Circulating lncRNA IFNG-AS1 expression correlates with increased disease risk, higher disease severity and elevated inflammation in patients with coronary artery disease

LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks

BACKGROUND

Long non-coding RNAs (lncRNAs) can prevent, diagnose, and treat a variety of complex human diseases, and it is crucial to establish a method to efficiently predict lncRNA-disease associations.

RESULTS

In this paper, we propose a prediction method for the lncRNA-disease association relationship, named LDAGM, which is based on the Graph Convolutional Autoencoder and Multilayer Perceptron model. The method first extracts the functional similarity and Gaussian interaction profile kernel similarity of lncRNAs and miRNAs, as well as the semantic similarity and Gaussian interaction profile kernel similarity of diseases. It then constructs six homogeneous networks and deeply fuses them using a deep topology feature extraction method. The fused networks facilitate feature complementation and deep mining of the original association relationships, capturing the deep connections between nodes. Next, by combining the obtained deep topological features with the similarity network of lncRNA, disease, and miRNA interactions, we construct a multi-view heterogeneous network model. The Graph Convolutional Autoencoder is employed for nonlinear feature extraction. Finally, the extracted nonlinear features are combined with the deep topological features of the multi-view heterogeneous network to obtain the final feature representation of the lncRNA-disease pair. Prediction of the lncRNA-disease association relationship is performed using the Multilayer Perceptron model. To enhance the performance and stability of the Multilayer Perceptron model, we introduce a hidden layer called the aggregation layer in the Multilayer Perceptron model. Through a gate mechanism, it controls the flow of information between each hidden layer in the Multilayer Perceptron model, aiming to achieve optimal feature extraction from each hidden layer.

CONCLUSIONS

Parameter analysis, ablation studies, and comparison experiments verified the effectiveness of this method, and case studies verified the accuracy of this method in predicting lncRNA-disease association relationships.

Identification and evaluation of candidate COVID-19 critical genes and medicinal drugs related to plasma cells

The ongoing COVID-19 pandemic, caused by the SARS-CoV-2 virus, represents one of the most significant global health crises in recent history. Despite extensive research into the immune mechanisms and therapeutic options for COVID-19, there remains a paucity of studies focusing on plasma cells. In this study, we utilized the DESeq2 package to identify differentially expressed genes (DEGs) between COVID-19 patients and controls using datasets GSE157103 and GSE152641. We employed the xCell algorithm to perform immune infiltration analyses, revealing notably elevated levels of plasma cells in COVID-19 patients compared to healthy individuals. Subsequently, we applied the Weighted Gene Co-expression Network Analysis (WGCNA) algorithm to identify COVID-19 related plasma cell module genes. Further, positive cluster biomarker genes for plasma cells were extracted from single-cell RNA sequencing data (GSE171524), leading to the identification of 122 shared genes implicated in critical biological processes such as cell cycle regulation and viral infection pathways. We constructed a robust protein-protein interaction (PPI) network comprising 89 genes using Cytoscape, and identified 20 hub genes through cytoHubba. These genes were validated in external datasets (GSE152418 and GSE179627). Additionally, we identified three potential small molecules (GSK-1070916, BRD-K89997465, and idarubicin) that target key hub genes in the network, suggesting a novel therapeutic approach. These compounds were characterized by their ability to down-regulate AURKB, KIF11, and TOP2A effectively, as evidenced by their low free binding energies determined through computational analyses using cMAP and AutoDock. This study marks the first comprehensive exploration of plasma cells' role in COVID-19, offering new insights and potential therapeutic targets. It underscores the importance of a systematic approach to understanding and treating COVID-19, expanding the current body of knowledge and providing a foundation for future research.

Expression analysis of Treg-related lncRNAs in neuromyelitis optica spectrum disorder

Neuromyelitis Optica Spectrum Disorder (NMOSD) is an autoimmune condition affecting the central nervous system, in which various kinds of immune cells, including T and B cells, and numerous cytokines and chemokines are implicated. LncRNAs modulating the function or differentiation of regulatory T cells (Tregs) may be involved in the pathoetiology of NMO. To assess the involvement of these lncRNAs in this disease, we studied the expression levels of TH2-LCR, MAFTRR, NEST, RMRP, and FLICR in NMO patients and healthy subjects. All of the lncRNAs listed were up-regulated in NMO patients compared with healthy controls. Although the interaction of group and gender factors significantly affected the expression of NEST, RMRP, and TH2-LCR genes, we detected no effect of gender factor on the expression of the examined genes. The highest expression correlation was found between RMRP and TH2-LCR among cases with correlation coefficient 0.73. ROC curve analysis indicated that TH2-LCR, MAFTRR, RMRP, and FLICR had significant prospective diagnostic power (AUC ± SD = 0.99 ± 0.002, 0.97 ± 0.01, 0.91 ± 0.01 and 0.84 ± 0.04, respectively). Best of these genes was TH2-LCR with AUC ± SD = 0.99 ± 0.002, sensitivity= 0.97, specificity= 1, P-value= <0.0001. RMRP and TH2-LCR had a positive correlation with age and age at onset and a negative correlation with EDSS. Cumulatively, TH2-LCR, MAFTRR, RMRP, and FLICR lncRNAs, particularly TH2-LCR, could be considered as potential contributors to the pathogenesis of NMO disease.

Role of lncRNAs in acute pancreatitis: pathogenesis, diagnosis, and therapy

Acute pancreatitis (AP) is one of the most common acute abdominal diseases characterized by an injury and inflammatory disorder of the pancreas with complicated pathological mechanisms. Long non-coding RNAs (lncRNAs) have been shown to play an important role in various physiological and pathological processes in humans, and they have emerged as potential biomarkers of diagnosis and therapeutic targets in various diseases. Recently, accumulating evidence has shown significant alterations in the expression of lncRNAs, which are involved in the pathogenesis of AP, such as premature trypsinogen activation, impaired autophagy, inflammatory response, and acinar cell death. Moreover, lncRNAs can be the direct target of AP treatment and show potential as biomarkers for the diagnosis. Thus, in this review, we focus on the role of lncRNAs in the pathogenesis, diagnosis, and therapy of AP and emphasize the future directions to study lncRNAs in AP, providing new insight into understanding the cellular and molecular mechanisms of AP and seeking novel biomarkers for the diagnosis and therapeutic targets to improve clinical management in the future.

Potential roles of microRNAs and long noncoding RNAs as diagnostic, prognostic and therapeutic biomarkers in coronary artery disease

Coronary artery disease (CAD), which is mainly caused by atherosclerotic processes in coronary arteries, became a significant health issue. MicroRNAs (miRNAs), and long noncoding RNAs (lncRNAs), have been shown to be stable in plasma and could thereby be adopted as biomarkers for CAD diagnosis and treatment. MiRNAs can regulate CAD development through different pathways and mechanisms, including modulation of vascular smooth muscle cell (VSMC) activity, inflammatory responses, myocardial injury, angiogenesis, and leukocyte adhesion. Similarly, previously studies have indicated that the causal effects of lncRNAs in CAD pathogenesis and their utility in CAD diagnosis and treatment, has been found to lead to cell cycle transition, proliferation dysregulation, and migration in favour of CAD development. Differential expression of miRNAs and lncRNAs in CAD patients has been identified and served as diagnostic, prognostic and therapeutic biomarkers for the assessment of CAD patients. Thus, in the current review, we summarize the functions of miRNAs and lncRNAs, which aimed to identify novel targets for the CAD diagnosis, prognosis, and treatment.

The correlation of long non-coding RNAs IFNG-AS1 and ZEB2-AS1 with IFN-γ and ZEB-2 expression in PBMCs and clinical features of patients with coronary artery disease

BACKGROUND

Aberrant expression of long non-coding RNAs (lncRNAs) can contribute to the pathogenesis of coronary artery disease (CAD). In this study, we aimed to evaluate the expression of lncRNA interferon γ-antisense 1 (IFNG-AS1), zinc finger E-box binding homeobox 2 antisense RNA 1 (ZEB2-AS1), and their direct target genes (IFN-γ and ZEB2, respectively) in peripheral blood mononuclear cell (PBMC) from CAD and healthy individuals.

METHODS AND RESULTS

We recruited 40 CAD patients and 40 healthy individuals. After doing some bioinformatics analyses, the expressions of IFNG-AS1/ ZEB2-AS1 lncRNAs and IFN-γ/ ZEB2 in PBMCs were measured using quantitative real-time PCR. The possible correlation between the putative lncRNAs and disease severity was also assessed. Receiver operating characteristic (ROC) curve analysis was used to evaluate the predictive role of lncRNAs as diagnostic biomarkers in CAD patients. The expressions of IFNG-AS1 lncRNA as well as IFN-γ and ZEB2 genes were significantly reduced in CAD patients compared to healthy subjects. In contrast, the expression of ZEB2-AS1 was up-regulated in these patients. Linear regression analysis unveiled that there is a positive correlation between the expression of IFNG-AS1 and IFN-γ, also similarly, ZEB2-AS1 and ZEB2 in PBMCs of subjects. Moreover, the expression of IFNG-AS1 and ZEB2-AS1 correlated with the Gensini score. The area under the ROC curves ranged from 0.633-0.742 for ZEB2-AS1/ZEB2 and IFNG-AS1/IFN-γ, respectively.

CONCLUSIONS

Our results indicated that the dysregulation of IFNG-AS1/IFN-γ and ZEB2-AS1/ZEB2 in PBMCs of CAD patients may be involved in CAD pathogenesis.

Risk Prediction of Coronary Artery Stenosis in Patients with Coronary Heart Disease Based on Logistic Regression and Artificial Neural Network

Objective

Coronary heart disease (CHD) is considered an inflammatory relative disease. This study is aimed at analyzing the health information of serum interferon in CHD based on logistic regression and artificial neural network (ANN) model.

Method

A total of 155 CHD patients diagnosed by coronary angiography in our department from January 2017 to March 2020 were included. All patients were randomly divided into a training set (n = 108) and a test set (n = 47). Logistic regression and ANN models were constructed using the training set data. The predictive factors of coronary artery stenosis were screened, and the predictive effect of the model was evaluated by using the test set data. All the health information of participants was collected. Expressions of serum IFN-γ, MIG, and IP-10 were detected by double antibody sandwich ELISA. Spearman linear correlation analysis determined the relationship between the interferon and degree of stenosis. The logistic regression model was used to evaluate independent risk factors of CHD.

Result

The Spearman correlation analysis showed that the degree of stenosis was positively correlated with serum IFN-γ, MIG, and IP-10 levels. The logistic regression analysis and ANN model showed that the MIG and IP-10 were independent predictors of Gensini score: MIG (95% CI: 0.876~0.934, P < 0.001) and IP-10 (95% CI: 1.009~1.039, P < 0.001). There was no statistically significant difference between the logistic regression and the ANN model (P > 0.05).

Conclusion

The logistic regression model and ANN model have similar predictive performance for coronary artery stenosis risk factors in patients with CHD. In patients with CHD, the expression levels of IFN-γ, IP-10, and MIG are positively correlated with the degree of stenosis. The IP-10 and MIG are independent risk factors for coronary artery stenosis.

Circulating non-coding RNAs as biomarkers in coronary artery disease

Coronary artery disease (CAD) is a leading cause of mortality worldwide. Atherosclerosis involves an interplay of different pathological mechanisms, such as progressive inflammation, abnormal lipid metabolism, and oxidative stress, and as such represents the basic pathological phenomenon underlying CAD. Atherosclerotic plaque narrows the lumen of coronary arteries, creating an ischemic environment for the heart muscle, which finally leads to clinical complications, such as acute myocardial infarction. Currently, there are no biomarkers that could predict plaque stability or major adverse cardiovascular events (MACE). Numerous functional non-coding RNA (ncRNA) species influence basic cellular functions, and as such play a role in the development and progression of CAD. Of these ncRNAs, micro RNAs (miRNAs) and long non-coding RNAs (lncRNAs) are the most investigated. Considering that ncRNAs detected in extracellular fluids can originate from different cells, circulating ncRNAs are being intensively investigated as potential biomarkers in the diagnosis and prognosis of CAD. In the following paper, we provide current insights into potential molecular mechanisms by which miRNAs and lncRNAs contribute to the pathology of CAD and discuss their potential role as biomarkers in diagnosis and prognosis of disease.

Significance of long non-coding RNA IFNG-AS1 in the progression and clinical prognosis in colon adenocarcinoma

Colon adenocarcinoma originates from adenoma and triggers serious healthy burdensome. lncRNAs develop a crucial role in the progression of colorectal carcinoma. In this study, we aimed to investigate the clinical value and potential role of lncRNA interferon (IFN) gamma antisense RNA 1 (IFNG-AS1) in colon adenocarcinoma. This study enrolled 95 colorectal adenoma patients, 128 colorectal adenocarcinoma patients, and 88 healthy individuals. The serum, tissue IFNG-AS1 expression levels were explored by real-time quantitative reverse transcription-PCR (RT-qPCR) assay. The receiver operator characteristic curve and Kaplan-Meier method were used to assess the clinical significance of IFNG-AS1. The chi-square test was used to analyze the association between tissue IFNG-AS1 and clinical characteristics. Functional experiments were conducted to delve into the effects of IFNG-AS1 on cellular activities (cell viability/migration/invasion). The target miRNA of IFNG-AS1 was also explored. IFNG-AS1 expression in both serum and tissue samples was elevated in patients. Serum IFNG-AS1 could diagnose colon adenoma and adenocarcinoma patients from the healthy control. High tissue IFNG-AS1 was correlated with several clinical characteristics and a shorter overall survival time. Silence of IFNG-AS1 could be available for repressing cellular capacities via the sponge to miR-627-3p. IFNG-AS1 was rised in colon adenocarcinoma and it was relevant to tumor size, TNM stage, and poor prognosis of patients. Beyond that, downregulated expression of IFNG-AS1 may repress malignant progression of colon adenocarcinoma by regulating miR-627-3p. IFNG-AS1 might be a potential diagnosis or prognosis predictor for colon adenocarcinoma patients.

Long non-coding RNAs in metabolic disorders: pathogenetic relevance and potential biomarkers and therapeutic targets

BACKGROUND

It has been suggested that dysregulation of long non-coding RNAs (lncRNAs) could be associated with the incidence and development of metabolic disorders.

AIM

Accordingly, this narrative review described the molecular mechanisms of lncRNAs in the development of metabolic diseases including insulin resistance, diabetes, obesity, non-alcoholic fatty liver disease (NAFLD), cirrhosis, and coronary artery diseases (CAD). Furthermore, we investigated the up-to-date findings on the association of deregulated lncRNAs in the metabolic disorders, and potential use of lncRNAs as biomarkers and therapeutic targets.

CONCLUSION

LncRNAs/miRNA/regulatory proteins axis plays a crucial role in progression of metabolic disorders and may be used in development of therapeutic and diagnostic approaches.

Endothelial Dysfunction, Inflammation and Coronary Artery Disease: Potential Biomarkers and Promising Therapeutical Approaches

Coronary artery disease (CAD) and its complications are the leading cause of death worldwide. Inflammatory activation and dysfunction of the endothelium are key events in the development and pathophysiology of atherosclerosis and are associated with an elevated risk of cardiovascular events. There is great interest to further understand the pathophysiologic mechanisms underlying endothelial dysfunction and atherosclerosis progression, and to identify novel biomarkers and therapeutic strategies to prevent endothelial dysfunction, atherosclerosis and to reduce the risk of developing CAD and its complications. The use of liquid biopsies and new molecular biology techniques have allowed the identification of a growing list of molecular and cellular markers of endothelial dysfunction, which have provided insight on the molecular basis of atherosclerosis and are potential biomarkers and therapeutic targets for the prevention and or treatment of atherosclerosis and CAD. This review describes recent information on normal vascular endothelium function, as well as traditional and novel potential biomarkers of endothelial dysfunction and inflammation, and pharmacological and non-pharmacological therapeutic strategies aimed to protect the endothelium or reverse endothelial damage, as a preventive treatment for CAD and related complications.

Relationship between long non-coding RNA polymorphism and the risk of coronary artery disease: A protocol for systematic review and meta-analysis

BACKGROUND

Previous epidemiological studies displayed that long non-coding RNA (LncRNA) polymorphisms are associated with an increased risk of coronary artery disease, while the results are inconsistent. Therefore, we conducted a meta-analysis to more accurately determine the association between LncRNA polymorphism and the risk of coronary artery disease.

METHODS

PubMed, EmBase and Web of Science databases were searched, and the time to build the database was set until December 2020. The association between LncRNA polymorphism and the risk of coronary artery disease was collected and evaluated. Meta-analysis was performed by STATA 14.0 software, and the odds ratio and its 95% confidence interval (95%CI) were applied to estimate the association between LncRNA polymorphism and the risk of coronary artery disease.

RESULTS

The results of this meta-analysis will be submitted to a peer-reviewed journal for publication.

CONCLUSION

This meta-analysis will summarize the relationship between LncRNA polymorphism and coronary disease risk.

ETHICS AND DISSEMINATION

Ethical approval was not required for this study. The systematic review will be published in a peer-reviewed journal, presented at conferences, and shared on social media platforms. This review would be disseminated in a peer-reviewed journal or conference presentations.

OSF REGISTRATION NUMBER

DOI 10.17605/OSF.IO/9XPHS.

The Emerging Role of Long Non-coding RNAs and Circular RNAs in Coronary Artery Disease

Coronary artery disease (CAD) is a common disorder caused by atherosclerotic processes in the coronary arteries. This condition results from abnormal interactions between numerous cell types in the artery walls. The main participating factors in this process are accumulation of lipid deposits, endothelial cell dysfunction, macrophage induction, and changes in smooth muscle cells. Several lines of evidence underscore participation of long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in the pathogenesis of CAD. Several lncRNAs such as H19, ANRIL, MIAT, lnc-DC, IFNG-AS1, and LEF1-AS1 have been shown to be up-regulated in the biological materials obtained from CAD patients. On the other hand, Gas5, Chast, HULC, DICER1-AS1, and MEG3 have been down-regulated in CAD patients. Meanwhile, a number of circRNAs have been demonstrated to influence function of endothelial cells or vascular smooth muscle cells, thus contributing to the pathogenesis of CAD. In the current review, we summarize the function of lncRNAs and circRNAs in the development and progression of CAD.

Disease-Causing Mutations and Rearrangements in Long Non-coding RNA Gene Loci

The classic understanding of molecular disease-mechanisms is largely based on protein-centric models. During the past decade however, genetic studies have identified numerous disease-loci in the human genome that do not encode proteins. Such non-coding DNA variants increasingly gain attention in diagnostics and personalized medicine. Of particular interest are long non-coding RNA (lncRNA) genes, which generate transcripts longer than 200 nucleotides that are not translated into proteins. While most of the estimated ~20,000 lncRNAs currently remain of unknown function, a growing number of genetic studies link lncRNA gene aberrations with the development of human diseases, including diabetes, AIDS, inflammatory bowel disease, or cancer. This suggests that the protein-centric view of human diseases does not capture the full complexity of molecular patho-mechanisms, with important consequences for molecular diagnostics and therapy. This review illustrates well-documented lncRNA gene aberrations causatively linked to human diseases and discusses potential lessons for molecular disease models, diagnostics, and therapy.

Lnc-ITSN1-2, Derived From RNA Sequencing, Correlates With Increased Disease Risk, Activity and Promotes CD4+ T Cell Activation, Proliferation and Th1/Th17 Cell Differentiation by Serving as a ceRNA for IL-23R via Sponging miR-125a in Inflammatory Bowel Disease

Background: This study aimed to investigate long-non-coding RNA (lncRNA) expression profiles and the correlation of lnc-ITSN1-2 expression with disease risk, activity and inflammation, and its influence on CD4⁺ T cell activation, proliferation, and differentiation of inflammatory bowel disease (IBD).

Methods: LncRNA expression profiles were detected in intestinal mucosa samples from six IBD patients and six healthy controls (HCs). Intestinal mucosa and PBMC lnc-ITSN1-2, IL-23R, and inflammatory cytokines were measured in 120 IBD patients [60 Crohn's disease (CD) and 60 ulcerative colitis (UC)] and 30 HCs. Effect of lnc-ITSN1-2 on IBD CD4⁺ T cell activation, proliferation, and differentiation was determined and its regulatory interaction with miR-125a and IL-23R was detected.

Results: Three-hundred-and-nine upregulated and 310 downregulated lncRNAs were identified in IBD patients by RNA-Sequencing, which were enriched in regulating immune and inflammation related pathways. Large-sample qPCR validation disclosed that both intestinal mucosa and PBMC lnc-ITSN1-2 expressions were increased in IBD patients compared to HCs, and presented with good predictive values for IBD risk, especially for active disease conditions, and they positively correlated with disease activity, inflammation cytokines, and IL-23R in IBD patients. Lnc-ITSN1-2 was decreased after infliximab treatment in active-CD patients. Furthermore, lnc-ITSN1-2 promoted IBD CD4⁺ T cell activation and proliferation, and stimulated Th1/Th17 cell differentiation. Multiple rescue experiments disclosed that lnc-ITSN1-2 functioned in IBD CD4⁺ T cells via targeting miR-125a, then positively regulating IL-23R. Luciferase Reporter assay observed that lnc-ITSN1-2 bound miR-125a, and miR-125a bound IL-23R.

Conclusion: Lnc-ITSN1-2 correlates with increased disease risk, activity, and inflammatory cytokines of IBD, and promotes IBD CD4⁺ T cell activation, proliferation, and Th1/Th17 cell differentiation by serving as a competing endogenous RNA for IL-23R via sponging miR-125a.

IFNG/IFNG-AS1 expression level balance: implications for autism spectrum disorder

Autism spectrum disorder (ASD) is a neurodevelopmental disorder associated with different epidemiological, genetic, epigenetic, and environmental factors. Although its etiology is not fully understood, immune dysfunction is implicated in this disease. Recently, a large number of genes encoding long noncoding RNAs (lncRNAs) were discovered which act as positive or negative regulators of neighboring target genes. The lncRNA, Interferon gamma-antisense RNA (IFNG-AS1), regulates expression levels of the Interferon gamma (IFNG) gene. In the present study, we investigated expression of IFNG and IFNG-AS1 in 50 children with ASD (15 females and 35 males, mean age: 6 ± 1.4 years) and 50 healthy controls (14 females and 36 males, mean age: 6 ± 1.74 years) by real time PCR technique. The results showed significant up-regulation of IFNG and down-regulation of IFNG-AS1 expression in children with ASD compared to controls (Fold change = 1.5, P < 0.0001; Fold change = -0.143, P = 0.013, respectively). The IFNG expression level increase was more pronounced in male ASD children (Fold change = 1.621; p < 0.0001). Our data reveal a functional disruption in the interactive network of IFNG/IFNG-AS1 regulation, which could be a contributing factor in the chronic inflammatory aspect of ASD. Our findings can help understanding the underlying contributors to ASD pathogenesis and find novel treatment options for children with ASD.

Non-coding RNAs and Coronary Artery Disease

Coronary artery disease (CAD) is the leading death cause worldwide. Non-coding RNA (ncRNA) are key regulators of genetic expression and thus can affect directly or indirectly the development and progression of different diseases. ncRNA can be classified in several types depending on the length or structure, as long non-coding RNA (lncRNA), microRNA (miRNA) and circularRNA (circRNA), among others. These types of RNA are present within cells or in circulation, and for this reason they have been used as biomarkers of different diseases, therefore revolutionizing precision medicine. Recent research studied the capability of circulating ncRNA to inform about CAD presence and predict the outcome of the disease. In this chapter we present a list of the miRNA, lncRNA and circRNA which are potential biomarkers of CAD.

Predictive value of long non-coding RNA intersectin 1-2 for occurrence and in-hospital mortality of severe acute pancreatitis

Background

This study aimed to investigate the predictive value of long non‐coding RNA intersectin 1‐2 (lnc‐ITSN1‐2) for severe acute pancreatitis (SAP) risk, and its correlation with disease severity and in‐hospital mortality in SAP patients.

Methods

Plasma samples from 60 SAP, 60 moderate‐severe acute pancreatitis (MSAP) and 60 mild acute pancreatitis (MAP) patients were collected within 24 hours, and plasma samples from 60 age and gender‐matched healthy controls (HCs) were collected when enrollment. Lnc‐ITSN1‐2 was detected by reverse transcription‐quantitative polymerase chain reaction. In AP patients, disease severity was evaluated and in‐hospital deaths were recorded.

Results

Lnc‐ITSN1‐2 was increased in SAP patients compared with MSAP, MAP patients, and HCs, and it is well‐discriminated SAP patients from MSAP patients (area under curve (AUC): 0.699, 95% confidence interval (CI): 0.605‐0.792), MAP patients (AUC: 0.862, 95% CI: 0.798‐0.926), and HCs (AUC: 0.958, 95% CI: 0.925‐0.990). For disease severity, lnc‐ITSN1‐2 was positively correlated with Ranson's score, acute pathologic and chronic health evaluation (APACHE) II score, sequential organ failure assessment (SOFA) score, and C‐reactive protein (CRP) in SAP patients, MSAP patients, and MAP patients; meanwhile, the correlation coefficients were highest in SAP patients. Furthermore, lnc‐ITSN1‐2 displayed a good predictive value for increased in‐hospital mortality in SAP (AUC: 0.803, 95% CI: 0.673‐0.933) and MSAP (AUC: 0.854, 95% CI: 0.752‐0.956) patients, which was similar with several common prognostic factors (including Ranson's score, APACHE II score, SOFA score, and CRP).

Conclusion

Lnc‐ITSN1‐2 might be a potential biomarker for discrimination of SAP to improve the prognosis of SAP patients.

The correlation of long non-coding RNA intersectin 1-2 with disease risk, disease severity, inflammation, and prognosis of acute ischemic stroke

Background

This study aimed to evaluate the predictive value of long non‐coding RNA intersectin 1‐2 (lnc‐ITSN1‐2) for acute ischemic stroke (AIS) risk, and investigate its correlation with disease severity, inflammation, and recurrence‐free survival (RFS) in AIS patients.

Methods

Three hundred and twenty AIS patients were recruited, and plasma samples were collected within 24 hours after admission. lnc‐ITSN1‐2 expression form plasma was detected by reverse transcription‐quantitative polymerase chain reaction (RT‐qPCR). The National Institute of Health Stroke Scale (NIHSS) score was assessed, and RFS was calculated. Meanwhile, 320 controls were enrolled and plasma samples were collected on the enrollment, and lnc‐ITSN1‐2 expression was detected by RT‐qPCR.

Results

lnc‐ITSN1‐2 expression was increased in AIS patients compared to controls (P < .001), and receiver operating characteristic curve revealed its predictive value for AIS risk (area under the curve: 0.804, 95% confidence interval, 0.763‐0.845). In AIS patients, lnc‐ITSN1‐2 expression was positively correlated with NIHSS score (r = 0.464, P < .001). For inflammation, lnc‐ITSN1‐2 expression was positively correlated with CRP (r = 0.398, P < .001), TNF‐α (r = 0.502, P < .001), IL‐1β (r = 0.313, P < .001), IL‐6 (r = 0.207, P < .001), IL‐8 (r = 0.400, P < .001), IL‐17 (r = 0.272, P < .001), and IL‐22 (r = 0.222, P < .001). In terms of predicted target microRNAs, lnc‐ITSN1‐2 expression was negatively correlated with microRNA (miR)‐107 (r = −0.467, P < .001), miR‐125a (r = −0.494, P < .001), and miR‐146a (r = −0.126, P = .025). For prognosis, high lnc‐ITSN1‐2 expression was correlated with worse RFS in AIS patients.

Conclusion

lnc‐ITSN1‐2 exerts a good predictive value for AIS risk; meanwhile, its increased expression is correlated with enhanced disease severity, elevated inflammation, and worse RFS in AIS patients.

Cell-Free Nucleic Acids and their Emerging Role in the Pathogenesis and Clinical Management of Inflammatory Bowel Disease

Cell-free nucleic acids (cfNAs) are defined as any nucleic acids that are present outside the cell. They represent valuable biomarkers in various diagnostic protocols such as prenatal diagnostics, the detection of cancer, and cardiovascular or autoimmune diseases. However, in the current literature, little is known about their implication in inflammatory bowel disease (IBD). IBD is a group of multifactorial, autoimmune, and debilitating diseases with increasing incidence worldwide. Despite extensive research, their etiology and exact pathogenesis is still unclear. Since cfNAs were observed in other autoimmune diseases and appear to be relevant in inflammatory processes, their role in the pathogenesis of IBD has also been suggested. This review provides a summary of knowledge from the available literature about cfDNA and cfRNA and the structures involving them such as exosomes and neutrophil extracellular traps and their association with IBD. Current studies showed the promise of cfNAs in the management of IBD not only as biomarkers distinguishing patients from healthy people and differentiating active from inactive disease state, but also as a potential therapeutic target. However, the detailed biological characteristics of cfNAs need to be fully elucidated in future experimental and clinical studies.

Immune cells as targets for cardioprotection: new players and novel therapeutic opportunities

New therapies are required to reduce myocardial infarct (MI) size and prevent the onset of heart failure in patients presenting with acute myocardial infarction (AMI), one of the leading causes of death and disability globally. In this regard, the immune cell response to AMI, which comprises an initial pro-inflammatory reaction followed by an anti-inflammatory phase, contributes to final MI size and post-AMI remodelling [changes in left ventricular (LV) size and function]. The transition between these two phases is critical in this regard, with a persistent and severe pro-inflammatory reaction leading to adverse LV remodelling and increased propensity for developing heart failure. In this review article, we provide an overview of the immune cells involved in orchestrating the complex and dynamic inflammatory response to AMI-these include neutrophils, monocytes/macrophages, and emerging players such as dendritic cells, lymphocytes, pericardial lymphoid cells, endothelial cells, and cardiac fibroblasts. We discuss potential reasons for past failures of anti-inflammatory cardioprotective therapies, and highlight new treatment targets for modulating the immune cell response to AMI, as a potential therapeutic strategy to improve clinical outcomes in AMI patients. This article is part of a Cardiovascular Research Spotlight Issue entitled 'Cardioprotection Beyond the Cardiomyocyte', and emerged as part of the discussions of the European Union (EU)-CARDIOPROTECTION Cooperation in Science and Technology (COST) Action, CA16225.

Elevated circulating lnc-ANRIL/miR-125a axis level predicts higher risk, more severe disease condition, and worse prognosis of sepsis

AIM

This study aimed to investigate the correlation of lnc-ANRIL/miR-125a axis with risk, severity, inflammation, and prognosis of sepsis.

METHODS

A hundred and twenty-six sepsis patients and 125 healthy controls were recruited, and then, blood samples were collected, and plasma was separated for lnc-ANRIL, miR-125a, lnc-ANRIL/miR-125a axis, and inflammatory cytokine level detections. In addition, basic characteristics, 28-day mortality, and accumulating survival of sepsis patients were recorded.

RESULTS

Plasma lnc-ANRIL expression was increased, miR-125a expression was decreased, and lnc-ANRIL/miR-125a axis level was elevated in sepsis patients compared with healthy controls, and all of them had good value for predicting sepsis risk with AUCs of 0.800, 0.817, and 0.843, respectively. Lnc-ANRIL and lnc-ANRIL/miR-125a axis were positively correlated with biochemical index levels including CRP and PCT levels, disease severity scale scores, and pro-inflammatory cytokine levels in sepsis patients, while miR-125a displayed the opposite trend. Lnc-ANRIL and lnc-ANRIL/miR-125a axis expressions were elevated, while miR-125a expression was declined in deaths compared with survivors, and all of them predicted 28-day mortality in sepsis patients with AUCs of 0.765, 0.745, and 0.785, respectively. Subsequently, the Kaplan-Meier analysis revealed that patients with high lnc-ANRIL, low miR-125a, and high lnc-ANRIL/miR-125a axis levels presented with worse accumulating survival. In addition, multivariate regression model analyses revealed that high plasma lnc-ANRIL/miR-125a axis was an independent predictive factor for both increased 28-day mortality and worse accumulating survival.

CONCLUSION

Circulating lnc-ANRIL/miR-125a axis was upregulated and could serve as a biomarker for severity, inflammation, and prognosis in sepsis patients.

Diagnostic potential of circulating LncRNAs in human cardiovascular disease: a meta-analysis

Cardiovascular disease (CVD) is a major killer of the human population around the world. Identifying effective diagnostic biomarkers for CVDs is particularly important in order to guide optimizing treatment. Accumulating evidence on aberrantly regulated circulating long non-coding RNAs (LncRNAs) promise to serve as a diagnostic or prognostic biomarker for various types of CVDs. We summarized studies to identify the potential diagnostic values of LncRNAs in CVD patients. We included articles reporting on the association between LncRNAs and diagnosis in CVDs. We calculated sensitivities, specificities, and area under the curves of LncRNAs. The pooled overall sensitivity and specificity for LncRNAs expression profile in differentiating CVD patients from controls (non-CVDs or healthy subjects) were 0.74 (95%CI 0.68–0.80) and 0.81 (95%CI 0.76–0.85), respectively; the overall positive likelihood ratio, 3.9 (95%CI 3.1–4.9); the negative likelihood ratio, 0.32 (95%CI 0.25–0.40); corresponding to an area under curve of 0.85 (95%CI 0.82–0.88) and overall diagnostic odds ratio 12 (95%CI 9–18). Subgroup analysis showed that the detection of LncRNAs expression in plasma substantially improved the diagnostic accuracy. Likewise, meta-regression analysis indicated that the detection method and sample size were the main source of heterogeneity. All these results suggested a relatively good reference value of LncRNAs as auxiliary biomarkers for CVDs, and should be considered in cases where the diagnosis is uncertain. Population-based prospective cohort studies are warranted to confirm our findings.

Global expression profiling of metabolic pathway-related lncRNAs in human gastric cancer and the identification of RP11-555H23.1 as a new diagnostic biomarker

BACKGROUND

Long noncoding RNAs (lncRNAs) have roles in regulating metabolism; however, the global expression profile of metabolic pathway-associated lncRNAs in gastric cancer is unknown. The purpose of our study was to examine metabolic pathway-related lncRNAs in gastric cancer and their possible diagnostic values.

METHODS

Differential expression patterns of metabolic pathway-related lncRNAs between gastric cancer and paired nontumor tissues were detected using metabolic pathway-associated lncRNA microarrays. The expression of RP11-555H23.1, one representative metabolic pathway-associated lncRNA, was validated using quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). The associations between RP11-55H23.1 expression and the clinicopathological features of gastric cancer patients were analyzed. A receiver operating characteristic (ROC) curve was further established.

RESULTS

A total of 114 differentially expressed metabolic pathway-associated lncRNAs (fold change >2, P < 0.05) between cancer and nontumor tissues were found (GEO No. GSE96856). Among them, TUG1, RP11-555H23.1, RP1-257I20.13, UGP2, GCSHP3, and XLOC_000889 lncRNAs were downregulated more than sixfold in gastric cancer tissues. In contrast, RP11-605F14.2, TBC1D3P5, BC130595, LINC00475, RP11-19P22.6, BC080653, XLOC_004923, AFAP1-AS1, EPB49, and RP11-296I10.3 lncRNAs were upregulated more than sixfold in gastric cancer tissues. We further demonstrated that RP11-555H23.1 expression was significantly correlated with TNM stage (P = 0.038). The area under the ROC curve (AUC) was 0.65, and the specificity and sensitivity were 62% and 81%, respectively.

CONCLUSIONS

Metabolic pathway-associated lncRNAs play an important role in the occurrence of gastric cancer, and metabolic pathway-associated lncRNAs, such as RP11-555H23.1, may represent novel biomarkers of gastric cancer.

Circulating lncRNA IFNG-AS1 expression correlates with increased disease risk, higher disease severity and elevated inflammation in patients with coronary artery disease

BACKGROUND

This study aimed to investigate the associations of circulating long, non-coding (lncRNA) IFNG-AS1, lncRNA ANRIL and lncRNA ITSN1 relative expressions with disease risk, severity and inflammatory cytokines levels in coronary artery disease (CAD) patients.

METHODS

One hundred and ninety-one patients suspected of CAD who underwent coronary angiography were consecutively enrolled in this casecontrol study, and divided into CAD patients (N = 102) and controls (N = 89) according to coronary angiographic results. Blood samples of all participants were collected. Plasma lncRNA IFNG-AS1, lncRNA ANRIL and lncRNA ITSN1 expressions were detected using quantitative polymerase chain reaction (qPCR). Serum tumor necrosis factor-α (TNF-α), interleukin (IL)-1β (IL-1β), IL-6, IL-8, IL-10, and IL-17 were assessed using enzyme-linked immunosorbent assay (ELISA). Gensini Score was used to evaluate the disease severity of CAD patients.

RESULTS

LncRNA IFNG-AS1 relative expression in CAD patients was upregulated compared with that in controls (P < .001), and the receiver operating characteristic (ROC) curve showed that the area under curve (AUC) of lncRNA-IFNG-AS1 for predicting the risk of CAD was 0.755 (95% CI: 0.688-0.821). lncRNA IFNG-AS1 relative expression was remarkably associated with Gensini Score (r = .259, P = .009). Additionally, lncRNA IFNG-AS1 relative expression was positively associated with high-sensitivity C-reactive protein (hs-CRP) (r = .283, P = .004), TNF-α (r = .269, P = .006), and IL-6 levels (r = .425, P < .001), while it was negatively correlated with IL-10 level (r = -.263, P = .008). lncRNA ANRIL or lncRNA ITSN1 was not correlated with CA D risk, Gensini Score, hs-CRP, ESR, TNF-α, IL-1β, IL-6, IL-8, IL-10, or IL-17 levels (all P > .05).

CONCLUSION

Circulating lncRNA IFNG-AS1 expression correlates with increased disease risk, higher disease severity and elevated inflammation in CAD patients.