Alharbi Hajed Obaid A, Khan Asifa, Rahmani Arshad Husain
Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraydah 51452, Saudi Arabia.
Department of Molecular, Cell and Cancer Biology, UMass Chan Medical School, Worcester, MA 01605, USA.
Biology (Basel). 2024 Oct 25;13(11):867. doi: 10.3390/biology13110867.
Atherosclerosis (AS) is a chronic inflammatory condition of the arteries, characterized by plaque formation that can restrict blood flow and lead to potentially fatal cardiovascular events. Given that AS is responsible for a quarter of global deaths, this study aimed to develop a systematic bioinformatics approach to identify biomarkers and regulatory targets involved in plaque development, with the goal of reducing cardiovascular disease risk. AS-specific mRNA expression profiles were retrieved from a publicly accessible database, followed by differentially expressed genes (DEGs) identification and AS-specific weighted gene co-expression network (WGCN) construction. Thereafter, calcification and atherosclerosis-specific (CASS) DEGs were utilized for protein-protein interaction network (PPIN) formation, followed by gene ontology (GO) term and pathway enrichment analyses. Lastly, AS-specific 3-node miRNA feed-forward loop (FFL) construction and analysis was performed. Microarray datasets GSE43292 and GSE28829 were obtained from gene expression omnibus (GEO). A total of 3785 and 6176 DEGs were obtained in case of GSE28829 and GSE43292; 3256 and 5962 module DEGs corresponding to GSE28829 and GSE43292 were obtained from WGCN. From a total of 54 vascular calcification (VC) genes, 20 and 29 CASS-DEGs corresponding to GSE28829 and GSE43292 were overlapped. As observed from FFL centrality measures, the highest-order subnetwork motif comprised one TF (), one miRNA (miR-484), and one mRNA () in the case of GSE28829. Also, in the case of GSE43292, the highest-order subnetwork motif comprised one TF (), one miRNA (miR-214-3p), and one mRNA (). These findings have important implications for developing new therapeutic strategies for AS. The identified TFs and miRNAs may serve as potential therapeutic targets for treating atherosclerotic plaques, offering insights into the molecular mechanisms underlying the pathogenesis and highlighting new avenues for research and treatment.
动脉粥样硬化（AS）是一种动脉的慢性炎症性疾病，其特征是形成斑块，可限制血流并导致潜在致命的心血管事件。鉴于AS导致全球四分之一的死亡，本研究旨在开发一种系统的生物信息学方法，以识别参与斑块形成的生物标志物和调控靶点，目标是降低心血管疾病风险。从一个可公开访问的数据库中检索AS特异性mRNA表达谱，随后进行差异表达基因（DEG）鉴定和AS特异性加权基因共表达网络（WGCN）构建。此后，利用钙化和动脉粥样硬化特异性（CASS）DEG构建蛋白质-蛋白质相互作用网络（PPIN），随后进行基因本体（GO）术语和通路富集分析。最后，进行AS特异性三节点miRNA前馈环（FFL）构建和分析。微阵列数据集GSE43292和GSE28829从基因表达综合数据库（GEO）获得。在GSE28829和GSE43292的情况下，分别获得了3785个和6176个DEG；从WGCN中获得了与GSE28829和GSE43292对应的3256个和5962个模块DEG。在总共54个血管钙化（VC）基因中，与GSE28829和GSE43292对应的20个和29个CASS-DEG重叠。从FFL中心性测量中观察到，在GSE28829的情况下，最高阶子网基序由一个转录因子（）、一个miRNA（miR-484）和一个mRNA（）组成。同样，在GSE43292的情况下，最高阶子网基序由一个转录因子（）、一个miRNA（miR-214-3p）和一个mRNA（）组成。这些发现对开发AS的新治疗策略具有重要意义。所鉴定的转录因子和miRNA可能作为治疗动脉粥样硬化斑块的潜在治疗靶点，为发病机制的分子机制提供见解，并突出新的研究和治疗途径。
