MicroRNAs in copy number variants in schizophrenia: misregulation of genome-wide gene expression programs

Differentiation value of miR-26b for major depressive disorder, schizophrenia, generalized anxiety disorder

Introduction

First episode and drug naive schizophrenia (SZ) patients comorbid with major depressive episode and generalized anxiety disorder (GAD) comorbid with major depressive disorder (MDD) are common in clinical practice, overlapping symptomatology during first presentation of MDD, SZ and GAD challenged the diagnostic process.

Materials and Methods

This study aimed to investigate the differentiation value of peripheral microRNA-26b expression in 52 patients of MDD, SZ, and GAD, respectively, and 52 controls. Quantitative real-time reverse transcription polymerase chain reaction was used to further verify aberrant miRNAs of previous identified in MDD and investigate expression level of these peripheral miRNAs in SZ and GAD.

Results

The expression levels of miR-26b and miR-4743 were significantly upregulated and of miR-4498, miR-4485, and miR-1972 had no significant difference. There were no significant differences of expression levels of miR-26b, miR-4498, miR-4485, and miR-1972 except miR-4743 between SZ patients and control group and of miR-26b, miR-1972, miR-4498, and miR-4485 between GAD group and the controls. The receiver operating characteristic (ROC) curve of miR-26b in MDD patients showed that its sensitivity and specificity for diagnosis were 0.540 and 0.830, respectively, with the area under curve (AUC) being 0.728; the ROC of miR-26b for SZ and MDD differentiation showed that its sensitivity and specificity were 0.580 and 0.710, respectively, with AUC being 0.631; the ROC of miR-26b for GAD and MDD differentiation suggested that sensitivity and specificity were 0.560 and 0.750, respectively, with AUC being 0.637.

Conclusion

MiR-26b might have potential value of differentiation biomarker for MDD, SZ, and GAD.

Classification of miRNA-related sequence variations

miRNA regulome is whole set of regulatory elements that regulate miRNA expression or are under control of miRNAs. Its understanding is vital for comprehension of miRNA functions. Classification of miRNA-related genetic variability is challenging because miRNA interact with different genomic elements and are studied at different omics levels. In the present study, miRNA-associated genetic variability is presented at three levels: miRNA genes and their upstream regulation, miRNA silencing machinery and miRNA targets. Several types of miRNA-associated genetic variations are known, including short and structural polymorphisms and epimutations. Differential expression can also affect miRNA regulome function. Classification of miRNA-associated genetic variability presents a baseline for complementing sequence variant nomenclature, planning of experiments, protocols for multi-omics data integration and development of biomarkers.

Whole-Genome Sequencing Suggests Schizophrenia Risk Mechanisms in Humans with 22q11.2 Deletion Syndrome

Chromosome 22q11.2 microdeletions impart a high but incomplete risk for schizophrenia. Possible mechanisms include genome-wide effects of DGCR8 haploinsufficiency. In a proof-of-principle study to assess the power of this model, we used high-quality, whole-genome sequencing of nine individuals with 22q11.2 deletions and extreme phenotypes (schizophrenia, or no psychotic disorder at age >50 years). The schizophrenia group had a greater burden of rare, damaging variants impacting protein-coding neurofunctional genes, including genes involved in neuron projection (nominal P = 0.02, joint burden of three variant types). Variants in the intact 22q11.2 region were not major contributors. Restricting to genes affected by a DGCR8 mechanism tended to amplify between-group differences. Damaging variants in highly conserved long intergenic noncoding RNA genes also were enriched in the schizophrenia group (nominal P = 0.04). The findings support the 22q11.2 deletion model as a threshold-lowering first hit for schizophrenia risk. If applied to a larger and thus better-powered cohort, this appears to be a promising approach to identify genome-wide rare variants in coding and noncoding sequence that perturb gene networks relevant to idiopathic schizophrenia. Similarly designed studies exploiting genetic models may prove useful to help delineate the genetic architecture of other complex phenotypes.