Zou Jun-Hua, Wang Hua-Wei, Long Jia-Zhi, Yang Xiao-Na, Yang Li-Hong, Li Long-Jun, Chen Li-Xing, Dong Ling, Chen Jing, Meng Zhao-Hui, Wan Wen
The First Department of Cardiology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
The Third Department of Cardiology, The First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China.
Int J Cardiol. 2025 Dec 15;441:133635. doi: 10.1016/j.ijcard.2025.133635. Epub 2025 Aug 7.
Hyperlipidemia (HLP) exacerbates myocardial cell injury by impairing lipophagy, a crucial lipid metabolic process, thereby increasing the risk of acute myocardial infarction (AMI). This study aims to identify biomarkers associated with HLP and lipophagy that are relevant to AMI risk through a combined transcriptomic and Mendelian randomization (MR) approach.
mRNA expression data for AMI, along with genes related to HLP (HRGs) and lipophagy (LRGs), were obtained from public databases. Biomarkers were identified using differential expression analysis, weighted gene co-expression network analysis (WGCNA), MR analysis, and receiver operating characteristic (ROC) analysis, augmented by two machine learning algorithms and expression validation. These biomarkers were further used to explore the role of platelet activation-related genes (PARGs) in AMI, with enrichment analysis providing insights into their underlying mechanisms. Expression of selected biomarkers was validated in clinical samples using reverse transcription-quantitative polymerase chain reaction (RT-qPCR).
Three biomarkers consistently exhibited significant upregulation in AMI samples, which was confirmed by RT-qPCR. Specifically, PLAUR [Odds ratio (OR) = 1.115, 95 % confidence interval (CI): 1.006-1.237, P = 0.038] and IVNS1ABP (OR = 1.047, 95 % CI: 1.000-1.096, P = 0.048) were identified as AMI risk factors, while QKI (OR = 0.946, 95 % CI: 0.903-0.991, P = 0.020) was recognized as a protective factor. PLAUR, QKI, and IVNS1ABP demonstrated strong diagnostic performance with area under the curve (AUC) values of 0.773, 0.933, and 0.807, respectively. When combined in a nomogram, the AUC reached 0.924. These genes were primarily enriched in pathways related to cardiovascular diseases, inflammation, and cellular metabolism, and were notably linked to platelet activation, as evidenced by their strong associations with PARGs.
In conclusion, the biomarkers PLAUR, QKI, and IVNS1ABP, associated with HLP and lipophagy, exhibit a potential causal relationship with AMI and significant diagnostic potential for predicting AMI risk, providing valuable insights for clinical diagnostics and AMI research.
高脂血症（HLP）通过损害脂噬这一关键的脂质代谢过程加重心肌细胞损伤，从而增加急性心肌梗死（AMI）的风险。本研究旨在通过整合转录组学和孟德尔随机化（MR）方法，鉴定与HLP和脂噬相关且与AMI风险相关的生物标志物。
从公共数据库中获取AMI的mRNA表达数据，以及与HLP相关的基因（HRGs）和脂噬相关的基因（LRGs）。使用差异表达分析、加权基因共表达网络分析（WGCNA）、MR分析和受试者工作特征（ROC）分析鉴定生物标志物，并通过两种机器学习算法和表达验证进行补充。这些生物标志物进一步用于探索血小板活化相关基因（PARGs）在AMI中的作用，富集分析为其潜在机制提供了见解。使用逆转录定量聚合酶链反应（RT-qPCR）在临床样本中验证所选生物标志物的表达。
三种生物标志物在AMI样本中始终表现出显著上调，这通过RT-qPCR得到证实。具体而言，PLAUR [比值比（OR）=1.115，95%置信区间（CI）：1.006-1.237，P=0.038]和IVNS1ABP（OR=1.047，95%CI：1.000-1.096，P=0.048）被确定为AMI风险因素，而QKI（OR=0.946，95%CI：0.903-0.991，P=0.020）被认为是保护因素。PLAUR、QKI和IVNS1ABP表现出强大的诊断性能，曲线下面积（AUC）值分别为0.773、0.933和0.807。当组合在列线图中时，AUC达到0.924。这些基因主要富集在与心血管疾病、炎症和细胞代谢相关的途径中，并且与血小板活化显著相关，这通过它们与PARGs的强关联得到证明。
总之，与HLP和脂噬相关的生物标志物PLAUR、QKI和IVNS1ABP与AMI存在潜在因果关系，对预测AMI风险具有显著诊断潜力，为临床诊断和AMI研究提供了有价值的见解。
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