Microarray profile of circular RNAs identifies hsa_circ_000455 as a new circular RNA biomarker for deep vein thrombosis

Lou, Zhenkai; Li, Xing; Li, Chengyong; Li, Xingguo; Du, Kaili; Zhang, Fan; Wang, Bing

doi:10.1177/17085381211016150

Cited by 3 publications

(3 citation statements)

References 37 publications

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“…Lou et al ( 16 ) have found that hsa_circ_000455 is a new circRNA biomarker for DVT in patients, according to microarray profiling. Their findings have indicated that certain circRNAs can be used as indicators of DVT.…”

Section: Discussionmentioning

confidence: 99%

“…To date, numerous studies have shown that circRNAs are closely associated with the diagnosis and treatment of cardiovascular diseases, and certain circRNAs have been identified as cardiovascular disease biomarkers (11)(12)(13)(14)(15). Recently, circRNAs have been reported to accelerate lower extremity DVT via sponging miRNA, thus regulating mRNA expression (16,17). Although circRNAs have been suggested to be involved in the pathogenesis and regulatory mechanism of DVT, few studies have examined the global dynamic changes in circRNAs and mRNAs during DVT progression.…”

Section: Introductionmentioning

confidence: 99%

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Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis

et al. 2023

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The goal of the present study was to identify different transcriptome expression profiles involved in the pathogenesis of deep vein thrombosis (DVT), and to illustrate the diagnostic and therapeutic potential of circular RNAs (circRNAs) and mRNAs in DVT progression. A Sprague-Dawley rat model of DVT was successfully established through the stenosis method and samples were sequenced at four time points (1, 6 and 12 h, and 3 days after ligation) to observe the dynamic changes in circRNAs and mRNAs during DVT progression. RNA sequencing was used to analyze the circRNA and mRNA expression profiles, and associated functions and pathways, in the blood of DVT rats at the four time points. In addition, Short Time Series Expression Miner (STEM) analysis was performed to explore temporal gene expression. Differential expression of 1,680, 4,018, 3,724, and 3,036 circRNAs, and 400, 1,176, 373, and 573 mRNAs was observed in the 1, 6 and 12 h, and 3-day groups, respectively, compared with the sham group (fold change >2.0 or <-2.0, P<0.05). Functional enrichment analysis indicated that differentially expressed mRNAs were associated with the following terms: Immune response, cell activation, blood stasis facilitated organelle, extracellular membrane-bounded organelle, and blood microparticle, oxygen transporter activity. STEM analysis indicated that the expression of 366 circRNAs in circRNA profile 45 and 270 mRNAs in mRNA profile 45 was consistent with thrombus progression. Enrichment analysis was performed on mRNA profile 45. The main Gene Ontology annotations were chromosome segregation, mitotic sister chromatid segregation, cell cycle process, and ligand-dependent nuclear receptor transcription coactivator activity. Pathway enrichment analysis identified the platelet-associated pathway, immune-associated pathway, and inflammation-relation pathway. According to the enriched platelet-associated pathways, four mRNAs and ten candidate circRNAs were selected for reverse transcription-quantitative PCR verification. The expression of nine of the ten circRNAs and all four mRNAs was consistent with the sequencing results. In summary, differentially expressed circRNAs and mRNAs are dynamically involved in DVT development. Dysregulated transcriptome profiles and the corresponding functions and pathways may provide mechanistic insights into DVT diagnosis and treatment.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis

et al. 2023

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“…Thyroid hormones may have non-genetic effects on the behavior of endothelial cells [17,18]. In a study regarding tumor thrombosis, Lou [19] found that 303 circular RNAs were differentially expressed in DVT using microarray. Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis revealed that the most significantly enriched pathways included thyroid hormone-signaling pathway and endocytosis, and also increased level of proteoglycans in cancer.…”

Section: Introductionmentioning

confidence: 99%

Associations between deep venous thrombosis and thyroid diseases: a two-sample bidirectional Mendelian randomization study

Zhang,

Li,

Yang

et al. 2024

Eur J Med Res

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Background Some previous observational studies have linked deep venous thrombosis (DVT) to thyroid diseases; however, the findings were contradictory. This study aimed to investigate whether some common thyroid diseases can cause DVT using a two-sample Mendelian randomization (MR) approach. Methods This two-sample MR study used single nucleotide polymorphisms (SNPs) identified by the FinnGen genome-wide association studies (GWAS) to be highly associated with some common thyroid diseases, including autoimmune hyperthyroidism (962 cases and 172,976 controls), subacute thyroiditis (418 cases and 187,684 controls), hypothyroidism (26,342 cases and 59,827 controls), and malignant neoplasm of the thyroid gland (989 cases and 217,803 controls. These SNPs were used as instruments. Outcome datasets for the GWAS on DVT (6,767 cases and 330,392 controls) were selected from the UK Biobank data, which was obtained from the Integrative Epidemiology Unit (IEU) open GWAS project. The inverse variance weighted (IVW), MR-Egger and weighted median methods were used to estimate the causal association between DVT and thyroid diseases. The Cochran’s Q test was used to quantify the heterogeneity of the instrumental variables (IVs). MR Pleiotropy RESidual Sum and Outlier test (MR-PRESSO) was used to detect horizontal pleiotropy. When the causal relationship was significant, bidirectional MR analysis was performed to determine any reverse causal relationships between exposures and outcomes. Results This MR study illustrated that autoimmune hyperthyroidism slightly increased the risk of DVT according to the IVW [odds ratio (OR) = 1.0009; p = 0.024] and weighted median methods [OR = 1.001; p = 0.028]. According to Cochran’s Q test, there was no evidence of heterogeneity in IVs. Additionally, MR-PRESSO did not detect horizontal pleiotropy (p = 0.972). However, no association was observed between other thyroid diseases and DVT using the IVW, weighted median, and MR-Egger regression methods. Conclusions This study revealed that autoimmune hyperthyroidism may cause DVT; however, more evidence and larger sample sizes are required to draw more precise conclusions.

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Hsa_circ_0001020 accelerates the lower extremity deep vein thrombosis via sponging miR-29c-3p to promote MDM2 expression

Lou¹,

Ma²,

Li³

et al. 2022

Thrombosis Research

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Microarray profile of circular RNAs identifies hsa_circ_000455 as a new circular RNA biomarker for deep vein thrombosis

Cited by 3 publications

References 37 publications

Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis

Dynamic observation of circRNA and mRNA profiles in a rat model of deep vein thrombosis

Associations between deep venous thrombosis and thyroid diseases: a two-sample bidirectional Mendelian randomization study

Hsa_circ_0001020 accelerates the lower extremity deep vein thrombosis via sponging miR-29c-3p to promote MDM2 expression

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