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Identification and preliminary validation of differently expressed genes as candidate biomarkers associated with atherosclerosis

生物 小桶 计算生物学 小RNA 微阵列 基因 微阵列分析技术 遗传学 基因表达 转录组
作者
Liqin Zhou,Liping Zhou,Yong‐Min Liang,Congying Chen,Yuanyuan Qian,Dayong Lou,Huanjie Ma,S Alex Wang
出处
期刊:Gene [Elsevier BV]
卷期号:915: 148410-148410
标识
DOI:10.1016/j.gene.2024.148410
摘要

Atherosclerosis (AS) is the primary cause of deadly cardio-cerebro vascular diseases globally. This study aims to explore the key differentially expressed genes (DEGs), potentially serving as predictive biomarkers for AS. Microarray datasets were retrieved from the GEO database for DEGs and DE-miRNAs identification. Then biological function of DEGs were elucidated based on gene ontology (GO) and KEGG pathway enrichment analysis. The protein–protein interaction (PPI) network and DEGs-DE-miRNAs network were constructed, with emphasis on hub DEGs selection and their interconnections. Additionally, receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic precision of hub DEGs for AS. More importantly, an AS Syrian Golden hamster model was established to validate the expression levels of hub DEGs in AS. A total of 203 DEGs and 10 DE-miRNAs were screened, with six genes were chosen as hub DEGs. These DEGs were significantly enriched in AS-related biological processes and pathways, such as immune and inflammatory response, cellular response to IL-1 and TNF, positive regulation of angiogenesis, Type I diabetes mellitus, Cytokine-cytokine receptor interaction, TLR signaling pathway. Also, these DEGs and DE-miRNAs formed a closely-interacted DE-miRNAs - DEGs - KEGG pathway network. Besides, hub DEGs presented promising diagnostic potential for AS (AUC: 0.781 ∼ 0.887). In addition, the protein expression levels of TNF-α, CXCL8, CCL4, IL-1β, CCL3 and CCR8 were significantly increased in AS group Syrian Golden hamsters. The identified candidate genes TNF, CXCL8, CCL4, IL1B, CCL3 and CCR8 may have the potential to serve as prognostic biomarker in diagnosing AS.
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