Characterization of LncRNA expression profile and identification of novel LncRNA biomarkers to diagnose coronary artery disease

Clinical value of BRE-AS1 in myocardial infarction and its role in myocardial infarction-induced cardiac muscle cell apoptosis

Objectives. The aim of this study was to investigate the expression of long non-coding RNA (lncRNA) brain and reproductive organ-expressed protein (BRE) antisense RNA 1 (BRE-AS1) in patients with acute myocardial infarction (AMI) and its effect on ischemia/reperfusion (I/R)-induced oxidative stress and apoptosis of cardiomyocytes. Methods. Serum BRE-AS1 levels in patients with AMI was detected using quantitative real-time polymerase chain reaction (qRT-PCR). The diagnostic and prognostic values of BRE-AS1 were evaluated. H9c2 cells were treated with hypoxia/reoxygenation to establish an in vitro myocardial infarction cell model. The levels of inflammatory cytokines such as tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and IL-6 were detected by enzyme-linked immunosorbent assay (ELISA). Levels of lactate dehydrogenase (LDH), malondialdehyde (MDA), superoxide dismutase (SOD), and glutathione peroxidase (GSH-Px) were determined by commercial kits. Cell counting kit-8 (CCK-8) and flow cytometry were used to evaluate the cell viability and cell apoptosis. Results. The expression of BRE-AS1 in serum of patients with AMI is upregulated, which shows the clinical diagnostic value for AMI. In the I/R injury cell model, the knockout of BRE-AS1 can significantly alleviate the increase in TNF-α, IL-1β, and IL-6 levels, inhibit the production of LDH and MDA, increase the activities of SOD and GSH-Px, promote the cell viability and suppress cell apoptosis. Conclusions. Abnormally elevated BRE-AS1 has a high diagnostic value for AMI as well as a prognostic value for major adverse cardiovascular events (MACEs). The elevation of BRE-AS1 promoted oxidative stress injury and cell apoptosis in vitro.

Circulating long noncoding RNA PDE4DIPP6: A novel biomarker for improving the clinical management of non-ST-segment elevation myocardial infarction

BACKGROUND

Long noncoding RNAs (lncRNAs) have emerged as promising diagnostic biomarkers. Here, we investigated the cardiac-expressed and plasma-detectable lncRNA PDE4DIPP6 as a biomarker for non-ST-segment elevation myocardial infarction (NSTEMI), specifically assessing its potential to enhance the diagnostic efficacy of high-sensitivity cardiac troponin (hs-cTnT).

METHODS AND RESULTS

The study enrolled individuals presenting with suspected acute coronary syndrome (ACS). LncRNA quantification was performed in plasma samples using RT-qPCR. The discriminatory performance was assessed by calculating the Area Under the Curve (AUC). Reclassification metrics, including the Integrated Discrimination Improvement (IDI) and Net Reclassification Improvement (NRI) indexes, were utilized to evaluate enhancements in diagnostic accuracy. Among the 252 patients with suspected ACS, 50.8 % were diagnosed with ACS, and 13.9 % with NSTEMI. Initially, the association of lncRNA PDE4DIPP6 with ACS was investigated. Elevated levels of this lncRNA were observed in ACS patients compared to non-ACS subjects. No association was found between lncRNA PDE4DIPP6 levels and potential confounding factors, nor was a significant correlation with hs-cTnT levels (rho = 0.071). The inclusion of lncRNA PDE4DIPP6 on top of hs-cTnT significantly improved the discrimination and classification of ACS patients, as reflected by an enhanced AUC of 0.734, an IDI of 0.066 and NRI of 0.471. Subsequently, the lncRNA PDE4DIPP6 was evaluated as biomarker of NSTEMI. Elevated levels of the lncRNA were observed in NSTEMI patients compared to patients without NSTEMI. Consistent with previous findings, the addition of lncRNA PDE4DIPP6 to hs-cTnT improved the discrimination and classification of patients, increasing the AUC from 0.859 to 0.944, with an IDI of 0.237 and NRI of 0.658.

CONCLUSION

LncRNA PDE4DIPP6 offers additional diagnostic insights beyond hs-cTnT, suggesting its potential to improve the clinical management of patients with NSTEMI.

Beyond the silence: A comprehensive exploration of long non-coding RNAs as genetic whispers and their essential regulatory functions in cardiovascular disorders

Long non-coding RNAs (lncRNAs) are RNA molecules that regulate gene expression at several levels, including transcriptional, post-transcriptional, and translational. They have a length of more than 200 nucleotides and cannot code. Many human diseases have been linked to aberrant lncRNA expression, highlighting the need for a better knowledge of disease etiology to drive improvements in diagnostic, prognostic, and therapeutic methods. Cardiovascular diseases (CVDs) are one of the leading causes of death worldwide. LncRNAs play an essential role in the complex process of heart formation, and their abnormalities have been associated with several CVDs. This Review article looks at the roles and relationships of long non-coding RNAs (lncRNAs) in a wide range of CVDs, such as heart failure, myocardial infarction, atherosclerosis, and cardiac hypertrophy. In addition, the review delves into the possible uses of lncRNAs in diagnostics, prognosis, and clinical treatments of cardiovascular diseases. Additionally, it considers the field's future prospects while examining how lncRNAs might be altered and its clinical applications.

LncRNA/CircRNA-miRNA-mRNA Axis in Atherosclerotic Inflammation: Research Progress

Atherosclerosis is characterized by chronic inflammation of the arterial wall. However, the exact mechanism underlying atherosclerosis-related inflammation has not been fully elucidated. To gain insight into the mechanisms underlying the inflammatory process that leads to atherosclerosis, there is need to identify novel molecular markers. Non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-protein-coding RNAs (lncRNAs) and circular RNAs (circRNAs) have gained prominence in recent years. LncRNAs/circRNAs act as competing endogenous RNAs (ceRNAs) that bind to miRNAs via microRNA response elements (MREs), thereby inhibiting the silencing of miRNA target mRNAs. Inflammatory mediators and inflammatory signaling pathways are closely regulated by ceRNA regulatory networks in atherosclerosis. In this review, we discuss the role of LncRNA/CircRNA-miRNA-mRNA axis in atherosclerotic inflammation and how it can be targeted for early clinical detection and treatment.

Protein Tyrosine Phosphatase SHP2 in Macrophages Acts as an Antiatherosclerotic Regulator in Mice

BACKGROUND

Macrophages have versatile roles in atherosclerosis. SHP2 (Src homology 2 containing protein tyrosine phosphatase 2) has been demonstrated to play a critical role in regulating macrophage activation. However, the mechanism of SHP2 regulation of macrophage function in an atherosclerotic microenvironment remains unknown.

METHODS

APOE (apolipoprotein E) or LDLR (low-density lipoprotein receptor) null mice treated with SHP099 were fed a Western diet for 8 weeks, while Shp2MKO:ApoE-/- or Shp2MKO:Ldlr-/- mice and exo-AAV8-SHP2E76K/ApoE-/- mice were fed a Western diet for 12 weeks. In vitro, levels of proinflammatory factors and phagocytic function were then studied in mouse peritoneal macrophages. RNA sequencing was used to identify PPARγ (peroxisome proliferative activated receptor γ) as the key downstream molecule. A PPARγ agonist was used to rescue the phenotypes observed in SHP2-deleted mice.

RESULTS

Pharmacological inhibition and selective deletion in macrophages of SHP2 aggravated atherosclerosis in APOE and LDLR null mice with increased plaque macrophages and apoptotic cells. In vitro, SHP2 deficiency in APOE and LDLR null macrophages enhanced proinflammatory polarization and its efferocytosis was dramatically impaired. Conversely, the expression of gain-of-function mutation of SHP2 in mouse macrophages reduced atherosclerosis. The SHP2 agonist lovastatin repressesed macrophage inflammatory activation and enhanced efferocytosis. Mechanistically, RNA sequencing analysis identified PPARγ as a key downstream transcription factor. PPARγ was decreased in macrophages upon SHP2 deletion and inhibition. Importantly, PPARγ agonist decreased atherosclerosis in SHP2 knockout mice, restored efferocytotic defects, and reduced inflammatory activation in SHP2 deleted macrophages. PPARγ was decreased by the ubiquitin-mediated degradation upon SHP2 inhibition or deletion. Finally, we found that SHP2 was downregulated in atherosclerotic vessels.

CONCLUSIONS

Overall, SHP2 in macrophages was found to act as an antiatherosclerotic regulator by stabilizing PPARγ in APOE/LDLR null mice.

lncRNA TPRG1-AS1 Screened the Onset of Acute Coronary Syndromes and Predicted Severity and the Occurrence of MACE During Patients' Hospitalization

Purpose

Acute coronary syndrome (ACS) is a common acute myocardial ischemia syndrome and is one of the death-related causes of cardiovascular diseases. Identifying biomarkers to indicate disease severity and predict the occurrence of major adverse cardiovascular events (MACE) would benefit the clinical prognosis of ACS. This study estimated the expression and significance of lncRNA TPRG1-AS1 in the onset and development of ACS, aiming to explore a novel biomarker for the diagnosis and prognosis of ACS.

Patients and Methods

A total of 109 ACS patients and 66 patients who received coronary angiography and excluded ACS were enrolled in this study. TPRG1-AS1 in the serum of study subjects was analyzed by PCR. The significance of TPRG1-AS1 in screening ACS was evaluated by ROC analysis. The association of TPRG1-AS1 with the disease severity of ACS was assessed by Pearson correlation analysis with patients' clinicopathological features. The potential of TPRG1-AS1 in predicting the occurrence of MACE was assessed by logistic regression analysis.

Results

Significant upregulation of TPRG1-AS1 was observed in ACS patients, which served as a risk factor for ACS and distinguish between ACS patients and the normal group. TPRG1-AS1 was positively correlated with Gensini score, cys-C, cTnI, and NT-proBNP levels of ACS patients, which indicate severe development of ACS. Additionally, increasing serum TPRG1-AS1 was associated with the high incidence of MACE during patients' hospitalization and was identified as a risk factor for MACE in ACS patients.

Conclusion

Upregulated TPRG1-AS1 in ACS served as a diagnostic biomarker and predicted the severe development of patients.

Long Non-Coding RNA TUG1 Gene Polymorphism and TUG1 Expression Level as Molecular Biomarkers of Systemic Lupus Erythematosus and Lupus Nephritis

Long non-coding RNA (lncRNA) TUG1 acts as a proto-oncogene, allowing the proliferation of tumor cells, and it has been related to inflammation. Therefore, we aimed in this study to investigate for the first time the role of TUG1 gene polymorphism and the TUG1 level as biomarkers in systemic lupus erythematosus (SLE) and their link to lupus nephritis 145 SLE. A total of 145 healthy controls were subjected to clinical and laboratory evaluation. The disease activity was assessed by the SLE disease activity index (SLEDAI) score. SLE patients were divided into two subgroups according to the presence of lupus nephritis. The TUG1 gene polymorphisms rs5749201 and rs886471 were determined by Sanger sequencing, and TUG1 expression was assessed by qRT-PCR. There was a significant increase in the risk of SLE AA, TA, dominant genotypes, and the A allele of rs5749201 (p < 0.001) by 4.9-, 10.1-, 6.5-, and 2.5-fold in comparison to the relative control. GG and TG, dominant genotypes and the G allele of rs886471 (p < 0.01) increased the risk by 5.09-, 11.9-, 6.5-, and 2.6-fold. AA, A allele, dominant and recessive rs5749201genotypes increased the risk of lupus nephritis by 16.6-, 7.4-, 7.1-, and 12.2-fold, respectively (p < 0.05). GG, dominant and recessive genotypes, and the G allele of rs886471 increased the risk of lupus nephritis by 17.04-, 7.8-, 9.4-, and 6.08-fold, respectively (p < 0.05). Additionally, the AG haplotype increased the risk of SLE and lupus nephritis by 2.7- and 7.8-fold, respectively. The AA rs5749201 and GG rs886471 variants are significantly associated with more severe disease (p < 0.001). TUG1 expression was significantly higher in SLE than in the control and in the lupus nephritis than in non-lupus nephritis cases (p < 0.05). Interestingly, AA rs5749201 and GG rs886471 were significantly associated with higher TUG1 levels (p < 0.001). It was also found that AA rs5749201 and high SLEDAI were predictors of lupus nephritis. Overall, our findings illustrated for the first time that TUG1 gene rs5749201 and rs886471 variants were associated with increased risk of SLE, more severe disease, and lupus nephritis, and the TUG1 level could be used as a diagnostic biomarker of SLE and lupus nephritis.

The Role of Long Non-Coding RNAs in Cardiovascular Diseases

Long non-coding RNAs (lncRNAs) are non-coding RNA molecules longer than 200 nucleotides that regulate gene expression at the transcriptional, post-transcriptional, and translational levels. Abnormal expression of lncRNAs has been identified in many human diseases. Future improvements in diagnostic, prognostic, and therapeutic techniques will be facilitated by a deeper understanding of disease etiology. Cardiovascular diseases (CVDs) are the main cause of death globally. Cardiac development involves lncRNAs, and their abnormalities are linked to many CVDs. This review examines the relationship and function of lncRNA in a variety of CVDs, including atherosclerosis, myocardial infarction, myocardial hypertrophy, and heart failure. Therein, the potential utilization of lncRNAs in clinical diagnostic, prognostic, and therapeutic applications will also be discussed.

Identification and validation of potential hypoxia-related genes associated with coronary artery disease

Introduction: Coronary artery disease (CAD) is one of the most life-threatening cardiovascular emergencies with high mortality and morbidity. Increasing evidence has demonstrated that the degree of hypoxia is closely associated with the development and survival outcomes of CAD patients. However, the role of hypoxia in CAD has not been elucidated. Methods: Based on the GSE113079 microarray dataset and the hypoxia-associated gene collection, differential analysis, machine learning, and validation of the screened hub genes were carried out. Results: In this study, 54 differentially expressed hypoxia-related genes (DE-HRGs), and then 4 hub signature genes (ADM, PPFIA4, FAM162A, and TPBG) were identified based on microarray datasets GSE113079 which including of 93 CAD patients and 48 healthy controls and hypoxia-related gene set. Then, 4 hub genes were also validated in other three CAD related microarray datasets. Through GO and KEGG pathway enrichment analyses, we found three upregulated hub genes (ADM, PPFIA4, TPBG) were strongly correlated with differentially expressed metabolic genes and all the 4 hub genes were mainly enriched in many immune-related biological processes and pathways in CAD. Additionally, 10 immune cell types were found significantly different between the CAD and control groups, especially CD8 T cells, which were apparently essential in cardiovascular disease by immune cell infiltration analysis. Furthermore, we compared the expression of 4 hub genes in 15 cell subtypes in CAD coronary lesions and found that ADM, FAM162A and TPBG were all expressed at higher levels in endothelial cells by single-cell sequencing analysis. Discussion: The study identified four hypoxia genes associated with coronary heart disease. The findings provide more insights into the hypoxia landscape and, potentially, the therapeutic targets of CAD.

LncRNA CASC11 upregulation promotes HDAC4 to alleviate oxidized low-density lipoprotein-induced injury of cardiac microvascular endothelial cells

Long noncoding RNAs (LncRNAs) are essential to regulate the pathogenesis of coronary artery disease (CAD). This study was conducted to analyze the functionality of long noncoding RNA cancer susceptibility candidate 11 (lncRNA CASC11) in oxidized low-density lipoprotein (ox-LDL)-induced injury of cardiac microvascular endothelial cells (CMECs). CMECs were treated with ox-LDL to induce the CAD cell model. The cellular expression levels of CASC11 and histone deacetylase 4 (HDAC4) were determined by real-time quantitative polymerase chain reaction or Western blot assay. Cell absorbance, apoptosis, angiogenesis, and inflammation were evaluated by cell counting kit-8, flow cytometry, tube formation, and enzyme-linked immunosorbent assays. The subcellular localization of CASC11 was examined by the nuclear/cytoplasmic fractionation assay. The binding of human antigen R (HuR) to CASC11 and HDAC4 was analyzed by RNA immunoprecipitation. HDAC4 stability was determined after actinomycin D treatment. CASC11 was found to be decreased in the CAD cell model. CASC11 upregulation increased cell viability and angiogenesis and reduced apoptosis and inflammation. CASC11 bound to HuR and improved HDAC4 expression. HDAC4 downregulation counteracted the protective role of CASC11 overexpression in CMECs. In summary, CASC11 alleviated ox-LDL-induced injury of CMECs by binding to HuR and stabilizing HDAC4.

Long non-coding RNA in coronary artery disease: the role of PDXDC1-AS1 and SFI1-AS1

This study investigates the interaction between long non-coding RNAs (lncRNAs) and metabolic risk factors that contribute to coronary artery disease (CAD). A total transcriptome high throughput sequencing study was conducted on peripheral blood mononuclear cells from five patients with CAD and five healthy controls. Validation assay by qRT-PCR was conducted among 270 patients and 47 controls. Finally, to evaluate the lncRNAs' diagnostic value for CAD, the Spearman correlation test and receiver operating characteristic curve (ROC) analysis were utilized. Additionally, univariate and multivariate logistic regression along with crossover analyses were conducted to identify the interaction between lncRNA and environmental risk factors. A total of 2149 of 26,027 lncRNAs identified by RNA sequencing were differentially expressed in CAD patients compared to controls. Validation by qRT-PCR showed significantly different relative expression levels for lncRNAs PDXDC1-AS1, SFI1-AS1, RP13-143G15.3, DAPK1-IT1, PPIE-AS1, and RP11-362A1.1 between the two groups (all P<0.05). The area under the ROC values of PDXDC1-AS1 and SFI1-AS1 is 0.645 (sensitivity=0.443 and specificity=0.920) and 0.629 (sensitivity=0.571 and specificity=0.909), especially. Multivariate logistic regression analyses showed that lncRNAs PDXDC1-AS1 (OR=2.285, 95%CI=1.390-3.754, p=0.001) and SFI1-AS1 (OR=1.163, 95%CI=1.163-2.264, p=0.004) were protective factors against CAD. Under the additive model, cross-over analyses demonstrated significant interactions between lncRNAs PDXDC1-AS1 and smoking in relation to CAD risk (S=3.871, 95%CI=1.140-6.599). PDXDC1-AS1 and SFI1-AS1 were sensitive and specific biomarkers for CAD and exhibited synergistic effects with certain environmental factors. These results highlighted their potential use as CAD diagnostic biomarkers for future research.

Long Noncoding RNA AC078850.1 Induces NLRP3 Inflammasome-Mediated Pyroptosis in Atherosclerosis by Upregulating ITGB2 Transcription via Transcription Factor HIF-1α

As a chronic progressive inflammatory disease, atherosclerosis constitutes a leading cause of cardiovascular disease, with high mortality and morbidity worldwide. The effect of lncRNA AC078850.1 in atherosclerosis is unknown; this study aims to explore the regulatory mechanism of the lncRNA AC078850.1/HIF-1α complex in atherosclerosis. Initially, we identified the lncRNA AC078850.1 associated with atherosclerosis using multiple bioinformatic methods, finding that the level of lncRNA AC078850.1 in peripheral blood mononuclear cells was positively related to the severity of carotid atherosclerosis. LncRNA AC078850.1 was upregulated, and found to be predominately localized in the nucleus of THP-1 macrophage-derived foam cells. Both the knockdown of lncRNA AC078850.1 and the transcription factor HIF-1α can each markedly suppress ITGB2 gene transcription, ROS production, NLRP3 inflammasome, IL-1β/18 release, lipid accumulation, and pyroptotic cell death in ox-LDL-stimulated THP-1-derived macrophages. Additionally, the downregulation of HIF-1α attenuated the positive effects of lncRNA AC078850.1 on pyroptosis and foam cell formation. In addition, the knockdown of lncRNA AC078850.1 suppressed HIF-1α-aggravated macrophages pyroptosis and foam cell formation. Meanwhile, inhibition of ITGB2 gene expression ameliorated HIF-1α-aggravated ROS generation in THP-1-derived macrophages. Taken together, our study demonstrated that lncRNA AC078850.1 was involved in the regulation of ITGB2 gene transcription by binding to the HIF-1α and lncRNA AC078850.1/HIF-1α complex, promoting both NLRP3 inflammasome-mediated pyroptosis and foam cell formation through the ROS-dependent pathway in cases of atherosclerosis.

NONHSAT098487.2 protects cardiomyocytes from oxidative stress injury by regulating the Notch pathway

Acute myocardial infarction has increasingly become a global health problem and is a primary cause of cardiovascular disease-related death. Although long noncoding RNAs have been reported to play an important role in various cardiovascular diseases, their protective effects on cardiomyocytes against reactive oxygen species-induced oxidative injury have nonetheless been poorly studied. The present study aims to explore the effect of a novel long noncoding RNA, NONHSAT098487.2, on cardiomyocyte injury induced by H2O2. The expression of NONHSAT098487.2 and pathway-related genes was evaluated by quantitative real-time polymerase chain reaction. Cell viability, release of lactate dehydrogenase, and apoptosis levels were detected by cell counting kit-8, lactate dehydrogenase release assay, and flow cytometry analysis, respectively. The protein levels were estimated by western blotting. The results showed that NONHSAT098487.2 was expressed at a high level in peripheral blood mononuclear cells from acute myocardial infarction patients, which showed a positive correlation with the HS-TnT and CK-MB levels of patients. Furthermore, it is also upregulated in human AC16 cardiomyocytes treated with H2O2 or exposed to hypoxia/reoxygenation conditions. Knockdown of NONHSAT098487.2 restrained the Notch signalling pathway and aggravated H2O2-induced cardiomyocyte oxidative stress injury. In contrast, overexpression of NONHSAT098487.2 activated the Notch signalling pathway and suppressed H2O2-induced oxidative stress injury. However, the Notch inhibitor DAPT weakened the protective effects of NONHSAT098487.2. Therefore, the novel lncRNA NONHSAT098487.2 may play a role in protecting cardiomyocytes from oxidative stress injury by regulating the Notch pathway.

SLC26A4-AS1 Aggravates AngII-induced Cardiac Hypertrophy by Enhancing SLC26A4 Expression

BACKGROUND

It has been reported that solute carrier family 26 members 4 antisense RNA 1 (SLC26A4-AS1) is highly related to cardiac hypertrophy.

OBJECTIVE

This research aims to investigate the role and specific mechanism of SLC26A4-AS1 in cardiac hypertrophy, providing a novel marker for cardiac hypertrophy treatment.

METHODS

Angiotensin II (AngII) was infused into neonatal mouse ventricular cardiomyocytes (NMVCs) to induce cardiac hypertrophy. Gene expression was detected by quantitative real-time PCR (RT-qPCR). Protein levels were evaluated via western blot. Functional assays analyzed the role of SLC26A4-AS1. The mechanism of SLC26A4-AS1 was assessed by RNA-binding protein immunoprecipitation (RIP), RNA pull-down, and luciferase reporter assays. The P value <0.05 was identified as statistical significance. Student's t-test evaluated the two-group comparison. The difference between different groups was analyzed by one-way analysis of variance (ANOVA).

RESULTS

SLC26A4-AS1 is upregulated in AngII-treated NMVCs and promotes AngII-induced cardiac hypertrophy. SLC26A4-AS1 regulates its nearby gene solute carrier family 26 members 4 (SLC26A4) via functioning as a competing endogenous RNA (ceRNA) to modulate the microRNA (miR)-301a-3p and miR-301b-3p in NMVCs. SLC26A4-AS1 promotes AngII-induced cardiac hypertrophy via upregulating SLC26A4 or sponging miR-301a-3p/miR-301b-3p.

CONCLUSION

SLC26A4-AS1 aggravates AngII-induced cardiac hypertrophy via sponging miR-301a-3p or miR-301b-3p to enhance SLC26A4 expression.

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.

Discovery of Transacting Long Noncoding RNAs That Regulate Smooth Muscle Cell Phenotype

BACKGROUND

Smooth muscle cells (SMC), the major cell type in atherosclerotic plaques, are vital in coronary artery diseases (CADs). SMC phenotypic transition, which leads to the formation of various cell types in atherosclerotic plaques, is regulated by a network of genetic and epigenetic mechanisms and governs the risk of disease. The involvement of long noncoding RNAs (lncRNAs) has been increasingly identified in cardiovascular disease. However, SMC lncRNAs have not been comprehensively characterized, and their regulatory role in SMC state transition remains unknown.

METHODS

A discovery pipeline was constructed and applied to deeply strand-specific RNA sequencing from perturbed human coronary artery SMC with different disease-related stimuli, to allow for the detection of novel lncRNAs. The functional relevance of a select few novel lncRNAs were verified in vitro.

RESULTS

We identified 4579 known and 13 655 de novo lncRNAs in human coronary artery SMC. Consistent with previous long noncoding RNA studies, these lncRNAs overall have fewer exons, are shorter in length than protein-coding genes (pcGenes), and have relatively low expression level. Genomic location of these long noncoding RNA is disproportionately enriched near CAD-related TFs (transcription factors), genetic loci, and gene regulators of SMC identity, suggesting the importance of their function in disease. Two de novo lncRNAs, ZIPPOR (ZEB-interacting suppressor) and TNS1-AS2 (TNS1-antisense 2), were identified by our screen. Combining transcriptional data and in silico modeling along with in vitro validation, we identified CAD gene ZEB2 as a target through which these lncRNAs exert their function in SMC phenotypic transition.

CONCLUSIONS

Expression of a large and diverse set of lncRNAs in human coronary artery SMC are highly dynamic in response to CAD-related stimuli. The dynamic changes in expression of these lncRNAs correspond to alterations in transcriptional programs that are relevant to CAD, suggesting a critical role for lncRNAs in SMC phenotypic transition and human atherosclerotic disease.

Non-coding RNAs as biomarkers of myocardial infarction

Non-coding RNAs (ncRNAs) encompass a family of ubiquitous RNA molecules that lack protein-coding potential and have tissue-specific expression. A significant body of evidence indicates that ncRNA's aberrant expression plays a critical role in disease onset and development. NcRNAs' biochemical characteristics such as disease-associated concentration changes, structural stability, and high abundance in body fluids make them promising prognostic and diagnostic biomarkers. Myocardial infarction (MI) is a leading cause of mortality worldwide. Acute myocardial infarction (AMI), the term in use to describe MI's early phase, is generally diagnosed by physical examination, electrocardiogram (ECG), and the presence of specific biomarkers. In this regard, compared to standard MI biomarkers, such as the cardiac troponin isoforms (cTnT & cTnI) and the Creatinine Kinase (CK), ncRNAs appears to provide better sensitivity and specificity, ensuring a rapid and correct diagnosis, an earlier treatment, and consequently a good prognosis for the patients. This review aims to summarize and discuss the most promising and recent data on the potential clinical use of circulating ncRNAs as MI biomarkers. Specifically, we focused primarily on miRNAs and lncRNAs, highlighting their significant specificity and sensitivity, discussing their limitations, and suggesting possible overcoming approaches.

LncRNA PEG11as aggravates cerebral ischemia/reperfusion injury after ischemic stroke through miR-342-5p/PFN1 axis

AIM

LncRNAs are highly expressed in the CNS and regulate pathophysiological processes. However, the potential role of lncRNAs inischemic stroke (IS) remains unknown. In this study, we investigated the functions and possible molecular mechanism of lncRNA paternal expressed gene 11 antisense (PEG11as) in this process.

METHODS

Middle cerebral artery occlusion/reperfusion (MCAO/R) mice model and N2a cells model from oxygen-glucose deprivation/reoxygenation (OGD/R) were used to simulate cerebral I/R in vivo and in vitro. High-throughput sequencing (RNA-Seq) was used todetect differential expression of lncRNAs in cerebral I/R. QRT-PCR was used to detect the expression of PEG11as and miR-342-5p. Bioinformatics analysis, FISH, luciferase reporter assay, RIP, Western blot, and immunofluorescence were used to detect the interaction between PEG11as, miR-342-5p and PFN1. The effect on neuronal apoptosis was analyzed using loss-of-function combined with TUNEL, Hoechst, and caspase3 activity assays.

KEY FINDINGS

254 lncRNAs were differentially expressed in MCAO1h/R6h mice. Among them, PEG11as was significantly up-regulated. PEG11as down-regulated could markedly attenuate the brain infarct volume, alleviate neurological deficit in vivo, and effectively promote neuron survival, attenuate neuronal apoptosis both in vivo and in vitro. FISH assay discovered that PEG11as was mainly located in the cytoplasm. Furthermore, we demonstrated that PEG11as was able to bind miR-342-5p to inhibit miR-342-5p activity, whereas the down-regulated of miR-342-5p resulted in profilin 1 (PFN1) overexpression and thus promoting apoptosis.

SIGNIFICANCE

This study suggests that PEG11as regulates neuronal apoptosis by miR-342-5p/PFN1 axis, which may contribute to our understanding of pathogenesis and provide a potential therapeutic option for cerebral I/R.

Transcriptome analysis reveals potential marker genes for diagnosis of Alzheimer's disease and vascular dementia

Alzheimer's disease (AD) and vascular dementia (VD) are the two most common forms of dementia, share similar symptoms, and are sometimes difficult to distinguish. To investigate the potential mechanisms by which they differ, we identified differentially expressed genes in blood and brain samples from patients with these diseases, and performed weighted gene co-expression network analysis and other bioinformatics analyses. Weighted gene co-expression network analysis resulted in mining of different modules based on differences in gene expression between these two diseases. Enrichment analysis and generation of a protein-protein interaction network were used to identify core pathways for each disease. Modules were significantly involved in cAMP and AMPK signaling pathway, which may be regulated cell death in AD and VD. Genes of cAMP and neurotrophin signaling pathways, including ATP1A3, PP2A, NCEH1, ITPR1, CAMKK2, and HDAC1, were identified as key markers. Using the least absolute shrinkage and selection operator method, a diagnostic model for AD and VD was generated and verified through analysis of gene expression in blood of patients. Furthermore, single sample gene set enrichment analysis was used to characterize immune cell infiltration into brain tissue. That results showed that infiltration of DCs and pDCs cells was increased, and infiltration of B cells and TFH cells was decreased in the brain tissues of patients with AD and VD. In summary, classification based on target genes showed good diagnostic efficiency, and filled the gap in the diagnostic field or optimizes the existing diagnostic model, which could be used to distinguish between AD and VD.

Long Noncoding RNA TPRG1-AS1 Suppresses Migration of Vascular Smooth Muscle Cells and Attenuates Atherogenesis via Interacting With MYH9 Protein

BACKGROUND

Migration of human aortic smooth muscle cells (HASMCs) contributes to the pathogenesis of atherosclerosis. This study aims to functionally characterize long noncoding RNA TPRG1-AS1 (tumor protein p63 regulated 1, antisense 1) in HASMCs and reveal the underlying mechanism of TPRG1-AS1 in HASMCs migration, neointima formation, and subsequent atherosclerosis.

METHODS

The expression of TPRG1-AS1 in atherosclerotic plaques was verified a series of in silico analysis and quantitative real-time polymerase chain reaction analysis. Northern blot, rapid amplification of cDNA ends and Sanger sequencing were used to determine its full length. In vitro transcription-translation assay was used to investigate the protein-coding capacity of TPRG1-AS1. RNA fluorescent in situ hybridization was used to confirm its subcellular localization. Loss- and gain-of-function studies were used to investigate the function of TPRG1-AS1. Furthermore, the effect of TPRG1-AS1 on the pathological response was evaluated in carotid balloon injury model, wire injury model, and atherosclerosis model, respectively.

RESULTS

TPRG1-AS1 was significantly increased in atherosclerotic plaques. TPRG1-AS1 did not encode any proteins and its full length was 1279nt, which was bona fide a long noncoding RNA. TPRG1-AS1 was mainly localized in cytoplasmic and perinuclear regions in HASMCs. TPRG1-AS1 directly interacted with MYH9 (myosin heavy chain 9) protein in HASMCs, promoted MYH9 protein degradation through the proteasome pathway, hindered F-actin stress fiber formation, and finally inhibited HASMCs migration. Vascular smooth muscle cell-specific transgenic overexpression of TPRG1-AS1 significantly reduced neointima formation, and attenuated atherosclerosis in apolipoprotein E knockout (Apoe^-/-) mice.

CONCLUSIONS

This study demonstrated that TPRG1-AS1 inhibited HASMCs migration through interacting with MYH9 protein and consequently suppressed neointima formation and atherosclerosis.

Coronary artery disease risk factors affected by RNA modification-related genetic variants

Background

Single nucleotide polymorphisms that affect RNA modification (RNAm-SNPs) may have functional roles in coronary artery disease (CAD). The aim of this study was to identify RNAm-SNPs in CAD susceptibility loci and highlight potential risk factors.

Methods

CAD-associated RNAm-SNPs were identified in the CARDIoGRAMplusC4D and UK Biobank genome-wide association studies. Gene expression and circulating protein levels affected by the RNAm-SNPs were identified by QTL analyses. Cell experiments and Mendelian randomization (MR) methods were applied to test whether the gene expression levels were associated with CAD.

Results

We identified 81 RNAm-SNPs that were associated with CAD or acute myocardial infarction (AMI), including m6A-, m1A-, m5C-, A-to-I- and m7G-related SNPs. The m6A-SNPs rs3739998 in JCAD, rs148172130 in RPL14 and rs12190287 in TCF21 and the m7G-SNP rs186643756 in PVT1 were genome-wide significant. The RNAm-SNPs were associated with gene expression (e.g., MRAS, DHX36, TCF21, JCAD and SH2B3), and the expression levels were associated with CAD. Differential m6A methylation and differential expression in FTO-overexpressing human aorta smooth muscle cells and peripheral blood mononuclear cells of CAD patients and controls were detected. The RNAm-SNPs were associated with circulating levels of proteins with specific biological functions, such as blood coagulation, and the proteins (e.g., cardiotrophin-1) were confirmed to be associated with CAD and AMI in MR analyses.

Conclusion

The present study identified RNAm-SNPs in CAD susceptibility genes, gene expression and circulating proteins as risk factors for CAD and suggested that RNA modification may play a role in the pathogenesis of CAD.

Knockdown of lncRNA H19 alleviates ox-LDL-induced HCAECs inflammation and injury by mediating miR-20a-5p/HDAC4 axis

BACKGROUND

Coronary artery disease (CAD) seriously disturbs the life of people. LncRNA H19 is reported to promote the progression of CAD; Nevertheless, the detailed mechanism by which H19 modulates CAD development is unclear.

METHODS

Clinical samples of CAD patients were collected, meanwhile we established in vitro and in vivo models of CAD by treating HCAECs with ox-LDL and feeding ApoE^-/- mice with high fat diets (HFD). MTT assay was adopted to assess the cell viability. Transwell detection was applied to test the migration, and apoptosis was tested by flow cytometry. The levels of inflammatory cytokines were examined by ELISA. The relation among H19, miR-20a-5p and HDAC4 was explored by dual luciferase reporter and RIP assay.

RESULTS

H19 and HDAC4 levels were elevated, while miR-20a-5p was reduced in plasma of CAD patients and ox-LDL-treated HCAECs. ox-LDL increased H19 level and induced apoptosis and inflammation in HCAECs, while silencing of H19 rescued this phenomenon. In addition, the level of H19 was negatively correlated with miR-20a-5p, and miR-20a-5p inhibitor restored the effect of H19 silencing on HCAECs function. HDAC4 was the downstream mRNA of miR-20a-5p, and miR-20a-5p upregulation reversed ox-LDL-induced HCAECs injury through targeting HDAC4. Furthermore, H19 silencing significantly alleviated the coronary atherosclerotic plaques and inhibited the inflammatory responses in vivo.

CONCLUSIONS

We proved that knockdown of H19 alleviated ox-LDL-induced HCAECs injury via miR-20a-5p/HDAC4 axis, which might provide a new tactics against CAD.

DYSF promotes monocyte activation in atherosclerotic cardiovascular disease as a DNA methylation-driven gene

Dysferlin (DYSF) has drawn much attention due to its involvement in dysferlinopathy and was reported to affect monocyte functions in recent studies. However, the role of DYSF in the pathogenesis of atherosclerotic cardiovascular diseases (ASCVD) and the regulation mechanism of DYSF expression have not been fully studied. In this study, Gene Expression Omnibus (GEO) database and epigenome-wide association study (EWAS) literatures were searched to find the DNA methylation-driven genes (including DYSF) of ASCVD. The hub genes related to DYSF were also identified through weighted correlation network analysis (WGCNA). Regulation of DYSF expression through its promoter methylation status was verified using peripheral blood leucocytes (PBLs) from ASCVD patients and normal controls, and experiments on THP1 cells and Apoe^-/- mice. Similarly, the expressions of DYSF related hub genes, mainly contained SELL, STAT3 and TMX1, were also validated. DYSF functions were then evaluated by phagocytosis, transwell and adhesion assays in DYSF knock-down and overexpressed THP1 cells. The results showed that DYSF promoter hypermethylation up-regulated its expression in clinical samples, THP1 cells and Apoe^-/- mice, confirming DYSF as a DNA methylation-driven gene. The combination of DYSF expression and methylation status in PBLs had a considerable prediction value for ASCVD. Besides, DYSF could enhance the phagocytosis, migration and adhesion ability of THP1 cells. Among DYSF related hub genes, SELL was proven to be the downstream target of DYSF by wet experiments. In conclusion, DYSF promoter hypermethylation upregulated its expression and promoted monocytes activation, which further participated in the pathogenesis of ASCVD.

Identification of circulating lncRNA in chronic kidney disease based on bioinformatics analysis

Chronic kidney disease (CKD) is a high mortality disease and generally remains asymptomatic in the early stages. Long non-coding RNA (lncRNA) is defined as a non-protein-coding transcript more than 200 nucleotides which participate in numerous biological processes and have been identified as novel diagnostic markers for many diseases. Detection of circulating lncRNAs is a rapidly evolving, new area of molecular diagnosis. The purpose of our research was to identify circulating lncRNA expression profiles and possible molecular mechanisms involved in CKD. Blood samples were obtained from patients with CKD and healthy volunteers, and high-throughput sequencing was performed to identify differentially expressed (DE) lncRNAs and mRNAs. DE lncRNAs and mRNAs in peripheral blood mononuclear cells (PBMCs) were confirmed by quantitative reverse transcription polymerase chain reaction (qRT-PCR) to ensure the reliability and validity of RNA-seq data. Bioinformatics analysis was used to obtain biological functions and key pathways related to the pathogenesis of CKD. The interaction and co-expression functional networks for DE lncRNAs and mRNAs were also constructed. Our data showed that of the 425 DE lncRNAs detected, 196 lncRNAs were upregulated, while that of 229 lncRNAs were downregulated. A total of 433 DE mRNAs were identified in patients with CKD compared to healthy individuals. GO analysis revealed that DE lncRNAs were highly correlated with binding and pathway regulation. KEGG analysis suggested that DE lncRNAs were obviously enriched in regulatory pathways, such as antigen processing and presentation. We successfully constructed a potential DE lncRNA-mRNA co-expression network and analyzed the target genes of DE lncRNAs to predict cis- and trans-regulation in CKD. 100 lncRNAs that corresponded to 14 transcription factors (TFs) were identified in the TF-lncRNA binary network. Our findings on the lncRNA expression profiles and functional networks may help to interpret the possible molecular mechanisms implied in the pathogenesis of CKD; the results demonstrated that lncRNAs could potentially to be used as diagnostic biomarkers in CKD.

Transcriptomic Analyses Reveal Long Non-Coding RNA in Peripheral Blood Mononuclear Cells as a Novel Biomarker for Diagnosis and Prognosis of Hepatocellular Carcinoma

Novel biomarkers are highly required for the diagnosis and predicting prognosis of hepatocellular carcinoma (HCC). In this study, we investigated the profiles of long non-coding RNAs (lncRNAs) obtained from the peripheral blood mononuclear cells (PBMCs) of patients with HCC and PBMCs from a co-culture model using transcriptomic analysis. The differentially expressed lncRNAs (DElncRNAs) were then characterized and integrated as cancer-induced lncRNAs. Among them, three up-regulating DElncRNAs including MIR4435-2HG, SNHG9 and lnc-LCP2-1 and one down-regulating, lnc-POLD3-2, were identified. The functional analysis showed that these enriched lncRNAs were mainly associated with carcinogenesis and immune responses. Following further validation in PBMCs samples (100 HBV-related HCC, 100 chronic hepatitis B and 100 healthy controls), MIR4435-2HG, lnc-POLD3-2 and their combination were revealed to be sensitive biomarkers in discriminating HCC from non-HCC (AUROC = 0.78, 0.80, and 0.87, respectively), particularly among individuals with normal serum alpha-fetoprotein levels. Additionally, high circulating SNHG9 expression was shown to be an independent prognostic factor of overall survival in patients with HCC. These results indicate that determining these lncRNAs in PBMCs could serve as novel diagnostic and prognostic biomarkers for HBV-related HCC.

Upregulation of the Long Non-coding RNA LINC01480 Is Associated With Immune Infiltration in Coronary Artery Disease Based on an Immune-Related lncRNA-mRNA Co-expression Network

Coronary artery disease (CAD) is considered one of the leading causes of death worldwide. Although dysregulation of long non-coding RNAs (lncRNAs) has been reported to be associated with the initiation and progression of CAD, the knowledge regarding their specific functions as well their physiological/pathological significance in CAD is very limited. In this study, we aimed to systematically analyze immune-related lncRNAs in CAD and explore the relationship between key immune-related lncRNAs and the immune cell infiltration process. Based on differential expression analysis of mRNAs and lncRNAs, an immune-related lncRNA-mRNA weighted gene co-expression network containing 377 lncRNAs and 119 mRNAs was constructed. LINC01480 and AL359237.1 were identified as the hub immune-related lncRNAs in CAD using the random forest-recursive feature elimination and least absolute shrinkage and selection operator logistic regression. Furthermore, 93 CAD samples were divided into two subgroups according to the expression values of LINC01480 and AL359237.1 by consensus clustering analysis. By performing gene set enrichment analysis, we found that cluster 2 enriched more cardiovascular risk pathways than cluster 1. The immune cell infiltration analysis of ischemic cardiomyopathy (ICM; an advanced stage of CAD) samples revealed that the proportion of macrophage M2 was upregulated in the LINC01480 highly expressed samples, thus suggesting that LINC01480 plays a protective role in the progression of ICM. Based on the findings of this study, lncRNA LINC01480 may be used as a novel biomarker and therapeutic target for CAD.

Epithelial-mesenchymal transition-related genes in coronary artery disease

Epithelial-mesenchymal transition (EMT) is critical in the development of coronary artery disease (CAD). However, landscapes of EMT-related genes have not been fully established in CAD. We identified the differentially expressed mRNAs and lncRNAs (DElncRNAs) from the Gene Expression Omnibus database. Pearson’s correlation analysis, the least absolute shrinkage and selection operator regression, and support vector machine reverse feature elimination algorithms were used to screen EMT-related lncRNAs. The cis–trans regulatory networks were constructed based on EMT-related lncRNAs. Quantitative real-time polymerase chain reaction was performed to validate the expression of EMT-related genes in a cohort of six patients with CAD and six healthy controls. We further estimated the infiltration of the immune cells in CAD patients with five algorithms, and the correlation between EMT-related genes and infiltrating immune cells was analyzed. We identified eight EMT-related lncRNAs in CAD. The area under curve value was greater than 0.95. The immune analysis revealed significant CD8 T cells, monocytes, and NK cells in CAD and found that EMT-related lncRNAs were correlated with these immune cell subsets. Moreover, SNAI2, an EMT-TF gene, was found in the trans-regulatory network of EMT-related lncRNAs. Further, we found SNAI2 as a biomarker for the diagnosis of CAD but it also had a close correlation with immune cell subsets in CAD. Eight EMT-related lncRNAs and SNAI2 have important significance in the diagnosis of CAD patients.

LncRNA TARID induces cell proliferation through cell cycle pathway associated with coronary artery disease

BACKGROUND/AIM

Long non-coding RNA TARID (lncRNA TARID) can activate the tumor suppressor TCF21 in tumorigenesis by inducing promoter demethylation. However, the impact on lncRNA TARID and its variants of coronary artery disease (CAD) are poorly understood.

METHODS

We performed a case-control study enrolling 949 cases and 892 controls to assess genotype. Five variants were genotyped by TaqMan assay. 20 cases and 20 controls were used to evaluate the expression of lncRNA TARID. The cell proliferation rate was evaluated by CCK-8. The RT-qPCR and cell cycle analysis were applied to examine cell proliferation-related mRNA and cell distribution.

RESULTS

This study indicated that rs2327433 GG genotype was associated with CAD risk adjusting for traditional risk factors (OR = 2.74, 95%CI: 1.10-6.83, P = 0.03). Our results analyses revealed that the genotype of rs2327433 was related to the proportion of CAD patients with left anterior descending artery disease and left circumflex artery disease (P = 0.025 and P = 0.025, respectively). The results showed that the minor allele frequency of rs2327433 was significantly correlated with the severity of the disease (P = 0.029). The eQTL analysis showed that rs2327433 may affect the transcription factors TCF21 regulated by lncRNA TARID. We found that TARID silencing regulated cell proliferation and altered cell cycle progression by induced upregulation of CDK1 and PCNA.

CONCLUSIONS

SNP rs2327433 in lncRNA TARID was associated with CAD risk and the severity of CAD in the Chinese Han population. Furthermore, SNP rs2327433 may affect the expression of atherosclerosis-related transcription factor TCF21 regulated by lncRNA TARID. Finally, our study provided a new lncRNA-dictated regulatory mechanism participating in cell proliferation.

Long non-coding RNA screening and identification of potential biomarkers for type 2 diabetes

BACKGROUND

To investigate new lncRNAs as molecular markers of T2D.

METHODS

We used microarrays to identify differentially expressed lncRNAs and mRNAs from five patients with T2D and paired controls. Through bioinformatics analysis, qRT-PCR validation, ELISA, and receiver operating characteristic (ROC) curve analysis of 100 patients with T2D and 100 controls to evaluate the correlation between lncRNAs and T2D, and whether lncRNAs could be used in the diagnosis of T2D patients.

RESULTS

We identified 68 and 74 differentially expressed lncRNAs and mRNAs, respectively. The top five upregulated lncRNAs are ENST00000381108.3, ENST00000515544.1, ENST00000539543.1, ENST00000508174.1, and ENST00000564527.1, and the top five downregulated lncRNAs are TCONS_00017539, ENST00000430816.1, ENST00000533203.1, ENST00000609522.1, and ENST00000417079.1. The top five upregulated mRNAs are Q59H50, CYP27A1, DNASE1L3, GRIP2, and lnc-TMEM18-12, and the top five downregulated mRNAs are GSTM4, PODN, GLYATL2, ZNF772, and CLTC. Examination of lncRNA-mRNA interaction pairs indicated that the target gene of lncRNA XR_108954.2 is E2F2. Multiple linear regression analysis showed that XR_108954.2 (r = 0.387, p < 0.01) and E2F2 (r = 0.368, p < 0.01) expression levels were positively correlated with glucose metabolism indicators. Moreover, E2F2 was positively correlated with lipid metabolism indicators (r = 0.333, p < 0.05). The area under the ROC curve was 0.704 (95% CI: 0.578-0.830, p = 0.05) for lncRNA XR_108954.2 and 0.653 (95% CI: 0.516-0.790, p = 0.035) for E2F2.

CONCLUSIONS

This transcriptome analysis explored the aberrantly expressed lncRNAs and identified E2F2 and lncRNA XR_108954.2 as potential biomarkers for patients with T2D.

LncRNAs and Cardiovascular Disease

A novel class of RNA molecule emerged from human transcriptome sequencing studies termed long non-coding RNAs. These RNA molecules differ from other classes of non-coding RNAs such as microRNAs in their sizes, sequence motifs and structures. Studies have demonstrated that long non-coding RNAs play a prominent role in the development and progression of cardiovascular disease. They provide the cell with tiered levels of gene regulation interacting with DNA, other RNA molecules or proteins acting in various capacities to control a variety of cellular mechanisms. Cell specificity is a hallmark of lncRNA studies and they have been identified in macrophages, smooth muscle cells, endothelial cells and hepatocytes. Recent lncRNA studies have uncovered functional micropeptides encoded within lncRNA genes that can have a different function to the lncRNA. Disease associated mutations in the genome tend to occur in non-coding regions signifying the importance of non-coding genes in disease associations. There is a great deal of work to be done in the non-coding RNA field and tremendous therapeutic potential due to their cell type specificity. A better understanding of the functions and interactions of lncRNAs will inevitably have clinical implications.

Long noncoding RNA DANCR expression and its predictive value in patients with atherosclerosis

Long noncoding RNAs (lncRNAs) act crucial roles in the progression of vascular diseases, including atherosclerosis. This study aims to investigate the expression levels of the atherosclerosis-associated lncRNA DANCR in patients diagnosed with atherosclerosis and whether its abnormal expression affects the progress of atherosclerosis. The expression of DANCR in the serum samples of all study participants was quantified using RT-qPCR. Then, the predictive capacities of DANCR for the detection of atherosclerosis patients were evaluated via receiver operating characteristic (ROC) curve analysis. The effects of DANCR on vascular smooth muscle cells (VSMCs) proliferation and migration were then explored using cell counting kit-8 (CCK-8) and Transwell migration assays. The DANCR exhibited increased expression trends in patients with atherosclerosis than healthy controls. Moreover, there were differences in the levels of low-density lipoprotein cholesterol (LDL-C), homocysteine (Hcy), and C-reactive protein (CRP) between the healthy controls and atherosclerosis patients. The DANCR expression was positively correlated with serum LDL-C, Hcy, and CRP levels. DANCR expression could distinguish patients with atherosclerosis from healthy individuals with a high area under the ROC curve (AUC), sensitivity, and specificity. Additionally, knockdown of DANCR weakened the proliferative abilities and migration capacities of VSMCs. It was also shown that DANCR could compete with miR-335-5p binding. Herein, it appears that the LncRNA DANCR was closely associated with the progression of atherosclerosis by targeting miR-335-5p, which might be a potential detective predictor and target for the treatment of atherosclerosis.

Expression profiles of long noncoding and messenger RNAs in epicardial adipose tissue derived from patients with coronary atherosclerosis

BACKGROUND

Given its close anatomical location to the heart and its endocrine properties, attention on epicardial adipose tissue (EAT) has increased.

OBJECTIVE

This study investigated the expression profiles of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in EAT derived from patients with coronary artery disease (CAD).

METHODS

EAT samples from 8 CAD and 8 non-CAD patients were obtained during open-heart surgery. The expression of lncRNAs and mRNAs in each EAT sample was investigated using microarray analysis and further verified using reverse transcription-quantitative polymerase chain reaction.

RESULTS

Overall, 1,093 differentially expressed mRNAs and 2,282 differentially expressed lncRNAs were identified in EAT from CAD vs non-CAD patients. Analysis using Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes showed that these differentially expressed genes were mainly enriched in various inflammatory, immune, and metabolic processes. They were also involved in osteoclast differentiation, B cell receptor and adipocytokine signaling, and insulin resistance pathways. Additionally, lncRNA-mRNA and lncRNA-target pathway networks were built to identify potential core genes (e.g. Lnc-CCDC68-2:1, AC010148.1, NONHSAT104810) involved in atherosclerosis pathogenesis.

CONCLUSION

In summary, lncRNA and mRNA profiles in EAT were markedly different between CAD and non-CAD patients. Our study identifies several potential key genes and pathways that may participate in atherosclerosis development.

Relationship between Expression of Plasma lncRNA-HEIH and Prognosis in Patients with Coronary Artery Disease

Objective

We aimed to investigate the expression of long noncoding RNA- (lncRNA-) HEIH in patients with coronary artery disease (CAD) and its impact on patients' prognosis. Patients and Methods. From July 2015 to December 2018, 250 patients who underwent coronary angiography, including 50 in the control group and 150 in the CAD group, were collected for detection of the expression of lncRNA-HEIH by real-time quantitative polymerase chain reaction (qPCR). The severity of CAD was evaluated through SYNTAX scoring system. In addition, these patients with CAD were followed up for 3 years, and the major cardiac adverse events such as myocardial infarction and revascularization were recorded.

Results

The expression of lncRNA-HEIH in plasma of patients with CAD was remarkably higher than that in the control subjects and was verified to be relevant to the severity of CAD. Meanwhile, it was found that CAD patients with high expression of lncRNA-HEIH had higher rates of dyslipidemia as well as CAD family history and higher overall incidence of major cardiac adverse events than those with low expression of lncRNA-HEIH.

Conclusions

lncRNA-HEIH expression is upregulated in the plasma of CAD patients, which is capable of affecting the prognosis of patients.

The age, NT-proBNP, and Ejection Fraction Score as a Novel Predictor of Clinical Outcomes in CAD Patients After PCI

Background

Previous evidences have been proved that age, N-terminal pro-B-type natriuretic peptide (NT-proBNP), and ejection fraction are tightly associated with the long-term outcomes in patients suffered from coronary artery disease (CAD). Therefore, the present study aimed to assess the prognosis value of age, NT-proBNP, and ejection fraction (ABEF) score in CAD patients who underwent percutaneous coronary intervention (PCI).

Methods

Observational cohort methodology was used in this study which enrolled totally 3561 patients. And the patients were followed up regularly for 37.59 ± 22.24 months. Patients were classed into three groups based on the tertiles of ABEF sore: first tertile (<5.06, n = 831), second tertile (5.06-6.25, n = 839), and third tertile (≥ 6.25, n = 834). The ABEF score was calculated as follows: age (years)/ejection fraction (%) + NT-proBNP (NT-proBNP<177pg/mL was 1, 177≤NT-proBNP≥524pg/mL was 2 and NT-proBNP > 524pg/mL is 3). The association between ABEF score and adverse prognosis, including all-cause death (ACD), cardiac death (CD), major adverse cardiovascular events (MACEs) and major adverse cardiac and cerebrovascular events (MACCEs), in patients who underwent PCI was analyzed.

Results

According to the risk category of ABEF score, the incidences of ACD (P < .001), CD (P < .001) and MACCEs (P = .021) among the three groups showed significant differences. Multivariate Cox regression analysis suggested that the respective risks of ACD and CD were increased 3.013 folds (hazard risk [HR] = 4.013 [95% confidence interval [CI]: 1.922-8.378], P < .001) and 4.922 folds ([HR] = 5.922 [95% [CI]: 2.253-15.566], P < .001) in the third tertile compared with those in the first tertile. Kaplan-Meier survival analyses showed that the cumulative risks of ACD,CD and MACCEs in patients with the high ABEF score tended to increase.

Conclusion

The present study indicated ABEF score was a novel biomarker suitable for predicting adverse prognosis in patients after PCI, which may be used for early recognition and risk stratification.

Comprehensive Analysis to Identify Key Genes Involved in Advanced Atherosclerosis

Background

The study was aimed at finding accurate and effective therapeutic targets and deepening our understanding of the mechanisms of advanced atherosclerosis (AA).

Methods

We downloaded the gene expression datasets GSE28829, GSE120521, and GSE43292 from Gene Expression Omnibus. Weighted gene coexpression network analysis (WGCNA) was performed for GSE28829, and functional enrichment analysis and protein–protein interaction network analysis were conducted on the key module. Significant genes in the key module were analyzed by molecular complex detection, and genes in the most important subnetwork were defined as hub genes. Multiple dataset analyses for hub genes were conducted. Genes that overlapped between hub genes and differentially expressed genes (DEGs) of GSE28829 and GSE120521 were defined as key genes. Further validation for key genes was performed using GSE28829 and GSE43292. Gene set enrichment analysis (GSEA) was applied to key genes.

Results

A total of 77 significant genes in the key module of GSE28829 were screened out that were mainly associated with inflammation and immunity. The subnetwork was obtained from significant genes, and 18 genes in this module were defined as hub genes, which were related to immunity and expressed in multiple diseases, particularly systemic lupus erythematosus. Some hub genes were regulated by SPI1 and associated with the blood, spleen, and lung. After overlapping with DEGs of GSE28829 and GSE120521, a total of 10 genes (HCK, ITGAM, CTSS, TYROBP, LAPTM5, FCER1G, ITGB2, NCF2, AIF1, and CD86) were identified as key genes. All key genes were validated and evaluated successfully and were related to immune response pathways.

Conclusion

Our study suggests that the key genes related to immune and inflammatory responses are involved in the development of AA. This may deepen our understanding of the mechanisms of and provide valuable therapeutic targets for AA.

Comprehensive analysis of the ceRNA network in coronary artery disease

With the rapid aging of the population, coronary artery disease (CAD) has become one of the most fatal chronic diseases. However, the genetic mechanism of CAD is still unclear. The purpose of this study is to construct the lncRNA-miRNA-mRNA regulatory network for CAD diseases and systematically identify differentially expressed genes in patients with coronary heart disease. In this study, two lncRNA datasets (GSE69587 and GSE113079) and a microRNA dataset (GSE105449) which contained 393 and 38 CAD samples were selected. In addition, two mRNA datasets which named GSE113079 (98 CAD samples) and GSE9820 (8 CAD samples) were selected to search the differentially expressed genes (DEGs). By comparing the expression data between CAD and control samples, a total of 1111 lncRNAs, 2595 mRNAs and 22 miRNAs were identified. Based on the DEGs, a lncRNA-miRNA-mRNA ceRNA network was constructed to explore the hub nodes in CAD. In the ceRNA network, the lncRNAs KCNQ1OT1 and H19 showed high connectivity with the nine miRNAs. GO and KEGG results showed that genes in ceRNA networks were mainly involved in nitrogen compound metabolic process, PI3K-Akt signaling pathway and retrograde endocannabinoid signaling. These findings will improve the understanding of the occurrence and development mechanism of CAD.

The Preventive Effect of Cardiac Sympathetic Denervation Induced by 6-OHDA on Myocardial Ischemia-Reperfusion Injury: The Changes of lncRNA/circRNAs-miRNA-mRNA Network of the Upper Thoracic Spinal Cord in Rats

In this study, we investigated whether chemical 6-hydroxydopamine (6-OHDA) stimuli caused cardiac sympathetic denervation (SD), and we analyzed gene expression profiles to determine the changes in the lncRNA/circRNAs-miRNA-mRNA network in the affected spinal cord segments to identify putative target genes and molecular pathways in rats with myocardial ischemia–reperfusion injury (MIRI). Our results showed that cardiac sympathetic denervation induced by 6-OHDA alleviated MIRI. Compared with the ischemia reperfusion (IR, MIRI model) group, there were 148 upregulated and 51 downregulated mRNAs, 165 upregulated and 168 downregulated lncRNAs, 70 upregulated and 52 downregulated circRNAs, and 12 upregulated and 11 downregulated miRNAs in the upper thoracic spinal cord of the SD-IR group. Furthermore, we found that the differential genes related to cellular components were mainly enriched in extracellular and cortical cytoskeleton, and molecular functions were mainly enriched in chemokine activity. Pathway analysis showed that the differentially expressed genes were mainly related to the interaction of cytokines and cytokine receptors, sodium ion reabsorption, cysteine and methionine metabolism, mucoglycan biosynthesis, cGMP-PKG signaling pathway, and MAPK signaling pathway. In conclusion, the lncRNA/circRNAs-miRNA-mRNA networks in the upper thoracic spinal cord play an important role in the preventive effect of cardiac sympathetic denervation induced by 6-OHDA on MIRI, which offers new insights into the pathogenesis of MIRI and provides new targets for MIRI.

Identification of Two Long Non-Coding RNAs AC010082.1 and AC011443.1 as Biomarkers of Coronary Heart Disease Based on Logistic Stepwise Regression Prediction Model

Coronary heart disease (CHD) is a global health concern with high morbidity and mortality rates. This study aimed to identify the possible long non-coding RNA (lncRNA) biomarkers of CHD. The lncRNA- and mRNA-related data of patients with CHD were downloaded from the Gene Expression Omnibus database (GSE113079). The limma package was used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively). Then, miRcode, TargetScan, miRDB, and miRTarBase databases were used to form the competing endogenous RNA (ceRNA) network. Furthermore, SPSS Modeler 18.0 was used to construct a logistic stepwise regression prediction model for CHD diagnosis based on DElncRNAs. Of the microarray data, 70% was used as a training set and 30% as a test set. Moreover, a validation cohort including 30 patients with CHD and 30 healthy controls was used to verify the hub lncRNA expression through real-time reverse transcription-quantitative PCR (RT-qPCR). A total of 185 DElncRNAs (114 upregulated and 71 downregulated) and 382 DEmRNAs (162 upregulated and 220 downregulated) between CHD and healthy controls were identified from the microarray data. Furthermore, through bioinformatics prediction, a 38 lncRNA-21miRNA-40 mRNA ceRNA network was constructed. Next, by constructing a logistic stepwise regression prediction model for 38 DElncRNAs, we screened two hub lncRNAs AC010082.1 and AC011443.1 (p < 0.05). The sensitivity, specificity, and area under the curve were 98.41%, 100%, and 0.995, respectively, for the training set and 93.33%, 91.67%, and 0.983, respectively, for the test set. We further verified the significant upregulation of AC010082.1 (p < 0.01) and AC011443.1 (p < 0.05) in patients with CHD using RT-qPCR in the validation cohort. Our results suggest that lncRNA AC010082.1 and AC011443.1 are potential biomarkers of CHD. Their pathological mechanism in CHD requires further validation.

TGF-β1 induced proliferation, migration, and ECM accumulation through the SNHG11/miR-34b/LIF pathway in human pancreatic stellate cells

Chronic pancreatitis (CP) is a chronic inflammatory and fibrotic disease of the pancreas, and activated pancreatic stellate cells (PSCs) play a vital role in the progression of pancreatic fibrosis in CP. It has been reported that long non-coding RNA small nucleolar RNA host gene 11 (SNHG11) is highly expressed in chronic pancreatitis (CP) patients. However, the role of SNHG11 in CP progression is unclear. The purport of the study was to survey the role of SNHG11 in CP. We employed transforming growth factor (TGF)-beta1 (TGF-β1) to activate human pancreatic stellate cells (PSCs). Expression of SNHG11 was assessed with qRT-PCR. Loss-of-function experiments were executed to evaluate the effects of SNHG11 on the proliferation and migration of TGF-β1-treated PSCs. Some protein levels were detected by western blotting. The regulatory mechanism of SNHG11 was verified by the dual-luciferase reporter and RIP assays. As a result, SNHG11 was upregulated in plasma of CP patients and TGF-β1-treated PSCs. Also, SNHG11 inhibition reduced TGF-β1-induced proliferation, migration, and ECM accumulation in PSCs. Mechanistically, SNHG11 regulated leukemia inhibitory factor (LIF) expression by sponging miR-34b. Furthermore, miR-34b inhibitor abolished SNHG11 silencing-mediated effects on TGF-β1-treated PSC proliferation, migration, and ECM accumulation. LIF overexpression counteracted the repressive influence of miR-34b mimic on proliferation, migration, and ECM accumulation of TGF-β1-treated PSCs. In conclusion, SNHG11 knockdown reduced TGF-β1-induced PSC proliferation, migration, and ECM accumulation by the miR-34b/LIF axis.

The role of noncoding RNAs in Parkinson's disease: biomarkers and associations with pathogenic pathways

The discovery of various noncoding RNAs (ncRNAs) and their biological implications is a growing area in cell biology. Increasing evidence has revealed canonical and noncanonical functions of long and small ncRNAs, including microRNAs, long ncRNAs (lncRNAs), circular RNAs, PIWI-interacting RNAs, and tRNA-derived fragments. These ncRNAs have the ability to regulate gene expression and modify metabolic pathways. Thus, they may have important roles as diagnostic biomarkers or therapeutic targets in various diseases, including neurodegenerative disorders, especially Parkinson's disease. Recently, through diverse sequencing technologies and a wide variety of bioinformatic analytical tools, such as reverse transcriptase quantitative PCR, microarrays, next-generation sequencing and long-read sequencing, numerous ncRNAs have been shown to be associated with neurodegenerative disorders, including Parkinson's disease. In this review article, we will first introduce the biogenesis of different ncRNAs, including microRNAs, PIWI-interacting RNAs, circular RNAs, long noncoding RNAs, and tRNA-derived fragments. The pros and cons of the detection platforms of ncRNAs and the reproducibility of bioinformatic analytical tools will be discussed in the second part. Finally, the recent discovery of numerous PD-associated ncRNAs and their association with the diagnosis and pathophysiology of PD are reviewed, and microRNAs and long ncRNAs that are transported by exosomes in biofluids are particularly emphasized.

Long non-coding RNA THRIL is upregulated in coronary heart disease and binds to microRNA-424 to upregulate TXNIP in mice

Cardiovascular disease, particularly coronary heart disease (CHD), is one of the diseases with the highest fatality. The close correlation between long non-coding RNAs (lncRNAs) and the occurrence and development of myocardial injury has been highlighted recently. This article mainly focused on the regulation of THRIL on myocardial injury caused by CHD in mice. After establishment of a mouse model with CHD, a lncRNA microarray analysis was performed on mouse myocardial tissues to detect differentially expressed lncRNAs, followed by RT-qPCR validation. CHD was induced in mice by high-fat diet feeding and THRIL was silenced using si-THRIL. The results showed that treating CHD mice with si-THRIL attenuated myocardial damage by restoring LVEF, LVFS, and HDL-C levels, while lowering HMI, LVMI, TC, TG, LDL-C, CK-MB, and cTnI levels. Meanwhile, mechanistical studies using bioinformatics prediction, dual-luciferase and subcellular fractionation assays revealed that THRIL bound to microRNA (miR)-424, inhibited miR-424 interaction with TXNIP and promoted TXNIP expression in the myocardial tissues. The cardioprotective effects of si-THRIL on mice were attenuated when miR-424 was downregulated. Moreover, TXNIP exerted its effects on myocardial injury by mediating the p53 pathway. Taken together, this study demonstrated that THRIL inhibition alleviates myocardial injury in CHD possibly through the miR-424/TXNIP/p53 axis.

Long noncoding RNA distal-less homeobox 2 antisense 1 restrains inflammatory response and apoptosis of periodontal ligament cells by binding with microRNA-330-3p to regulate Ro60, Y RNA binding protein

OBJECTIVE

This study aims to investigate the role of long noncoding RNA distal-less homeobox 2 antisense 1 (DLX2-AS1) in lipopolysaccharide-induced inflammatory response and apoptosis of periodontal ligament cells (PDLCs).

DESIGN

Lipopolysaccharide was used to induce inflammation response of PDLCs. The expression of DLX2-AS1, microRNA-330-3p and Ro60, Y RNA binding protein (RO60) in lipopolysaccharide-treated PDLCs was detected by reverse transcription quantitative polymerase chain reaction (RT-qPCR). Enzyme linked immunosorbent assay (ELISA) was performed to evaluate the concentration of inflammatory cytokines in PDLCs after DLX2-AS1 overexpression or RO60 downregulation. The apoptosis of PDLCs after lipopolysaccharide treatment or indicated transfection was analyzed by flow cytometry analysis. The level of apoptosis-related proteins, Bax and Bcl-2, were examined by western blotting. The binding capacity between microRNA-330-3p and DLX2-AS1 (or RO60) was verified by luciferase reporter assays.

RESULTS

DLX2-AS1 was downregulated in PDLCs after lipopolysaccharide treatment. DLX2-AS1 overexpression decreased the production of inflammatory cytokines and inhibited cell apoptosis. microRNA-330-3p bound with DLX2-AS1 and displayed high expression in lipopolysaccharide-induced PDLCs. In addition, the downregulation of RO60, a target gene of microRNA-330-3p, reversed the suppressive influence of DLX2-AS1 overexpression on the inflammatory response and apoptosis of PDLCs.

CONCLUSIONS

DLX2-AS1 restrains inflammatory response and apoptosis of PDLCs via the microRNA-330-3p/RO60 axis.

Long Non-Coding RNAs in Cardiovascular Diseases: Potential Function as Biomarkers and Therapeutic Targets of Exercise Training

Despite advances in treatments and therapies, cardiovascular diseases (CVDs) remain one of the leading causes of death worldwide. The discovery that most of the human genome, although transcribed, does not encode proteins was crucial for focusing on the potential of long non-coding RNAs (lncRNAs) as essential regulators of cell function at the epigenetic, transcriptional, and post-transcriptional levels. This class of non-coding RNAs is related to the pathophysiology of the cardiovascular system. The different expression profiles of lncRNAs, in different contexts of CVDs, change a great potential in their use as a biomarker and targets of therapeutic intervention. Furthermore, regular physical exercise plays a protective role against CVDs; on the other hand, little is known about its underlying molecular mechanisms. In this review, we look at the accumulated knowledge on lncRNAs and their functions in the cardiovascular system, focusing on the cardiovascular pathology of arterial hypertension, coronary heart disease, acute myocardial infarction, and heart failure. We discuss the potential of these molecules as biomarkers for clinical use, their limitations, and how the manipulation of the expression profile of these transcripts through physical exercise can begin to be suggested as a strategy for the treatment of CVDs.

Characterization of LncRNA expression profile and identification of functional LncRNAs associated with unstable angina

Background

Increasing evidences suggest that long noncoding RNAs (lncRNAs) play critical roles in the pathogenesis of coronary artery disease (CAD). However, the association between lncRNAs expression profiles and unstable angina (UA) remained poorly known. Thus, the present study aims to investigate expression patterns, biological functions, and diagnostic value of lncRNAs in UA.

Methods

The present study explored the lncRNA and mRNA expression profiles in peripheral blood mononuclear cells (PBMCs) of UA patients and normal coronary artery (NCA) controls using RNA‐seq. The biological function of differentially expressed lncRNAs was analyzed using gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The expression of the selected lncRNAs was validated in another 44 UA patients and 46 NCA controls. Receiver operating characteristic curve (ROC) was performed to evaluate the diagnostic value of lncRNAs for UA.

Results

A total of 98 lncRNAs and 615 mRNAs were observed differentially expressed in PBMCs of UA patients as compared to NCA controls. The 10 most upregulated lncRNAs were LNC_000226, DANCR, RP1‐167A14.2, LNC_002091, LNC_001526, LNC_001165, LNC_002772, LNC_000088, LNC_001226, and FAM157C, and the 10 most downregulated lncRNAs were RP11‐734I18.1, RP11‐185E8.1, RP11‐360I2.1, LNC_001302, LNC_001287, RN7SL471P, LNC_000914, LINC01506, RP11‐160E2.6, and LNC_000995. LNC_000226 and MALAT1 have high area under the curve values (AUC) for distinguishing UA from NCA patients (0.810 and 0.799, respectively), and the combination of MALAT1 and LNC_000226 increased the AUC value to 0.878.

Conclusions

The present study added our understanding about the lncRNA expression profile in UA patients and provided potential biomarkers for the diagnosis of UA.

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.

Upregulation of long non-coding RNA myocardial infarction-associated transcription is correlated with coronary artery stenosis and elevated inflammation in patients with coronary atherosclerotic heart disease

Coronary atherosclerotic heart disease (CAD) is a chronic disease caused by multiple risk factors. Aberrant expression of long non-coding RNAs (lncRNAs) has been regarded as an independent risk factor of CAD. This study evaluated lncRNA myocardial infarction-associated transcription (MIAT) expression in CAD patients and its clinical significance. Totally, 155 CAD patients and 76 non-CAD controls were enrolled. MIAT expression was detected using reverse transcription quantitative polymerase chain reaction. The clinical diagnostic significance of MIAT was evaluated by plotting the receiver operating characteristic (ROC) curve. The levels of inflammatory cytokines were detected using enzyme-linked immunosorbent assay. microRNA (miR)-29b-3p expression and pregnancy-associated plasma protein A (PAPPA) level were detected. MIAT expression in CAD patients (4.23 [1.22-6.50]) was higher than that in non-CAD controls (1.64 [0.05-2.93]) (p < 0.01) and had an independent correlation with CAD. The area under ROC curve of predicting CAD was calculated as 0.790, the specificity as 71.40%, and the sensitivity as 70.00%. MIAT expression was positively correlated with the C-reactive protein level (r = 0.769, p < 0.0001) and pro-inflammatory cytokines tumor necrosis factor-α (TNF-α), interleukin 6 (IL-6), and IL-8 levels, while negatively correlated with the anti-inflammatory cytokine IL-10. MIAT was positively correlated with Gensini score and had an independent correlation with it. LncRNA MIAT sponged miR-29b-3p and miR-29b-3p targeted PAPPA. In conclusion, lncRNA MIAT was upregulated in the peripheral blood of CAD patients and elicited clinical diagnostic significance. MIAT participated in the development of CAD via miR-29b-3p/PAPPA axis. This study provides insights into a potential target for the diagnosis and treatment of CAD.

Classifiers for Predicting Coronary Artery Disease Based on Gene Expression Profiles in Peripheral Blood Mononuclear Cells

Objective

Coronary artery disease (CAD) is a serious global health concern. Current diagnostic methods for CAD involve risk to the patient and are costly, so better diagnostic tools are needed. We defined four classifiers based on gene expression profiles in peripheral blood mononuclear cells and determined their potential for CAD detection.

Methods

We downloaded a CAD-related data set (GSE113079) from the Gene Expression Omnibus (GEO) database. We identified differentially expressed genes (DEGs) in peripheral blood mononuclear cells between CAD samples and healthy controls. DEGs were analyzed for functional enrichment. To create a robust CAD classifier, DEGs were identified by feature selection using the principal component analysis. Then, least absolute shrinkage and selection operator (LASSO) logistic regression, random forest, and support vector machine (SVM) models were created. Gene set variation analysis (GSVA) score and gene set enrichment analysis (GSEA) were also conducted. The performance of the models was evaluated in terms of the area under receiver operating characteristic curves (AUC).

Results

In the training set, we found 135 up-regulated genes and 104 down-regulated genes in CAD patients compared with controls. The DEGs were involved in some pathways associated with CAD, such as pathways involving calcium and interleukin-17 signaling. Twenty genes were identified as optimal features and used to generate the logistic classifier based on LASSO. The AUC for the classifier was 1.00 in the training set and 0.997 in the test set. Using the 20 DEGs, SVM and random forest classifiers were also generated and showed high diagnostic efficacy, with respective AUCs of 0.997 and 1.00 against the training set. A GSVA score was also established using the top 20 significant DEGs, which showed an AUC of 0.971 in the training set and 0.989 in the test set. Furthermore, GSEA showed autophagy and the proteasome to be major pathways involving the DEGs.

Conclusion

We identified a set of genes specific for CAD whose expression can be measured non-invasively. Using these genes, we defined four diagnostic classifiers using multiple methods.

Diagnostic biomarkers and potential drug targets for coronary artery disease as revealed by systematic analysis of lncRNA characteristics

Background

The expression profile of lncRNAs in coronary artery disease (CAD) patients has not yet been fully explored. Therefore, the current study aimed to investigate lncRNA-based prognostic biomarkers for CAD.

Methods

The expression profiles of lncRNA and messenger RNA (mRNA) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed lncRNA (DElncRNAs) and DEmRNAs were identified from CAD and normal samples, and weighted gene co-expression network analysis (WGCNA) was conducted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the principal functions of significantly dysregulated genes. The potential drugs of new CAD-specific genes were identified by network distance method. Receiver operating characteristic (ROC) was used to verify the classification performance of genes.

Results

A total of 512 differentially expressed genes (DEGs) and 308 DElncRNAs were identified from GSE113079 dataset to classify CAD samples. Through WGCNA co-expression analysis, 24 co-expression modules were obtained. A total of 187 DElncRNAs and 253 DEGs were determined from 7 modules correlated with CAD. Functional enrichment analysis showed that these DEGs were mainly related to inflammatory and immune-related pathways. Furthermore, 36 regulatory pairs of significantly shared micro RNAs (miRNAs) were identified as dysregulated lncRNA-mRNA (LRM-CAD), which contained 11 lncRNAs and 33 genes. Compared with a single lncRNA or gene, LRM-CAD showed stronger classification performance [average area under the curve (AUC) =0.958]. We screened 3 potential therapeutic drugs, DB09105, DB12371, and DB12612, a by binding drug-target gene interaction network. Molecular docking verified that the S1PR1 gene bound relatively closely to DB12371 and DB12612. The ROC analysis on external data sets showed that S1PR1, AC012640.4, and S1PR1-AC012640.4 could effectively distinguish CAD samples from control samples.

Conclusions

We provided a transcriptome overview of abnormally expressed lncRNAs in CAD patients and identified novel biomarkers for diagnosing CAD.

Integrative network analysis of N6 methylation-related genes reveal potential therapeutic targets for spinal cord injury

The diagnosis of the severity of spinal cord injury (SCI) and the revelation of potential therapeutic targets are crucial for urgent clinical care and improved patient outcomes. Here, we analyzed the overall gene expression data in peripheral blood leukocytes during the acute injury phase collected from Gene Expression Omnibus (GEO) and identified six m6A regulators specifically expressed in SCI compared to normal samples. LncRNA-mRNA network analysis identified AKT2/3 and PIK3R1 related to m6A methylation as potential therapeutic targets for SCI and constructed a classifier to identify patients of SCI to assist clinical diagnosis. Moreover, FTO (eraser) and RBMX (reader) were found to be significantly down-regulated in SCI and the functional gene co-expressed with them was found to be involved in the signal transduction of multiple pathways related to nerve injury. Through the construction of the drug-target gene network, eight key genes were identified as drug targets and it was emphasized that fostamatinib can be used as a potential drug for the treatment of SCI. Taken together, our study characterized the pathogenesis and identified a potential therapeutic target of SCI providing theoretical support for the development of precision medicine.

Dysregulated Circulating Apoptosis- and Autophagy-Related lncRNAs as Diagnostic Markers in Coronary Artery Disease

Objective

Increasing evidence emphasizes the implications of dysregulated apoptosis and autophagy cellular processes in coronary artery disease (CAD). Herein, we aimed to explore apoptosis- and autophagy-related long noncoding RNAs (lncRNAs) in peripheral blood of CAD patients.

Methods

The mRNA and lncRNA expression profiles were retrieved from the Gene Expression Omnibus (GEO) database. With ∣fold change | >1.5 and adjusted p value < 0.05, differentially expressed apoptosis- and autophagy-related mRNAs were screened between CAD and healthy blood samples. Also, differentially expressed lncRNAs were identified for CAD. Using the psych package, apoptosis- and autophagy-related lncRNAs were defined with Spearson's correlation analysis. Receiver operating characteristic (ROC) curves were conducted for the assessment of the diagnosed efficacy of these apoptosis- and autophagy-related lncRNAs.

Results

Our results showed that 24 apoptosis- and autophagy-related mRNAs were abnormally expressed in CAD than normal controls. 12 circulating upregulated and 1 downregulated apoptosis- and autophagy-related lncRNAs were identified for CAD. The ROCs confirmed that AC004485.3 (AUC = 0.899), AC004920.3 (AUC = 0.93), AJ006998.2 (AUC = 0.776), H19 (AUC = 0.943), RP5-902P8.10 (AUC = 0.956), RP5-1114G22.2 (AUC = 0.883), RP11-247A12.1 (AUC = 0.885), RP11-288L9.4 (AUC = 0.928), RP11-344B5.2 (AUC = 0.858), RP11-452C8.1 (AUC = 0.929), RP11-565A3.1 (AUC = 0.893), and XXbac-B33L19.4 (AUC = 0.932) exhibited good performance in differentiating CAD from healthy controls.

Conclusion

Collectively, our findings proposed that circulating apoptosis- and autophagy-related lncRNAs could become underlying diagnostic markers for CAD in clinical practice.