Integrated Bioinformatics Analysis Reveals the Aberrantly Methylated Differentially Expressed Genes in Dilated Cardiomyopathy.

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-07-08 eCollection Date: 2024-01-01 DOI:10.7150/ijms.92537
Nana Li, Jinglin Wang, Xuhong Wang, Lingfeng Zha
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Abstract

Dilated cardiomyopathy (DCM) causes heart failure and sudden death. Epigenetics is crucial in cardiomyopathy susceptibility and progression; however, the relationship between epigenetics, particularly DNA methylation, and DCM remains unknown. Therefore, this study identified aberrantly methylated differentially expressed genes (DEGs) associated with DCM using bioinformatics analysis and characterized their clinical utility in DCM. DNA methylation expression profiles and transcriptome data from public datasets of human DCM and healthy control cardiac tissues were obtained from the Gene Expression Omnibus public datasets. Then an epigenome-wide association study was performed. DEGs were identified in both DCM and healthy control cardiac tissues. In total, 3,353 cytosine-guanine dinucleotide sites annotated to 2,818 mRNAs were identified, and 479 DCM-related genes were identified. Subsequently, core genes were screened using logistic, least absolute shrinkage and selection operator, random forest, and support vector machine analyses. The overlapping of these genes resulted in DEGs with abnormal methylation patterns. Cross-tabulation analysis identified 8 DEGs with abnormal methylation. Real-time quantitative polymerase chain reaction confirmed the expression of aberrantly methylated DEGs in mice. In DCM murine cardiac tissues, the expressions of SLC16A9, SNCA, PDE5A, FNDC1, and HTRA1 were higher compared to normal murine cardiac tissues. Moreover, logistic regression model associated with aberrantly methylated DEGs was developed to evaluate the diagnostic value, and the area under the receiver operating characteristic curve was 0.949, indicating that the diagnostic model could reliably distinguish DCM from non-DCM samples. In summary, our study identified 5 DEGs through integrated bioinformatic analysis and in vivo experiments, which could serve as potential targets for further comprehensive investigation.

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综合生物信息学分析揭示了扩张型心肌病中甲基化异常的差异表达基因
扩张型心肌病(DCM)会导致心力衰竭和猝死。表观遗传学对心肌病的易感性和进展至关重要;然而,表观遗传学(尤其是 DNA 甲基化)与 DCM 之间的关系仍然未知。因此,本研究通过生物信息学分析确定了与 DCM 相关的异常甲基化差异表达基因(DEGs),并描述了它们在 DCM 中的临床作用。研究人员从基因表达总库(Gene Expression Omnibus)的公开数据集中获得了人类 DCM 和健康对照心脏组织的 DNA 甲基化表达谱和转录组数据。然后进行了表观基因组关联研究。在 DCM 和健康对照心脏组织中均鉴定出了 DEGs。总共确定了 3,353 个胞嘧啶-鸟嘌呤二核苷酸位点,注释到 2,818 个 mRNA,并确定了 479 个 DCM 相关基因。随后,利用逻辑分析、最小绝对收缩和选择算子分析、随机森林分析和支持向量机分析对核心基因进行了筛选。这些基因的重叠产生了甲基化模式异常的 DEGs。交叉分析发现了 8 个甲基化异常的 DEGs。实时定量聚合酶链反应证实了甲基化异常的 DEGs 在小鼠中的表达。与正常小鼠心脏组织相比,DCM小鼠心脏组织中SLC16A9、SNCA、PDE5A、FNDC1和HTRA1的表达量更高。此外,我们还建立了与异常甲基化 DEGs 相关的逻辑回归模型来评估其诊断价值,其接收者操作特征曲线下面积为 0.949,表明该诊断模型能可靠地区分 DCM 与非 DCM 样本。总之,我们的研究通过综合生物信息学分析和体内实验发现了 5 个 DEGs,这些 DEGs 可作为进一步全面研究的潜在靶点。
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CiteScore
7.20
自引率
4.30%
发文量
567
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