1. NCF2, MYO1F, S1PR4, and FCN1 as potential noninvasive diagnostic biomarkers in patients with obstructive coronary artery: A weighted gene co‐expression network analysis
- Author
-
Saber Imani, Yao Yang, Yue Cai, Youcai Deng, Bingbo Chen, Xuqiang Nie, Guo-rong Dan, Xian‐Gang Mo, Wei Liu, Rixing Zhan, Jun Yan, Shan Lu, and Xiaohui Li
- Subjects
0301 basic medicine ,Male ,medicine.medical_specialty ,Candidate gene ,Arterial Occlusive Diseases ,Coronary Artery Disease ,Biochemistry ,Coronary artery disease ,03 medical and health sciences ,Myosin Type I ,0302 clinical medicine ,Internal medicine ,Lectins ,Medicine ,Diagnostic biomarker ,Humans ,In patient ,Gene Regulatory Networks ,Myocardial infarction ,cardiovascular diseases ,FCN1 ,NCF2 ,S1PR4 ,Molecular Biology ,Sphingosine-1-Phosphate Receptors ,Research Articles ,Cells, Cultured ,business.industry ,Gene Expression Profiling ,noninvasive diagnostic biomarkers ,obstructive coronary artery disease ,NADPH Oxidases ,Cell Biology ,medicine.disease ,030104 developmental biology ,medicine.anatomical_structure ,Gene Ontology ,ROC Curve ,030220 oncology & carcinogenesis ,Cardiology ,Leukocytes, Mononuclear ,Gene co-expression network ,Biomarker (medicine) ,Female ,MYO1F ,business ,Biomarkers ,Artery ,Research Article - Abstract
This study aims to explore the predictive noninvasive biomarker for obstructive coronary artery disease (CAD). By using the data set GSE90074, weighted gene co‐expression network analysis (WGCNA), and protein–protein interactive network, construction of differentially expressed genes in peripheral blood mononuclear cells was conducted to identify the most significant gene clusters associated with obstructive CAD. Univariate and multivariate stepwise logistic regression analyses and receiver operating characteristic analysis were used to predicate the diagnostic accuracy of biomarker candidates in the detection of obstructive CAD. Furthermore, functional prediction of candidate gene biomarkers was further confirmed in ST‐segment elevation myocardial infarction (STEMI) patients or stable CAD patients by using the datasets of GSE62646 and GSE59867. We found that the blue module discriminated by WGCNA contained 13 hub‐genes that could be independent risk factors for obstructive CAD (P .05). This four‐gene signature could also act as a prognostic biomarker to discriminate STEMI patients from stable CAD patients. These findings suggest a four‐gene signature (NCF2, MYO1F, S1PR4, and FCN1) alone or combined with two risk factors (male sex and hyperlipidemia) as a promising prognostic biomarker in the diagnosis of STEMI. Well‐designed cohort studies should be implemented to warrant the diagnostic value of these genes in clinical purpose.
- Published
- 2019