Construction of lncRNA-Mediated ceRNA Network for Investigating Immune Pathogenesis of Ischemic Stroke

Integrating Bulk RNA and Single-Cell Sequencing Data Unveils Efferocytosis Patterns and ceRNA Network in Ischemic Stroke

Excessive inflammatory response following ischemic stroke (IS) injury is a key factor affecting the functional recovery of patients. The efferocytic clearance of apoptotic cells within ischemic brain tissue is a critical mechanism for mitigating inflammation, presenting a promising avenue for the treatment of ischemic stroke. However, the cellular and molecular mechanisms underlying efferocytosis in the brain after IS and its impact on brain injury and recovery are poorly understood. This study explored the roles of inflammation and efferocytosis in IS with bioinformatics. Three Gene Expression Omnibus Series (GSE) (GSE137482-3 m, GSE137482-18 m, and GSE30655) were obtained from NCBI (National Center for Biotechnology Information) and GEO (Gene Expression Omnibus). Differentially expressed genes (DEGs) were processed for GSEA (Gene Set Enrichment Analysis), GO (Gene Ontology Functional Enrichment Analysis), and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analyses. Efferocytosis-related genes were identified from the existing literature, following which the relationship between Differentially Expressed Genes (DEGs) and efferocytosis-related genes was examined. The single-cell dataset GSE174574 was employed to investigate the distinct expression profiles of efferocytosis-related genes. The identified hub genes were verified using the dataset of human brain and peripheral blood sample datasets GSE56267 and GSE122709. The dataset GSE215212 was used to predict competing endogenous RNA (ceRNA) network, and GSE231431 was applied to verify the expression of differential miRNAs. At last, the middle cerebral artery (MCAO) model was established to validate the efferocytosis process and the expression of hub genes. DEGs in two datasets were significantly enriched in pathways involved in inflammatory response and immunoregulation. Based on the least absolute shrinkage and selection operator (LASSO) analyses, we identified hub efferocytosis-related genes (Abca1, C1qc, Ptx3, Irf5, and Pros1) and key transcription factors (Stat5). The scRNA-seq analysis showed that these hub genes were mainly expressed in microglia and macrophages which are the main cells with efferocytosis function in the brain. We then identified miR-125b-5p as a therapeutic target of IS based on the ceRNA network. Finally, we validated the phagocytosis and clearance of dead cells by efferocytosis and the expression of hub gene Abca1 in MCAO mice models.

The exo-microRNA (miRNA) signaling pathways in pathogenesis and treatment of stroke diseases: Emphasize on mesenchymal stem cells (MSCs)

A major factor in long-term impairment is stroke. Patients with persistent stroke and severe functional disabilities have few therapy choices. Long noncoding RNAs (lncRNAs) may contribute to the regulation of the pathophysiologic processes of ischemic stroke as shown by altered expression of lncRNAs and microRNA (miRNAs) in blood samples of acute ischemic stroke patients. On the other hand, multipotent mesenchymal stem cells (MSCs) increase neurogenesis, and angiogenesis, dampen neuroinflammation, and boost brain plasticity to improve functional recovery in experimental stroke models. MSCs can be procured from various sources such as the bone marrow, adipose tissue, and peripheral blood. Under the proper circumstances, MSCs can differentiate into a variety of mature cells, including neurons, astrocytes, and oligodendrocytes. Accordingly, the capability of MSCs to exert neuroprotection and also neurogenesis has recently attracted more attention. Nowadays, lncRNAs and miRNAs derived from MSCs have opened new avenues to alleviate stroke symptoms. Accordingly, in this review article, we examined various studies concerning the lncRNAs and miRNAs' role in stroke pathogenesis and delivered an overview of the therapeutic role of MSC-derived miRNAs and lncRNAs in stroke conditions.

AIM2 inflammasome: A potential therapeutic target in ischemic stroke

Ischemic stroke (IS) is a significant global public health issue with a high incidence, disability, and mortality rate. A robust inflammatory cascade with complex and wide-ranging mechanisms occurs following ischemic brain injury. Inflammasomes are multiprotein complexes in the cytoplasm that modulate the inflammatory response by releasing pro-inflammatory cytokines and inducing cellular pyroptosis. Among these inflammasomes, the Absent in Melanoma 2 (AIM2) inflammasome shows the ability to detect a wide range of pathogen DNAs, thereby triggering an inflammatory response. Recent studies have indicated that the aberrant expression of AIM2 inflammasome in various cells is closely associated with the pathological processes of ischemic brain injury. This paper summarizes the expression and regulatory role of AIM2 in CNS and peripheral immune cells and discusses current therapeutic approaches targeting AIM2 inflammasome. These findings aim to serve as a reference for future research in this field.

lncRNA CCAT2 Protects Against Cardiomyocyte Injury After Myocardial Ischemia/Reperfusion by Regulating BMI1 Expression

Myocardial ischemia/reperfusion (I/R) decreases cardiac function and efficiency. Accumulating evidence suggests that long noncoding RNAs (lncRNAs) have been linked to the cellular processes of myocardial I/R injury. The present investigation elucidated the function of lncRNA colon cancer-associated transcript 2 (CCAT2) in myocardial I/R injury and the related mechanisms.AC16 cardiomyocytes were exposed to hypoxia (16 hours) /reoxygenation (6 hours) (H/R) to mimic myocardial I/R models in vitro. CCAT2 and microRNA (miR) -539-3p expressions in AC16 cardiomyocytes were measured using real-time quantitative polymerase chain reaction. B-cell-specific Moloney murine leukemia virus insertion region 1 (BMI1) protein levels in AC16 cardiomyocytes were determined by western blotting. Cell viability, lactate dehydrogenase (LDH) leakage, reactive oxygen species (ROS) levels, mitochondrial membrane potential, and apoptosis were detected using Counting Kit-8, LDH Assay Kit, dihydroethidium assay, 5,5',6,6'-tetrachloro1,1',3,3'-tetramethylbenzimidazolylcarbocyanine iodide staining, flow cytometry, and western blotting, respectively. The interactions between the molecules were confirmed using the dual-luciferase gene reporter. The wingless/integrated/beta-catenin (Wnt/β-catenin) pathway under the H/R condition was detected by western blotting.CCAT2 and BMI1 mRNA expressions were reduced in H/R-exposed AC16 cardiomyocytes. CCAT2 overexpression exerted protective effects against H/R-induced cardiomyocyte injury, as demonstrated by increased cell viability and mitochondrial membrane potential and decreased LDH leakage, ROS levels, and apoptosis. In addition, CCAT2 positively regulated BMI1 expression by binding to miR-539-3p. CCAT2 knockdown or miR-539-3p overexpression restrained the protective effects of BMI1 against H/R-induced cardiomyocyte injury. In addition, miR-539-3p overexpression reversed the protective effects of CCAT2. Furthermore, CCAT2 activated the Wnt/β-catenin pathway under the H/R condition via the miR-539-3p/BMI1 axis.Overall, this investigation showed the protective effects of the CCAT2/miR-539-3p/BMI1/Wnt/β-catenin regulatory axis against cardiomyocyte injury induced by H/R.

Unveiling the LncRNA-miRNA-mRNA Regulatory Network in Arsenic-Induced Nerve Injury in Rats through High-Throughput Sequencing

Arsenic is a natural toxin which is widely distributed in the environment, incurring diverse toxicities and health problems. Previous studies have shown that long non-coding RNAs (LncRNAs) are also reported to contribute to As-induced adverse effects. LncRNAs are involved in the development of nerve injury, generally acting as sponges for microRNAs (miRNAs). This study aimed to investigate the competitive endogenous RNA (ceRNA) regulatory networks associated with arsenic-induced nerve damage. A total of 40 male Wistar rats were exposed to different doses of arsenic for 12 weeks, and samples were collected for pathological observation and high-throughput sequencing. The ceRNA network was constructed using Cytoscape, and key genes were identified through the PPI network and CytoHubba methods. A real-time quantitative PCR assay was performed to validate gene expression levels. The results showed that subchronic exposure to arsenic in drinking water resulted in pathological and ultrastructural damage to the hippocampal tissue, including changes in neuron morphology, mitochondria, and synapses. Exposure to arsenic results in the dysregulation of LncRNA and mRNA expression in the hippocampal tissues of rats. These molecules participated in multiple ceRNA axes and formed a network of ceRNAs associated with nerve injury. This study also verified key molecules within the ceRNA network and provided preliminary evidence implicating the ENRNOT-00000022622-miR-206-3p-Bdnf axis in the mechanism of neural damage induced by arsenic in rats. These findings provide novel insights into the underlying mechanism of nervous system damage induced by arsenic exposure.

Construction of chronic glomerulonephritis‑related lncRNA‑mRNA regulatory network and lncRNA‑-miRNA‑mRNA ceRNA network by bioinformatics analysis

Long non-coding RNAs (lncRNAs) are ncRNA transcripts >200 nucleotides that are important genetic regulators. LncRNAs can directly regulate mRNA through a lncRNA-mRNA regulatory mode and can also regulate mRNA through competitive binding to micro (mi)RNA, which is generally known as the competitive endogenous RNA (ceRNA) network. The present study evaluated the functional roles and regulatory networks of lncRNAs in chronic glomerulonephritis (CGN). The proliferative ability of mouse glomerular mesangial cells (GMCs) induced by different concentrations of lipopolysaccharide (LPS) was assessed using the Cell Counting Kit-8 assay, and RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs in LPS-induced GMCs. Based on the sequencing results, six lncRNAs were selected for validation using reverse transcription-quantitative PCR (RT-qPCR). Furthermore, the lncRNA-mRNA regulatory network and the lncRNA-miRNA-mRNA ceRNA network were constructed to assess the role and mechanism of CGN-related lncRNAs. To elucidate the biological functions of lncRNAs, Gene Ontology (GO) biological process term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on all mRNAs involved in the lncRNA-mRNA regulatory network and in the ceRNA network. A total of 1,532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were identified using RNA-seq. The results of RT-qPCR validation were consistent with RNA-seq results. An lncRNA-mRNA regulatory network, including 236 lncRNAs and 556 mRNAs, and a ceRNA network, including 6 lncRNAs, 18 miRNAs and 419 mRNAs, were successfully constructed. The GO biological process term enrichment and KEGG pathway enrichment analyses demonstrated that those lncRNAs were often related to inflammatory response and substance metabolism. The present study identified key CGN-related lncRNAs in LPS-induced GMCs, and further demonstrated a global view of the lncRNA-mRNA regulatory network and ceRNA network involved in CGN. These results offered novel insights into the roles of lncRNAs in the pathogenesis of CGN and identified potential diagnostic biomarkers.

LINC00638 promotes the progression of non-small cell lung cancer by regulating the miR-541-3p/IRS1/PI3K/Akt axis

Background

Preceding works reveal the function of long non-coding RNAs (abbreviated to lncRNAs) during non-small cell lung cancer (NSCLC) evolvement. We explored the profile and biological functions of the lncRNA LINC00638 in NSCLC.

Methods

Reverse transcription-quantitative PCR examined LINC00638 level in NSCLC and corresponding non-tumor tissues, human normal lung epithelial cells BEAS-2B, and NSCLC cells (NCI-H460, HCC-827, A549, H1299, H1975, H460). The gain- and loss-of-function assay of LINC00638 ascertained its function in modulating the proliferation, apoptosis, and invasion of NSCLC cells (HCC-827 and H460). Bioinformatics analysis investigated the underlying mechanisms. Dual luciferase reporter gene and RNA immunoprecipitation (RIP) checked the interactions between LINC00638 and microRNA (miR)-541-3p, miR-541-3p and insulin receptor substrate 1 (IRS1).

Results

LINC00638 was upregulated in NSCLC tissues by contrast to the profiles found in the corresponding non-tumor normal tissues, as well as in NSCLC cells vis-à-vis BEAS-2B cells. LINC00638 upregulation pertained to the poorer survival rates of NSCLC patients. Overexpressing LINC00638 augmented NSCLC cells' proliferation, growth, migration, and invasion but inhibited their apoptosis, while down-regulating LINC00638 led to the opposite. miR-541-3p might be an underlying target of LINC00638, which targeted IRS1, inhibited NSCLC progression, and reversed the carcinogenic effects of LINC00638. Mechanistically, LINC00638/miR-541-3p regulated the IRS1/phosphoinositide 3-kinase (PI3K)/Akt signaling pathway. Repressing IRS1/2 using its inhibitor NT157 repressed LINC00638-mediated oncogenic effects.

Conclusion

LINC00638 may function as an oncogene in NSCLC by modulating the miR-541-3p/IRS1/PI3K/Akt axis.

Competing endogenous RNA network analysis of the molecular mechanisms of ischemic stroke

BACKGROUND

Ischemic stroke (IS) is a serious neurological disease that largely results in long-term disability and death. Extensive evidence has indicated that the activation of inflammation and ferroptosis significantly contribute to the development of IS pathology. However, the underlying molecular mechanism remains unclear. In this study, we aimed to identify potential biomarkers associated with IS through the construction of a competing endogenous RNA (ceRNA) network and to investigate the possible inflammatory and ferroptosis-related molecular mechanisms.

RESULTS

We identified 178 differentially expressed target messenger RNAs (DETmRNAs) associated with IS. As revealed through enrichment analysis, the DEmRNAs were mainly enriched in the inflammatory signaling pathways and also related to ferroptosis mechanism. The CIBERSORT algorithm showed immune infiltration landscapes in which the naïve B cells, naïve T cells, and monocytes had statistically different numbers in the cerebral infarction group compared with the control group. A ceRNA network was constructed in this study involving 44 long non-coding RNAs (lncRNAs), 15 microRNAs (miRNAs), and 160 messenger RNAs (mRNAs). We used the receiver operating characteristic (ROC) analysis to identify three miRNAs (miR-103a-3p, miR-140-3p, and miR-17-5p), one mRNA (TLR4), and one lncRNA (NEAT1) as the potential key biomarkers of the ceRNA network. The key mRNA and lncRNA were shown to be highly related to the ferroptosis mechanism of IS. The expression of these key biomarkers was also further validated by a method of quantitative real-time polymerase chain reaction in SH-SY5Y cells, and the validated results were consistent with the findings predicted by bioinformatics.

CONCLUSION

Our results suggest that the ceRNA network may exert an important role in the inflammatory and ferroptosis molecular mechanisms of IS, providing new insight into therapeutic IS targets.

Analysis of long non-coding RNA expression profile of bovine monocyte-macrophage infected by Mycobacterium avium subsp. paratuberculosis

Mycobacterium avium subsp. paratuberculosis (MAP) is the causative agent of paratuberculosis. As a potential zoonotic pathogen, MAP also seriously threatens human health and social security. At present, long non-coding RNA (lncRNA) has attracted wide attention as an useful biomarker in various diseases. Therefore, our study analyzed the lncRNA expression profiles and lncRNA-mRNA regulatory network of MAP infected bovine monocytes-macrophages and uninfected bovine cells by high-throughput sequencing. A total of 4641 differentially expressed lncRNAs genes were identified, including 3111 up-regulated genes and 1530 down-regulated genes. In addition, lncRNA-mRNA interaction analysis was performed to predict the target genes of lncRNA. Among them, after MAP infection, 86 lncRNAs targeted to mRNA, of which only 6 genes were significantly different. The results of Gene Ontology (GO) enrichment analysis showed that the differentially expressed genes significantly enriched in functional groups were related to immune regulation. Multiple signal pathways including NF-κB, NOD-like receptor, Cytokine-cytokine receptor, Toll-like receptor signaling pathway, Chemokine signaling pathway, and other important biochemical, metabolic and signal transduction pathways were enriched in Kyoto Encyclopedia of Genes and Genomes (KEGG). In this study, analysis of macrophage transcriptomes in response to MAP infection is expected to provide key information to deeply understand role of the pathogen in initiating an inappropriate and persistent infection in susceptible hosts and molecular mechanisms that might underlie the early phases of paratuberculosis.

Construction of an immune-related ceRNA network to screen for potential diagnostic markers for autism spectrum disorder

Purpose: The diagnosis of autism spectrum disorder (ASD) is reliant on evaluation of patients' behavior. We screened the potential diagnostic and therapeutic targets of ASD through bioinformatics analysis. Methods: Four ASD-related datasets were downloaded from the Gene Expression Omnibus database. The "limma" package was employed to analyze differentially expressed messenger (m)RNAs, long non-coding (lnc)RNAs, and micro (mi)RNAs between ASD patients and healthy volunteers (HVs). We constructed a competing endogenous-RNA (ceRNA) network. Enrichment analyses of key genes were undertaken using the Gene Ontology database and Kyoto Encyclopedia of Genes and Genomes database. The ImmucellAI database was used to analyze differences in immune-cell infiltration (ICI) in ASD and HV samples. Synthetic analyses of the ceRNA network and ICI was done to obtain a diagnostic model using LASSO regression analysis. Analyses of receiver operating characteristic (ROC) curves were done for model verification. Results: The ceRNA network comprised 49 lncRNAs, 30 miRNAs, and 236 mRNAs. mRNAs were associated with 41 cellular components, 208 biological processes, 39 molecular functions, and 35 regulatory signaling pathways. Significant differences in the abundance of 10 immune-cell species between ASD patients and HVs were noted. Using the ceRNA network and ICI results, we constructed a diagnostic model comprising five immune cell-associated genes: adenosine triphosphate-binding cassette transporter A1 (ABCA1), DiGeorge syndrome critical region 2 (DGCR2), glucose-fructose oxidoreductase structural domain gene 1 (GFOD1), glutaredoxin (GLRX), and SEC16 homolog A (SEC16A). The diagnostic performance of our model was revealed by an area under the ROC curve of 0.923. Model verification was done using the validation dataset and serum samples of patients. Conclusion: ABCA1, DGCR2, GFOD1, GLRX, and SEC16A could be diagnostic biomarkers and therapeutic targets for ASD.

The construction of neurogenesis-related ceRNA network of ischemic stroke treated by oxymatrine

BACKGROUND

Known as a disease associated with high mortality, disability and a significant financial burden, ischemic stroke ranks as one of the three diseases threatening human health. Recent advances in omics technology created opportunities to uncover the mechanism in ischemic stroke occurrence and treatment. In this study, we aimed to construct the competitive endogenous RNA (ceRNA) networks of ischemic stroke treated by oxymatrine intervention.

METHOD

The middle cerebral artery occlusion (MCAO) mouse model of ischemic stroke was constructed, and oxymatrine was administered. Then RNA-Sequencing was performed and integrated analysis of mRNAs, lncRNAs and circRNAs was conducted to reveal the pharmacology of oxymatrine. Functional enrichment analysis was performed to explore the underlying mechanism of differentially expressed (DE) mRNAs. The protein-protein interaction (PPI) network of neurogenesis-related genes and long noncoding RNAs (lncRNAs)/circular RNAs (circRNAs) based ceRNA networks were constructed.

RESULTS

First, this study revealed the DE-mRNAs, DE-lncRNAs and DE-circRNAs between Oxymatrine treated group and the MCAO group. Then, the common 1231 DE-mRNAs, 32 DE-lncRNAs and 31 DE-circRNAs with opposite trends were identified. The Kyoto Encyclopedia of Genes and Genomes to identify the functional enrichment of 1231 DE-mRNAs were enriched in neurogenesis-related biological processes. Based on neurogenesis-related DE-mRNAs, the PPI network was constructed, and hub genes were identified based on centrality. Finally, both the lncRNA-based and circRNAs-based ceRNA networks were constructed.

CONCLUSION

In summary, this study identified novel coding and noncoding ischemic stroke targets of oxymatrine-treated MCAO. Most importantly, we identified lncRNAs and circRNAs candidates as potential oxymatrine targets and constructed the neurogenesis-related ceRNA networks.

Network Pharmacology and Bioinformatics Methods Reveal the Mechanism of Berberine in the Treatment of Ischaemic Stroke

Aim

To elucidate the mechanism of action of berberine on ischaemic stroke based on network pharmacology, bioinformatics, and experimental verification.

Methods

Berberine-related long noncoding RNAs (lncRNAs) were screened from public databases. Differentially expressed lncRNAs in ischaemic stroke were retrieved from the Gene Expression Omnibus (GEO) database. GSE102541 was comprehensively analysed using GEO2R. The correlation between lncRNAs and ischaemic stroke was evaluated by the mammalian noncoding RNA-disease repository (MNDR) database. The component-target-disease network and protein-protein interaction (PPI) network of berberine in the treatment of ischaemic stroke were constructed by using network pharmacology. We then performed gene ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) enrichment analyses. Finally, according to the molecular docking analysis and the binding probability between the lncRNA and key proteins, the effectiveness of the results was further verified by in vitro experiments.

Results

After matching stroke-related lncRNAs with berberine-related lncRNAs, four genes were selected as potential targets of berberine in the treatment of ischaemic stroke. Subsequently, lncRNA H19 was identified as the potential crucial regulatory lncRNA of berberine. Here, 52 target proteins of berberine in the treatment of ischaemic stroke were identified through database mining. Through topological analysis, 20 key targets were identified which were enriched in inflammation, apoptosis, and immunity. Molecular docking results showed that MAPK8, JUN, and EGFR were central genes. Finally, in vitro experiments demonstrated that lncRNA H19, p-JNK1/JNK1, p-c-Jun/c-Jun, and EGFR expressions were significantly increased in hypoxia-treated SH-SY5Y cells and were restored by berberine treatment.

Conclusion

The potential targets and biological effects of berberine in the treatment of ischaemic stroke were predicted in this study. The lncRNA H19/EGFR/JNK1/c-Jun signalling pathway may be a key mechanism of berberine-induced neuroprotection in ischaemic stroke.

The Construction and Analysis of Immune Infiltration and Competing Endogenous RNA Network in Acute Ischemic Stroke

Acute ischemic stroke (AIS) is a common neurological disease that seriously endangers both the physical and mental health of human. After AIS, activated immune cells are recruited to the stroke site, where inflammatory mediators are released locally, and severe immune inflammatory reactions occur within a short time, which affects the progress and prognosis of IS. Circular RNA (circRNA) is a type of non-coding RNA (ncRNA) with a closed-loop structure and high stability. Studies have found that circRNA can affect the course of IS. However, there is no report on ceRNA’s pathogenesis in AIS that is mediated by circRNA. In this study, the CIBERSORT algorithm was used to analyze the distribution of immune cells in patients with AIS. mRNA dataset was downloaded from the GEO database, and the weighted gene co-expression network analysis (WGCNA) method was used to construct weighted gene co-expression to determine 668 target genes, using GO, KEGG enrichment analysis, construction of protein-protein interaction (PPI) network analysis, and molecular complex detection (MCODE) plug-in analysis. The results showed that the biological function of the target gene was in line with the activation and immune regulation of neutrophils; signal pathways were mostly enriched in immune inflammation-related pathways. A Venn diagram was used to obtain 52 intersection genes between target genes and disease genes. By analyzing the correlation between the intersection genes and immune cells, we found that the top 5 hub genes were TOM1, STAT3, RAB3D, MDM2, and FOS, which were all significantly positively correlated with neutrophils and significantly negatively correlated with eosinophils. A total of 52 intersection genes and the related circRNA and miRNA were used as input for Cytoscape software to construct a circRNA-mediated ceRNA competition endogenous network, where a total of 18 circRNAs were found. Further analysis of the correlation between circRNA and immune cells found that 4 circRNAs are positively correlated with neutrophils. Therefore, we speculate that there may be a regulatory relationship between circRNA-mediated ceRNA and the immune mechanism in AIS. This study has important guiding significance for the progress, outcome of AIS, and the development of new medicine.

Comprehensive Analysis of Hub Genes Associated With Competing Endogenous RNA Networks in Stroke Using Bioinformatics Analysis

Background: Acute ischemic stroke (AIS) is the second leading cause of death and the third leading cause of disability worldwide. Long noncoding RNAs (lncRNAs) are promising biomarkers for the early diagnosis of AIS and closely participate in the mechanism of stroke onset. However, studies focusing on lncRNAs functioning as microRNA (miRNA) sponges to regulate the mRNA expression are rare and superficial. Methods: In this study, we systematically analyzed the expression profiles of lncRNA, mRNA (GSE58294), and miRNA (GSE110993) from the GEO database. Gene ontology (GO) analysis was performed to reveal the functions of differentially expressed genes (DEGs), and we used weighted gene co-expression network analysis (WGCNA) to investigate the relationships between clinical features and expression profiles and the co-expression of miRNA and lncRNA. Finally, we constructed a lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network with selected DEGs using bioinformatics methods and obtained ROC curves to assess the diagnostic efficacy of differentially expressed lncRNAs (DElncRNAs) and differentially expressed mRNAs (DEmRNAs) in our network. The GSE22255 dataset was used to confirm the diagnostic value of candidate genes. Results: In total, 199 DElncRNAs, 2068 DEmRNAs, and 96 differentially expressed miRNAs were detected. The GO analysis revealed that DEmRNAs primarily participate in neutrophil activation, neutrophil degranulation, vacuolar transport, and lysosomal transport. WGCNA screened out 16 lncRNAs and 195 mRNAs from DEGs, and only eight DElncRNAs maintained an area under the curve higher than 0.9. By investigating the relationships between lncRNAs and mRNAs, a ceRNA network containing three lncRNAs, three miRNAs, and seven mRNAs was constructed. GSE22255 confirmed that RP1-193H18.2 is more advantageous for diagnosing stroke, whereas no mRNA showed realistic diagnostic efficacy. Conclusion: The ceRNA network may broaden our understanding of AIS pathology, and the candidate lncRNA from the ceRNA network is assumed to be a promising therapeutic target and diagnostic biomarker for AIS.

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.