Yanjun Wang

Dr. Yanjun Wang


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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14 June 2023 in BMC Medical Genomics
Verified
Journal Article
Open access
PDF file
SHShu He
Shu He
YFYahong Fu
Yahong Fu
CLChengcheng Li
Chengcheng Li
XGXiongkang Gan
Xiongkang Gan
YWYanjun Wang
Yanjun Wang
Enzhi JiaEnzhi Jia
Enzhi Jia
Background: Recent studies suggest that classical coronary risk factors play a significant role in the pathogenesis of coronary artery disease. Our study aims to explore the interaction of circRNA with classical coronary risk factors in coronary atherosclerotic disease. Method: Combined analysis of RNA sequencing results from coronary segments and peripheral blood mononuclear cells of patients with coronary atherosclerotic disease was employed to identify critical circRNAs. Competing endogenous RNA networks were constructed by miRanda-3.3a and TargetScan7.0. The relative expression quantity of circRNA in peripheral blood mononuclear cells was determined by qRT-PCR in a large cohort including 256 patients and 49 controls. Spearman’s correlation test, receiver operating characteristic curve analysis, multivariable logistic regression analysis, one-way analysis of variance, and crossover analysis were performed. Results: A total of 34 circRNAs were entered into our study, hsa_circRPRD1A, hsa_circHERPUD2, hsa_circLMBR1, and hsa_circDHTKD1 were selected for further investigation. A circRNA-miRNA-mRNA network is composed of 20 microRNAs and 66 mRNAs. The expression of hsa_circRPRD1A (P = 0.004) and hsa_circHERPUD2 (P = 0.003) were significantly down-regulated in patients with coronary artery disease compared to controls. The area under the curve of hsa_circRPRD1A and hsa_circHERPUD2 is 0.689 and 0.662, respectively. Univariate and multivariable logistic regression analyses identified hsa_circRPRD1A (OR = 0.613, 95%CI:0.380–0.987, P = 0.044) as a protective factor for coronary artery disease. Based on the additive model, crossover analysis demonstrated that there was an antagonistic interaction between the expression of hsa_circHERPUD2 and alcohol consumption in subjects with coronary artery disease. Conclusion: Our findings imply that hsa_circRPRD1A and hsa_circHERPUD2 could be used as biomarkers for the diagnosis of coronary artery disease and provide epidemiological support for the interactions between circRNAs and classical coronary risk factors.

3 July 2023 in Functional & Integrative Genomics
Verified
Journal Article
Closed access
PDF file
SHShu He
Shu He
SZSheng Zhang
Sheng Zhang
YWYanjun Wang
Yanjun Wang
XGXiong-Kang Gan
Xiong-Kang Gan
JCJia-Xin Chen
Jia-Xin Chen
Enzhi JiaEnzhi Jia
Enzhi Jia