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 multi-center neuroimaging data, we analyzed brain MRI scans from 2,028 schizophrenia patients and 2,540 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 to 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) and 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 that 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 employed across brain phenotypes and disorders and encourages analysis and data sharing efforts to further our understanding of severe mental illness.

The Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Consortium is a collaborative network of researchers working together on a range of large-scale studies that integrate data from 70 institutions worldwide. Organized into Working Groups that tackle questions in neuroscience, genetics, and medicine, ENIGMA studies have analyzed neuroimaging data from over 12,826 subjects. In addition, data from 12,171 individuals were provided by the CHARGE consortium for replication of findings, in a total of 24,997 subjects. By meta-analyzing results from many sites, ENIGMA has detected factors that affect the brain that no individual site could detect on its own, and that require larger numbers of subjects than any individual neuroimaging study has currently collected. ENIGMA’s first project was a genome-wide association study identifying common variants in the genome associated with hippocampal volume or intracranial volume. Continuing work is exploring genetic associations with subcortical volumes (ENIGMA2) and white matter microstructure (ENIGMA-DTI). Working groups also focus on understanding how schizophrenia, bipolar illness, major depression and attention deficit/hyperactivity disorder (ADHD) affect the brain. We review the current progress of the ENIGMA Consortium, along with challenges and unexpected discoveries made on the way.

Following publication of the above article, the authors noticed that the forty-third author's last name was presented incorrectly. The author's name should have been listed as HE Hulshoff Pol. The publisher regrets the error.

BACKGROUND: Schizophrenia and bipolar disorder share genetic liability, and some structural brain abnormalities are common to both conditions. First-degree relatives of patients with schizophrenia (FDRs-SZ) show similar brain abnormalities to patients, albeit with smaller effect sizes. Imaging findings in first-degree relatives of patients with bipolar disorder (FDRs-BD) have been inconsistent in the past, but recent studies report regionally greater volumes compared with control subjects. METHODS: We performed a meta-analysis of global and subcortical brain measures of 6008 individuals (1228 FDRs-SZ, 852 FDRs-BD, 2246 control subjects, 1016 patients with schizophrenia, 666 patients with bipolar disorder) from 34 schizophrenia and/or bipolar disorder family cohorts with standardized methods. Analyses were repeated with a correction for intracranial volume (ICV) and for the presence of any psychopathology in the relatives and control subjects. RESULTS: FDRs-BD had significantly larger ICV (d = 10.16, q , .05 corrected), whereas FDRs-SZ showed smaller thalamic volumes than control subjects (d = 20.12, q , .05 corrected). ICV explained the enlargements in the brain measures in FDRs-BD. In FDRs-SZ, after correction for ICV, total brain, cortical gray matter, cerebral white matter, cerebellar gray and white matter, and thalamus volumes were significantly smaller; the cortex was thinner (d , 20.09, q , .05 corrected); and third ventricle was larger (d = 10.15, q , .05 corrected). The findings were not explained by psychopathology in the relatives or control subjects. CONCLUSIONS: Despite shared genetic liability, FDRs-SZ and FDRs-BD show a differential pattern of structural brain abnormalities, specifically a divergent effect in ICV. This may imply that the neurodevelopmental trajectories leading to brain anomalies in schizophrenia or bipolar disorder are distinct.

There are established differences in cortical thickness (CT) in schizophrenia (SCZ) and bipolar (BD) patients when compared to healthy controls (HC). However, it is unknown to what extent environmental or genetic risk factors impact on CT in these populations. We have investigated the effect of Environmental Risk Scores (ERS) and Polygenic Risk Scores for SCZ (PGRS-SCZ) on CT. Structural MRI scans were acquired at 3T for patients with SCZ or BD (n=57) and controls (n=41). Cortical reconstructions were generated in FreeSurfer (v5.3). The ERS was created by determining exposure to cannabis use, childhood adverse events, migration, urbanicity and obstetric complications. The PGRS-SCZ were generated, for a subset of the sample (Patients=43, HC=32), based on the latest PGC GWAS findings. ANCOVAs were used to test the hypotheses that ERS and PGRS-SCZ relate to CT globally, and in frontal and temporal lobes. An increase in ERS was negatively associated with CT within temporal lobe for patients. A higher PGRS-SCZ was also related to global cortical thinning for patients. ERS effects remained significant when including PGRS-SCZ as a fixed effect. No relationship which survived FDR correction was found for ERS and PGRS-SCZ in controls. Environmental risk for SCZ was related to localised cortical thinning in patients with SCZ and BD, while increased PGRS-SCZ was associated with global cortical thinning. Genetic and environmental risk factors for SCZ appear therefore to have differential effects. This provides a mechanistic means by which different risk factors may contribute to the development of SCZ and BD.