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Objective:To screen genetic and epigenetic expression differences associated with pulmonary embolism through integrated bioinformatics analysis.Methods:Four patients with pulmonary embolism and healthy physical examination in the Third Affiliated Hospital of Xinjiang Medical University in 2019 were selected as the research objects, using high-throughput sequencing technologies and methylation chip technology to detect, screening and integrated peripheral blood difference genomes and the epigenome data to identify the pathogenesis of pulmonary embolism caused by methylation of drive and differentially expressed genes, GO and KEGG enrichment analysis were performed.Results:Coexpression analysis of DNA methylation and gene expression data between the pulmonary embolism group and the healthy control group showed that differential methylation in the upstream region of genes was negatively correlated with gene expression. Among them, 8 significantly methylated genes in the upstream region of genes were screened out, and independent sample t-test and Pearson correlation analysis were done. In the pulmonary embolism group, there were 6 significant methylated genes of TSS1500, namely TSPO2, C1QA, AQP1, TNFSF9, MIA and STAB1, and the differential expression multiple log2FC of corresponding genes was 1.298, 1.629, 1.024, 2.746, 2.539, 1.060, respectively. The correlation between gene expression and gene methylation were -0.908, -0.900, -0.824, -0.784, -0.783, -0.779, respectively, and the methylation differences between the two groups were -0.049, -0.053, -0.048, -0.057, -0.050, respectively. -0.053 ( P < 0.05). There were three significantly methylated genes in the TSS200 region, namely TSPO2, SLC9A, and SIGLEC1. The gene expression differential multiple log2FC was 1.298, -2.252, and 1.866, respectively. The correlation between gene expression and gene methylation was -0.860, -0.774, and -0.739, respectively. The methylation difference between the two groups was -0.051, 0.027, -0.048 ( P < 0.05). In the pulmonary embolism group, 7 genes, including TSPO2, C1QA, AQP1, TNFSF9, MIA, STAB1 and SIGLEC1, showed hypomethylation and high expression in the TSS region. SLC9A3 gene showed high methylation and low expression. In the analysis of GO function, significant enrichment was obtained in complement activation, immune response and activation protein cascade. In the KEGG signaling pathway, the immune system, bacterial infection, and signaling molecules and interactions are significantly enriched, thereby regulating the occurrence of pulmonary embolism. Conclusions:Based on the combined analysis of DNA methylation and gene expression, a new idea of the occurrence and development of pulmonary embolism has been found, which can be further studied in the future.
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Objective To explore related factors affecting bone mineral density (BMD) and osteoporosis (OP) in patients with type 2 diabetes mellitus (T2DM). Methods Dual-energy X-ray absorptiometry was used to measure BMD of the femoral neck and the lumbar vertebrae in 220 patients with T2DM. All the patients were divided into three groups:normal bone mass group, decreased bone mass group and OP group according to the value of BMD. The clinical data and biochemical indicators were compared and analyzed between these groups, and the influencing factors of T2DM and OP were explored. Results Compared with normal bone mass group and decreased bone mass group, there were more older patients, longer course of T2DM, lower BMI and high density lipoprotein cholesterol (HDL-C), and higher glycated hemoglobin (HbA1c) level in OP group. There were significantly higher age, longer course of T2DM, higher level of HbA1c, and lower levels of BMI, HDL-C in decreased bone mass group than those of normal bone mass group (P＜0.05). There were no significant differences in waist-to-hip ratio, systolic blood pressure (SBP), diastolic blood pressure (DBP), postmenopausal women (PMW) ratio, fasting plasma glucose (FPG), 2-h postprandial blood glucose (2hPG), blood phosphorus, calcium, total cholesterol (TC), three acyl glycerin (TG) and low-density lipoprotein cholesterol (LDL-C) between three groups. The risk factors for T2DM combined with OP were older, female, long duration of T2DM, higher levels of FPG, 2hPG and HbA1c. Conclusion Older and female T2DM patients were high-risk group of OP. The treatment plan should be timely adjusted by regularly monitoring indexes of blood glucose and HbA1c.