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131 results on '"Van der Wee, NJA"'

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

Author: Wise, T, Radua, J, Via, E, Cardoner, N, Abe, O, Adams, TM, Amico, F, Cheng, Y, Cole, JH, de Azevedo Marques Périco, C, Dickstein, DP, Farrow, TFD, Frodl, T, Wagner, G, Gotlib, IH, Gruber, O, Ham, BJ, Job, DE, Kempton, MJ, Kim, MJ, Koolschijn, PCMP, Malhi, GS, Mataix-Cols, D, McIntosh, AM, Nugent, AC, O'Brien, JT, Pezzoli, S, Phillips, ML, Sachdev, PS, Salvadore, G, Selvaraj, S, Stanfield, AC, Thomas, AJ, van Tol, MJ, van der Wee, NJA, Veltman, DJ, Young, AH, Fu, CH, Cleare, AJ, and Arnone, D
Subjects: Biological Psychology, Biomedical and Clinical Sciences, Clinical Sciences, Psychology, Biomedical Imaging, Brain Disorders, Neurosciences, Mental Health, Serious Mental Illness, Major Depressive Disorder, Depression, Mental health, Adult, Bipolar Disorder, Brain, Case-Control Studies, Depressive Disorder, Major, Female, Gray Matter, Humans, Magnetic Resonance Imaging, Male, Neuroimaging, Prefrontal Cortex, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract: Finding robust brain substrates of mood disorders is an important target for research. The degree to which major depression (MDD) and bipolar disorder (BD) are associated with common and/or distinct patterns of volumetric changes is nevertheless unclear. Furthermore, the extant literature is heterogeneous with respect to the nature of these changes. We report a meta-analysis of voxel-based morphometry (VBM) studies in MDD and BD. We identified studies published up to January 2015 that compared grey matter in MDD (50 data sets including 4101 individuals) and BD (36 data sets including 2407 individuals) using whole-brain VBM. We used statistical maps from the studies included where available and reported peak coordinates otherwise. Group comparisons and conjunction analyses identified regions in which the disorders showed common and distinct patterns of volumetric alteration. Both disorders were associated with lower grey-matter volume relative to healthy individuals in a number of areas. Conjunction analysis showed smaller volumes in both disorders in clusters in the dorsomedial and ventromedial prefrontal cortex, including the anterior cingulate cortex and bilateral insula. Group comparisons indicated that findings of smaller grey-matter volumes relative to controls in the right dorsolateral prefrontal cortex and left hippocampus, along with cerebellar, temporal and parietal regions were more substantial in major depression. These results suggest that MDD and BD are characterised by both common and distinct patterns of grey-matter volume changes. This combination of differences and similarities has the potential to inform the development of diagnostic biomarkers for these conditions.
Published: 2017

2. Suspected Transverse Myelitis with Normal MRI and CSF Findings in a Patient with Lupus: What to Do? A Case Series and Systematic Review

Author: Monahan RC, Beaart HJL, Fronczek R, Terwindt GM, Beaart-van de Voorde LJJ, de Bresser J, Kloppenburg M, van der Wee NJA, Huizinga TWJ, and Steup-Beekman GM
Subjects: lupus, neuropsychiatric, transverse myelitis, mri, csf, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract: Rory C Monahan,1 Hannelore JL Beaart,1 Rolf Fronczek,2,3 Gisela M Terwindt,2 Liesbeth JJ Beaart-van de Voorde,1 Jeroen de Bresser,4 Margreet Kloppenburg,1,5 Nic JA van der Wee,6 Tom WJ Huizinga,1 Gerda M Steup-Beekman1,7 1Department of Rheumatology, Leiden University Medical Center (LUMC), Leiden, the Netherlands; 2Department of Neurology, LUMC, Leiden, the Netherlands; 3Sleep-Wake Center SEIN, Heemstede, the Netherlands; 4Department of Radiology, LUMC, Leiden, the Netherlands; 5Department of Clinical Epidemiology, LUMC, Leiden, the Netherlands; 6Department of Psychiatry, LUMC, Leiden, the Netherlands; 7Department of Rheumatology, Haaglanden Medical Center, The Hague, the NetherlandsCorrespondence: Rory C MonahanDepartment of Rheumatology, Leiden University Medical Center (LUMC), Leiden 2333 ZA, the NetherlandsTel +3171-5265762Fax +3171-5266752Email r.c.monahan@lumc.nlPurpose: To evaluate the use of immunosuppressive treatment, clinical outcome and diagnostic strategy in patients with systemic lupus erythematosus (SLE) presenting with clinical features of transverse myelitis (TM), but normal MRI of the spinal cord (sMRI) and normal cerebrospinal fluid (CSF) assessment, and to suggest a clinical guideline.Patients and Methods: All patients with SLE and clinical features compatible with (sub)acute TM visiting the NPSLE clinic of the LUMC between 2007 and 2020 were included. Information on baseline characteristics, investigations, treatment and outcomes was collected from electronic medical records. In addition, a systematic review of individual participant data was performed up to April 2020 in PubMed, Embase and Web of Science, identifying all patients with TM, SLE and sMRI assessment. Data regarding sMRI, CSF analysis, treatment and outcome were extracted, and outcome was compared between patients with normal sMRI and CSF (sMRI-/CSF-) and patients with abnormalities.Results: Twelve SLE patients with a clinical diagnosis of TM were identified: four sMRI-/CSF- and one sMRI- with CSF not available. All patients received immunosuppressive treatment, but outcome in sMRI-/CSF- patients was worse: no recovery (n=1) or partial recovery (n=3) compared to partial recovery (n=4) and (nearly) complete recovery (n=3) in MRI+ patients. The systematic literature review yielded 146 articles eligible for inclusion, 90% case reports. A total of 427 SLE patients with TM were identified, of which only four cases were sMRI-/CSF- (1%), showing no improvement (n=1), partial improvement (n=2) and complete recovery (n=1) after immunosuppressive treatment.Conclusion: Outcome in SLE patients presenting with clinically suspected TM with normal sMRI and CSF is less favorable, despite treatment with immunosuppressive therapy. Taking a functional neurological disorder into consideration may be helpful in order to start other therapeutic strategies. We suggest prescribing immunosuppressive treatment for a restricted period of time to evaluate its effect in cases where a functional disorder initially is considered unlikely.Keywords: lupus, neuropsychiatric, transverse myelitis, MRI, CSF
Published: 2020

3. ENIGMA-anxiety working group: Rationale for and organization of large-scale neuroimaging studies of anxiety disorders.

Author: Bas-Hoogendam, JM, Groenewold, NA, Aghajani, M, Freitag, GF, Harrewijn, A, Hilbert, K, Jahanshad, N, Thomopoulos, SI, Thompson, PM, Veltman, DJ, Winkler, AM, Lueken, U, Pine, DS, van der Wee, NJA, Stein, DJ, ENIGMA-Anxiety Working Group, Bas-Hoogendam, JM, Groenewold, NA, Aghajani, M, Freitag, GF, Harrewijn, A, Hilbert, K, Jahanshad, N, Thomopoulos, SI, Thompson, PM, Veltman, DJ, Winkler, AM, Lueken, U, Pine, DS, van der Wee, NJA, Stein, DJ, and ENIGMA-Anxiety Working Group
Abstract: Anxiety disorders are highly prevalent and disabling but seem particularly tractable to investigation with translational neuroscience methodologies. Neuroimaging has informed our understanding of the neurobiology of anxiety disorders, but research has been limited by small sample sizes and low statistical power, as well as heterogenous imaging methodology. The ENIGMA-Anxiety Working Group has brought together researchers from around the world, in a harmonized and coordinated effort to address these challenges and generate more robust and reproducible findings. This paper elaborates on the concepts and methods informing the work of the working group to date, and describes the initial approach of the four subgroups studying generalized anxiety disorder, panic disorder, social anxiety disorder, and specific phobia. At present, the ENIGMA-Anxiety database contains information about more than 100 unique samples, from 16 countries and 59 institutes. Future directions include examining additional imaging modalities, integrating imaging and genetic data, and collaborating with other ENIGMA working groups. The ENIGMA consortium creates synergy at the intersection of global mental health and clinical neuroscience, and the ENIGMA-Anxiety Working Group extends the promise of this approach to neuroimaging research on anxiety disorders.
Published: 2022

4. Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium

Author: van Velzen, LS, Dauvermann, MR, Colic, L, Villa, LM, Savage, HS, Toenders, YJ, Zhu, AH, Bright, JK, Campos, A, Salminen, LE, Ambrogi, S, Ayesa-Arriola, R, Banaj, N, Basgoze, Z, Bauer, J, Blair, K, Blair, RJ, Brosch, K, Cheng, Y, Colle, R, Connolly, CG, Corruble, E, Couvy-Duchesne, B, Crespo-Facorro, B, Cullen, KR, Dannlowski, U, Davey, CG, Dohm, K, Fullerton, JM, Gonul, AS, Gotlib, IH, Grotegerd, D, Hahn, T, Harrison, BJ, He, M, Hickie, IB, Ho, TC, Iorfino, F, Jansen, A, Jollant, F, Kircher, T, Klimes-Dougan, B, Klug, M, Leehr, EJ, Lippard, ETC, McLaughlin, KA, Meinert, S, Miller, AB, Mitchell, PB, Mwangi, B, Nenadic, I, Ojha, A, Overs, BJ, Pfarr, J-K, Piras, F, Ringwald, KG, Roberts, G, Romer, G, Sanches, M, Sheridan, MA, Soares, JC, Spalletta, G, Stein, F, Teresi, G, Tordesillas-Gutierrez, D, Uyar-Demir, A, van der Wee, NJA, van der Werff, SJ, Vermeiren, RRJM, Winter, A, Wu, M-J, Yang, TT, Thompson, PM, Renteria, ME, Jahanshad, N, Blumberg, HP, Van Harmelen, A-L, Schmaal, L, van Velzen, LS, Dauvermann, MR, Colic, L, Villa, LM, Savage, HS, Toenders, YJ, Zhu, AH, Bright, JK, Campos, A, Salminen, LE, Ambrogi, S, Ayesa-Arriola, R, Banaj, N, Basgoze, Z, Bauer, J, Blair, K, Blair, RJ, Brosch, K, Cheng, Y, Colle, R, Connolly, CG, Corruble, E, Couvy-Duchesne, B, Crespo-Facorro, B, Cullen, KR, Dannlowski, U, Davey, CG, Dohm, K, Fullerton, JM, Gonul, AS, Gotlib, IH, Grotegerd, D, Hahn, T, Harrison, BJ, He, M, Hickie, IB, Ho, TC, Iorfino, F, Jansen, A, Jollant, F, Kircher, T, Klimes-Dougan, B, Klug, M, Leehr, EJ, Lippard, ETC, McLaughlin, KA, Meinert, S, Miller, AB, Mitchell, PB, Mwangi, B, Nenadic, I, Ojha, A, Overs, BJ, Pfarr, J-K, Piras, F, Ringwald, KG, Roberts, G, Romer, G, Sanches, M, Sheridan, MA, Soares, JC, Spalletta, G, Stein, F, Teresi, G, Tordesillas-Gutierrez, D, Uyar-Demir, A, van der Wee, NJA, van der Werff, SJ, Vermeiren, RRJM, Winter, A, Wu, M-J, Yang, TT, Thompson, PM, Renteria, ME, Jahanshad, N, Blumberg, HP, Van Harmelen, A-L, and Schmaal, L
Abstract: Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk.
Published: 2022

5. The association between clinical and biological characteristics of depression and structural brain alterations

Author: Toenders, YJ, Schmaal, L, Nawijn, L, Han, LKM, Binnewies, J, van der Wee, NJA, van Tol, M-J, Veltman, DJ, Milaneschi, Y, Lamers, F, Penninx, BWJH, Toenders, YJ, Schmaal, L, Nawijn, L, Han, LKM, Binnewies, J, van der Wee, NJA, van Tol, M-J, Veltman, DJ, Milaneschi, Y, Lamers, F, and Penninx, BWJH
Abstract: BACKGROUND: Structural brain alterations are observed in major depressive disorder (MDD). However, MDD is a highly heterogeneous disorder and specific clinical or biological characteristics of depression might relate to specific structural brain alterations. Clinical symptom subtypes of depression, as well as immuno-metabolic dysregulation associated with subtypes of depression, have been associated with brain alterations. Therefore, we examined if specific clinical and biological characteristics of depression show different brain alterations compared to overall depression. METHOD: Individuals with and without depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA) (328 participants from three timepoints leading to 541 observations) and the Mood Treatment with Antidepressants or Running (MOTAR) study (123 baseline participants) were included. Symptom profiles (atypical energy-related profile, melancholic profile and depression severity) and biological indices (inflammatory, metabolic syndrome, and immuno-metabolic indices) were created. The associations of the clinical and biological profiles with depression-related structural brain measures (anterior cingulate cortex [ACC], orbitofrontal cortex, insula, and nucleus accumbens) were examined dimensionally in both studies and meta-analysed. RESULTS: Depression severity was negatively associated with rostral ACC thickness (B = -0.55, pFDR = 0.03), and melancholic symptoms were negatively associated with caudal ACC thickness (B = -0.42, pFDR = 0.03). The atypical energy-related symptom profile and immuno-metabolic indices did not show a consistent association with structural brain measures across studies. CONCLUSION: Overall depression- and melancholic symptom severity showed a dose-response relationship with reduced ACC thickness. No associations between immuno-metabolic dysregulation and structural brain alterations were found, suggesting that although both are associated with
Published: 2022

6. Brain Correlates of Suicide Attempt in 18,925 Participants Across 18 International Cohorts

Author: Campos, A, Thompson, PM, Veltman, DJ, Pozzi, E, van Veltzen, LS, Jahanshad, N, Adams, MJ, Baune, BT, Berger, K, Brosch, K, Bulow, R, Connolly, CG, Dannlowski, U, Davey, CG, de Zubicaray, G, Dima, D, Erwin-Grabner, T, Evans, JW, Fu, CHY, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Grotegerd, D, Harris, MA, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, McMahon, K, MacMaster, FP, Martin, NG, McIntosh, AM, Medland, SE, Meinert, S, Meller, T, Nenadic, I, Opel, N, Redlich, R, Reneman, L, Repple, J, Sacchet, MD, Schmitt, S, Schrantee, A, Sim, K, Singh, A, Stein, F, Strike, LT, van Der Wee, NJA, van Der Werff, SJA, Volzke, H, Waltemate, L, Whalley, HC, Wittfeld, K, Wright, MJ, Yang, TT, Zarate, CA, Schmaal, L, Renteria, ME, Campos, A, Thompson, PM, Veltman, DJ, Pozzi, E, van Veltzen, LS, Jahanshad, N, Adams, MJ, Baune, BT, Berger, K, Brosch, K, Bulow, R, Connolly, CG, Dannlowski, U, Davey, CG, de Zubicaray, G, Dima, D, Erwin-Grabner, T, Evans, JW, Fu, CHY, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Grotegerd, D, Harris, MA, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Ho, TC, Kircher, T, Krug, A, Lagopoulos, J, Lemke, H, McMahon, K, MacMaster, FP, Martin, NG, McIntosh, AM, Medland, SE, Meinert, S, Meller, T, Nenadic, I, Opel, N, Redlich, R, Reneman, L, Repple, J, Sacchet, MD, Schmitt, S, Schrantee, A, Sim, K, Singh, A, Stein, F, Strike, LT, van Der Wee, NJA, van Der Werff, SJA, Volzke, H, Waltemate, L, Whalley, HC, Wittfeld, K, Wright, MJ, Yang, TT, Zarate, CA, Schmaal, L, and Renteria, ME
Abstract: BACKGROUND: Neuroimaging studies of suicidal behavior have so far been conducted in small samples, prone to biases and false-positive associations, yielding inconsistent results. The ENIGMA-MDD Working Group aims to address the issues of poor replicability and comparability by coordinating harmonized analyses across neuroimaging studies of major depressive disorder and related phenotypes, including suicidal behavior. METHODS: Here, we pooled data from 18 international cohorts with neuroimaging and clinical measurements in 18,925 participants (12,477 healthy control subjects and 6448 people with depression, of whom 694 had attempted suicide). We compared regional cortical thickness and surface area and measures of subcortical, lateral ventricular, and intracranial volumes between suicide attempters, clinical control subjects (nonattempters with depression), and healthy control subjects. RESULTS: We identified 25 regions of interest with statistically significant (false discovery rate < .05) differences between groups. Post hoc examinations identified neuroimaging markers associated with suicide attempt including smaller volumes of the left and right thalamus and the right pallidum and lower surface area of the left inferior parietal lobe. CONCLUSIONS: This study addresses the lack of replicability and consistency in several previously published neuroimaging studies of suicide attempt and further demonstrates the need for well-powered samples and collaborative efforts. Our results highlight the potential involvement of the thalamus, a structure viewed historically as a passive gateway in the brain, and the pallidum, a region linked to reward response and positive affect. Future functional and connectivity studies of suicidal behaviors may focus on understanding how these regions relate to the neurobiological mechanisms of suicide attempt risk.
Published: 2021

7. Contributing factors to advanced brain aging in depression and anxiety disorders

Author: Han, LKM, Schnack, HG, Brouwer, RM, Veltman, DJ, van der Wee, NJA, van Tol, M-J, Aghajani, M, Penninx, BWJH, Han, LKM, Schnack, HG, Brouwer, RM, Veltman, DJ, van der Wee, NJA, van Tol, M-J, Aghajani, M, and Penninx, BWJH
Abstract: Depression and anxiety are common and often comorbid mental health disorders that represent risk factors for aging-related conditions. Brain aging has shown to be more advanced in patients with major depressive disorder (MDD). Here, we extend prior work by investigating multivariate brain aging in patients with MDD, anxiety disorders, or both, and examine which factors contribute to older-appearing brains. Adults aged 18-57 years from the Netherlands Study of Depression and Anxiety underwent structural MRI. A pretrained brain-age prediction model based on >2000 samples from the ENIGMA consortium was applied to obtain brain-predicted age differences (brain PAD, predicted brain age minus chronological age) in 65 controls and 220 patients with current MDD and/or anxiety. Brain-PAD estimates were associated with clinical, somatic, lifestyle, and biological factors. After correcting for antidepressant use, brain PAD was significantly higher in MDD (+2.78 years, Cohen's d = 0.25, 95% CI -0.10-0.60) and anxiety patients (+2.91 years, Cohen's d = 0.27, 95% CI -0.08-0.61), compared with controls. There were no significant associations with lifestyle or biological stress systems. A multivariable model indicated unique contributions of higher severity of somatic depression symptoms (b = 4.21 years per unit increase on average sum score) and antidepressant use (-2.53 years) to brain PAD. Advanced brain aging in patients with MDD and anxiety was most strongly associated with somatic depressive symptomatology. We also present clinically relevant evidence for a potential neuroprotective antidepressant effect on the brain-PAD metric that requires follow-up in future research.
Published: 2021

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

Author: Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Frangou, S, Dima, D, Modabbernia, A, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, Ortiz-Garcia De la Foz, V, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, Van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Williams, SCR, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Frangou, S
Abstract: Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry. In response, we capitalized on the resources of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to examine age-related trajectories inferred from cross-sectional measures of the ventricles, the basal ganglia (caudate, putamen, pallidum, and nucleus accumbens), the thalamus, hippocampus and amygdala using magnetic resonance imaging data obtained from 18,605 individuals aged 3-90 years. All subcortical structure volumes were at their maximum value early in life. The volume of the basal ganglia showed a monotonic negative association with age thereafter; there was no significant association between age and the volumes of the thalamus, amygdala and the hippocampus (with some degree of decline in thalamus) until the sixth decade of life after which they also showed a steep negative association with age. The lateral ventricles showed continuous enlargement throughout the lifespan. Age was positively associated with inter-individual variability in the hippocampus and amygdala and the lateral ventricles. These results were robust to potential confounders and could be used to examine the functional significance of deviations from typical age-related morphometric patterns.
Published: 2021

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

Author: Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, Dima, D, Frangou, S, Modabbernia, A, Williams, SCR, Papachristou, E, Doucet, GE, Agartz, I, Aghajani, M, Akudjedu, TN, Albajes-Eizagirre, A, Alnaes, D, Alpert, K, Andersson, M, Andreasen, NC, Andreassen, OA, Asherson, P, Banaschewski, T, Bargallo, N, Baumeister, S, Baur-Streubel, R, Bertolino, A, Bonvino, A, Boomsma, D, Borgwardt, S, Bourque, J, Brandeis, D, Breier, A, Brodaty, H, Brouwer, RM, Buitelaar, JK, Busatto, GF, Buckner, RL, Calhoun, V, Canales-Rodriguez, EJ, Cannon, DM, Caseras, X, Castellanos, FX, Cervenka, S, Chaim-Avancini, TM, Ching, CRK, Chubar, V, Clark, VP, Conrod, P, Conzelmann, A, Crespo-Facorro, B, Crivello, F, Crone, EA, Dale, AM, Davey, C, de Geus, EJC, de Haan, L, de Zubicaray, G, den Braber, A, Dickie, EW, Di Giorgio, A, Nhat, TD, Dorum, ES, Ehrlich, S, Erk, S, Espeseth, T, Fatouros-Bergman, H, Fisher, SE, Fouche, J-P, Franke, B, Frodl, T, Fuentes-Claramonte, P, Glahn, DC, Gotlib, IH, Grabe, H-J, Grimm, O, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Gur, RE, Gur, RC, Harrison, BJ, Hartman, CA, Hatton, SN, Heinz, A, Heslenfeld, DJ, Hibar, DP, Hickie, IB, Ho, B-C, Hoekstra, PJ, Hohmann, S, Holmes, AJ, Hoogman, M, Hosten, N, Howells, FM, Pol, HEH, Huyser, C, Jahanshad, N, James, A, Jernigan, TL, Jiang, J, Jonsson, EG, Joska, JA, Kahn, R, Kalnin, A, Kanai, R, Klein, M, Klyushnik, TP, Koenders, L, Koops, S, Kraemer, B, Kuntsi, J, Lagopoulos, J, Lazaro, L, Lebedeva, I, Lee, WH, Lesch, K-P, Lochner, C, Machielsen, MWJ, Maingault, S, Martin, NG, Martinez-Zalacain, I, Mataix-Cols, D, Mazoyer, B, McDonald, C, McDonald, BC, McIntosh, AM, McMahon, KL, McPhilemy, G, Menchon, JM, Medland, SE, Meyer-Lindenberg, A, Naaijen, J, Najt, P, Nakao, T, Nordvik, JE, Nyberg, L, Oosterlaan, J, de la Foz, VO-G, Paloyelis, Y, Pauli, P, Pergola, G, Pomarol-Clotet, E, Portella, MJ, Potkin, SG, Radua, J, Reif, A, Rinker, DA, Roffman, JL, Rosa, PGP, Sacchet, MD, Sachdev, PS, Salvador, R, Sanchez-Juan, P, Sarro, S, Satterthwaite, TD, Saykin, AJ, Serpa, MH, Schmaal, L, Schnell, K, Schumann, G, Sim, K, Smoller, JW, Sommer, I, Soriano-Mas, C, Stein, DJ, Strike, LT, Swagerman, SC, Tamnes, CK, Temmingh, HS, Thomopoulos, S, Tomyshev, AS, Tordesillas-Gutierrez, D, Trollor, JN, Turner, JA, Uhlmann, A, van den Heuvel, OA, van den Meer, D, van der Wee, NJA, van Haren, NEM, van't Ent, D, van Erp, TGM, Veer, IM, Veltman, DJ, Voineskos, A, Voelzke, H, Walter, H, Walton, E, Wang, L, Wang, Y, Wassink, TH, Weber, B, Wen, W, West, JD, Westlye, LT, Whalley, H, Wierenga, LM, Wittfeld, K, Wolf, DH, Worker, A, Wright, MJ, Yang, K, Yoncheva, Y, Zanetti, M, Ziegler, GC, Thompson, PM, and Dima, D
Abstract: Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes.
Published: 2021

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

Author: Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, Paus, T, Patel, Y, Parker, N, Shin, J, Howard, D, French, L, Thomopoulos, SI, Pozzi, E, Abe, Y, Abe, C, Anticevic, A, Alda, M, Aleman, A, Alloza, C, Alonso-Lana, S, Ameis, SH, Anagnostou, E, McIntosh, AA, Arango, C, Arnold, PD, Asherson, P, Assogna, F, Auzias, G, Ayesa-Arriola, R, Bakker, G, Banaj, N, Banaschewski, T, Bandeira, CE, Baranov, A, Bargallo, N, Bau, CHD, Baumeister, S, Baune, BT, Bellgrove, MA, Benedetti, F, Bertolino, A, Boedhoe, PSW, Boks, M, Bollettini, I, del Mar Bonnin, C, Borgers, T, Borgwardt, S, Brandeis, D, Brennan, BP, Bruggemann, JM, Bulow, R, Busatto, GF, Calderoni, S, Calhoun, VD, Calvo, R, Canales-Rodriguez, EJ, Cannon, DM, Carr, VJ, Cascella, N, Cercignani, M, Chaim-Avancini, TM, Christakou, A, Coghill, D, Conzelmann, A, Crespo-Facorro, B, Cubillo, AI, Cullen, KR, Cupertino, RB, Daly, E, Dannlowski, U, Davey, CG, Denys, D, Deruelle, C, Di Giorgio, A, Dickie, EW, Dima, D, Dohm, K, Ehrlich, S, Ely, BA, Erwin-Grabner, T, Ethofer, T, Fair, DA, Fallgatter, AJ, Faraone, SV, Fatjo-Vilas, M, Fedor, JM, Fitzgerald, KD, Ford, JM, Frodl, T, Fu, CHY, Fullerton, JM, Gabel, MC, Glahn, DC, Roberts, G, Gogberashvili, T, Goikolea, JM, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Green, MJ, Grevet, EH, Groenewold, NA, Grotegerd, D, Gruber, O, Gruner, P, Guerrero-Pedraza, A, Gur, RE, Gur, RC, Haar, S, Haarman, BCM, Haavik, J, Hahn, T, Hajek, T, Harrison, BJ, Harrison, NA, Hartman, CA, Whalley, HC, Heslenfeld, DJ, Hibar, DP, Hilland, E, Hirano, Y, Ho, TC, Hoekstra, PJ, Hoekstra, L, Hohmann, S, Hong, LE, Hoschl, C, Hovik, MF, Howells, FM, Nenadic, I, Jalbrzikowski, M, James, AC, Janssen, J, Jaspers-Fayer, F, Xu, J, Jonassen, R, Karkashadze, G, King, JA, Kircher, T, Kirschner, M, Koch, K, Kochunov, P, Kohls, G, Konrad, K, Kramer, B, Krug, A, Kuntsi, J, Kwon, JS, Landen, M, Landro, NI, Lazaro, L, Lebedeva, IS, Leehr, EJ, Lera-Miguel, S, Lesch, K-P, Lochner, C, Louza, MR, Luna, B, Lundervold, AJ, MacMaster, FP, Maglanoc, LA, Malpas, CB, Portella, MJ, Marsh, R, Martyn, FM, Mataix-Cols, D, Mathalon, DH, McCarthy, H, McDonald, C, McPhilemy, G, Meinert, S, Menchon, JM, Minuzzi, L, Mitchell, PB, Moreno, C, Morgado, P, Muratori, F, Murphy, CM, Murphy, D, Mwangi, B, Nabulsi, L, Nakagawa, A, Nakamae, T, Namazova, L, Narayanaswamy, J, Jahanshad, N, Nguyen, DD, Nicolau, R, O'Gorman Tuura, RL, O'Hearn, K, Oosterlaan, J, Opel, N, Ophoff, RA, Oranje, B, Garcia de la Foz, VO, Overs, BJ, Paloyelis, Y, Pantelis, C, Parellada, M, Pauli, P, Pico-Perez, M, Picon, FA, Piras, F, Plessen, KJ, Pomarol-Clotet, E, Preda, A, Puig, O, Quide, Y, Radua, J, Ramos-Quiroga, JA, Rasser, PE, Rauer, L, Reddy, J, Redlich, R, Reif, A, Reneman, L, Repple, J, Retico, A, Richarte, V, Richter, A, Rosa, PGP, Rubia, KK, Hashimoto, R, Sacchet, MD, Salvador, R, Santonja, J, Sarink, K, Sarro, S, Satterthwaite, TD, Sawa, A, Schall, U, Schofield, PR, Schrantee, A, Seitz, J, Serpa, MH, Setien-Suero, E, Shaw, P, Shook, D, Silk, TJ, Sim, K, Simon, S, Simpson, HB, Singh, A, Skoch, A, Skokauskas, N, Soares, JC, Soreni, N, Soriano-Mas, C, Spalletta, G, Spaniel, F, Lawrie, SM, Stern, ER, Stewart, SE, Takayanagi, Y, Temmingh, HS, Tolin, DF, Tomecek, D, Tordesillas-Gutierrez, D, Tosetti, M, Uhlmann, A, van Amelsvoort, T, van der Wee, NJA, van der Werff, SJA, van Haren, NEM, van Wingen, GA, Vance, A, Vazquez-Bourgon, J, Vecchio, D, Venkatasubramanian, G, Vieta, E, Vilarroya, O, Vives-Gilabert, Y, Voineskos, AN, Volzke, H, von Polier, GG, Walton, E, Weickert, TW, Weickert, CS, Weideman, AS, Wittfeld, K, Wolf, DH, Wu, M-J, Yang, TT, Yang, K, Yoncheva, Y, Yun, J-Y, Cheng, Y, Zanetti, MV, Ziegler, GC, Franke, B, Hoogman, M, Buitelaar, JK, van Rooij, D, Andreassen, OA, Ching, CRK, Veltman, DJ, Schmaal, L, Stein, DJ, van den Heuvel, OA, Turner, JA, van Erp, TGM, Pausova, Z, Thompson, PM, 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 (except for OCD); collectively, gene
Published: 2021

11. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group.

Author: Han, LKM, Dinga, R, Hahn, T, Ching, CRK, Eyler, LT, Aftanas, L, Aghajani, M, Aleman, A, Baune, BT, Berger, K, Brak, I, Filho, GB, 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, Kähler, C, Kircher, T, Klimes-Dougan, B, Krämer, 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, Sämann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinsträter, 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, Völzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abé, C, Alda, M, Andreassen, OA, Bøen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsåshagen, 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, Landén, 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, Sarró, 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, Filho, GB, 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, Kähler, C, Kircher, T, Klimes-Dougan, B, Krämer, 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, Sämann, PG, Schnell, K, Schrantee, A, Simulionyte, E, Soares, JC, Sommer, J, Stein, DJ, Steinsträter, 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, Völzke, H, Yang, TT, Zannias, V, de Zubicaray, GI, Zunta-Soares, GB, Abé, C, Alda, M, Andreassen, OA, Bøen, E, Bonnin, CM, Canales-Rodriguez, EJ, Cannon, D, Caseras, X, Chaim-Avancini, TM, Elvsåshagen, 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, Landén, 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, Sarró, 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.
Published: 2021

12. ENIGMA and global neuroscience: A decade of large-scale studies of the brain in health and disease across more than 40 countries

Author: Thompson, PM, Jahanshad, N, Ching, CRK, Salminen, LE, Thomopoulos, SI, Bright, J, Baune, BT, Bertolin, S, Bralten, J, Bruin, WB, Buelow, R, Chen, J, Chye, Y, Dannlowski, U, de Kovel, CGF, Donohoe, G, Eyler, LT, Faraone, SV, Favre, P, Filippi, CA, Frodl, T, Garijo, D, Gil, Y, Grabe, HJ, Grasby, KL, Hajek, T, Han, LKM, Hatton, SN, Hilbert, K, Ho, TC, Holleran, L, Homuth, G, Hosten, N, Houenou, J, Ivanov, I, Jia, T, Kelly, S, Klein, M, Kwon, JS, Laansma, MA, Leerssen, J, Lueken, U, Nunes, A, Neill, JO, Opel, N, Piras, F, Postema, MC, Pozzi, E, Shatokhina, N, Soriano-Mas, C, Spalletta, G, Sun, D, Teumer, A, Tilot, AK, Tozzi, L, van der Merwe, C, Van Someren, EJW, van Wingen, GA, Voelzke, H, Walton, E, Wang, L, Winkler, AM, Wittfeld, K, Wright, MJ, Yun, J-Y, Zhang, G, Zhang-James, Y, Adhikari, BM, Agartz, I, Aghajani, M, Aleman, A, Althoff, RR, Altmann, A, Andreassen, OA, Baron, DA, Bartnik-Olson, BL, Bas-Hoogendam, J, Baskin-Sommers, AR, Bearden, CE, Berner, LA, Boedhoe, PSW, Brouwer, RM, Buitelaar, JK, Caeyenberghs, K, Cecil, CAM, Cohen, RA, Cole, JH, Conrod, PJ, De Brito, SA, de Zwarte, SMC, Dennis, EL, Desrivieres, S, Dima, D, Ehrlich, S, Esopenko, C, Fairchild, G, Fisher, SE, Fouche, J-P, Francks, C, Frangou, S, Franke, B, Garavan, HP, Glahn, DC, Groenewold, NA, Gurholt, TP, Gutman, BA, Hahn, T, Harding, IH, Hernaus, D, Hibar, DP, Hillary, FG, Hoogman, M, Pol, HE, Jalbrzikowski, M, Karkashadze, GA, Klapwijk, ET, Knickmeyer, RC, Kochunov, P, Koerte, IK, Kong, X-Z, Liew, S-L, Lin, AP, Logue, MW, Luders, E, Macciardi, F, Mackey, S, Mayer, AR, McDonald, CR, McMahon, AB, Medland, SE, Modinos, G, Morey, RA, Mueller, SC, Mukherjee, P, Namazova-Baranova, L, Nir, TM, Olsen, A, Paschou, P, Pine, DS, Pizzagalli, F, Renteria, ME, Rohrer, JD, Saemann, PG, Schmaal, L, Schumann, G, Shiroishi, MS, Sisodiya, SM, Smit, DJA, Sonderby, IE, Stein, DJ, Stein, JL, Tahmasian, M, Tate, DF, Turner, JA, van den Heuvel, OA, van der Wee, NJA, van der Werf, YD, van Erp, TGM, van Haren, NEM, van Rooij, D, van Velzen, LS, Veer, IM, Veltman, DJ, Villalon-Reina, JE, Walter, H, Whelan, CD, Wilde, EA, Zarei, M, Zelman, V, Thompson, PM, Jahanshad, N, Ching, CRK, Salminen, LE, Thomopoulos, SI, Bright, J, Baune, BT, Bertolin, S, Bralten, J, Bruin, WB, Buelow, R, Chen, J, Chye, Y, Dannlowski, U, de Kovel, CGF, Donohoe, G, Eyler, LT, Faraone, SV, Favre, P, Filippi, CA, Frodl, T, Garijo, D, Gil, Y, Grabe, HJ, Grasby, KL, Hajek, T, Han, LKM, Hatton, SN, Hilbert, K, Ho, TC, Holleran, L, Homuth, G, Hosten, N, Houenou, J, Ivanov, I, Jia, T, Kelly, S, Klein, M, Kwon, JS, Laansma, MA, Leerssen, J, Lueken, U, Nunes, A, Neill, JO, Opel, N, Piras, F, Postema, MC, Pozzi, E, Shatokhina, N, Soriano-Mas, C, Spalletta, G, Sun, D, Teumer, A, Tilot, AK, Tozzi, L, van der Merwe, C, Van Someren, EJW, van Wingen, GA, Voelzke, H, Walton, E, Wang, L, Winkler, AM, Wittfeld, K, Wright, MJ, Yun, J-Y, Zhang, G, Zhang-James, Y, Adhikari, BM, Agartz, I, Aghajani, M, Aleman, A, Althoff, RR, Altmann, A, Andreassen, OA, Baron, DA, Bartnik-Olson, BL, Bas-Hoogendam, J, Baskin-Sommers, AR, Bearden, CE, Berner, LA, Boedhoe, PSW, Brouwer, RM, Buitelaar, JK, Caeyenberghs, K, Cecil, CAM, Cohen, RA, Cole, JH, Conrod, PJ, De Brito, SA, de Zwarte, SMC, Dennis, EL, Desrivieres, S, Dima, D, Ehrlich, S, Esopenko, C, Fairchild, G, Fisher, SE, Fouche, J-P, Francks, C, Frangou, S, Franke, B, Garavan, HP, Glahn, DC, Groenewold, NA, Gurholt, TP, Gutman, BA, Hahn, T, Harding, IH, Hernaus, D, Hibar, DP, Hillary, FG, Hoogman, M, Pol, HE, Jalbrzikowski, M, Karkashadze, GA, Klapwijk, ET, Knickmeyer, RC, Kochunov, P, Koerte, IK, Kong, X-Z, Liew, S-L, Lin, AP, Logue, MW, Luders, E, Macciardi, F, Mackey, S, Mayer, AR, McDonald, CR, McMahon, AB, Medland, SE, Modinos, G, Morey, RA, Mueller, SC, Mukherjee, P, Namazova-Baranova, L, Nir, TM, Olsen, A, Paschou, P, Pine, DS, Pizzagalli, F, Renteria, ME, Rohrer, JD, Saemann, PG, Schmaal, L, Schumann, G, Shiroishi, MS, Sisodiya, SM, Smit, DJA, Sonderby, IE, Stein, DJ, Stein, JL, Tahmasian, M, Tate, DF, Turner, JA, van den Heuvel, OA, van der Wee, NJA, van der Werf, YD, van Erp, TGM, van Haren, NEM, van Rooij, D, van Velzen, LS, Veer, IM, Veltman, DJ, Villalon-Reina, JE, Walter, H, Whelan, CD, Wilde, EA, Zarei, M, and Zelman, V
Abstract: This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.
Published: 2020

13. ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing

Author: Schmaal, L, Pozzi, E, Ho, TC, van Velzen, LS, Veer, IM, Opel, N, Van Someren, EJW, Han, LKM, Aftanas, L, Aleman, A, Baune, BT, Berger, K, Blanken, TF, Capitao, L, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, C, Erwin-Grabner, T, Evans, J, Frodl, T, Fu, CHY, Godlewska, B, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gutman, BA, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Hilland, E, Irungu, B, Jonassen, R, Kelly, S, Kircher, T, Klimes-Dougan, B, Krug, A, Landro, NI, Lagopoulos, J, Leerssen, J, Li, M, Linden, DEJ, MacMaster, FP, McIntosh, AM, Mehler, DMA, Nenadic, I, Penninx, BWJH, Portella, MJ, Reneman, L, Renteria, ME, Sacchet, MD, Saemann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Tozzi, L, van Der Wee, NJA, van Tol, M-J, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, Whalley, HC, Wittfeld, K, Whittle, S, Wright, MJ, Yang, TT, Zarate, C, Thomopoulos, SI, Jahanshad, N, Thompson, PM, Veltman, DJ, Schmaal, L, Pozzi, E, Ho, TC, van Velzen, LS, Veer, IM, Opel, N, Van Someren, EJW, Han, LKM, Aftanas, L, Aleman, A, Baune, BT, Berger, K, Blanken, TF, Capitao, L, Couvy-Duchesne, B, Cullen, KR, Dannlowski, U, Davey, C, Erwin-Grabner, T, Evans, J, Frodl, T, Fu, CHY, Godlewska, B, Gotlib, IH, Goya-Maldonado, R, Grabe, HJ, Groenewold, NA, Grotegerd, D, Gruber, O, Gutman, BA, Hall, GB, Harrison, BJ, Hatton, SN, Hermesdorf, M, Hickie, IB, Hilland, E, Irungu, B, Jonassen, R, Kelly, S, Kircher, T, Klimes-Dougan, B, Krug, A, Landro, NI, Lagopoulos, J, Leerssen, J, Li, M, Linden, DEJ, MacMaster, FP, McIntosh, AM, Mehler, DMA, Nenadic, I, Penninx, BWJH, Portella, MJ, Reneman, L, Renteria, ME, Sacchet, MD, Saemann, PG, Schrantee, A, Sim, K, Soares, JC, Stein, DJ, Tozzi, L, van Der Wee, NJA, van Tol, M-J, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, Whalley, HC, Wittfeld, K, Whittle, S, Wright, MJ, Yang, TT, Zarate, C, Thomopoulos, SI, Jahanshad, N, Thompson, PM, and Veltman, DJ
Abstract: A key objective in the field of translational psychiatry over the past few decades has been to identify the brain correlates of major depressive disorder (MDD). Identifying measurable indicators of brain processes associated with MDD could facilitate the detection of individuals at risk, and the development of novel treatments, the monitoring of treatment effects, and predicting who might benefit most from treatments that target specific brain mechanisms. However, despite intensive neuroimaging research towards this effort, underpowered studies and a lack of reproducible findings have hindered progress. Here, we discuss the work of the ENIGMA Major Depressive Disorder (MDD) Consortium, which was established to address issues of poor replication, unreliable results, and overestimation of effect sizes in previous studies. The ENIGMA MDD Consortium currently includes data from 45 MDD study cohorts from 14 countries across six continents. The primary aim of ENIGMA MDD is to identify structural and functional brain alterations associated with MDD that can be reliably detected and replicated across cohorts worldwide. A secondary goal is to investigate how demographic, genetic, clinical, psychological, and environmental factors affect these associations. In this review, we summarize findings of the ENIGMA MDD disease working group to date and discuss future directions. We also highlight the challenges and benefits of large-scale data sharing for mental health research.
Published: 2020

14. Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort

Author: Tozzi, L, Garczarek, L, Janowitz, D, Stein, DJ, Wittfeld, K, Dobrowolny, H, Lagopoulos, J, Hatton, SN, Hickie, IB, Carballedo, A, Brooks, SJ, Vuletic, D, Uhlmann, A, Veer, IM, Walter, H, Buelow, R, Voelzke, H, Klinger-Koenig, J, Schnell, K, Schoepf, D, Grotegerd, D, Opel, N, Dannlowski, U, Kugel, H, Schramm, E, Konrad, C, Kircher, T, Jueksel, DI, Nenadic, I, Krug, A, Hahn, T, Steinstraeter, O, Redlich, R, Zaremba, D, Zurowski, B, Fu, CHY, Dima, D, Cole, J, Grabe, HJ, Connolly, CG, Yang, TT, Ho, TC, Lewinn, KZ, Li, M, Groenewold, NA, Salminen, LE, Walter, M, Simmons, AN, van Erp, TGM, Jahanshad, N, Baune, BT, van der Wee, NJA, van Tol, M-J, Penninx, BWJH, Hibar, DP, Thompson, PM, Veltman, DJ, Schmaal, L, Frodl, T, Tozzi, L, Garczarek, L, Janowitz, D, Stein, DJ, Wittfeld, K, Dobrowolny, H, Lagopoulos, J, Hatton, SN, Hickie, IB, Carballedo, A, Brooks, SJ, Vuletic, D, Uhlmann, A, Veer, IM, Walter, H, Buelow, R, Voelzke, H, Klinger-Koenig, J, Schnell, K, Schoepf, D, Grotegerd, D, Opel, N, Dannlowski, U, Kugel, H, Schramm, E, Konrad, C, Kircher, T, Jueksel, DI, Nenadic, I, Krug, A, Hahn, T, Steinstraeter, O, Redlich, R, Zaremba, D, Zurowski, B, Fu, CHY, Dima, D, Cole, J, Grabe, HJ, Connolly, CG, Yang, TT, Ho, TC, Lewinn, KZ, Li, M, Groenewold, NA, Salminen, LE, Walter, M, Simmons, AN, van Erp, TGM, Jahanshad, N, Baune, BT, van der Wee, NJA, van Tol, M-J, Penninx, BWJH, Hibar, DP, Thompson, PM, Veltman, DJ, Schmaal, L, and Frodl, T
Abstract: BACKGROUND: Childhood maltreatment (CM) plays an important role in the development of major depressive disorder (MDD). The aim of this study was to examine whether CM severity and type are associated with MDD-related brain alterations, and how they interact with sex and age. METHODS: Within the ENIGMA-MDD network, severity and subtypes of CM using the Childhood Trauma Questionnaire were assessed and structural magnetic resonance imaging data from patients with MDD and healthy controls were analyzed in a mega-analysis comprising a total of 3872 participants aged between 13 and 89 years. Cortical thickness and surface area were extracted at each site using FreeSurfer. RESULTS: CM severity was associated with reduced cortical thickness in the banks of the superior temporal sulcus and supramarginal gyrus as well as with reduced surface area of the middle temporal lobe. Participants reporting both childhood neglect and abuse had a lower cortical thickness in the inferior parietal lobe, middle temporal lobe, and precuneus compared to participants not exposed to CM. In males only, regardless of diagnosis, CM severity was associated with higher cortical thickness of the rostral anterior cingulate cortex. Finally, a significant interaction between CM and age in predicting thickness was seen across several prefrontal, temporal, and temporo-parietal regions. CONCLUSIONS: Severity and type of CM may impact cortical thickness and surface area. Importantly, CM may influence age-dependent brain maturation, particularly in regions related to the default mode network, perception, and theory of mind.
Published: 2020

15. The genetic architecture of the human cerebral cortex

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

16. Predicting individual clinical trajectories of depression with generative embedding

Author: Fraessle, S, Marquand, AF, Schmaal, L, Dinga, R, Veltman, DJ, van der Wee, NJA, van Tol, M-J, Schoebi, D, Penninx, BWJH, Stephan, KE, Fraessle, S, Marquand, AF, Schmaal, L, Dinga, R, Veltman, DJ, van der Wee, NJA, van Tol, M-J, Schoebi, D, Penninx, BWJH, and Stephan, KE
Abstract: Patients with major depressive disorder (MDD) show heterogeneous treatment response and highly variable clinical trajectories: while some patients experience swift recovery, others show relapsing-remitting or chronic courses. Predicting individual clinical trajectories at an early stage is a key challenge for psychiatry and might facilitate individually tailored interventions. So far, however, reliable predictors at the single-patient level are absent. Here, we evaluated the utility of a machine learning strategy - generative embedding (GE) - which combines interpretable generative models with discriminative classifiers. Specifically, we used functional magnetic resonance imaging (fMRI) data of emotional face perception in 85 MDD patients from the NEtherlands Study of Depression and Anxiety (NESDA) who had been followed up over two years and classified into three subgroups with distinct clinical trajectories. Combining a generative model of effective (directed) connectivity with support vector machines (SVMs), we could predict whether a given patient would experience chronic depression vs. fast remission with a balanced accuracy of 79%. Gradual improvement vs. fast remission could still be predicted above-chance, but less convincingly, with a balanced accuracy of 61%. Generative embedding outperformed classification based on conventional (descriptive) features, such as functional connectivity or local activation estimates, which were obtained from the same data and did not allow for above-chance classification accuracy. Furthermore, predictive performance of GE could be assigned to a specific network property: the trial-by-trial modulation of connections by emotional content. Given the limited sample size of our study, the present results are preliminary but may serve as proof-of-concept, illustrating the potential of GE for obtaining clinical predictions that are interpretable in terms of network mechanisms. Our findings suggest that abnormal dynamic changes of con
Published: 2020

17. Placebo Effects in the Neuroendocrine System: Conditioning of the Oxytocin Responses.

Author: Skvortsova, A, Veldhuijzen, DS, Pacheco-Lopez, G, Bakermans-Kranenburg, M, van IJzendoorn, M, Smeets, MAM, Wilderjans, TF, Dahan, A, van den Bergh, O, Chavannes, NH, van der Wee, NJA, Grewen, KM, van Middendorp, H, Evers, AWM, Skvortsova, A, Veldhuijzen, DS, Pacheco-Lopez, G, Bakermans-Kranenburg, M, van IJzendoorn, M, Smeets, MAM, Wilderjans, TF, Dahan, A, van den Bergh, O, Chavannes, NH, van der Wee, NJA, Grewen, KM, van Middendorp, H, and Evers, AWM
Abstract: OBJECTIVE: There is evidence that placebo effects may influence hormone secretion. However, few studies have examined placebo effects in the endocrine system, including oxytocin placebo effects. We studied whether it is possible to trigger oxytocin placebo effects using a classical conditioning paradigm. METHODS: Ninety-nine women were assigned to a conditioned, control, or drug control group. In the two-phase conditioning paradigm, participants in the conditioned and drug control groups received an oxytocin nasal spray combined with a distinctive smell (conditioned stimulus [CS]) for three acquisition days, whereas the control group received placebo spray. Subsequently, the conditioned and control groups received placebo spray with the CS and the drug control group received oxytocin spray for three evocation days. Salivary oxytocin was measured several times during each day. Pain sensitivity and facial evaluation tests previously used in oxytocin research were also administered. RESULTS: On evocation day 1, in the conditioned group, oxytocin significantly increased from baseline to 5 minutes after CS (B[slope] = 19.55, SE = 5.88, p < .001) and remained increased from 5 to 20 (B = -10.42, SE = 5.81, p = .071) and 50 minutes (B = -0.70, SE = 3.37, p = .84). On evocation day 2, a trend for increase in oxytocin was found at 5 minutes (B = 15.22, SE = 8.14, p = .062). No placebo effect was found on evocation day 3 (B = 3.57, SE = 3.26, p = .28). Neither exogenous nor conditioned oxytocin affected pain or facial tasks. CONCLUSIONS: Results indicate that oxytocin release can be conditioned and that this response extinguishes over time. Triggering hormonal release by placebo manipulation offers various clinical possibilities, such as enhancing effects of pharmacological treatments or reducing dosages of medications. TRIAL REGISTRATION: The study was registered as a clinical trial on www.trialregister.nl (number NTR5596).
Published: 2020

18. White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Author: van Velzen, LS, Kelly, S, Isaev, D, Aleman, A, Aftanas, L, Bauer, J, Baune, BT, Brak, I, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Danilenko, K, Dannlowski, U, Enneking, V, Filimonova, E, Foerster, K, Frodl, T, Gotlib, IH, Groenewold, NA, Grotegerd, D, Harris, MA, Hatton, SN, Hawkins, EL, Hickie, IB, Ho, TC, Jansen, A, Kircher, T, Klimes-Dougan, B, Kochunov, P, Krug, A, Lagopoulos, J, Lee, R, Lett, TA, Li, M, MacMaster, FP, Martin, NG, McIntosh, AM, McLellan, Q, Meinert, S, Nenadic, I, Osipov, E, Penninx, BWJH, Portella, MJ, Repple, J, Roos, A, Sacchet, MD, Saemann, PG, Schnell, K, Shen, X, Sim, K, Stein, DJ, van Tol, M-J, Tomyshev, AS, Tozzi, L, Veer, IM, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, van der Wee, NJA, van der Werff, SJA, Schreiner, MW, Whalley, HC, Wright, MJ, Yang, TT, Zhu, A, Veltman, DJ, Thompson, PM, Jahanshad, N, Schmaal, L, van Velzen, LS, Kelly, S, Isaev, D, Aleman, A, Aftanas, L, Bauer, J, Baune, BT, Brak, I, Carballedo, A, Connolly, CG, Couvy-Duchesne, B, Cullen, KR, Danilenko, K, Dannlowski, U, Enneking, V, Filimonova, E, Foerster, K, Frodl, T, Gotlib, IH, Groenewold, NA, Grotegerd, D, Harris, MA, Hatton, SN, Hawkins, EL, Hickie, IB, Ho, TC, Jansen, A, Kircher, T, Klimes-Dougan, B, Kochunov, P, Krug, A, Lagopoulos, J, Lee, R, Lett, TA, Li, M, MacMaster, FP, Martin, NG, McIntosh, AM, McLellan, Q, Meinert, S, Nenadic, I, Osipov, E, Penninx, BWJH, Portella, MJ, Repple, J, Roos, A, Sacchet, MD, Saemann, PG, Schnell, K, Shen, X, Sim, K, Stein, DJ, van Tol, M-J, Tomyshev, AS, Tozzi, L, Veer, IM, Vermeiren, R, Vives-Gilabert, Y, Walter, H, Walter, M, van der Wee, NJA, van der Werff, SJA, Schreiner, MW, Whalley, HC, Wright, MJ, Yang, TT, Zhu, A, Veltman, DJ, Thompson, PM, Jahanshad, N, and Schmaal, L
Abstract: Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.
Published: 2020

19. Decreased functional connectivity of the insula within the salience network as an indicator for prospective insufficient response to antidepressants.

Author: Geugies, H, Opmeer, EM, Marsman, JBC, Figueroa, CA, van Tol, MJ, Schmaal, L, van der Wee, NJA, Aleman, A, Penninx, BWJH, Veltman, DJ, Schoevers, RA, Ruhé, HG, Geugies, H, Opmeer, EM, Marsman, JBC, Figueroa, CA, van Tol, MJ, Schmaal, L, van der Wee, NJA, Aleman, A, Penninx, BWJH, Veltman, DJ, Schoevers, RA, and Ruhé, HG
Abstract: Insufficient response to treatment is the main cause of prolonged suffering from major depressive disorder (MDD). Early identification of insufficient response could result in faster and more targeted treatment strategies to reduce suffering. We therefore explored whether baseline alterations within and between resting state functional connectivity networks could serve as markers of insufficient response to antidepressant treatment in two years of follow-up. We selected MDD patients (N = 17) from the NEtherlands Study of Depression and Anxiety (NESDA), who received ≥ two antidepressants, indicative for insufficient response, during the two year follow-up, a group of MDD patients who received only one antidepressant (N = 32) and a healthy control group (N = 19) matched on clinical characteristics and demographics. An independent component analysis (ICA) of baseline resting-state scans was conducted after which functional connectivity within the components was compared between groups. We observed lower connectivity of the right insula within the salience network in the group with ≥ two antidepressants compared to the group with one antidepressant. No difference in connectivity was found between the patient groups and healthy control group. Given the suggested role of the right insula in switching between task-positive mode (activation during attention-demanding tasks) and task-negative mode (activation during the absence of any task), we explored whether right insula activation differed during switching between these two modes. We observed that in the ≥2 antidepressant group, the right insula was less active compared to the group with one antidepressant, when switching from task-positive to task-negative mode than the other way around. These findings imply that lower right insula connectivity within the salience network may serve as an indicator for prospective insufficient response to antidepressants. This result, supplemented by the diminished insula activation when
Published: 2019

20. Novel genetic loci associated with hippocampal volume

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

21. Childhood adversity impacts on brain subcortical structures relevant to depression

Author: Frodl, T, Janowitz, D, Schmaal, L, Tozzi, L, Dobrowolny, H, Stein, DJ, Veltman, DJ, Wittfeld, K, van Erp, TGM, Jahanshad, N, Block, A, Hegenscheid, K, Voelzke, H, Lagopoulos, J, Hatton, SN, Hickie, IB, Frey, EM, Carballedo, A, Brooks, SJ, Vuletic, D, Uhlmann, A, Veer, IM, Walter, H, Schnell, K, Grotegerd, D, Arolt, V, Kugel, H, Schramm, E, Konrad, C, Zurowski, B, Baune, BT, van der Wee, NJA, van Tol, M-J, Penninx, BWJH, Thompson, PM, Hibar, DP, Dannlowski, U, Grabe, HJ, Frodl, T, Janowitz, D, Schmaal, L, Tozzi, L, Dobrowolny, H, Stein, DJ, Veltman, DJ, Wittfeld, K, van Erp, TGM, Jahanshad, N, Block, A, Hegenscheid, K, Voelzke, H, Lagopoulos, J, Hatton, SN, Hickie, IB, Frey, EM, Carballedo, A, Brooks, SJ, Vuletic, D, Uhlmann, A, Veer, IM, Walter, H, Schnell, K, Grotegerd, D, Arolt, V, Kugel, H, Schramm, E, Konrad, C, Zurowski, B, Baune, BT, van der Wee, NJA, van Tol, M-J, Penninx, BWJH, Thompson, PM, Hibar, DP, Dannlowski, U, and Grabe, HJ
Abstract: Childhood adversity plays an important role for development of major depressive disorder (MDD). There are differences in subcortical brain structures between patients with MDD and healthy controls, but the specific impact of childhood adversity on such structures in MDD remains unclear. Thus, aim of the present study was to investigate whether childhood adversity is associated with subcortical volumes and how it interacts with a diagnosis of MDD and sex. Within the ENIGMA-MDD network, nine university partner sites, which assessed childhood adversity and magnetic resonance imaging in patients with MDD and controls, took part in the current joint mega-analysis. In this largest effort world-wide to identify subcortical brain structure differences related to childhood adversity, 3036 participants were analyzed for subcortical brain volumes using FreeSurfer. A significant interaction was evident between childhood adversity, MDD diagnosis, sex, and region. Increased exposure to childhood adversity was associated with smaller caudate volumes in females independent of MDD. All subcategories of childhood adversity were negatively associated with caudate volumes in females - in particular emotional neglect and physical neglect (independently from age, ICV, imaging site and MDD diagnosis). There was no interaction effect between childhood adversity and MDD diagnosis on subcortical brain volumes. Childhood adversity is one of the contributors to brain structural abnormalities. It is associated with subcortical brain abnormalities that are relevant to psychiatric disorders such as depression.
Published: 2017

22. Emotional face processing in adolescents with childhood sexual abuse-related posttraumatic stress disorder, internalizing disorders and healthy controls

Author: van Hoof, M J, van den Bulk, BG, Rombouts, S, Rinne-Albers, MAW, van der Wee, NJA, van IJzendoorn, Marinus, Vermeiren, R, van Hoof, M J, van den Bulk, BG, Rombouts, S, Rinne-Albers, MAW, van der Wee, NJA, van IJzendoorn, Marinus, and Vermeiren, R
Published: 2017

23. Effect of childhood maltreatment and brain-derived neurotrophic factor on brain morphology

Author: van Velzen, LS, Schmaal, L, Jansen, R, Milaneschi, Y, Opmeer, EM, Elzinga, BM, van der Wee, NJA, Veltman, DJ, Penninx, BWJH, van Velzen, LS, Schmaal, L, Jansen, R, Milaneschi, Y, Opmeer, EM, Elzinga, BM, van der Wee, NJA, Veltman, DJ, and Penninx, BWJH
Abstract: Childhood maltreatment (CM) has been associated with altered brain morphology, which may partly be due to a direct impact on neural growth, e.g. through the brain-derived neurotrophic factor (BDNF) pathway. Findings on CM, BDNF and brain volume are inconsistent and have never accounted for the entire BDNF pathway. We examined the effects of CM, BDNF (genotype, gene expression and protein level) and their interactions on hippocampus, amygdala and anterior cingulate cortex (ACC) morphology. Data were collected from patients with depression and/or an anxiety disorder and healthy subjects within the Netherlands Study of Depression and Anxiety (NESDA) (N = 289). CM was assessed using the Childhood Trauma Interview. BDNF Val66Met genotype, gene expression and serum protein levels were determined in blood and T1 MRI scans were acquired at 3T. Regional brain morphology was assessed using FreeSurfer. Covariate-adjusted linear regression analyses were performed. Amygdala volume was lower in maltreated individuals. This was more pronounced in maltreated met-allele carriers. The expected positive relationship between BDNF gene expression and volume of the amygdala is attenuated in maltreated subjects. Finally, decreased cortical thickness of the ACC was identified in maltreated subjects with the val/val genotype. CM was associated with altered brain morphology, partly in interaction with multiple levels of the BNDF pathway. Our results suggest that CM has different effects on brain morphology in met-carriers and val-homozygotes and that CM may disrupt the neuroprotective effect of BDNF.
Published: 2016

24. Predicting the Naturalistic Course of Major Depressive Disorder Using Clinical and Multimodal Neuroimaging Information: A Multivariate Pattern Recognition Study

Author: Schmaal, L, Marquand, AF, Rhebergen, D, van Tol, M-J, Ruhe, HG, van der Wee, NJA, Veltman, DJ, Penninx, BWJH, Schmaal, L, Marquand, AF, Rhebergen, D, van Tol, M-J, Ruhe, HG, van der Wee, NJA, Veltman, DJ, and Penninx, BWJH
Abstract: BACKGROUND: A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. METHODS: One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). RESULTS: Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. CONCLUSIONS: Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data.
Published: 2015

25. Routine outcome monitoring in psychiatric clinical practice: background, overview and implications for person-centered psychiatry

Author: Van Noorden, Martijn, primary, Van der Wee, NJA, additional, Zitman, FG, additional, and Giltay, EJ, additional
Published: 2013
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26. Treatment of Chronic Phantom Limb Pain Using a Trauma-Focused Psychological Approach

Author: de Roos, C, primary, Veenstra, AC, additional, de Jongh, A, additional, den Hollander-Gijsman, ME, additional, van der Wee, NJA, additional, Zitman, FG, additional, and van Rood, YR, additional
Published: 2010
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27. Reduced Functional Connectivity in Major Depression: a Whole Brain Study of Multiple Resting-State Networks

Author: Veer, IM, primary, Beckmann, CF, additional, Baerends, E, additional, van Tol, MJ, additional, Ferrarini, L, additional, Milles, JR, additional, Veltman, DJ, additional, Aleman, A, additional, van Buchem, MA, additional, van der Wee, NJA, additional, and Rombouts, SARB, additional
Published: 2009
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28. The Netherlands Study of Anxiety and Depression (NESDA): Amygdala response to facial expressions.

Author: Demenescu, LR, primary, Kortekaas, R, additional, Renken, R, additional, van Tol, MJ, additional, van der Wee, NJA, additional, Veltman, DJ, additional, den Boer, JA, additional, and Aleman, A, additional
Published: 2009
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29. Progression of cerebral white matter lesions is not associated with development of depressive symptoms in elderly subjects at risk of cardiovascular disease: The PROSPER Study.

Author: Versluis CE, van der Mast RC, van Buchem MA, Bollen ELE, Blauw GJ, Eekhof JAH, van der Wee NJA, de Craen AJM, and PROSPER Study
Abstract: BACKGROUND: Cerebral white matter hyperintensities on magnetic resonance imaging (MRI) scans have been associated with vascular disease and late-life depression, both in the general population and in psychiatric patients. Therefore, a cerebrovascular etiology for late-onset depression has been hypothesized. However, longitudinal studies on the causal role of white matter hyperintensities in the development of depressive symptoms in elderly adults are lacking. OBJECTIVE: To investigate the relation between white matter hyperintensities and depressive symptoms in elderly subjects at risk of cardiovascular disease. METHODS: In the Dutch sample of the PROSPER (PROspective Study of Pravastatine in the Elderly at Risk of cardiovascular disease) cohort, 527 non-demented elderly, all aged 70 years or older, received a cranial MRI scan and the 15-item Geriatric Depression Scale, at baseline and 33 months (SD 1.6) later. RESULTS: Presence of white matter hyperintensities at baseline was not related to baseline depressive symptoms nor to the development of depressive symptoms during follow-up. Moreover, no association was found between progression of white matter lesion volume and progression of depressive symptoms. CONCLUSION: This longitudinal study does not confirm the involvement of cerebrovascular disease expressed as MRI white matter hyperintensities in the development of depressive symptoms in elderly subjects. [ABSTRACT FROM AUTHOR]
Published: 2006
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30. Cortical and Subcortical Brain Alterations in Specific Phobia and Its Animal and Blood-Injection-Injury Subtypes: A Mega-Analysis From the ENIGMA Anxiety Working Group.

Author: Hilbert K, Boeken OJ, Langhammer T, Groenewold NA, Bas-Hoogendam JM, Aghajani M, Zugman A, Åhs F, Arolt V, Beesdo-Baum K, Björkstrand J, Blackford JU, Blanco-Hinojo L, Böhnlein J, Bülow R, Cano M, Cardoner N, Caseras X, Dannlowski U, Domschke K, Fehm L, Feola B, Fredrikson M, Goossens L, Grabe HJ, Grotegerd D, Gur RE, Hamm AO, Harrewijn A, Heinig I, Herrmann MJ, Hofmann D, Jackowski AP, Jansen A, Kaczkurkin AN, Kindt M, Kingsley EN, Kircher T, Klahn AL, Koelkebeck K, Krug A, Kugel H, Larsen B, Leehr EJ, Leonhardt L, Lotze M, Margraf J, Michałowski J, Muehlhan M, Nenadić I, Pan PM, Pauli P, Peñate W, Pittig A, Plag J, Pujol J, Richter J, Rivero FL, Salum GA, Satterthwaite TD, Schäfer A, Schäfer J, Schienle A, Schneider S, Schrammen E, Schruers K, Schulz SM, Seidl E, Stark RM, Stein F, Straube B, Straube T, Ströhle A, Suchan B, Thomopoulos SI, Ventura-Bort C, Visser R, Völzke H, Wabnegger A, Wannemüller A, Wendt J, Wiemer J, Wittchen HU, Wittfeld K, Wright B, Yang Y, Zilverstand A, Zwanzger P, Veltman DJ, Winkler AM, Pine DS, Jahanshad N, Thompson PM, Stein DJ, Van der Wee NJA, and Lueken U
Subjects: Humans, Adult, Female, Male, Child, Adolescent, Young Adult, Middle Aged, Brain pathology, Brain diagnostic imaging, Aged, Child, Preschool, Aged, 80 and over, Cerebral Cortex pathology, Cerebral Cortex diagnostic imaging, Animals, Case-Control Studies, Phobic Disorders pathology, Magnetic Resonance Imaging
Abstract: Objective: Specific phobia is a common anxiety disorder, but the literature on associated brain structure alterations exhibits substantial gaps. The ENIGMA Anxiety Working Group examined brain structure differences between individuals with specific phobias and healthy control subjects as well as between the animal and blood-injection-injury (BII) subtypes of specific phobia. Additionally, the authors investigated associations of brain structure with symptom severity and age (youths vs. adults)., Methods: Data sets from 31 original studies were combined to create a final sample with 1,452 participants with phobia and 2,991 healthy participants (62.7% female; ages 5-90). Imaging processing and quality control were performed using established ENIGMA protocols. Subcortical volumes as well as cortical surface area and thickness were examined in a preregistered analysis., Results: Compared with the healthy control group, the phobia group showed mostly smaller subcortical volumes, mixed surface differences, and larger cortical thickness across a substantial number of regions. The phobia subgroups also showed differences, including, as hypothesized, larger medial orbitofrontal cortex thickness in BII phobia (N=182) compared with animal phobia (N=739). All findings were driven by adult participants; no significant results were observed in children and adolescents., Conclusions: Brain alterations associated with specific phobia exceeded those of other anxiety disorders in comparable analyses in extent and effect size and were not limited to reductions in brain structure. Moreover, phenomenological differences between phobia subgroups were reflected in diverging neural underpinnings, including brain areas related to fear processing and higher cognitive processes. The findings implicate brain structure alterations in specific phobia, although subcortical alterations in particular may also relate to broader internalizing psychopathology.
Published: 2024
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31. A healthy dietary pattern is associated with microbiota diversity in recently diagnosed bipolar patients: The Bipolar Netherlands Cohort (BINCO) study.

Author: Riedinger MA, Mesbah R, Koenders M, Henderickx JGE, Smits WK, El Filali E, Geleijnse JM, van der Wee NJA, de Leeuw M, and Giltay EJ
Subjects: Humans, Female, Adult, Dietary Patterns, Netherlands, RNA, Ribosomal, 16S genetics, Diet, Bipolar Disorder, Gastrointestinal Microbiome genetics
Abstract: Background: Diet largely impacts the gut microbiota, and may affect mental and somatic health via the gut-brain axis. As such, the relationship between diet and the microbiota in Bipolar Disorder (BD) could be of importance, but has not been studied before. The aim was therefore to assess whether dietary quality is associated with the gut microbiota diversity in patients with recently diagnosed BD, and whether changes occur in dietary quality and microbiota diversity during their first year of treatment., Methods: Seventy recently (<1 year) diagnosed patients with BD were included in the "Bipolar Netherlands Cohort" (BINCO), and a total of 45 participants were assessed after one year. A 203-item Food Frequency Questionnaire (FFQ) data yielded the Dutch Healthy index (DHD-15), and the microbiota composition and diversity of fecal samples were characterized by 16S rRNA gene amplicon sequencing at baseline and 1-year follow-up. Associations and changes over time were analyzed using multivariate regression analyses and t-tests for paired samples., Results: Included patients had a mean age of 34.9 years (SD ± 11.2), and 58.6 % was female. Alpha diversity (Shannon diversity index), richness (Chao1 index) and evenness (Pielou's Evenness Index) were positively associated with the DHD-15 total score, after adjustment for sex, age and educational level (beta = 0.55; P < 0.001, beta = 0.39; P = 0.024, beta = 0.54; P = 0.001 respectively). The positive correlations were largely driven by the combined positive effect of fish, beans, fruits and nuts, and inverse correlations with alcohol and processed meats. No significant changes were found in DHD-15 total score, nor in microbiota diversity, richness and evenness indexes during one year follow-up and regular treatment., Conclusion: A healthy and varied diet is associated with the diversity of the microbiota in BD patients. Its potential consequences for maintaining mood stability and overall health should be studied further., Competing Interests: Declaration of competing interest All authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)
Published: 2024
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32. Dynamic reconfigurations of brain networks in depressive and anxiety disorders: The influence of antidepressants.

Author: Broeders TAA, Linsen F, Louter TS, Nawijn L, Penninx BWJH, van Tol MJ, van der Wee NJA, Veltman DJ, van der Werf YD, Schoonheim MM, and Vinkers CH
Subjects: Adult, Humans, Anxiety Disorders drug therapy, Anxiety Disorders epidemiology, Antidepressive Agents pharmacology, Antidepressive Agents therapeutic use, Brain, Comorbidity, Depressive Disorder, Major complications, Depressive Disorder, Major drug therapy, Depressive Disorder, Major epidemiology
Abstract: Major Depressive Disorder (MDD) and anxiety disorders are highly comorbid recurrent psychiatric disorders. Reduced dynamic reconfiguration of brain regions across subnetworks may play a critical role underlying these deficits, with indications of normalization after treatment with antidepressants. This study investigated dynamic reconfigurations in controls and individuals with a current MDD and/or anxiety disorder including antidepressant users and non-users in a large sample (N = 207) of adults. We quantified the number of subnetworks a region switched to (promiscuity) as well as the total number of switches (flexibility). Average whole-brain (i.e., global) values and subnetwork-specific values were compared between diagnosis and antidepressant groups. No differences in reconfiguration dynamics were found between individuals with a current MDD (N = 49), anxiety disorder (N = 46), comorbid MDD and anxiety disorder (N = 55), or controls (N = 57). Global and sensorimotor network (SMN) promiscuity and flexibility were higher in antidepressant users (N = 49, regardless of diagnosis) compared to non-users (N = 101) and controls. Dynamic reconfigurations were considerably higher in antidepressant users relative to non-users and controls, but not significantly altered in individuals with a MDD and/or anxiety disorder. The increase in antidepressant users was apparent across the whole brain and in the SMN when investigating subnetworks. These findings help disentangle how antidepressants improve symptoms., Competing Interests: Declaration of competing interest All authors report no competing interests., (Copyright © 2024. Published by Elsevier B.V.)
Published: 2024
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33. Multi-site benchmark classification of major depressive disorder using machine learning on cortical and subcortical measures.

Author: Belov V, Erwin-Grabner T, Aghajani M, Aleman A, Amod AR, Basgoze Z, Benedetti F, Besteher B, Bülow R, Ching CRK, Connolly CG, Cullen K, Davey CG, Dima D, Dols A, Evans JW, Fu CHY, Gonul AS, Gotlib IH, Grabe HJ, Groenewold N, Hamilton JP, Harrison BJ, Ho TC, Mwangi B, Jaworska N, Jahanshad N, Klimes-Dougan B, Koopowitz SM, Lancaster T, Li M, Linden DEJ, MacMaster FP, Mehler DMA, Melloni E, Mueller BA, Ojha A, Oudega ML, Penninx BWJH, Poletti S, Pomarol-Clotet E, Portella MJ, Pozzi E, Reneman L, Sacchet MD, Sämann PG, Schrantee A, Sim K, Soares JC, Stein DJ, Thomopoulos SI, Uyar-Demir A, van der Wee NJA, van der Werff SJA, Völzke H, Whittle S, Wittfeld K, Wright MJ, Wu MJ, Yang TT, Zarate C, Veltman DJ, Schmaal L, Thompson PM, and Goya-Maldonado R
Subjects: Humans, Benchmarking, Brain diagnostic imaging, Neuroimaging methods, Machine Learning, Magnetic Resonance Imaging methods, Depressive Disorder, Major diagnostic imaging, Depressive Disorder, Major psychology
Abstract: Machine learning (ML) techniques have gained popularity in the neuroimaging field due to their potential for classifying neuropsychiatric disorders. However, the diagnostic predictive power of the existing algorithms has been limited by small sample sizes, lack of representativeness, data leakage, and/or overfitting. Here, we overcome these limitations with the largest multi-site sample size to date (N = 5365) to provide a generalizable ML classification benchmark of major depressive disorder (MDD) using shallow linear and non-linear models. Leveraging brain measures from standardized ENIGMA analysis pipelines in FreeSurfer, we were able to classify MDD versus healthy controls (HC) with a balanced accuracy of around 62%. But after harmonizing the data, e.g., using ComBat, the balanced accuracy dropped to approximately 52%. Accuracy results close to random chance levels were also observed in stratified groups according to age of onset, antidepressant use, number of episodes and sex. Future studies incorporating higher dimensional brain imaging/phenotype features, and/or using more advanced machine and deep learning methods may yield more encouraging prospects., (© 2024. The Author(s).)
Published: 2024
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34. Neuroimaging-based classification of PTSD using data-driven computational approaches: A multisite big data study from the ENIGMA-PGC PTSD consortium.

Author: Zhu X, Kim Y, Ravid O, He X, Suarez-Jimenez B, Zilcha-Mano S, Lazarov A, Lee S, Abdallah CG, Angstadt M, Averill CL, Baird CL, Baugh LA, Blackford JU, Bomyea J, Bruce SE, Bryant RA, Cao Z, Choi K, Cisler J, Cotton AS, Daniels JK, Davenport ND, Davidson RJ, DeBellis MD, Dennis EL, Densmore M, deRoon-Cassini T, Disner SG, Hage WE, Etkin A, Fani N, Fercho KA, Fitzgerald J, Forster GL, Frijling JL, Geuze E, Gonenc A, Gordon EM, Gruber S, Grupe DW, Guenette JP, Haswell CC, Herringa RJ, Herzog J, Hofmann DB, Hosseini B, Hudson AR, Huggins AA, Ipser JC, Jahanshad N, Jia-Richards M, Jovanovic T, Kaufman ML, Kennis M, King A, Kinzel P, Koch SBJ, Koerte IK, Koopowitz SM, Korgaonkar MS, Krystal JH, Lanius R, Larson CL, Lebois LAM, Li G, Liberzon I, Lu GM, Luo Y, Magnotta VA, Manthey A, Maron-Katz A, May G, McLaughlin K, Mueller SC, Nawijn L, Nelson SM, Neufeld RWJ, Nitschke JB, O'Leary EM, Olatunji BO, Olff M, Peverill M, Phan KL, Qi R, Quidé Y, Rektor I, Ressler K, Riha P, Ross M, Rosso IM, Salminen LE, Sambrook K, Schmahl C, Shenton ME, Sheridan M, Shih C, Sicorello M, Sierk A, Simmons AN, Simons RM, Simons JS, Sponheim SR, Stein MB, Stein DJ, Stevens JS, Straube T, Sun D, Théberge J, Thompson PM, Thomopoulos SI, van der Wee NJA, van der Werff SJA, van Erp TGM, van Rooij SJH, van Zuiden M, Varkevisser T, Veltman DJ, Vermeiren RRJM, Walter H, Wang L, Wang X, Weis C, Winternitz S, Xie H, Zhu Y, Wall M, Neria Y, and Morey RA
Subjects: Humans, Reproducibility of Results, Big Data, Neuroimaging, Magnetic Resonance Imaging methods, Brain diagnostic imaging, Stress Disorders, Post-Traumatic diagnostic imaging
Abstract: Background: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group., Methods: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality., Results: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60 % test AUC for s-MRI, 59 % for rs-fMRI and 56 % for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75 % AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance., Conclusion: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable., Competing Interests: Declaration of Competing Interest Dr. Thompson received partial grant support from Biogen, Inc., and Amazon, Inc., for work unrelated to the current study; Dr. Lebois reports unpaid membership on the Scientific Committee for International Society for the Study of Trauma and Dissociation (ISSTD), grant support from the National Institute of Mental Health, K01 MH118467 and the Julia Kasparian Fund for Neuroscience Research, McLean Hospital. Dr. Lebois also reports spousal IP payments from Vanderbilt University for technology licensed to Acadia Pharmaceuticals unrelated to the present work. ISSTD and NIMH were not involved in the analysis or preparation of the manuscript; Dr. Etkin reports salary and equity from Alto Neuroscience, equity from Mindstrong Health and Akili Interactive. Other authors have no conflicts of interest to declare., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)
Published: 2023
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35. Development of a body dysmorphic disorder screener for DSM-5 (BDDS-5).

Author: Van Rood YR, Wyk van N, Böhringer S, van der Wee NJA, Möllmann A, and Dingemans AE
Subjects: Humans, Diagnostic and Statistical Manual of Mental Disorders, Severity of Illness Index, Psychometrics, Body Dysmorphic Disorders diagnosis, Body Dysmorphic Disorders psychology, Feeding and Eating Disorders diagnosis
Abstract: Early identification of individuals with Body dysmorphic disorder (BDD) is essential to direct them to appropriate care and to reduce the chance of developing or maintaining comorbid psychiatric disorders (like an eating disorder (ED)). The present study aimed to develop a simple screener, the Body Dysmorphic Disorder Screener for DSM-5 (BDDS-5), to overcome existing screeners' limitations and test its psychometric properties. The BDDS-5 consists of 12 statements with dichotomous answer options. Specific attention is paid to the readability of the screener for those with lower reading skills. Additional eating disorder screening questions (S section) were added to investigate whether these questions are necessary for detecting potential BDD cases. Finally, the factor structure, internal consistency, and validity of the BDDS-5 were examined within populations with a high risk of screening positive for BDD or ED. Principal axis factor analysis showed that two factors accounted for 63.5% of the variance. The factor analysis was based on polychoric correlation. Based on the BDDS-5, 33 persons (14% of N = 235) were screened as likely BDD cases. Nineteen persons were excluded as potential BDD cases based on the eating disorder related question (question D). Based on the S-section, this turned out to be largely correct for the majority, however, in 8% (n = 4) of the cases BDD was probably missed. The convergent validity appeared to be high (r > 0.80) with three other BDD measures. The BDDS-5 is a valid and widely applicable screener for BDD that may help in the early detection of BDD. The BDDS-5 uses simple wording and is thus suitable for people 8 years and older., Competing Interests: Declaration of Competing Interest The authors declare no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)
Published: 2023
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36. The role of the circadian system in the etiology of depression.

Author: de Leeuw M, Verhoeve SI, van der Wee NJA, van Hemert AM, Vreugdenhil E, and Coomans CP
Subjects: Humans, Depression etiology, Hydrocortisone, Circadian Rhythm physiology, Sleep Disorders, Circadian Rhythm etiology, Sleep Disorders, Circadian Rhythm therapy, Circadian Clocks physiology
Abstract: Circadian rhythms have evolved in almost all organisms enabling them to anticipate alternating changes in the environment. As a consequence, the circadian clock controls a broad range of bodily functions including appetite, sleep, activity and cortisol levels. The circadian clock synchronizes itself to the external world mainly by environmental light cues and can be disturbed by a variety of factors, including shift-work, jet-lag, stress, ageing and artificial light at night. Interestingly, mood has also been shown to follow a diurnal rhythm. Moreover, circadian disruption has been associated with various mood disorders and patients suffering from depression have irregular biological rhythms in sleep, appetite, activity and cortisol levels suggesting that circadian rhythmicity is crucially involved in the etiology and pathophysiology of depression. The aim of the present review is to give an overview and discuss recent findings in both humans and rodents linking a disturbed circadian rhythm to depression. Understanding the relation between a disturbed circadian rhythm and the etiology of depression may lead to novel therapeutic and preventative strategies., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)
Published: 2023
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37. Lithium in bipolar depression: A review of the evidence.

Author: Riedinger MA, van der Wee NJA, Giltay EJ, and de Leeuw M
Subjects: Humans, Lithium therapeutic use, Mania drug therapy, Lithium Compounds therapeutic use, Bipolar Disorder drug therapy
Abstract: Background: Lithium is widely used as treatment of acute mania and as prophylactic therapy for bipolar disorder. International and national guidelines also consider lithium as a possible treatment of acute bipolar depression. Research on the use of lithium in bipolar depression, however, seems to be limited compared to the data available for its efficacy in the other phases of bipolar disorder., Objective: To provide a systematic review of the evidence for lithium in the treatment of acute bipolar depression and provide directions for further research., Method: A systematic review of clinical studies investigating the use of lithium in bipolar depression was performed using preferred reporting items for systematic reviews and meta-analyses guidelines in Pubmed, Embase and Psychinfo using the medical subjects headings and free text terms "lithium," "bipolar depression," "dosage," "serum concentration" and "bipolar disorders.", Results: This review included 15 studies with a total of 1222 patients, between the age of 18 and 65, suffering from bipolar depression of which 464 were treated with lithium. There are currently only limited and low-quality data on the efficacy of lithium as a treatment of bipolar depression. It appears that there have been no placebo controlled randomized controlled trials with lithium concentrations that are considered to be therapeutic. The older studies suffered from limitations such as small sample sizes, insufficient treatment lengths, and insufficient monitoring of serum concentrations., Conclusion: In contrast to data for the treatment of mania and prophylaxis, robust data on the efficacy of lithium in bipolar depression is currently lacking, making it impossible to make conclusions regarding efficacy or inefficacy, for which further research is needed., (© 2023 The Authors. Human Psychopharmacology: Clinical and Experimental published by John Wiley & Sons Ltd.)
Published: 2023
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38. Association Between the Fronto-Limbic Network and Cognitive and Emotional Functioning in Individuals With Bipolar Disorder: A Systematic Review and Meta-analysis.

Author: Mesbah R, Koenders MA, van der Wee NJA, Giltay EJ, van Hemert AM, and de Leeuw M
Subjects: Adult, Humans, Female, Male, Brain, Emotions physiology, Prefrontal Cortex diagnostic imaging, Magnetic Resonance Imaging methods, Cognition physiology, Bipolar Disorder psychology
Abstract: Importance: Individuals with bipolar disorder (BD) experience cognitive and emotional dysfunctions. Various brain circuits are implicated in BD but have not been investigated in a meta-analysis of functional magnetic resonance imaging (fMRI) studies., Objective: To investigate the brain functioning of individuals with BD compared with healthy control individuals in the domains of emotion processing, reward processing, and working memory., Data Sources: All fMRI experiments on BD published before March 2020, as identified in a literature search of PubMed, Embase, Web of Science, Cochrane Library, PsycInfo, Emcare, Academic Search Premier, and ScienceDirect. The literature search was conducted on February 21, 2017, and March 2, 2020, and data were analyzed from January 2021 to January 2022., Study Selection: fMRI experiments comparing adult individuals with BD and healthy control individuals were selected if they reported whole-brain results, including a task assessing at least 1 of the domains. In total, 2320 studies were screened, and 253 full-text articles were evaluated., Data Extraction and Synthesis: A total of 49 studies were included after selection procedure. Coordinates reporting significant activation differences between individuals with BD and healthy control individuals were extracted. Differences in brain region activity were tested using the activation likelihood estimation method., Main Outcomes and Measures: A whole-brain meta-analysis evaluated whether reported differences in brain activation in response to stimuli in 3 cognitive domains between individuals with BD and healthy control individuals were different., Results: The study population included 999 individuals with BD (551 [55.2%] female) and 1027 healthy control individuals (532 [51.8%] female). Compared with healthy control individuals, individuals with BD showed amygdala and hippocampal hyperactivity and hypoactivation in the inferior frontal gyrus during emotion processing (20 studies; 324 individuals with BD and 369 healthy control individuals), hyperactivation in the orbitofrontal cortex during reward processing (9 studies; 195 individuals with BD and 213 healthy control individuals), and hyperactivation in the ventromedial prefrontal cortex and subgenual anterior cingulate cortex during working memory (20 studies; 530 individuals with BD and 417 healthy control individuals). Limbic hyperactivation was only found during euthymia in the emotion and reward processing domains; abnormalities in frontal cortex activity were also found in individuals with BD with mania and depression., Conclusions and Relevance: This systematic review and meta-analysis revealed evidence for activity disturbances in key brain areas involved in cognitive and emotion processing in individuals with BD. Most of the regions are part of the fronto-limbic network. The results suggest that aberrations in the fronto-limbic network, present in both euthymic and symptomatic individuals, may be underlying cognitive and emotional dysfunctions in BD.
Published: 2023
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39. Volume of subcortical brain regions in social anxiety disorder: mega-analytic results from 37 samples in the ENIGMA-Anxiety Working Group.

Author: Groenewold NA, Bas-Hoogendam JM, Amod AR, Laansma MA, Van Velzen LS, Aghajani M, Hilbert K, Oh H, Salas R, Jackowski AP, Pan PM, Salum GA, Blair JR, Blair KS, Hirsch J, Pantazatos SP, Schneier FR, Talati A, Roelofs K, Volman I, Blanco-Hinojo L, Cardoner N, Pujol J, Beesdo-Baum K, Ching CRK, Thomopoulos SI, Jansen A, Kircher T, Krug A, Nenadić I, Stein F, Dannlowski U, Grotegerd D, Lemke H, Meinert S, Winter A, Erb M, Kreifelts B, Gong Q, Lui S, Zhu F, Mwangi B, Soares JC, Wu MJ, Bayram A, Canli M, Tükel R, Westenberg PM, Heeren A, Cremers HR, Hofmann D, Straube T, Doruyter AGG, Lochner C, Peterburs J, Van Tol MJ, Gur RE, Kaczkurkin AN, Larsen B, Satterthwaite TD, Filippi CA, Gold AL, Harrewijn A, Zugman A, Bülow R, Grabe HJ, Völzke H, Wittfeld K, Böhnlein J, Dohm K, Kugel H, Schrammen E, Zwanzger P, Leehr EJ, Sindermann L, Ball TM, Fonzo GA, Paulus MP, Simmons A, Stein MB, Klumpp H, Phan KL, Furmark T, Månsson KNT, Manzouri A, Avery SN, Blackford JU, Clauss JA, Feola B, Harper JC, Sylvester CM, Lueken U, Veltman DJ, Winkler AM, Jahanshad N, Pine DS, Thompson PM, Stein DJ, and Van der Wee NJA
Subjects: Adult, Adolescent, Humans, Magnetic Resonance Imaging methods, Brain, Anxiety, Neuroimaging methods, Phobia, Social
Abstract: There is limited convergence in neuroimaging investigations into volumes of subcortical brain regions in social anxiety disorder (SAD). The inconsistent findings may arise from variations in methodological approaches across studies, including sample selection based on age and clinical characteristics. The ENIGMA-Anxiety Working Group initiated a global mega-analysis to determine whether differences in subcortical volumes can be detected in adults and adolescents with SAD relative to healthy controls. Volumetric data from 37 international samples with 1115 SAD patients and 2775 controls were obtained from ENIGMA-standardized protocols for image segmentation and quality assurance. Linear mixed-effects analyses were adjusted for comparisons across seven subcortical regions in each hemisphere using family-wise error (FWE)-correction. Mixed-effects d effect sizes were calculated. In the full sample, SAD patients showed smaller bilateral putamen volume than controls (left: d = -0.077, p FWE = 0.037; right: d = -0.104, p FWE = 0.001), and a significant interaction between SAD and age was found for the left putamen (r = -0.034, p FWE = 0.045). Smaller bilateral putamen volumes (left: d = -0.141, p FWE < 0.001; right: d = -0.158, p FWE < 0.001) and larger bilateral pallidum volumes (left: d = 0.129, p FWE = 0.006; right: d = 0.099, p FWE = 0.046) were detected in adult SAD patients relative to controls, but no volumetric differences were apparent in adolescent SAD patients relative to controls. Comorbid anxiety disorders and age of SAD onset were additional determinants of SAD-related volumetric differences in subcortical regions. To conclude, subtle volumetric alterations in subcortical regions in SAD were detected. Heterogeneity in age and clinical characteristics may partly explain inconsistencies in previous findings. The association between alterations in subcortical volumes and SAD illness progression deserves further investigation, especially from adolescence into adulthood., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)
Published: 2023
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40. Clinical outcome in patients with suspected inflammatory neuropsychiatric lupus treated with immunosuppression: an observational cohort study.

Author: Monahan RC, Beaart-van de Voorde LJJ, Fronczek R, de Bresser J, Eikenboom J, Kloppenburg M, Middelkoop HAM, Terwindt GM, van der Wee NJA, Huizinga TWJ, and Steup-Beekman GM
Subjects: Humans, Cohort Studies, Immunosuppressive Agents therapeutic use, Immunosuppression Therapy, Lupus Vasculitis, Central Nervous System diagnosis, Lupus Vasculitis, Central Nervous System drug therapy, Lupus Erythematosus, Systemic
Abstract: Background: The short-term and long-term outcome of inflammatory neuropsychiatric SLE (NPSLE) with immunosuppressive treatment is largely unknown. We used clinical data from our tertiary referral centre for NPSLE to investigate the type of inflammatory NPSLE manifestations, type of immunosuppressive treatment prescribed for these manifestations and clinical outcomes., Methods: All patients with SLE visiting the Leiden University Medical Centre NPSLE clinic between 2007 and 2021 receiving immunosuppressive therapy for neuropsychiatric symptoms were included. Clinical, immunological and radiological information was collected in as standardised way during a 1-day multidisciplinary assessment. In a multidisciplinary consensus meeting, the presence of NPSLE and the type of NPSLE manifestations and treatment were determined. For this study, short-term (0-6 months) and long-term outcomes (7-24 months) of the NP symptoms were assessed by two independent readers and scored on a 7-point Likert scale, ranging from death to resolved., Results: In total, 95 out of 398 (24%) patients visiting the NPSLE clinic between 2007 and 2021 received any form of immunosuppressive treatment for 101 separate NPSLE events. The most common NP manifestation was cognitive dysfunction (50%) as identified by formal cognitive assessment, often present in combination with other NPSLE manifestations. Treatment modalities were induction (24%), induction and maintenance (73%) and other therapy (3%). The treatments mostly consisted of (combinations of) prednisone (97%), methylprednisolone (53%), azathioprine (generally 2 mg/kg daily) (49%) and cyclophosphamide (generally induction 750 mg/m 2 every 4 weeks for 24 weeks or 500mg biweekly for 12 weeks) (42%). Short-term outcome showed improvement on the Likert scale in 73% (improved: 22%, much improved: 29%, resolved: 22%), no change in 21% and worsening in 6% of patients. Long-term outcome was available for 78 out of 101 events and showed improvement in 70% (improved: 14%, much improved: 28%, resolved: 28%), no change in 17%, worsening in 10% and death in 3% of patients (none directly NPSLE-related)., Conclusion: The outcome of inflammatory NPSLE after immunosuppressive treatment is generally good, with improvement of neuropsychiatric symptoms occuring in approximately 70% of events., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)
Published: 2023
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41. PTSD Symptom dynamics after the great east japan earthquake: mapping the temporal structure using Dynamic Time Warping.

Author: van der Does FHS, Nagamine M, van der Wee NJA, Chiba T, Edo N, Kitano M, Vermetten E, and Giltay EJ
Subjects: Humans, Japan epidemiology, Cross-Sectional Studies, Syndrome, Earthquakes, Stress Disorders, Post-Traumatic diagnosis
Abstract: Background: After the Great East Japan Earthquake [GEJE], approximately 70,000 Japan Ground Self Defense Force [JGSDF] personnel were deployed, risking Post-Traumatic Stress Disorder [PTSD]. The network approach to psychopathology suggests that symptoms may cause and exacerbate each other, resulting in the emergence and maintenance of disorders, including PTSD. It is therefore important to further explore the temporal interplay between symptoms. Most studies assessing the factor structure of the Impact of Event Scale-Revised [IES-R] have used cross-sectional designs. In this study, the structure of the IES-R was re-evaluated while incorporating the temporal interplay between symptoms. Methods: Using Dynamic Time Warping [DTW] the distances between PTSD symptoms on the IES-R were modelled in 1120 JGSDF personnel. Highly correlated symptoms were clustered at the group level using Distatis three-way principal component analyses of the distance matrices. The resulting clusters were compared to the original three subscales of the IES-R using a Confirmatory Factor Analysis (CFA). Results: The DTW analysis yielded four symptom clusters: Intrusion (five items), Hyperarousal (six items), Avoidance (six items), and Dissociation (five items). CFA yielded better fit estimates for this four-factor solution (RMSEA = 0.084, CFI = 0.918, TLI = 0.906), compared to the original three subscales of the IES-R (RMSEA = 0.103, CFI = 0.873, TLI = 0.858). Conclusions: DTW offers a new method of modelling the temporal relationships between symptoms. It yielded four IES-R symptom clusters, which may facilitate understanding of PTSD as a complex dynamic system.
Published: 2023
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42. Functional MRI correlates of emotion regulation in major depressive disorder related to depressive disease load measured over nine years.

Author: van Kleef RS, Müller A, van Velzen LS, Marie Bas-Hoogendam J, van der Wee NJA, Schmaal L, Veltman DJ, Rive MM, Ruhé HG, Marsman JC, and van Tol MJ
Subjects: Humans, Brain diagnostic imaging, Emotions physiology, Magnetic Resonance Imaging methods, Depressive Disorder, Major diagnostic imaging, Emotional Regulation
Abstract: Major Depressive Disorder (MDD) often is a recurrent and chronic disorder. We investigated the neurocognitive underpinnings of the incremental risk for poor disease course by exploring relations between enduring depression and brain functioning during regulation of negative and positive emotions using cognitive reappraisal. We used fMRI-data from the longitudinal Netherlands Study of Depression and Anxiety acquired during an emotion regulation task in 77 individuals with MDD. Task-related brain activity was related to disease load, calculated from presence and severity of depression in the preceding nine years. Additionally, we explored task related brain-connectivity. Brain functioning in individuals with MDD was further compared to 35 controls to explore overlap between load-effects and general effects related to MDD history/presence. Disease load was not associated with changes in affect or with brain activity, but with connectivity between areas essential for processing, integrating and regulating emotional information during downregulation of negative emotions. Results did not overlap with general MDD-effects. Instead, MDD was generally associated with lower parietal activity during downregulation of negative emotions. During upregulation of positive emotions, disease load was related to connectivity between limbic regions (although driven by symptomatic state), and connectivity between frontal, insular and thalamic regions was lower in MDD (vs controls). Results suggest that previous depressive load relates to brain connectivity in relevant networks during downregulation of negative emotions. These abnormalities do not overlap with disease-general abnormalities and could foster an incremental vulnerability to recurrence or chronicity of MDD. Therefore, optimizing emotion regulation is a promising therapeutic target for improving long-term MDD course., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)
Published: 2023
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43. Structural brain alterations associated with suicidal thoughts and behaviors in young people: results from 21 international studies from the ENIGMA Suicidal Thoughts and Behaviours consortium.

Author: van Velzen LS, Dauvermann MR, Colic L, Villa LM, Savage HS, Toenders YJ, Zhu AH, Bright JK, Campos AI, Salminen LE, Ambrogi S, Ayesa-Arriola R, Banaj N, Başgöze Z, Bauer J, Blair K, Blair RJ, Brosch K, Cheng Y, Colle R, Connolly CG, Corruble E, Couvy-Duchesne B, Crespo-Facorro B, Cullen KR, Dannlowski U, Davey CG, Dohm K, Fullerton JM, Gonul AS, Gotlib IH, Grotegerd D, Hahn T, Harrison BJ, He M, Hickie IB, Ho TC, Iorfino F, Jansen A, Jollant F, Kircher T, Klimes-Dougan B, Klug M, Leehr EJ, Lippard ETC, McLaughlin KA, Meinert S, Miller AB, Mitchell PB, Mwangi B, Nenadić I, Ojha A, Overs BJ, Pfarr JK, Piras F, Ringwald KG, Roberts G, Romer G, Sanches M, Sheridan MA, Soares JC, Spalletta G, Stein F, Teresi GI, Tordesillas-Gutiérrez D, Uyar-Demir A, van der Wee NJA, van der Werff SJ, Vermeiren RRJM, Winter A, Wu MJ, Yang TT, Thompson PM, Rentería ME, Jahanshad N, Blumberg HP, van Harmelen AL, and Schmaal L
Subjects: Adolescent, Humans, Brain, Neuroimaging methods, Mood Disorders, Suicidal Ideation, Suicide, Attempted
Abstract: Identifying brain alterations associated with suicidal thoughts and behaviors (STBs) in young people is critical to understanding their development and improving early intervention and prevention. The ENIGMA Suicidal Thoughts and Behaviours (ENIGMA-STB) consortium analyzed neuroimaging data harmonized across sites to examine brain morphology associated with STBs in youth. We performed analyses in three separate stages, in samples ranging from most to least homogeneous in terms of suicide assessment instrument and mental disorder. First, in a sample of 577 young people with mood disorders, in which STBs were assessed with the Columbia Suicide Severity Rating Scale (C-SSRS). Second, in a sample of young people with mood disorders, in which STB were assessed using different instruments, MRI metrics were compared among healthy controls without STBs (HC; N = 519), clinical controls with a mood disorder but without STBs (CC; N = 246) and young people with current suicidal ideation (N = 223). In separate analyses, MRI metrics were compared among HCs (N = 253), CCs (N = 217), and suicide attempters (N = 64). Third, in a larger transdiagnostic sample with various assessment instruments (HC = 606; CC = 419; Ideation = 289; HC = 253; CC = 432; Attempt=91). In the homogeneous C-SSRS sample, surface area of the frontal pole was lower in young people with mood disorders and a history of actual suicide attempts (N = 163) than those without a lifetime suicide attempt (N = 323; FDR-p = 0.035, Cohen's d = 0.34). No associations with suicidal ideation were found. When examining more heterogeneous samples, we did not observe significant associations. Lower frontal pole surface area may represent a vulnerability for a (non-interrupted and non-aborted) suicide attempt; however, more research is needed to understand the nature of its relationship to suicide risk., (© 2022. Crown.)
Published: 2022
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44. The association between clinical and biological characteristics of depression and structural brain alterations.

Author: Toenders YJ, Schmaal L, Nawijn L, Han LKM, Binnewies J, van der Wee NJA, van Tol MJ, Veltman DJ, Milaneschi Y, Lamers F, and Penninx BWJH
Subjects: Anxiety Disorders, Brain diagnostic imaging, Brain metabolism, Depression, Gyrus Cinguli metabolism, Humans, Depressive Disorder, Major diagnosis
Abstract: Background: Structural brain alterations are observed in major depressive disorder (MDD). However, MDD is a highly heterogeneous disorder and specific clinical or biological characteristics of depression might relate to specific structural brain alterations. Clinical symptom subtypes of depression, as well as immuno-metabolic dysregulation associated with subtypes of depression, have been associated with brain alterations. Therefore, we examined if specific clinical and biological characteristics of depression show different brain alterations compared to overall depression., Method: Individuals with and without depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA) (328 participants from three timepoints leading to 541 observations) and the Mood Treatment with Antidepressants or Running (MOTAR) study (123 baseline participants) were included. Symptom profiles (atypical energy-related profile, melancholic profile and depression severity) and biological indices (inflammatory, metabolic syndrome, and immuno-metabolic indices) were created. The associations of the clinical and biological profiles with depression-related structural brain measures (anterior cingulate cortex [ACC], orbitofrontal cortex, insula, and nucleus accumbens) were examined dimensionally in both studies and meta-analysed., Results: Depression severity was negatively associated with rostral ACC thickness (B = -0.55, p FDR = 0.03), and melancholic symptoms were negatively associated with caudal ACC thickness (B = -0.42, p FDR = 0.03). The atypical energy-related symptom profile and immuno-metabolic indices did not show a consistent association with structural brain measures across studies., Conclusion: Overall depression- and melancholic symptom severity showed a dose-response relationship with reduced ACC thickness. No associations between immuno-metabolic dysregulation and structural brain alterations were found, suggesting that although both are associated with depression, distinct mechanisms may be involved., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)
Published: 2022
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45. Structural Brain Correlates of Childhood Inhibited Temperament: An ENIGMA-Anxiety Mega-analysis.

Author: Bas-Hoogendam JM, Bernstein R, Benson BE, Buss KA, Gunther KE, Pérez-Edgar K, Salum GA, Jackowski AP, Bressan RA, Zugman A, Degnan KA, Filippi CA, Fox NA, Henderson HA, Tang A, Zeytinoglu S, Harrewijn A, Hillegers MHJ, White T, van IJzendoorn MH, Schwartz CE, Felicione JM, DeYoung KA, Shackman AJ, Smith JF, Tillman RM, van den Berg YHM, Cillessen AHN, Roelofs K, Tyborowska A, Hill SY, Battaglia M, Tettamanti M, Dougherty LR, Jin J, Klein DN, Leung HC, Avery SN, Blackford JU, Clauss JA, Hayden EP, Liu P, Vandermeer MRJ, Goldsmith HH, Planalp EM, Nichols TE, Thompson PM, Westenberg PM, van der Wee NJA, Groenewold NA, Stein DJ, Winkler AM, and Pine DS
Subjects: Anxiety Disorders, Brain physiology, Child, Preschool, Humans, Retrospective Studies, Anxiety psychology, Temperament physiology
Abstract: Temperament involves stable behavioral and emotional tendencies that differ between individuals, which can be first observed in infancy or early childhood and relate to behavior in many contexts and over many years. 1 One of the most rigorously characterized temperament classifications relates to the tendency of individuals to avoid the unfamiliar and to withdraw from unfamiliar people, objects, and unexpected events. This temperament is referred to as behavioral inhibition or inhibited temperament (IT). 2 IT is a moderately heritable trait 1 that can be measured in multiple species. 3 In humans, levels of IT can be quantified from the first year of life through direct behavioral observations or reports by caregivers or teachers. Similar approaches as well as self-report questionnaires on current and/or retrospective levels of IT 1 can be used later in life., (Copyright © 2022 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.)
Published: 2022
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46. Exploring the course of adolescent anxiety and depression: associations with white matter tract microstructure.

Author: Roelofs EF, Bas-Hoogendam JM, van der Werff SJA, Valstar SD, van der Wee NJA, and Vermeiren RRJM
Subjects: Adolescent, Anisotropy, Anxiety diagnostic imaging, Brain diagnostic imaging, Child, Cross-Sectional Studies, Depression diagnostic imaging, Depression pathology, Diffusion Tensor Imaging methods, Humans, White Matter diagnostic imaging, White Matter pathology
Abstract: Cross-sectional Diffusion Tensor Imaging (DTI) studies have reported alterations in white matter (WM) microstructure in adolescents with internalizing psychopathology. Yet, longitudinal studies investigating the course of WM microstructure are lacking. This study explored WM alterations and its relation to clinical symptoms over time in adolescents with internalizing disorders. DTI scans were acquired at baseline and after three months in 22 adolescents with clinical depression and comorbid anxiety (INT), and 21 healthy peers (HC) (age: 12-18). Tract-based spatial statistics was used for three voxelwise analyses: i) changes in WM microstructure between and within the INT and HC group; ii) associations between changes in symptom severity and changes in WM microstructure within youths with INT; and iii) associations between baseline WM parameters with changes in symptom severity within youths with INT. Data did not reveal changes in WM microstructure between or within groups over three months' time nor associations between changes in WM microstructure and changes in self-reported symptoms (analyses corrected for age, gender and puberty stage). Lower baseline levels of fractional anisotropy (FA) in the right posterior corona radiata (PCR) and right cingulum were associated with a higher decrease of depressive symptoms within the INT group. Post hoc analysis of additional WM parameters in the significant FA clusters showed that higher levels of baseline mean diffusivity and radial diffusivity in the PCR were associated with a lower decrease in depressive symptoms. Baseline WM microstructure characteristics were associated with a higher decrease in depressive symptoms over time. These findings increase our understanding of neurobiological mechanisms underlying the course of internalizing disorders in adolescents., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany.)
Published: 2022
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47. Resting-State Functional Connectivity Characteristics of Resilience to Traumatic Stress in Dutch Police Officers.

Author: Setroikromo SNW, van der Werff SJA, Smit AS, Vermetten E, and Van Der Wee NJA
Abstract: Background: Insights into the neurobiological basis of resilience can have important implications for the prevention and treatment of stress-related disorders, especially in populations that are subjected to high-stress environments. Evaluating large-scale resting-state networks (RSNs) can provide information regarding resilient specific brain function which may be useful in understanding resilience. This study aimed to explore functional connectivity patterns specific for (high) resilience in Dutch policemen after exposure to multiple work-related traumatic events. We investigated resting-state functional connectivity (RSFC) of the salience network (SN), limbic network, and the default-mode network (DMN)., Methods: Resting-state functional MRI scans were obtained from trauma-exposed executive personnel of the Dutch police force and non-trauma-exposed recruits from the police academy. Participants were divided into three groups: a resilient group ( n = 31; trauma exposure; no psychopathology), a vulnerable group ( n = 32; trauma exposure, psychopathology), and a control group ( n = 19; no trauma exposure, no psychopathology). RSFC of the three networks of interest was compared between these groups, using an independent component analysis and a dual regression approach., Results: We found decreased resilience-specific positive RSFC of the salience network with several prefrontal regions. The DMN and limbic network RFSC did not show resilience-specific patterns., Conclusion: This study shows a differential RSFC specific for resilient police officers. This differential RSFC may be related to a greater capacity for internal-focused thought and interoceptive awareness, allowing more effective higher-order responses to stress in highly resilient individuals., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Setroikromo, van der Werff, Smit, Vermetten and Van Der Wee.)
Published: 2022
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48. Neural correlates of anxious distress in depression: A neuroimaging study of reactivity to emotional faces and resting-state functional connectivity.

Author: Nawijn L, Dinga R, Aghajani M, van Tol MJ, van der Wee NJA, Wunder A, Veltman DJ, and Penninx BWHJ
Subjects: Anxiety psychology, Anxiety Disorders psychology, Depression, Humans, Magnetic Resonance Imaging, Neuroimaging, Depressive Disorder, Major drug therapy
Abstract: Background: Comorbid anxiety disorders and anxious distress are highly prevalent in major depressive disorder (MDD). The presence of the DSM-5 anxious distress specifier (ADS) has been associated with worse treatment outcomes and chronic disease course. However, little is known about the neurobiological correlates of anxious distress in MDD., Methods: We probed the relation between the DSM-5 ADS and task-related reactivity to emotional faces, as well as resting-state functional connectivity patterns of intrinsic salience and basal ganglia networks in unmedicated MDD patients with (MDD/ADS+, N = 24) and without ADS (MDD/ADS-, N = 48) and healthy controls (HC, N = 59). Both categorical and dimensional measures of ADS were investigated., Results: MDD/ADS+ patients had higher left amygdala responses to emotional faces compared to MDD/ADS- patients (p = .015)-part of a larger striato-limbic cluster. MDD/ADS+ did not differ from MDD/ADS- or controls in resting-state functional connectivity of the salience or basal ganglia networks., Conclusions: Current findings suggest that amygdala and striato-limbic hyperactivity to emotional faces may be a neurobiological hallmark specific to MDD with anxious distress, relative to MDD without anxious distress. This may provide preliminary indications of the underlying mechanisms of anxious distress in depression, and underline the importance to account for heterogeneity in depression research., (© 2022 The Authors. Depression and Anxiety published by Wiley Periodicals LLC.)
Published: 2022
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49. Cross-disorder and disorder-specific deficits in social functioning among schizophrenia and alzheimer's disease patients.

Author: Saris IMJ, Aghajani M, Jongs N, Reus LM, van der Wee NJA, Bilderbeck AC, Winter van Rossum I, Arango C, de la Torre-Luque A, Malik A, Raslescu A, Dawson GR, Ayuso-Mateos JL, Kas MJ, and Penninx BWJH
Subjects: Humans, Loneliness, Social Adjustment, Social Interaction, Alzheimer Disease, Schizophrenia diagnosis
Abstract: Background: Social functioning is often impaired in schizophrenia (SZ) and Alzheimer's disease (AD). However, commonalities and differences in social dysfunction among these patient groups remain elusive., Materials and Methods: Using data from the PRISM study, behavioral (all subscales and total score of the Social Functioning Scale) and affective (perceived social disability and loneliness) indicators of social functioning were measured in patients with SZ (N = 56), probable AD (N = 50) and age-matched healthy controls groups (HC, N = 29 and N = 28). We examined to what extent social functioning differed between disease and age-matched HC groups, as well as between patient groups. Furthermore, we examined how severity of disease and mood were correlated with social functioning, irrespective of diagnosis., Results: As compared to HC, both behavioral and affective social functioning seemed impaired in SZ patients (Cohen's d's 0.81-1.69), whereas AD patients mainly showed impaired behavioral social function (Cohen's d's 0.65-1.14). While behavioral indices of social functioning were similar across patient groups, SZ patients reported more perceived social disability than AD patients (Cohen's d's 0.65). Across patient groups, positive mood, lower depression and anxiety levels were strong determinants of better social functioning (p's <0.001), even more so than severity of disease., Conclusions: AD and SZ patients both exhibit poor social functioning in comparison to age- and sex matched HC participants. Social dysfunction in SZ patients may be more severe than in AD patients, though this may be due to underreporting by AD patients. Across patients, social functioning appeared as more influenced by mood states than by severity of disease., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: CA has been a consultant to or has received honoraria or grants from Acadia, Angelini, Gedeon Richter, Janssen Cilag, Lundbeck, Minerva, Otsuka, Roche, Sage, Servier, Shire, Schering Plough, Sumitomo Dainippon Pharma, Sunovion and Takeda. ACB has received salaries from P1vital Ltd. MK has received (non-related) research funding from Novartis. BP has received (non-related) research funding from Jansen Research and Boehringer Ingelheim. This does not alter our adherence to PLOS ONE policies on sharing data and materials.
Published: 2022
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50. No indications for altered EEG oscillatory activity in patients with chronic post-burn itch compared to healthy controls.

Author: Millard SK, Bokelmann K, Schalbroeck R, van der Wee NJA, van Loey NEE, and van Laarhoven AIM
Subjects: Adult, Bayes Theorem, Cross-Sectional Studies, Electroencephalography, Humans, Pilot Projects, Pruritus etiology, Pruritus therapy, Quality of Life
Abstract: A large proportion of patients with burn injuries develop chronic itch, which impacts quality of life. The underlying pathophysiological mechanisms are poorly understood. This cross-sectional pilot study investigates whether altered cortical oscillatory processes are involved in chronic post-burn itch. Continuous electroencephalography (EEG) data were recorded during rest and stimulation of non-injured skin, inducing itch (histamine and electrical) and cold-pressor task pain for 15 adults with chronic post-burn itch and 15 matched healthy controls. Quantitative metrics comprised oscillatory power and peak frequencies in theta, alpha, and beta bands. No statistical differences between patients and healthy controls were found in oscillatory activity during rest or stimulation, with Bayesian analysis suggesting equivocal evidence. However, post-traumatic stress symptoms and duration of chronic itch may be associated with changes in oscillatory activity. A lack of differences in cortical oscillatory processing and itch levels at non-injured sites, suggests that itch symptoms have a localised character in this sample of patients with post-burn itch. For future studies, a biopsychological approach with integration of peripheral and central nervous system techniques, linear and non-linear EEG analysis, injured and non-injured stimulation sites, and incorporation of individual characteristics is recommended. Insight into pathophysiological mechanisms underlying chronic post-burn itch could improve diagnostics and treatments., (© 2022. The Author(s).)
Published: 2022
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