- van Erp, TGM;
- Hibar, DP;
- Rasmussen, JM;
- Glahn, DC;
- Pearlson, GD;
- Andreassen, OA;
- Agartz, I;
- Westlye, LT;
- Haukvik, UK;
- Dale, AM;
- Melle, I;
- Hartberg, CB;
- Gruber, O;
- Kraemer, B;
- Zilles, D;
- Donohoe, G;
- Kelly, S;
- McDonald, C;
- Morris, DW;
- Cannon, DM;
- Corvin, A;
- Machielsen, MWJ;
- Koenders, L;
- de Haan, L;
- Veltman, DJ;
- Satterthwaite, TD;
- Wolf, DH;
- Gur, RC;
- Gur, RE;
- Potkin, SG;
- Mathalon, DH;
- Mueller, BA;
- Preda, A;
- Macciardi, F;
- Ehrlich, S;
- Walton, E;
- Hass, J;
- Calhoun, VD;
- Bockholt, HJ;
- Sponheim, SR;
- Shoemaker, JM;
- van Haren, NEM;
- Pol, HEH;
- Ophoff, RA;
- Kahn, RS;
- Roiz-Santiañez, R;
- Crespo-Facorro, B;
- Wang, L;
- Alpert, KI;
- Jönsson, EG;
- Dimitrova, R;
- Bois, C;
- Whalley, HC;
- McIntosh, AM;
- Lawrie, SM;
- Hashimoto, R;
- Thompson, PM;
- Turner, JA
The profile of brain structural abnormalities in schizophrenia is still not fully understood, despite decades of research using brain scans. To validate a prospective meta-analysis approach to analyzing multicenter neuroimaging data, we analyzed brain MRI scans from 2028 schizophrenia patients and 2540 healthy controls, assessed with standardized methods at 15 centers worldwide. We identified subcortical brain volumes that differentiated patients from controls, and ranked them according to their effect sizes. Compared with healthy controls, patients with schizophrenia had smaller hippocampus (Cohen's d=-0.46), amygdala (d=-0.31), thalamus (d=-0.31), accumbens (d=-0.25) and intracranial volumes (d=-0.12), as well as larger pallidum (d=0.21) and lateral ventricle volumes (d=0.37). Putamen and pallidum volume augmentations were positively associated with duration of illness and hippocampal deficits scaled with the proportion of unmedicated patients. Worldwide cooperative analyses of brain imaging data support a profile of subcortical abnormalities in schizophrenia, which is consistent with that based on traditional meta-analytic approaches. This first ENIGMA Schizophrenia Working Group study validates that collaborative data analyses can readily be used across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.