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1,151 results on '"Turner, JA"'

1. Identifying canonical and replicable multi‐scale intrinsic connectivity networks in 100k+ resting‐state fMRI datasets

Author

Iraji, A, Fu, Z, Faghiri, A, Duda, M, Chen, J, Rachakonda, S, DeRamus, T, Kochunov, P, Adhikari, BM, Belger, A, Ford, JM, Mathalon, DH, Pearlson, GD, Potkin, SG, Preda, A, Turner, JA, van Erp, TGM, Bustillo, JR, Yang, K, Ishizuka, K, Faria, A, Sawa, A, Hutchison, K, Osuch, EA, Theberge, J, Abbott, C, Mueller, BA, Zhi, D, Zhuo, C, Liu, S, Xu, Y, Salman, M, Liu, J, Du, Y, Sui, J, Adali, T, and Calhoun, VD

Subjects
Biomedical and Clinical Sciences, Biological Psychology, Cognitive and Computational Psychology, Neurosciences, Psychology, Bioengineering, Clinical Research, Neurological, Humans, Brain Mapping, Magnetic Resonance Imaging, Reproducibility of Results, Nerve Net, Brain, functional connectivity, functional templates, independent component analysis, intrinsic connectivity networks, Cognitive Sciences, Experimental Psychology, Biological psychology, Cognitive and computational psychology
Abstract

Despite the known benefits of data-driven approaches, the lack of approaches for identifying functional neuroimaging patterns that capture both individual variations and inter-subject correspondence limits the clinical utility of rsfMRI and its application to single-subject analyses. Here, using rsfMRI data from over 100k individuals across private and public datasets, we identify replicable multi-spatial-scale canonical intrinsic connectivity network (ICN) templates via the use of multi-model-order independent component analysis (ICA). We also study the feasibility of estimating subject-specific ICNs via spatially constrained ICA. The results show that the subject-level ICN estimations vary as a function of the ICN itself, the data length, and the spatial resolution. In general, large-scale ICNs require less data to achieve specific levels of (within- and between-subject) spatial similarity with their templates. Importantly, increasing data length can reduce an ICN's subject-level specificity, suggesting longer scans may not always be desirable. We also find a positive linear relationship between data length and spatial smoothness (possibly due to averaging over intrinsic dynamics), suggesting studies examining optimized data length should consider spatial smoothness. Finally, consistency in spatial similarity between ICNs estimated using the full data and subsets across different data lengths suggests lower within-subject spatial similarity in shorter data is not wholly defined by lower reliability in ICN estimates, but may be an indication of meaningful brain dynamics which average out as data length increases.

Published
2023

2. Moving beyond the 'CAP' of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping.

Author

Iraji, A, Faghiri, A, Fu, Z, Kochunov, P, Adhikari, BM, Belger, A, Ford, JM, McEwen, S, Mathalon, DH, Pearlson, GD, Potkin, SG, Preda, A, Turner, JA, Van Erp, TGM, Chang, C, and Calhoun, VD

Subjects
Brain, Nerve Net, Humans, Magnetic Resonance Imaging, Brain Mapping, Functional Neuroimaging, Activation spatial map, Co-activation patterns, Event absent time points, Event present time points, Functional connectivity, Independent component analysis, Intrinsic connectivity networks, Brain Disorders, Neurosciences, Biomedical Imaging, 1.1 Normal biological development and functioning, Underpinning research, Mental health, Neurological, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery
Abstract

Resting-state functional magnetic resonance imaging is currently the mainstay of functional neuroimaging and has allowed researchers to identify intrinsic connectivity networks (aka functional networks) at different spatial scales. However, little is known about the temporal profiles of these networks and whether it is best to model them as continuous phenomena in both space and time or, rather, as a set of temporally discrete events. Both categories have been supported by series of studies with promising findings. However, a critical question is whether focusing only on time points presumed to contain isolated neural events and disregarding the rest of the data is missing important information, potentially leading to misleading conclusions. In this work, we argue that brain networks identified within the spontaneous blood oxygenation level-dependent (BOLD) signal are not limited to temporally sparse burst moments and that these event present time points (EPTs) contain valuable but incomplete information about the underlying functional patterns. We focus on the default mode and show evidence that is consistent with its continuous presence in the BOLD signal, including during the event absent time points (EATs), i.e., time points that exhibit minimum activity and are the least likely to contain an event. Moreover, our findings suggest that EPTs may not contain all the available information about their corresponding networks. We observe distinct default mode connectivity patterns obtained from all time points (AllTPs), EPTs, and EATs. We show evidence of robust relationships with schizophrenia symptoms that are both common and unique to each of the sets of time points (AllTPs, EPTs, EATs), likely related to transient patterns of connectivity. Together, these findings indicate the importance of leveraging the full temporal data in functional studies, including those using event-detection approaches.

Published
2022

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

Author

Walton, E, Hibar, DP, van Erp, TGM, Potkin, SG, Roiz-Santiañez, R, Crespo-Facorro, B, Suarez-Pinilla, P, van Haren, NEM, de Zwarte, SMC, Kahn, RS, Cahn, W, Doan, NT, Jørgensen, KN, Gurholt, TP, Agartz, I, Andreassen, OA, Westlye, LT, Melle, I, Berg, AO, Morch-Johnsen, L, Færden, A, Flyckt, L, Fatouros-Bergman, H, Karolinska Schizophrenia Project Consortium (KaSP), Jönsson, EG, Hashimoto, R, Yamamori, H, Fukunaga, M, Jahanshad, N, De Rossi, P, Piras, F, Banaj, N, Spalletta, G, Gur, RE, Gur, RC, Wolf, DH, Satterthwaite, TD, Beard, LM, Sommer, IE, Koops, S, Gruber, O, Richter, A, Krämer, B, Kelly, S, Donohoe, G, McDonald, C, Cannon, DM, Corvin, A, Gill, M, Di Giorgio, A, Bertolino, A, Lawrie, S, Nickson, T, Whalley, HC, Neilson, E, Calhoun, VD, Thompson, PM, Turner, JA, and Ehrlich, S

Subjects
Karolinska Schizophrenia Project Consortium, Prefrontal Cortex, Humans, Magnetic Resonance Imaging, Linear Models, Schizophrenia, Psychiatric Status Rating Scales, Schizophrenic Psychology, Internationality, Image Processing, Computer-Assisted, Adult, Female, Male, Functional Laterality, Cortical thickness, ENIGMA, FreeSurfer, MRI, PANSS, SANS, medial orbitofrontal cortex, negative symptoms, schizophrenia, Image Processing, Computer-Assisted, Psychiatry, Psychology, Public Health and Health Services, Neurosciences
Abstract

BackgroundOur understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.MethodsThis study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).ResultsMeta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (β std = -0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.ConclusionsUsing an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

Published
2018

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

Author

Walton, E, Hibar, DP, Erp, TGM, Potkin, SG, Roiz‐Santiañez, R, Crespo‐Facorro, B, Suarez‐Pinilla, P, Van Haren, NEM, Zwarte, SMC, Kahn, RS, Cahn, W, Doan, NT, Jørgensen, KN, Gurholt, TP, Agartz, I, Andreassen, OA, Westlye, LT, Melle, I, Berg, AO, Mørch‐Johnsen, L, Færden, A, Flyckt, L, Fatouros‐Bergman, H, Consortium, Karolinska Schizophrenia Project, Jönsson, EG, Hashimoto, R, Yamamori, H, Fukunaga, M, Preda, A, De Rossi, P, Piras, F, Banaj, N, Ciullo, V, Spalletta, G, Gur, RE, Gur, RC, Wolf, DH, Satterthwaite, TD, Beard, LM, Sommer, IE, Koops, S, Gruber, O, Richter, A, Krämer, B, Kelly, S, Donohoe, G, McDonald, C, Cannon, DM, Corvin, A, Gill, M, Di Giorgio, A, Bertolino, A, Lawrie, S, Nickson, T, Whalley, HC, Neilson, E, Calhoun, VD, Thompson, PM, Turner, JA, and Ehrlich, S

Subjects
Schizophrenia, Mental Health, Brain Disorders, Mental health, Good Health and Well Being, Adult, Brain Mapping, Female, Humans, Magnetic Resonance Imaging, Male, Prospective Studies, Psychiatric Status Rating Scales, Schizophrenic Psychology, Temporal Lobe, schizophrenia, positive symptoms, superior temporal gyrus, cortical thickness, ENIGMA, FreeSurfer, MRI, scale for the assessment of positive symptoms, positive and negative syndrome scale, Karolinska Schizophrenia Project Consortium, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

ObjectiveBased on the role of the superior temporal gyrus (STG) in auditory processing, language comprehension and self-monitoring, this study aimed to investigate the relationship between STG cortical thickness and positive symptom severity in schizophrenia.MethodThis prospective meta-analysis includes data from 1987 individuals with schizophrenia collected at seventeen centres around the world that contribute to the ENIGMA Schizophrenia Working Group. STG thickness measures were extracted from T1-weighted brain scans using FreeSurfer. The study performed a meta-analysis of effect sizes across sites generated by a model predicting left or right STG thickness with a positive symptom severity score (harmonized SAPS or PANSS-positive scores), while controlling for age, sex and site. Secondary models investigated relationships between antipsychotic medication, duration of illness, overall illness severity, handedness and STG thickness.ResultsPositive symptom severity was negatively related to STG thickness in both hemispheres (left: βstd = -0.052; P = 0.021; right: βstd = -0.073; P = 0.001) when statistically controlling for age, sex and site. This effect remained stable in models including duration of illness, antipsychotic medication or handedness.ConclusionOur findings further underline the important role of the STG in hallmark symptoms in schizophrenia. These findings can assist in advancing insight into symptom-relevant pathophysiological mechanisms in schizophrenia.

Published
2017

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

Author

Jiang, Y, Luo, C, Wang, J, Palaniyappan, L, Chang, X, Xiang, S, Zhang, J, Duan, M, Huang, H, Gaser, C, Nemoto, K, Miura, K, Hashimoto, R, Westlye, LT, Richard, G, Fernandez-Cabello, S, Parker, N, Andreassen, OA, Kircher, T, Nenadić, I, Stein, F, Thomas-Odenthal, F, Teutenberg, L, Usemann, P, Dannlowski, U, Hahn, T, Grotegerd, D, Meinert, S, Lencer, R, Tang, Y, Zhang, T, Li, C, Yue, W, Zhang, Y, Yu, X, Zhou, E, Lin, C-P, Tsai, S-J, Rodrigue, AL, Glahn, D, Pearlson, G, Blangero, J, Karuk, A, Pomarol-Clotet, E, Salvador, R, Fuentes-Claramonte, P, Garcia-León, MÁ, Spalletta, G, Piras, F, Vecchio, D, Banaj, N, Cheng, J, Liu, Z, Yang, J, Gonul, AS, Uslu, O, Burhanoglu, BB, Uyar Demir, A, Rootes-Murdy, K, Calhoun, VD, Sim, K, Green, M, Quidé, Y, Chung, YC, Kim, W-S, Sponheim, SR, Demro, C, Ramsay, IS, Iasevoli, F, de Bartolomeis, A, Barone, A, Ciccarelli, M, Brunetti, A, Cocozza, S, Pontillo, G, Tranfa, M, Park, MTM, Kirschner, M, Georgiadis, F, Kaiser, S, Van Rheenen, TE, Rossell, SL, Hughes, M, Woods, W, Carruthers, SP, Sumner, P, Ringin, E, Spaniel, F, Skoch, A, Tomecek, D, Homan, P, Homan, S, Omlor, W, Cecere, G, Nguyen, DD, Preda, A, Thomopoulos, SI, Jahanshad, N, Cui, L-B, Yao, D, Thompson, PM, Turner, JA, van Erp, TGM, Cheng, W, ENIGMA Schizophrenia Consortium, Feng, J, ZIB Consortium, Jiang, Y, Luo, C, Wang, J, Palaniyappan, L, Chang, X, Xiang, S, Zhang, J, Duan, M, Huang, H, Gaser, C, Nemoto, K, Miura, K, Hashimoto, R, Westlye, LT, Richard, G, Fernandez-Cabello, S, Parker, N, Andreassen, OA, Kircher, T, Nenadić, I, Stein, F, Thomas-Odenthal, F, Teutenberg, L, Usemann, P, Dannlowski, U, Hahn, T, Grotegerd, D, Meinert, S, Lencer, R, Tang, Y, Zhang, T, Li, C, Yue, W, Zhang, Y, Yu, X, Zhou, E, Lin, C-P, Tsai, S-J, Rodrigue, AL, Glahn, D, Pearlson, G, Blangero, J, Karuk, A, Pomarol-Clotet, E, Salvador, R, Fuentes-Claramonte, P, Garcia-León, MÁ, Spalletta, G, Piras, F, Vecchio, D, Banaj, N, Cheng, J, Liu, Z, Yang, J, Gonul, AS, Uslu, O, Burhanoglu, BB, Uyar Demir, A, Rootes-Murdy, K, Calhoun, VD, Sim, K, Green, M, Quidé, Y, Chung, YC, Kim, W-S, Sponheim, SR, Demro, C, Ramsay, IS, Iasevoli, F, de Bartolomeis, A, Barone, A, Ciccarelli, M, Brunetti, A, Cocozza, S, Pontillo, G, Tranfa, M, Park, MTM, Kirschner, M, Georgiadis, F, Kaiser, S, Van Rheenen, TE, Rossell, SL, Hughes, M, Woods, W, Carruthers, SP, Sumner, P, Ringin, E, Spaniel, F, Skoch, A, Tomecek, D, Homan, P, Homan, S, Omlor, W, Cecere, G, Nguyen, DD, Preda, A, Thomopoulos, SI, Jahanshad, N, Cui, L-B, Yao, D, Thompson, PM, Turner, JA, van Erp, TGM, Cheng, W, ENIGMA Schizophrenia Consortium, Feng, J, and ZIB Consortium

Abstract

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Published
2024

6. Abnormal asymmetries in subcortical brain volume in schizophrenia

Author

Okada, N, Fukunaga, M, Yamashita, F, Koshiyama, D, Yamamori, H, Ohi, K, Yasuda, Y, Fujimoto, M, Watanabe, Y, Yahata, N, Nemoto, K, Hibar, DP, van Erp, TGM, Fujino, H, Isobe, M, Isomura, S, Natsubori, T, Narita, H, Hashimoto, N, Miyata, J, Koike, S, Takahashi, T, Yamasue, H, Matsuo, K, Onitsuka, T, Iidaka, T, Kawasaki, Y, Yoshimura, R, Suzuki, M, Turner, JA, Takeda, M, Thompson, PM, Ozaki, N, Kasai, K, and Hashimoto, R

Subjects
Clinical Research, Mental Health, Brain Disorders, Neurosciences, Schizophrenia, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adult, Amygdala, Basal Ganglia, Brain, Brain Mapping, Cohort Studies, Cross-Sectional Studies, Female, Functional Laterality, Hippocampus, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Psychiatric Status Rating Scales, Putamen, Thalamus, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

Subcortical structures, which include the basal ganglia and parts of the limbic system, have key roles in learning, motor control and emotion, but also contribute to higher-order executive functions. Prior studies have reported volumetric alterations in subcortical regions in schizophrenia. Reported results have sometimes been heterogeneous, and few large-scale investigations have been conducted. Moreover, few large-scale studies have assessed asymmetries of subcortical volumes in schizophrenia. Here, as a work completely independent of a study performed by the ENIGMA consortium, we conducted a large-scale multisite study of subcortical volumetric differences between patients with schizophrenia and controls. We also explored the laterality of subcortical regions to identify characteristic similarities and differences between them. T1-weighted images from 1680 healthy individuals and 884 patients with schizophrenia, obtained with 15 imaging protocols at 11 sites, were processed with FreeSurfer. Group differences were calculated for each protocol and meta-analyzed. Compared with controls, patients with schizophrenia demonstrated smaller bilateral hippocampus, amygdala, thalamus and accumbens volumes as well as intracranial volume, but larger bilateral caudate, putamen, pallidum and lateral ventricle volumes. We replicated the rank order of effect sizes for subcortical volumetric changes in schizophrenia reported by the ENIGMA consortium. Further, we revealed leftward asymmetry for thalamus, lateral ventricle, caudate and putamen volumes, and rightward asymmetry for amygdala and hippocampal volumes in both controls and patients with schizophrenia. Also, we demonstrated a schizophrenia-specific leftward asymmetry for pallidum volume. These findings suggest the possibility of aberrant laterality in neural pathways and connectivity patterns related to the pallidum in schizophrenia.

Published
2016

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

Author

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

Subjects
Biological Psychology, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Psychology, Serious Mental Illness, Brain Disorders, Schizophrenia, Clinical Research, Neurosciences, Mental Health, Biomedical Imaging, Rare Diseases, Aetiology, 2.1 Biological and endogenous factors, Mental health, Good Health and Well Being, Adult, Brain, Brain Mapping, Case-Control Studies, Female, Functional Laterality, Humans, Image Processing, Computer-Assisted, Longitudinal Studies, Magnetic Resonance Imaging, Male, Middle Aged, Neuroimaging, Prospective Studies, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry, Clinical sciences, Biological psychology, Clinical and health psychology
Abstract

The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

Published
2016

8. Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

Author

Damaraju, E, Allen, EA, Belger, A, Ford, JM, McEwen, S, Mathalon, DH, Mueller, BA, Pearlson, GD, Potkin, SG, Preda, A, Turner, JA, Vaidya, JG, van Erp, TG, and Calhoun, VD

Subjects
Biological Psychology, Biomedical and Clinical Sciences, Psychology, Brain Disorders, Serious Mental Illness, Schizophrenia, Mental Health, Neurosciences, Clinical Research, Underpinning research, 1.1 Normal biological development and functioning, Mental health, Adult, Brain, Brain Mapping, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Neural Pathways, Biological psychology, Clinical and health psychology
Abstract

Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical-subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences.

Published
2014

9. Studying hallucinations within the NIMH RDoC framework

Author

Ford, Judith, Ford, JM, Morris, SE, Hoffman, RE, Sommer, I, Waters, F, McCarthy-Jones, S, Thoma, RJ, Turner, JA, Keedy, SK, and Badcock, JC

Abstract

We explore how hallucinations might be studied within the National Institute of Mental Health (NIMH) Research Domain Criteria (RDoC) framework, which asks investigators to step back from diagnoses based on symptoms and focus on basic dimensions of function

Published
2014

10. Towards structured sharing of raw and derived neuroimaging data across existing resources

Author

Keator, DB, Helmer, K, Steffener, J, Turner, JA, Van Erp, TGM, Gadde, S, Ashish, N, Burns, GA, and Nichols, BN

Subjects
Biomedical and Clinical Sciences, Health Sciences, Networking and Information Technology R&D (NITRD), Bioengineering, Neurosciences, Database Management Systems, Databases, Factual, Humans, Informatics, Information Dissemination, Internet, Neuroimaging, XCEDE, Provenance, Data model, Database, Web services, cs.DB, q-bio.NC, Medical and Health Sciences, Psychology and Cognitive Sciences, Neurology & Neurosurgery, Biomedical and clinical sciences, Health sciences
Abstract

Data sharing efforts increasingly contribute to the acceleration of scientific discovery. Neuroimaging data is accumulating in distributed domain-specific databases and there is currently no integrated access mechanism nor an accepted format for the critically important meta-data that is necessary for making use of the combined, available neuroimaging data. In this manuscript, we present work from the Derived Data Working Group, an open-access group sponsored by the Biomedical Informatics Research Network (BIRN) and the International Neuroimaging Coordinating Facility (INCF) focused on practical tools for distributed access to neuroimaging data. The working group develops models and tools facilitating the structured interchange of neuroimaging meta-data and is making progress towards a unified set of tools for such data and meta-data exchange. We report on the key components required for integrated access to raw and derived neuroimaging data as well as associated meta-data and provenance across neuroimaging resources. The components include (1) a structured terminology that provides semantic context to data, (2) a formal data model for neuroimaging with robust tracking of data provenance, (3) a web service-based application programming interface (API) that provides a consistent mechanism to access and query the data model, and (4) a provenance library that can be used for the extraction of provenance data by image analysts and imaging software developers. We believe that the framework and set of tools outlined in this manuscript have great potential for solving many of the issues the neuroimaging community faces when sharing raw and derived neuroimaging data across the various existing database systems for the purpose of accelerating scientific discovery.

Published
2013

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

Author

Schijven, D, Postema, MC, Fukunaga, M, Matsumoto, J, Miura, K, de Zwarte, SMC, van Haren, NEM, Cahn, W, Pol, HEH, Kahn, RS, Ayesa-Arriola, R, de la Foz, VO-G, Tordesillas-Gutierrez, D, Vazquez-Bourgon, J, Crespo-Facorro, B, Alnaes, D, Dahl, A, Westlye, LT, Agartz, I, Andreassen, OA, Jonsson, EG, Kochunov, P, Bruggemann, JM, Catts, SV, Michie, PT, Mowry, BJ, Quide, Y, Rasser, PE, Schall, U, Scott, RJ, Carr, VJ, Green, MJ, Henskens, FA, Loughland, CM, Pantelis, C, Weickert, CS, Weickert, TW, De Haan, L, Brosch, K, Pfarr, J-K, Ringwald, KG, Stein, F, Jansen, A, Kircher, TTJ, Nenadic, I, Kramer, B, Gruber, O, Satterthwaite, TD, Bustillo, J, Mathalon, DH, Preda, A, Calhoun, VD, Ford, JM, Potkin, SG, Chen, J, Tan, Y, Wang, Z, Xiang, H, Fan, F, Bernardoni, F, Ehrlich, S, Fuentes-Claramonte, P, Garcia-Leon, MA, Guerrero-Pedraza, A, Salvador, R, Sarro, S, Pomarol-Clotet, E, Ciullo, V, Piras, F, Vecchio, D, Banaj, N, Spalletta, G, Michielse, S, van Amelsvoort, T, Dickie, EW, Voineskos, AN, Sim, K, Ciufolini, S, Dazzan, P, Murray, RM, Kim, W-S, Chung, Y-C, Andreou, C, Schmidt, A, Borgwardt, S, McIntosh, AM, Whalley, HC, Lawrie, SM, Du Plessis, S, Luckhoff, HK, Scheffler, F, Emsley, R, Grotegerd, D, Lencer, R, Dannlowski, U, Edmond, JT, Rootes-Murdy, K, Stephen, JM, Mayer, AR, Antonucci, LA, Fazio, L, Pergola, G, Bertolino, A, Diaz-Caneja, CM, Janssen, J, Lois, NG, Arango, C, Tomyshev, AS, Lebedeva, I, Cervenkav, S, Sellgrenv, CM, Georgiadis, F, Kirschner, M, Kaiser, S, Hajek, T, Skoch, A, Spaniel, F, Kim, M, Bin Kwak, Y, Oh, S, Kwon, JS, James, A, Bakker, G, Knochel, C, Stablein, M, Oertel, V, Uhlmann, A, Howells, FM, Stein, DJ, Temmingh, HS, Diaz-Zuluaga, AM, Pineda-Zapata, JA, Lopez-Jaramillo, C, Homan, S, Ji, E, Surbeck, W, Homan, P, Fishera, SE, Franke, B, Glahn, DC, Gur, RC, Hashimoto, R, Jahanshad, N, Luders, E, Medland, SE, Thompson, PM, Turner, JA, van Erp, TGM, Francks, C, Schijven, D, Postema, MC, Fukunaga, M, Matsumoto, J, Miura, K, de Zwarte, SMC, van Haren, NEM, Cahn, W, Pol, HEH, Kahn, RS, Ayesa-Arriola, R, de la Foz, VO-G, Tordesillas-Gutierrez, D, Vazquez-Bourgon, J, Crespo-Facorro, B, Alnaes, D, Dahl, A, Westlye, LT, Agartz, I, Andreassen, OA, Jonsson, EG, Kochunov, P, Bruggemann, JM, Catts, SV, Michie, PT, Mowry, BJ, Quide, Y, Rasser, PE, Schall, U, Scott, RJ, Carr, VJ, Green, MJ, Henskens, FA, Loughland, CM, Pantelis, C, Weickert, CS, Weickert, TW, De Haan, L, Brosch, K, Pfarr, J-K, Ringwald, KG, Stein, F, Jansen, A, Kircher, TTJ, Nenadic, I, Kramer, B, Gruber, O, Satterthwaite, TD, Bustillo, J, Mathalon, DH, Preda, A, Calhoun, VD, Ford, JM, Potkin, SG, Chen, J, Tan, Y, Wang, Z, Xiang, H, Fan, F, Bernardoni, F, Ehrlich, S, Fuentes-Claramonte, P, Garcia-Leon, MA, Guerrero-Pedraza, A, Salvador, R, Sarro, S, Pomarol-Clotet, E, Ciullo, V, Piras, F, Vecchio, D, Banaj, N, Spalletta, G, Michielse, S, van Amelsvoort, T, Dickie, EW, Voineskos, AN, Sim, K, Ciufolini, S, Dazzan, P, Murray, RM, Kim, W-S, Chung, Y-C, Andreou, C, Schmidt, A, Borgwardt, S, McIntosh, AM, Whalley, HC, Lawrie, SM, Du Plessis, S, Luckhoff, HK, Scheffler, F, Emsley, R, Grotegerd, D, Lencer, R, Dannlowski, U, Edmond, JT, Rootes-Murdy, K, Stephen, JM, Mayer, AR, Antonucci, LA, Fazio, L, Pergola, G, Bertolino, A, Diaz-Caneja, CM, Janssen, J, Lois, NG, Arango, C, Tomyshev, AS, Lebedeva, I, Cervenkav, S, Sellgrenv, CM, Georgiadis, F, Kirschner, M, Kaiser, S, Hajek, T, Skoch, A, Spaniel, F, Kim, M, Bin Kwak, Y, Oh, S, Kwon, JS, James, A, Bakker, G, Knochel, C, Stablein, M, Oertel, V, Uhlmann, A, Howells, FM, Stein, DJ, Temmingh, HS, Diaz-Zuluaga, AM, Pineda-Zapata, JA, Lopez-Jaramillo, C, Homan, S, Ji, E, Surbeck, W, Homan, P, Fishera, SE, Franke, B, Glahn, DC, Gur, RC, Hashimoto, R, Jahanshad, N, Luders, E, Medland, SE, Thompson, PM, Turner, JA, van Erp, TGM, and Francks, C

Abstract

Left-right asymmetry is an important organizing feature of the healthy brain that may be altered in schizophrenia, but most studies have used relatively small samples and heterogeneous approaches, resulting in equivocal findings. We carried out the largest case-control study of structural brain asymmetries in schizophrenia, with MRI data from 5,080 affected individuals and 6,015 controls across 46 datasets, using a single image analysis protocol. Asymmetry indexes were calculated for global and regional cortical thickness, surface area, and subcortical volume measures. Differences of asymmetry were calculated between affected individuals and controls per dataset, and effect sizes were meta-analyzed across datasets. Small average case-control differences were observed for thickness asymmetries of the rostral anterior cingulate and the middle temporal gyrus, both driven by thinner left-hemispheric cortices in schizophrenia. Analyses of these asymmetries with respect to the use of antipsychotic medication and other clinical variables did not show any significant associations. Assessment of age- and sex-specific effects revealed a stronger average leftward asymmetry of pallidum volume between older cases and controls. Case-control differences in a multivariate context were assessed in a subset of the data (N = 2,029), which revealed that 7% of the variance across all structural asymmetries was explained by case-control status. Subtle case-control differences of brain macrostructural asymmetry may reflect differences at the molecular, cytoarchitectonic, or circuit levels that have functional relevance for the disorder. Reduced left middle temporal cortical thickness is consistent with altered left-hemisphere language network organization in schizophrenia.

Published
2023

13. Cross disorder comparisons of brain structure in schizophrenia, bipolar disorder, major depressive disorder, and 22q11.2 deletion syndrome: A review of ENIGMA findings

Author

Cheon, E-J, Bearden, CE, Sun, D, Ching, CRK, Andreassen, OA, Schmaal, L, Veltman, DJ, Thomopoulos, S, Kochunov, P, Jahanshad, N, Thompson, PM, Turner, JA, van Erp, TGM, Cheon, E-J, Bearden, CE, Sun, D, Ching, CRK, Andreassen, OA, Schmaal, L, Veltman, DJ, Thomopoulos, S, Kochunov, P, Jahanshad, N, Thompson, PM, Turner, JA, and van Erp, TGM

Abstract

This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder-related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes.

Published
2022

14. The Enhancing NeuroImaging Genetics through Meta-Analysis Consortium: 10 Years of Global Collaborations in Human Brain Mapping

Author

Thompson, PM, Jahanshad, N, Schmaal, L, Turner, JA, Winkler, AM, Thomopoulos, SI, Egan, GF, Kochunov, P, Thompson, PM, Jahanshad, N, Schmaal, L, Turner, JA, Winkler, AM, Thomopoulos, SI, Egan, GF, and Kochunov, P

Abstract

This Special Issue of Human Brain Mapping is dedicated to a 10-year anniversary of the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium. It reports updates from a broad range of international neuroimaging projects that pool data from around the world to answer fundamental questions in neuroscience. Since ENIGMA was formed in December 2009, the initiative grew into a worldwide effort with over 2,000 participating scientists from 45 countries, and over 50 working groups leading large-scale studies of human brain disorders. Over the last decade, many lessons were learned on how best to pool brain data from diverse sources. Working groups were created to develop methods to analyze worldwide data from anatomical and diffusion magnetic resonance imaging (MRI), resting state and task-based functional MRI, electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance spectroscopy (MRS). The quest to understand genetic effects on human brain development and disease also led to analyses of brain scans on an unprecedented scale. Genetic roadmaps of the human cortex were created by researchers worldwide who collaborated to perform statistically well-powered analyses of common and rare genetic variants on brain measures and rates of brain development and aging. Here, we summarize the 31 papers in this Special Issue, covering: (a) technical approaches to harmonize analysis of different types of brain imaging data, (b) reviews of the last decade of work by several of ENIGMA's clinical and technical working groups, and (c) new empirical papers reporting large-scale international brain mapping analyses in patients with substance use disorders, schizophrenia, bipolar disorders, major depression, posttraumatic stress disorder, obsessive compulsive disorder, epilepsy, and stroke.

Published
2022

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

Author

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

Abstract

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

Published
2022

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

Author

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

Abstract

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

Published
2022

17. Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Author

Kirschner, M, Hodzic-Santor, B, Antoniades, M, Nenadic, I, Kircher, T, Krug, A, Meller, T, Grotegerd, D, Fornito, A, Arnatkeviciute, A, Bellgrove, MA, Tiego, J, Dannlowski, U, Koch, K, Huelsmann, C, Kugel, H, Enneking, V, Klug, M, Leehr, EJ, Boehnlein, J, Gruber, M, Mehler, D, DeRosse, P, Moyett, A, Baune, BT, Green, M, Quide, Y, Pantelis, C, Chan, R, Wang, Y, Ettinger, U, Debbane, M, Derome, M, Gaser, C, Besteher, B, Diederen, K, Spencer, TJ, Fletcher, P, Roessler, W, Smigielski, L, Kumari, V, Premkumar, P, Park, HRP, Wiebels, K, Lemmers-Jansen, I, Gilleen, J, Allen, P, Kozhuharova, P, Marsman, J-B, Lebedeva, I, Tomyshev, A, Mukhorina, A, Kaiser, S, Fett, A-K, Sommer, I, Schuite-Koops, S, Paquola, C, Lariviere, S, Bernhardt, B, Dagher, A, Grant, P, van Erp, TGM, Turner, JA, Thompson, PM, Aleman, A, Modinos, G, Kirschner, M, Hodzic-Santor, B, Antoniades, M, Nenadic, I, Kircher, T, Krug, A, Meller, T, Grotegerd, D, Fornito, A, Arnatkeviciute, A, Bellgrove, MA, Tiego, J, Dannlowski, U, Koch, K, Huelsmann, C, Kugel, H, Enneking, V, Klug, M, Leehr, EJ, Boehnlein, J, Gruber, M, Mehler, D, DeRosse, P, Moyett, A, Baune, BT, Green, M, Quide, Y, Pantelis, C, Chan, R, Wang, Y, Ettinger, U, Debbane, M, Derome, M, Gaser, C, Besteher, B, Diederen, K, Spencer, TJ, Fletcher, P, Roessler, W, Smigielski, L, Kumari, V, Premkumar, P, Park, HRP, Wiebels, K, Lemmers-Jansen, I, Gilleen, J, Allen, P, Kozhuharova, P, Marsman, J-B, Lebedeva, I, Tomyshev, A, Mukhorina, A, Kaiser, S, Fett, A-K, Sommer, I, Schuite-Koops, S, Paquola, C, Lariviere, S, Bernhardt, B, Dagher, A, Grant, P, van Erp, TGM, Turner, JA, Thompson, PM, Aleman, A, and Modinos, G

Abstract

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Published
2022

18. Mapping brain asymmetry in health and disease through the ENIGMA consortium

Author

Kong, X-Z, Postema, MC, Guadalupe, T, de Kovel, C, Boedhoe, PSW, Hoogman, M, Mathias, SR, van Rooij, D, Schijven, D, Glahn, DC, Medland, SE, Jahanshad, N, Thomopoulos, S, Turner, JA, Buitelaar, J, van Erp, TGM, Franke, B, Fisher, SE, van den Heuvel, OA, Schmaal, L, Thompson, PM, Francks, C, Kong, X-Z, Postema, MC, Guadalupe, T, de Kovel, C, Boedhoe, PSW, Hoogman, M, Mathias, SR, van Rooij, D, Schijven, D, Glahn, DC, Medland, SE, Jahanshad, N, Thomopoulos, S, Turner, JA, Buitelaar, J, van Erp, TGM, Franke, B, Fisher, SE, van den Heuvel, OA, Schmaal, L, Thompson, PM, and Francks, C

Abstract

Left-right asymmetry of the human brain is one of its cardinal features, and also a complex, multivariate trait. Decades of research have suggested that brain asymmetry may be altered in psychiatric disorders. However, findings have been inconsistent and often based on small sample sizes. There are also open questions surrounding which structures are asymmetrical on average in the healthy population, and how variability in brain asymmetry relates to basic biological variables such as age and sex. Over the last 4 years, the ENIGMA-Laterality Working Group has published six studies of gray matter morphological asymmetry based on total sample sizes from roughly 3,500 to 17,000 individuals, which were between one and two orders of magnitude larger than those published in previous decades. A population-level mapping of average asymmetry was achieved, including an intriguing fronto-occipital gradient of cortical thickness asymmetry in healthy brains. ENIGMA's multi-dataset approach also supported an empirical illustration of reproducibility of hemispheric differences across datasets. Effect sizes were estimated for gray matter asymmetry based on large, international, samples in relation to age, sex, handedness, and brain volume, as well as for three psychiatric disorders: autism spectrum disorder was associated with subtly reduced asymmetry of cortical thickness at regions spread widely over the cortex; pediatric obsessive-compulsive disorder was associated with altered subcortical asymmetry; major depressive disorder was not significantly associated with changes of asymmetry. Ongoing studies are examining brain asymmetry in other disorders. Moreover, a groundwork has been laid for possibly identifying shared genetic contributions to brain asymmetry and disorders.

Published
2022

19. ENIGMA-DTI: Translating reproducible white matter deficits into personalized vulnerability metrics in cross-diagnostic psychiatric research

Author

Kochunov, P, Hong, LE, Dennis, EL, Morey, RA, Tate, DF, Wilde, EA, Logue, M, Kelly, S, Donohoe, G, Favre, P, Houenou, J, Ching, CRK, Holleran, L, Andreassen, OA, van Velzen, LS, Schmaal, L, Villalon-Reina, JE, Bearden, CE, Piras, F, Spalletta, G, van den Heuvel, OA, Veltman, DJ, Stein, DJ, Ryan, MC, Tan, Y, van Erp, TGM, Turner, JA, Haddad, L, Nir, TM, Glahn, DC, Thompson, PM, Jahanshad, N, Kochunov, P, Hong, LE, Dennis, EL, Morey, RA, Tate, DF, Wilde, EA, Logue, M, Kelly, S, Donohoe, G, Favre, P, Houenou, J, Ching, CRK, Holleran, L, Andreassen, OA, van Velzen, LS, Schmaal, L, Villalon-Reina, JE, Bearden, CE, Piras, F, Spalletta, G, van den Heuvel, OA, Veltman, DJ, Stein, DJ, Ryan, MC, Tan, Y, van Erp, TGM, Turner, JA, Haddad, L, Nir, TM, Glahn, DC, Thompson, PM, and Jahanshad, N

Abstract

The ENIGMA-DTI (diffusion tensor imaging) workgroup supports analyses that examine the effects of psychiatric, neurological, and developmental disorders on the white matter pathways of the human brain, as well as the effects of normal variation and its genetic associations. The seven ENIGMA disorder-oriented working groups used the ENIGMA-DTI workflow to derive patterns of deficits using coherent and coordinated analyses that model the disease effects across cohorts worldwide. This yielded the largest studies detailing patterns of white matter deficits in schizophrenia spectrum disorder (SSD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), traumatic brain injury (TBI), and 22q11 deletion syndrome. These deficit patterns are informative of the underlying neurobiology and reproducible in independent cohorts. We reviewed these findings, demonstrated their reproducibility in independent cohorts, and compared the deficit patterns across illnesses. We discussed translating ENIGMA-defined deficit patterns on the level of individual subjects using a metric called the regional vulnerability index (RVI), a correlation of an individual's brain metrics with the expected pattern for a disorder. We discussed the similarity in white matter deficit patterns among SSD, BD, MDD, and OCD and provided a rationale for using this index in cross-diagnostic neuropsychiatric research. We also discussed the difference in deficit patterns between idiopathic schizophrenia and 22q11 deletion syndrome, which is used as a developmental and genetic model of schizophrenia. Together, these findings highlight the importance of collaborative large-scale research to provide robust and reproducible effects that offer insights into individual vulnerability and cross-diagnosis features.

Published
2022

20. Cerebral blood flow and cardiovascular risk effects on resting brain regional homogeneity

Author

Adhikari, BM, Adhikari, BM, Hong, LE, Zhao, Z, Wang, DJJ, Thompson, PM, Jahanshad, N, Zhu, AH, Holiga, S, Turner, JA, van Erp, TGM, Calhoun, VD, Hatch, KS, Bruce, H, Hare, SM, Chiappelli, J, Goldwaser, EL, Kvarta, MD, Ma, Y, Du, X, Nichols, TE, Shuldiner, AR, Mitchell, BD, Dukart, J, Chen, S, Kochunov, P, Adhikari, BM, Adhikari, BM, Hong, LE, Zhao, Z, Wang, DJJ, Thompson, PM, Jahanshad, N, Zhu, AH, Holiga, S, Turner, JA, van Erp, TGM, Calhoun, VD, Hatch, KS, Bruce, H, Hare, SM, Chiappelli, J, Goldwaser, EL, Kvarta, MD, Ma, Y, Du, X, Nichols, TE, Shuldiner, AR, Mitchell, BD, Dukart, J, Chen, S, and Kochunov, P

Abstract

Regional homogeneity (ReHo) is a measure of local functional brain connectivity that has been reported to be altered in a wide range of neuropsychiatric disorders. Computed from brain resting-state functional MRI time series, ReHo is also sensitive to fluctuations in cerebral blood flow (CBF) that in turn may be influenced by cerebrovascular health. We accessed cerebrovascular health with Framingham cardiovascular risk score (FCVRS). We hypothesize that ReHo signal may be influenced by regional CBF; and that these associations can be summarized as FCVRS→CBF→ReHo. We used three independent samples to test this hypothesis. A test-retest sample of N = 30 healthy volunteers was used for test-retest evaluation of CBF effects on ReHo. Amish Connectome Project (ACP) sample (N = 204, healthy individuals) was used to evaluate association between FCVRS and ReHo and testing if the association diminishes given CBF. The UKBB sample (N = 6,285, healthy participants) was used to replicate the effects of FCVRS on ReHo. We observed strong CBF→ReHo links (p<2.5 × 10−3) using a three-point longitudinal sample. In ACP sample, marginal and partial correlations analyses demonstrated that both CBF and FCVRS were significantly correlated with the whole-brain average (p<10−6) and regional ReHo values, with the strongest correlations observed in frontal, parietal, and temporal areas. Yet, the association between ReHo and FCVRS became insignificant once the effect of CBF was accounted for. In contrast, CBF→ReHo remained significantly linked after adjusting for FCVRS and demographic covariates (p<10−6). Analysis in N = 6,285 replicated the FCVRS→ReHo effect (p = 2.7 × 10−27). In summary, ReHo alterations in health and neuropsychiatric illnesses may be partially driven by region-specific variability in CBF, which is, in turn, influenced by cardiovascular factors.

Published
2022

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

Author

ENIGMA Clinical High Risk for Psychosis Working Group, Jalbrzikowski M, Hayes RA, Wood SJ, Nordholm D, Zhou JH, Fusar-Poli P, Uhlhaas PJ, Takahashi T, Sugranyes G, Kwak YB, Mathalon DH, Katagiri N, Hooker CI, Smigielski L, Colibazzi T, Esther Via Virgili, Tang J, Koike S, Rasser PE, Michel C, Lebedeva I, Hegelstad WTV, de la Fuente-Sandoval C, Waltz JA, Mizrahi R, Corcoran CM, Resch F, Tamnes CK, Haas SS, Lemmers-Jansen ILJ, Agartz I, Allen P, Amminger GP, Andreassen OA, Atkinson K, Bachman P, Baeza I, Baldwin H, Bartholomeusz CF, Borgwardt S, Catalano S, Chee MWL, Chen X, Cho KIK, Cooper RE, Cropley VL, Dolz M, Ebdrup BH, Fortea A, Glenthøj LB, Glenthøj BY, de Haan L, Hamilton HK, Harris MA, Haut KM, He Y, Heekeren K, Heinz A, Hubl D, Hwang WJ, Kaess M, Kasai K, Kim M, Kindler J, Klaunig MJ, Koppel A, Kristensen TD, Kwon JS, Lawrie SM, Lee J, León-Ortiz P, Lin A, Loewy RL, Ma X, McGorry P, McGuire P, Mizuno M, Møller P, Moncada-Habib T, Muñoz Samons D, Nelson B, Nemoto T, Nordentoft M, Omelchenko MA, Oppedal K, Ouyang L, Pantelis C, Pariente JC, Raghava JM, Reyes-Madrigal F, Roach BJ, Røssberg JI, Rössler W, Salisbury DF, Sasabayashi D, Schall U, Schiffman J, Schlagenhauf F, Schmidt A, Sørensen ME, Suzuki M, Theodoridou A, Tomyshev AS, Tor J, Værnes TG, Velakoulis D, Venegoni GD, Vinogradov S, Wenneberg C, Westlye LT, Yamasue H, Yuan L, Yung AR, van Amelsvoort TAMJ, Turner JA, van Erp TGM, Thompson PM, and Hernaus D

Abstract

IMPORTANCE: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. OBJECTIVE: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. MAIN OUTCOMES AND MEASURES: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). RESULTS: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with those in the CHR-PS+ group, age showed a stronger negative association with left fusiform CT measures (F = 9.8; P < .001; q < .001) and left paracentral CT measures (F = 5.9; P = .005; q = .02). Effect sizes representing lower CT associated with psychosis conversion resembled patterns of CT differences observed in ENIGMA studies of schizophrenia (? = 0.35; 95% CI, 0.12 to 0.55; P = .004) and individuals with 22q11.2 microdeletion syndrome and a psychotic disorder diagnosis (? = 0.43; 95% CI, 0.20 to 0.61; P = .001). CONCLUSIONS AND RELEVANCE: This study provides evidence for widespread subtle, lower CT measures in individuals at CHR. The pattern of CT measure differences in those in the CHR-PS+ group was similar to those reported in other large-scale investigations of psychosis. Additionally, a subset of these regions displayed abnormal age associations. Widespread disruptions in CT coupled with abnormal age associations in those at CHR may point to disruptions in postnatal brain developmental processes.

Published
2021

22. Cortical and Subcortical Neuroanatomical Signatures of Schizotypy in 2,952 Individuals Assessed in a Worldwide ENIGMA Study

Author

Kirschner, M, Hodzic-Santor, B, Antoniades, M, Nenadic, I, Kircher, T, Krug, A, Fornito, A, Arnatkeviciute, A, Dannlowski, U, DeRosse, P, Baune, BT, Green, M, Quide, Y, Pantelis, C, Chan, R, Ettinger, U, Debbane, M, Derome, M, Gaser, C, Besteher, B, Diederen, K, Spencer, TJ, Fletcher, P, Roessler, W, Kumari, V, Park, H, Lemmers-Jansen, I, Gilleen, J, Allen, P, Marsman, J-B, Lebedeva, I, Kaiser, S, Fett, A-K, Sommer, I, Lariviere, S, Bernhardt, BC, Dagher, A, van Erp, TGM, Turner, JA, Thompson, PM, Aleman, A, Kirschner, M, Hodzic-Santor, B, Antoniades, M, Nenadic, I, Kircher, T, Krug, A, Fornito, A, Arnatkeviciute, A, Dannlowski, U, DeRosse, P, Baune, BT, Green, M, Quide, Y, Pantelis, C, Chan, R, Ettinger, U, Debbane, M, Derome, M, Gaser, C, Besteher, B, Diederen, K, Spencer, TJ, Fletcher, P, Roessler, W, Kumari, V, Park, H, Lemmers-Jansen, I, Gilleen, J, Allen, P, Marsman, J-B, Lebedeva, I, Kaiser, S, Fett, A-K, Sommer, I, Lariviere, S, Bernhardt, BC, Dagher, A, van Erp, TGM, Turner, JA, Thompson, PM, and Aleman, A

Published
2021

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

Author

Jalbrzikowski, M, Hayes, RA, Wood, SJ, Nordholm, D, Zhou, JH, Fusar-Poli, P, Uhlhaas, PJ, Takahashi, T, Sugranyes, G, Kwak, YB, Mathalon, DH, Katagiri, N, Hooker, CI, Smigielski, L, Colibazzi, T, Via, E, Tang, J, Koike, S, Rasser, PE, Michel, C, Lebedeva, I, Hegelstad, WTV, de la Fuente-Sandoval, C, Waltz, JA, Mizrahi, R, Corcoran, CM, Resch, F, Tamnes, CK, Haas, SS, Lemmers-Jansen, ILJ, Agartz, I, Allen, P, Amminger, GP, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Baldwin, H, Bartholomeusz, CF, Borgwardt, S, Catalano, S, Chee, MWL, Chen, X, Cho, KIK, Cooper, RE, Cropley, VL, Dolz, M, Ebdrup, BH, Fortea, A, Glenthoj, LB, Glenthoj, BY, de Haan, L, Hamilton, HK, Harris, MA, Haut, KM, He, Y, Heekeren, K, Heinz, A, Hubl, D, Hwang, WJ, Kaess, M, Kasai, K, Kim, M, Kindler, J, Klaunig, MJ, Koppel, A, Kristensen, TD, Kwon, JS, Lawrie, SM, Lee, J, Leon-Ortiz, P, Lin, A, Loewy, RL, Ma, X, McGorry, P, McGuire, P, Mizuno, M, Moller, P, Moncada-Habib, T, Munoz-Samons, D, Nelson, B, Nemoto, T, Nordentoft, M, Omelchenko, MA, Oppedal, K, Ouyang, L, Pantelis, C, Pariente, JC, Raghava, JM, Reyes-Madrigal, F, Roach, BJ, Rossberg, JI, Rossler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Schiffman, J, Schlagenhauf, F, Schmidt, A, Sorensen, ME, Suzuki, M, Theodoridou, A, Tomyshev, AS, Tor, J, Vaernes, TG, Velakoulis, D, Venegoni, GD, Vinogradov, S, Wenneberg, C, Westlye, LT, Yamasue, H, Yuan, L, Yung, AR, van Amelsvoort, TAMJ, Turner, JA, van Erp, TGM, Thompson, PM, Hernaus, D, Jalbrzikowski, M, Hayes, RA, Wood, SJ, Nordholm, D, Zhou, JH, Fusar-Poli, P, Uhlhaas, PJ, Takahashi, T, Sugranyes, G, Kwak, YB, Mathalon, DH, Katagiri, N, Hooker, CI, Smigielski, L, Colibazzi, T, Via, E, Tang, J, Koike, S, Rasser, PE, Michel, C, Lebedeva, I, Hegelstad, WTV, de la Fuente-Sandoval, C, Waltz, JA, Mizrahi, R, Corcoran, CM, Resch, F, Tamnes, CK, Haas, SS, Lemmers-Jansen, ILJ, Agartz, I, Allen, P, Amminger, GP, Andreassen, OA, Atkinson, K, Bachman, P, Baeza, I, Baldwin, H, Bartholomeusz, CF, Borgwardt, S, Catalano, S, Chee, MWL, Chen, X, Cho, KIK, Cooper, RE, Cropley, VL, Dolz, M, Ebdrup, BH, Fortea, A, Glenthoj, LB, Glenthoj, BY, de Haan, L, Hamilton, HK, Harris, MA, Haut, KM, He, Y, Heekeren, K, Heinz, A, Hubl, D, Hwang, WJ, Kaess, M, Kasai, K, Kim, M, Kindler, J, Klaunig, MJ, Koppel, A, Kristensen, TD, Kwon, JS, Lawrie, SM, Lee, J, Leon-Ortiz, P, Lin, A, Loewy, RL, Ma, X, McGorry, P, McGuire, P, Mizuno, M, Moller, P, Moncada-Habib, T, Munoz-Samons, D, Nelson, B, Nemoto, T, Nordentoft, M, Omelchenko, MA, Oppedal, K, Ouyang, L, Pantelis, C, Pariente, JC, Raghava, JM, Reyes-Madrigal, F, Roach, BJ, Rossberg, JI, Rossler, W, Salisbury, DF, Sasabayashi, D, Schall, U, Schiffman, J, Schlagenhauf, F, Schmidt, A, Sorensen, ME, Suzuki, M, Theodoridou, A, Tomyshev, AS, Tor, J, Vaernes, TG, Velakoulis, D, Venegoni, GD, Vinogradov, S, Wenneberg, C, Westlye, LT, Yamasue, H, Yuan, L, Yung, AR, van Amelsvoort, TAMJ, Turner, JA, van Erp, TGM, Thompson, PM, and Hernaus, D

Abstract

IMPORTANCE: The ENIGMA clinical high risk (CHR) for psychosis initiative, the largest pooled neuroimaging sample of individuals at CHR to date, aims to discover robust neurobiological markers of psychosis risk. OBJECTIVE: To investigate baseline structural neuroimaging differences between individuals at CHR and healthy controls as well as between participants at CHR who later developed a psychotic disorder (CHR-PS+) and those who did not (CHR-PS-). DESIGN, SETTING, AND PARTICIPANTS: In this case-control study, baseline T1-weighted magnetic resonance imaging (MRI) data were pooled from 31 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. CHR status was assessed using the Comprehensive Assessment of At-Risk Mental States or Structured Interview for Prodromal Syndromes. MRI scans were processed using harmonized protocols and analyzed within a mega-analysis and meta-analysis framework from January to October 2020. MAIN OUTCOMES AND MEASURES: Measures of regional cortical thickness (CT), surface area, and subcortical volumes were extracted from T1-weighted MRI scans. Independent variables were group (CHR group vs control group) and conversion status (CHR-PS+ group vs CHR-PS- group vs control group). RESULTS: Of the 3169 included participants, 1428 (45.1%) were female, and the mean (SD; range) age was 21.1 (4.9; 9.5-39.9) years. This study included 1792 individuals at CHR and 1377 healthy controls. Using longitudinal clinical information, 253 in the CHR-PS+ group, 1234 in the CHR-PS- group, and 305 at CHR without follow-up data were identified. Compared with healthy controls, individuals at CHR exhibited widespread lower CT measures (mean [range] Cohen d = -0.13 [-0.17 to -0.09]), but not surface area or subcortical volume. Lower CT measures in the fusiform, superior temporal, and paracentral regions were associated with psychosis conversion (mean Cohen d = -0.22; 95% CI, -0.35 to 0.10). Among healthy controls, compared with t

Published
2021

24. Approaches for estimating benefits and costs of interventions in plant biosecurity across invasion phases

Author

Welsh, MJ, Turner, JA, Epanchin-Niell, RS, Monge, JJ, Soliman, T, Robinson, AP, Kean, JM, Phillips, C, Stringer, LD, Vereijssen, J, Liebhold, AM, Kompas, T, Ormsby, M, Brockerhoff, EG, Welsh, MJ, Turner, JA, Epanchin-Niell, RS, Monge, JJ, Soliman, T, Robinson, AP, Kean, JM, Phillips, C, Stringer, LD, Vereijssen, J, Liebhold, AM, Kompas, T, Ormsby, M, and Brockerhoff, EG

Abstract

Nonnative plant pests cause billions of dollars in damages. It is critical to prevent or reduce these losses by intervening at various stages of the invasion process, including pathway risk management (to prevent pest arrival), surveillance and eradication (to counter establishment), and management of established pests (to limit damages). Quantifying benefits and costs of these interventions is important to justify and prioritize investments and to inform biosecurity policy. However, approaches for these estimations differ in (1) the assumed relationship between supply, demand, and prices, and (2) the ability to assess different types of direct and indirect costs at invasion stages, for a given arrival or establishment probability. Here we review economic approaches available to estimate benefits and costs of biosecurity interventions to inform the appropriate selection of approaches. In doing so, we complement previous studies and reviews on estimates of damages from invasive species by considering the influence of economic and methodological assumptions. Cost accounting is suitable for rapid decisions, specific impacts, and simple methodological assumptions but fails to account for feedbacks, such as market adjustments, and may overestimate long-term economic impacts. Partial equilibrium models consider changes in consumer and producer surplus due to pest impacts or interventions and can account for feedbacks in affected sectors but require specialized economic models, comprehensive data sets, and estimates of commodity supply and demand curves. More intensive computable general equilibrium models can account for feedbacks across entire economies, including capital and labor, and linkages among these. The two major considerations in choosing an approach are (1) the goals of the analysis (e.g., consideration of a single pest or intervention with a limited range of impacts vs. multiple interventions, pests or sectors), and (2) the resources available for analysis su

Published
2021

25. 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

26. Key Questions for Research and Conservation of Mesophotic Coral Ecosystems and Temperate Mesophotic Ecosystems

Author

Turner, JA, Andradi-Brown, DA, Gori, A, Bongaerts, P, Burdett, HL, Ferrier-Pagès, C, Voolstra, CR, Weinstein, DK, Bridge, TCL, Costantini, F, Gress, E, Laverick, J, Loya, Y, Goodbody-Gringley, G, Rossi, S, Taylor, ML, Viladrich, N, Voss, J, Williams, J, Woodall, LC, Eyal, G, and Puglise, K

Abstract

Mesophotic coral ecosystems (MCEs) and temperate mesophotic ecosystems (TMEs) have received increasing research attention during the last decade as many new and improved methods and technologies have become more accessible to explore deeper parts of the ocean. However, large voids in knowledge remain in our scientific understanding, limiting our ability to make scientifically based decisions for conservation and management of these ecosystems. Here, we present a list of key research and conservation questions to enhance progress in the field. Questions were generated following an initial open call to MCE and TME experts, representing a range of career levels, interests, organizations (including academia, governmental, and nongovernmental), and geographic locations. Questions were refined and grouped into eight broad themes: (1) Distribution, (2) Environmental and Physical Processes, (3) Biodiversity and Community Structure, (4) Ecological Processes, (5) Connectivity, (6) Physiology, (7) Threats, and (8) Management and Policy.

Published
2020

27. 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

28. M156. CORTICAL NEUROANATOMICAL SIGNATURE OF SCHIZOTYPY IN 2,695 INDIVIDUALS ASSESSED IN A WORLDWIDE ENIGMA STUDY

Author

Antoniades, M, Nenadic, I, Kircher, T, Krug, A, Meller, T, Grotegerd, D, Fornito, A, Arnatkeviciute, A, Dannlowski, U, DeRosse, P, Moyett, A, Baune, B, Green, M, Quide, Y, Pantelis, C, Chan, RCK, Wang, Y, Ettinger, U, Debbane, M, Derome, M, Gaser, C, Besteher, B, Diederen, K, Spencer, T, Rössler, W, Smigielski, L, Kumari, V, Park, H, Wiebels, K, Lemmers-Jansen, I, Allen, P, Kozhuharova, P, Marsman, J-B, Gilleen, J, Kirschner, M, Dagher, A, Lebedeva, I, Tomyshev, A, Kaiser, S, Fett, A-K, Sommer, I, van Erp, TGM, Turner, JA, Thompson, PM, Aleman, A, Modinos, G, Antoniades, M, Nenadic, I, Kircher, T, Krug, A, Meller, T, Grotegerd, D, Fornito, A, Arnatkeviciute, A, Dannlowski, U, DeRosse, P, Moyett, A, Baune, B, Green, M, Quide, Y, Pantelis, C, Chan, RCK, Wang, Y, Ettinger, U, Debbane, M, Derome, M, Gaser, C, Besteher, B, Diederen, K, Spencer, T, Rössler, W, Smigielski, L, Kumari, V, Park, H, Wiebels, K, Lemmers-Jansen, I, Allen, P, Kozhuharova, P, Marsman, J-B, Gilleen, J, Kirschner, M, Dagher, A, Lebedeva, I, Tomyshev, A, Kaiser, S, Fett, A-K, Sommer, I, van Erp, TGM, Turner, JA, Thompson, PM, Aleman, A, and Modinos, G

Abstract

Background Cortical neuroanatomical abnormalities have been reported along a continuum between individuals with chronic schizophrenia, first-episode psychosis, clinical high risk for psychosis, and healthy individuals self-reporting subclinical psychotic-like experiences (or schizotypy). Recently, the Schizophrenia Working Group within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium provided meta-analytic evidence for robust cortical thickness abnormalities in schizophrenia, while also indicating that these abnormalities are influenced by illness severity and treatment with antipsychotic medications. In this context, schizotypy research allows the investigation of cortical neuroanatomy associated with the expression of subclinical psychotic-like symptoms without the potential influence of a psychotic illness, its severity, or the use of antipsychotics. This study presents the first large-scale imaging meta-analysis of cortical thickness in schizotypy using standardized methods from 23 datasets worldwide. Methods Cortical thickness and surface area were assessed in MRI scans of 2,695 healthy individuals (mean [range] age of 29.1 [17–55.8], 46.3% male) who had also completed validated self-report schizotypy questionnaires. Each site processed their local T1-weighted MRI scans using FreeSurfer and, following the protocol outlined in the ENIGMA Schizophrenia Working Group study, extracted cortical thickness for 70 Desikan-Killiany (DK) atlas regions (34 regions per hemisphere + left and right hemisphere mean thickness). At each site, partial correlation analyses were performed between regional cortical thickness by ROI and total schizotypy scores in R, predicting the left, right and mean cortical thickness, adjusting for sex, age and site. Random-effects meta-analyses of partial correlation effect sizes for each of the DK atlas regions were performed using R’s metafor package. False discovery rate (pFDR < .05) was used to c

Published
2020

29. 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

30. The Association Between Familial Risk and Brain Abnormalities Is Disease Specific: An ENIGMA-Relatives Study of Schizophrenia and Bipolar Disorder

Author

de Zwarte, SMC, Brouwer, RM, Agartz, I, Alda, M, Aleman, A, Alpert, KI, Bearden, CE, Bertolino, A, Bois, C, Bonvino, A, Bramon, E, Buimer, EEL, Cahn, W, Cannon, DM, Cannon, TD, Caseras, X, Castro-Fornieles, J, Chen, Q, Chung, Y, De la Serna, E, Di Giorgio, A, Doucet, GE, Eker, MC, Erk, S, Fears, SC, Foley, SF, Frangou, S, Frankland, A, Fullerton, JM, Glahn, DC, Goghari, VM, Goldman, AL, Gonul, AS, Gruber, O, de Haan, L, Hajek, T, Hawkins, EL, Heinz, A, Hillegers, MHJ, Hulshoff Pol, HE, Hultman, CM, Ingvar, M, Johansson, V, Jönsson, EG, Kane, F, Kempton, MJ, Koenis, MMG, Kopecek, M, Krabbendam, L, Krämer, B, Lawrie, SM, Lenroot, RK, Marcelis, M, Marsman, JBC, Mattay, VS, McDonald, C, Meyer-Lindenberg, A, Michielse, S, Mitchell, PB, Moreno, D, Murray, RM, Mwangi, B, Najt, P, Neilson, E, Newport, J, van Os, J, Overs, B, Ozerdem, A, Picchioni, MM, Richter, A, Roberts, G, Aydogan, AS, Schofield, PR, Simsek, F, Soares, JC, Sugranyes, G, Toulopoulou, T, Tronchin, G, Walter, H, Wang, L, Weinberger, DR, Whalley, HC, Yalin, N, Andreassen, OA, Ching, CRK, van Erp, TGM, Turner, JA, Jahanshad, N, Thompson, PM, Kahn, RS, van Haren, NEM, de Zwarte, SMC, Brouwer, RM, Agartz, I, Alda, M, Aleman, A, Alpert, KI, Bearden, CE, Bertolino, A, Bois, C, Bonvino, A, Bramon, E, Buimer, EEL, Cahn, W, Cannon, DM, Cannon, TD, Caseras, X, Castro-Fornieles, J, Chen, Q, Chung, Y, De la Serna, E, Di Giorgio, A, Doucet, GE, Eker, MC, Erk, S, Fears, SC, Foley, SF, Frangou, S, Frankland, A, Fullerton, JM, Glahn, DC, Goghari, VM, Goldman, AL, Gonul, AS, Gruber, O, de Haan, L, Hajek, T, Hawkins, EL, Heinz, A, Hillegers, MHJ, Hulshoff Pol, HE, Hultman, CM, Ingvar, M, Johansson, V, Jönsson, EG, Kane, F, Kempton, MJ, Koenis, MMG, Kopecek, M, Krabbendam, L, Krämer, B, Lawrie, SM, Lenroot, RK, Marcelis, M, Marsman, JBC, Mattay, VS, McDonald, C, Meyer-Lindenberg, A, Michielse, S, Mitchell, PB, Moreno, D, Murray, RM, Mwangi, B, Najt, P, Neilson, E, Newport, J, van Os, J, Overs, B, Ozerdem, A, Picchioni, MM, Richter, A, Roberts, G, Aydogan, AS, Schofield, PR, Simsek, F, Soares, JC, Sugranyes, G, Toulopoulou, T, Tronchin, G, Walter, H, Wang, L, Weinberger, DR, Whalley, HC, Yalin, N, Andreassen, OA, Ching, CRK, van Erp, TGM, Turner, JA, Jahanshad, N, Thompson, PM, Kahn, RS, and van Haren, NEM

Abstract

Background: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. Methods: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. Results: FDRs-BD had significantly larger ICV (d = +0.16, q <.05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = −0.12, q <.05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d < −0.09, q <.05 corrected); and third ventricle was larger (d = +0.15, q <.05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. Conclusions: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

Published
2019

31. High and low levels of an NTRK2-driven genetic profile affect motor- and cognition-associated frontal gray matter in prodromal Huntington’s disease

Author

Ciarochi, JA, Liu, J, Calhoun, V, Johnson, H, Misiura, M, Bockholt, HJ, Espinoza, FA, Caprihan, A, Plis, S, Turner, JA, Paulsen, JS, Long, JD, Johnson, HJ, Brashers-Krug, T, Danzer, P, Miller, A, Montross, K, Harrington, D, Westervelt, H, Aylward, E, Rao, S, Moser, DJ, Williams, J, Downing, N, Magnotta, VA, Vaidya, J, O Leary, D, Kim, EY, Kim, JI, Lourens, S, Zhang, Y, Lu, W, Erwin, C, Nance, M, Evans, J, Zschiegner, R, Chiu, E, Loi, S, Chua, P, Raymond, L, Ross, CA, Mallonee, WM, Samii, A, Jones, R, Barker, RA, McCusker, E, Loy, C, Orth, M, Süßmuth, S, Quaid, K, Guttman, M, Perlman, S, Geschwind, MD, Sha, S, Warner, T, Rosser, A, Marshall, F, Panegyres, P, Lee, J, Perlmutter, J, Miedzybrodzka, Z, Craufurd, D, Mazzoni, P, Marder, K, Kumar, R, Wheelock, V, Martin, W, Suchowersky, O, Ahmed, A, De Soriano, I, Shadrick, C, Preston, J, Goh, A, Antonopoulos, S, Komiti, A, Decolongon, J, Fan, M, Coleman, A, Varvaris, M, Ong, M, Yoritomo, N, Suter, G, Freney, EP, Macaraeg, A, Wood-Siverio, C, Factor, SA, Mason, S, Guzman, NV, Griffith, J, McMillan, J, Raymond, Lucy [0000-0003-2652-3355], Barker, Roger [0000-0001-8843-7730], Mason, Sarah [0000-0001-6715-4109], and Apollo - University of Cambridge Repository

Subjects
supplementary motor, independent component analysis, tropomyosin receptor kinase B, brain-derived neurotrophic factor, Huntington’s disease
Abstract

This study assessed how BDNF (brain-derived neurotrophic factor) and other genes involved in its signaling influence brain structure and clinical functioning in pre-diagnosis Huntington’s disease (HD). Parallel independent component analysis (pICA), a multivariate method for identifying correlated patterns in multimodal datasets, was applied to gray matter concentration (GMC) and genomic data from a sizeable PREDICT-HD prodromal cohort (N = 715). pICA identified a genetic component highlighting NTRK2, which encodes BDNF’s TrkB receptor, that correlated with a GMC component including supplementary motor, precentral/premotor cortex, and other frontal areas (p < 0.001); this association appeared to be driven by participants with high or low levels of the genetic profile. The frontal GMC profile correlated with cognitive and motor variables (Trail Making Test A (p = 0.03); Stroop Color (p = 0.017); Stroop Interference (p = 0.04); Symbol Digit Modalities Test (p = 0.031); Total Motor Score (p = 0.01)). A top-weighted NTRK2 variant (rs2277193) was protectively associated with Trail Making Test B (p = 0.007); greater minor allele numbers were linked to a better performance. These results support the idea of a protective role of NTRK2 in prodromal HD, particularly in individuals with certain genotypes, and suggest that this gene may influence the preservation of frontal gray matter that is important for clinical functioning.

Published
2018

33. Deep Learning for Quality Control of Subcortical Brain 3D Shape Models

Author

Petrov, D, Reuter, Martin1, Wachinger, Christian, Lombaert, Hervé, Paniagua, Beatriz, Lüthi, Marcel, Egger, Bernhard, Petrov, D, Gutman, BA, Kuznetsov, E, Ching, CRK, Alpert, K, Zavaliangos-Petropulu, A, Isaev, D, Turner, JA, van Erp, TGM, Wang, L, Schmaal, L, Veltman, D, Thompson, PM, Petrov, D, Reuter, Martin1, Wachinger, Christian, Lombaert, Hervé, Paniagua, Beatriz, Lüthi, Marcel, Egger, Bernhard, Petrov, D, Gutman, BA, Kuznetsov, E, Ching, CRK, Alpert, K, Zavaliangos-Petropulu, A, Isaev, D, Turner, JA, van Erp, TGM, Wang, L, Schmaal, L, Veltman, D, and Thompson, PM

Abstract

We present several deep learning models for assessing the morphometric fidelity of deep grey matter region models extracted from brain MRI. We test three different convolutional neural net architectures (VGGNet, ResNet and Inception) over 2D maps of geometric features. Further, we present a novel geometry feature augmentation technique based on parametric spherical mapping. Finally, we present an approach for model decision visualization, allowing human raters to see the areas of subcortical shapes most likely to be deemed of failing quality by the machine. Our training data is comprised of 5200 subjects from the ENIGMA Schizophrenia MRI cohorts, and our test dataset contains 1500 subjects from the ENIGMA Major Depressive Disorder cohorts. Our final models reduce human rater time by 46–70%. ResNet outperforms VGGNet and Inception for all of our predictive tasks.

Published
2018

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

Author

van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, W, Glahn, DC, Pearlson, GD, Yao, N, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Pol, HEH, Kahn, RS, Ophoff, RA, van Haren, NEM, Andreassen, OA, Dale, AM, Nhat, TD, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jorgensen, KN, Lagerberg, T, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santianez, R, Tordesillas-Gutierrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quide, Y, Schall, U, Scott, RJ, Cairns, MJ, Seal, M, Tooney, PA, Rasser, PE, Cooper, G, Weickert, CS, Weickert, TW, Morris, DW, Hong, E, Kochunov, P, Beard, LM, Gur, RE, Gur, RC, Satterthwaite, TD, Wolf, DH, Belger, A, Brown, GG, Ford, JM, Macciardi, F, Mathalon, DH, O'Leary, DS, Potkin, SG, Preda, A, Voyvodic, J, Lim, KO, McEwen, S, Yang, F, Tan, Y, Tan, S, Wang, Z, Fan, F, Chen, J, Xiang, H, Tang, S, Guo, H, Wan, P, Wei, D, Bockholt, HJ, Ehrlich, S, Wolthusen, RPF, King, MD, Shoemaker, JM, Sponheim, SR, De Haan, L, Koenders, L, Machielsen, MW, van Amelsvoort, T, Veltman, DJ, Assogna, F, Banaj, N, de Rossi, P, Iorio, M, Piras, F, Spalletta, G, McKenna, PJ, Pomarol-Clotet, E, Salvador, R, Corvin, A, Donohoe, G, Kelly, S, Whelan, CD, Dickie, EW, Rotenberg, D, Voineskos, AN, Ciufolini, S, Radua, J, Dazzan, P, Murray, R, Marques, TR, Simmons, A, Borgwardt, S, Egloff, L, Harrisberger, F, Riecher-Roessler, A, Smieskova, R, Alpert, K, Wang, L, Jonsson, EG, Koops, S, Sommer, IEC, Bertolino, A, Bonvino, A, Di Giorgio, A, Neilson, E, Mayer, AR, Stephen, JM, Kwon, JS, Yun, J-Y, Cannon, DM, McDonald, C, Lebedeva, I, Tomyshev, AS, Akhadov, T, Kaleda, V, Fatouros-Bergman, H, Flyckt, L, Busatto, GF, Rosa, PGP, Serpa, MH, Zanetti, M, Hoschl, C, Skoch, A, Spaniel, F, Tomecek, D, Hagenaars, SP, McIntosh, AM, Whalley, HC, Lawrie, SM, Knoechel, C, Oertel-Knoechel, V, Staeblein, M, Howells, FM, Stein, DJ, Temmingh, HS, Uhlmann, A, Lopez-Jaramillo, C, Dima, D, McMahon, A, Faskowitz, J, Gutman, BA, Jahanshad, N, Thompson, PM, Turner, JA, van Erp, TGM, Walton, E, Hibar, DP, Schmaal, L, Jiang, W, Glahn, DC, Pearlson, GD, Yao, N, Fukunaga, M, Hashimoto, R, Okada, N, Yamamori, H, Bustillo, JR, Clark, VP, Agartz, I, Mueller, BA, Cahn, W, de Zwarte, SMC, Pol, HEH, Kahn, RS, Ophoff, RA, van Haren, NEM, Andreassen, OA, Dale, AM, Nhat, TD, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jorgensen, KN, Lagerberg, T, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santianez, R, Tordesillas-Gutierrez, D, Loughland, C, Carr, VJ, Catts, S, Cropley, VL, Fullerton, JM, Green, MJ, Henskens, FA, Jablensky, A, Lenroot, RK, Mowry, BJ, Michie, PT, Pantelis, C, Quide, Y, Schall, U, Scott, RJ, Cairns, MJ, Seal, M, Tooney, PA, Rasser, PE, Cooper, G, Weickert, CS, Weickert, TW, Morris, DW, Hong, E, Kochunov, P, Beard, LM, Gur, RE, Gur, RC, Satterthwaite, TD, Wolf, DH, Belger, A, Brown, GG, Ford, JM, Macciardi, F, Mathalon, DH, O'Leary, DS, Potkin, SG, Preda, A, Voyvodic, J, Lim, KO, McEwen, S, Yang, F, Tan, Y, Tan, S, Wang, Z, Fan, F, Chen, J, Xiang, H, Tang, S, Guo, H, Wan, P, Wei, D, Bockholt, HJ, Ehrlich, S, Wolthusen, RPF, King, MD, Shoemaker, JM, Sponheim, SR, De Haan, L, Koenders, L, Machielsen, MW, van Amelsvoort, T, Veltman, DJ, Assogna, F, Banaj, N, de Rossi, P, Iorio, M, Piras, F, Spalletta, G, McKenna, PJ, Pomarol-Clotet, E, Salvador, R, Corvin, A, Donohoe, G, Kelly, S, Whelan, CD, Dickie, EW, Rotenberg, D, Voineskos, AN, Ciufolini, S, Radua, J, Dazzan, P, Murray, R, Marques, TR, Simmons, A, Borgwardt, S, Egloff, L, Harrisberger, F, Riecher-Roessler, A, Smieskova, R, Alpert, K, Wang, L, Jonsson, EG, Koops, S, Sommer, IEC, Bertolino, A, Bonvino, A, Di Giorgio, A, Neilson, E, Mayer, AR, Stephen, JM, Kwon, JS, Yun, J-Y, Cannon, DM, McDonald, C, Lebedeva, I, Tomyshev, AS, Akhadov, T, Kaleda, V, Fatouros-Bergman, H, Flyckt, L, Busatto, GF, Rosa, PGP, Serpa, MH, Zanetti, M, Hoschl, C, Skoch, A, Spaniel, F, Tomecek, D, Hagenaars, SP, McIntosh, AM, Whalley, HC, Lawrie, SM, Knoechel, C, Oertel-Knoechel, V, Staeblein, M, Howells, FM, Stein, DJ, Temmingh, HS, Uhlmann, A, Lopez-Jaramillo, C, Dima, D, McMahon, A, Faskowitz, J, Gutman, BA, Jahanshad, N, Thompson, PM, and Turner, JA

Abstract

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia.

Published
2018

35. Index

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

36. Back Cover

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

41. Bibliography

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

42. Notes

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

45. Acknowledgments

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

48. Series List

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

49. Cover

Author

Sutter, Paul S. and Turner, James Morton

Published
2022

50. The Research Diagnostic Criteria for Temporomandibular disorders. IV: evaluation of psychometric properties of the axis II measures.

Author

Ohrbach R, Turner JA, Sherman JJ, Mancl LA, Truelove EL, Schiffman EL, and Dworkin SF

Abstract

AIMS: To evaluate the psychometric properties of the Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) biobehavioral (Axis II) screening instruments. METHODS: Participants with Axis I TMD diagnoses (n = 626) completed the Axis II instruments (Depression, Nonspecific Physical Symptoms, Graded Chronic Pain) and other instruments assessing psychological distress, pain, and disability at three study sites. Internal consistency, temporal stability, and convergent/discriminant validity of the Axis II measures were assessed. To assess criterion validity of Nonspecific Physical Symptoms and Depression instruments as screeners, 170 participants completed a structured psychiatric diagnostic interview. RESULTS: The Axis II instruments showed very good to excellent internal consistency (Cronbach's alpha coefficients = 0.80 to 0.95). Their convergent (correlation range 0.3 to 0.9) and discriminant (range 0.0 to 0.6) validity were generally supported, although Nonspecific Physical Symptoms was more strongly associated with depressive than with somatic symptoms. Temporal stability was high for characteristic pain intensity (Lin's correlation concordance coefficient [CCC] = 0.91), interference (CCC = 0.89), and chronic pain grade (weighted kappa = 0.87), and fair to good for Depression and Nonspecific Physical Symptoms (CCC = 0.63 to 0.78). The Depression instrument normal versus moderate to severe cutoff point was good at identifying current-year depression and dysthymia diagnoses (sensitivity 87%, specificity 53%). Nonspecific Physical Symptoms did not have high utility for detecting psychiatric disorders (sensitivity 86%, specificity 31%). CONCLUSION: The Axis-II Depression and Graded Chronic Pain instruments have clinically relevant and acceptable psychometric properties for reliability and validity and utility as instruments for identifying TMD patients with high levels of distress, pain, and disability that can interfere with treatment response and course of Axis I disorders. [ABSTRACT FROM AUTHOR]

Published
2010

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