Identification of differentially expressed non-coding RNAs and mRNAs involved in Qi stagnation and blood stasis syndrome

Abstract

Qi stagnation and blood stasis syndrome (QSBSS) is a common Zheng in Traditional Chinese Medicine (TCM), describes the condition of unsmooth flow of Qi and blood, which manifests as distending pain in a fixed body part and emotional disorders, including irritability and depression. However, the underlying molecular mechanisms remain largely elusive. RNAs are the connection between DNA and proteins, which reflect the interaction between the genotypes and the phenotype. Of note, non-coding (nc)RNA is a type of RNA that is not translated into any protein, but has regulatory functions. Despite the growing interest in exploring the biological basis of TCM Zhengs, the specific roles of ncRNAs in QSBSS have remained largely elusive. In the present study, next-generation sequencing was performed to investigate the ncRNA profile in patients with three different types of disease, but who had QSBSS. A total of 104 long non-coding RNAs, 2 circular RNAs and 697 mRNAs were identified to be significantly differentially expressed in QSBSS patients. Further bioinformatics analysis revealed that the most significantly enriched pathways by the differentially expressed RNAs in QSBSS were the sphingolipid signaling pathway, the neurotrophin signaling pathway, 5'AMP-activated protein kinase and endocytosis. In addition, a network pharmacology analysis indicated that several of the differentially expressed RNAs were included in the targets of TCM herbs for treating QSBSS. The present study was the first to identify ncRNAs that are deregulated in QSBSS by next-generation sequencing technology. The results may offer insight into the biological basis of TCM Zheng and the optimization of ancient formulae, as well as the discovery of novel drugs, to pave the way toward advanced TCM theory and improved health care delivery.

Keywords: Qi stagnation and blood stasis syndrome; Traditional Chinese Medicine; expression profiles; non-coding RNAs; sequencing.

Figure 1.

Volcano plot and clustering map of DE lncRNAs. Upper panel, volcano plots indicating up- and down-regulated lncRNAs for the comparison of the normal controls with groups (A) a, (B) b and (C) c. The respective heat maps presenting the hierarchical clustering of DE lncRNAs are displayed in the lower panel. Groups: a, QSBSS patients with coronary heart disease (n=5); b, QSBSS patients with chronic gastritis (n=5); c, QSBSS patients with rheumatoid arthritis (n=5). QSBSS, Qi stagnation and blood stasis syndrome; lncRNA, long non-coding RNA; DE, differentially expressed.

Figure 2.

Volcano plot and clustering map of DE circRNAs. Upper panel, volcano plots indicating up- and down-regulated circRNAs for the comparison of the normal controls with groups (A) a, (B) b and (C) c. The respective heat maps presenting the hierarchical clustering of DE circRNAs are displayed in the lower panel. Groups: a, QSBSS patients with coronary heart disease (n=5); b, QSBSS patients with chronic gastritis (n=5); c, QSBSS patients with rheumatoid arthritis (n=5). QSBSS, Qi stagnation and blood stasis syndrome; circRNA, circular RNA; DE, differentially expressed.

Figure 3.

Volcano plot and clustering map of DE mRNAs. Upper panel, volcano plots indicating up- and down-regulated mRNAs for the comparison of the normal controls with groups (A) a, (B) b and (C) c. The respective heat maps presenting the hierarchical clustering of DE mRNAs are displayed in the lower panel. Groups: a, QSBSS patients with coronary heart disease (n=5); b, QSBSS patients with chronic gastritis (n=5); c, QSBSS patients with rheumatoid arthritis (n=5). QSBSS, Qi stagnation and blood stasis syndrome; DE, differentially expressed.

Figure 4.

Venn diagram of overlapped DE lncRNAs, circRNAs and mRNAs. Venn diagrams displaying the number of overlapped up-regulated (upper panel) and down-regulated (lower panel) DE (A) lncRNAs, (B) circRNAs and (C) mRNAs among groups a, b and c. Groups: (a) QSBSS patients with coronary heart disease (n=5); (b) QSBSS patients with chronic gastritis (n=5); (c) QSBSS patients with rheumatoid arthritis (n=5). QSBSS, Qi stagnation and blood stasis syndrome; lncRNA, long non-coding RNA; circRNA, circular RNA; DE, differentially expressed.

Figure 5.

Analysis of DE RNAs by ClueGo. The enrichment analysis of DE RNAs was performed using ClueGo and the most significant terms are presented, where a higher score indicates a higher number of genes involved. The same color indicates that it was possible to cluster the respective terms. DE, differentially expressed.

Figure 6.

GO analysis of DE RNAs. The GO enrichment analysis of DE RNAs is represented by the pie charts. GO, gene ontology; DE, differentially expressed.

Figure 7.

Enriched Kyoto Encyclopedia of Genes and Genomes pathways. The pathway scatterplot displays the statistics of the pathway enrichment of the differentially expressed RNAs. MAPK, mitogen-activated protein kinase; NF, nuclear factor; Fox, forkhead box; AMPK, 5′AMP-activated protein kinase; NOD, nucleotide-binding oligomerization domain.

Figure 8.

Putative targets for Xuefu Zhuyu decoction, a treatment for Qi stagnation and blood stasis syndrome. The triangular nodes represent the screened ingredients and the circular nodes represent the predicted targets.

Figure 9.

Network of the targets of Xuefu Zhuyu decoction (treatment for QSBSS) and differentially expressed RNAs in QSBSS. The green triangular nodes represent active components, the green circular nodes represent targets and the red nodes represent shared targets of QSBSS and Xuefu Zhuyu Decoction. QSBSS, Qi stagnation and blood stasis syndrome.