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1. Widespread white matter microstructural differences in schizophrenia across 4322 individuals: results from the ENIGMA Schizophrenia DTI Working Group

Author

Kelly, S, Jahanshad, N, Zalesky, A, Kochunov, P, Agartz, I, Alloza, C, Andreassen, OA, Arango, C, Banaj, N, Bouix, S, Bousman, CA, Brouwer, RM, Bruggemann, J, Bustillo, J, Cahn, W, Calhoun, V, Cannon, D, Carr, V, Catts, S, Chen, J, Chen, J-X, Chen, X, Chiapponi, C, Cho, Kl K, Ciullo, V, Corvin, AS, Crespo-Facorro, B, Cropley, V, De Rossi, P, Diaz-Caneja, CM, Dickie, EW, Ehrlich, S, Fan, F-M, Faskowitz, J, Fatouros-Bergman, H, Flyckt, L, Ford, JM, Fouche, J-P, Fukunaga, M, Gill, M, Glahn, DC, Gollub, R, Goudzwaard, ED, Guo, H, Gur, RE, Gur, RC, Gurholt, TP, Hashimoto, R, Hatton, SN, Henskens, FA, Hibar, DP, Hickie, IB, Hong, LE, Horacek, J, Howells, FM, Hulshoff Pol, HE, Hyde, CL, Isaev, D, Jablensky, A, Jansen, PR, Janssen, J, Jönsson, EG, Jung, LA, Kahn, RS, Kikinis, Z, Liu, K, Klauser, P, Knöchel, C, Kubicki, M, Lagopoulos, J, Langen, C, Lawrie, S, Lenroot, RK, Lim, KO, Lopez-Jaramillo, C, Lyall, A, Magnotta, V, Mandl, RCW, Mathalon, DH, McCarley, RW, McCarthy-Jones, S, McDonald, C, McEwen, S, McIntosh, A, Melicher, T, Mesholam-Gately, RI, Michie, PT, Mowry, B, Mueller, BA, Newell, DT, O'Donnell, P, Oertel-Knöchel, V, Oestreich, L, Paciga, SA, Pantelis, C, Pasternak, O, Pearlson, G, Pellicano, GR, Pereira, A, and Pineda Zapata, J

Subjects
Neurosciences, Brain Disorders, Mental Health, Serious Mental Illness, Biomedical Imaging, Schizophrenia, Clinical Research, Mental health, Adult, Aged, Aged, 80 and over, Brain, Cohort Studies, Corpus Callosum, Diffusion Magnetic Resonance Imaging, Diffusion Tensor Imaging, Female, Humans, Image Processing, Computer-Assisted, Male, Middle Aged, White Matter, Young Adult, Biological Sciences, Medical and Health Sciences, Psychology and Cognitive Sciences, Psychiatry
Abstract

The regional distribution of white matter (WM) abnormalities in schizophrenia remains poorly understood, and reported disease effects on the brain vary widely between studies. In an effort to identify commonalities across studies, we perform what we believe is the first ever large-scale coordinated study of WM microstructural differences in schizophrenia. Our analysis consisted of 2359 healthy controls and 1963 schizophrenia patients from 29 independent international studies; we harmonized the processing and statistical analyses of diffusion tensor imaging (DTI) data across sites and meta-analyzed effects across studies. Significant reductions in fractional anisotropy (FA) in schizophrenia patients were widespread, and detected in 20 of 25 regions of interest within a WM skeleton representing all major WM fasciculi. Effect sizes varied by region, peaking at (d=0.42) for the entire WM skeleton, driven more by peripheral areas as opposed to the core WM where regions of interest were defined. The anterior corona radiata (d=0.40) and corpus callosum (d=0.39), specifically its body (d=0.39) and genu (d=0.37), showed greatest effects. Significant decreases, to lesser degrees, were observed in almost all regions analyzed. Larger effect sizes were observed for FA than diffusivity measures; significantly higher mean and radial diffusivity was observed for schizophrenia patients compared with controls. No significant effects of age at onset of schizophrenia or medication dosage were detected. As the largest coordinated analysis of WM differences in a psychiatric disorder to date, the present study provides a robust profile of widespread WM abnormalities in schizophrenia patients worldwide. Interactive three-dimensional visualization of the results is available at www.enigma-viewer.org.

Published
2018

2. Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC

Author

Rootes-Murdy, K, Panta, S, Kelly, R, Romero, J, Quide, Y, Cairns, MJ, Loughland, C, Carr, VJ, Catts, S, Jablensky, A, Green, MJ, Henskens, F, Kiltschewskij, D, Michie, PT, Mowry, B, Pantelis, C, Rasser, PE, Reay, WR, Schall, U, Scott, RJ, Watkeys, OJ, Roberts, G, Mitchell, PB, Fullerton, JM, Overs, BJ, Kikuchi, M, Hashimoto, R, Matsumoto, J, Fukunaga, M, Sachdev, PS, Brodaty, H, Wen, W, Jiang, J, Fani, N, Ely, TD, Lorio, A, Stevens, JS, Ressler, K, Jovanovic, T, van Rooij, SJH, Federmann, LM, Jockwitz, C, Teumer, A, Forstner, AJ, Caspers, S, Cichon, S, Plis, SM, Sarwate, AD, Calhoun, VD, Rootes-Murdy, K, Panta, S, Kelly, R, Romero, J, Quide, Y, Cairns, MJ, Loughland, C, Carr, VJ, Catts, S, Jablensky, A, Green, MJ, Henskens, F, Kiltschewskij, D, Michie, PT, Mowry, B, Pantelis, C, Rasser, PE, Reay, WR, Schall, U, Scott, RJ, Watkeys, OJ, Roberts, G, Mitchell, PB, Fullerton, JM, Overs, BJ, Kikuchi, M, Hashimoto, R, Matsumoto, J, Fukunaga, M, Sachdev, PS, Brodaty, H, Wen, W, Jiang, J, Fani, N, Ely, TD, Lorio, A, Stevens, JS, Ressler, K, Jovanovic, T, van Rooij, SJH, Federmann, LM, Jockwitz, C, Teumer, A, Forstner, AJ, Caspers, S, Cichon, S, Plis, SM, Sarwate, AD, and Calhoun, VD

Abstract

Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns (n = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders.

Published
2024

3. 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

4. Virtual Ontogeny of Cortical Growth Preceding Mental Illness

Author

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

Abstract

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

Published
2022

5. Altered Functional Connectivity and Cognition Persists 4 Years After a Transient Ischemic Attack or Minor Stroke

Author

Nicolas, K, Goodin, P, Visser, MM, Michie, PT, Bivard, A, Levi, C, Parsons, MW, Karayanidis, F, Nicolas, K, Goodin, P, Visser, MM, Michie, PT, Bivard, A, Levi, C, Parsons, MW, and Karayanidis, F

Abstract

Background and Purpose: Altered executive functions and resting-state functional connectivity (rsFC) are common following a minor stroke or transient ischemic attack (TIA). However, the long-term persistence of these abnormalities is not well-studied. We investigated whether there were cognitive and rsFC differences between (a) controls and minor cerebrovascular event (CVE) patients and (b) between CVE patients with and without an imaging confirmed infarct (i.e., minor stroke and TIA, respectively) at an average of 3.8 years following their event. Methods: Structural and resting-state imaging and cognitive assessments including the Montreal Cognitive Assessment, the Trail Making Task and the National Institute of Health (NIH) Cognition Toolbox were conducted on 42 patients (minor stroke = 17, TIA = 25) and 20 healthy controls (total N = 62). Results: Controls performed better than patients on two measures of executive functioning (both p < 0.046) and had reduced rsFC between the frontoparietal and default mode networks (FPN and DMN, respectively; p = 0.035). No cognitive differences were found between minor stroke and TIA patients, however, rsFC differences were found within the FPN and the DMN (both p < 0.013). Specifically, increased connectivity within the FPN was associated with faster performance in the minor stroke group but not the TIA group (p = 0.047). Conclusions: These findings suggest that transient or relatively minor cerebrovascular events are associated with persistent disruption of functional connectivity of neural networks and cognitive performance. These findings suggest a need for novel interventions beyond secondary prevention to reduce the risk of persistent cognitive deficits.

Published
2021

6. Effect of Immune Activation during Early Gestation or Late Gestation on Inhibitory Markers in Adult Male Rats

Author

Rahman, T, Weickert, CS, Harms, L, Meehan, C, Schall, U, Todd, J, Hodgson, DM, Michie, PT, Purves-Tyson, T, Rahman, T, Weickert, CS, Harms, L, Meehan, C, Schall, U, Todd, J, Hodgson, DM, Michie, PT, and Purves-Tyson, T

Abstract

People with schizophrenia exhibit deficits in inhibitory neurons and cognition. The timing of maternal immune activation (MIA) may present distinct schizophrenia-like phenotypes in progeny. We investigated whether early gestation [gestational day (GD) 10] or late gestation (GD19) MIA, via viral mimetic polyI:C, produces deficits in inhibitory neuron indices (GAD1, PVALB, SST, SSTR2 mRNAs) within cortical, striatal, and hippocampal subregions of male adult rat offspring. In situ hybridisation revealed that polyI:C offspring had: (1) SST mRNA reductions in the cingulate cortex and nucleus accumbens shell, regardless of MIA timing; (2) SSTR2 mRNA reductions in the cortex and striatum of GD19, but not GD10, MIA; (3) no alterations in cortical or striatal GAD1 mRNA of polyI:C offspring, but an expected reduction of PVALB mRNA in the infralimbic cortex, and; (4) no alterations in inhibitory markers in hippocampus. Maternal IL-6 response negatively correlated with adult offspring SST mRNA in cortex and striatum, but not hippocampus. These results show lasting inhibitory-related deficits in cortex and striatum in adult offspring from MIA. SST downregulation in specific cortical and striatal subregions, with additional deficits in somatostatin-related signalling through SSTR2, may contribute to some of the adult behavioural changes resulting from MIA and its timing.

Published
2020

7. Erratum: A Neuroethics Framework for the Australian Brain Initiative (Neuron (2019) 101(3) (365–369), (S0896627319300054), (10.1016/j.neuron.2019.01.004))

Author

Carter, A, Richards, LJ, Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, PG, Fitzgibbon, BM, Forlini, C, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, AJ, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, T, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, Waters, A, Carter, A, Richards, LJ, Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, PG, Fitzgibbon, BM, Forlini, C, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, AJ, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, T, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, and Waters, A

Abstract

(Neuron 101, 365–369; February 6, 2019) In the original publication of this NeuroView, the member list for the Australian Brain Alliance was omitted. This has now been corrected online. Neuron apologizes for the error.

Published
2020

8. Correction : A Neuroethics Framework for the Australian Brain Initiative (Neuron (2019) 101(3) (365–369), (S0896627319300054), (10.1016/j.neuron.2019.01.004))

Author

Carter, Adrian, Richards, Linda J., Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, Michael, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, Peter, Fitzgibbon, BM, Forlini, Cynthia, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, Andrew J, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, Timothy, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, Waters, A, Carter, Adrian, Richards, Linda J., Apthorp, D, Azghadi, MR, Badcock, DR, Balleine, B, Bekkers, JM, Berk, Michael, Bourne, JA, Bradley, AP, Breakspear, M, Brichta, A, Carter, O, Castles, A, Chakli, K, Cohen-Woods, S, Conn, SJ, Cornish, J, Cornish, K, de Zubicaray, G, Egan, GF, Enticott, Peter, Fitzgibbon, BM, Forlini, Cynthia, Fornito, A, Griffiths, L, Gullifer, J, Hall, W, Halliday, G, Hannan, AJ, Harrer, S, Harvey, A, Hatherly, C, Hickie, IB, Kennett, J, Kiernan, M, Kilpatrick, T, Kiral-Kornek, I, Korgaonkar, MS, Lawrence, Andrew J, Leventer, R, Levy, N, Licinio, J, Lovell, N, Mackellar, G, Malcolm, L, Mason, A, Mattingley, JB, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Poole-Warren, L, Sah, P, Sarnyai, Z, Schofield, PR, Shimoni, O, Shum, DHK, Silk, Timothy, Slee, M, Smith, AE, Soulis, T, Sriram, S, Stuart, GJ, Tapson, J, Thompson, MB, van Schaik, A, Vincent, NA, Vissel, B, and Waters, A

Published
2020

9. 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

10. Cognition in the First Year After a Minor Stroke, Transient Ischemic Attack, or Mimic Event and the Role of Vascular Risk Factors

Author

Nicolas, K, Levi, C, Evans, T-J, Michie, PT, Magin, P, Quain, D, Bivard, A, Karayanidis, F, Nicolas, K, Levi, C, Evans, T-J, Michie, PT, Magin, P, Quain, D, Bivard, A, and Karayanidis, F

Abstract

Background: Cognitive impairment following a minor stroke or transient ischemic attack (TIA) is common; however, due to diagnostic difficulties, the prevalence and underlying cause of impairment remain poorly defined. We compared cognition in patients after a minor stroke, TIA, or mimic event at three time points in the first year following the event. We examine whether cognitive impairment occurs following these events and whether this impairment differs based on the event type. Further, we measure whether these findings persist after controlling for age, education, and the presence of vascular risk factors and whether the presence of vascular risk factors, independent of event etiology, is associated with cognitive impairment. Lastly, we investigate whether increased stroke risk, as assessed by the ABCD2, is associated with reduced cognition. Methods: Medical information, a cognitive screening test, and a measure of executive functioning were collected from 613 patients (123 minor stroke, 175 TIA, and 315 mimics) using phone interviews at three time points in the first year following the event. Linear mixed models were used to determine the effect of event type, vascular risk factors, and predicted stroke risk on cognitive performance while controlling for confounders. Results: There was no relationship between event type and performance on either cognitive measure. When all confounders are controlled for, performance on the cognitive screening test was uniquely accounted for by the presence of heart failure, myocardial infarction, angina, and hypertension (all p < 0.047), whereas the measure of executive functioning was uniquely accounted for by the presence of hypertension and angina (all p < 0.032). Increased stroke risk also predicted performance on the cognitive screening test and the measure of executive functioning (all p < 0.002). Conclusions: Our findings indicate that cognitive impairment following a minor stroke or TIA may be attributed to the high prev

Published
2020

11. 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, Hulshoff Pol, HE, Kahn, RS, Ophoff, RA, van Haren, NEM, Andreassen, OA, Dale, AM, Doan, NT, Gurholt, TP, Hartberg, CB, Haukvik, UK, Jørgensen, KN, Lagerberg, TV, Melle, I, Westlye, LT, Gruber, O, Kraemer, B, Richter, A, Zilles, D, Calhoun, VD, Crespo-Facorro, B, Roiz-Santiañez, R, Tordesillas-Gutiérrez, 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, Quidé, Y, Schall, U, and Scott, RJ

Abstract

© 2018 Society of Biological Psychiatry 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
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12. Genome-wide association study reveals greater polygenic loading for schizophrenia in cases with a family history of illness

Author

Bigdeli, T. B, Ripke, S, Bacanu, Sa, Lee, S. H, Wray, Nr, Gejman, P. V, Rietschel, M, Cichon, S, St Clair, D, Corvin, A, Kirov, G, Mcquillin, A, Gurling, H, Rujescu, D, Andreassen, O. A, Werge, T, Blackwood, D. H. R, Pato, C. N, Pato, M. T, Malhotra, A. K, O'Donovan, M. C, Kendler, K. S, Fanous, A. H, Neale, Bm, Walters, Jt, Farh, Kh, Holmans, Pa, Lee, P, Bulik Sullivan, B, Collier, Da, Huang, H, Pers, Th, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Begemann, M, Belliveau, Ra, Bene, J, Bergen, Se, Bevilacqua, E, Bigdeli, Tb, Black, Dw, Børglum, Ad, Bruggeman, R, Buccola, Ng, Buckner, Rl, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, Rm, Carr, Vj, Carrera, N, Catts, Sv, Chambert, Kd, Chan, Rc, Chen, Ry, Chen, Ey, Cheng, W, Cheung, Ef, Chong, Sa, Cloninger, C, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, Jj, Curtis, D, Davidson, M, Davis, Kl, Degenhardt, F, Del, Favero, J, Delisi, Le, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott Price, V, Essioux, L, Fanous, Ah, Farrell, Ms, Frank, J, Franke, L, Freedman, R, Freimer, Nb, Friedl, M, Friedman, Ji, Fromer, M, Genovese, G, Georgieva, L, Gershon, Es, Giegling, I, Giusti Rodríguez, P, Godard, S, Goldstein, Ji, Golimbet, V, Gopal, S, Gratten, J, Grove, J, Haan, De, L, Hammer, C, Hamshere, Ml, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, Am, Henskens, Fa, Herms, S, Hirschhorn, Jn, Hoffmann, P, Hofman, A, Hollegaard, Mv, Hougaard, Dm, Ikeda, M, Joa, I, Julìa, A, Kahn, Rs, Kalaydjieva, L, Karachanak Yankova, S, Karjalainen, J, Kavanagh, D, Keller, Mc, Kelly, Bj, Kennedy, Jl, Khrunin, A, Kim, Y, Klovins, J, Knowles, Ja, Konte, B, Kucinskas, V, Kucinskiene, Za, Kuzelova Ptackova, H, Kähler, Ak, Laurent, C, Keong, Jl, Lee, S, Legge, Se, Lerer, B, Li, M, Li, T, Liang, Ky, Lieberman, J, Limborska, S, Loughland, Cm, Lubinski, J, Lönnqvist, J, Macek, M, Magnusson, Pk, Maher, Bs, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, Mccarley, Rw, Mcdonald, C, Mcintosh, Am, Meier, S, Meijer, Cj, Melegh, B, Melle, I, Mesholam Gately, Ri, Metspalu, A, Michie, Pt, Milani, L, Milanova, V, Mokrab, Y, Morris, Dw, Mors, O, Mortensen, Pb, Murphy, Kc, Murray, Rm, Myin Germeys, I, Müller Myhsok, B, Nelis, M, Nenadic, I, Nertney, Da, Nestadt, G, Nicodemus, Kk, Nikitina Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, F, Sy, Oh, Olincy, A, Olsen, L, Jv, Os, Pantelis, C, Papadimitriou, Gn, Papiol, S, Parkhomenko, E, Pato, Mt, Paunio, T, Pejovic Milovancevic, M, Perkins, Do, Pietiläinen, O, Pimm, J, Pocklington, Aj, Powell, J, Price, A, Pulver, Ae, Purcell, Sm, Quested, D, Rasmussen, Hb, Reichenberg, A, Reimers, Ma, Richards, Al, Roffman, Jl, Roussos, P, Ruderfer, Dm, Salomaa, V, Sanders, Ar, Schall, U, Schubert, Cr, Schulze, Tg, Schwab, Sg, Scolnick, Em, Scott, Rj, Seidman, Lj, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, Jm, Sim, K, Slominsky, P, Smoller, Jw, Hc, So, Spencer, Cc, Stahl, Ea, Stefansson, H, Steinberg, S, Stogmann, E, Straub, Re, Strengman, E, Strohmaier, J, Stroup, T, Subramaniam, M, Suvisaari, J, Svrakic, Dm, Szatkiewicz, Jp, Söderman, E, Thirumalai, S, Toncheva, D, Tooney, Pa, Tosato, Sarah, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, Bt, Weiser, M, Wildenauer, Db, Williams, Nm, Williams, S, Witt, Sh, Wolen, Ar, Wong, Eh, Wormley, Bk, Jq, Wu, Hs, Xi, Zai, Cc, Zheng, X, Zimprich, F, Stefansson, K, Visscher, Pm, Adolfsson, R, Andreassen, Oa, Blackwood, Dh, Bramon, E, Buxbaum, Jd, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, Pv, Gill, M, Hultman, Cm, Iwata, N, Jablensky, Av, Jönsson, Eg, Kendler, Ks, Knight, J, Lencz, T, Levinson, Df, Qs, Li, Liu, J, Malhotra, Ak, Mccarroll, Sa, Moran, Jl, Mowry, Bj, Nöthen, Mm, Ophoff, Ra, Owen, Mj, Palotie, A, Pato, Cn, Petryshen, Tl, Posthuma, D, Riley, Bp, Sham, Pc, Sklar, P, Clair, Ds, Weinberger, Dr, Wendland, Jr, Daly, Mj, Sullivan, Pf, O'Donovan, Mc, Complex Trait Genetics, Amsterdam Neuroscience - Complex Trait Genetics, Bigdeli, Tim B, Ripke, Stephan, Bacanu, Silviu-Alin, Lee, Sang Hong, Fanous, Ayman H, Schizophrenia Working Group of the Psychiatric Genomics Consortium, Psychosis Endophenotype International Consortium, Wellcome Trust Case-Control Consortium 2, Other departments, Adult Psychiatry, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, MUMC+: MA Psychiatrie (3), MUMC+: Hersen en Zenuw Centrum (3), and Del-Favero, Jurgen

Subjects
0301 basic medicine, Multifactorial Inheritance, Bipolar Disorder, Inheritance Patterns, Genome-wide association study, Single-nucleotide polymorphism, polygenic, heritability, Biology, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Cellular and Molecular Neuroscience, 0302 clinical medicine, medicine, Humans, SNP, GWAS, Family, Genetic Predisposition to Disease, Family history, Allele, Genetics (clinical), Genetic association, Genetics & Heredity, Psychiatry, Genetics, Depressive Disorder, Major, family history, Models, Genetic, Case-control study, medicine.disease, 3. Good health, schizophrenia, Psychiatry and Mental health, 030104 developmental biology, Schizophrenia, Case-Control Studies, Human medicine, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWAS) of schizophrenia have yielded more than 100 common susceptibility variants, and strongly support a substantial polygenic contribution of a large number of small allelic effects. It has been hypothesized that familial schizophrenia is largely a consequence of inherited rather than environmental factors. We investigated the extent to which familiality of schizophrenia is associated with enrichment for common risk variants detectable in a large GWAS. We analyzed single nucleotide polymorphism (SNP) data for cases reporting a family history of psychotic illness (N=978), cases reporting no such family history (N=4,503), and unscreened controls (N=8,285) from the Psychiatric Genomics Consortium (PGC1) study of schizophrenia. We used a multinomial logistic regression approach with model-fitting to detect allelic effects specific to either family history subgroup. We also considered a polygenic model, in which we tested whether family history positive subjects carried more schizophrenia risk alleles than family history negative subjects, on average. Several individual SNPs attained suggestive but not genome-wide significant association with either family history subgroup. Comparison of genome-wide polygenic risk scores based on GWAS summary statistics indicated a significant enrichment for SNP effects among family history positive compared to family history negative cases (Nagelkerke's R-2=0.0021; P=0.00331; P-value threshold

Published
2016
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13. A Neuroethics Framework for the Australian Brain Initiative

Author

Kennett, J, Carter, A, Bourne, JA, Hall, W, Levy, N, Mattingley, JB, Lawrence, AJ, Forlini, C, Malcolm, L, Vincent, N, Richards, LJ, Egan, GF, Breakspear, M, Cornish, K, Halliday, G, Poole-Warren, L, Sriram, S, Soulis, T, Fitzgibbon, B, Kiral-Kornek, I, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bradley, A, Brichta, A, Carter, O, Castles, A, Clements, J, Cornish, J, de Zubicaray, G, Enticott, PG, Fornito, A, Griffiths, L, Gullifer, J, Hannan, AJ, Harrer, S, Harvey, A, Hickie, IB, Jazwinska, L, Kiernan, M, Kilpatrick, T, Leventer, R, Licinio, J, Lovell, N, Mackellar, G, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Rossell, S, Sah, P, Sarnyai, Z, Schofield, PR, Shum, DHK, Silk, T, Slee, M, Stuart, GJ, Tapson, J, van Schaik, A, Vissel, B, Waters, A, Apthorp, D, Cohen-Woods, S, Conn, SJ, Korgaonkar, M, Mason, A, Azghadi, MR, Shimoni, O, Smith, A, Thompson, MB, Kennett, J, Carter, A, Bourne, JA, Hall, W, Levy, N, Mattingley, JB, Lawrence, AJ, Forlini, C, Malcolm, L, Vincent, N, Richards, LJ, Egan, GF, Breakspear, M, Cornish, K, Halliday, G, Poole-Warren, L, Sriram, S, Soulis, T, Fitzgibbon, B, Kiral-Kornek, I, Badcock, DR, Balleine, B, Bekkers, JM, Berk, M, Bradley, A, Brichta, A, Carter, O, Castles, A, Clements, J, Cornish, J, de Zubicaray, G, Enticott, PG, Fornito, A, Griffiths, L, Gullifer, J, Hannan, AJ, Harrer, S, Harvey, A, Hickie, IB, Jazwinska, L, Kiernan, M, Kilpatrick, T, Leventer, R, Licinio, J, Lovell, N, Mackellar, G, Medland, SE, Michie, PT, Nithianantharajah, J, Parker, J, Payne, JM, Rossell, S, Sah, P, Sarnyai, Z, Schofield, PR, Shum, DHK, Silk, T, Slee, M, Stuart, GJ, Tapson, J, van Schaik, A, Vissel, B, Waters, A, Apthorp, D, Cohen-Woods, S, Conn, SJ, Korgaonkar, M, Mason, A, Azghadi, MR, Shimoni, O, Smith, A, and Thompson, MB

Abstract

Neuroethics is central to the Australian Brain Initiative's aim to sustain a thriving and responsible neurotechnology industry. Diverse and inclusive community and stakeholder engagement and a trans-disciplinary approach to neuroethics will be key to the success of the Australian Brain Initiative.

Published
2019

14. Population-based identity-by-descent mapping combined with exome sequencing to detect rare risk variants for schizophrenia

Author

Harold, D, Connolly, S, Riley, BP, Kendler, KS, McCarthy, SE, McCombie, WR, Richards, A, Owen, MJ, O'Donovan, MC, Walters, J, Donnelly, P, Bates, L, Barroso, I, Blackwell, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Hopkins, L, Pirinen, M, Pearson, R, Strange, A, Su, Z, Vukcevic, D, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Ripke, S, Neale, BM, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M-L, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chan, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Lee, J, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Muller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Buxbaum, JD, Borglum, AD, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, Harold, D, Connolly, S, Riley, BP, Kendler, KS, McCarthy, SE, McCombie, WR, Richards, A, Owen, MJ, O'Donovan, MC, Walters, J, Donnelly, P, Bates, L, Barroso, I, Blackwell, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Hopkins, L, Pirinen, M, Pearson, R, Strange, A, Su, Z, Vukcevic, D, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Ripke, S, Neale, BM, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M-L, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chan, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Lee, J, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Muller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Buxbaum, JD, Borglum, AD, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, and Sullivan, PF

Abstract

Genome-wide association studies (GWASs) are highly effective at identifying common risk variants for schizophrenia. Rare risk variants are also important contributors to schizophrenia etiology but, with the exception of large copy number variants, are difficult to detect with GWAS. Exome and genome sequencing, which have accelerated the study of rare variants, are expensive so alternative methods are needed to aid detection of rare variants. Here we re-analyze an Irish schizophrenia GWAS dataset (n = 3,473) by performing identity-by-descent (IBD) mapping followed by exome sequencing of individuals identified as sharing risk haplotypes to search for rare risk variants in coding regions. We identified 45 rare haplotypes (>1 cM) that were significantly more common in cases than controls. By exome sequencing 105 haplotype carriers, we investigated these haplotypes for functional coding variants that could be tested for association in independent GWAS samples. We identified one rare missense variant in PCNT but did not find statistical support for an association with schizophrenia in a replication analysis. However, IBD mapping can prioritize both individual samples and genomic regions for follow-up analysis but genome rather than exome sequencing may be more effective at detecting risk variants on rare haplotypes.

Published
2019

15. Partitioning heritability of regulatory and cell-type-specific variants across 11 common diseases

Author

Gusev, A, Lee, Sh, SWE SCZ, Consortium, O'Dushlaine, Cgusev, Trynka, G, Finucane, H, Vilhjálmsson, Bj, Xu, H, Zang, C, Ripke, S, Bulik Sullivan, B, Stahl, E, Schizophrenia, Working, Neale, Bm, Corvin, A, Walters, Jt, Farh, Kh, Holmans, Pa, Lee, P, Collier, Da, Huang, H, Pers, Th, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, Sa, Begemann, M, Belliveau, Ra, Bene, J, Bergen, Se, Bevilacqua, E, Bigdeli, Tb, Black, Dw, Børglum, Ad, Bruggeman, R, Buccola, Ng, Buckner, Rl, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, Rm, Carr, Vj, Carrera, N, Catts, Sv, Chambert, Kd, Chan, Rc, Chen, Ry, Chen, Ey, Cheng, W, Cheung, Ef, Chong, Sa, Cloninger, Cr, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, Jj, Curtis, D, Davidson, M, Davis, Kl, Degenhardt, F, Del, Favero, Delisi, Le, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott Price, V, Essioux, L, Fanous, Ah, Farrell, Ms, Frank, J, Franke, L, Freedman, R, Freimer, Nb, Friedl, M, Friedman, Ji, Fromer, M, Genovese, G, Georgieva, L, Gershon, Es, Giegling, I, Giusti Rodrguez, P, Godard, S, Goldstein, Ji, Golimbet, V, Gopal, S, Gratten, J, Grove, J, Haan, De, Hammer, C, Hamshere, Ml, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, Am, Henskens, Fa, Herms, S, Hirschhorn, Jn, Hoffmann, P, Hofman, A, Hollegaard, Mv, Hougaard, Dm, Ikeda, M, Joa, I, Julià, A, Kahn, Rs, Kalaydjieva, L, Karachanak Yankova, S, Karjalainen, J, Kavanagh, D, Keller, Mc, Kelly, Bj, Kennedy, Jl, Khrunin, A, Kim, Y, Klovins, J, Knowles, Ja, Konte, B, Kucinskas, V, Kucinskiene, Za, Kuzelova Ptackova, H, Kähler, Ak, Laurent, C, Keong, Jl, Legge, Se, Lerer, B, Li, M, Li, T, Liang, Ky, Lieberman, J, Limborska, S, Loughland, Cm, Lubinski, J, Lnnqvist, J, Macek, M, Magnusson, Pk, Maher, Bs, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, Mccarley, Rw, Mcdonald, C, Mcintosh, Am, Meier, S, Meijer, Cj, Melegh, B, Melle, I, Mesholam Gately, Ri, Metspalu, A, Michie, Pt, Milani, L, Milanova, V, Mokrab, Y, Morris, Dw, Mors, O, Mortensen, Pb, Murphy, Kc, Murray, Rm, Myin Germeys, I, Mller Myhsok, B, Nelis, M, Nenadic, I, Nertney, Da, Nestadt, G, Nicodemus, Kk, Nikitina Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, Fa, Sy, Oh, Olincy, A, Olsen, L, Van, Os, Pantelis, C, Papadimitriou, Gn, Papiol, S, Parkhomenko, E, Pato, Mt, Paunio, T, Pejovic Milovancevic, M, Perkins, Do, Pietilinen, O, Pimm, J, Pocklington, Aj, Powell, J, Price, A, Pulver, Ae, Purcell, Sm, Quested, D, Rasmussen, Hb, Reichenberg, A, Reimers, Ma, Richards, Al, Roffman, Jl, Roussos, P, Ruderfer, Dm, Salomaa, V, Sanders, Ar, Schall, U, Schubert, Cr, Schulze, Tg, Schwab, Sg, Scolnick, Em, Scott, Rj, Seidman, Lj, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, Jm, Sim, K, Slominsky, P, Smoller, Jw, Hc, So, Spencer, Cc, Stahl, Ea, Stefansson, H, Steinberg, S, Stogmann, E, Straub, Re, Strengman, E, Strohmaier, J, Stroup, Ts, Subramaniam, M, Suvisaari, J, Svrakic, Dm, Szatkiewicz, Jp, Sderman, E, Thirumalai, S, Toncheva, D, Tooney, Pa, Tosato, Sarah, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, Bt, Weiser, M, Wildenauer, Db, Williams, Nm, Williams, S, Witt, Sh, Wolen, Ar, Wong, Eh, Wormley, Bk, Jq, Wu, Hs, Xi, Zai, Cc, Zheng, X, Zimprich, F, Wray, Nr, Stefansson, K, Visscher, Pm, Adolfsson, R, Andreassen, Oa, Blackwood, Dh, Bramon, E, Buxbaum, Jd, Brglum, Ad, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, Pv, Gill, M, Gurling, H, Hultman, Cm, Iwata, N, Jablensky, Av, Jönsson, Eg, Kendler, Ks, Kirov, G, Knight, J, Lencz, T, Levinson, Df, Qs, Li, Liu, J, Malhotra, Ak, Mccarroll, Sa, Mcquillin, A, Moran, Jl, Mowry, Bj, Nthen, Mm, Ophoff, Ra, Owen, Mj, Palotie, A, Pato, Cn, Petryshen, Tl, Posthuma, D, Rietschel, M, Riley, Bp, Rujescu, D, Sham, Pc, Sklar, P, Clair, St, Weinberger, Dr, Wendland, Jr, Werge, T, Daly, Mj, Sullivan, Pf, O'Donovan, Mc, Chambert, K, Akterin, S, Bergen, S, Ruderfer, D, Scolnick, E, Purcell, S, Mccarroll, S, Daly, M, Pasaniuc, B, Raychaudhuri, S, Price, Al, Gusev, Alexander, Lee, S Hong, Trynka, Gosia, Finucane, Hilary K, Price, Alkes L, Schizophrenia Working Group of the Psychiatric Genomics Consortium, SWE-SCZ Consortium, ANS - Amsterdam Neuroscience, Adult Psychiatry, Other departments, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, Complex Trait Genetics, Functional Genomics, and Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease

Subjects
Linkage disequilibrium, GWAS, schizophrenia, SNP, trait heritability, disease architecture, Inheritance Patterns, Single-nucleotide polymorphism, Genome-wide association study, Biology, Article, Open Reading Frames, SDG 3 - Good Health and Well-being, Genetic, Models, Genotype, Genetics, Humans, Genetics(clinical), Computer Simulation, Regulatory Elements, Transcriptional, Exome, Genetics (clinical), genotype imputation, Genetic association, Genetics & Heredity, genome-wide association study, Models, Genetic, Genetic Diseases, Inborn, Genetic Variation, Heritability, exome chips, Regulatory Elements, Inborn, Genetic Diseases, Transcriptional, coding variants, Genome-Wide Association Study
Abstract

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (h(g)(2)) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of h(g)(2) from imputed SNPs (5.1 x enrichment; p = 3.7 x 10(-17)) and 38% (SE = 4%) of h(g)(2) from genotyped SNPs (1.6 x enrichment, p = 1.0 x 10(-4)). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained

Published
2014
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16. Variability in Working Memory Performance Explained by Epistasis vs Polygenic Scores in the ZNF804A Pathway

Author

Nicodemus, Kk, Hargreaves, A, Morris, D, Anney, R, Gill, M, Corvin, A, Donohoe, G, Ripke, S, Sanders, Ar, Kendler, Ks, Levinson, Df, Sklar, P, Holmans, Pa, Lin, Dy, Duan, J, Ophoff, Ra, Andreassen, Oa, Scolnick, E, Cichon, S, Clair, St, D, Gurling, H, Werge, T, Rujescu, D, Blackwood, Dh, Pato, Cn, Malhotra, Ak, Purcell, S, Dudbridge, F, Neale, Bm, Rossin, L, Visscher, Pm, Posthuma, D, Ruderfer, Dm, Fanous, A, Stefansson, H, Steinberg, S, Mowry, Bj, Golimbet, V, Hert, De, M, Jönsson, Eg, Bitter, I, Pietiläinen, Op, Collier, Da, Tosato, Sarah, Agartz, I, Albus, M, Alexander, M, Amdur, Rl, Amin, F, Bass, N, Bergen, Se, Black, Dw, Børglum, Ad, Brown, Ma, Bruggeman, R, Buccola, Ng, Byerley, Wf, Cahn, W, Cantor, Rm, Carr, Vj, Catts, Sv, Choudhury, K, Cloninger, C, Cormican, P, Craddock, N, Danoy, Pa, Datta, S, Haan, De, L, Demontis, D, Dikeos, D, Djurovic, S, Donnelly, P, Duong, L, Dwyer, S, Fink Jensen, A, Freedman, R, Freimer, Nb, Friedl, M, Georgieva, L, Giegling, I, Glenthøj, B, Godard, S, Hamshere, M, Hansen, M, Hansen, T, Hartmann, Am, Henskens, Fa, Hougaard, Dm, Hultman, Cm, Ingason, A, Jablensky, Av, Jakobsen, Kd, Jay, M, Jürgens, G, Kahn, Rs, Keller, Mc, Kenis, G, Kenny, E, Kim, Y, Kirov, Gk, Konnerth, H, Konte, B, Krabbendam, L, Krasucki, R, Lasseter, Vk, Laurent, C, Lawrence, J, Lencz, T, Lerer, F, Liang, Ky, Lichtenstein, P, Lieberman, Ja, Linszen, Dh, Lönnqvist, J, Loughland, Cm, Maclean, Aw, Maher, Bs, Maier, W, Mallet, J, Malloy, P, Mattheisen, M, Mattingsdal, M, Mcghee, Ka, Mcgrath, Jj, Mcintosh, A, Mclean, De, Mcquillin, A, Melle, I, Michie, Pt, Milanova, V, Morris, Dw, Mors, O, Mortensen, Pb, Moskvina, V, Muglia, P, Myin Germeys, I, Nertney, Da, Nestadt, G, Nielsen, J, Nikolov, I, Nordentoft, M, Norton, N, Nöthen, Mm, O'Dushlaine, Ct, Olincy, A, Olsen, L, O'Neill, F, Ørntoft, Tf, Owen, Mj, Pantelis, C, Papadimitriou, G, Pato, Mt, Peltonen, L, Petursson, H, Pickard, B, Pimm, J, Pulver, Ae, Puri, V, Quested, D, Quinn, Em, Rasmussen, Hb, Réthelyi, Jm, Ribble, R, Rietschel, M, Riley, Bp, Ruggeri, Mirella, Schall, U, Schulze, Tg, Schwab, Sg, Scott, Rj, Shi, J, Sigurdsson, E, Silverman, Jm, Spencer, Cc, Stefansson, K, Strange, A, Strengman, E, Stroup, T, Suvisaari, J, Terenius, L, Thirumalai, S, Thygesen, Jh, Timm, S, Toncheva, D, Van, Den, Oord, E, Van, Os, Van, J, Winkel, R, Veldink, J, Walsh, D, Wang, Ag, Wiersma, D, Wildenauer, Db, Williams, Hj, Williams, Nm, Wormley, B, Zammit, S, Sullivan, Pf, O'Donovan, Mc, Daly, Mj, Gejman, P., Functional Genomics, Complex Trait Genetics, De Hert, Marc, Myin-Germeys, Inez, van Winkel, Ruud, Psychiatrie & Neuropsychologie, RS: MHeNs - R2 - Mental Health, Amsterdam Neuroscience, and Adult Psychiatry

Subjects
epistasis, Male, Multifactorial Inheritance, polygenic, Neuropsychological Tests, involvement, 0302 clinical medicine, Neural Pathways, 2.1 Biological and endogenous factors, Psychology, schizophrenia risk, psychosis variant, Aetiology, 0303 health sciences, susceptibility gene znf804a, medicine.diagnostic_test, phenotypes, Zinc Fingers, Neuropsychological test, Single Nucleotide, Middle Aged, Serious Mental Illness, Psychiatry and Mental health, Memory, Short-Term, Mental Health, Schizophrenia, Major depressive disorder, Female, Cognitive Sciences, social and economic factors, Adult, medicine.medical_specialty, Psychosis, working memory, schizophrenia, IQ, Schizoaffective disorder, Polymorphism, Single Nucleotide, Article, 03 medical and health sciences, Gene interaction, Genetic, Social cognition, Memory, Clinical Research, 2.3 Psychological, Behavioral and Social Science, medicine, Genetics, Humans, Genetic Predisposition to Disease, Bipolar disorder, Polymorphism, Psychiatry, 030304 developmental biology, Other Medical and Health Sciences, Prevention, Wellcome Trust Case Control Consortium 2, Neurosciences, Genetic Variation, Epistasis, Genetic, Schizophrenia Psychiatric Genome-wide Association Study (GWAS) Consortium, medicine.disease, attention, Brain Disorders, deficits, Short-Term, Psychotic Disorders, genome-wide association, Epistasis, healthy controls, identification, Cognition Disorders, 030217 neurology & neurosurgery, Genome-Wide Association Study
Abstract

IMPORTANCE We investigated the variation in neuropsychological function explained by risk alleles at the psychosis susceptibility gene ZNF804A and its interacting partners using single nucleotide polymorphisms (SNPs), polygenic scores, and epistatic analyses. Of particular importance was the relative contribution of the polygenic score vs epistasis in variation explained. OBJECTIVES To (1) assess the association between SNPs in ZNF804A and the ZNF804A polygenic score with measures of cognition in cases with psychosis and (2) assess whether epistasis within the ZNF804A pathway could explain additional variation above and beyond that explained by the polygenic score. DESIGN, SETTING, AND PARTICIPANTS Patients with psychosis (n = 424)were assessed in areas of cognitive ability impaired in schizophrenia including IQ, memory, attention, and social cognition.We used the Psychiatric GWAS Consortium 1 schizophrenia genome-wide association study to calculate a polygenic score based on identified risk variants within this genetic pathway. Cognitive measures significantly associated with the polygenic score were tested for an epistatic component using a training set (n = 170), which was used to develop linear regression models containing the polygenic score and 2-SNP interactions. The best-fitting models were tested for replication in 2 independent test sets of cases: (1) 170 individuals with schizophrenia or schizoaffective disorder and (2) 84 patients with broad psychosis (including bipolar disorder, major depressive disorder, and other psychosis). MAIN OUTCOMES AND MEASURES Participants completed a neuropsychological assessment battery designed to target the cognitive deficits of schizophrenia including general cognitive function, episodic memory, working memory, attentional control, and social cognition. RESULTS Higher polygenic scores were associated with poorer performance among patients on IQ, memory, and social cognition, explaining 1%to 3%of variation on these scores (range, P = .01 to .03). Using a narrow psychosis training set and independent test sets of narrow phenotype psychosis (schizophrenia and schizoaffective disorder), broad psychosis, and control participants (n = 89), the addition of 2 interaction terms containing 2 SNPs each increased the R2 for spatial working memory strategy in the independent psychosis test sets from 1.2%using the polygenic score only to 4.8%(P = .11 and .001, respectively) but did not explain additional variation in control participants. CONCLUSIONS AND RELEVANCE These data support a role for the ZNF804A pathway in IQ, memory, and social cognition in cases. Furthermore, we showed that epistasis increases the variation explained above the contribution of the polygenic score. © 2014 American Medical Association. All rights reserved.

Published
2014
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17. Age at first birth in women is genetically associated with increased risk of schizophrenia

Author

Ni, G, Gratten, J, Wray, NR, Lee, SH, Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, KH, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodríguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Haan, L de, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Juliá, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kähler, AK, Laurent, C, Keong, JLC, Legge, SE, Lerer, B, Li, M, Li, T, Liang, KY, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lönnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Müller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, SY, Olincy, A, Olsen, L, van Os, JV, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietiläinen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, HC, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Söderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, Xuebin, Zimprich, F, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Børglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jönsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Nöthen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, Daniëlle, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Clair, DS, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, O'Donovan, MC, Ni, G, Gratten, J, Wray, NR, Lee, SH, Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, KH, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodríguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Haan, L de, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Juliá, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kähler, AK, Laurent, C, Keong, JLC, Legge, SE, Lerer, B, Li, M, Li, T, Liang, KY, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lönnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Müller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, SY, Olincy, A, Olsen, L, van Os, JV, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietiläinen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, HC, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Söderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, Xuebin, Zimprich, F, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Børglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jönsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Nöthen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, Daniëlle, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Clair, DS, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, and O'Donovan, MC

Published
2018

18. Effects of immune activation during early or late gestation on schizophrenia-related behaviour in adult rat offspring

Author

Meehan, C, Harms, L, Frost, JD, Barreto, R, Todd, J, Schall, U, Shannon Weickert, C, Zavitsanou, K, Michie, PT, Hodgson, DM, Meehan, C, Harms, L, Frost, JD, Barreto, R, Todd, J, Schall, U, Shannon Weickert, C, Zavitsanou, K, Michie, PT, and Hodgson, DM

Abstract

Maternal exposure to infectious agents during gestation has been identified as a significant risk factor for schizophrenia. Using a mouse model, past work has demonstrated that the gestational timing of the immune-activating event can impact the behavioural phenotype and expression of dopaminergic and glutamatergic neurotransmission markers in the offspring. In order to determine the inter-species generality of this effect to rats, another commonly used model species, the current study investigated the impact of a viral mimetic Poly (I:C) at either an early (gestational day 10) or late (gestational day 19) time-point on schizophrenia-related behaviour and neurotransmitter receptor expression in rat offspring. Exposure to Poly (I:C) in late, but not early, gestation resulted in transient impairments in working memory. In addition, male rats exposed to maternal immune activation (MIA) in either early or late gestation exhibited sensorimotor gating deficits. Conversely, neither early nor late MIA exposure altered locomotor responses to MK-801 or amphetamine. In addition, increased dopamine 1 receptor mRNA levels were found in the nucleus accumbens of male rats exposed to early gestational MIA. The findings from this study diverge somewhat from previous findings in mice with MIA exposure, which were often found to exhibit a more comprehensive spectrum of schizophrenia-like phenotypes in both males and females, indicating potential differences in the neurodevelopmental vulnerability to MIA exposure in the rat with regards to schizophrenia related changes.

Published
2017

19. White Matter Disruptions in Schizophrenia Are Spatially Widespread and Topologically Converge on Brain Network Hubs

Author

Klauser, P, Baker, ST, Cropley, VL, Bousman, C, Fornito, A, Cocchi, L, Fullerton, JM, Rasser, P, Schall, U, Henskens, F, Michie, PT, Loughland, C, Catts, SV, Mowry, B, Weickert, TW, Shannon Weickert, C, Carr, V, Lenroot, R, Pantelis, C, Zalesky, A, Klauser, P, Baker, ST, Cropley, VL, Bousman, C, Fornito, A, Cocchi, L, Fullerton, JM, Rasser, P, Schall, U, Henskens, F, Michie, PT, Loughland, C, Catts, SV, Mowry, B, Weickert, TW, Shannon Weickert, C, Carr, V, Lenroot, R, Pantelis, C, and Zalesky, A

Abstract

White matter abnormalities associated with schizophrenia have been widely reported, although the consistency of findings across studies is moderate. In this study, neuroimaging was used to investigate white matter pathology and its impact on whole-brain white matter connectivity in one of the largest samples of patients with schizophrenia. Fractional anisotropy (FA) and mean diffusivity (MD) were compared between patients with schizophrenia or schizoaffective disorder (n = 326) and age-matched healthy controls (n = 197). Between-group differences in FA and MD were assessed using voxel-based analysis and permutation testing. Automated whole-brain white matter fiber tracking and the network-based statistic were used to characterize the impact of white matter pathology on the connectome and its rich club. Significant reductions in FA associated with schizophrenia were widespread, encompassing more than 40% (234ml) of cerebral white matter by volume and involving all cerebral lobes. Significant increases in MD were also widespread and distributed similarly. The corpus callosum, cingulum, and thalamic radiations exhibited the most extensive pathology according to effect size. More than 50% of cortico-cortical and cortico-subcortical white matter fiber bundles comprising the connectome were disrupted in schizophrenia. Connections between hub regions comprising the rich club were disproportionately affected. Pathology did not differ between patients with schizophrenia and schizoaffective disorder and was not mediated by medication. In conclusion, although connectivity between cerebral hubs is most extensively disturbed in schizophrenia, white matter pathology is widespread, affecting all cerebral lobes and the cerebellum, leading to disruptions in the majority of the brain's fiber bundles.

Published
2017

20. Effects of immune activation during early or late gestation on N-Methyl-D-Aspartate receptor measures in adult rat offspring

Author

Rahman, T, Zavitsanou, K, Purves-Tyson, T, Harms, LR, Meehan, C, Schall, U, Todd, J, Hodgson, DM, Michie, PT, Weickert, CS, Rahman, T, Zavitsanou, K, Purves-Tyson, T, Harms, LR, Meehan, C, Schall, U, Todd, J, Hodgson, DM, Michie, PT, and Weickert, CS

Abstract

Background: Glutamatergic receptor [N-methyl-d-aspartate receptor (NMDAR)] alterations within cortex, hippocampus, and striatum are linked to schizophrenia pathology. Maternal immune activation (MIA) is an environmental risk factor for the development of schizophrenia in offspring. In rodents, gestational timing of MIA may result in distinct behavioral outcomes in adulthood, but how timing of MIA may impact the nature and extent of NMDAR-related changes in brain is not known. We hypothesize that NMDAR-related molecular changes in rat cortex, striatum, and hippocampus are induced by MIA and are dependent on the timing of gestational inflammation and sex of the offspring. Methods: Wistar dams were treated the with viral mimic, polyriboinosinic:polyribocytidylic acid (polyI:C), or vehicle on either gestational day 10 or 19. Fresh-frozen coronal brain sections were collected from offspring between postnatal day 63-91. Autoradiographic binding was used to infer levels of the NMDAR channel, and NR2A and NR2B subunits in cortex [cingulate (Cg), motor, auditory], hippocampus (dentate gyrus, cornu ammonis area 3, cornu ammonis area 1), and striatum [dorsal striatum, nucleus accumbens core, and nucleus accumbens shell (AS)]. NR1 and NR2A mRNA levels were measured by in situ hybridization in cortex, hippocampus, and striatum in male offspring only. Results: In the total sample, NMDAR channel binding was elevated in the Cg of polyI:C offspring. NR2A binding was elevated, while NR2B binding was unchanged, in all brain regions of polyI:C offspring overall. Male, but not female, polyI:C offspring exhibited increased NMDAR channel and NR2A binding in the striatum overall, and increased NR2A binding in the cortex overall. Male polyI:C offspring exhibited increased NR1 mRNA in the AS, and increased NR2A mRNA in cortex and subregions of the hippocampus. Conclusion: MIA may alter glutamatergic signaling in cortical and hippocampal regions via alterations in NMDAR indices; however, this

Published
2017

21. Electrophysiological, cognitive and clinical profiles of at-risk mental state: The longitudinal minds in transition (MinT) study

Author

Atkinson, RJ, Fulham, WR, Michie, PT, Ward, PB, Todd, J, Stain, H, Langdon, R, Thienel, R, Paulik, G, Cooper, G, Anthes, L, Bowen, D, Case, V, Clark, S, Collins-Langworthy, J, Curtis, J, Ehlkes, T, Haddow, T, Lawrence, C, Logan, S, Loneragan, C, Loughland, C, Mathersul, D, O'Donnell, M, Paine, K, Sharp, T, Scott, R, Sculley, A, Seal, M, Thompson, P, Tooney, M, Tooney, P, Treen, L, Whitton, A, Rasser, P, Carr, V, Weickert, TW, Schall, U, Atkinson, RJ, Fulham, WR, Michie, PT, Ward, PB, Todd, J, Stain, H, Langdon, R, Thienel, R, Paulik, G, Cooper, G, Anthes, L, Bowen, D, Case, V, Clark, S, Collins-Langworthy, J, Curtis, J, Ehlkes, T, Haddow, T, Lawrence, C, Logan, S, Loneragan, C, Loughland, C, Mathersul, D, O'Donnell, M, Paine, K, Sharp, T, Scott, R, Sculley, A, Seal, M, Thompson, P, Tooney, M, Tooney, P, Treen, L, Whitton, A, Rasser, P, Carr, V, Weickert, TW, and Schall, U

Abstract

The onset of schizophrenia is typically preceded by a prodromal period lasting several years during which sub-threshold symptoms may be identified retrospectively. Clinical interviews are currently used to identify individuals who have an ultra-high risk (UHR) of developing a psychotic illness with a view to provision of interventions that prevent, delay or reduce severity of future mental health issues. The utility of bio-markers as an adjunct in the identification of UHR individuals is not yet established. Several event-related potential measures, especially mismatch-negativity (MMN), have been identified as potential biomarkers for schizophrenia. In this 12-month longitudinal study, demographic, clinical and neuropsychological data were acquired from 102 anti-psychotic naive UHR and 61 healthy controls, of whom 80 UHR and 58 controls provided valid EEG data during a passive auditory task at baseline. Despite widespread differences between UHR and controls on demographic, clinical and neuropsychological measures, MMN and P3a did not differ between these groups. Of 67 UHR at the 12-month follow-up, 7 (10%) had transitioned to a psychotic illness. The statistical power to detect differences between those who did or did not transition was limited by the lower than expected transition rate. ERPs did not predict transition, with trends in the opposite direction to that predicted. In exploratory analysis, the strongest predictors of transition were measures of verbal memory and subjective emotional disturbance.

Published
2017

22. Auditory prediction errors as individual biomarkers of schizophrenia

Author

Taylor, JA, Matthews, N, Michie, PT, Rosa, MJ, Garrido, MI, Taylor, JA, Matthews, N, Michie, PT, Rosa, MJ, and Garrido, MI

Abstract

Schizophrenia is a complex psychiatric disorder, typically diagnosed through symptomatic evidence collected through patient interview. We aim to develop an objective biologically-based computational tool which aids diagnosis and relies on accessible imaging technologies such as electroencephalography (EEG). To achieve this, we used machine learning techniques and a combination of paradigms designed to elicit prediction errors or Mismatch Negativity (MMN) responses. MMN, an EEG component elicited by unpredictable changes in sequences of auditory stimuli, has previously been shown to be reduced in people with schizophrenia and this is arguably one of the most reproducible neurophysiological markers of schizophrenia. EEG data were acquired from 21 patients with schizophrenia and 22 healthy controls whilst they listened to three auditory oddball paradigms comprising sequences of tones which deviated in 10% of trials from regularly occurring standard tones. Deviant tones shared the same properties as standard tones, except for one physical aspect: 1) duration - the deviant stimulus was twice the duration of the standard; 2) monaural gap - deviants had a silent interval omitted from the standard, or 3) inter-aural timing difference, which caused the deviant location to be perceived as 90° away from the standards. We used multivariate pattern analysis, a machine learning technique implemented in the Pattern Recognition for Neuroimaging Toolbox (PRoNTo) to classify images generated through statistical parametric mapping (SPM) of spatiotemporal EEG data, i.e. event-related potentials measured on the two-dimensional surface of the scalp over time. Using support vector machine (SVM) and Gaussian processes classifiers (GPC), we were able classify individual patients and controls with balanced accuracies of up to 80.48% (p-values = 0.0326, FDR corrected) and an ROC analysis yielding an AUC of 0.87. Crucially, a GP regression revealed that MMN predicted global assessment of funct

Published
2017

23. Genetic schizophrenia risk variants jointly modulate total brain and white matter volume

Author

Terwisscha van Scheltinga, Af, Bakker, Sc, van Haren, Ne, Derks, Em, Buizer Voskamp, Je, Boos, Hb, Cahn, W, Hulshoff, Pol, Ripke, S, Ophoff, Ra, Kahn, Rs, Sanders, Ar, Kendler, Ks, Levinson, Df, Sklar, P, Holmans, Pa, Lin, Dy, Duan, J, Andreassen, Oa, Scolnick, E, Cichon, S, Clair, St, D, Corvin, A, Gurling, H, Werge, T, Rujescu, D, Blackwood, Dh, Pato, Cn, Malhotra, Ak, Purcell, S, Dudbridge, F, Neale, Bm, Rossin, L, Visscher, Pm, Posthuma, D, Ruderfer, Dm, Fanous, A, Stefansson, H, Steinberg, S, Mowry, Bj, Golimbet, V, Hert, De, M, Jonsson, Eg, Bitter, I, Pietiläinen, Op, Collier, Da, Tosato, Sarah, Agartz, I, Albus, M, Alexander, M, Amdur, Rl, Amin, F, Bass, N, Bergen, Se, Black, Dw, Børglum, Ad, Brown, Ma, Bruggeman, R, Buccola, Ng, Byerley, Wf, Cantor, Rm, Carr, Vj, Catts, Sv, Choudhury, K, Cloninger, C, Cormican, P, Craddock, N, Danoy, Pa, Datta, S, Haan, De, L, Demontis, D, Dikeos, D, Djurovic, S, Donnelly, P, Donohoe, G, Duong, L, Dwyer, S, Fink Jensen, A, Freedman, R, Freimer, Nb, Friedl, M, Georgieva, L, Giegline, I, Gill, M, Glenthøj, B, Godard, S, Hamshere, M, Hansen, M, Hansen, T, Hartmann, Am, Henskens, Fa, Hougaard, Dm, Hultman, Cm, Ingason, A, Jablensky, Av, Jakobsen, Kd, Jay, M, Jürgens, G, Keller, Mc, Kenis, G, Kenny, E, Kim, Y, Kirov, Gk, Konnerth, H, Konte, B, Krabbendam, L, Krasucki, R, Lasseter, Vk, Laurent, C, Lawrence, J, Lencz, T, Lerer, F, Liang, Ky, Lichtenstein, P, Lieberman, Ja, Linszen, Dh, Lönnqvist, J, Loughland, Cm, Maclean, Aw, Maher, Bs, Maier, W, Mallet, J, Malloy, P, Mattheisen, M, Mattingsdal, M, Mcghee, Ka, Mcgrath, Jj, Mcintosh, A, Mclean, De, Mcquillin, A, Melle, I, Michie, Pt, Milanova, V, Morris, Dw, Mors, O, Mortensen, Pb, Moskvina, V, Muglia, P, Myin Germeys, I, Nertney, Da, Nestadt, G, Nielsen, J, Nikolov, I, Nordentoft, M, Norton, N, Nöthen, Mm, O'Dushlaine, C, Olincy, A, Olsen, L, O'Neill, F, Ørntoft, Tf, Owen, Mj, Pantelis, C, Papadimitriou, G, Pato, Mt, Peltonen, L, Petursson, H, Pickard, B, Pimm, J, Pulver, Ae, Puri, V, Quested, D, Quinn, Em, Rasmussen, Hb, Réthelyi, Jm, Ribble, R, Rietschel, M, Riley, Bp, Ruggeri, Mirella, Schall, U, Schulze, Tg, Schwab, Sg, Scott, Rj, Shi, J, Sigurdsson, E, Silverman, Jm, Spencer, Cc, Stefansson, K, Strange, A, Strengman, E, Stroup, Ts, Suvisaari, J, Terenius, L, Thirumalai, S, Thygesen, Jh, Timm, S, Toncheva, D, van den Oord, E, van Os, J, Van, Winkel, R, Veldink, J, Walsh, D, Wang, Ag, Wiersma, D, Wildenauer, Db, Williams, Hj, Williams, Nm, Wormley, B, Zammit, S, Sullivan, Pf, O'Donovan, Mc, Daly, Mj, Gejman, Pv, ANS - Amsterdam Neuroscience, APH - Amsterdam Public Health, Adult Psychiatry, Functional Genomics, Neuroscience Campus Amsterdam - Neurobiology of Mental Health, Neuroscience Campus Amsterdam - Brain Mechanisms in Health & Disease, Psychiatrie & Neuropsychologie, RS: MHeNs School for Mental Health and Neuroscience, Myin-Germeys, Inez, De Hert, Marc, and van Winkel, Ruud

Subjects
Adult, Male, Psychosis, Genotype, Single-nucleotide polymorphism, Genome-wide association study, Biology, Nerve Fibers, Myelinated, Polymorphism, Single Nucleotide, Article, White matter, genome-wide, 03 medical and health sciences, 0302 clinical medicine, SDG 3 - Good Health and Well-being, mental disorders, medicine, Genetic predisposition, Humans, Genetic Predisposition to Disease, Biological Psychiatry, structural MRI, Genetics, neuroimaging, Case-control study, Brain, imaging, medicine.disease, 030227 psychiatry, 3. Good health, schizophrenia, Endophenotype, Phenotype, medicine.anatomical_structure, psychiatric, Schizophrenia, Case-Control Studies, Female, endophenotype, Genome-Wide Association Study, SNPs, Atrophy, 030217 neurology & neurosurgery
Abstract

BACKGROUND: Thousands of common single nucleotide polymorphisms (SNPs) are weakly associated with schizophrenia. It is likely that subsets of disease-associated SNPs are associated with distinct heritable disease-associated phenotypes. Therefore, we examined the shared genetic susceptibility modulating schizophrenia and brain volume. METHODS: Odds ratios for genome-wide SNP data were calculated in the sample collected by the Psychiatric Genome-wide Association Study Consortium (8690 schizophrenia patients and 11,831 control subjects, excluding subjects from the present study). These were used to calculate individual polygenic schizophrenia (risk) scores in an independent sample of 152 schizophrenia patients and 142 healthy control subjects with available structural magnetic resonance imaging scans. RESULTS: In the entire group, the polygenic schizophrenia score was significantly associated with total brain volume (R2 = .048, p = 1.6 × 10(-4)) and white matter volume (R2 = .051, p = 8.6 × 10(-5)) equally in patients and control subjects. The number of (independent) SNPs that substantially influenced both disease risk and white matter (n = 2020) was much smaller than the entire set of SNPs that modulated disease status (n = 14,751). From the set of 2020 SNPs, a group of 186 SNPs showed most evidence for association with white matter volume and an explorative functional analysis showed that these SNPs were located in genes with neuronal functions. CONCLUSIONS: These results indicate that a relatively small subset of schizophrenia genetic risk variants is related to the (normal) development of white matter. This, in turn, suggests that disruptions in white matter growth increase the susceptibility to develop schizophrenia.

Published
2013
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24. Systematic review of neurocognition in people with co-occurring alcohol misuse and depression

Author

Hunt, SA, Kay-Lambkin, FJ, Baker, AL, Michie, PT, Hunt, SA, Kay-Lambkin, FJ, Baker, AL, and Michie, PT

Abstract

© 2015 Elsevier B.V. Background Alcohol misuse and depression represent two major social and health problems globally. These conditions commonly co-occur and both are associated with significant cognitive impairment. Despite this, few studies have examined the impact on cognitive functioning of co-occurring alcohol misuse and depression. This study aims to critically review findings from peer-reviewed published articles examining neuropsychological test performance among samples of people with co-occurring alcohol misuse and depression. Method A comprehensive literature search was conducted, yielding six studies reporting neuropsychological profiles of people with co-occurring alcohol misuse and depression. Results comparing cognitive functioning of people with this comorbidity to those with alcohol misuse alone, depression alone, healthy controls and published norms were examined as well as those describing the correlation between depressive symptoms and cognitive functioning in people with alcohol use disorders. Results In the majority of instances, the comorbid groups did not differ significantly from those with depression only or alcohol misuse only, nor from healthy controls or published norms. In the cases where a difference in neuropsychological test scores between groups was found, it was not consistently identified across studies. However, visual memory was identified in two studies as being impaired in comorbid samples and is worthy of inclusion in future studies. Limitations Due to the small number of included studies and the large variation in inclusion criteria as well as differing assessment tools and methodologies between studies, the review did not include a quantitative synthesis. Conclusions Research into cognitive deficits among people with singly occurring versus co-occurring alcohol misuse and depression is accumulating. Evidence suggests that the neuropsychological performance among samples with this comorbidity is generally not severely impair

Published
2015

25. Biological insights from 108 schizophrenia-associated genetic loci

Author

Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Keong, JLC, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Mueller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Borglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Noethen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, O'Donovan, MC, Ripke, S, Neale, BM, Corvin, A, Walters, JTR, Farh, K-H, Holmans, PA, Lee, P, Bulik-Sullivan, B, Collier, DA, Huang, H, Pers, TH, Agartz, I, Agerbo, E, Albus, M, Alexander, M, Amin, F, Bacanu, SA, Begemann, M, Belliveau, RA, Bene, J, Bergen, SE, Bevilacqua, E, Bigdeli, TB, Black, DW, Bruggeman, R, Buccola, NG, Buckner, RL, Byerley, W, Cahn, W, Cai, G, Campion, D, Cantor, RM, Carr, VJ, Carrera, N, Catts, SV, Chambert, KD, Chan, RCK, Chen, RYL, Chen, EYH, Cheng, W, Cheung, EFC, Chong, SA, Cloninger, CR, Cohen, D, Cohen, N, Cormican, P, Craddock, N, Crowley, JJ, Curtis, D, Davidson, M, Davis, KL, Degenhardt, F, Del Favero, J, Demontis, D, Dikeos, D, Dinan, T, Djurovic, S, Donohoe, G, Drapeau, E, Duan, J, Dudbridge, F, Durmishi, N, Eichhammer, P, Eriksson, J, Escott-Price, V, Essioux, L, Fanous, AH, Farrell, MS, Frank, J, Franke, L, Freedman, R, Freimer, NB, Friedl, M, Friedman, JI, Fromer, M, Genovese, G, Georgieva, L, Giegling, I, Giusti-Rodriguez, P, Godard, S, Goldstein, JI, Golimbet, V, Gopal, S, Gratten, J, de Haan, L, Hammer, C, Hamshere, ML, Hansen, M, Hansen, T, Haroutunian, V, Hartmann, AM, Henskens, FA, Herms, S, Hirschhorn, JN, Hoffmann, P, Hofman, A, Hollegaard, MV, Hougaard, DM, Ikeda, M, Joa, I, Julia, A, Kahn, RS, Kalaydjieva, L, Karachanak-Yankova, S, Karjalainen, J, Kavanagh, D, Keller, MC, Kennedy, JL, Khrunin, A, Kim, Y, Klovins, J, Knowles, JA, Konte, B, Kucinskas, V, Kucinskiene, ZA, Kuzelova-Ptackova, H, Kahler, AK, Laurent, C, Keong, JLC, Lee, SH, Legge, SE, Lerer, B, Li, M, Li, T, Liang, K-Y, Lieberman, J, Limborska, S, Loughland, CM, Lubinski, J, Lonnqvist, J, Macek, M, Magnusson, PKE, Maher, BS, Maier, W, Mallet, J, Marsal, S, Mattheisen, M, Mattingsdal, M, McCarley, RW, McDonald, C, McIntosh, AM, Meier, S, Meijer, CJ, Melegh, B, Melle, I, Mesholam-Gately, RI, Metspalu, A, Michie, PT, Milani, L, Milanova, V, Mokrab, Y, Morris, DW, Mors, O, Murphy, KC, Murray, RM, Myin-Germeys, I, Mueller-Myhsok, B, Nelis, M, Nenadic, I, Nertney, DA, Nestadt, G, Nicodemus, KK, Nikitina-Zake, L, Nisenbaum, L, Nordin, A, O'Callaghan, E, O'Dushlaine, C, O'Neill, FA, Oh, S-Y, Olincy, A, Olsen, L, Van Os, J, Pantelis, C, Papadimitriou, GN, Papiol, S, Parkhomenko, E, Pato, MT, Paunio, T, Pejovic-Milovancevic, M, Perkins, DO, Pietilainen, O, Pimm, J, Pocklington, AJ, Powell, J, Price, A, Pulver, AE, Purcell, SM, Quested, D, Rasmussen, HB, Reichenberg, A, Reimers, MA, Richards, AL, Roffman, JL, Roussos, P, Ruderfer, DM, Salomaa, V, Sanders, AR, Schall, U, Schubert, CR, Schulze, TG, Schwab, SG, Scolnick, EM, Scott, RJ, Seidman, LJ, Shi, J, Sigurdsson, E, Silagadze, T, Silverman, JM, Sim, K, Slominsky, P, Smoller, JW, So, H-C, Spencer, CCA, Stahl, EA, Stefansson, H, Steinberg, S, Stogmann, E, Straub, RE, Strengman, E, Strohmaier, J, Stroup, TS, Subramaniam, M, Suvisaari, J, Svrakic, DM, Szatkiewicz, JP, Soderman, E, Thirumalai, S, Toncheva, D, Tosato, S, Veijola, J, Waddington, J, Walsh, D, Wang, D, Wang, Q, Webb, BT, Weiser, M, Wildenauer, DB, Williams, NM, Williams, S, Witt, SH, Wolen, AR, Wong, EHM, Wormley, BK, Xi, HS, Zai, CC, Zheng, X, Zimprich, F, Wray, NR, Stefansson, K, Visscher, PM, Adolfsson, R, Andreassen, OA, Blackwood, DHR, Bramon, E, Buxbaum, JD, Borglum, AD, Cichon, S, Darvasi, A, Domenici, E, Ehrenreich, H, Esko, T, Gejman, PV, Gill, M, Gurling, H, Hultman, CM, Iwata, N, Jablensky, AV, Jonsson, EG, Kendler, KS, Kirov, G, Knight, J, Lencz, T, Levinson, DF, Li, QS, Liu, J, Malhotra, AK, McCarroll, SA, McQuillin, A, Moran, JL, Mortensen, PB, Mowry, BJ, Noethen, MM, Ophoff, RA, Owen, MJ, Palotie, A, Pato, CN, Petryshen, TL, Posthuma, D, Rietschel, M, Riley, BP, Rujescu, D, Sham, PC, Sklar, P, St Clair, D, Weinberger, DR, Wendland, JR, Werge, T, Daly, MJ, Sullivan, PF, and O'Donovan, MC

Abstract

Schizophrenia is a highly heritable disorder. Genetic risk is conferred by a large number of alleles, including common alleles of small effect that might be detected by genome-wide association studies. Here we report a multi-stage schizophrenia genome-wide association study of up to 36,989 cases and 113,075 controls. We identify 128 independent associations spanning 108 conservatively defined loci that meet genome-wide significance, 83 of which have not been previously reported. Associations were enriched among genes expressed in brain, providing biological plausibility for the findings. Many findings have the potential to provide entirely new insights into aetiology, but associations at DRD2 and several genes involved in glutamatergic neurotransmission highlight molecules of known and potential therapeutic relevance to schizophrenia, and are consistent with leading pathophysiological hypotheses. Independent of genes expressed in brain, associations were enriched among genes expressed in tissues that have important roles in immunity, providing support for the speculated link between the immune system and schizophrenia.

Published
2014

26. Early detection of microstructural white matter changes associated with arterial pulsatility

Author

Jolly, TAD, Bateman, GA, Levi, CR, Parsons, MW, Michie, PT, Karayanidis, F, Jolly, TAD, Bateman, GA, Levi, CR, Parsons, MW, Michie, PT, and Karayanidis, F

Abstract

Increased cerebral blood flow pulsatility is common in vascular dementia and is associated with macrostructural damage to cerebral white matter or leukoaraiosis (LA). In this study, we examine whether cerebral blood flow pulsatility is associated with macrostructural and microstructural changes in cerebral white matter in older adults with no or mild LA and no evidence of dementia. Diffusion Tensor Imaging was used to measure fractional anisotropy (FA), an index of the microstructural integrity of white matter, and radial diffusivity (RaD), a measure sensitive to the integrity of myelin. When controlling for age, increased arterial pulsation was associated with deterioration in both measures of white matter microstructure but not LA severity. A stepwise multiple linear regression model revealed that arterial pulsatility index was the strongest predictor of FA (R = 0.483, adjusted R (2) = 0.220), followed by LA severity, but not age. These findings suggest that arterial pulsatility may provide insight into age-related reduction in white matter FA. Specifically, increased arterial pulsatility may increase perivascular shear stress and lead to accumulation of damage to perivascular oligodendrocytes, resulting in microstructural changes in white matter and contributing to proliferation of LA over time. Changes in cerebral blood flow pulsatility may therefore provide a sensitive index of white matter health that could facilitate the early detection of risk for perivascular white matter damage and the assessment of the effectiveness of preventative treatment targeted at reducing pulsatility.

Published
2013

28. Risk of road traffic accidents in patients discharged following treatment for psychotropic drug overdose: a self-controlled case series study in Australia.

Author

Dassanayake TL, Jones AL, Michie PT, Carter GL, McElduff P, Stokes BJ, Whyte IM, Dassanayake, Tharaka L, Jones, Alison L, Michie, Patricia T, Carter, Gregory L, McElduff, Patrick, Stokes, Barrie J, and Whyte, Ian M

Abstract

Background: Use of psychotropic drugs is known to impair driving and increase the risk of road traffic accidents. They are also the most common drugs taken in overdose in hospital-treated episodes of self-poisoning. Most patients who take psychotropic drug overdoses are discharged within 48 hours, while they still have possible subclinical drug effects.Objective: Using a self-controlled case series design, we aimed to determine whether patients with psychotropic drug overdose are at a higher risk of a traffic accident in the period following discharge compared with a control period not associated with hospital-treated drug overdose.Methodology: Using the New South Wales (NSW) Admitted Patient Data Collection (APDC) as the primary source, we retrieved 40 845 hospital separation records dated between 1 July 2000 and 30 June 2008 (8 years) in patients aged 18-80 years admitted to a hospital in NSW following an intentional self-poisoning with a psychotropic drug (coded X61 or X62 as the International Classification of Diseases, 10th Edition, [ICD-10] external cause of injury). Of these, 33459 hospital separations (i.e. discharges, transfers and deaths) involving 24 284 patients were considered eligible as the patients were discharged directly into the community where they could have driven a motor vehicle. We selected three separate post-admission periods (3 days, 1 week and 4 weeks), subtracted the number of inpatient days from each and calculated three separate post-discharge periods (immediate, intermediate and extended, respectively) for each episode of overdose. The control period was the duration of the study period where the individual was aged 18 years or older, excluding the total person-days in the post-discharge period/s and the index inpatient period/s. The APDC dataset was linked to the NSW Roads and Traffic Authority CrashLink dataset to identify any accidents in which each patient was involved as a motor-vehicle driver during the follow-up period. Incidence rate ratio (IRR) for matched post-discharge and control periods was found using random effects Poisson regression.Results: Seventy-two percent of the subjects were discharged within 2 days following their admission with overdose. Compared with the corresponding control periods the risk of a traffic accident was 3.5 times higher (IRR = 3.49; 95% CI 1.66, 7.33; p = 0.001) during the immediate, 1.9 times higher (IRR = 1.88; 95% CI 1.09, 3.25; p = 0.023) during the intermediate and 1.6 times higher (IRR = 1.65; 95% CI 1.27, 2.15; p = 0.0002) during the extended post-discharge period.Conclusions: Self-poisoning with psychotropic drugs is associated with a markedly increased risk of a traffic accident during the first few days following discharge. These findings raise clinical and medico-legal implications concerning fitness-to-drive during this period. The risk reduces with time but remains significantly elevated after 4 weeks post-overdose. Further research is necessary to find out the factors contributing to this ongoing risk. [ABSTRACT FROM AUTHOR]

Published
2012
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30. Contextualised Processing of Stimuli Modulates Auditory Mismatch Responses in the Rat.

Author

Jalewa J, Todd J, Michie PT, Hodgson DM, and Harms L

Subjects
Animals, Rats, Male, Evoked Potentials, Auditory physiology, Electroencephalography methods, Rats, Wistar, Acoustic Stimulation methods, Auditory Perception physiology
Abstract

Mismatch negativity (MMN), an auditory prediction error signal, is an enhanced response to unexpected (deviant) stimuli compared to expected (standard) stimuli. There is strong interest in MMN due to reliable findings of reduced MMN in schizophrenia. To interpret reduced MMN in schizophrenia, an enhanced understanding of the factors that influence MMN amplitude could lead to a better understanding of neural mechanisms underpinning the reduction. While several laboratories have observed mismatch responses (MMRs) in rodents, this study assesses how MMR is altered in more complex auditory sequences in rats. Prediction-errors are elicited in relation to "predictive" internal models of regularities. These internal models are updated dynamically when a regularity changes, but human MMN exhibits order effects when two regularities alternate; while deviants in both regularities elicit MMN (ie, the model updates) there is a slower build-up in MMN amplitude over time in the second encountered regularity type. We investigate whether order effects occur in rat MMRs. MMRs were studied to rare ascending and descending frequency deviations in awake, freely moving Wistar rats using wireless telemetry in both separate sequences (one regularity at a time) and in alternating sequences where regularities changed back and forth. The rat MMR did not show order effects, however, substantial MMRs occurred in response to both ascending and descending deviants in the alternating context but to the ascending deviant only when the same regularities were presented separately. The longer-term sequence structure altered prediction-error signalling in rat auditory system revealing a long term context sensitivity in internal models., Competing Interests: Declaration of Conflicting InterestsThe authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Published
2025
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31. Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study.

Author

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

Subjects
Humans, Adult, Female, Male, Cerebral Cortex pathology, Cerebral Cortex physiopathology, Nerve Net pathology, Nerve Net physiopathology, Nerve Net diagnostic imaging, Brain pathology, Brain physiopathology, Middle Aged, Neural Pathways physiopathology, Neural Pathways pathology, Young Adult, Schizophrenia pathology, Schizophrenia physiopathology, Connectome methods, Magnetic Resonance Imaging methods
Abstract

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia., (© 2024. The Author(s).)

Published
2024
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32. Cortical similarities in psychiatric and mood disorders identified in federated VBM analysis via COINSTAC.

Author

Rootes-Murdy K, Panta S, Kelly R, Romero J, Quidé Y, Cairns MJ, Loughland C, Carr VJ, Catts SV, Jablensky A, Green MJ, Henskens F, Kiltschewskij D, Michie PT, Mowry B, Pantelis C, Rasser PE, Reay WR, Schall U, Scott RJ, Watkeys OJ, Roberts G, Mitchell PB, Fullerton JM, Overs BJ, Kikuchi M, Hashimoto R, Matsumoto J, Fukunaga M, Sachdev PS, Brodaty H, Wen W, Jiang J, Fani N, Ely TD, Lorio A, Stevens JS, Ressler K, Jovanovic T, van Rooij SJH, Federmann LM, Jockwitz C, Teumer A, Forstner AJ, Caspers S, Cichon S, Plis SM, Sarwate AD, and Calhoun VD

Abstract

Structural neuroimaging studies have identified a combination of shared and disorder-specific patterns of gray matter (GM) deficits across psychiatric disorders. Pooling large data allows for examination of a possible common neuroanatomical basis that may identify a certain vulnerability for mental illness. Large-scale collaborative research is already facilitated by data repositories, institutionally supported databases, and data archives. However, these data-sharing methodologies can suffer from significant barriers. Federated approaches augment these approaches by enabling access or more sophisticated, shareable and scaled-up analyses of large-scale data. We examined GM alterations using Collaborative Informatics and Neuroimaging Suite Toolkit for Anonymous Computation, an open-source, decentralized analysis application. Through federated analysis of eight sites, we identified significant overlap in the GM patterns ( n  = 4,102) of individuals with schizophrenia, major depressive disorder, and autism spectrum disorder. These results show cortical and subcortical regions that may indicate a shared vulnerability to psychiatric disorders., Competing Interests: The authors declare no competing interests.

Published
2024
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33. Estimating multimodal brain variability in schizophrenia spectrum disorders: A worldwide ENIGMA study.

Author

Omlor W, Rabe F, Fuchs S, Cecere G, Homan S, Surbeck W, Kallen N, Georgiadis F, Spiller T, Seifritz E, Weickert T, Bruggemann J, Weickert C, Potkin S, Hashimoto R, Sim K, Rootes-Murdy K, Quide Y, Houenou J, Banaj N, Vecchio D, Piras F, Piras F, Spalletta G, Salvador R, Karuk A, Pomarol-Clotet E, Rodrigue A, Pearlson G, Glahn D, Tomecek D, Spaniel F, Skoch A, Kirschner M, Kaiser S, Kochunov P, Fan FM, Andreassen OA, Westlye LT, Berthet P, Calhoun VD, Howells F, Uhlmann A, Scheffler F, Stein D, Iasevoli F, Cairns MJ, Carr VJ, Catts SV, Di Biase MA, Jablensky A, Green MJ, Henskens FA, Klauser P, Loughland C, Michie PT, Mowry B, Pantelis C, Rasser PE, Schall U, Scott R, Zalesky A, de Bartolomeis A, Barone A, Ciccarelli M, Brunetti A, Cocozza S, Pontillo G, Tranfa M, Di Giorgio A, Thomopoulos SI, Jahanshad N, Thompson PM, van Erp T, Turner J, and Homan P

Abstract

Objective: Schizophrenia is a multifaceted disorder associated with structural brain heterogeneity. Despite its relevance for identifying illness subtypes and informative biomarkers, structural brain heterogeneity in schizophrenia remains incompletely understood. Therefore, the objective of this study was to provide a comprehensive insight into the structural brain heterogeneity associated with schizophrenia., Methods: This meta- and mega-analysis investigated the variability of multimodal structural brain measures of white and gray matter in individuals with schizophrenia versus healthy controls. Using the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6139 individuals for a given brain measure, we examined variability in cortical thickness, surface area, folding index, subcortical volume and fractional anisotropy., Results: We found that individuals with schizophrenia are distinguished by higher heterogeneity in the frontotemporal network with regard to multimodal structural measures. Moreover, individuals with schizophrenia showed higher homogeneity of the folding index, especially in the left parahippocampal region., Conclusions: Higher multimodal heterogeneity in frontotemporal regions potentially implies different subtypes of schizophrenia that converge on impaired frontotemporal interaction as a core feature of the disorder. Conversely, more homogeneous folding patterns in the left parahippocampal region might signify a consistent characteristic of schizophrenia shared across subtypes. These findings underscore the importance of structural brain variability in advancing our neurobiological understanding of schizophrenia, and aid in identifying illness subtypes as well as informative biomarkers.

Published
2023
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34. Why mismatch negativity continues to hold potential in probing altered brain function in schizophrenia.

Author

Todd J, Salisbury D, and Michie PT

Abstract

The brain potential known as mismatch negativity (MMN) is one of the most studied indices of altered brain function in schizophrenia. This review looks at what has been learned about MMN in schizophrenia over the last three decades and why the level of interest and activity in this field of research remains strong. A diligent consideration of available evidence suggests that MMN can serve as a biomarker in schizophrenia, but perhaps not the kind of biomarker that early research supposed. This review concludes that MMN measurement is likely to be most useful as a monitoring and response biomarker enabling tracking of an underlying pathology and efficacy of interventions, respectively. The role of, and challenges presented by, pre-clinical models is discussed as well as the merits of different methodologies that can be brought to bear in pursuing a deeper understanding of pathophysiology that might explain smaller MMN in schizophrenia., Competing Interests: The authors declare no conflicts of interest., (© 2023 The Authors. Psychiatry and Clinical Neurosciences Reports published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Psychiatry and Neurology.)

Published
2023
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35. 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, Hulshoff Pol HE, Kahn RS, Ayesa-Arriola R, Ortiz-García de la Foz V, Tordesillas-Gutierrez D, Vázquez-Bourgon J, Crespo-Facorro B, Alnæs D, Dahl A, Westlye LT, Agartz I, Andreassen OA, Jönsson EG, Kochunov P, Bruggemann JM, Catts SV, Michie PT, Mowry BJ, Quidé 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 JK, Ringwald KG, Stein F, Jansen A, Kircher TTJ, Nenadić I, Krämer 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, Sarró 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 WS, Chung YC, 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, Díaz-Caneja CM, Janssen J, Lois NG, Arango C, Tomyshev AS, Lebedeva I, Cervenka S, Sellgren CM, Georgiadis F, Kirschner M, Kaiser S, Hajek T, Skoch A, Spaniel F, Kim M, Kwak YB, Oh S, Kwon JS, James A, Bakker G, Knöchel C, Stäblein M, Oertel V, Uhlmann A, Howells FM, Stein DJ, Temmingh HS, Diaz-Zuluaga AM, Pineda-Zapata JA, López-Jaramillo C, Homan S, Ji E, Surbeck W, Homan P, Fisher 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

Subjects
Male, Female, Humans, Case-Control Studies, Brain diagnostic imaging, Cerebral Cortex, Magnetic Resonance Imaging methods, Functional Laterality, Schizophrenia diagnostic imaging
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
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36. The effect of schizophrenia risk factors on mismatch responses in a rat model.

Author

Jalewa J, Todd J, Michie PT, Hodgson DM, and Harms L

Subjects
Animals, Female, Male, Pregnancy, Rats, Acoustic Stimulation, Electroencephalography, Evoked Potentials, Auditory physiology, Rats, Wistar, Risk Factors, Schizophrenia chemically induced
Abstract

Reduced mismatch negativity (MMN), a robust finding in schizophrenia, has prompted interest in MMN as a preclinical biomarker of schizophrenia. The rat brain can generate human-like mismatch responses (MMRs) which therefore enables the exploration of the neurobiology of reduced MMRs. Given epidemiological evidence that two developmental factors, maternal infection and adolescent cannabis use, increase the risk of schizophrenia, we determined the effect of these two developmental risk factors on rat MMR amplitude in different auditory contexts. MMRs were assessed in awake adult male and female Wistar rats that were offspring of pregnant dams treated with either a viral infection mimetic (poly I:C) inducing maternal immune activation (MIA) or saline control. In adolescence, subgroups of the prenatal treatment groups were exposed to either a synthetic cannabinoid (adolescent cannabinoid exposure: ACE) or vehicle. The context under which MMRs were obtained was manipulated by employing two different oddball paradigms, one that manipulated the physical difference between rare and common auditory stimuli, and another that manipulated the probability of the rare stimulus. The design of the multiple stimulus sequences across the two paradigms also allowed an investigation of context on MMRs to two identical stimulus sequences. Male offspring exposed to each of the risk factors for schizophrenia (MIA, ACE or both) showed a reduction in MMR, which was evident only in the probability paradigm, with no effects seen in the physical difference. Our findings highlight the importance of contextual factors induced by paradigm manipulations and sex for modeling schizophrenia-like MMN impairments in rats., (© 2022 The Authors. Psychophysiology published by Wiley Periodicals LLC on behalf of Society for Psychophysiological Research.)

Published
2023
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37. Virtual Ontogeny of Cortical Growth Preceding Mental Illness.

Author

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

Subjects
Cerebral Cortex, Child, Female, Humans, Infant, Newborn, Magnetic Resonance Imaging methods, Pregnancy, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder genetics, Autism Spectrum Disorder pathology, Bipolar Disorder, Depressive Disorder, Major pathology, Premature Birth pathology
Abstract

Background: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life., Methods: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed., Results: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth., Conclusions: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy., (Copyright © 2022 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.)

Published
2022
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38. Acute effects of Δ 9 -tetrahydrocannabinol and cannabidiol on auditory mismatch negativity.

Author

Greenwood LM, Broyd SJ, van Hell HH, Todd J, Jones A, Murray RM, Croft RJ, Michie PT, and Solowij N

Subjects
Dronabinol pharmacology, Humans, Cannabidiol pharmacology, Cannabinoids, Cannabis, Hallucinogens
Abstract

Rationale: Mismatch negativity (MMN) is a candidate endophenotype for schizophrenia subserved by N-methyl-D-aspartate receptor (NMDAR) function and there is increasing evidence that prolonged cannabis use adversely affects MMN generation. Few human studies have investigated the acute effects of cannabinoids on brain-based biomarkers of NMDAR function and synaptic plasticity., Objectives: The current study investigated the acute effects of Δ 9 -tetrahydrocannabinol (THC) and cannabidiol (CBD) alone and in combination on the mismatch negativity (MMN)., Methods: In a randomised, double-blind, crossover placebo-controlled study, 18 frequent and 18 less-frequent cannabis users underwent 5 randomised drug sessions administered via vaporiser: (1) placebo; (2) THC 8 mg; (3) CBD 400 mg; (4) THC 8 mg + CBD 4 mg [THC + CBD low ]; (5) THC 12 mg + CBD 400 mg [THC + CBD high ]. Participants completed a multifeature MMN auditory oddball paradigm with duration, frequency and intensity deviants (6% each)., Results: Relative to placebo, both THC and CBD were observed to increase duration and intensity MMN amplitude in less-frequent users, and THC also increased frequency MMN in this group. The addition of low-dose CBD added to THC attenuated the effect of THC on duration and intensity MMN amplitude in less-frequent users. The same pattern of effects was observed following high-dose CBD added to THC on duration and frequency MMN in frequent users., Conclusions: The pattern of effects following CBD combined with THC on MMN may be subserved by different underlying neurobiological interactions within the endocannabinoid system that vary as a function of prior cannabis exposure. These results highlight the complex interplay between the acute effects of exogenous cannabinoids and NMDAR function. Further research is needed to determine how this process normalises after the acute effects dissipate and following repeated acute exposure., (© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Published
2022
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39. Mapping genomic loci implicates genes and synaptic biology in schizophrenia.

Author

Trubetskoy V, Pardiñas AF, Qi T, Panagiotaropoulou G, Awasthi S, Bigdeli TB, Bryois J, Chen CY, Dennison CA, Hall LS, Lam M, Watanabe K, Frei O, Ge T, Harwood JC, Koopmans F, Magnusson S, Richards AL, Sidorenko J, Wu Y, Zeng J, Grove J, Kim M, Li Z, Voloudakis G, Zhang W, Adams M, Agartz I, Atkinson EG, Agerbo E, Al Eissa M, Albus M, Alexander M, Alizadeh BZ, Alptekin K, Als TD, Amin F, Arolt V, Arrojo M, Athanasiu L, Azevedo MH, Bacanu SA, Bass NJ, Begemann M, Belliveau RA, Bene J, Benyamin B, Bergen SE, Blasi G, Bobes J, Bonassi S, Braun A, Bressan RA, Bromet EJ, Bruggeman R, Buckley PF, Buckner RL, Bybjerg-Grauholm J, Cahn W, Cairns MJ, Calkins ME, Carr VJ, Castle D, Catts SV, Chambert KD, Chan RCK, Chaumette B, Cheng W, Cheung EFC, Chong SA, Cohen D, Consoli A, Cordeiro Q, Costas J, Curtis C, Davidson M, Davis KL, de Haan L, Degenhardt F, DeLisi LE, Demontis D, Dickerson F, Dikeos D, Dinan T, Djurovic S, Duan J, Ducci G, Dudbridge F, Eriksson JG, Fañanás L, Faraone SV, Fiorentino A, Forstner A, Frank J, Freimer NB, Fromer M, Frustaci A, Gadelha A, Genovese G, Gershon ES, Giannitelli M, Giegling I, Giusti-Rodríguez P, Godard S, Goldstein JI, González Peñas J, González-Pinto A, Gopal S, Gratten J, Green MF, Greenwood TA, Guillin O, Gülöksüz S, Gur RE, Gur RC, Gutiérrez B, Hahn E, Hakonarson H, Haroutunian V, Hartmann AM, Harvey C, Hayward C, Henskens FA, Herms S, Hoffmann P, Howrigan DP, Ikeda M, Iyegbe C, Joa I, Julià A, Kähler AK, Kam-Thong T, Kamatani Y, Karachanak-Yankova S, Kebir O, Keller MC, Kelly BJ, Khrunin A, Kim SW, Klovins J, Kondratiev N, Konte B, Kraft J, Kubo M, Kučinskas V, Kučinskiene ZA, Kusumawardhani A, Kuzelova-Ptackova H, Landi S, Lazzeroni LC, Lee PH, Legge SE, Lehrer DS, Lencer R, Lerer B, Li M, Lieberman J, Light GA, Limborska S, Liu CM, Lönnqvist J, Loughland CM, Lubinski J, Luykx JJ, Lynham A, Macek M Jr, Mackinnon A, Magnusson PKE, Maher BS, Maier W, Malaspina D, Mallet J, Marder SR, Marsal S, Martin AR, Martorell L, Mattheisen M, McCarley RW, McDonald C, McGrath JJ, Medeiros H, Meier S, Melegh B, Melle I, Mesholam-Gately RI, Metspalu A, Michie PT, Milani L, Milanova V, Mitjans M, Molden E, Molina E, Molto MD, Mondelli V, Moreno C, Morley CP, Muntané G, Murphy KC, Myin-Germeys I, Nenadić I, Nestadt G, Nikitina-Zake L, Noto C, Nuechterlein KH, O'Brien NL, O'Neill FA, Oh SY, Olincy A, Ota VK, Pantelis C, Papadimitriou GN, Parellada M, Paunio T, Pellegrino R, Periyasamy S, Perkins DO, Pfuhlmann B, Pietiläinen O, Pimm J, Porteous D, Powell J, Quattrone D, Quested D, Radant AD, Rampino A, Rapaport MH, Rautanen A, Reichenberg A, Roe C, Roffman JL, Roth J, Rothermundt M, Rutten BPF, Saker-Delye S, Salomaa V, Sanjuan J, Santoro ML, Savitz A, Schall U, Scott RJ, Seidman LJ, Sharp SI, Shi J, Siever LJ, Sigurdsson E, Sim K, Skarabis N, Slominsky P, So HC, Sobell JL, Söderman E, Stain HJ, Steen NE, Steixner-Kumar AA, Stögmann E, Stone WS, Straub RE, Streit F, Strengman E, Stroup TS, Subramaniam M, Sugar CA, Suvisaari J, Svrakic DM, Swerdlow NR, Szatkiewicz JP, Ta TMT, Takahashi A, Terao C, Thibaut F, Toncheva D, Tooney PA, Torretta S, Tosato S, Tura GB, Turetsky BI, Üçok A, Vaaler A, van Amelsvoort T, van Winkel R, Veijola J, Waddington J, Walter H, Waterreus A, Webb BT, Weiser M, Williams NM, Witt SH, Wormley BK, Wu JQ, Xu Z, Yolken R, Zai CC, Zhou W, Zhu F, Zimprich F, Atbaşoğlu EC, Ayub M, Benner C, Bertolino A, Black DW, Bray NJ, Breen G, Buccola NG, Byerley WF, Chen WJ, Cloninger CR, Crespo-Facorro B, Donohoe G, Freedman R, Galletly C, Gandal MJ, Gennarelli M, Hougaard DM, Hwu HG, Jablensky AV, McCarroll SA, Moran JL, Mors O, Mortensen PB, Müller-Myhsok B, Neil AL, Nordentoft M, Pato MT, Petryshen TL, Pirinen M, Pulver AE, Schulze TG, Silverman JM, Smoller JW, Stahl EA, Tsuang DW, Vilella E, Wang SH, Xu S, Adolfsson R, Arango C, Baune BT, Belangero SI, Børglum AD, Braff D, Bramon E, Buxbaum JD, Campion D, Cervilla JA, Cichon S, Collier DA, Corvin A, Curtis D, Forti MD, Domenici E, Ehrenreich H, Escott-Price V, Esko T, Fanous AH, Gareeva A, Gawlik M, Gejman PV, Gill M, Glatt SJ, Golimbet V, Hong KS, Hultman CM, Hyman SE, Iwata N, Jönsson EG, Kahn RS, Kennedy JL, Khusnutdinova E, Kirov G, Knowles JA, Krebs MO, Laurent-Levinson C, Lee J, Lencz T, Levinson DF, Li QS, Liu J, Malhotra AK, Malhotra D, McIntosh A, McQuillin A, Menezes PR, Morgan VA, Morris DW, Mowry BJ, Murray RM, Nimgaonkar V, Nöthen MM, Ophoff RA, Paciga SA, Palotie A, Pato CN, Qin S, Rietschel M, Riley BP, Rivera M, Rujescu D, Saka MC, Sanders AR, Schwab SG, Serretti A, Sham PC, Shi Y, St Clair D, Stefánsson H, Stefansson K, Tsuang MT, van Os J, Vawter MP, Weinberger DR, Werge T, Wildenauer DB, Yu X, Yue W, Holmans PA, Pocklington AJ, Roussos P, Vassos E, Verhage M, Visscher PM, Yang J, Posthuma D, Andreassen OA, Kendler KS, Owen MJ, Wray NR, Daly MJ, Huang H, Neale BM, Sullivan PF, Ripke S, Walters JTR, and O'Donovan MC

Subjects
Alleles, Genetic Predisposition to Disease genetics, Genomics, Humans, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study, Schizophrenia genetics
Abstract

Schizophrenia has a heritability of 60-80% 1 , much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Published
2022
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40. Improvements in Hope, Engagement and Functioning Following a Recovery-Focused Sub-Acute Inpatient Intervention: a Six-Month Evaluation.

Author

Hollier TM, Frost BG, Michie PT, Lewin TJ, and Sly KA

Subjects
Adult, Aftercare, Humans, Inpatients, Patient Discharge, Mental Disorders therapy, Mental Health Services
Abstract

Few studies have examined the post-discharge benefits associated with recover-oriented programs delivered in inpatient and sub-acute mental health settings. The aim of this study was to evaluate the medium-term outcomes of a 6-week sub-acute inpatient intervention program for 27 service users with a diagnosis of serious mental illness (mean age = 33.22 years, 70.4% with a psychosis diagnosis). Recovery data were collected on admission, at discharge, and at 3- and 6-months post-discharge using self-report, collaborative and clinical measures. The three clinician-rated measures (assessing therapeutic engagement, functioning, and life skills) revealed linear improvements from admission to 6-month follow-up (with mean z-change ranging from 0.72 to 1.35), as did the self-reported social connection measure (Mental Health Recovery Star, MHRS; mean z-change: 1.05). There were also curvilinear improvements in self-determination and self-reported MHRS symptom management and functioning scores; however, only modest changes were detected in hope (Herth Hope Index) and MHRS self-belief scores. Change scores based on self-reported and clinician-rated measures tended to be uncorrelated. An exploration of client-level outcomes revealed three recovery trajectory subgroups: transient (21.7%), gradual (34.8%), or sustained (43.5%) improvement; with members of the latter group tending to have longer illness durations. The study's findings are encouraging, to the extent that they demonstrate recovery-focused sub-acute inpatient programs can promote clinical recovery and aspects of personal recovery. However, they also suggest that recovery perspectives differ between clients and clinicians, and that far more work is required to understand the psychological factors that generate and sustain the hope that recovery is possible., (© 2021. Crown.)

Published
2021
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41. Dissociable theta networks underlie the switch and mixing costs during task switching.

Author

McKewen M, Cooper PS, Skippen P, Wong ASW, Michie PT, and Karayanidis F

Subjects
Adolescent, Adult, Female, Humans, Male, Young Adult, Cerebral Cortex physiology, Connectome, Electroencephalography, Executive Function physiology, Nerve Net physiology, Psychomotor Performance physiology, Theta Rhythm physiology
Abstract

During task-switching paradigms, both event-related potentials and time-frequency analyses show switch and mixing effects at frontal and parietal sites. Switch and mixing effects are associated with increased power in broad frontoparietal networks, typically stronger in the theta band (~4-8 Hz). However, it is not yet known whether mixing and switch costs rely upon common or distinct networks. In this study, we examine proactive and reactive control networks linked to task switching and mixing effects, and whether strength of connectivity in these networks is associated with behavioural outcomes. Participants (n = 197) completed a cued-trials task-switching paradigm with concurrent electroencephalography, after substantial task practice to establish strong cue-stimulus-response representations. We used inter-site phase clustering, a measure of functional connectivity across electrode sites, to establish cross-site connectivity from a frontal and a parietal seed. Distinct theta networks were activated during proactive and reactive control periods. During the preparation interval, mixing effects were associated with connectivity from the frontal seed to parietal sites, and switch effects with connectivity from the parietal seed to occipital sites. Lateralised occipital connectivity was common to both switch and mixing effects. After target onset, frontal and parietal seeds showed a similar pattern of connectivity across trial types. These findings are consistent with distinct and common proactive control networks and common reactive networks in highly practised task-switching performers., (© 2021 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.)

Published
2021
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42. Altered Functional Connectivity and Cognition Persists 4 Years After a Transient Ischemic Attack or Minor Stroke.

Author

Nicolas K, Goodin P, Visser MM, Michie PT, Bivard A, Levi C, Parsons MW, and Karayanidis F

Abstract

Background and Purpose: Altered executive functions and resting-state functional connectivity (rsFC) are common following a minor stroke or transient ischemic attack (TIA). However, the long-term persistence of these abnormalities is not well-studied. We investigated whether there were cognitive and rsFC differences between (a) controls and minor cerebrovascular event (CVE) patients and (b) between CVE patients with and without an imaging confirmed infarct (i.e., minor stroke and TIA, respectively) at an average of 3.8 years following their event. Methods: Structural and resting-state imaging and cognitive assessments including the Montreal Cognitive Assessment, the Trail Making Task and the National Institute of Health (NIH) Cognition Toolbox were conducted on 42 patients (minor stroke = 17, TIA = 25) and 20 healthy controls (total N = 62). Results: Controls performed better than patients on two measures of executive functioning (both p < 0.046) and had reduced rsFC between the frontoparietal and default mode networks (FPN and DMN, respectively; p = 0.035). No cognitive differences were found between minor stroke and TIA patients, however, rsFC differences were found within the FPN and the DMN (both p < 0.013). Specifically, increased connectivity within the FPN was associated with faster performance in the minor stroke group but not the TIA group ( p = 0.047). Conclusions: These findings suggest that transient or relatively minor cerebrovascular events are associated with persistent disruption of functional connectivity of neural networks and cognitive performance. These findings suggest a need for novel interventions beyond secondary prevention to reduce the risk of persistent cognitive deficits., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Nicolas, Goodin, Visser, Michie, Bivard, Levi, Parsons and Karayanidis.)

Published
2021
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43. The Role of Glutamate Neurotransmission in Mismatch Negativity (MMN), A Measure of Auditory Synaptic Plasticity and Change-detection.

Author

Harms L, Parras GG, Michie PT, and Malmierca MS

Subjects
Acoustic Stimulation, Electroencephalography, Neuronal Plasticity, Synaptic Transmission, Evoked Potentials, Auditory, Glutamic Acid
Abstract

Mismatch negativity (MMN) is an electrophysiological signature that occurs in response to unexpected stimuli. It is often referred to as a measure of memory-based change detection, because the elicitation of a prediction error response relies on the formation of a prediction, which in turn, is dependent upon intact memory of previous auditory stimulation. As such, the MMN is altered in conditions in which memory is affected, such as Alzheimer's disease, schizophrenia and healthy aging. The most prominent pharmacological finding for MMN strengthens the link between MMN and synaptic plasticity, as glutamate N-methyl-d-aspartate receptor (NMDA-R) antagonists reduce the MMN response. However, recent data has begun to demonstrate that the link between NMDA-R function and MMN is not as clear as once thought, with low dose and low affinity NMDA-R antagonists observed to facilitate MMN., (Copyright © 2020 IBRO. Published by Elsevier Ltd. All rights reserved.)

Published
2021
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44. Do rat auditory event related potentials exhibit human mismatch negativity attributes related to predictive coding?

Author

Jalewa J, Todd J, Michie PT, Hodgson DM, and Harms L

Subjects
Acoustic Stimulation, Animals, Electroencephalography, Humans, Rats, Schizophrenia, Evoked Potentials, Auditory
Abstract

Rodent models play a significant role in understanding disease mechanisms and the screening of new treatments. With regard to psychiatric disorders such as schizophrenia, however, it is difficult to replicate the human symptoms in rodents because these symptoms are often either 'uniquely human' or are only conveyed via self-report. There is a growing interest in rodent mismatch responses (MMRs) as a translatable 'biomarker' for disorders such as schizophrenia. In this review, we will summarize the attributes of human MMN, and discuss the scope of exploring the attributes of human MMN in rodents. Here, we examine how reliably MMRs that are measured in rats mimic human attributes, and present original data examining whether manipulations of stimulus conditions known to modulate human MMN, do the same for rat MMRs. Using surgically-implanted epidural electroencephalographic electrodes and wireless telemetry in freely-moving rats, we observed human-like modulations of MMRs, namely that larger MMRs were elicited to unexpected (deviant) stimuli that a) had a larger change in pitch compared to the expected (standard) stimulus, b) were less frequently presented (lower probability), and c) had no jitter (stable stimulus onset asynchrony) compared to high jitter. Overall, these findings contribute to the mounting evidence for rat MMRs as a good analogue of human MMN, bolstering the development of a novel approach in future to validate the preclinical models based on a translatable biomarker, MMN., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Published
2021
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45. Reconsidering electrophysiological markers of response inhibition in light of trigger failures in the stop-signal task.

Author

Skippen P, Fulham WR, Michie PT, Matzke D, Heathcote A, and Karayanidis F

Subjects
Adult, Electroencephalography, Event-Related Potentials, P300 physiology, Humans, Attention physiology, Evoked Potentials physiology, Executive Function physiology, Inhibition, Psychological, Psychomotor Performance physiology
Abstract

This study investigates the neural correlates underpinning response inhibition using a parametric ex-Gaussian model of stop-signal task performance, fit with hierarchical Bayesian methods, in a large healthy sample (N = 156). The parametric model accounted for both stop-signal reaction time (SSRT) and trigger failure (i.e., failures to initiate the inhibition process). The returned SSRT estimate (SSRT EXG3 ) was attenuated by ≈65 ms compared to traditional nonparametric SSRT estimates (SSRT int ). The amplitude and latency of the N1 and P3 event-related potential components were derived for both stop-success and stop-failure trials and compared to behavioral estimates derived from traditional (SSRT int ) and parametric (SSRT EXG3 , trigger failure) models. Both the fronto-central N1 and P3 peaked earlier and were larger for stop-success than stop-failure trials. For stop-failure trials only, N1 peak latency correlated with both SSRT estimates as well as trigger failure and temporally coincided with SSRT EXG3 , but not SSRT int . In contrast, P3 peak and onset latency were not associated with any behavioral estimates of inhibition for either trial type. While the N1 peaked earlier for stop-success than stop-failure trials, this effect was not found in poor task performers (i.e., high trigger failure/slow SSRT). These findings are consistent with attentional modulation of both the speed and reliability of the inhibition process, but not for poor performers. Together with the absence of any P3 onset latency effect, our findings suggest that attentional mechanisms are important in supporting speeded and reliable inhibition processes required in the stop-signal task., (© 2020 Society for Psychophysiological Research.)

Published
2020
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46. Adolescent cannabinoid exposure interacts with other risk factors in schizophrenia: A review of the evidence from animal models.

Author

Dunn AL, Michie PT, Hodgson DM, and Harms L

Subjects
Adolescent, Animals, Disease Models, Animal, Female, Humans, Male, Maternal Deprivation, Risk Factors, Cannabinoids, Cannabis, Schizophrenia
Abstract

Many factors and their interaction are linked to the aetiology of schizophrenia, leading to the development of animal models of multiple risk factors and adverse exposures. Differentiating between separate and combined effects for each factor could better elucidate schizophrenia pathology, and drive development of preventative strategies for high-load risk factors. An epidemiologically valid risk factor commonly associated with schizophrenia is adolescent cannabis use. The aim of this review is to evaluate how early-life adversity from various origins, in combination with adolescent cannabinoid exposure interact, and whether these interactions confer main, synergistic or protective effects in animal models of schizophrenia-like behavioural, cognitive and morphological alterations. Patterns emerge regarding which models show consistent synergistic or protective effects, particularly those models incorporating early-life exposure to maternal deprivation and maternal immune activation, and sex-specific effects are observed. It is evident that more research needs to be conducted to better understand the risks and alterations of interacting factors, with particular interest in sex differences, to better understand the translatability of these preclinical models to humans., Competing Interests: Declaration of Competing Interest The authors have no declarations of interest., (Copyright © 2020 Elsevier Ltd. All rights reserved.)

Published
2020
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47. Wnt receptor gene FZD1 was associated with schizophrenia in genome-wide SNP analysis of the Australian Schizophrenia Research Bank cohort.

Author

Liu X, Low SK, Atkins JR, Wu JQ, Reay WR, Cairns HM, Green MJ, Schall U, Jablensky A, Mowry B, Michie PT, Catts SV, Henskens F, Pantelis C, Loughland C, Boddy AV, Tooney PA, Scott RJ, Carr VJ, and Cairns MJ

Subjects
Australia, Cohort Studies, Frizzled Receptors genetics, Genetic Predisposition to Disease, Humans, Polymorphism, Single Nucleotide genetics, Genome-Wide Association Study, Schizophrenia genetics
Abstract

Objectives: Large-scale genetic analysis of common variation in schizophrenia has been a powerful approach to understanding this complex but highly heritable psychotic disorder. To further investigate loci, genes and pathways associated more specifically in the well-characterized Australian Schizophrenia Research Bank cohort, we applied genome-wide single-nucleotide polymorphism analysis in these three annotation categories., Methods: We performed a case-control genome-wide association study in 429 schizophrenia samples and 255 controls. Post-genome-wide association study analyses were then integrated with genomic annotations to explore the enrichment of variation at the gene and pathway level. We also examine candidate single-nucleotide polymorphisms with potential function within expression quantitative trait loci and investigate overall enrichment of variation within tissue-specific functional regulatory domains of the genome., Results: The strongest finding ( p  = 2.01 × 10 -6 , odds ratio = 1.82, 95% confidence interval = [1.42, 2.33]) in genome-wide association study was with rs10252923 at 7q21.13, downstream of FZD1 (frizzled class receptor 1). While this did not stand alone after correction, the involvement of FZD1 was supported by gene-based analysis, which exceeded the threshold for genome-wide significance ( p  = 2.78 × 10 -6 )., Conclusion: The identification of FZD1 , as an independent association signal at the gene level, supports the hypothesis that the Wnt signalling pathway is altered in the pathogenesis of schizophrenia and may be an important target for therapeutic development.

Published
2020
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48. The effect of NMDA-R antagonist, MK-801, on neuronal mismatch along the rat auditory thalamocortical pathway.

Author

Parras GG, Valdés-Baizabal C, Harms L, Michie PT, and Malmierca MS

Subjects
Animals, Auditory Cortex drug effects, Dose-Response Relationship, Drug, Evoked Potentials drug effects, Female, Rats, Auditory Cortex cytology, Dizocilpine Maleate pharmacology, Neurons cytology, Neurons drug effects, Receptors, N-Methyl-D-Aspartate antagonists & inhibitors, Thalamus cytology
Abstract

Efficient sensory processing requires that the brain maximize its response to unexpected stimuli, while suppressing responsivity to expected events. Mismatch negativity (MMN) is an auditory event-related potential that occurs when a regular pattern is interrupted by an event that violates the expected properties of the pattern. According to the predictive coding framework there are two mechanisms underlying the MMN: repetition suppression and prediction error. MMN has been found to be reduced in individuals with schizophrenia, an effect believed to be underpinned by glutamate N-methyl-D-aspartate receptor (NMDA-R) dysfunction. In the current study, we aimed to test how the NMDA-R antagonist, MK-801 in the anaesthetized rat, affected repetition suppression and prediction error processes along the auditory thalamocortical pathway. We found that low-dose systemic administration of MK-801 differentially affect thalamocortical responses, namely, increasing thalamic repetition suppression and cortical prediction error. Results demonstrate an enhancement of neuronal mismatch, also confirmed by large scale-responses. Furthermore, MK-801 produces faster and stronger dynamics of adaptation along the thalamocortical hierarchy. Clearly more research is required to understand how NMDA-R antagonism and dosage affects processes contributing to MMN. Nonetheless, because a low dose of an NMDA-R antagonist increased neuronal mismatch, the outcome has implications for schizophrenia treatment.

Published
2020
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49. Greater activation of the response inhibition network in females compared to males during stop signal task performance.

Author

Gaillard A, Rossell SL, Carruthers SP, Sumner PJ, Michie PT, Woods W, Neill E, Phillipou A, Toh WL, and Hughes ME

Subjects
Adult, Amygdala physiology, Brain physiology, Brain Mapping methods, Cerebral Cortex physiology, Female, Humans, Inhibition, Psychological, Magnetic Resonance Imaging methods, Male, Neuropsychological Tests, Sex Factors, Executive Function physiology, Psychomotor Performance physiology
Abstract

Previous neuroimaging studies have reported differences in regional brain activation between males and females during stop signal task performance, suggesting the presence of sex-linked differences in brain network organization of inhibitory ability. Despite a growing literature on sex differences during stop signal task performance, a consensus still has not been reached due to variations in task design and analysis methods. Due to these disparate findings we used up to date stop signal task methods to compare behavioral performance and associated brain activation between males and females using an event-related functional magnetic resonance imaging design. We observed that males were faster in inhibiting their responses, but females exhibited marked increased in stopping network activation, in addition to increased activation of the anterior insula and left amygdala. These findings suggest that males and females process stop signals differently., Competing Interests: Declaration of Competing Interest The authors declare that there are no conflicts of interest., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Published
2020
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50. Task-switching costs have distinct phase-locked and nonphase-locked EEG power effects.

Author

McKewen M, Cooper PS, Wong ASW, Michie PT, Sauseng P, and Karayanidis F

Subjects
Adolescent, Adult, Cues, Female, Humans, Male, Young Adult, Brain Waves physiology, Evoked Potentials physiology, Executive Function physiology, Psychomotor Performance physiology, Reaction Time physiology
Abstract

Event-related potentials (ERPs) and total time-frequency power analyses have shown that performance costs during task switching are related to differential preparation to switch tasks (switch cost) and repeat the same task (mixing cost) during both proactive control (cue-to-target interval; CTI) and reactive control (post-target). The time-frequency EEG signal is comprised of both phase-locked activity (associated with stimulus-specific processes) and nonphase-locked activity (represents processes thought to persist over longer timeframes and do not contribute to the average ERP). In the present study, we used a cued task-switching paradigm to examine whether phase-locked and nonphase-locked power are differentially modulated by switch and mixing effects in intervals associated with the need for proactive control (CTI) and reactive control (post-target interval). Phase-locked activity was observed in the theta and alpha bands, closely resembled that seen for total power, and was consistent with switch and mixing ERP positivities. Nonphase-locked analyses showed theta and alpha power effects for both switch and mixing effects early in the CTI and as well as more sustained alpha and beta activity around cue onset, and extending from mid-CTI into the post-target interval. Nonphase-locked activity in pretarget alpha and posttarget theta power were both correlated with response time mixing cost. These findings provide novel insight into phase-locked and nonphase-locked activity associated with switch and mixing costs that are not evident with ERP or total time-frequency analyses., (© 2020 Society for Psychophysiological Research.)

Published
2020
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