Esther Walton

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.

This review summarizes the last decade of work by the ENIGMA (Enhancing NeuroImaging Genetics through Meta Analysis) Consortium, a global alliance of over 1400 scientists across 43 countries, studying the human brain in health and disease. Building on large-scale genetic studies that discovered the first robustly replicated genetic loci associated with brain metrics, ENIGMA has diversified into over 50 working groups (WGs), pooling worldwide data and expertise to answer fundamental questions in neuroscience, psychiatry, neurology, and genetics. Most ENIGMA WGs focus on specific psychiatric and neurological conditions, other WGs study normal variation due to sex and gender differences, or development and aging; still other WGs develop methodological pipelines and tools to facilitate harmonized analyses of "big data" (i.e., genetic and epigenetic data, multimodal MRI, and electroencephalography data). These international efforts have yielded the largest neuroimaging studies to date in schizophrenia, bipolar disorder, major depressive disorder, post-traumatic stress disorder, substance use disorders, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorders, epilepsy, and 22q11.2 deletion syndrome. More recent ENIGMA WGs have formed to study anxiety disorders, suicidal thoughts and behavior, sleep and insomnia, eating disorders, irritability, brain injury, antisocial personality and conduct disorder, and dissociative identity disorder. Here, we summarize the first decade of ENIGMA's activities and ongoing projects, and describe the successes and challenges encountered along the way. We highlight the advantages of collaborative large-scale coordinated data analyses for testing reproducibility and robustness of findings, offering the opportunity to identify brain systems involved in clinical syndromes across diverse samples and associated genetic, environmental, demographic, cognitive, and psychosocial factors.

Given the difficulty of procuring human brain tissue, a key question in molecular psychiatry concerns the extent to which epigenetic signatures measured in more accessible tissues such as blood can serve as a surrogate marker for the brain. Here, we aimed (1) to investigate the blood-brain correspondence of DNA methylation using a within-subject design and (2) to identify changes in DNA methylation of brain-related biological pathways in schizophrenia.We obtained paired blood and temporal lobe biopsy samples simultaneously from 12 epilepsy patients during neurosurgical treatment. Using the Infinium 450K methylation array we calculated similarity of blood and brain DNA methylation for each individual separately. We applied our findings by performing gene set enrichment analyses (GSEA) of peripheral blood DNA methylation data (Infinium 27K) of 111 schizophrenia patients and 122 healthy controls and included only Cytosine-phosphate-Guanine (CpG) sites that were significantly correlated across tissues.Only 7.9% of CpG sites showed a statistically significant, large correlation between blood and brain tissue, a proportion that although small was significantly greater than predicted by chance. GSEA analysis of schizophrenia data revealed altered methylation profiles in pathways related to precursor metabolites and signaling peptides.Our findings indicate that most DNA methylation markers in peripheral blood do not reliably predict brain DNA methylation status. However, a subset of peripheral data may proxy methylation status of brain tissue. Restricting the analysis to these markers can identify meaningful epigenetic differences in schizophrenia and potentially other brain disorders.