Dysregulation of NF-κB-Associated lncRNAs in Multiple Sclerosis Patients

Diagnostic efficacy of long non-coding RNAs in multiple sclerosis: a systematic review and meta-analysis

Background

Currently, an increasing body of research suggests that blood-based long non-coding RNAs (lncRNAs) could serve as biomarkers for diagnosing multiple sclerosis (MS). This meta-analysis evaluates the diagnostic capabilities of selected lncRNAs in distinguishing individuals with MS from healthy controls and in differentiating between the relapsing and remitting phases of the disease.

Methods

We conducted comprehensive searches across seven databases in both Chinese and English to identify relevant studies, applying stringent inclusion and exclusion criteria. The quality of the selected references was rigorously assessed using the QUADAS-2 tool. The analysis involved calculating summarized sensitivity (SSEN), specificity (SSPE), positive likelihood ratio (SPLR), negative likelihood ratio (SNLR), and diagnostic odds ratio (DOR) with 95% confidence intervals (CIs). Accuracy was assessed using summary receiver operating characteristic (SROC) curves.

Results

Thirteen high-quality studies were selected for inclusion in the meta-analysis. Our meta-analysis assessed the combined diagnostic performance of lncRNAs in distinguishing MS patients from healthy controls. We found a SSEN of 0.81 (95% CI: 0.74-0.87), SSPE of 0.84 (95% CI: 0.78-0.89), SPLR of 5.14 (95% CI: 3.63-7.28), SNLR of 0.22 (95% CI: 0.16-0.31), and DOR of 23.17 (95% CI: 14.07-38.17), with an AUC of 0.90 (95% CI: 0.87-0.92). For differentiating between relapsing and remitting MS, the results showed a SSEN of 0.79 (95% CI: 0.71-0.85), SSPE of 0.76 (95% CI: 0.64-0.85), SPLR of 3.34 (95% CI: 2.09-5.33), SNLR of 0.28 (95% CI: 0.19-0.40), and DOR of 12.09 (95% CI: 5.70-25.68), with an AUC of 0.84 (95% CI: 0.81-0.87).

Conclusion

This analysis underscores the significant role of lncRNAs as biomarkers in MS diagnosis and differentiation between its relapsing and remitting forms.

Expression profile of long-noncoding RNAs MIR31HG, NKILA, and PACER in systemic lupus erythematosus patients

OBJECTIVES

Growing evidence suggests that systemic lupus erythematosus (SLE), an organ-damaging systemic autoimmune illness, may be influenced by long-noncoding RNAs (lncRNAs). This study aimed to assess the relative expression of lncRNAs (MIR31HG, NKILA, and PACER) in patients with SLE to evaluate their role in the disease.

DESIGN AND METHODS

This study involved 70 patients with SLE and 70 apparently healthy control subjects. The expression levels of lnc-MIR31HG, NKILA, and PACER were quantified using real-time PCR.

RESULTS

Lnc-MIR31HG, NKILA, and PACER were significantly upregulated in SLE cases compared to controls (P < 0.001). ROC curve analysis revealed a 91.43 % sensitivity of PACER for the diagnosis of SLE at a cutoff point of > 1.46, followed by NKILA with 90 % sensitivity at a cutoff point of > 1.16, and MIR31HG with 85.71 % sensitivity at a cutoff point of > 1.43. MIR31HG had the highest sensitivity for the diagnosis of lupus nephritis (86.67 %) at a cutoff point of > 7.19, then NKILA with 80 % sensitivity at a cutoff point of > 8.12, and finally PACER expression with 73.33 % sensitivity at a cutoff point of > 18.19. Moreover, MIR31HG and NKILA revealed a significant correlation with albumin/creatinine ratio, estimated glomerular filtration rate, and the SLEDAI score. Regression analysis revealed the potential roles of MIR31HG, NKILA, and PACER expression as predictors for SLE.

CONCLUSION

An upregulated lncRNA panel (MIR31HG, NKILA, and PACER) could play a role in the pathogenesis and, hence, the predispositiontoSLE. MIR31HG and NKILA can serve as prognostic markers significantly linked with disease activity.

Multiple Sclerosis: Roles of miRNA, lcnRNA, and circRNA and Their Implications in Cellular Pathways

Multiple sclerosis (MS) is a degenerative condition characterized by axonal damage and demyelination induced by autoreactive immune cells that occur in the Central Nervous System (CNS). The interaction between epigenetic changes and genetic factors can be widely involved in the onset, development, and progression of the disease. Although numerous efforts were made to discover new therapies able to prevent and improve the course of MS, definitive curative treatments have not been found yet. However, in recent years, it has been reported that non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long ncRNAs (lncRNAs), and circular RNAs (circRNAs), acting as gene expression regulators, could be used as potential therapeutic targets or biomarkers to diagnose and fight MS. In this review, we discussed the role of miRNAs, lncRNAs, and circRNAs, as well as their expression level changes and signaling pathways that are related to preclinical and human MS studies. Hence, the investigation of ncRNAs could be important to provide additional information regarding MS pathogenesis as well as promote the discovery of new therapeutic strategies or biomarkers.

Effect of nanoparticle macroalgae in the treatment of fatty liver disease using logistic regression, and support vector machine

One of the major health issues facing people worldwide is liver fibrosis. Liver fibrosis may be brought on by long-term exposure to harmful substances, medicines, and microorganisms. The development of liver fibrosis in children was particularly worrying due to their longer life-span, which was possibly related to a great risk of developing long-term complications. Marine algae species have provided a biological variety in the research phase of novel approaches to the treatment of numerous ailments. Marine macroalgae have recently been the subject of research due to their rich bioactive chemical composition and potential for the production of various nutraceuticals. Macroalgae are potentially excellent sources of bioactive substances with particular and distinct biological activity when compared to their terrestrial equivalents. Macroalgae in diverse marine cases offer a few biologically active metabolites, comprising sterols, polyunsaturated fatty acids, carotenoids, oligosaccharides, polysaccharides, proteins, polyphenols, vitamins, and minerals. Accordingly, there is great interest in their high potential for supporting immunomodulatory, antimicrobial, antidiabetic, antitumoral, anti-inflammatory, antiangiogenic, and neuroprotective properties. Using an experimental model, the current research intends to collect data on the therapeutic value of macroalgae nanoparticles for fatty liver disease. The researchers' goal of predicting illnesses from the extensive medical datasets is quite difficult. The purpose of this research is to assess the protective effects of a seaweed, Padina pavonia (PP), on liver fibrosis caused by carbon tetrachloride (CCl4). This research presents two models of logistic regression (LR) and support vector machines (SVM) for predicting the likelihood of liver disease incidence. The performance of the model was evaluated using a dataset. PP macro-algae considerably reduce the high blood concentrations of aminotransferases, alkaline phosphatases, and lactate dehydrogenases, as well as causing a considerable (p < 0.05) decrease in serum bilirubin levels. In addition to improving kidney function (urea and creatinine), algal extracts enhance fat metabolism (triglycerides and cholesterol). With an accuracy rate of 70.2%, a sensitivity of 92.3%, a specificity of 74.7%, a type I error of 9.1%, and a type II error of 21.0%, the predictive model has demonstrated excellent performance. The model validated laboratory tests' ability to predict illness (age; direct bilirubin (DB), total proteins (TP), and albumin (ALB). These classifier methods are compared on the basis of their execution time and classification accuracy.

Expression analysis of mTOR-associated lncRNAs in multiple sclerosis

mTOR has been shown to be involved in the regulation of immune responses and differentiation of immune cells. This protein is a candidate molecule for unraveling the molecular mechanisms of autoimmune disorders such as multiple sclerosis (MS). We designed the current study to assess expression of MTOR, and four associated long non-coding RNAs (lncRNAs), namely SNHG1, SNHG3, SHNG5 and DANCR in the peripheral blood of patients with MS compared with healthy controls. Analysis of real-time PCR results has shown down-regulation of SNHG5 and DANCR in MS patients compared with controls. Sex of study participants had no significant effect on expression of either genes and the interaction of sex and disease on expression levels of all studied genes were insignificant. There was a significant negative correlation between expression levels of MTOR gene and disease duration. No other significant correlations were detected between genes expressions and clinical/demographic data. SNHG5 and DANCR transcript levels had AUC values of 0.88 and 0.68 in separation of patients with MS from healthy controls, respectively. Taken together, our study suggests participation of two mTOR-related lncRNAs, i.e. SNHG5 and DANCR in the pathophysiology of MS.

Identification of Novel Key Genes and Pathways in Multiple Sclerosis Based on Weighted Gene Coexpression Network Analysis and Long Noncoding RNA-Associated Competing Endogenous RNA Network

Objective

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by chronic inflammation and demyelination. This study is aimed at identifying crucial genes and molecular pathways involved in MS pathogenesis.

Methods

Raw data in GSE52139 were collected from the Gene Expression Omnibus. The top 50% expression variants were subjected to weighted gene coexpression network analysis (WGCNA), and the key module associated with MS occurrence was identified. A long noncoding RNA- (lncRNA-) associated competing endogenous RNA (ceRNA) network was constructed in the key module. The hub gene candidates were subsequently verified in an individual database.

Results

Of the 18 modules obtained, the cyan module was designated as the key module. The established ceRNA network was composed of seven lncRNAs, 45 mRNAs, and 21 microRNAs (miRNAs), and the FAM13A-AS1 was the lncRNA with the highest centrality. Functional assessments indicated that the genes in the cyan module primarily gathered in ribosome-related functional terms. Interestingly, the targeted mRNAs of the ceRNA network enriched in diverse categories. Moreover, highly expressed CYBRD1, GNG12, and SMAD1, which were identified as hub genes, may be associated with “valine leucine and isoleucine degradation,” “base excision repair,” and “fatty acid metabolism,” respectively, according to the results of single gene-based genomes and gene set enrichment analysis (GSEA).

Conclusions

Combined with the WGCNA and ceRNA network, our findings provide novel insights into the pathogenesis of MS. The hub genes discovered herein might also serve as novel biomarkers that correlate with the development and management of MS.

Long Non-Coding RNAs, Novel Offenders or Guardians in Multiple Sclerosis: A Scoping Review

Multiple sclerosis (MS), a chronic inflammatory demyelinating disease of the central nervous system, is one of the most common neurodegenerative diseases worldwide. MS results in serious neurological dysfunctions and disability. Disturbances in coding and non-coding genes are key components leading to neurodegeneration along with environmental factors. Long non-coding RNAs (lncRNAs) are long molecules in cells that take part in the regulation of gene expression. Several studies have confirmed the role of lncRNAs in neurodegenerative diseases such as MS. In the current study, we performed a systematic analysis of the role of lncRNAs in this disorder. In total, 53 studies were recognized as eligible for this systematic review. Of the listed lncRNAs, 52 lncRNAs were upregulated, 37 lncRNAs were downregulated, and 11 lncRNAs had no significant expression difference in MS patients compared with controls. We also summarized some of the mechanisms of lncRNA functions in MS. The emerging role of lncRNAs in neurodegenerative diseases suggests that their dysregulation could trigger neuronal death via still unexplored RNA-based regulatory mechanisms. Evaluation of their diagnostic significance and therapeutic potential could help in the design of novel treatments for MS.

Scavenging the hidden impacts of non-coding RNAs in multiple sclerosis

Multiple sclerosis (MS) is a chronic neuroinflammatory disease that causes severe neurological dysfunction leading to disabilities in patients. The prevalence of the disease has been increasing gradually worldwide, and the specific etiology behind the disease is not yet fully understood. Therapies aimed against treating MS patients have been growing lately, intending to delay the disease progression and increase the patients' quality of life. Various pathways play crucial roles in developing the disease, and several therapeutic approaches have been tackling those pathways. However, these strategies have shown several side effects and inconsistent efficacy. MicroRNAs (miRNAs), long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) have been shown to act as key players in various disease pathogenesis and development. Several proinflammatory and anti-inflammatory miRNAs have been reported to participate in the development of MS. Hence, the review assesses the role of miRNAs, lncRNAs, and circRNAs in regulating immune cell functions better to understand their impact on the molecular mechanics of MS.

Expression analysis of NF-κB-associated long noncoding RNAs in peripheral blood mononuclear cells from relapsing-remitting multiple sclerosis patients

Long noncoding RNAs (lncRNAs) as potential disease biomarkers might be related to severe course of multiple sclerosis (MS). We evaluated expression levels of NF-κB-associated lncRNAs including HOTAIR, THRIL, H19, NKILA, and ANRIL; as well as expression of IL-6, TNF-α and MMP9, in peripheral blood mononuclear cells (PBMCs) from 60 relapse-remitting MS (RRMS) patients. At relapse phase of RRMS, up-regulation of ANRIL and H19 was positively correlated with the overexpression of IL-6; high levels of THRIL and HOTAIR was positively correlated with increased levels of TNF-α and MMP9, respectively; however, the NKILA expression was negatively correlated with the expression of TNF-α.

Screening of Potential Key Genes Related to Tubal Factor Infertility Based on Competitive Endogenous RNA Network

Background: The molecular biological mechanism of tubal factor infertility (TFI) is still unclear. Long noncoding RNAs (lncRNAs) are considered a major part of the competitive endogenous RNA (ceRNA) network and have attracted growing attention. Our study aimed to explore the regulatory mechanisms of lncRNAs associated with TFI and screen potential key genes related to TFI. Materials and Methods: Differentially expressed lncRNAs (DELs) and differentially expressed genes (DEGs) were identified by comparing normal and TFI expression patterns of lncRNAs and mRNAs in eutopic endometrial tissues obtained from 3 normal and 3 TFI patients during implantation. These data were used to develop a protein-protein interaction (PPI) network of DEGs using the STRING online software. The identified DELs and DEGs were then used to construct a ceRNA network, and the Network Analyzer Tool Kit in Cytoscape was used to analyze the ceRNA network topology and stability. Finally, the overlapping genes present in both the ceRNA and PPI networks were selected as the potential key genes related to TFI. Results: Ninety-six DEGs (59 up and 37 down) and 45 DELs (28 up and 17 down) were identified. Thirty-four DEGs were mapped in a PPI network. A ceRNA network, including two lncRNAs (LINC00305 and DLX6-AS1), four microRNAs (hsa-miR-20b-5p, hsa-miR-17-5p, hsa-miR-107, and hsa-miR-24-3p), and four mRNAs (MAP3K3, HMGB3, FAM103A1, and TMEM209), was successfully constructed. Importantly, a potential key gene (TMEM209) related to TFI was identified. Conclusion: The construction of a ceRNA network related to TFI may help elucidate the regulatory mechanism by which genes and lncRNAs function as ceRNA networks. Importantly, TMEM209 may be further evaluated as potential therapeutic targets for TFI.