MacQueen, GM, Frey, EM, Carballedo, A, van Velzen, LS, van Tol, MJ, van der Wee, NJ, Veer, IM, Walter, H, Schnell, K, Schramm, E, Normann, C, Schoepf, D, Konrad, C, Zurowski, B, Nickson, T, McIntosh, AM, Papmeyer, M, Whalley, HC, Sussmann, JE, Godlewska, BR, Cowen, PJ, Fischer, FH, Rose, M, Penninx, BWJH, Thompson, PM, and Hibar, DP
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Brain ,Hippocampus ,Humans ,Magnetic Resonance Imaging ,Case-Control Studies ,Depressive Disorder ,Major ,Adult ,Middle Aged ,Female ,Male ,Neuroimaging ,major depressive disorder ,structural volumes ,ENIGMA consortium ,meta-analysis ,hippocampus ,Depressive Disorder ,Major ,Psychiatry ,Medical and Health Sciences ,Biological Sciences ,Psychology and Cognitive Sciences - Abstract
The pattern of structural brain alterations associated with major depressive disorder (MDD) remains unresolved. This is in part due to small sample sizes of neuroimaging studies resulting in limited statistical power, disease heterogeneity and the complex interactions between clinical characteristics and brain morphology. To address this, we meta-analyzed three-dimensional brain magnetic resonance imaging data from 1728 MDD patients and 7199 controls from 15 research samples worldwide, to identify subcortical brain volumes that robustly discriminate MDD patients from healthy controls. Relative to controls, patients had significantly lower hippocampal volumes (Cohen's d=-0.14, % difference=-1.24). This effect was driven by patients with recurrent MDD (Cohen's d=-0.17, % difference=-1.44), and we detected no differences between first episode patients and controls. Age of onset ⩽21 was associated with a smaller hippocampus (Cohen's d=-0.20, % difference=-1.85) and a trend toward smaller amygdala (Cohen's d=-0.11, % difference=-1.23) and larger lateral ventricles (Cohen's d=0.12, % difference=5.11). Symptom severity at study inclusion was not associated with any regional brain volumes. Sample characteristics such as mean age, proportion of antidepressant users and proportion of remitted patients, and methodological characteristics did not significantly moderate alterations in brain volumes in MDD. Samples with a higher proportion of antipsychotic medication users showed larger caudate volumes in MDD patients compared with controls. This currently largest worldwide effort to identify subcortical brain alterations showed robust smaller hippocampal volumes in MDD patients, moderated by age of onset and first episode versus recurrent episode status.
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- 2016
11. Functional connectivity signatures of major depressive disorder: machine learning analysis of two multicenter neuroimaging studies
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Gallo, S, El-Gazzar, A, Zhutovsky, P, Thomas, RM, Javaheripour, N, Li, M, Bartova, L, Bathula, D, Dannlowski, U, Davey, C, Frodl, T, Gotlib, I, Grimm, S, Grotegerd, D, Hahn, T, Hamilton, PJ, Harrison, BJ, Jansen, A, Kircher, T, Meyer, B, Nenadic, I, Olbrich, S, Paul, E, Pezawas, L, Sacchet, MD, Saemann, P, Wagner, G, Walter, H, Walter, M, van Wingen, G, Gallo, S, El-Gazzar, A, Zhutovsky, P, Thomas, RM, Javaheripour, N, Li, M, Bartova, L, Bathula, D, Dannlowski, U, Davey, C, Frodl, T, Gotlib, I, Grimm, S, Grotegerd, D, Hahn, T, Hamilton, PJ, Harrison, BJ, Jansen, A, Kircher, T, Meyer, B, Nenadic, I, Olbrich, S, Paul, E, Pezawas, L, Sacchet, MD, Saemann, P, Wagner, G, Walter, H, Walter, M, and van Wingen, G
- Abstract
The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.
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- 2023
12. Functional connectivity signatures of major depressive disorder: Machine learning analysis of two multicenter neuroimaging studies
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Gallo, S., Elgazzar, A.G.M.A., Zhutovsky, P., Thomas, R.M., Javaheripour, N., Li, M., Bartova, L., Bathula, D., Dannlowski, U., Davey, C., Frodl, T., Gotlib, I.H., Grimm, S., Grotegerd, D., Hahn, T., Hamilton, P.J., Harrison, B.J., Jansen, A., Kircher, T.T.J., Meyer, B., Nenadic, I., Olbrich, S., Paul, E., Pezawas, L., Sacchet, M.D., Sämann, P.G., Wagner, G., Walter, H., Walter, M., Wingen, G.A. van, Gallo, S., Elgazzar, A.G.M.A., Zhutovsky, P., Thomas, R.M., Javaheripour, N., Li, M., Bartova, L., Bathula, D., Dannlowski, U., Davey, C., Frodl, T., Gotlib, I.H., Grimm, S., Grotegerd, D., Hahn, T., Hamilton, P.J., Harrison, B.J., Jansen, A., Kircher, T.T.J., Meyer, B., Nenadic, I., Olbrich, S., Paul, E., Pezawas, L., Sacchet, M.D., Sämann, P.G., Wagner, G., Walter, H., Walter, M., and Wingen, G.A. van
- Abstract
15 februari 2023, Item does not contain fulltext, The promise of machine learning has fueled the hope for developing diagnostic tools for psychiatry. Initial studies showed high accuracy for the identification of major depressive disorder (MDD) with resting-state connectivity, but progress has been hampered by the absence of large datasets. Here we used regular machine learning and advanced deep learning algorithms to differentiate patients with MDD from healthy controls and identify neurophysiological signatures of depression in two of the largest resting-state datasets for MDD. We obtained resting-state functional magnetic resonance imaging data from the REST-meta-MDD (N = 2338) and PsyMRI (N = 1039) consortia. Classification of functional connectivity matrices was done using support vector machines (SVM) and graph convolutional neural networks (GCN), and performance was evaluated using 5-fold cross-validation. Features were visualized using GCN-Explainer, an ablation study and univariate t-testing. The results showed a mean classification accuracy of 61% for MDD versus controls. Mean accuracy for classifying (non-)medicated subgroups was 62%. Sex classification accuracy was substantially better across datasets (73-81%). Visualization of the results showed that classifications were driven by stronger thalamic connections in both datasets, while nearly all other connections were weaker with small univariate effect sizes. These results suggest that whole brain resting-state connectivity is a reliable though poor biomarker for MDD, presumably due to disease heterogeneity as further supported by the higher accuracy for sex classification using the same methods. Deep learning revealed thalamic hyperconnectivity as a prominent neurophysiological signature of depression in both multicenter studies, which may guide the development of biomarkers in future studies.
- Published
- 2023
13. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years
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Dima, D., Modabbernia, A., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dannlowski, U., Dale, A.M., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Kalnin, A., Naaijen, J., Klein, M., Thompson, P.M., Frangou, S., Dima, D., Modabbernia, A., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dannlowski, U., Dale, A.M., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Kalnin, A., Naaijen, J., Klein, M., Thompson, P.M., and Frangou, S.
- Abstract
Contains fulltext : 245411.pdf (Publisher’s version ) (Open Access), 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
14. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years
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Frangou, S., Modabbernia, A., Williams, S.C.R., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dale, A.M., Dannlowski, U., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., Klein, M., Frangou, S., Modabbernia, A., Williams, S.C.R., Papachristou, E., Doucet, G.E., Agartz, I., Aghajani, M., Akudjedu, T.N., Albajes-Eizagirre, A., Alnaes, D., Alpert, K.I., Andersson, M., Andreasen, N.C., Andreassen, O.A., Asherson, P., Banaschewski, T., Bargallo, N., Baumeister, S., Baur-Streubel, R., Bertolino, A., Bonvino, A., Boomsma, D.I., Borgwardt, S., Bourque, J., Brandeis, D., Breier, A., Brodaty, H., Brouwer, R.M., Buitelaar, J.K., Busatto, G.F., Buckner, R.L., Calhoun, V., Canales-Rodríguez, E.J., Cannon, D.M., Caseras, X., Castellanos, F.X., Cervenka, S., Chaim-Avancini, T.M., Ching, C.R., Chubar, V., Clark, V.P., Conrod, P., Conzelmann, A., Crespo-Facorro, B., Crivello, F., Crone, E.A.M., Dale, A.M., Dannlowski, U., Davey, C., Geus, E.J. de, Haan, L. de, Zubicaray, G.I. de, Braber, A., Dickie, E.W., Giorgio, A. Di, Doan, N.T., Dørum, E.S., Ehrlich, S., Erk, S., Espeseth, T., Fatouros-Bergman, H., Fisher, S.E., Fouche, J.P., Franke, B., Frodl, T., Fuentes-Claramonte, P., Glahn, D.C., Gotlib, I.H., Grabe, H.J., Grimm, O., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Gur, R.E., Gur, R.C., Hahn, T., Harrison, B.J., Hartman, Catharina A., Hatton, S.N., Heinz, A., Heslenfeld, D.J., Hibar, D.P., Hickie, I.B., Ho, B.C.H., Hoekstra, P.J., Hohmann, S., Holmes, A.J., Hoogman, M., Hosten, N., Howells, F.M., Pol, H.E.H., Huyser, C., Jahanshad, N., James, A., Jernigan, T.L., Jiang, J., Jönsson, E.G., Joska, J.A., Kahn, R., and Klein, M.
- Abstract
Contains fulltext : 245396.pdf (Publisher’s version ) (Open Access), 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.
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- 2022
15. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure
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Hoogman, M., Rooij, D. van, Klein, M., Boedhoe, P., Ilioska, I., Li, T., Patel, Y., Postema, M.C., Zhang-James, Y., Anagnostou, E., Arango, C., Auzias, G., Banaschewski, T., Bau, C.H.D., Behrmann, M., Bellgrove, Mark A., Brandeis, D., Brem, S., Busatto, G.F., Calderoni, S., Calvo, R., Castellanos, F.X., Coghill, D., Conzelmann, A., Daly, E., Deruelle, C., Dinstein, I., Durston, S., Ecker, C., Ehrlich, S., Epstein, J.N., Fair, D.A., Fitzgerald, J., Freitag, C.M., Frodl, T., Gallagher, L., Grevet, E.H., Haavik, J., Hoekstra, P.J., Janssen, J., Karkashadze, G., King, J.A., Konrad, K., Kuntsi, J., Lazaro, L., Lerch, J.P., Lesch, K.P., Louza, M.R., Luna, B., Mattos, P., McGrath, J., Muratori, F., Murphy, C., Nigg, J.T., Oberwelland-Weiss, E., Tuura, R.L. O'Gorman, O'Hearn, K., Oosterlaan, J., Parellada, M., Pauli, P., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Retico, A., Rosa, P.G., Rubia, K., Shaw, P., Silk, T.J., Tamm, L., Vilarroya, O., Walitza, S., Jahanshad, N., Faraone, S.V, Francks, C., Heuvel, O.A. van den, Paus, T., Thompson, P.M., Buitelaar, J.K., Franke, B., Hoogman, M., Rooij, D. van, Klein, M., Boedhoe, P., Ilioska, I., Li, T., Patel, Y., Postema, M.C., Zhang-James, Y., Anagnostou, E., Arango, C., Auzias, G., Banaschewski, T., Bau, C.H.D., Behrmann, M., Bellgrove, Mark A., Brandeis, D., Brem, S., Busatto, G.F., Calderoni, S., Calvo, R., Castellanos, F.X., Coghill, D., Conzelmann, A., Daly, E., Deruelle, C., Dinstein, I., Durston, S., Ecker, C., Ehrlich, S., Epstein, J.N., Fair, D.A., Fitzgerald, J., Freitag, C.M., Frodl, T., Gallagher, L., Grevet, E.H., Haavik, J., Hoekstra, P.J., Janssen, J., Karkashadze, G., King, J.A., Konrad, K., Kuntsi, J., Lazaro, L., Lerch, J.P., Lesch, K.P., Louza, M.R., Luna, B., Mattos, P., McGrath, J., Muratori, F., Murphy, C., Nigg, J.T., Oberwelland-Weiss, E., Tuura, R.L. O'Gorman, O'Hearn, K., Oosterlaan, J., Parellada, M., Pauli, P., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Retico, A., Rosa, P.G., Rubia, K., Shaw, P., Silk, T.J., Tamm, L., Vilarroya, O., Walitza, S., Jahanshad, N., Faraone, S.V, Francks, C., Heuvel, O.A. van den, Paus, T., Thompson, P.M., Buitelaar, J.K., and Franke, B.
- Abstract
Contains fulltext : 248364.pdf (Publisher’s version ) (Open Access), Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.
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- 2022
16. Reproducibility in the absence of selective reporting: An illustration from large-scale brain asymmetry research
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Kong, XZ, Francks, C, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Asherson, P, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Cannon, DM, Caparelli, EC, Castellanos, FX, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dannlowski, U, de Bruttopilo, SA, de Zeeuw, P, Deary, IJ, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Flint, C, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, JM, Garavan, H, do Santos Garcia, D, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, del Carmen Valdés Hernández, M, Kong, XZ, Francks, C, Mathias, SR, Guadalupe, T, Abé, C, Agartz, I, Akudjedu, TN, Aleman, A, Alhusaini, S, Allen, NB, Ames, D, Andreassen, OA, Vasquez, AA, Armstrong, NJ, Asherson, P, Bergo, F, Bastin, ME, Batalla, A, Bauer, J, Baune, BT, Baur-Streubel, R, Biederman, J, Blaine, SK, Boedhoe, P, Bøen, E, Bose, A, Bralten, J, Brandeis, D, Brem, S, Brodaty, H, Yüksel, D, Brooks, SJ, Buitelaar, J, Bürger, C, Bülow, R, Calhoun, V, Calvo, A, Canales-Rodríguez, EJ, Cannon, DM, Caparelli, EC, Castellanos, FX, Cendes, F, Chaim-Avancini, TM, Chantiluke, K, Chen, QL, Chen, X, Cheng, Y, Christakou, A, Clark, VP, Coghill, D, Connolly, CG, Conzelmann, A, Córdova-Palomera, A, Cousijn, J, Crow, T, Cubillo, A, Dannlowski, U, de Bruttopilo, SA, de Zeeuw, P, Deary, IJ, Demeter, DV, Di Martino, A, Dickie, EW, Dietsche, B, Doan, NT, Doherty, CP, Doyle, A, Durston, S, Earl, E, Ehrlich, S, Ekman, CJ, Elvsåshagen, T, Epstein, JN, Fair, DA, Faraone, SV, Fernández, G, Flint, C, Filho, GB, Förster, K, Fouche, JP, Foxe, JJ, Frodl, T, Fuentes-Claramonte, P, Fullerton, JM, Garavan, H, do Santos Garcia, D, Gotlib, IH, Goudriaan, AE, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gurholt, T, Haavik, J, Hahn, T, Hansell, NK, Harris, MA, Hartman, CA, and del Carmen Valdés Hernández, M
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- 2022
17. Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years
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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.
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- 2022
18. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years
- Author
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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.
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- 2022
19. Consortium neuroscience of attention deficit/hyperactivity disorder and autism spectrum disorder: The ENIGMA adventure
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Hoogman, M, van Rooij, D, Klein, M, Boedhoe, P, Ilioska, I, Li, T, Patel, Y, Postema, MC, Zhang-James, Y, Anagnostou, E, Arango, C, Auzias, G, Banaschewski, T, Bau, CHD, Behrmann, M, Bellgrove, MA, Brandeis, D, Brem, S, Busatto, GF, Calderoni, S, Calvo, R, Castellanos, FX, Coghill, D, Conzelmann, A, Daly, E, Deruelle, C, Dinstein, I, Durston, S, Ecker, C, Ehrlich, S, Epstein, JN, Fair, DA, Fitzgerald, J, Freitag, CM, Frodl, T, Gallagher, L, Grevet, EH, Haavik, J, Hoekstra, PJ, Janssen, J, Karkashadze, G, King, JA, Konrad, K, Kuntsi, J, Lazaro, L, Lerch, JP, Lesch, K-P, Louza, MR, Luna, B, Mattos, P, McGrath, J, Muratori, F, Murphy, C, Nigg, JT, Oberwelland-Weiss, E, Tuura, RLO, O'Hearn, K, Oosterlaan, J, Parellada, M, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Shaw, P, Silk, TJ, Tamm, L, Vilarroya, O, Walitza, S, Jahanshad, N, Faraone, S, Francks, C, van den Heuvel, OA, Paus, T, Thompson, PM, Buitelaar, JK, Franke, B, Hoogman, M, van Rooij, D, Klein, M, Boedhoe, P, Ilioska, I, Li, T, Patel, Y, Postema, MC, Zhang-James, Y, Anagnostou, E, Arango, C, Auzias, G, Banaschewski, T, Bau, CHD, Behrmann, M, Bellgrove, MA, Brandeis, D, Brem, S, Busatto, GF, Calderoni, S, Calvo, R, Castellanos, FX, Coghill, D, Conzelmann, A, Daly, E, Deruelle, C, Dinstein, I, Durston, S, Ecker, C, Ehrlich, S, Epstein, JN, Fair, DA, Fitzgerald, J, Freitag, CM, Frodl, T, Gallagher, L, Grevet, EH, Haavik, J, Hoekstra, PJ, Janssen, J, Karkashadze, G, King, JA, Konrad, K, Kuntsi, J, Lazaro, L, Lerch, JP, Lesch, K-P, Louza, MR, Luna, B, Mattos, P, McGrath, J, Muratori, F, Murphy, C, Nigg, JT, Oberwelland-Weiss, E, Tuura, RLO, O'Hearn, K, Oosterlaan, J, Parellada, M, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Retico, A, Rosa, PGP, Rubia, K, Shaw, P, Silk, TJ, Tamm, L, Vilarroya, O, Walitza, S, Jahanshad, N, Faraone, S, Francks, C, van den Heuvel, OA, Paus, T, Thompson, PM, Buitelaar, JK, and Franke, B
- Abstract
Neuroimaging has been extensively used to study brain structure and function in individuals with attention deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) over the past decades. Two of the main shortcomings of the neuroimaging literature of these disorders are the small sample sizes employed and the heterogeneity of methods used. In 2013 and 2014, the ENIGMA-ADHD and ENIGMA-ASD working groups were respectively, founded with a common goal to address these limitations. Here, we provide a narrative review of the thus far completed and still ongoing projects of these working groups. Due to an implicitly hierarchical psychiatric diagnostic classification system, the fields of ADHD and ASD have developed largely in isolation, despite the considerable overlap in the occurrence of the disorders. The collaboration between the ENIGMA-ADHD and -ASD working groups seeks to bring the neuroimaging efforts of the two disorders closer together. The outcomes of case-control studies of subcortical and cortical structures showed that subcortical volumes are similarly affected in ASD and ADHD, albeit with small effect sizes. Cortical analyses identified unique differences in each disorder, but also considerable overlap between the two, specifically in cortical thickness. Ongoing work is examining alternative research questions, such as brain laterality, prediction of case-control status, and anatomical heterogeneity. In brief, great strides have been made toward fulfilling the aims of the ENIGMA collaborations, while new ideas and follow-up analyses continue that include more imaging modalities (diffusion MRI and resting-state functional MRI), collaborations with other large databases, and samples with dual diagnoses.
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- 2022
20. Do (epi)genetics impact the brain in functional neurologic disorders?
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Frodl, T., primary
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- 2016
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21. Treatment patterns and clinical outcomes
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Heerlein, K., Perugi, G., Otte, C., Frodl, T., Degraeve, G., Hagedoorn, W., Oliveira-Maia, A. J., Perez Sola, V., Rathod, S., Rosso, G., Sierra, P., Malynn, S., Morrens, J., Verrijcken, C., Gonzalez, B., Young, A. H., and NOVA Medical School|Faculdade de Ciências Médicas (NMS|FCM)
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Clinical Psychology ,Psychiatry and Mental health ,SDG 3 - Good Health and Well-being - Abstract
BACKGROUND: Treatment resistant depression (TRD) characterizes a subgroup of 10-30% of patients with major depressive disorder, and is associated with considerable morbidity and mortality. A consensus treatment for TRD does not exist, which often leads to wide variations in treatment strategies. Real-world studies on treatment patterns and outcomes in TRD patients in Europe are lacking and could help elucidate current treatment strategies and their efficacy. METHODS: This non-interventional cohort study of patients with TRD (defined as treatment failure on ≥2 oral antidepressants given at adequate dose and duration) with moderate to severe depression collected real-world data on treatment patterns and outcomes in several European countries. Patients were started on a new treatment for depression according to routine clinical practice. RESULTS: Among 411 patients enrolled, after 6 months, only 16.7% achieved remission and 73.5% showed no response. At Month 12, while 19.2% achieved remission and 69.2% showed no response, 33.3% of those in remission at Month 6 were no longer in remission. Pharmacological treatments employed were heterogenous; 54 different drugs were recorded at baseline, and the top 5 treatment types according to drug classes accounted for 40.0% of patients. Even though remission rates were very low, at Month 12, 60.0% of patients had not changed treatment since enrolment. CONCLUSIONS: The heterogeneity of treatments highlights a lack of consensus. Moreover, despite low response rates, patients often remained on treatments for substantial periods of time. These data further support existence of an unmet treatment need for TRD patients in Europe. publishersversion published
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- 2021
22. Real-World Evidence from a European Cohort Study of Patients with Treatment Resistant Depression: Healthcare Resource Utilization
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Heerlein, K., primary, De Giorgi, S., additional, Degraeve, G., additional, Frodl, T., additional, Hagedoorn, W., additional, Oliveira-Maia, A.J., additional, Otte, C., additional, Sola, V. Perez, additional, Rathod, S., additional, Rosso, G., additional, Sierra, P., additional, Vita, A., additional, Morrens, J., additional, Rive, B., additional, Haughey, S. Mulhern, additional, Kambarov, Y., additional, and Young, A.H., additional
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- 2021
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23. Assessment of Surgical Skills Competence Using fMRI: A Feasibility Study: Education and Training 0046
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Morris, M. C., Frodl, T., DʼSouza, A., Fagan, A. J., and Ridgway, P. F.
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- 2015
24. P 20. Stimulus-dependent behavioural disorder in patients with ANT-DBS for Epilepsy
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Kukhlenko, R., primary, Frantsev, R., additional, Buentjen, L., additional, Voges, J., additional, Kukhlenko, O., additional, Haghikia, A., additional, Frodl, T., additional, and Schmitt, F., additional
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- 2021
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25. Real-world evidence from a European cohort study of patients with treatment resistant depression: Treatment patterns and clinical outcomes
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Heerlein, K., primary, Perugi, G., additional, Otte, C., additional, Frodl, T., additional, Degraeve, G., additional, Hagedoorn, W., additional, Oliveira-Maia, A.J., additional, Perez Sola, V., additional, Rathod, S., additional, Rosso, G., additional, Sierra, P., additional, Malynn, S., additional, Morrens, J., additional, Verrijcken, C., additional, Gonzalez, B., additional, and Young, A.H., additional
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- 2021
- Full Text
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26. Real-World Evidence from a European Cohort Study of Patients with Treatment Resistant Depression: Healthcare Resource Utilization: Healthcare resource utilization
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Heerlein, K., De Giorgi, S., Degraeve, G., Frodl, T., Hagedoorn, W., Oliveira-Maia, A.J., Otte, C., Perez Sola, V., Rathod, S., Rosso, G., Sierra, Pilar, Vita, A., Morrens, J., Rive, B., Mulhern Haughey, S., Kambarov, Y., and Young, A.H.
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Psiquiatria - Abstract
Background: Treatment resistant depression (TRD) is diagnosed when patients experiencing a major depressive episode fail to respond to ≥2 treatments. Along with substantial indirect costs, patients with TRD have higher healthcare resource utilization (HCRU) than other patients with depression. However, research on the economic impact of this HCRU, and differences according to response to treatment, is lacking. Methods: This multicenter, observational study documented HCRU among patients with TRD in European clinical practice initiating new antidepressant treatments. Data regarding access to outpatient consultations and other healthcare resources for the first 6 months, collected using a questionnaire, were analyzed qualitatively according to response and remission status. The economic impact of HCRU, estimated using European costing data, was analyzed quantitatively. Results: Among 411 patients, average HCRU was higher in non-responders, attending five times more general practitioner (GP) consultations and spending longer in hospital (1.7 versus 1.1 days) than responders. Greater differences were observed according to remission status, with non-remitters attending seven times more GP consultations and spending approximately three times longer in hospital (1.7 versus 0.6 days) than remitters. Consequently, the estimated economic impacts of non-responders and non-remitters were significantly greater than those of responders and remitters, respectively. Limitations: Key limitations are small cohort size, absence of control groups and generalizability to different healthcare systems.
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- 2021
27. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
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Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., Schmaal, L., Han, L.K.M., Dinga, R., Hahn, T., Ching, C.R., Eyler, L.T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B.T., Berger, K., Brak, I., Filho, G.B., Carballedo, A., Connolly, C.G., Couvy-Duchesne, B., Cullen, K.R., Dannlowski, U., Davey, C.G., Dima, D., Duran, F.L.S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C.H.Y., Godlewska, B.R., Gotlib, I.H., Grabe, H.J., Groenewold, N.A., Grotegerd, D., Gruber, O., Hall, G.B., Harrison, B.J., Hatton, S.N., Hermesdorf, M., Hickie, I.B., Ho, T.C., Hosten, N., Jansen, Andreas, Kähler, C., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F.P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K.L., Medland, S.E., Mueller, B.A., Mwangi, B., Osipov, E., Portella, M.J., Pozzi, E., Reneman, L., Repple, J., Rosa, P.G., Sacchet, M.D., Sämann, P.G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J.C., Sommer, J., Stein, D.J., Steinsträter, O., Strike, L.T., Thomopoulos, S.I., Tol, M.J.D. van, Veer, I.M., Vermeiren, R., Walter, H., Wee, N.J.A. van der, Werff, S.J.A. van der, Whalley, H., Winter, N.R., Wittfeld, K., Wright, M.J., Wu, M.J., Völzke, H., Yang, T.T., Zannias, V., Zubicaray, G.I. de, Zunta-Soares, G.B., Abé, C., Alda, M., Andreassen, O.A., Bøen, E., Bonnin, C.M., Canales-Rodriguez, E.J., Cannon, D., Caseras, X., Chaim-Avancini, T.M., Elvsåshagen, T., Favre, P., Foley, S.F., Fullerton, J.M., Ruhé, H.G., Schene, A.H., Marquand, A.F., Cole, J., and Schmaal, L.
- Abstract
Item does not contain fulltext, Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
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- 2021
28. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets
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Postema, M.C., Hoogman, M., Ambrosino, S., Asherson, P., Banaschewski, T., Bandeira, C.E., Baranov, A., Bau, C.H.D., Baumeister, S., Baur-Streubel, R., Bellgrove, Mark A., Biederman, J., Bralten, J.B., Brandeis, D., Brem, S., Buitelaar, J.K., Busatto, G.F., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Cupertino, R.B., Zeeuw, P. de, Doyle, A.E., Durston, S., Earl, E.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Frodl, T., Gabel, M.C., Gogberashvili, T., Grevet, E.H., Haavik, J., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hoekstra, P.J., Hohmann, S., Høvik, M.F., Jernigan, T.L., Kardatzki, B., Karkashadze, G., Kelly, C., Kohls, G., Konrad, K., Kuntsi, J., Lazaro, L., Lera-Miguel, S., Lesch, K.P., Louza, M.R., Lundervold, A.J., Malpas, C.B., Mattos, P., McCarthy, H., Namazova-Baranova, L., Nicolau, R., Nigg, J.T., Novotny, S.E., Weiss, E. Oberwelland, Tuura, R.L. O'Gorman, Oosterlaan, J., Oranje, B., Paloyelis, Y., Pauli, P., Picon, F.A., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Rosa, P.G., Rubia, K., Schrantee, A., Schweren, L.J., Seitz, J., Shaw, P., Silk, T.J., Skokauskas, N., Vila, J.C. Soliva, Stevens, M.C., Sudre, G., Tamm, L., Tovar-Moll, F., Erp, T.G. van, Vance, A., Vilarroya, O., Vives-Gilabert, Y., Polier, G.G. von, Walitza, S., Yoncheva, Y.N., Zanetti, M.V., Ziegler, G.C., Glahn, D.C., Fisher, S.E., Franke, B., Francks, C., Postema, M.C., Hoogman, M., Ambrosino, S., Asherson, P., Banaschewski, T., Bandeira, C.E., Baranov, A., Bau, C.H.D., Baumeister, S., Baur-Streubel, R., Bellgrove, Mark A., Biederman, J., Bralten, J.B., Brandeis, D., Brem, S., Buitelaar, J.K., Busatto, G.F., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Cupertino, R.B., Zeeuw, P. de, Doyle, A.E., Durston, S., Earl, E.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Frodl, T., Gabel, M.C., Gogberashvili, T., Grevet, E.H., Haavik, J., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hoekstra, P.J., Hohmann, S., Høvik, M.F., Jernigan, T.L., Kardatzki, B., Karkashadze, G., Kelly, C., Kohls, G., Konrad, K., Kuntsi, J., Lazaro, L., Lera-Miguel, S., Lesch, K.P., Louza, M.R., Lundervold, A.J., Malpas, C.B., Mattos, P., McCarthy, H., Namazova-Baranova, L., Nicolau, R., Nigg, J.T., Novotny, S.E., Weiss, E. Oberwelland, Tuura, R.L. O'Gorman, Oosterlaan, J., Oranje, B., Paloyelis, Y., Pauli, P., Picon, F.A., Plessen, K.J., Ramos-Quiroga, J.A., Reif, A., Reneman, L., Rosa, P.G., Rubia, K., Schrantee, A., Schweren, L.J., Seitz, J., Shaw, P., Silk, T.J., Skokauskas, N., Vila, J.C. Soliva, Stevens, M.C., Sudre, G., Tamm, L., Tovar-Moll, F., Erp, T.G. van, Vance, A., Vilarroya, O., Vives-Gilabert, Y., Polier, G.G. von, Walitza, S., Yoncheva, Y.N., Zanetti, M.V., Ziegler, G.C., Glahn, D.C., Fisher, S.E., Franke, B., and Francks, C.
- Abstract
Item does not contain fulltext, OBJECTIVE: Some studies have suggested alterations of structural brain asymmetry in attention-deficit/hyperactivity disorder (ADHD), but findings have been contradictory and based on small samples. Here, we performed the largest ever analysis of brain left-right asymmetry in ADHD, using 39 datasets of the ENIGMA consortium. METHODS: We analyzed asymmetry of subcortical and cerebral cortical structures in up to 1,933 people with ADHD and 1,829 unaffected controls. Asymmetry Indexes (AIs) were calculated per participant for each bilaterally paired measure, and linear mixed effects modeling was applied separately in children, adolescents, adults, and the total sample, to test exhaustively for potential associations of ADHD with structural brain asymmetries. RESULTS: There was no evidence for altered caudate nucleus asymmetry in ADHD, in contrast to prior literature. In children, there was less rightward asymmetry of the total hemispheric surface area compared to controls (t = 2.1, p = .04). Lower rightward asymmetry of medial orbitofrontal cortex surface area in ADHD (t = 2.7, p = .01) was similar to a recent finding for autism spectrum disorder. There were also some differences in cortical thickness asymmetry across age groups. In adults with ADHD, globus pallidus asymmetry was altered compared to those without ADHD. However, all effects were small (Cohen's d from -0.18 to 0.18) and would not survive study-wide correction for multiple testing. CONCLUSION: Prior studies of altered structural brain asymmetry in ADHD were likely underpowered to detect the small effects reported here. Altered structural asymmetry is unlikely to provide a useful biomarker for ADHD, but may provide neurobiological insights into the trait.
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- 2021
29. Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3–90 years
- Author
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Frangou, S. (Sophia), Modabbernia, A. (Amirhossein), Williams, S.C.R. (Steven C. R.), Papachristou, E. (Efstathios), Doucet, G.E. (Gaelle E.), Agartz, I. (Ingrid), Aghajani, M. (Moji), Akudjedu, T.N. (Theophilus N.), Albajes-Eizagirre, A. (Anton), Alnæs, D. (Dag), Alpert, K. (Kathryn), Andersson, M. (Micael), Andreasen, N.C. (Nancy C.), Andreassen, O.A. (Ole), Asherson, P. (Philip), Banaschewski, T. (Tobias), Bargallo, N. (Nuria), Baumeister, S. (Sarah), Baur-Streubel, R. (Ramona), Bertolino, A. (Alessandro), Bonvino, A. (Aurora), Boomsma, D.I. (Dorret I.), Borgwardt, S. (Stefan), Bourque, J. (Josiane), Brandeis, D. (Daniel), Breier, A. (Alan), Brodaty, H. (Henry), Brouwer, R.M. (Rachel), Buitelaar, J.K. (Jan K.), Busatto, G.F. (Geraldo F.), Buckner, M., Calhoun, V.D. (Vince), Canales-Rodríguez, E.J. (Erick J.), Cannon, D.M. (Dara M.), Caseras, X. (Xavier), Castellanos, F.X. (Francisco X.), Cervenka, S. (Simon), Chaim-Avancini, T.M. (Tiffany M.), Ching, C.R.K. (Christopher), Chubar, V. (Victoria), Clark, V.P. (Vincent P.), Conrod, P. (Patricia), Conzelmann, A. (Annette), Crespo-Facorro, B. (Benedicto), Crivello, F. (Fabrice), Crone, E.A. (Eveline), Dale, A.M. (Anders), Davey, C.G. (Christopher), Geus, E.J.C. (Eco) de, Haan, L. (Lieuwe) de, Zubicaray, G.I. (Greig) de, Braber, A. (Anouk) den, Dickie, E.W. (Erin W.), Di Giorgio, A. (Annabella), Doan, N.T. (Nhat Trung), Dørum, E.S. (Erlend S.), Ehrlich, S.M. (Stefan), Erk, S., Espeseth, T. (Thomas), Fatouros-Bergman, H. (Helena), Fisher, S.E. (Simon), Fouche, J.-P. (Jean-Paul), Franke, B. (Barbara), Frodl, T. (Thomas), Fuentes-Claramonte, P. (Paola), Glahn, D.C. (David), Gotlib, I.H. (Ian H.), Grabe, H.J. (Hans Jörgen), Grimm, O. (Oliver), Groenewold, N.A. (Nynke A.), Grotegerd, D. (Dominik), Gruber, O. (Oliver), Gruner, P. (Patricia), Gur, R.E. (Rachel E.), Gur, R.C. (Ruben C.), Harrison, B.J. (Ben J.), Hartman, C.A. (Catharine A.), Hatton, W., Heinz, A. (Andreas), Heslenfeld, D.J. (Dirk), Hibar, D.P. (Derrek P.), Hickie, I.B. (Ian), Ho, B.-C. (Beng-Choon), Hoekstra, P.J. (Pieter), Hohmann, S. (Sarah), Holmes, A.J. (Avram J.), Hoogman, M. (Martine), Hosten, N. (Norbert), Howells, F.M. (Fleur M.), Hulshoff Pol, H.E. (Hilleke E.), Huyser, J. (Jochanan), Jahanshad, N. (Neda), James, A., Jernigan, T.L. (Terry L.), Jiang, J. (Jiyang), Jönsson, E.G. (Erik G.), Joska, J.A. (John A.), Kahn, R. (Rene), Kalnin, A. (Andrew), Kanai, R. (Ryota), Klein, M. (Marieke), Klyushnik, T.P. (Tatyana P.), Koenders, L. (Laura), Koops, S. (Sanne), Krämer, B. (Bernd), Kuntsi, J. (Jonna), Lagopoulos, J. (Jim), Lázaro, L. (Luisa), Lebedeva, I. (Irina), Lee, W.H. (Won Hee), Lesch, K.-P. (Klaus-Peter), Lochner, C. (Christine), Machielsen, M.W.J. (Marise), Maingault, S. (Sophie), Martin, N.G. (Nicholas G.), Martínez-Zalacaín, I. (Ignacio), Mataix-Cols, D. (David), Mazoyer, B. (Bernard), McDonald, C. (Colm), McDonald, B.C. (Brenna C.), McIntosh, A.M. (Andrew), McMahon, K.L. (Katie L.), McPhilemy, G. (Genevieve), Menchón, J.M. (José M.), Medland, S.E. (Sarah), Meyer-Lindenberg, A. (Andreas), Naaijen, J. (Jilly), Najt, P. (Pablo), Nakao, T. (Tomohiro), Nordvik, J.E. (Jan E.), Nyberg, L. (Lisa), Oosterlaan, J. (Jaap), de la Foz, V.O.-G. (Víctor Ortiz-García), Paloyelis, Y. (Yannis), Pauli, P. (Paul), Pergola, G. (Giulio), Pomarol-Clotet, E. (Edith), Portella, M.J. (Maria J.), Potkin, S.G. (Steven G.), Radua, J. (Joaquim), Reif, A. (Andreas), Rinker, D.A. (Daniel A.), Roffman, J.L. (Joshua), Rosa, P.G.P. (Pedro G. P.), Sacchet, M.D. (Matthew D.), Sachdev, P.S. (Perminder), Salvador, R. (Raymond), Sánchez-Juan, P. (Pascual), Sarró, S. (Salvador), Satterthwaite, T.D. (Theodore), Saykin, A.J. (Andrew), Serpa, M.H. (Mauricio H.), Schmaal, L. (Lianne), Schnell, K. (Kerry), Schumann, G. (Gunter), Sim, K. (Kang), Smoller, J.W., Sommer, I. (Iris), Soriano-Mas, C. (Carles), Stein, D.J. (Dan J.), Strike, L.T. (Lachlan), Swagerman, S.C. (Suzanne C.), Tamnes, C.K. (Christian K.), Temmingh, H.S. (Henk S.), Thomopoulos, S.I. (Sophia I.), Tomyshev, A.S. (Alexander S.), Tordesillas-Gutierrez, D. (Diana), Trollor, J., Turner, J.A. (Jessica A.), Uhlmann, A. (Anne), Heuvel, O.A. (Odile A.), van den Meer, D. (Dennis), Wee, N.J. (Nic) van der, van Haren, N.E.M. (Neeltje E. M.), Ent, D. (Dennis) van 't, Erp, T.G.M. (Theo G.) van, Veer, I.M. (Ilya), Veltman, D.J. (Dick), Voineskos, A. (Aristotle), Völzke, H. (Henry), Walter, H. (Henrik), Walton, E. (Esther), Wang, L. (Lei), Wang, Y. (Yang), Wassink, A.M.J. (Annemarie), Weber, B. (Bernd), Wen, W. (Wei), West, J.D. (John D.), Westlye, L.T. (Lars), Whalley, H. (Heather), Wierenga, L.M. (Lara M.), Wittfeld, K. (Katharina), Wolf, D.H. (Daniel H.), Worker, A. (Amanda), Wright, M.J. (Margaret J.), Yang, K. (Kun), Yoncheva, Y. (Yulyia), Zanetti, M.V. (Marcus V.), Ziegler, G.C. (Georg C.), Thompson, P.M. (Paul), Dima, D. (Danai), Frangou, S. (Sophia), Modabbernia, A. (Amirhossein), Williams, S.C.R. (Steven C. R.), Papachristou, E. (Efstathios), Doucet, G.E. (Gaelle E.), Agartz, I. (Ingrid), Aghajani, M. (Moji), Akudjedu, T.N. (Theophilus N.), Albajes-Eizagirre, A. (Anton), Alnæs, D. (Dag), Alpert, K. (Kathryn), Andersson, M. (Micael), Andreasen, N.C. (Nancy C.), Andreassen, O.A. (Ole), Asherson, P. (Philip), Banaschewski, T. (Tobias), Bargallo, N. (Nuria), Baumeister, S. (Sarah), Baur-Streubel, R. (Ramona), Bertolino, A. (Alessandro), Bonvino, A. (Aurora), Boomsma, D.I. (Dorret I.), Borgwardt, S. (Stefan), Bourque, J. (Josiane), Brandeis, D. (Daniel), Breier, A. (Alan), Brodaty, H. (Henry), Brouwer, R.M. (Rachel), Buitelaar, J.K. (Jan K.), Busatto, G.F. (Geraldo F.), Buckner, M., Calhoun, V.D. (Vince), Canales-Rodríguez, E.J. (Erick J.), Cannon, D.M. (Dara M.), Caseras, X. (Xavier), Castellanos, F.X. (Francisco X.), Cervenka, S. (Simon), Chaim-Avancini, T.M. (Tiffany M.), Ching, C.R.K. (Christopher), Chubar, V. (Victoria), Clark, V.P. (Vincent P.), Conrod, P. (Patricia), Conzelmann, A. (Annette), Crespo-Facorro, B. (Benedicto), Crivello, F. (Fabrice), Crone, E.A. (Eveline), Dale, A.M. (Anders), Davey, C.G. (Christopher), Geus, E.J.C. (Eco) de, Haan, L. (Lieuwe) de, Zubicaray, G.I. (Greig) de, Braber, A. (Anouk) den, Dickie, E.W. (Erin W.), Di Giorgio, A. (Annabella), Doan, N.T. (Nhat Trung), Dørum, E.S. (Erlend S.), Ehrlich, S.M. (Stefan), Erk, S., Espeseth, T. (Thomas), Fatouros-Bergman, H. (Helena), Fisher, S.E. (Simon), Fouche, J.-P. (Jean-Paul), Franke, B. (Barbara), Frodl, T. (Thomas), Fuentes-Claramonte, P. (Paola), Glahn, D.C. (David), Gotlib, I.H. (Ian H.), Grabe, H.J. (Hans Jörgen), Grimm, O. (Oliver), Groenewold, N.A. (Nynke A.), Grotegerd, D. (Dominik), Gruber, O. (Oliver), Gruner, P. (Patricia), Gur, R.E. (Rachel E.), Gur, R.C. (Ruben C.), Harrison, B.J. (Ben J.), Hartman, C.A. (Catharine A.), Hatton, W., Heinz, A. (Andreas), Heslenfeld, D.J. (Dirk), Hibar, D.P. (Derrek P.), Hickie, I.B. (Ian), Ho, B.-C. (Beng-Choon), Hoekstra, P.J. (Pieter), Hohmann, S. (Sarah), Holmes, A.J. (Avram J.), Hoogman, M. (Martine), Hosten, N. (Norbert), Howells, F.M. (Fleur M.), Hulshoff Pol, H.E. (Hilleke E.), Huyser, J. (Jochanan), Jahanshad, N. (Neda), James, A., Jernigan, T.L. (Terry L.), Jiang, J. (Jiyang), Jönsson, E.G. (Erik G.), Joska, J.A. (John A.), Kahn, R. (Rene), Kalnin, A. (Andrew), Kanai, R. (Ryota), Klein, M. (Marieke), Klyushnik, T.P. (Tatyana P.), Koenders, L. (Laura), Koops, S. (Sanne), Krämer, B. (Bernd), Kuntsi, J. (Jonna), Lagopoulos, J. (Jim), Lázaro, L. (Luisa), Lebedeva, I. (Irina), Lee, W.H. (Won Hee), Lesch, K.-P. (Klaus-Peter), Lochner, C. (Christine), Machielsen, M.W.J. (Marise), Maingault, S. (Sophie), Martin, N.G. (Nicholas G.), Martínez-Zalacaín, I. (Ignacio), Mataix-Cols, D. (David), Mazoyer, B. (Bernard), McDonald, C. (Colm), McDonald, B.C. (Brenna C.), McIntosh, A.M. (Andrew), McMahon, K.L. (Katie L.), McPhilemy, G. (Genevieve), Menchón, J.M. (José M.), Medland, S.E. (Sarah), Meyer-Lindenberg, A. (Andreas), Naaijen, J. (Jilly), Najt, P. (Pablo), Nakao, T. (Tomohiro), Nordvik, J.E. (Jan E.), Nyberg, L. (Lisa), Oosterlaan, J. (Jaap), de la Foz, V.O.-G. (Víctor Ortiz-García), Paloyelis, Y. (Yannis), Pauli, P. (Paul), Pergola, G. (Giulio), Pomarol-Clotet, E. (Edith), Portella, M.J. (Maria J.), Potkin, S.G. (Steven G.), Radua, J. (Joaquim), Reif, A. (Andreas), Rinker, D.A. (Daniel A.), Roffman, J.L. (Joshua), Rosa, P.G.P. (Pedro G. P.), Sacchet, M.D. (Matthew D.), Sachdev, P.S. (Perminder), Salvador, R. (Raymond), Sánchez-Juan, P. (Pascual), Sarró, S. (Salvador), Satterthwaite, T.D. (Theodore), Saykin, A.J. (Andrew), Serpa, M.H. (Mauricio H.), Schmaal, L. (Lianne), Schnell, K. (Kerry), Schumann, G. (Gunter), Sim, K. (Kang), Smoller, J.W., Sommer, I. (Iris), Soriano-Mas, C. (Carles), Stein, D.J. (Dan J.), Strike, L.T. (Lachlan), Swagerman, S.C. (Suzanne C.), Tamnes, C.K. (Christian K.), Temmingh, H.S. (Henk S.), Thomopoulos, S.I. (Sophia I.), Tomyshev, A.S. (Alexander S.), Tordesillas-Gutierrez, D. (Diana), Trollor, J., Turner, J.A. (Jessica A.), Uhlmann, A. (Anne), Heuvel, O.A. (Odile A.), van den Meer, D. (Dennis), Wee, N.J. (Nic) van der, van Haren, N.E.M. (Neeltje E. M.), Ent, D. (Dennis) van 't, Erp, T.G.M. (Theo G.) van, Veer, I.M. (Ilya), Veltman, D.J. (Dick), Voineskos, A. (Aristotle), Völzke, H. (Henry), Walter, H. (Henrik), Walton, E. (Esther), Wang, L. (Lei), Wang, Y. (Yang), Wassink, A.M.J. (Annemarie), Weber, B. (Bernd), Wen, W. (Wei), West, J.D. (John D.), Westlye, L.T. (Lars), Whalley, H. (Heather), Wierenga, L.M. (Lara M.), Wittfeld, K. (Katharina), Wolf, D.H. (Daniel H.), Worker, A. (Amanda), Wright, M.J. (Margaret J.), Yang, K. (Kun), Yoncheva, Y. (Yulyia), Zanetti, M.V. (Marcus V.), Ziegler, G.C. (Georg C.), Thompson, P.M. (Paul), and Dima, D. (Danai)
- 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.
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- 2021
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30. Virtual histology of cortical thickness and shared neurobiology in 6 psychiatric disorders
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Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abé, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargalló, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, Del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bülow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodríguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjó-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Silk, Timothy, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abé, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargalló, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, Del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bülow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodríguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjó-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, and Silk, Timothy
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- 2021
31. Characterizing neuroanatomic heterogeneity in people with and without ADHD based on subcortical brain volumes
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Li, T, van Rooij, D, Roth Mota, N, Buitelaar, JK, Hoogman, M, Arias Vasquez, A, Franke, B, Ambrosino, S, Banaschewski, T, Bandeira, CE, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Berm, S, Busatto, GF, Calvo, A, Castellanos, FX, Cercignani, M, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fallgatter, AJ, Fair, DA, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Høvik, MF, Jahanshad, N, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Nicolau, R, Nigg, JT, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Carlos Soliva Vila, J, Soloveva, A, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Anikin, A, Asherson, P, Li, T, van Rooij, D, Roth Mota, N, Buitelaar, JK, Hoogman, M, Arias Vasquez, A, Franke, B, Ambrosino, S, Banaschewski, T, Bandeira, CE, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Berm, S, Busatto, GF, Calvo, A, Castellanos, FX, Cercignani, M, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fallgatter, AJ, Fair, DA, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Høvik, MF, Jahanshad, N, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Nicolau, R, Nigg, JT, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Carlos Soliva Vila, J, Soloveva, A, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Anikin, A, and Asherson, P
- Published
- 2021
32. Evidence for similar structural brain anomalies in youth and adult attention-deficit/hyperactivity disorder: a machine learning analysis
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Zhang-James, Y, Helminen, EC, Liu, J, Busatto, GF, Calvo, A, Cercignani, M, Chaim-Avancini, TM, Gabel, MC, Harrison, NA, Lazaro, L, Lera-Miguel, S, Louza, MR, Nicolau, R, Rosa, PGP, Schulte-Rutte, M, Zanetti, MV, Ambrosino, S, Asherson, P, Banaschewski, T, Baranov, A, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Buitelaar, JK, Castellanos, FX, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Dale, AM, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Frodl, T, Gogberashvili, T, Haavik, J, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jahanshad, N, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lesch, KP, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Mehta, MA, Namazova-Baranova, L, Nigg, JT, Novotny, SE, O’Gorman Tuura, RL, Weiss, EO, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rubia, K, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Silk, Timothy, Skokauskas, N, Vila, JCS, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zhang-James, Y, Helminen, EC, Liu, J, Busatto, GF, Calvo, A, Cercignani, M, Chaim-Avancini, TM, Gabel, MC, Harrison, NA, Lazaro, L, Lera-Miguel, S, Louza, MR, Nicolau, R, Rosa, PGP, Schulte-Rutte, M, Zanetti, MV, Ambrosino, S, Asherson, P, Banaschewski, T, Baranov, A, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Bramati, IE, Brandeis, D, Brem, S, Buitelaar, JK, Castellanos, FX, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Dale, AM, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Frodl, T, Gogberashvili, T, Haavik, J, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jahanshad, N, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lesch, KP, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Mehta, MA, Namazova-Baranova, L, Nigg, JT, Novotny, SE, O’Gorman Tuura, RL, Weiss, EO, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rubia, K, Schrantee, A, Schwarz, L, Schweren, LJS, Seitz, J, Shaw, P, Silk, Timothy, Skokauskas, N, Vila, JCS, Stevens, MC, Sudre, G, Tamm, L, Thompson, PM, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, and Yoncheva, YN
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- 2021
33. Analysis of structural brain asymmetries in attention-deficit/hyperactivity disorder in 39 datasets
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Postema, MC, Hoogman, M, Ambrosino, S, Asherson, P, Banaschewski, T, Bandeira, CE, Baranov, A, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Brandeis, D, Brem, S, Buitelaar, JK, Busatto, GF, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Namazova-Baranova, L, Nicolau, R, Nigg, JT, Novotny, SE, Oberwelland Weiss, E, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Soliva Vila, JC, Stevens, MC, Sudre, G, Tamm, L, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Glahn, DC, Jahanshad, N, Postema, MC, Hoogman, M, Ambrosino, S, Asherson, P, Banaschewski, T, Bandeira, CE, Baranov, A, Bau, CHD, Baumeister, S, Baur-Streubel, R, Bellgrove, MA, Biederman, J, Bralten, J, Brandeis, D, Brem, S, Buitelaar, JK, Busatto, GF, Castellanos, FX, Cercignani, M, Chaim-Avancini, TM, Chantiluke, KC, Christakou, A, Coghill, D, Conzelmann, A, Cubillo, AI, Cupertino, RB, de Zeeuw, P, Doyle, AE, Durston, S, Earl, EA, Epstein, JN, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Frodl, T, Gabel, MC, Gogberashvili, T, Grevet, EH, Haavik, J, Harrison, NA, Hartman, CA, Heslenfeld, DJ, Hoekstra, PJ, Hohmann, S, Høvik, MF, Jernigan, TL, Kardatzki, B, Karkashadze, G, Kelly, C, Kohls, G, Konrad, K, Kuntsi, J, Lazaro, L, Lera-Miguel, S, Lesch, KP, Louza, MR, Lundervold, AJ, Malpas, CB, Mattos, P, McCarthy, H, Namazova-Baranova, L, Nicolau, R, Nigg, JT, Novotny, SE, Oberwelland Weiss, E, O'Gorman Tuura, RL, Oosterlaan, J, Oranje, B, Paloyelis, Y, Pauli, P, Picon, FA, Plessen, KJ, Ramos-Quiroga, JA, Reif, A, Reneman, L, Rosa, PGP, Rubia, K, Schrantee, A, Schweren, LJS, Seitz, J, Shaw, P, Silk, Tim, Skokauskas, N, Soliva Vila, JC, Stevens, MC, Sudre, G, Tamm, L, Tovar-Moll, F, van Erp, TGM, Vance, A, Vilarroya, O, Vives-Gilabert, Y, von Polier, GG, Walitza, S, Yoncheva, YN, Zanetti, MV, Ziegler, GC, Glahn, DC, and Jahanshad, N
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- 2021
34. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders (May, 2020, 10.1038/s41380-020-0774-9)
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Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Samann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, IV, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, van der Auwera, S, Wittfeld, K, Hosten, N, Volzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U
- Published
- 2021
35. Brain structural abnormalities in obesity: relation to age, genetic risk, and common psychiatric disorders Evidence through univariate and multivariate mega-analysis including 6420 participants from the ENIGMA MDD working group
- Author
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Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, Dannlowski, U, Opel, N, Thalamuthu, A, Milaneschi, Y, Grotegerd, D, Flint, C, Leenings, R, Goltermann, J, Richter, M, Hahn, T, Woditsch, G, Berger, K, Hermesdorf, M, McIntosh, A, Whalley, HC, Harris, MA, MacMaster, FP, Walter, H, Veer, IM, Frodl, T, Carballedo, A, Krug, A, Nenadic, I, Kircher, T, Aleman, A, Groenewold, NA, Stein, DJ, Soares, JC, Zunta-Soares, GB, Mwangi, B, Wu, M-J, Walter, M, Li, M, Harrison, BJ, Davey, CG, Cullen, KR, Klimes-Dougan, B, Mueller, BA, Saemann, PG, Penninx, B, Nawijn, L, Veltman, DJ, Aftanas, L, Brak, I, Filimonova, EA, Osipov, EA, Reneman, L, Schrantee, A, Grabe, HJ, Van der Auwera, S, Wittfeld, K, Hosten, N, Voelzke, H, Sim, K, Gotlib, IH, Sacchet, MD, Lagopoulos, J, Hatton, SN, Hickie, I, Pozzi, E, Thompson, PM, Jahanshad, N, Schmaal, L, Baune, BT, and Dannlowski, U
- Abstract
Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = -0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.
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- 2021
36. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
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Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, Schmaal, L, Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Busatto Filho, G, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, CG, Dima, D, Duran, FLS, Enneking, V, Filimonova, E, Frenzel, S, Frodl, T, Fu, CHY, Godlewska, BR, Gotlib, IH, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Hosten, N, Jansen, A, Kaehler, C, Kircher, T, Klimes-Dougan, B, Kraemer, B, Krug, A, Lagopoulos, J, Leenings, R, MacMaster, FP, MacQueen, G, McIntosh, A, McLellan, Q, McMahon, KL, Medland, SE, Mueller, BA, Mwangi, B, Osipov, E, Portella, MJ, Pozzi, E, Reneman, L, Repple, J, Rosa, PGP, Sacchet, MD, Saemann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinstraeter, O, Strike, LT, Thomopoulos, SI, van Tol, M-J, Veer, IM, Vermeiren, RRJM, Walter, H, van der Wee, NJA, van der Werff, SJA, Whalley, H, Winter, NR, Wittfeld, K, Wright, MJ, Wu, M-J, Voelzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abe, C, Alda, M, Andreassen, OA, Boen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsashagen, T, Favre, P, Foley, SF, Fullerton, JM, Goikolea, JM, Haarman, BCM, Hajek, T, Henry, C, Houenou, J, Howells, FM, Ingvar, M, Kuplicki, R, Lafer, B, Landen, M, Machado-Vieira, R, Malt, UF, McDonald, C, Mitchell, PB, Nabulsi, L, Otaduy, MCG, Overs, BJ, Polosan, M, Pomarol-Clotet, E, Radua, J, Rive, MM, Roberts, G, Ruhe, HG, Salvador, R, Sarro, S, Satterthwaite, TD, Savitz, J, Schene, AH, Schofield, PR, Serpa, MH, Sim, K, Soeiro-de-Souza, MG, Sutherland, AN, Temmingh, HS, Timmons, GM, Uhlmann, A, Vieta, E, Wolf, DH, Zanetti, MV, Jahanshad, N, Thompson, PM, Veltman, DJ, Penninx, BWJH, Marquand, AF, Cole, JH, and Schmaal, L
- Abstract
Major depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in adult MDD patients, and whether this process is associated with clinical characteristics in a large multicenter international dataset. We performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 19 samples worldwide. Healthy brain aging was estimated by predicting chronological age (18-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 952 male and 1236 female controls from the ENIGMA MDD working group. The learned model coefficients were applied to 927 male controls and 986 depressed males, and 1199 female controls and 1689 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted "brain age" and chronological age was calculated to indicate brain-predicted age difference (brain-PAD). On average, MDD patients showed a higher brain-PAD of +1.08 (SE 0.22) years (Cohen's d = 0.14, 95% CI: 0.08-0.20) compared with controls. However, this difference did not seem to be driven by specific clinical characteristics (recurrent status, remission status, antidepressant medication use, age of onset, or symptom severity). This highly powered collaborative effort showed subtle patterns of age-related structural brain abnormalities in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the clinical value of these brain-PAD estimates.
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- 2021
37. Altered resting-state functional connectome in major depressive disorder: a mega-analysis from the PsyMRI consortium
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Javaheripour, N, Li, M, Chand, T, Krug, A, Kircher, T, Dannlowski, U, Nenadic, I, Hamilton, JP, Sacchet, MD, Gotlib, IH, Walter, H, Frodl, T, Grimm, S, Harrison, BJ, Wolf, CR, Olbrich, S, van Wingen, G, Pezawas, L, Parker, G, Hyett, MP, Saemann, PG, Hahn, T, Steinstraeter, O, Jansen, A, Yuksel, D, Kaempe, R, Davey, CG, Meyer, B, Bartova, L, Croy, I, Walter, M, Wagner, G, Javaheripour, N, Li, M, Chand, T, Krug, A, Kircher, T, Dannlowski, U, Nenadic, I, Hamilton, JP, Sacchet, MD, Gotlib, IH, Walter, H, Frodl, T, Grimm, S, Harrison, BJ, Wolf, CR, Olbrich, S, van Wingen, G, Pezawas, L, Parker, G, Hyett, MP, Saemann, PG, Hahn, T, Steinstraeter, O, Jansen, A, Yuksel, D, Kaempe, R, Davey, CG, Meyer, B, Bartova, L, Croy, I, Walter, M, and Wagner, G
- Abstract
Major depressive disorder (MDD) is associated with abnormal neural circuitry. It can be measured by assessing functional connectivity (FC) at resting-state functional MRI, that may help identifying neural markers of MDD and provide further efficient diagnosis and monitor treatment outcomes. The main aim of the present study is to investigate, in an unbiased way, functional alterations in patients with MDD using a large multi-center dataset from the PsyMRI consortium including 1546 participants from 19 centers ( www.psymri.com ). After applying strict exclusion criteria, the final sample consisted of 606 MDD patients (age: 35.8 ± 11.9 y.o.; females: 60.7%) and 476 healthy participants (age: 33.3 ± 11.0 y.o.; females: 56.7%). We found significant relative hypoconnectivity within somatosensory motor (SMN), salience (SN) networks and between SMN, SN, dorsal attention (DAN), and visual (VN) networks in MDD patients. No significant differences were detected within the default mode (DMN) and frontoparietal networks (FPN). In addition, alterations in network organization were observed in terms of significantly lower network segregation of SMN in MDD patients. Although medicated patients showed significantly lower FC within DMN, FPN, and SN than unmedicated patients, there were no differences between medicated and unmedicated groups in terms of network organization in SMN. We conclude that the network organization of cortical networks, involved in processing of sensory information, might be a more stable neuroimaging marker for MDD than previously assumed alterations in higher-order neural networks like DMN and FPN.
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- 2021
38. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders
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Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., Paus, T., Patel, Y., Parker, N., Shin, J., Howard, D., French, L., Thomopoulos, S.I., Pozzi, E., Abe, Y., Abé, C., Anticevic, A., Alda, M., Aleman, A., Alloza, C., Alonso-Lana, S., Ameis, S.H., Anagnostou, E., McIntosh, A.A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Ayesa-Arriola, R., Bakker, G., Banaj, N., Banaschewski, T., Bandeira, C.E., Baranov, A., Bargalló, N., Bau, C.H.D., Baumeister, S., Baune, B.T., Bellgrove, M.A., Benedetti, F., Bertolino, A., Boedhoe, P.S.W., Boks, M., Bollettini, I., Del Mar Bonnin, C., Borgers, T., Borgwardt, S., Brandeis, D., Brennan, B.P., Bruggemann, J.M., Bülow, R., Busatto, G.F., Calderoni, S., Calhoun, V.D., Calvo, R., Canales-Rodríguez, E.J., Cannon, D.M., Carr, V.J., Cascella, N., Cercignani, M., Chaim-Avancini, T.M., Christakou, A., Coghill, D., Conzelmann, A., Crespo-Facorro, B., Cubillo, A.I., Cullen, K.R., Cupertino, R.B., Daly, E., Dannlowski, U., Davey, C.G., Denys, D., Deruelle, C., Di Giorgio, A., Dickie, E.W., Dima, D., Dohm, K., Ehrlich, S., Ely, B.A., Erwin-Grabner, T., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V., Fatjó-Vilas, M., Fedor, J.M., Fitzgerald, K.D., Ford, J.M., Frodl, T., Fu, C.H.Y., Fullerton, J.M., Gabel, M.C., Glahn, D.C., Roberts, G., Gogberashvili, T., Goikolea, J.M., Gotlib, I.H., Goya-Maldonado, R., Grabe, H.J., Green, M.J., Grevet, E.H., Groenewold, N.A., Grotegerd, D., Gruber, O., Gruner, P., Guerrero-Pedraza, A., Gur, R.E., Gur, R.C., Haar, S., Haarman, B.C.M., Haavik, J., Hahn, T., Hajek, T., Harrison, B.J., Harrison, N.A., Hartman, C.A., Whalley, H.C., Heslenfeld, D.J., Hibar, D.P., Hilland, E., Hirano, Y., Ho, T.C., Hoekstra, P.J., Hoekstra, L., Hohmann, S., Hong, L.E., Höschl, C., Høvik, M.F., Howells, F.M., Nenadic, I., Jalbrzikowski, M., James, A.C., Janssen, J., Jaspers-Fayer, F., Xu, J., Jonassen, R., Karkashadze, G., King, J.A., Kircher, T., Kirschner, M., Koch, K., Kochunov, P., Kohls, G., Konrad, K., Krämer, B., Krug, A., Kuntsi, J., Kwon, J.S., Landén, M., Landrø, N.I., Lazaro, L., Lebedeva, I.S., Leehr, E.J., Lera-Miguel, S., Lesch, K.-P., Lochner, C., Louza, M.R., Luna, B., Lundervold, A.J., Macmaster, F.P., Maglanoc, L.A., Malpas, C.B., Portella, M.J., Marsh, R., Martyn, F.M., Mataix-Cols, D., Mathalon, D.H., McCarthy, H., McDonald, C., McPhilemy, G., Meinert, S., Menchón, J.M., Minuzzi, L., Mitchell, P.B., Moreno, C., Morgado, P., Muratori, F., Murphy, C.M., Murphy, D., Mwangi, B., Nabulsi, L., Nakagawa, A., Nakamae, T., Namazova, L., Narayanaswamy, J., Jahanshad, N., Nguyen, D.D., Nicolau, R., O'Gorman Tuura, R.L., O'Hearn, K., Oosterlaan, J., Opel, N., Ophoff, R.A., Oranje, B., García De La Foz, V.O., Overs, B.J., Paloyelis, Y., Pantelis, C., Parellada, M., Pauli, P., Picó-Pérez, M., Picon, F.A., Piras, F., Plessen, K.J., Pomarol-Clotet, E., Preda, A., Puig, O., Quidé, Y., Radua, J., Ramos-Quiroga, J.A., Rasser, P.E., Rauer, L., Reddy, J., Redlich, R., Reif, A., Reneman, L., Repple, J., Retico, A., Richarte, V., Richter, A., Rosa, P.G.P., Rubia, K.K., Hashimoto, R., Sacchet, M.D., Salvador, R., Santonja, J., Sarink, K., Sarró, S., Satterthwaite, T.D., Sawa, A., Schall, U., Schofield, P.R., Schrantee, A., Seitz, J., Serpa, M.H., Setién-Suero, E., Shaw, P., Shook, D., Silk, T.J., Sim, K., Simon, S., Simpson, H.B., Singh, A., Skoch, A., Skokauskas, N., Soares, J.C., Soreni, N., Soriano-Mas, C., Spalletta, G., Spaniel, F., Lawrie, S.M., Stern, E.R., Stewart, S.E., Takayanagi, Y., Temmingh, H.S., Tolin, D.F., Tomecek, D., Tordesillas-Gutiérrez, D., Tosetti, M., Uhlmann, A., Van Amelsvoort, T., Van Der Wee, N.J.A., Van Der Werff, S.J.A., Van Haren, N.E.M., Van Wingen, G.A., Vance, A., Vázquez-Bourgon, J., Vecchio, D., Venkatasubramanian, G., Vieta, E., Vilarroya, O., Vives-Gilabert, Y., Voineskos, A.N., Völzke, H., Von Polier, G.G., Walton, E., Weickert, T.W., Weickert, C.S., Weideman, A.S., Wittfeld, K., Wolf, D.H., Wu, M.-J., Yang, T.T., Yang, K., Yoncheva, Y., Yun, J.-Y., Cheng, Y., Zanetti, M.V., Ziegler, G.C., Franke, B., Hoogman, M., Buitelaar, J.K., Van Rooij, D., Andreassen, O.A., Ching, C.R.K., Veltman, D.J., Schmaal, L., Stein, D.J., Van Den Heuvel, O.A., Turner, J.A., Van Erp, T.G.M., Pausova, Z., Thompson, P.M., and Paus, T.
- Abstract
Importance Large-scale neuroimaging studies have revealed group differences in cortical thickness across many psychiatric disorders. The underlying neurobiology behind these differences is not well understood. Objective To determine neurobiologic correlates of group differences in cortical thickness between cases and controls in 6 disorders: attention-deficit/hyperactivity disorder (ADHD), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), and schizophrenia. Design, Setting, and Participants Profiles of group differences in cortical thickness between cases and controls were generated using T1-weighted magnetic resonance images. Similarity between interregional profiles of cell-specific gene expression and those in the group differences in cortical thickness were investigated in each disorder. Next, principal component analysis was used to reveal a shared profile of group difference in thickness across the disorders. Analysis for gene coexpression, clustering, and enrichment for genes associated with these disorders were conducted. Data analysis was conducted between June and December 2019. The analysis included 145 cohorts across 6 psychiatric disorders drawn from the ENIGMA consortium. The numbers of cases and controls in each of the 6 disorders were as follows: ADHD: 1814 and 1602; ASD: 1748 and 1770; BD: 1547 and 3405; MDD: 2658 and 3572; OCD: 2266 and 2007; and schizophrenia: 2688 and 3244. Main Outcomes and Measures Interregional profiles of group difference in cortical thickness between cases and controls. Results A total of 12 721 cases and 15 600 controls, ranging from ages 2 to 89 years, were included in this study. Interregional profiles of group differences in cortical thickness for each of the 6 psychiatric disorders were associated with profiles of gene expression specific to pyramidal (CA1) cells, astrocytes (except for BD), and microglia (exce
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- 2021
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39. Dual-isotope SPECT imaging of striatal dopamine: a comparative study between never-treated and haloperidol-treated first-episode schizophrenic patients
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Schmitt, G. J. E., Dresel, S., Frodl, T., la Fougère, C., Boerner, R., Hahn, K., Möller, H.-J., and Meisenzahl, E. M.
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- 2012
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40. Structural brain alterations at different stages of schizophrenia: A voxel-based morphometric study
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Meisenzahl, E.M., Koutsouleris, N., Bottlender, R., Scheuerecker, J., Jäger, M., Teipel, S.J., Holzinger, S., Frodl, T., Preuss, U., Schmitt, G., Burgermeister, B., Reiser, M., Born, C., and Möller, H.-J.
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- 2008
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41. The hippocampus in major depression: evidence for the convergence of the bench and bedside in psychiatric research?
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MacQueen, G and Frodl, T
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- 2011
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42. Dual-isotope SPECT imaging of striatal dopamine: First episode, drug naïve schizophrenic patients
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Schmitt, G.J.E., la Fougère, C., Dresel, S., Frodl, T., Hahn, K., Möller, H.-J., and Meisenzahl, E.M.
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- 2008
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43. Cerebral changes and cognitive dysfunctions in medication-free schizophrenia – An fMRI study
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Scheuerecker, J., Ufer, S., Zipse, M., Frodl, T., Koutsouleris, N., Zetzsche, T., Wiesmann, M., Albrecht, J., Brückmann, H., Schmitt, G., Möller, H.-J., and Meisenzahl, E.M.
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- 2008
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44. Identifying a consistent pattern of neural function in attention deficit hyperactivity disorder: a meta-analysis
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McCarthy, H., Skokauskas, N., and Frodl, T.
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- 2014
45. Effects of a Cognitive Bias Modification Training on Resting State EEG Microstates in Patients with MDD and Healthy Controls.
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Kesik, J., Kratochwil, Z., Keskin-Gökcelli, D., Müller, B., and Frodl, T.
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COGNITIVE therapy ,PSYCHOLOGICAL tests ,COGNITIVE bias ,MENTAL depression ,ATTENTIONAL bias ,ELECTROENCEPHALOGRAPHY - Abstract
Introduction: Major Depressive Disorder (MDD) is associated with a high burden of disease and notable economic costs. Standard treatments (e.g. medication or cognitive therapy) have been shown to be effective, but some patients remain unresponsive. With the knowledge that MDD patients have been shown to display an attentional cognitive bias towards negative stimuli, Cognitive Bias Modification (CBM)-training to focus attention on positive information is thought to improve emotional processing and depressive symptoms. Some studies imply reduced duration and occurrence of microstate D in MDD compared to healthy controls. However, the effect of CBM on microstates is still unclear. Objectives: (1) To replicate previous findings that duration and occurrence of microstate D is reduced in patients with MDD compared to healthy controls in an independent sample and (2) to investigate the effect of an active CBM-training versus a control-training on microstates and its association with symptom improvements. Methods: Thirty patients receiving outpatient treatment with MDD according to DSM V (aged 18-60) will be recruited in Essen and Aachen. The control group will consist of 30 healthy age-and-sex-matched participants. Psychological testing will be administered and all participants will be randomized to either an active or a control training. During the next visit, resting state EEG and a GoNoGo Task with positive, neutral and negative pictures will be measured. The participants will take a tablet home to undergo 10 sessions of CBM within 14 days. The training will be consisted of a dot-probe-task. In the active condition the probe will be more likely to appear behind a positive versus a neutral picture, while appearing randomly in the control condition. After 14 days, a second EEG will be recorded. Results: Differences in duration and occurrence of microstate D between patients and healthy controls will be analyzed by conducting ANCOVAs with age and sex as covariates. ANCOVAs for repeated measurements will be calculated to study effects of time (pre- vs. post-training) and group (patients vs. healthy controls in active training; patients in active vs. patients in control-training), on duration and occurrence of microstate D. Conclusions: CBM-training is proposed to be an effective treatment option for MDD patients, reflected in a reduced topographical bias of microstate D in EEG. Disclosure of Interest: None Declared [ABSTRACT FROM AUTHOR]
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- 2024
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46. Reduced gray matter brain volumes are associated with variants of the serotonin transporter gene in major depression
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Frodl, T, Koutsouleris, N, Bottlender, R, Born, C, Jäger, M, Mörgenthaler, M, Scheuerecker, J, Zill, P, Baghai, T, Schüle, C, Rupprecht, R, Bondy, B, Reiser, M, Möller, H-J, and Meisenzahl, E M
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- 2008
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47. Effects of treatment with the atypical neuroleptic quetiapine on working memory function: a functional MRI follow-up investigation
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Meisenzahl, E.M., Scheuerecker, J., Zipse, M., Ufer, S., Wiesmann, M., Frodl, T., Koutsouleris, N., Zetzsche, T., Schmitt, G., Riedel, M., Spellmann, I., Dehning, S., Linn, J., Brückmann, H., and Möller, H.J.
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- 2006
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48. Striatal dopamine transporter availability is associated with the productive psychotic state in first episode, drug–naive schizophrenic patients
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Schmitt, G. J. E., Frodl, T., Dresel, S., la Fougère, C., Bottlender, R., Koutsouleris, N., Hahn, K., Möller, H.–J., and Meisenzahl, E. M.
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- 2006
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49. Behandlung vital gefährdeter Anorexia-nervosa-Patienten unter Berücksichtigung der Möglichkeiten des Betreuungsrechts
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Laakmann, G., Ortner, M., Kamleiter, M., Ufer, S., Frodl, T., Goldstein-Müller, B., Jäger, M., Padberg, F., Rüther, T., Sadowsky, N., Tischinger, M., and Stec, I.
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- 2006
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50. Subcortical brain volume, regional cortical thickness, and cortical surface area across disorders: Findings from the ENIGMA ADHD, ASD, and OCD Working Groups
- Author
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Boedhoe, P.S., Rooij, D. van, Hoogman, M., Twisk, J.W.R., Schmaal, L., Abe, Y., Alonso, P., Ameis, S.H., Anikin, A., Anticevic, A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Banaschewski, T., Baranov, A., Batistuzzo, M.C., Baumeister, S., Baur-Streubel, R., Behrmann, M., Bellgrove, M.A., Benedetti, F. De, Beucke, J.C., Biederman, J., Bollettini, I., Bose, A., Bralten, J., Bramati, I.E., Brandeis, D., Brem, S., Brennan, B.P., Busatto, G.F., Calderoni, S., Calvo, A., Calvo, R., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Cheng, Y., Cho, K.I.K., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Dale, A.M., Dallaspezia, S., Daly, E., Denys, D., Deruelle, C., Martino, A, Dinstein, I., Doyle, A.E., Durston, S., Earl, E.A., Ecker, C., Ehrlich, S., Ely, B.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Fedor, J., Feng, X., Feusner, J.D., Fitzgerald, J., Fitzgerald, K.D., Fouche, J.P., Freitag, C.M., Fridgeirsson, E.A., Frodl, T., Gabel, M.C., Gallagher, L., Gogberashvili, T., Gori, I., Gruner, P., Gürsel, D.A., Haar, S., Haavik, J., Hall, G.B., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hirano, Y., Hoekstra, P.J., Hoexter, M.Q., Hohmann, S., Høvik, M.F., Hu, H., Huyser, C., Jahanshad, N., Jalbrzikowski, M., James, A., Janssen, J, Jaspers-Fayer, F., Jernigan, T.L., Kapilushniy, D., Kardatzki, B., Buitelaar, J.K., Franke, B., Heuvel, O.A. van den, Boedhoe, P.S., Rooij, D. van, Hoogman, M., Twisk, J.W.R., Schmaal, L., Abe, Y., Alonso, P., Ameis, S.H., Anikin, A., Anticevic, A., Arango, C., Arnold, P.D., Asherson, P., Assogna, F., Auzias, G., Banaschewski, T., Baranov, A., Batistuzzo, M.C., Baumeister, S., Baur-Streubel, R., Behrmann, M., Bellgrove, M.A., Benedetti, F. De, Beucke, J.C., Biederman, J., Bollettini, I., Bose, A., Bralten, J., Bramati, I.E., Brandeis, D., Brem, S., Brennan, B.P., Busatto, G.F., Calderoni, S., Calvo, A., Calvo, R., Castellanos, F.X., Cercignani, M., Chaim-Avancini, T.M., Chantiluke, K.C., Cheng, Y., Cho, K.I.K., Christakou, A., Coghill, D., Conzelmann, A., Cubillo, A.I., Dale, A.M., Dallaspezia, S., Daly, E., Denys, D., Deruelle, C., Martino, A, Dinstein, I., Doyle, A.E., Durston, S., Earl, E.A., Ecker, C., Ehrlich, S., Ely, B.A., Epstein, J.N., Ethofer, T., Fair, D.A., Fallgatter, A.J., Faraone, S.V, Fedor, J., Feng, X., Feusner, J.D., Fitzgerald, J., Fitzgerald, K.D., Fouche, J.P., Freitag, C.M., Fridgeirsson, E.A., Frodl, T., Gabel, M.C., Gallagher, L., Gogberashvili, T., Gori, I., Gruner, P., Gürsel, D.A., Haar, S., Haavik, J., Hall, G.B., Harrison, N.A., Hartman, Catharina A., Heslenfeld, D.J., Hirano, Y., Hoekstra, P.J., Hoexter, M.Q., Hohmann, S., Høvik, M.F., Hu, H., Huyser, C., Jahanshad, N., Jalbrzikowski, M., James, A., Janssen, J, Jaspers-Fayer, F., Jernigan, T.L., Kapilushniy, D., Kardatzki, B., Buitelaar, J.K., Franke, B., and Heuvel, O.A. van den
- Abstract
Contains fulltext : 225388.pdf (Publisher’s version ) (Closed access), OBJECTIVE: Attention deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), and obsessive-compulsive disorder (OCD) are common neurodevelopmental disorders that frequently co-occur. The authors sought to directly compare these disorders using structural brain imaging data from ENIGMA consortium data. METHODS: Structural T(1)-weighted whole-brain MRI data from healthy control subjects (N=5,827) and from patients with ADHD (N=2,271), ASD (N=1,777), and OCD (N=2,323) from 151 cohorts worldwide were analyzed using standardized processing protocols. The authors examined subcortical volume, cortical thickness, and cortical surface area differences within a mega-analytical framework, pooling measures extracted from each cohort. Analyses were performed separately for children, adolescents, and adults, using linear mixed-effects models adjusting for age, sex, and site (and intracranial volume for subcortical and surface area measures). RESULTS: No shared differences were found among all three disorders, and shared differences between any two disorders did not survive correction for multiple comparisons. Children with ADHD compared with those with OCD had smaller hippocampal volumes, possibly influenced by IQ. Children and adolescents with ADHD also had smaller intracranial volume than control subjects and those with OCD or ASD. Adults with ASD showed thicker frontal cortices compared with adult control subjects and other clinical groups. No OCD-specific differences were observed across different age groups and surface area differences among all disorders in childhood and adulthood. CONCLUSIONS: The study findings suggest robust but subtle differences across different age groups among ADHD, ASD, and OCD. ADHD-specific intracranial volume and hippocampal differences in children and adolescents, and ASD-specific cortical thickness differences in the frontal cortex in adults, support previous work emphasizing structural brain differences in these disorders.
- Published
- 2020
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