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.

Previous studies on schizophrenia have detected elevated cytokines in both brain and blood, suggesting neuroinflammation may contribute to the pathophysiology in some cases. We aimed to determine the extent to which elevated peripheral cytokine messenger RNA (mRNA) expression: (1) characterizes a subgroup of people with schizophrenia and (2) shows a relationship to cognition, brain volume and/or symptoms. Forty-three outpatients with schizophrenia or schizoaffective disorder and matched healthy controls were assessed for peripheral cytokine mRNAs (interleukin (IL)-1β, IL-2, IL-6, IL-8 and IL-18), intelligence quotient, memory and verbal fluency, symptom severity and cortical brain volumes integral to language (that is, Broca's and Wernicke's areas). IL-1β mRNA levels were 28% increased in schizophrenia compared with controls (t(82)=2.64, P<0.01). Using a two-step clustering procedure, we identified a subgroup of people displaying relatively elevated cytokine mRNA levels (17/43 people with schizophrenia and 9/42 controls). Individuals with schizophrenia in the elevated cytokine subgroup performed significantly worse than the low-cytokine subgroup on verbal fluency (F(1,40)=15.7, P<0.001). There was a 17% volume reduction of the left pars opercularis (POp) (Broca's area) in patients with elevated cytokines compared with patients with lower cytokines (F(1,29)=9.41, P=0.005). Negative linear relationships between IL-1β mRNA levels and both verbal fluency and left POp volume were found in schizophrenia. This study is among the first to link blood biomarkers of inflammation with both cognitive deficits and brain volume reductions in people with schizophrenia, supporting that those with elevated cytokines represent a neurobiologically meaningful subgroup. These findings raise the possibility that targeted anti-inflammatory treatments may ameliorate cognitive and brain morphological abnormalities in some people with schizophrenia.

A common limitation of neuroimaging studies is their small sample sizes. To overcome this hurdle, the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium combines neuroimaging data from many institutions worldwide. However, this introduces heterogeneity due to different scanning devices and sequences. ENIGMA projects commonly address this heterogeneity with random-effects meta-analysis or mixed-effects mega-analysis. Here we tested whether the batch adjustment method, ComBat, can further reduce site-related heterogeneity and thus increase statistical power. We conducted random-effects meta-analyses, mixed-effects mega-analyses and ComBat mega-analyses to compare cortical thickness, surface area and subcortical volumes between 2897 individuals with a diagnosis of schizophrenia and 3141 healthy controls from 33 sites. Specifically, we compared the imaging data between individuals with schizophrenia and healthy controls, covarying for age and sex. The use of ComBat substantially increased the statistical significance of the findings as compared to random-effects meta-analyses. The findings were more similar when comparing ComBat with mixed-effects mega-analysis, although ComBat still slightly increased the statistical significance. ComBat also showed increased statistical power when we repeated the analyses with fewer sites. Results were nearly identical when we applied the ComBat harmonization separately for cortical thickness, cortical surface area and subcortical volumes. Therefore, we recommend applying the ComBat function to attenuate potential effects of site in ENIGMA projects and other multi-site structural imaging work. We provide easy-to-use functions in R that work even if imaging data are partially missing in some brain regions, and they can be trained with one data set and then applied to another (a requirement for some analyses such as machine learning).