ArticleFrontiers in genetics2020
Identification of Four Potential Biomarkers Associated With Coronary Artery Disease in Non-diabetic Patients by Gene Co-expression Network Analysis.
Article in Frontiers in genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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12 citing papers in PubMed, 18 citations in OpenAlex.
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- Identification and Validation of Immune-Related Genes Diagnostic for Progression of Atherosclerosis and Diabetes.Journal of inflammation research · 2023Article
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- Relationship between the Soluble F11 Receptor and Annexin A5 in African Americans Patients with Type-2 Diabetes Mellitus.Biomedicines · 2022Article
- LncRNA LYPLAL1-DT screening from type 2 diabetes with macrovascular complication contributes protective effects on human umbilical vein endothelial cells via regulating the miR-204-5p/SIRT1 axis.Cell death discovery · 2022Article
- Multi-Omic Approaches to Identify Genetic Factors in Metabolic Syndrome.Comprehensive Physiology · 2021Article
- Ischemic heart injury leads to HIF1-dependent differential splicing of CaMK2γ.Scientific reports · 2021Article
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- Exome sequencing in patient-parent trios suggests new candidate genes for early-onset primary sclerosing cholangitis.Liver international : official journal of the International Association for the Study of the Liver · 2021Article
- Weighted Co-Expression Network Analysis Identifies RNF181 as a Causal Gene of Coronary Artery Disease.Frontiers in genetics · 2021Article
- Identifying RBM47, HCK, CD53, TYROBP, and HAVCR2 as Hub Genes in Advanced Atherosclerotic Plaques by Network-Based Analysis and Validation.Frontiers in genetics · 2020Article
- A novel multi-omics-machine learning pipeline reveals immune and metabolic links between type 2 diabetes and atherosclerosis.Diabetes & vascular disease researchArticle
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Authors and funding
13 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCoronary artery disease (CAD) is a type of cardiovascular disease that greatly hurts the health of human beings. Diabetic status is one of the largest clinical factors affecting CAD-associated gene expression changes. Most of the studies focus on diabetic patients, whereas few have been done for non-diabetic patients. Since the pathophysiological processes may vary among these patients, we cannot simply follow the standard based on the data from diabetic patients. Therefore, the prognostic and predictive diagnostic biomarkers for CAD in non-diabetic patient need to be fully recognized. MATERIALS AND
methodsTo screen out candidate genes associated with CAD in non-diabetic patients, weighted gene co-expression network analysis (WGCNA) was constructed to conduct an analysis of microarray expression profiling in patients with CAD. First, the microarray data GSE20680 and GSE20681 were downloaded from NCBI. We constructed co-expression modules
resultsThe results showed that the midnight blue module and the yellow module played vital roles in the pathogenesis of CAD in non-diabetic patients. Additionally, CD40, F11R, TNRC18, and calcium/calmodulin-dependent protein kinase type II gamma (CAMK2G) were screened out and validated using enzyme-linked immunosorbent assay (ELISA) in an independent patient cohort and immunohistochemical (IHC) staining in an atherosclerosis mouse model.
conclusionOur findings demonstrate that hub genes, CD40, F11R, TNRC18, and CAMK2G, are surrogate diagnostic biomarkers and/or therapeutic targets for CAD in non-diabetic patients and require deeper validation.
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