CXCR4 and TYROBP mediate the development of atrial fibrillation via inflammation.

Atrial fibrillation (AF) is a rapid supraventricular arrhythmia. However, the pathogenesis of atrial fibrillation remains controversial. We obtained transcriptome expression profiles GSE41177, GSE115574 and GSE79768 from GEO database. WGCNA was performed, DEGs were screened, PPI network was constructed using STRING database. CTD database was used to identify the reference score of hub genes associated with cardiovascular diseases. Prediction of miRNAs of hub genes was performed by TargetScan. DIANA-miRPath v3.0 was applied to make functional annotation of miRNA. The animal model of atrial fibrillation was constructed, RT-PCR was used to verify the expression of hub genes. Immunofluorescence assay for THBS2 and VCAN was made to identify molecular. Design of BP neural network was made to explore the prediction relationship of CXCR4 and TYROBP on AF. The merged datasets contained 104 up-regulated and 34 down-regulated genes. GO and KEGG enrichment analysis results of DEGs showed they were mainly enriched in 'regulation of release of sequestered calcium ion into cytosol', 'actin cytoskeleton organization' and 'focal adhesion'. The hub genes were CXCR4, SNAI2, S100A4, IGFBP3, CSNK2A1, CHGB, VCAN, APOE, C1QC and TYROBP, which were up-regulated expression in the AF compared with control tissues. There was strong correlation among the CXCR4, TYROBP and AF based on the BP neural network. Through training, best training performance is 9.6474e-05 at epoch 14, and the relativity was 0.99998. CXCR4 and TYROBP might be involved in the development of atrial fibrillation by affecting inflammation-related signalling pathways and may serve as targets for early diagnosis and preventive treatment.

Identification of biomarkers in macrophages of atherosclerosis by microarray analysis.

BACKGROUND: Atherosclerotic cardiovascular disease (ASCVD) refers to a series of diseases caused by atherosclerosis (AS). It is one of the most important causes of death worldwide. According to the inflammatory response theory, macrophages play a critical role in AS. However, the potential targets associated with macrophages in the development of AS are still obscure. This study aimed to use bioinformatics tools for screening and identifying molecular targets in AS macrophages. METHODS: Two expression profiling datasets (GSE7074 and GSE9874) were obtained from the Gene Expression Omnibus dataset, and differentially expressed genes (DEGs) between non-AS macrophages and AS macrophages were identified. Functional annotation of the DEGs was performed by analyzing the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases. STRING and Cytoscape were employed for constructing a protein-protein interaction network and analyzing hub genes. RESULTS: A total of 98 DEGs were distinguished between non-AS macrophages and AS macrophages. The functional variations in DEGs were mainly enriched in response to hypoxia, respiratory gaseous exchange, protein binding, and intracellular, ciliary tip, early endosome membrane, and Lys63-specific deubiquitinase activities. Three genes were identified as hub genes, including KDELR3, CD55, and DYNC2H1. CONCLUSION: Hub genes and DEGs identified by using microarray techniques can be used as diagnostic and therapeutic biomarkers for AS.

WGCNA Identification of Genes and Pathways Involved in the Pathogenesis of Postmenopausal Osteoporosis.

PURPOSE: Postmenopausal osteoporosis (PMO) patients may suffer from chronic pain and increased fractures due to brittle bones that seriously affect their normal work and life. Exploring the pathogenesis of PMO can help clinicians construct individualized therapeutic targets. METHODS: Differentially expressed genes (DEGs) were identified by analyzing the microarray assays of monocytes from 20 PMO and 20 control samples. Weighted correlation network analysis (WGCNA) and gene set enrichment analysis (GAEA) were performed. Genes associated with PMO were identified in the Comparative Toxicogenomics Database (CTD). miRNAs associated with osteoporosis were found in miRNet, and target genes were predicted. Hub genes and functional pathways associated with PMO were also identified. miRNA-mRNA networks were constructed. The association between hub genes and PMO was analyzed in the CTD. RESULTS: A total of 1055 genes were up-regulated, and 694 genes were down-regulated in PMO samples (P<0.01). Five modules were identified by WGCNA. The blue module was significantly associated with PMO and selected for further analysis (P < 0.05). A total of 229 genes were significantly associated with PMO gene significance and module membership. Pathway variations were predominantly enriched in mRNA metabolic process, RNA splicing, Notch signaling pathway, apoptosis, cytokine-cytokine receptor interaction and so on. We identified 10 hub genes associated with PMO with different inference scores. CONCLUSION: We identified genes, miRNAs, and pathways associated with PMO. These molecules may participate in the pathogenesis of PMO and serve as therapeutic targets.

Bioinformatics Analysis of Genes and Mechanisms in Postherpetic Neuralgia.

Objective: Elderly patients are prone to postherpetic neuralgia (PHN), which may cause anxiety, depression, and sleep disorders and reduce quality of life. As a result, the life quality of patients was seriously reduced. However, the pathogenesis of PHN has not been fully elucidated, and current treatments remain inadequate. Therefore, it is important to explore the molecular mechanism of PHN. Methods: We analyzed the GSE64345 dataset, which includes gene expression from the ipsilateral dorsal root ganglia (DRG) of PHN model rats. Differentially expressed genes (DEGs) were identified and analyzed by Gene Ontology. Protein-protein interaction (PPI) network was constructed. The miRNA associated with neuropathic pain and inflammation was found in miRNet. Hub genes were identified and analyzed in Comparative Toxicogenomics Database (CTD). miRNA-mRNA networks associated with PHN were constructed. Results: A total of 116 genes were up-regulated in the DRG of PHN rats, and 135 genes were down-regulated. Functional analysis revealed that variations were predominantly enriched for genes involved in neuroactive ligand-receptor interactions, the Jak-STAT signaling pathway, and calcium channel activity. Eleven and thirty-one miRNAs associated with neuropathic pain and inflammation, respectively, were found. Eight hub genes (S1PR1, OPRM1, PDYN, CXCL3, S1PR5, TBX5, TNNI3, MYL7, PTGDR2, and FBXW2) associated with PHN were identified. Conclusions: Bioinformatics analysis is a useful tool to explore the mechanism and pathogenesis of PHN. The identified hub genes may participate in the onset and development of PHN and serve as therapeutic targets.

Identification of Co-expressed Genes Between Atrial Fibrillation and Stroke.

Atrial fibrillation (AF) increases the risk of ischemic stroke and systemic arterial embolism. However, the risk factors or predictors of stroke in AF patients have not been clarified. Therefore, it is necessary to find effective diagnostic and therapeutic targets. Two datasets were downloaded from the Gene Expression Omnibus (GEO) database. Differently expressed genes (DEGs) were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network and significant module, and the receiver operator characteristic (ROC) curve analysis were performed. A total of 524 DEGs were common to both datasets. Analysis of KEGG pathways indicated that the top canonical pathways associated with DEGs were ubiquitin-mediated proteolysis, endocytosis, spliceosome, and so on. Ten hub genes (SMURF2, CDC42, UBE3A, RBBP6, CDC5L, NEDD4L, UBE2D2, UBE2B, UBE2I, and MAPK1) were identified from the PPI network and were significantly associated with a diagnosis of atrial fibrillation and stroke (AFST). In summary, a total of 524 DEGs and 10 hub genes were identified between samples of atrial fibrillation without stroke and atrial fibrillation with stroke. These genes may serve as the target of early diagnosis or treatment of AF complicated by stroke.

Effect of eating habits on obesity in adolescents: a study among Chinese college students.

OBJECTIVE: Obesity has been linked to cardiovascular disease, diabetes, and osteoarthritis. Obesity and overweight pose a serious threat to human health, with an estimated 190 million overweight and obese people worldwide. Thus, we investigated the influence of certain eating habits on weight among Chinese college students. METHODS: We conducted a cross-sectional survey of 536 college students in Shijiazhuang, China. The survey included questions about eating habits. We analyzed the relationship between participants' responses and obesity. RESULTS: Sex, residence, speed of eating, number of meals eaten per day, and a diet high in sugar were found to be correlated with obesity. Our results suggest that increasing the number of meals per day, slowing down the pace of eating, and reducing the intake of high-sugar foods have potential benefits for reducing obesity among college students. CONCLUSIONS: In the present study, we found that some dietary habits are related to the occurrence of obesity among college-aged individuals.

Chronic stress: a critical risk factor for atherosclerosis.

Chronic stress refers to the non-specific systemic reaction that occurs when the body is stimulated by various internal and external negative factors over a long time. The physiological response to chronic stress exposure has long been recognized as a potent modulator in the occurrence of atherosclerosis. Furthermore, research has confirmed the correlation between atherosclerosis and cardiovascular events. Chronic stress is pervasive during negative life events and may lead to the formation of plaque. Several epidemiological studies have shown that chronic stress is an independent risk factor for the development of vascular disease and for increased morbidity and mortality in patients with pre-existing coronary artery disease. One possible mechanism for this process is that chronic stress causes endothelial injury, directly activating macrophages, promoting foam cell formation and generating the formation of atherosclerotic plaque. This mechanism involves numerous variables, including inflammation, signal pathways, lipid metabolism and endothelial function. The mechanism of chronic stress in atherosclerosis should be further investigated to provide a theoretical basis for efforts to eliminate the effect of chronic stress on the cardiocerebral vascular system.