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. 2017 Dec 4;8(67):111608-111622.
doi: 10.18632/oncotarget.22877. eCollection 2017 Dec 19.

Differential gene expression profiles between two subtypes of ischemic stroke with blood stasis syndromes

Affiliations

Differential gene expression profiles between two subtypes of ischemic stroke with blood stasis syndromes

Tian-Long Liu et al. Oncotarget. .

Abstract

Ischemic stroke is a cerebrovascular thrombotic disease with high morbidity and mortality. Qi deficiency blood stasis (QDBS) and Yin deficiency blood stasis (YDBS) are the two major subtypes of ischemic stroke according to the theories of traditional Chinese medicine. This study was conducted to distinguish these two syndromes at transcriptomics level and explore the underlying mechanisms. Male rats were randomly divided into three groups: sham group, QDBS/MCAO group and YDBS/MCAO group. Morphological changes were assessed after 24 h of reperfusion. Microarray analysis with circulating mRNA was then performed to identify differential gene expression profile, gene ontology and pathway enrichment analyses were carried out to predict the gene function, gene co-expression and pathway networks were constructed to identify the hub biomarkers, which were further validated by western blotting and Tunel staining analysis. Three subsets of dysregulated genes were acquired, including 445 QDBS-specific genes, 490 YDBS-specific genes and 1676 blood stasis common genes. Our work reveals for the first time that T cell receptor, MAPK and apoptosis pathway were identified as the hub pathways based on the pathway networks, while Nfκb1, Egfr and Casp3 were recognized as the hub genes by co-expression networks. This research helps contribute to a clearer understanding of the pathological characteristics of ischemic stroke with QDBS and YDBS syndrome, the proposed biomarkers might provide insight into the accurate diagnose and proper treatment for ischemic stroke with blood stasis syndrome.

Keywords: blood stasis syndrome; ischemic stroke; network analysis; traditional Chinese medicine; transcriptomics.

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Conflict of interest statement

CONFLICTS OF INTEREST The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1. The flowchart of model establishment, microarray and bioinformatics analysis in this study
Figure 2
Figure 2. The morphological changes of ischemic stroke rats with QDBS or YDBS syndrome
(A) The neurologic score of rats after 24 h reperfusion (n=12). (B) The brain infarct volume after the neurological tests (n=6). (C) Whole blood viscosity (WBV) of shear rates’ varying from 1 to 200/s (n=6). (D) Coagulation parametersof plasma (n=6). The left Y-axis represents PT, TT and APTT value. The right Y-axis represents FIB value. Data presented as mean ±SD. *P < 0.05, **P < 0.01 compared with control group. Histopathological observation of cerebral cortex (E) and thoracic aorta (F).
Figure 3
Figure 3. The differentially expressed genes (DEGs) among the groups
Hierarchical clustering between QDBS (A) or YDBS (B) and control group. Green color represent down-regulated genes, red color represent up-regulated genes (P<0.05). Validation of a subset of genes differentially expressed between QDBS (C) or YDBS (D) and control group by qPCR. White bars represent the fold change at the expression level as indicated by microarray analysis; black bars represent the mean fold change of gene expression calculated by qPCR method. Values are the mean ± SEM (n = 6). The Venn diagram of up-regulated (E) and down-regulated (F) genes between QDBS/control and YDBS/control.
Figure 4
Figure 4. Histogram of GO and pathway enrichment analyses of dysregulated genes
GO analysis of QDBS-specific genes (A), YDBS-specific genes (C) and overlapping genes (E). Pathway analysis of QDBS-specific genes (B), YDBS-specific genes (D) and overlapping genes (F). X axis, negative logarithm of the P-value (− LgP). Y axis, name of the GO or pathway items.
Figure 5
Figure 5. The interaction net of the significant pathways
The pathway relation network of QDBS-specific genes (A), YDBS-specific genes (B) and overlapping genes (C). Nodes represent pathways. The area of nodes displays the degree that is the number of other genes that interact with this gene. Lines indicate interactions between pathways, where pathways indicated by the arrowhead are regulated by pathways of the arrow tail. Red nodes represent up-regulated pathways, blue nodes represent down-regulated pathways, and yellow nodes represent the up/down-regulated pathways. Nodes with black borders indicate the hub pathways identified by networks.
Figure 6
Figure 6. The co-expression network analysis of differentially expressed genes
The co-expression network of QDBS-specific genes (A), YDBS-specific genes (B) and overlapping genes (C). Nodes denote genes; Lines represent gene-gene interrelation; the size of the nodes represents the degree value. Red nodes represent up-regulated genes, dark blue nodes represent down-regulated genes, and yellow nodes represent the up/down-regulated genes. Nodes with black borders indicate the hub genes identified by networks.
Figure 7
Figure 7. Validation of the hub genes and pathways
Expression of NF-κB p50 and EGFR in brain tissue (A) and thoracic aorta (B) were detected by western blotting. The relative expression levels of p50 (C) and EGFR (D). Tunel staining of cerebral cortex (E) and thoracic aorta (F). Quantitative analyses of TUNEL-positive cells in brain tissue (G) and thoracic aorta (H). Error bars: ± S.D (n=6). *P < 0.05, **P < 0.01 compared with control group. #P < 0.05 compared with another model group.

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