Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia

Abstract

The application of microarray technology in schizophrenia research was heralded as paradigm-shifting, as it allowed for high-throughput assessment of cell and tissue function. This technology was widely adopted, initially in studies of postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.

PTSD Blood Transcriptome Mega-Analysis: Shared Inflammatory Pathways across Biological Sex and Modes of Trauma

“…To do so, we performed a megaanalysis of five independent transcriptome-wide peripheral blood studies covering seven types of trauma in 229 PTSD and 311 comparison individuals. To address our goals, a standardized multistep analytic approach was used that we have reviewed in the context of blood-based biomarker discovery in neuropsychiatric disorders (Breen et al, 2016), and that we have also applied to other transcriptome-wide mega-analyses (Hess et al, 2016;Tylee et al, 2016). To this end, our analyses specifically sought to: (1) determine the relatedness of PTSD gene expression signatures across different types of trauma; (2) identify candidate genes, pathways and co-regulatory networks in PTSD and determine if such alterations are distinct between different biological sex and trauma types; and (3) construct diagnostic blood-based gene expression classifiers to differentiate PTSD cases from trauma-exposed control individuals and clarify the potential clinical utility of peripheral blood gene expression.…”

Genetic correlations among psychiatric and immune-related phenotypes based on genome-wide association data

“…Evidence from both clinical and biomedical literature has demonstrated that individuals with these conditions show differences in circulating immunologic markers, functional capacities of isolated immune cells, and atypical prevalence of clinical immune-related phenotypes compared to individuals not affected by psychiatric or neurodevelopmental disorders. [1][2][3][4][5][6][7][8][9][10] It remains unclear what roles (if any) altered immunologic functions may play in the major psychiatric phenotypes, though plausible mechanisms linking altered immune functions with neurobiological changes during early brain development and in fully developed adults have been identified. [11][12][13][14][15][16][17][18] While some studies have already suggested potential genetic bases for the immune dysregulation observed in a subset of psychiatric patients, [19][20][21][22] the extent to which co-occurrence or segregation of clinical phenotypes may be influenced by similarities in genome-wide genetic risk signals warrants further examination.…”

Exon Array Biomarkers for the Differential Diagnosis of Schizophrenia and Bipolar Disorder

“…A recent mega-analysis of differentially expressed genes in SZ across 9 studies was conducted in blood-based transcriptomics [35]. There were 1,624 genes that survived the FDR that were compared to the top 122 genes identified by ANOVA in the present study.…”

“…A recent mega-analysis of blood samples comparing SZ cases and controls was conducted on a total of 578 subjects in 9 studies. The mega-analysis of the blood transcriptome showed that 220 genes reached a Bonferroni-corrected level of significance [35], indicating the utility of analysis of the blood transcriptome for finding differentially expressed genes. The stability of this potential dysregulation has not been tested across different time points.…”