Department of Cardiovascular Medicine, the Affiliated Hospital of Guizhou Medical University, Guiyang, China.
BMC Cardiovasc Disord. 2024 Oct 16;24(1):565. doi: 10.1186/s12872-024-04228-9.
This study aims to identify m6A methylation-related and immune cell-related key genes with diagnostic potential for heart failure (HF) by leveraging various bioinformatics techniques.
The GSE116250 and GSE141910 datasets were sourced from the Gene Expression Omnibus (GEO) database. Correlation analysis was conducted between differentially expressed genes (DEGs) in HF and control groups, alongside differential m6A regulatory factors, to identify m6A-related DEGs (m6A-DEGs). Subsequently, candidate genes were narrowed down by intersecting key module genes derived from weighted gene co-expression network analysis (WGCNA) with m6A-DEGs. Key genes were then identified through the Least Absolute Shrinkage and Selection Operator (LASSO) analysis. Correlation analyses between key genes and differentially expressed immune cells were performed, followed by the validation of key gene expression levels in public datasets. To ensure clinical applicability, five pairs of blood samples were collected for quantitative real-time fluorescence PCR (qRT-PCR) validation.
A total of 93 m6A-DEGs were identified (|COR| > 0.6, P < 0.05), and five key genes (LACTB2, NAMPT, SCAMP5, HBA1, and PRKAR2A) were selected for further analysis. Correlation analysis revealed that differential immune cells were negatively associated with the expression of LACTB2, NAMPT, and PRKAR2A (P < 0.05), while positively correlated with SCAMP5 and HBA1 (P < 0.05). Subsequent expression validation confirmed significant differences in key gene expression between the HF and control groups, with consistent expression trends observed across both training and validation sets. The expression trends of LACTB2, PRKAR2A, and HBA1 in blood samples from the qRT-PCR assay aligned with the results derived from public databases.
This study successfully identified five m6A methylation-related key genes with diagnostic significance, providing a theoretical foundation for further exploration of m6A methylation's molecular mechanisms in HF.
本研究旨在利用多种生物信息学技术，鉴定具有心力衰竭（HF）诊断潜力的 m6A 甲基化相关和免疫细胞相关关键基因。
从基因表达综合数据库（GEO）中获取 GSE116250 和 GSE141910 数据集。对 HF 组和对照组之间的差异表达基因（DEGs）进行相关性分析，以及差异 m6A 调节因子，以鉴定 m6A 相关 DEGs（m6A-DEGs）。然后，通过将加权基因共表达网络分析（WGCNA）得出的关键模块基因与 m6A-DEGs 进行交集，缩小候选基因的范围。通过最小绝对收缩和选择算子（LASSO）分析鉴定关键基因。对关键基因与差异表达免疫细胞之间的相关性进行分析，然后在公共数据集上验证关键基因的表达水平。为了确保临床适用性，收集了 5 对血液样本进行定量实时荧光 PCR（qRT-PCR）验证。
共鉴定出 93 个 m6A-DEGs（|COR|>0.6，P<0.05），并选择了 5 个关键基因（LACTB2、NAMPT、SCAMP5、HBA1 和 PRKAR2A）进行进一步分析。相关性分析表明，差异免疫细胞与 LACTB2、NAMPT 和 PRKAR2A 的表达呈负相关（P<0.05），而与 SCAMP5 和 HBA1 的表达呈正相关（P<0.05）。随后的表达验证证实了关键基因在 HF 组和对照组之间表达的显著差异，在训练集和验证集均观察到一致的表达趋势。qRT-PCR 检测血液样本中 LACTB2、PRKAR2A 和 HBA1 的表达趋势与公共数据库的结果一致。
本研究成功鉴定了具有诊断意义的 5 个 m6A 甲基化相关关键基因，为进一步探索 m6A 甲基化在 HF 中的分子机制提供了理论基础。
