Liu Jun, Chen Baofu, Lu Hongsheng, Chen Qi, Li Ji-Cheng
Department of Cardiothoracic Surgery and Department of Pathology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou 318000, China; Institute of Cell Biology, Zhejiang University, Hangzhou 310058, China.
Department of Cardiothoracic Surgery and Department of Pathology, Taizhou Central Hospital (Taizhou University Hospital), Taizhou 318000, China.
Clin Chim Acta. 2023 Aug 1;548:117506. doi: 10.1016/j.cca.2023.117506. Epub 2023 Aug 6.
Both pathological and normal processes depend on proteins. In this study, plasma protein profiles were analyzed by a novel proximity extension assay (PEA) to identify potential pathogenic mechanisms and diagnostic biomarkers in patients diagnosed with acute myocardial infarction (AMI).
In this study, we identified a total of 92 plasma proteins using the Olink Target 96 Cardiovascular III panel in a cohort consisting of 30 healthy controls (HC), 28 patients with unstable angina (UA) and 30 patients with AMI. Subsequently, we conducted a differential expression analysis to identify protein molecules that were specifically expressed in patients with AMI. To gain insights into the potential functional mechanisms of these differentially expressed molecules, we performed Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Following that, the utilization of least absolute shrinkage and selection operator (LASSO) regression facilitated the identification of potential protein biomarkers, enabling the differentiation between AMI and UA. A diagnostic model was subsequently developed through logistic regression, and the effectiveness of these markers was assessed using receiver operating characteristic (ROC) analysis. Ultimately, the diagnostic capabilities of these potential biomarkers were validated in an independent validation cohort consisting of 30 UA cases and 30 AMI cases.
In this study, a comprehensive analysis of plasma proteins identified a total of 92 proteins. Further analysis using analysis of variance revealed that 25 proteins exhibited specific expression in the AMI group compared to the HC and UA groups. Additionally, KEGG enrichment analysis indicated that these differentially expressed proteins were primarily associated with the activation of cytokine-cytokine receptor interaction, PI3K-Akt signaling pathway, and GnRH signaling pathway. AGRP, TGM2, IL6, GH1, and CA5A were identified through LASSO regression as prospective protein biomarkers for distinguishing between UA and AMI. The diagnostic model comprising these five proteins exhibited exceptional performance in both the discovery and validation datasets, surpassing AUC values of 0.9.
The findings of our study provide additional insights into the involvement of the inflammatory response and AKT cascade response in the development of AMI. Moreover, we have identified potential protein markers that could be utilized for the accurate diagnosis of AMI. These results offer a fresh perspective for clinical decision-making in the context of AMI.
病理过程和正常过程均依赖蛋白质。在本研究中，采用一种新型的邻位延伸分析（PEA）技术分析血浆蛋白质谱，以确定急性心肌梗死（AMI）患者潜在的致病机制和诊断生物标志物。
在本研究中，我们使用Olink Target 96心血管疾病III检测板，在一个由30名健康对照者（HC）、28名不稳定型心绞痛（UA）患者和30名AMI患者组成的队列中，共鉴定出92种血浆蛋白。随后，我们进行了差异表达分析，以确定在AMI患者中特异性表达的蛋白质分子。为深入了解这些差异表达分子的潜在功能机制，我们进行了基因本体（GO）富集分析和京都基因与基因组百科全书（KEGG）通路分析。在此之后，利用最小绝对收缩和选择算子（LASSO）回归有助于识别潜在的蛋白质生物标志物，从而区分AMI和UA。随后通过逻辑回归建立诊断模型，并使用受试者工作特征（ROC）分析评估这些标志物的有效性。最终，在一个由30例UA病例和30例AMI病例组成的独立验证队列中验证了这些潜在生物标志物的诊断能力。
在本研究中，对血浆蛋白进行的综合分析共鉴定出92种蛋白质。使用方差分析进一步分析发现，与HC组和UA组相比，有25种蛋白质在AMI组中呈现特异性表达。此外，KEGG富集分析表明，这些差异表达的蛋白质主要与细胞因子-细胞因子受体相互作用、PI3K-Akt信号通路和GnRH信号通路的激活有关。通过LASSO回归确定AGRP、TGM2、IL6、GH1和CA5A为区分UA和AMI的潜在蛋白质生物标志物。包含这五种蛋白质的诊断模型在发现数据集和验证数据集中均表现出卓越的性能，AUC值超过0.9。
我们的研究结果为炎症反应和AKT级联反应在AMI发生发展中的作用提供了更多见解。此外，我们已经鉴定出可用于准确诊断AMI的潜在蛋白质标志物。这些结果为AMI临床决策提供了新的视角。
