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Bioinformatics analysis of transcriptome related to blood stasis syndrome in diabetes mellitus patients

ABSTRACT: Bioinformatics analysis of transcriptome related to blood stasis syndrome in diabetes mellitus patients

PROVIDER: PRJNA430257 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR6496430_1.fastq.gz	Fastqsanger.gz
	SRR6496430_2.fastq.gz	Fastqsanger.gz
	SRR6496440_1.fastq.gz	Fastqsanger.gz
	SRR6496440_2.fastq.gz	Fastqsanger.gz
	SRR6496450.fastq.gz	Fastqsanger.gz

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Bioinformatics analysis of transcriptome related to blood stasis syndrome in diabetes mellitus patients

Project description:In traditional Chinese medicine (TCM), blood stasis syndrome (BSS) is mainly manifested by the increase of blood viscosity, platelet adhesion rate and aggregation, and the change of microcirculation, resulting in vascular endothelial injury. It is an important factor in the development of diabetes mellitus (DM). According to the differences in the internal and external environment of the individual disease, BSS were divided into qi-deficiency and blood stasis syndrome (QDBS), qi-stagnation and blood stasis syndrome (QSBS), cold-coagulation and blood stasis syndrome (CCBS), heat-accumulation and blood stasis syndrome (HABS). The aim of this study was to screen out the potential candidate mRNAs in DM patients with BSS by high-throughput sequencing (HTS) and bioinformatics analysis. CRL-1730 human umbilical vein endothelial cells (HUVECs) were incubated with 10% human serum to establish models of DM with BSS, DM without BSS (NBS) and normal control (NC). Total RNA of each sample was extracted and sequenced by the Hiseq2000 platform. Differentially expressed mRNAs (DE-mRNAs) were screened between samples. On the basis of mRNA expression profiles, four comparisons were made, including QDBS vs NBS and NC, QSBS vs NBS and NC, CCBS vs NBS and NC, HABS vs NBS and NC. Then, comparisons with P values <0.05 (Fisher's exact test), false discovery rates (FDR) <0.01 and |log2 ratios|≥1 were considered as DE-mRNAs in BSS. This study screened out the DE-mRNAs in DM patients with BSS by HTS and bioinformatics analysis.

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Bioinformatics analysis of microRNAs related to blood stasis syndrome in diabetes mellitus patients

Project description:Bioinformatics analysis of microRNAs related to blood stasis syndrome in diabetes mellitus patients

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Project description:In traditional Chinese medicine (TCM), blood stasis syndrome (BSS) is mainly manifested by the increase of blood viscosity, platelet adhesion rate and aggregation, and the change of microcirculation, resulting in vascular endothelial injury. It is an important factor in the development of diabetes mellitus (DM). The aim of the present study was to screen out the potential candidate microRNAs (miRNAs) in DM patients with BSS by high-throughput sequencing (HTS) and bioinformatics analysis. Human umbilical vein endothelial cells (HUVECs) were incubated with 10% human serum to establish models of DM with BSS, DM without BSS (NBS), and normal control (NC). Total RNA of each sample was extracted and sequenced by the Hiseq2000 platform. Differentially expressed miRNAs (DE-miRNAs) were screened between samples and compared with known changes in mRNA abundance. Target genes of miRNAs were predicted by softwares. Gene Ontology (GO) and pathway enrichment analysis of the target genes were conducted. According to the significantly enriched GO annotations and pathways (P-value ≤ 0.001), we selected the key miRNAs of DM with BSS. It showed that the number of DE-miRNAs in BSS was 32 compared with non-blood stasis syndrome (NBS) and NC. The potential candidate miRNAs were chosen from GO annotations in which target genes were significantly enriched (-log10 (P-value) > 5), which included miR-140-5p, miR-210, miR-362-5p, miR-590-3p, and miR-671-3p. The present study screened out the potential candidate miRNAs in DM patients with BSS by HTS and bioinformatics analysis. The miRNAs will be helpful to provide valuable suggestions on clinical studies of DM with BSS at the gene level.

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