Study findings suggest that (1) processing speed contributes to the association between white matter microstructure and working memory in schizophrenia and (2) white matter impairment in schizophrenia is regional tract-specific, particularly in tracts normally supporting processing speed performance.

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

Although schizophrenia is a brain disorder, increasing evidence suggests that there may be body-wide involvement in this illness. However, direct evidence of brain structures involved in the presumed peripheral-central interaction in schizophrenia is still unclear. Seventy-nine previously treatment-naïve first-episode schizophrenia patients who were within 2-week antipsychotics initial stabilization, and 41 age- and sex-matched healthy controls were enrolled in the study. Group differences in subcortical brain regional structures measured by MRI and the subclinical cardiovascular, metabolic, immune, and neuroendocrine biomarkers as indexed by allostatic load, and their associations were explored. Compared with controls, patients with schizophrenia had significantly higher allostatic load (P = .001). Lateral ventricle (P < .001), choroid plexus (P < .001), and thalamus volumes (P < .001) were significantly larger, whereas amygdala volume (P = .001) was significantly smaller in patients. The choroid plexus alone was significantly correlated with higher allostatic load after age, sex, education level, and the total intracranial volume were taken into account (t = 3.60, P < .001). Allostatic load was also significantly correlated with PANSS positive (r = 0.28, P = .016) and negative (r = −0.31, P = .008) symptoms, but in opposite directions. The peripheral multisystemic and central nervous system abnormalities in schizophrenia may interact through the choroid plexus during the early stage of the illness. The choroid plexus might provide a sensitive structural biomarker to study the treatment and prevention of brain-periphery interaction abnormalities in schizophrenia.

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Patients with schizophrenia have patterns of brain deficits including reduced cortical thickness, subcortical gray matter volumes, and cerebral white matter integrity. We proposed the regional vulnerability index (RVI) to translate the results of Enhancing Neuro Imaging Genetics Meta-Analysis studies to the individual level. We calculated RVIs for cortical, subcortical, and white matter measurements and a multimodality RVI.We evaluated RVI as a measure sensitive to schizophrenia-specific neuroanatomical deficits and symptoms and studied the timeline of deficit formations in: early (≤5 years since diagnosis, N = 45, age = 28.8 ± 8.5); intermediate (6-20 years, N = 30, age 43.3 ± 8.6); and chronic (21+ years, N = 44, age = 52.5 ± 5.2) patients and healthy controls (N = 76, age = 38.6 ± 12.4). All RVIs were significantly elevated in patients compared to controls, with the multimodal RVI showing the largest effect size, followed by cortical, white matter and subcortical RVIs (d = 1.57, 1.23, 1.09, and 0.61, all p < 10 −6 ).Multimodal RVI was significantly correlated with multiple cognitive variables including measures of visual learning, working memory and the total score of the MATRICS consensus cognitive battery, and with negative symptoms. The multimodality and white matter RVIs were significantly elevated in the intermediate and chronic versus early diagnosis group, consistent with ongoing progression. Cortical RVI was stable in the three disease-duration groups, suggesting neurodevelopmental origins of cortical deficits. In summary, neuroanatomical deficits in schizophrenia affect the entire brain; the heterochronicity of their appearance indicates both the neurodevelopmental and progressive nature of this illness. These deficit patterns may be useful for early diagnosis and as quantitative targets for more effective treatment strategies aiming to alter these neuroanatomical deficit patterns.