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Identification of novel diagnostic biomarkers for deep venous thrombosis.

ABSTRACT: The combination of a negative D-dimer and a Wells score can rule out, but not confirm, a diagnosis of deep venous thrombosis (DVT). We aimed to identify new diagnostic biomarkers for DVT and to investigate their relationship with hypercoagulability markers [D-dimer and activated protein C-protein C inhibitor (APC-PCI) complex]. We screened 92 cardiovascular-specific proteins in plasma samples from 45 confirmed DVT patients and 45 age- and sex-matched non-DVT patients selected from a prospective multicentre diagnostic management study (SCORE) by Proseek Multiplex CVDIII96×96 . Plasma levels of 30 proteins were significantly different between DVT and non-DVT patients. After Bonferroni correction, plasma levels of seven proteins: P-selectin, transferrin receptor protein 1, von Willebrand factor, tissue factor pathway inhibitor, osteopontin (OPN), bleomycin hydrolase and ST2 protein remained significantly different. The area under curve (AUC) for these proteins ranged from 0·70 to 0·84. Furthermore, all seven identified proteins were significantly associated with markers of hypercoagulability. A combination of OPN and APC-PCI had the best ability to discriminate DVT from non-DVT patients (AUC = 0·94; sensitivity = 89% and specificity = s84%). In conclusion, we identified multiple proteins associated with markers of hypercoagulability and with a potential to become novel diagnostic biomarkers for DVT.

SUBMITTER: Memon AA

PROVIDER: S-EPMC5918233 | biostudies-literature | 2018 May

REPOSITORIES: biostudies-literature

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Identification of novel diagnostic biomarkers for deep venous thrombosis.

Memon Ashfaque A AA Sundquist Kristina K PirouziFard Mirnabi M Elf Johan L JL Strandberg Karin K Svensson Peter J PJ Sundquist Jan J Zöller Bengt B

British journal of haematology 20180419 3

The combination of a negative D-dimer and a Wells score can rule out, but not confirm, a diagnosis of deep venous thrombosis (DVT). We aimed to identify new diagnostic biomarkers for DVT and to investigate their relationship with hypercoagulability markers [D-dimer and activated protein C-protein C inhibitor (APC-PCI) complex]. We screened 92 cardiovascular-specific proteins in plasma samples from 45 confirmed DVT patients and 45 age- and sex-matched non-DVT patients selected from a prospective ...[more]

PMID: 29672822

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Project description:Purpose: To explore the possible pathogenesis of venous thromboembolism from the perspective of circRNAs. Methods: The thrombus model of inferior vena cava in SD rats was established by stenosis method. Peripheral blood samples of DVT rats were collected at 1h, 6h,12h and 3d, which were sequenced with Illumina circRNAs and mRNA. The differential circRNAs and mRNA were analyzed by STEM analysis software. Clusters that can reflect the evolution of thrombus were selected for in-depth analysis, and circRNAs and mRNA were screened according to the pathway enrichment analysis of the selected clusters. Real time fluorescent quantitative PCR (qPCR) was used to verify and determine the candidate circRNAs and mRNA. The function of target circRNA was verified in DVT rats. The interacting miRNAs of circRNAs and mRNA were predicted by online database respectively. Candidate miRNAs were identified by integrating the related information of miRNAs and verified by qPCR. Results:The SD rat model of deep venous thrombosis was successfully established by the stenosis method. In model group, there were 736, 3691, 3406 and 2639 circRNAs up-regulated and 944, 327, 318 and 397 circRNAs down-regulated at 1h, 6h, 12h and 3d, respectively. Compared with Sham group, 169, 885, 298 and 500 mRNA were up-regulated and 231, 291,75 and 73 mRNA were down-regulated at 1h, 6h, 12h and 3d in model group, respectively. STEM analysis found that cluster 45 was similar to thrombus development. The pathway related to platelet function was selected in cluster 45, and 10 circrRNAs and 4 interacting mRNAs were selected for qPCR verification by combining the gene in platelet pathway and annotation gene of cluster 45 and mRNA-circRNA interaction network. According to qPCR results and whether ID is found in rat circRNA database (CIRCpedia-V2), CBT15_circR_3235 (ID in circpedia-v2: rno_CIRCpedia_1953) is determined as the target circRNA. In vivo，knockdown of rno_CIRCpedia_1953 attenuates the formation of DVT in rats. The potential target miRNAs of rno_CIRCpedia_1953 and Tuba4a were predicted by using online miRDB and miRWalk databases respectively, and rno-miR-3543, rno-miR-320-5p and rno-miR-26b-3p are preliminarily identified as potential target miRNAs that rno_CIRCpedia_1953 may combine to play the ceRNA mechanism. Conclusions: Animal model of DVT in rats was successfully established by stenosis method. High-throughput sequencing analysis of circRNAs showed that circRNAs participated in the evolution of DVT. According to STEM functional analysis of mRNA sequencing, a target circRNA rno_CIRCpedia _1953 was screened, verified and identified. rno_CIRCpedia_1953 may participate in the development of DVT by acting as miRNA molecular sponge.

Dataset Information

Identification of novel diagnostic biomarkers for deep venous thrombosis.

Publications

Identification of novel diagnostic biomarkers for deep venous thrombosis.

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