Associated transcriptional, brain and clinical variations in schizophrenia

Understanding the relationship between genetic variations and brain abnormalities is crucial for uncovering the cross-scale pathophysiological mechanisms underlying schizophrenia. This cross-sectional study identifies brain structural correlates of individual variation in gene expression in schizophrenia and its clinical implication. RNA-sequencing data from blood samples, magnetic resonance imaging scans and clinical assessments were collected from 43 patients with schizophrenia, together with data from 60 healthy controls. Using RNA-sequencing data we show alterations in both gene-level and isoform-level expression between patients with schizophrenia and healthy controls (1,836 genes and 1,104 isoforms, false-discover-rate-adjusted P < 0.05). We also show differential gene expression to be associated with schizophrenia-related genomic variations (based on genome-wide association study data on 76,755 patients and 243,649 controls; regression coefficient (β) = 0.211, P = 0.001) and differential brain gene expression (P < 0.001, hypergeometric test). Multivariate correlation analysis combining gene expression and brain imaging shows that transcriptional levels of differentially expressed genes significantly correlate with gray matter volume in the frontal and temporal regions of cognitive brain networks in patients with schizophrenia (P < 0.001, permutation test). Findings show a significant association between gene expression, gray matter volume and cognitive performance in patients (P = 0.031, permutation test). Our results suggest that genomic variants in individuals with schizophrenia are associated with alterations in the transcriptome, which plays a role in individual variations in macroscale brain structure and cognition, contributing to building a comprehensive, multi-omics marker for the assessment of schizophrenia. This study examining blood transcriptomic, neuroimaging and clinical data in people with schizophrenia shows a relationship between individual variations in gene transcription, brain structure and cognitive performance.