Expression of NF-κB associated lncRNAs in schizophrenia

Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

Expression of NF-κB-associated lncRNAs in different types of migraine

PURPOSE

NF-κB partakes in the pathophysiology of neurologic conditions. We quantified levels of NF-κB-associated genes in 119 patients with migraine versus healthy controls.

METHODS

We measured levels of NF-κB-associated genes in 42 patients with migraine compared with age- and sex-matched controls.

RESULTS

Comparison between patients without aura and controls revealed down-regulation of PACER [expression ratio (95% CI) 0.15 (0.06-0.36), P value < 0.0001]. Similar results were detected when comparing expression of PACER in patients with aura and controls [expression ratio (95% CI) 0.05 (0.02-0.12), P value < 0.0001]. Both DILC and CEBPA were over-expressed in patients with aura [expression ratio (95% CI) 4.9 (2.96-7.83), P value < 0.0001 and expression ratio (95% CI) 3.65 (2.39-5.24), P value < 0.0001, respectively] and in patients without aura compared with controls [expression ratio (95% CI) 3.6 (2.21-5.69), P value < 0.0001 and expression ratio (95% CI) 4.5 (2.53-7.11), P value < 0.0001, respectively]. ADINR was over-expressed in patients with aura [expression ratio (95% CI) 4.98 (3.09-8.33), P value < 0.0001] as well as patients without aura compared with controls [expression ratio (95% CI) 13.15 (7.41-23.58), P value < 0.0001]. Notably, ADINR levels were lower in patients with aura compared with patients without aura. When comparing ATG5 levels in patients with aura and controls, significant up-regulation was detected [expression ratio (95% CI) 4.4 (3.01-6.32), P value < 0.0001]. This pattern was also detected in patients without aura compared with controls [expression ratio (95% CI) 3.5 (2.28-5.35), P < 0.0001]. Finally, expression of DICER1-AS1 was elevated in patients with aura compared with patients without aura [expression ratio (95% CI) 2.47 (1.14-5.85), P = 0.03]. This lncRNA was under-expressed in patients without aura compared with controls [expression ratio (95% CI) 0.4 (0.21-1.31), P = 0.03]. CEBPA, ATG5 and ADINR had the best AUC values for distinguishing patients with aura from controls (AUC values = 0.91, 0.85 and 0.83, respectively). The AUC values for separation between patients without aura and controls were 0.90, 0.86 and 0.75 for CEBPA, ATG5 and ADINR, respectively.

CONCLUSION

Taken together, several genes in the NF-κB pathway has been revealed to be dysregulated in migraineurs and expression of these genes can be used as markers for this neurological condition.

Deregulation of NF-κB associated long non-coding RNAs in bipolar disorder

Long non-coding RNAs (lncRNAs) are major genetic factors whose disruption lead to many diseases, including nervous system diseases. Bipolar disorder (BD) is a neuro-psychiatric disease with no definitive diagnosis and incomplete treatment. Regarding the role of NF-κB-associated lncRNAs in the neuro-psychiatric disorders, we examined the expression of three lncRNAs, DICER1-AS1, DILC, and CHAST, in BD patients. To assess lncRNA expression in peripheral blood mononuclear cells (PBMCs) of 50 BD patients and 50 healthy individuals, Real-time PCR was used. Additionally, some clinical characteristics of BD patients were investigated via an analysis of ROC curves and correlations. Based on our results, the expression level of CHAST increased significantly in BD patients in comparison with healthy people, in BD men compared with healthy men, as well as in BD women in comparison with control females (p < 0.05). A similar increase in expression was observed for DILC and DICER1-AS1 lncRNAs in female patients compared with healthy women. Whereas compared to healthy men, DILC was decreased in diseased men. Based on the results of the ROC curve, the area under the curve (AUC) for CHAST lncRNA was 0.83 with a P value of 0.0001. So, the expression level of CHAST lncRNA could play a role in the pathobiology of the BD and be considered a good putative biomarker for individuals with bipolar disorder.

Long non-coding RNAs in schizophrenia: Genetic variations, treatment markers and potential targeted signaling pathways

Schizophrenia (SZ), a complex and debilitating spectrum of psychiatric disorders, is now mainly attributed to multifactorial etiology that includes genetic and environmental factors. Long non-coding RNAs (lncRNAs) are gaining popularity as a way to better understand the comprehensive mechanisms beneath the clinical manifestation of SZ. Only in recent years has it been elucidated that mammalian genomes encode thousands of lncRNAs. Strikingly, roughly 30-40% of these lncRNAs are extensively expressed in different regions across the brain, which may be closely associated with SZ. The therapeutic and adverse effects of atypical antipsychotic drugs (AAPDs) are partially reflected by their role in the regulation of lncRNAs. This begs the question directly, do any lncRNAs exist as biomarkers for AAPDs treatment? Furthermore, we comprehend a range of mechanistic investigations that have revealed the regulatory roles for lncRNAs both involved in the brain and the periphery of SZ. More crucially, we also combine insights from a variety of signaling pathways to argue that lncRNAs probably play critical roles in SZ via their interactive downstream factors. This review provides a thorough understanding regarding dysregulation of lncRNAs, corresponding genetic alternations, as well as their potential regulatory roles in the pathology of SZ, which might help reveal useful therapeutic targets in SZ.

Machine learning-based predictive models and drug prediction for schizophrenia in multiple programmed cell death patterns

Background

Schizophrenia (SC) is one of the most common mental illnesses. However, the underlying genes that cause it and its effective treatments are unknown. Programmed cell death (PCD) is associated with many immune diseases and plays an important role in schizophrenia, which may be a diagnostic indicator of the disease.

Methods

Two groups as training and validation groups were chosen for schizophrenia datasets from the Gene Expression Omnibus Database (GEO). Furthermore, the PCD-related genes of the 12 patterns were extracted from databases such as KEGG. Limma analysis was performed for differentially expressed genes (DEG) identification and functional enrichment analysis. Machine learning was employed to identify minimum absolute contractions and select operator (LASSO) regression to determine candidate immune-related center genes, construct protein–protein interaction networks (PPI), establish artificial neural networks (ANN), and validate with consensus clustering (CC) analysis, then Receiver operating characteristic curve (ROC curve) was drawn for diagnosis of schizophrenia. Immune cell infiltration was developed to investigate immune cell dysregulation in schizophrenia, and finally, related drugs with candidate genes were collected via the Network analyst online platform.

Results

In schizophrenia, 263 genes were crossed between DEG and PCD-related genes, and machine learning was used to select 42 candidate genes. Ten genes with the most significant differences were selected to establish a diagnostic prediction model by differential expression profiling. It was validated using artificial neural networks (ANN) and consensus clustering (CC), while ROC curves were plotted to assess diagnostic value. According to the findings, the predictive model had a high diagnostic value. Immune infiltration analysis revealed significant differences in Cytotoxic and NK cells in schizophrenia patients. Six candidate gene-related drugs were collected from the Network analyst online platform.

Conclusion

Our study systematically discovered 10 candidate hub genes (DPF2, ATG7, GSK3A, TFDP2, ACVR1, CX3CR1, AP4M1, DEPDC5, NR4A2, and IKBKB). A good diagnostic prediction model was obtained through comprehensive analysis in the training (AUC 0.91, CI 0.95–0.86) and validation group (AUC 0.94, CI 1.00–0.85). Furthermore, drugs that may be useful in the treatment of schizophrenia have been obtained (Valproic Acid, Epigallocatechin gallate).

Expression analysis of NF-ƙB-related long non-coding RNAs in bipolar disorder

Bipolar disorder (BD) is a mental disorder that leads to abnormal swings in mood, energy, activity level, attention, and the capability to accomplish daily tasks. Several long non-coding RNAs (lncRNAs) are dysregulated in BD patients. We have compared expression levels of five NF-κB-associated lncRNAs, namely ANRIL, CEBPA-DT, H19, NKILA and HNF1A-AS1 in blood samples of BD patients compared with controls. While ANRIL, CEBPA-DT and HNF1-AS1 were significantly under-expressed in BD patients compared with controls, NKILA levels were higher in patients versus controls. Among differentially expressed genes, HFN1A-AS1 exhibited the best diagnostic parameters in the separation of patients from controls (AUC ± SD = 0.86 ± 0.03, sensitivity = 0.82, specificity = 0.82, P value < 0.0001). AUC values for NKILA, ANRIL and CEBPA-DT were 0.71, 0.68 and 0.65, respectively. In accordance with the previously reported participation of NF-ƙB in the pathophysiology of BD, the current study provides evidence for dysregulation of NF-κB-associated lncRNAs in BD.

Sodium Benzoate—Harmfulness and Potential Use in Therapies for Disorders Related to the Nervous System: A Review

Currently, due to the large number of reports regarding the harmfulness of food additives, more and more consumers follow the so-called “clean label” trend, i.e., prefer and choose the least-processed food products. One of the compounds known as a preservative with a high safety profile is sodium benzoate. While some studies show that it can be used to treat conditions such as depression, pain, schizophrenia, autism spectrum disorders, and neurodegenerative diseases, others report its harmfulness. For example, it was found to cause mutagenic effects, generate oxidative stress, disrupt hormones, and reduce fertility. Due to such disparate results, the purpose of this study is to comprehensively discuss the safety profile of sodium benzoate and its potential use in neurodegenerative diseases, especially in autism spectrum disorder (ASD), schizophrenia, major depressive disorder (MDD), and pain relief.

The emerging role of long non-coding RNAs in schizophrenia

Schizophrenia (SZ) is a severe psychiatric disorder which is contributed by both genetic and environmental factors. However, at present, its specific pathogenesis is still not very clear, and there is a lack of objective and reliable biomarkers. Accumulating evidence indicates that long non-coding RNAs (lncRNAs) are involved in the pathophysiology of several psychiatric disorders, including SZ, and hold promise as potential biomarkers and therapeutic targets for psychiatric disorders. In this review, we summarize and discuss the role of lncRNAs in the pathogenesis of SZ and their potential value as biomarkers and therapeutic targets.

Abnormal expression of NF-κB-related transcripts in blood of patients with inflammatory peripheral nerve disorders

The NF-κB family includes some transcription factors which have important functions in the regulation of immune responses, therefore participating in the pathophysiology of inflammatory conditions such as peripheral neuropathies. We have quantified expression of a number of NF-κB-related transcripts in patients with Guillain-Barré syndrome (GBS) or chronic inflammatory demyelinating polyneuropathy (CIDP) versus healthy subjects. These transcripts have been previously shown to be functionally related with this family of transcription factors. Expressions of ATG5, DICER-AS1, PACER, DILC, NKILA and ADINR have been increased in both CIDP and GBS patients compared with controls. However, expression of ATG5 was not different between female CIDP cases and female controls. Moreover, expression of PACER was not different between male GBS cases and male controls. Expression levels of CHAST and CEBPA were not different between patients and controls. Expression of none of the assessed genes was different between GBS and CIDP cases. Significant correlations have been revealed between expression amounts of NF-κB-related transcripts both among CIDP/ GBS patients and among controls except for NKILA/ATG5, ADINR/ATG5 and PACER/ATG5 and DICER-AS1/ATG5 pairs among controls whose expression levels have not been correlated. In the patient group, CEBPA/PACER, CHAST/PACER and CHAST/DICER-AS1 pairs had the most robust correlations (r = 0.94). Among controls, NKILA/ADINR pair had the most strong correlation (r = 0.78). ADINR and DICER-AS1 levels could differentiate CIDP cases from controls with 100% sensitivity and specificity. In differentiation of GBS cases from controls, these two transcripts had the AUC values of 0.99 and 1. Combination transcript levels of NF-κB-related transcripts similarly detects CIDP and GBS cases from healthy controls with 100% sensitivity and specificity. Therefore, NF-κB-related transcripts are possibly involved in the pathophysiology of inflammatory peripheral nerve disorders and can be used as diagnostic markers for these conditions.

Expression Analysis of NF-κB-Related lncRNAs in Parkinson's Disease

Parkinson’s disease (PD) has been shown to affect approximately 1% of the persons aged more than 65 years. This multifactorial disorder has been associated with abnormal function of NF-κB signals. In this research, we have evaluated expressions of NF-κB-related long non-coding RNAs in the circulation of PD patients compared with healthy controls. Expression of PACER was lower in total PD patients compared with healthy persons (Ratio of mean expressions (RME)=0.32, P value<0.001). This pattern was also evident among males (RME=0.25, P value<0.001). Expression of DILC was higher in total PD patients (RME=4.07, P value<0.001), and in both sex-based subgroups (RME=3.77, P value=0.01 and RME=4.25, P value<0.001, for females and males, respectively). Similarly, CEBPA was significantly over-expressed in total PD patients (RME=14.76, P value<0.001), and in both sex-based subgroups (RME=12.42, P value<0.001 and RME=15.80, P value<0.001, for females and males, respectively). ATG5 had a similar expression pattern (RME=2.6, P value=1E-08, RME=1.73, P value=0.03 and RME=3.09, P value=1E-07, for total cases, females and males, respectively). H19 was up-regulated in total cases and male cases compared with corresponding controls (RME=2.19, P value<0.001, RME=2.68, P value=0.01, respectively). Finally, HNFA1-AS was down-regulated in all comparisons (RME=0.10, P value=2E-06, RME=0.08, P value<0.001 and RME=0.12, P value<0.001, for total cases, females and males, respectively). Among PD patients, expressions of NKILA and ADINR were robustly correlated with each other (r=0.75, P value=2.40E-10). In addition, expression levels of DICER1-AS were significantly correlated with those of ADINR, PACER and H19 in these patients (r=0.73, P value=1.76E-9; r=0.72, P value=5.15E-09 and r=0.72, P value=3.09E-09, respectively). Correlation analyses among healthy controls revealed robust correlations between CHAST and CEBPA (r=0.84, P value=3.09E-09), NKILA and ADINR (r=0.80, P value=4.24E-12) as well as between DILC and CHAST (r=0.76, P value=1.70E-10). CEBPA had the best parameters among all assessed genes (AUC=0.96, Sensitivity=0.90 and specificity=0.97). DILC and ATG5 were the most appropriate markers after CEBPA with AUC values of 0.82 and 0.80, respectively. Most notably, combination of all genes improved AUC, sensitivity and specificity parameters to 1, 0.97 and 0.99, respectively. Cumulatively, the current study provides evidence for participation of NF-κB-related lncRNAs in the pathoetiology of PD.

Dysregulation of NF-κB-Associated LncRNAs in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a long-standing neurodevelopmental condition with prominent effects on social behavior of affected children. This disorder has been linked with neuroinflammatory responses. NF-κB has been shown to affect these responses in the orbitofrontal cortex of patients with ASD, thus being implicated in the pathogenesis of ASD. We measured expression of some NF-κB-associated lncRNAs and mRNAs (DILC, ANRIL, PACER, CHAST, ADINR, DICER1-AS1, HNF1A-AS1, NKILA, ATG5 and CEBPA) in the peripheral blood of ASD kids vs. healthy children. Expression quantities of ADINR, ANRIL, DILC, NKILA and CHAST were meaningfully higher in ASD cases compared with healthy kids (Posterior Beta = 1.402, P value < 0.0001; Posterior Beta = 2.959, P value < 0.0001; Posterior Beta = 0.882, P value = 0.012; Posterior Beta = 1.461, P value < 0.0001; Posterior Beta = 0.541, P value = 0.043, respectively). The Bonferroni corrected P values for these lncRNAs remained significant except for CHAST and DILC. Expression levels of other genes were not considerably different between cases and controls. Expressions of ATG5, DICER-AS1 and DILC were correlated with age of ASD patients (P < 0.0001). Among ASD cases, the most robust correlation has been detected between ADINR and NKILA (r = 0.87, P < 0.0001). Expression of none of genes has been correlated with age of healthy children. Among this group of children, expression levels of ADINR and CHAST were robustly correlated (r = 0.83, P < 0.0001). ANRIL had the greatest AUC value (AUC = 0.857), thus the best diagnostic power among the assessed genes. NKILA ranked the second position in this regard (AUC = 0.757). Thus, NF-κB-associated lncRNAs might partake in the pathogenesis of ASD.

Neuroepigenetics of psychiatric disorders: Focus on lncRNA

Understanding the pathology of psychiatric disorders is challenging due to their complexity and multifactorial origin. However, development of high-throughput technologies has allowed for better insight into their molecular signatures. Advancement of sequencing methodologies have made it possible to study not only the protein-coding but also the noncoding genome. It is now clear that besides the genetic component, different epigenetic mechanisms play major roles in the onset and development of psychiatric disorders. Among them, examining the role of long noncoding RNAs (lncRNAs) is a relatively new field. Here, we present an overview of what is currently known about the involvement of lncRNAs in schizophrenia, major depressive and bipolar disorders, as well as suicide. The diagnosis of psychiatric disorders mainly relies on clinical evaluation without using measurable biomarkers. In this regard, lncRNA may open new opportunities for development of molecular tests. However, so far only a small set of known lncRNAs have been characterized at molecular level, which means they have a long way to go before clinical implementation. Understanding how changes in lncRNAs affect the appearance and development of psychiatric disorders may lead to a more classified and objective diagnostic system, but also open up new therapeutic targets for these patients.

Long Non-Coding RNA (lncRNA) Roles in Cell Biology, Neurodevelopment and Neurological Disorders

Development is a complex process regulated both by genetic and epigenetic and environmental clues. Recently, long non-coding RNAs (lncRNAs) have emerged as key regulators of gene expression in several tissues including the brain. Altered expression of lncRNAs has been linked to several neurodegenerative, neurodevelopmental and mental disorders. The identification and characterization of lncRNAs that are deregulated or mutated in neurodevelopmental and mental health diseases are fundamental to understanding the complex transcriptional processes in brain function. Crucially, lncRNAs can be exploited as a novel target for treating neurological disorders. In our review, we first summarize the recent advances in our understanding of lncRNA functions in the context of cell biology and then discussing their association with selected neuronal development and neurological disorders.