Relationship between phosphoinositide-3-kinase genetic polymorphism and schizophrenia

Lipid-correlated alterations in the transcriptome are enriched in several specific pathways in the postmortem prefrontal cortex of Japanese patients with schizophrenia

AIMS

Schizophrenia is a chronic relapsing psychiatric disorder that is characterized by many symptoms and has a high heritability. There were studies showing that the phospholipid abnormalities in subjects with schizophrenia (Front Biosci, S3, 2011, 153; Schizophr Bull, 48, 2022, 1125; Sci Rep, 7, 2017, 6; Anal Bioanal Chem, 400, 2011, 1933). Disturbances in prefrontal cortex phospholipid and fatty acid composition have been reported in subjects with schizophrenia (Sci Rep, 7, 2017, 6; Anal Bioanal Chem, 400, 2011, 1933; Schizophr Res, 215, 2020, 493; J Psychiatr Res, 47, 2013, 636; Int J Mol Sci, 22, 2021). For exploring the signaling pathways contributing to the lipid changes in previous study (Sci Rep, 7, 2017, 6), we performed two types of transcriptome analyses in subjects with schizophrenia: an unbiased transcriptome analysis solely based on RNA-seq data and a correlation analysis between levels of gene expression and lipids.

METHODS

RNA-Seq analysis was performed in the postmortem prefrontal cortex from 10 subjects with schizophrenia and 5 controls. Correlation analysis between the transcriptome and lipidome from 9 subjects, which are the same samples in the previous lipidomics study (Sci Rep, 7, 2017, 6).

RESULTS

Extraction of differentially expressed genes (DEGs) and further sequence and functional group analysis revealed changes in gene expression levels in phosphoinositide 3-kinase (PI3K)-Akt signaling and the complement system. In addition, a correlation analysis clarified alterations in ether lipid metabolism pathway, which is not found as DEGs in transcriptome analysis alone.

CONCLUSIONS

This study provided results of the integrated analysis of the schizophrenia-associated transcriptome and lipidome within the PFC and revealed that lipid-correlated alterations in the transcriptome are enriched in specific pathways including ether lipid metabolism pathway.

Construction of a Diagnostic Model and a lncRNA-Associated ceRNA Network Based on Apoptosis-Related Genes for Schizophrenia

Methods

Gene expression profiles and apoptosis-related data were downloaded from the Gene Expression Omnibus and Molecular Signature databases, respectively. Apoptosis-related differentially expressed mRNAs (DEGs) and miRNAs (DEMs) from blood samples between the schizophrenia and healthy control individuals were screened. A diagnostic model was developed using the data from univariate and least absolute shrinkage and selection operator (LASSO) regression analyses, followed by validation using the GSE38485 dataset. Cases were divided into low-risk (LR) and high-risk (HR) groups based on the risk score of the model, and differences in immune gene sets and pathways between these two groups were compared. Finally, a ceRNA network was constructed by integrating long non-coding RNAs (lncRNAs), DEMs, and DEGs.

Results

A diagnostic model containing 15 apoptosis-related genes was developed and its diagnostic efficiency was found to be robust. The HR group was correlated with higher immune scores of chemokines, cytokines, and interleukins; it was also significantly involved in pathways such as pancreatic beta cells and early estrogen response. A ceRNA network composed of 2 lncRNAs, 14 miRNAs, and 5 mRNAs was established.

Conclusions

The established model is a potential tool to improve the diagnostic efficiency of patients with schizophrenia, and the nodes included in the ceRNA network might serve as biomarkers and therapeutic targets for schizophrenia.

Comparison of Oncogenes, Tumor Suppressors, and MicroRNAs Between Schizophrenia and Glioma: The Balance of Power

The risk of cancer in schizophrenia has been controversial. Confounders of the issue are cigarette smoking in schizophrenia, and antiproliferative effects of antipsychotic medications. The author has previously suggested comparison of a specific cancer like glioma to schizophrenia might help determine a more accurate relationship between cancer and schizophrenia. To accomplish this goal, the author performed three comparisons of data; the first a comparison of conventional tumor suppressors and oncogenes between schizophrenia and cancer including glioma. This comparison determined schizophrenia has both tumor-suppressive and tumor-promoting characteristics. A second, larger comparison between brain-expressed microRNAs in schizophrenia with their expression in glioma was then performed. This identified a core carcinogenic group of miRNAs in schizophrenia offset by a larger group of tumor-suppressive miRNAs. This proposed "balance of power" between oncogenes and tumor suppressors could cause neuroinflammation. This was assessed by a third comparison between schizophrenia, glioma and inflammation in asbestos-related lung cancer and mesothelioma (ALRCM). This revealed that schizophrenia shares more oncogenic similarity to ALRCM than glioma.

Long-term effects of stress early in life on microRNA-30a and its network: Preventive effects of lurasidone and potential implications for depression vulnerability

Exposure to early life stress can interfere with neurodevelopmental trajectories to increase the vulnerability for psychiatric disorders later in life. With this respect, epigenetic mechanisms play a key role for the long-lasting changes in brain functions that may elicit and sustain psychopathologic outcomes.

Here, we investigated DNA methylation changes as possible epigenetic mechanism mediating the effect of prenatal stress (PNS), an experimental paradigm associated with behavioral and molecular alterations relevant for psychiatric disorders. We identified 138 genes as being differentially methylated in the prefrontal cortex (PFC) and in the hippocampus (HIP) of male and female adult rats exposed to PNS. Among these genes, miR-30a and Neurod1 emerged as potential players for the negative outcomes associated with PNS exposure. Indeed, in addition to showing consistent methylation differences in both brain regions and in both sexes, and interacting with each other, they are both involved in Axon guidance and Neurotrophin signaling, which are important to neurodevelopmental disorders. We also found a significant reduction in the expression of a panel of genes (CAMK2A, c-JUN, LIMK1, MAP2K1, MAP2K2, PIK3CA and PLCG1) that belong to these two biological pathways and are also validated targets of miR-30a, pointing to a down-regulation of these pathways as a consequence of PNS exposure. Interestingly, we also found that miR-30a levels were significantly upregulated in depressed patients exposed to childhood trauma, as compared to control individuals. Importantly, we also found that a sub-chronic treatment with the atypical antipsychotic drug, lurasidone, during adolescence was able to prevent the up-regulation of miR-30a and normalized the expression of its target genes in response to PNS exposure.

Our results demonstrate that miR-30a undergoes epigenetic changes following early life stress exposure and suggest that this miRNA could play a key role in producing broad and long-lasting alterations in neuroplasticity-related pathways, contributing to the etiology of psychiatric disorders.

•

MiR-30a and Neurod1 undergo epigenetic changes following PNS exposure.

•

MiR-30 and Neurod1 are involved in Axon guidance and Neurotrophin signaling, two important pathways for neurodevelopment.

•

We found lower expression levels of a panel of genes targeted by miR-30a.

•

MiR-30a was significantly up-regulated in depressed patients exposed to childhood trauma.

•

A chronic treatment with lurasidone during adolescence prevented the up-regulation of miR-30a following PNS exposure.

Overdispersed gene expression in schizophrenia

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.

Horizontal and vertical integrative analysis methods for mental disorders omics data

In recent biomedical studies, omics profiling has been extensively conducted on various types of mental disorders. In most of the existing analyses, a single type of mental disorder and a single type of omics measurement are analyzed. In the study of other complex diseases, integrative analysis, both vertical and horizontal integration, has been conducted and shown to bring significantly new insights into disease etiology, progression, biomarkers, and treatment. In this article, we showcase the applicability of integrative analysis to mental disorders. In particular, the horizontal integration of bipolar disorder and schizophrenia and the vertical integration of gene expression and copy number variation data are conducted. The analysis is based on the sparse principal component analysis, penalization, and other advanced statistical techniques. In data analysis, integration leads to biologically sensible findings, including the disease-related gene expressions, copy number variations, and their associations, which differ from the “benchmark” analysis. Overall, this study suggests the potential of integrative analysis in mental disorder research.

Characterization of biological pathways associated with semen traits in the Thai multibreed dairy population

The objective of this research was to characterize biological pathways associated with semen volume (VOL), number of sperm (NS), and sperm motility (MOT) of dairy bulls in the Thai multibreed dairy population. Phenotypes for VOL (n = 13,535), NS (n = 12,773), and MOT (n = 12,660) came from 131 bulls of the Dairy Farming Promotion Organization of Thailand. Genotypic data consisted of 76,519 imputed and actual single nucleotide polymorphisms (SNP) from 72 animals. The SNP variances for VOL, NS, and MOT were estimated using a three-trait genomic-polygenic repeatability model. Fixed effects were contemporary group, ejaculate order, age of bull, ambient temperature, and heterosis. Random effects were animal additive genetic, permanent environmental, and residual. Individual SNP explaining at least 0.001% of the total genetic variance for each trait were selected to identify associated genes in the NCBI database (UMD Bos taurus 3.1 assembly) using the R package Map2NCBI. A set of 1,999 NCBI genes associated with all three semen traits was utilized for the pathway analysis conducted with the ClueGO plugin of Cytoscape using information from the Kyoto Encyclopedia of Genes and Genomes database. The pathway analysis revealed seven significant biological pathways involving 127 genes that explained 1.04% of the genetic variance for VOL, NS, and MOT. These genes were known to affect cell structure, motility, migration, proliferation, differentiation, survival, apoptosis, signal transduction, oxytocin release, calcium channel, neural development, and immune system functions related to sperm morphology and physiology during spermatogenesis.