Identification of biomarkers of venous thromboembolism by bioinformatics analyses

CREB1 Silencing Protects Against Inflammatory Response in Rats with Deep Vein Thrombosis Through Reducing RPL9 Expression and Blocking NF-κB Signaling

Apoptosis and inflammation of vascular endothelial cells (VECs) are the most important causes of deep vein thrombosis (DVT). cAMP response element binding protein 1 (CREB1) encodes a transcription factor that binds as a homodimer to the cAMP-responsive element and can promote inflammation. CREB1 is found to be upregulated in the plasma of patients with venous thromboembolism. However, the biological functions of CREB1 in DVT remain unknown. We evaluated the effect of CREB1 in a rat model of inferior vena cava (IVA) stenosis-induced DVT. IVC stenosis resulted in stable thrombus, inflammatory response and CREB1 upregulation, whereas CREB1 knockdown inhibited thrombus and inflammation in DVT rats. In vitro analysis showed that CREB1 knockdown inhibited VEC apoptosis. Mechanistically, CREB1 knockdown reduced Ribosomal protein L9 (RPL9) expression and blocked the NF-κB pathway. Therefore, CREB1 may become a potential therapeutic target of DVT prevention.

Deep sequencing of circulating miRNAs and target mRNAs level in deep venous thrombosis patients

Deep venous thrombosis is one of the most common peripheral vascular diseases that lead to major morbidity and mortality. The authors aimed to identify potential differentially expressed miRNAs and target mRNAs, which were helpful in understanding the potential molecule mechanism of deep venous thrombosis. The plasma samples of patients with deep venous thrombosis were obtained for the RNA sequencing. Differentially expressed miRNAs were identified, followed by miRNA-mRNA target analysis. Enrichment analysis was used to analyze the potential biological function of target mRNAs. GSE19151 and GSE173461 datasets were used for expression validation of mRNAs and miRNAs. 131 target mRNAs of 21 differentially expressed miRNAs were identified. Among which, 8 differentially expressed miRNAs including hsa-miR-150-5p, hsa-miR-326, hsa-miR-144-3p, hsa-miR-199a-5p, hsa-miR-199b-5p, hsa-miR-125a-5p, hsa-let-7e-5p and hsa-miR-381-3p and their target mRNAs (PRKCA, SP1, TP53, SLC27A4, PDE1B, EPHB3, IRS1, HIF1A, MTUS1 and ZNF652) were found associated with deep venous thrombosis for the first time. Interestingly, PDE1B and IRS1 had a potential diagnostic value for patients. Additionally, 3 important signaling pathways including p53, PI3K-Akt and MAPK were identified in the enrichment analysis of target mRNAs (TP53, PRKCA and IRS1). Identified circulating miRNAs and target mRNAs and related signaling pathways may be involved in the process of deep venous thrombosis.

Integrated bioinformatics analysis identifies microRNA-200a-5p as a new plasma marker in patient with venous thromboembolism

AIMS

Venous thromboembolism (VTE) is a major global health problem with high incidence and mortality. Vein endothelial cell (VEC) dysfunction is the primary cause of VTE. MicroRNAs (miRNAs) assist in the regulation of VEC functional pathways. Our objective was to identify potential miRNA target genes associated with VTE.

MATERIALS AND METHODS

To explore the association between mRNAs and miRNAs in VTE, we performed mRNA or miRNA microarray analysis and experiments in vitro. In addition, five online bioinformatics tools identified the target genes of differentially expressed miRNAs, and miRNA-gene network was constructed. As a result, hub miRNA and mRNA were confirmed. Finally, wound healing assay and transwell migration assay were performed to elucidate the effect of hub miRNA in VEC. Luciferase reporter assay and real-time quantitative polymerase chain reaction (RT-qPCR) were performed to decide the role of miRNA in the expression of hub mRNA.

RESULTS

Screening identified eight overlapping dysregulated genes in patients with VTE, three of which demonstrated significantly decreased expression of miR-200a-5p. Low expression miR-200a-5p in VTE patients is confirmed by ROC analysis (AUC=0.800, P=0.023) and binary logistic regression (OR=0.359, 95% confidence interval: 0.605-0.995). RT-qPCR results showed that miR-200a-5p level was decreased in hypoxia VEC (P=0.038). MiR-200a-5p significantly promoted the migration ability of VEC. The result of Dual-luciferase reporter assay showed that cytochrome coxidaseⅦc(COX7C) directly inhibit the miR-200a-5p expression by binding 5'UTR of miR-200a-5p (P=0.011).

CONCLUSIONS

We anticipate that miR-200a-5p-COX7C pair might be involved in the progression of VTE. Moreover, miR-200a-5p might be a therapeutic target for VTE.

Identification of four hub genes in venous thromboembolism via weighted gene coexpression network analysis

Background

The pathogenic mechanisms of venous thromboembolism (VT) remain to be defined. This study aimed to identify differentially expressed genes (DEGs) that could serve as potential therapeutic targets for VT.

Methods

Two human datasets (GSE19151 and GSE48000) were analyzed by the robust rank aggregation method. Gene ontology and Kyoto encyclopedia of genes and genomes pathway enrichment analyses were conducted for the DEGs. To explore potential correlations between gene sets and clinical features and to identify hub genes, we utilized weighted gene coexpression network analysis (WGCNA) to build gene coexpression networks incorporating the DEGs. Then, the levels of the hub genes were analyzed in the GSE datasets. Based on the expression of the hub genes, the possible pathways were explored by gene set enrichment analysis and gene set variation analysis. Finally, the diagnostic value of the hub genes was assessed by receiver operating characteristic (ROC) analysis in the GEO database.

Results

In this study, we identified 54 upregulated and 10 downregulated genes that overlapped between normal and VT samples. After performing WGCNA, the magenta module was the module with the strongest negative correlation with the clinical characteristics. From the key module, FECH, GYPA, RPIA and XK were chosen for further validation. We found that these genes were upregulated in VT samples, and high expression levels were related to recurrent VT. Additionally, the four hub genes might be highly correlated with ribosomal and metabolic pathways. The ROC curves suggested a diagnostic value of the four genes for VT.

Conclusions

These results indicated that FECH, GYPA, RPIA and XK could be used as promising biomarkers for the prognosis and prediction of VT.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12872-021-02409-4.

Identification of genes, pathways and transcription factor-miRNA-target gene networks and experimental verification in venous thromboembolism

Venous thromboembolism (VTE) is a complex, multifactorial life-threatening disease that involves vascular endothelial cell (VEC) dysfunction. However, the exact pathogenesis and underlying mechanisms of VTE are not completely clear. The aim of this study was to identify the core genes and pathways in VECs that are involved in the development and progression of unprovoked VTE (uVTE). The microarray dataset GSE118259 was downloaded from the Gene Expression Omnibus database, and 341 up-regulated and 8 down-regulated genes were identified in the VTE patients relative to the healthy controls, including CREB1, HIF1α, CBL, ILK, ESM1 and the ribosomal protein family genes. The protein–protein interaction (PPI) network and the transcription factor (TF)-miRNA-target gene network were constructed with these differentially expressed genes (DEGs), and visualized using Cytoscape software 3.6.1. Eighty-nine miRNAs were predicted as the targeting miRNAs of the DEGs, and 197 TFs were predicted as regulators of these miRNAs. In addition, 237 node genes and 4 modules were identified in the PPI network. The significantly enriched pathways included metabolic, cell adhesion, cell proliferation and cellular response to growth factor stimulus pathways. CREB1 was a differentially expressed TF in the TF-miRNA-target gene network, which regulated six miRNA-target gene pairs. The up-regulation of ESM1, HIF1α and CREB1 was confirmed at the mRNA and protein level in the plasma of uVTE patients. Taken together, ESM1, HIF1α and the CREB1-miRNA-target genes axis play potential mechanistic roles in uVTE development.

Genetic Variants of RPL5 and RPL9 Genes among Saudi Patients Diagnosed with Thrombosis

BACKGROUND

Thrombosis directly affects the quality of life with increased mortality. The RPL5 (L5) gene on intron 6 on chromosome 1p22, rs6604026 is associated with multiple sclerosis risk, whereas RPL9 (L9) on 8 exons on chromosome 4p14 has been documented so far as being an essential involvement in the proliferation of protein synthesized cells mostly by gene products.

OBJECTIVE

The aim of this work was to assess genetic variants of RPL5 and RPL9 and thrombosis to characterize their role in the diagnosis of thrombosis among the Saudi population.

METHODS

The cross-sectional study involved 100 Saudi patients diagnosed with thrombosis (arterial or venous) in 50 healthy individuals as controls in the same age and sex groups. Primers were designed RPL5 and RPL9 for molecular analysis. The Sanger System ABI-3730xL (Hong Kong) automatic sequencing was used for DNA sequencing. Statistical analysis was performed using the Prism 5 and SPSS version-21 programs.

RESULTS

The male / female age ratio was 66.7 / 57.4, and the mean age was 61.2 years. Most of the patients were self-identifiable and without a previous history of thrombosis (61.0%). Most of the patients had just been diagnosed, that is, in the last five years (74.0%), about 43% of the patients underwent treatment using combination therapy (Aspirin and oral anticoagulants). New gene variants of RPL5 (5 SNPs) and RPL9 (9 SNPs) were detected in Saudi thrombotic patients.

CONCLUSION

Mutations in RPL5 and RPL9 were reported in all thrombotic patients, represented by a new variant of the ribosomal protein gene and correlated with thrombosis in the Saudi population. These results may reflect an association between the ribosomal protein SNP gene and the incidence and progression of thrombosis in the Saudi population.

Venous thromboembolic events in T-cell lymphoma patients: Incidence, risk factors and clinical features

INTRODUCTION

Patients with hematologic malignancies are prone to developing thromboembolism. The incidence, risk factors and clinical features for developing venous thromboembolism (VTE) are not well-elucidated in patients with T-cell lymphoma.

MATERIALS AND METHODS

The present study retrospectively analyzed 668 patients with VTE, including pulmonary embolism (PE) and deep vein thrombosis (DVT), who were admitted to Tianjin Medical University Cancer Institute and Hospital and Sun Yat-sen University Cancer Center from January 2006 to December 2018. All patients were diagnosed with T-cell lymphoma, and all episodes of symptomatic VTE were confirmed by imaging and ultrasound. The follow-up results were obtained through telephone communication and outpatient visits.

RESULTS

A total of 668 patients were analyzed. Thirty-three (4.94%) patients had at least one episode of VTE, and all of which were deep vein thrombosis alone. All VTEs occurred in patients who received chemotherapy, while no VTE occurred in patients who did not receive chemotherapy. By univariate analysis, central venous catheter (CVC) (odds ratio [OR] 6.63, confidence interval [CI] 2.24-19.57, P = 0.001), Eastern Cooperative Oncology Group (ECOG) performance status 2, 3, or 4 (OR: 62.15, CI: 15.42-250.48, P = 0.000), and stage III or IV (OR: 4.06, CI: 1.00-16.40, P = 0.049) were identified as risk factors for developing VTE. By multivariate analysis, CVC (OR: 3.23, CI: 1.49-7.23, P = 0.003) and stage III or IV (OR: 2.30, CI: 1.06-4.97, P = 0.035) were still significant risk factors for developing VTE.

CONCLUSION

The incidence of VTE in the present study population was comparable to that of lymphoma patients, other than T-cell lymphoma, and VTE was associated with CVC and advanced stage.

High-dimensionality Data Analysis of Pharmacological Systems Associated with Complex Diseases

It is widely accepted that molecular reductionist views of highly complex human physiologic activity, e.g., the aging process, as well as therapeutic drug efficacy are largely oversimplifications. Currently some of the most effective appreciation of biologic disease and drug response complexity is achieved using high-dimensionality (H-D) data streams from transcriptomic, proteomic, metabolomics, or epigenomic pipelines. Multiple H-D data sets are now common and freely accessible for complex diseases such as metabolic syndrome, cardiovascular disease, and neurodegenerative conditions such as Alzheimer's disease. Over the last decade our ability to interrogate these high-dimensionality data streams has been profoundly enhanced through the development and implementation of highly effective bioinformatic platforms. Employing these computational approaches to understand the complexity of age-related diseases provides a facile mechanism to then synergize this pathologic appreciation with a similar level of understanding of therapeutic-mediated signaling. For informative pathology and drug-based analytics that are able to generate meaningful therapeutic insight across diverse data streams, novel informatics processes such as latent semantic indexing and topological data analyses will likely be important. Elucidation of H-D molecular disease signatures from diverse data streams will likely generate and refine new therapeutic strategies that will be designed with a cognizance of a realistic appreciation of the complexity of human age-related disease and drug effects. We contend that informatic platforms should be synergistic with more advanced chemical/drug and phenotypic cellular/tissue-based analytical predictive models to assist in either de novo drug prioritization or effective repurposing for the intervention of aging-related diseases. SIGNIFICANCE STATEMENT: All diseases, as well as pharmacological mechanisms, are far more complex than previously thought a decade ago. With the advent of commonplace access to technologies that produce large volumes of high-dimensionality data (e.g., transcriptomics, proteomics, metabolomics), it is now imperative that effective tools to appreciate this highly nuanced data are developed. Being able to appreciate the subtleties of high-dimensionality data will allow molecular pharmacologists to develop the most effective multidimensional therapeutics with effectively engineered efficacy profiles.