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<p>Acute myocardial infarction (AMI) is a major contributor to cardiovascular-related mortality, and early diagnosis is crucial for effective treatment and better outcomes. While several biomarkers have been explored for AMI, there remains a need for reliable, non-invasive biomarkers that can accurately differentiate AMI patients from healthy individuals. This study aims to identify potential mRNA biomarkers in peripheral blood that could aid in the diagnosis and monitoring of AMI. We performed transcriptomic analysis of blood samples from 81 individuals, including 16 healthy controls, 58 AMI patients, and 7 post-treated AMI individuals. Through a combination of Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA), random forest (RF), Weighted Gene Co-expression Network Analysis (WGCNA), and LASSO regression, we identified mRNA markers that are significantly correlated with AMI. Specifically, the mRNA expressions of ANKRD52, ART1, NRP2, and PPP1R15A were elevated in AMI patients, whereas BAIAP2L1 and CCNE1 were downregulated. However, while these mRNA biomarkers show potential for distinguishing AMI patients from healthy individuals, further studies are needed to confirm their clinical applicability.</p>

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An exploratory study of high-throughput transcriptomic analysis reveals novel mRNA biomarkers for acute myocardial infarction using integrated methods

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年3月11日

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  • Fei Huang,
  • Zongning Chen,
  • Binjie Tan,
  • Rong He,
  • Xiaoyu Zhang,
  • Yali Chen,
  • Jinsong Gao,
  • Bo Sun

摘要

Acute myocardial infarction (AMI) is a major contributor to cardiovascular-related mortality, and early diagnosis is crucial for effective treatment and better outcomes. While several biomarkers have been explored for AMI, there remains a need for reliable, non-invasive biomarkers that can accurately differentiate AMI patients from healthy individuals. This study aims to identify potential mRNA biomarkers in peripheral blood that could aid in the diagnosis and monitoring of AMI. We performed transcriptomic analysis of blood samples from 81 individuals, including 16 healthy controls, 58 AMI patients, and 7 post-treated AMI individuals. Through a combination of Sparse Partial Least Squares-Discriminant Analysis (sPLS-DA), random forest (RF), Weighted Gene Co-expression Network Analysis (WGCNA), and LASSO regression, we identified mRNA markers that are significantly correlated with AMI. Specifically, the mRNA expressions of ANKRD52, ART1, NRP2, and PPP1R15A were elevated in AMI patients, whereas BAIAP2L1 and CCNE1 were downregulated. However, while these mRNA biomarkers show potential for distinguishing AMI patients from healthy individuals, further studies are needed to confirm their clinical applicability.