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Identification of biomarkers of venous thromboembolism by bioinformatics analyses.

Abstract Venous thromboembolism (VTE) is a common vascular disease and a major cause of mortality. This study intended to explore the biomarkers associated with VTE by bioinformatics analyses.Based on Gene Expression Omnibus (GEO) database, the GSE19151 expression profile data were downloaded. The differentially expressed genes (DEGs) between single VTE (sVTE)/recurrent VTE (rVTE) and control were identified. Then, pathway enrichment analysis of DEGs were performed, followed by protein-protein interaction (PPI) network construction.Total 433 upregulated and 222 downregulated DEGs were obtained between sVTE and control samples. For rVTE versus control, 625 upregulated and 302 downregulated DEGs were identified. The overlap DEGs were mainly enriched in the pathways related to ribosome, cancer, and immune disease. The DEGs specific to rVTE were enriched in several pathways, such as nod-like receptor signaling pathway. In the PPI network, 2 clusters of VTE genes, including ribosomal protein family genes and NADH family-ubiquinol-cytochrome genes, were identified, such as ribosomal protein L9 (RPL9), RPL5, RPS20, RPL23, and tumor protein p53 (TP53).The nod-like receptor signaling pathway, ribosomal protein family genes, such as RPL9, RPL5, RPS20, and RPL23, and DEG of TP53 may have the potential to be used as targets for diagnosis and treatment of VTE.
PMID
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Authors

Mayor MeshTerms

Genes, p53

Keywords
Journal Title medicine
Publication Year Start




PMID- 29620629
OWN - NLM
STAT- MEDLINE
DCOM- 20180416
LR  - 20180416
IS  - 1536-5964 (Electronic)
IS  - 0025-7974 (Linking)
VI  - 97
IP  - 14
DP  - 2018 Apr
TI  - Identification of biomarkers of venous thromboembolism by bioinformatics
      analyses.
PG  - e0152
LID - 10.1097/MD.0000000000010152 [doi]
AB  - Venous thromboembolism (VTE) is a common vascular disease and a major cause of
      mortality. This study intended to explore the biomarkers associated with VTE by
      bioinformatics analyses.Based on Gene Expression Omnibus (GEO) database, the
      GSE19151 expression profile data were downloaded. The differentially expressed
      genes (DEGs) between single VTE (sVTE)/recurrent VTE (rVTE) and control were
      identified. Then, pathway enrichment analysis of DEGs were performed, followed by
      protein-protein interaction (PPI) network construction.Total 433 upregulated and 
      222 downregulated DEGs were obtained between sVTE and control samples. For rVTE
      versus control, 625 upregulated and 302 downregulated DEGs were identified. The
      overlap DEGs were mainly enriched in the pathways related to ribosome, cancer,
      and immune disease. The DEGs specific to rVTE were enriched in several pathways, 
      such as nod-like receptor signaling pathway. In the PPI network, 2 clusters of
      VTE genes, including ribosomal protein family genes and NADH
      family-ubiquinol-cytochrome genes, were identified, such as ribosomal protein L9 
      (RPL9), RPL5, RPS20, RPL23, and tumor protein p53 (TP53).The nod-like receptor
      signaling pathway, ribosomal protein family genes, such as RPL9, RPL5, RPS20, and
      RPL23, and DEG of TP53 may have the potential to be used as targets for diagnosis
      and treatment of VTE.
FAU - Wang, Guiming
AU  - Wang G
AD  - Department of Vascular Surgery.
FAU - Zhao, Wenbo
AU  - Zhao W
AD  - Department of Vascular Surgery.
FAU - Yang, Yudong
AU  - Yang Y
AD  - Department of Vascular Surgery.
FAU - Yang, Gaochao
AU  - Yang G
AD  - Department of Vascular Surgery.
FAU - Wei, Zhigang
AU  - Wei Z
AD  - Department of Surgery, The First Hospital of Shanxi Medical University, Taiyuan, 
      PR, China.
FAU - Guo, Jiansheng
AU  - Guo J
AD  - Department of Surgery, The First Hospital of Shanxi Medical University, Taiyuan, 
      PR, China.
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Medicine (Baltimore)
JT  - Medicine
JID - 2985248R
RN  - 0 (Genetic Markers)
RN  - 0 (NLR Proteins)
RN  - 0 (Ribosomal Proteins)
RN  - 0U46U6E8UK (NAD)
SB  - AIM
SB  - IM
MH  - Computational Biology
MH  - Databases, Genetic
MH  - Down-Regulation
MH  - *Genes, p53
MH  - Genetic Markers/genetics
MH  - Humans
MH  - NAD/*genetics
MH  - NLR Proteins/*genetics
MH  - Protein Interaction Maps
MH  - Ribosomal Proteins/*genetics
MH  - Signal Transduction/genetics
MH  - Up-Regulation
MH  - Venous Thromboembolism/*genetics
EDAT- 2018/04/06 06:00
MHDA- 2018/04/17 06:00
CRDT- 2018/04/06 06:00
PHST- 2018/04/06 06:00 [entrez]
PHST- 2018/04/06 06:00 [pubmed]
PHST- 2018/04/17 06:00 [medline]
AID - 10.1097/MD.0000000000010152 [doi]
AID - 00005792-201804060-00007 [pii]
PST - ppublish
SO  - Medicine (Baltimore). 2018 Apr;97(14):e0152. doi: 10.1097/MD.0000000000010152.