<p>Schizophrenia is a common and severe psychotic disorder. While some common SNPs and rare copy number variants have been identified as being significantly associated with disease risk, the biological mechanisms remain undefined. To identify gene expression abnormalities in schizophrenia, we generated whole-genome gene expression profiles using RNAseq on lymphoblastoid cell lines from schizophrenia cases and controls of European ancestry. Subsets of these data have been used in three studies: (1) gene expression outliers (extreme tails of the distribution of transcript expression values) in 634 cases and 713 controls (<a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=26022996">PMID: 26022996</a>); (2) baseline differential gene expression by affection status in 529 cases and 660 controls (<a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=28418402">PMID: 28418402</a>); and (3) baseline versus dopamine stimulated differential gene expression by affection status in 514 cases and 690 controls (<a href="https://www.ncbi.nlm.nih.gov/pubmed/?term=30115913">PMID: 30115913</a>). Various classes of classes were enriched in the differentially expressed genes, especially brain expressed genes and genes related to immune processes.</p>

RNAseq Transcriptomic Analyses of European Ancestry Samples in MGS Dataset

Transcriptome sequencing study implicates immune-related genes differentially expressed in schizophrenia: new data and a meta-analysis

Transcriptomic signatures of schizophrenia revealed by dopamine perturbation in an ex vivo model

Transcriptome outlier analysis implicates schizophrenia susceptibility genes and enriches putatively functional rare genetic variants.