关键词: Atherosclerosis Bioinformatics analysis Immune infiltration Machine learning Polycystic ovary syndrome

Mesh : Polycystic Ovary Syndrome / genetics Female Humans Atherosclerosis / genetics Mice Animals Gene Regulatory Networks Gene Expression Profiling RAW 264.7 Cells Machine Learning Granulosa Cells / metabolism Biomarkers

来  源:   DOI:10.1038/s41598-024-69065-4   PDF(Pubmed)

Abstract:
Polycystic ovary syndrome (PCOS), which is the most prevalent endocrine disorder among women in their reproductive years, is linked to a higher occurrence and severity of atherosclerosis (AS). Nevertheless, the precise manner in which PCOS impacts the cardiovascular well-being of women remains ambiguous. The Gene Expression Omnibus database provided four PCOS datasets and two AS datasets for this study. Through the examination of genes originating from differentially expressed (DEGs) and critical modules utilizing functional enrichment analyses, weighted gene co-expression network (WGCNA), and machine learning algorithm, the research attempted to discover potential diagnostic genes. Additionally, the study investigated immune infiltration and conducted gene set enrichment analysis (GSEA) to examine the potential mechanism of the simultaneous occurrence of PCOS and AS. Two verification datasets and cell experiments were performed to assess biomarkers\' reliability. The PCOS group identified 53 genes and AS group identified 175 genes by intersecting DEGs and key modules of WGCNA. Then, 18 genes from two groups were analyzed by machine learning algorithm. Death Associated Protein Kinase 1 (DAPK1) was recognized as an essential gene. Immune infiltration and single-gene GSEA results suggest that DAPK1 is associated with T cell-mediated immune responses. The mRNA expression of DAPK1 was upregulated in ox-LDL stimulated RAW264.7 cells and in granulosa cells. Our research discovered the close association between AS and PCOS, and identified DAPK1 as a crucial diagnostic biomarker for AS in PCOS.
摘要:
多囊卵巢综合征(PCOS),这是育龄期妇女中最常见的内分泌紊乱,与动脉粥样硬化(AS)的较高发生率和严重程度有关。然而,PCOS影响女性心血管健康的确切方式仍然不明确.基因表达综合数据库为本研究提供了四个PCOS数据集和两个AS数据集。通过利用功能富集分析检查源自差异表达(DEGs)和关键模块的基因,加权基因共表达网络(WGCNA),和机器学习算法,这项研究试图发现潜在的诊断基因。此外,这项研究调查了免疫浸润并进行了基因集富集分析(GSEA),以研究PCOS和AS同时发生的潜在机制.进行两个验证数据集和细胞实验以评估生物标志物的可靠性。PCOS组通过与DEGs和WGCNA的关键模块相交,鉴定了53个基因,AS组鉴定了175个基因。然后,采用机器学习算法对两组18个基因进行分析。死亡相关蛋白激酶1(DAPK1)被认为是必需基因。免疫浸润和单基因GSEA结果表明DAPK1与T细胞介导的免疫应答相关。在ox-LDL刺激的RAW264.7细胞和颗粒细胞中,DAPK1的mRNA表达上调。我们的研究发现AS和PCOS之间的密切关系,并确定DAPK1是PCOS中AS的关键诊断生物标志物。
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