Abstract
Schizophrenia (SCZ) is a severe, highly heterogeneous psychiatric disorder with varied clinical presentations. The polygenic genetic architecture of SCZ makes identification of causal variants a daunting task. Gene expression analyses hold the promise of revealing connections between dysregulated transcription and underlying variants in SCZ. However, the most commonly used differential expression analysis often assumes grouped samples are from homogeneous populations and thus cannot be used to detect expression variance differences between samples. Here, we applied the test for equality of variances to normalized expression data, generated by the CommonMind Consortium (CMC), from brains of 212 SCZ and 214 unaffected control (CTL) samples. We identified 87 genes, including VEGFA (vascular endothelial growth factor) and BDNF (brain-derived neurotrophic factor), that showed a significantly higher expression variance among SCZ samples than CTL samples. In contrast, only one gene showed the opposite pattern. To extend our analysis to gene sets, we proposed a Mahalanobis distance-based test for multivariate homogeneity of group dispersions, with which we identified 110 gene sets with a significantly higher expression variability in SCZ, including sets of genes encoding phosphatidylinositol 3-kinase (PI3K) complex and several others involved in cerebellar cortex morphogenesis, neuromuscular junction development, and cerebellar Purkinje cell layer development. Taken together, our results suggest that SCZ brains are characterized by overdispersed gene expression—overall gene expression variability among SCZ samples is significantly higher than that among CTL samples. Our study showcases the application of variability-centric analyses in SCZ research.
Highlights
Schizophrenia (SCZ)—one of the most severe psychiatric disorders —affects about 1% of the general population[1,2,3]
Through the increased gene expression variability in SCZ is unlikely to be due application of this method, we show that multiple gene sets, to the existence of a small number of SCZ samples with extremely whose enriched functions are SCZ related, have higher expression high or low expression levels
We tested all common single nucleotide polymorphisms (SNPs) segregating in SCZ and CTL, i.e., minor allele frequency (MAF) > 0.15 in both populations, to identify those with genotypes associated with gene expression variance in SCZ (p < 1e−7, B–F test) but not in CTL (p > 0.05, B–F test, Fig. 3a)
Summary
Schizophrenia (SCZ)—one of the most severe psychiatric disorders —affects about 1% of the general population[1,2,3]. Patients diagnosed with SCZ can be classified into those with and without neurodevelopmental impairment[10,11,12] The former category is likely to be due to the impact of risk alleles, copy number variants (CNVs), or early environmental insults such as hypoxic damage to the hippocampus. We represent the the impact of these two outliers on the significance of the results of our differential variability (DV) analysis on single genes, statistical test for the DV gene detection The removal of these two showing an overwhelming pattern of increased variability at the extreme samples had no qualitative influence on the outcome of single-gene level associated with SCZ. We conclude we estimated the contributions of antipsychotics and antidepresby providing the interpretation of our results in the context of sants to gene expression variability in SCZ samples. For each of these DV genes, we compared its expression variance in SCZ patients received antipsychotics treatment with
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