Genes associated with inflammation may serve as biomarkers for the diagnosis of coronary artery disease and ischaemic stroke.

BACKGROUND: The current research aimed to expound the genes and pathways that are involved in coronary artery disease (CAD) and ischaemic stroke (IS) and the related mechanisms. METHODS: Two array CAD datasets of (GSE66360 and GSE97320) and an array IS dataset (GSE22255) were downloaded. Differentially expressed genes (DEGs) were identified using the limma package. The online tool Database for Annotation, Visualization and Integrated Discovery (DAVID) (version 6.8; david.abcc.ncifcrf.gov) was used to annotate the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) enrichment analyses of the DEGs. A protein-protein interaction (PPI) network was constructed by Cytoscape software, and then Molecular Complex Detection (MCODE) analysis was used to screen for hub genes. The hub genes were also confirmed by RT-qPCR and unconditional logistic regression analysis in our CAD and IS patients. RESULTS: A total of 20 common DEGs (all upregulated) were identified between the CAD/IS and control groups. Eleven molecular functions, 3 cellular components, and 49 biological processes were confirmed by GO enrichment analysis, and the 20 common upregulated DEGs were enriched in 21 KEGG pathways. A PPI network including 24 nodes and 68 edges was constructed with the STRING online tool. After MCODE analysis, the top 5 high degree genes, including Jun proto-oncogene (JUN, degree = 9), C-X-C motif chemokine ligand 8 (CXCL8, degree = 9), tumour necrosis factor (TNF, degree = 9), suppressor of cytokine signalling 3 (SOCS3, degree = 8) and TNF alpha induced protein 3 (TNFAIP3, degree = 8) were noted. RT-qPCR results demonstrated that the expression levels of CXCL8 were increased in IS patients than in normal participants and the expression levels of SOCS3, TNF and TNFAIP were higher in CAD/IS patients than in normal participants. Meanwhile, unconditional logistic regression analysis revealed that the incidence of CAD or IS was positively correlated with the CXCL8, SOCS3, TNF and TNFAIP3. CONCLUSIONS: The CXCL8, TNF, SOCS3 and TNFAIP3 associated with inflammation may serve as biomarkers for the diagnosis of CAD or IS. The possible mechanisms may involve the Toll-like receptor, TNF, NF-kappa B, cytokine-cytokine receptor interactions and the NOD-like receptor signalling pathways.

A novel circRNA-miRNA-mRNA network identifies circ-YOD1 as a biomarker for coronary artery disease.

Circular RNAs (circRNAs) are involved in many physiological functions. Whether circulating circRNAs serve as markers for coronary artery disease (CAD) is unknown. Seven CAD-related microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database and were analyzed using clustering and functional enrichment to identify hub mRNAs and miRNAs. StarBase V3.0 and circinteractome databases were used to predict interactions between circRNAs and miRNAs whereas miRwalk and DIANA TOOLS were used to predict interactions between miRNAs and mRNAs. Altogether, this helped establish a circRNA-miRNA-mRNA triple network for diagnosis of CAD. Five non-coding RNAs (ncRNAs) were identified in our study population with the use of quantitative real-time PCR (RT-PCR). The prognostic values of circYOD1, hsa-miR-21-3p and hsa-miR-296-3p were evaluated using a receiver operating characteristic (ROC) curve. A CAD circRNA-miRNA-mRNA network was established from our analyses containing one circRNA, four miRNAs and thirteen mRNAs. After performing RT-PCR validation between CAD and non-CAD samples, only three ncRNAs of five ncRNAs showed significance for further analysis. The area under ROC curve (AUC) of circ-YOD1 was 0.824, the AUC of hsa-miR-21-3p was 0.731 and hsa-miR-296-3p was 0.776. The pairwise comparison results showed that circ-YOD1 had statistical significance (PYOD1-21 < 0.01 and PYOD1-296 < 0.05). The results of functional enrichment analysis of interacting genes and microRNAs showed that the shared circ-YOD1 may act as a new biomarker for CAD. Our investigation of the triple regulatory networks of circRNA-miRNA-mRNA in CAD revealed circ-YOD1 as a potential biomarker for CAD.

Prevalence of hypertension and associated risk factors in Chinese Jing compared with Mulao populations.

OBJECTIVE: *These authors contributed equally to this work. At present, they work at the Hezhou People's Hospital, Hezhou, China.To retrospectively compare differences in the prevalence of hypertension and associated risk factors between the Chinese Jing and Mulao populations. METHODS: Subjects of Jing and Mulao ethnicities were surveyed using stratified randomized sampling. Demography, diet and lifestyle data were collected using standardized questionnaires. Several anthropometric parameters, blood pressure (BP) levels and serum lipid concentrations were obtained. RESULTS: Data from 915 Jing and 911 Mulao subjects aged ≥ 35 years were included. Diastolic BP levels and prevalence of hypertension were lower, but prevalence of isolated systolic hypertension was higher, in the Jing compared with the Mulao population. Prevalence of hypertension in the age 60-69 years, body mass index (BMI) > 24 kg/m(2), and smoker subgroups was lower in the Jing compared with the Mulao populations. Prevalence of hypertension correlated with age, cigarette smoking, triglyceride level, waist circumference, sodium intake and total dietary fibre in the Jing population; hypertension prevalence also correlated with age, triglyceride level, BMI, total fat, sodium intake and total dietary fibre in the Mulao population (unconditional logistic regression analyses). CONCLUSIONS: Prevalence of hypertension and associated risk factors were different between the two ethnic minorities, which might result from the combined effects of differences in their geographic, dietary, lifestyle, and genetic backgrounds.

Serum lipid profiles, the prevalence of dyslipidemia and the risk factors in two isolated Chinese minorities.

Both Jing and Mulao nationalities are the isolated minorities in China. Little is known about the prevalence of dyslipidemia between the two ethnic groups. Therefore, the aim of this study was to compare the differences in serum lipid profiles, the prevalence of dyslipidemia and their risk factors between the Jing and Mulao populations. A cross-sectional study of dyslipidemia was conducted in Dongxing city, Guangxi, China, during Dec 2011 and Jan 2012. A total of 1254 subjects of Jing and 1251 participants of Mulao were surveyed by a stratified randomized sampling. Information on demography, diet and lifestyle was collected with standardized questionnaire. Serum lipid levels were detected using the commercially available kits. The levels of low-density lipoprotein cholesterol (LDL-C), apolipoprotein (Apo) A1, and the ratio of ApoA1 to ApoB were lower but the levels of ApoB were higher in Jing than in Mulao (P < 0.001 for all). The prevalence of hypertriglyceridemia (32.38% vs. 24.38%), high ApoB (35.25% vs. 15.35%) and low ApoA1/ApoB ratio (22.65% vs. 16.87%) was higher and low high-density lipoprotein cholesterol (0.48% vs. 2.16%), high LDL-C (17.54% vs. 40.53%) and low ApoA1 (5.98% vs. 11.43%) was lower in Jing than in Mulao (P < 0.001 for all). The risk factors for serum lipid parameters and hyperlipidemia were different between the two ethnic groups. Serum lipid profiles, the prevalence of dyslipidemia and their risk factors are different between the Jing and Mulao populations. These differences may result from the combined effects of different diet, lifestyle, and genetic factors.