Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learning - Takeaways - MDSpire

Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learning

  • By

  • Hanmo Zhang

  • Hongyu Huang

  • Zhuo Jiang

  • Shuangqi Qian

  • Xiandu Jin

  • Zeyan Peng

  • Fan Huang

  • Peipei Li

  • Liping Wei

  • Zhi Qi

  • Xin Qi

  • June 5, 2026

  • 0 min

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  • 1

    The study identifies 13 senescence-related genes (SRGs) associated with acute myocardial infarction (AMI) using multi-omics and machine learning approaches.

  • 2

    Four key SRGs, FOS, SOD2, MXD1, and GRN, demonstrated consistent diagnostic relevance across multiple datasets.

  • 3

    A four-gene diagnostic model achieved an AUC of 0.808, indicating strong potential for clinical application in AMI diagnosis.

  • 4

    Patient stratification revealed distinct groups based on senescence levels, correlating low-senescence with anti-inflammatory cells.

  • 5

    The findings suggest that neutrophil infiltration is linked to senescence-related transcriptional features in AMI, informing future research.

Original Source(s)

Identification and analysis of diagnostic senescence-related gene signatures for acute myocardial infarction based on multi-omics data and machine learning

  • by Hanmo Zhang, Hongyu Huang, Zhuo Jiang, Shuangqi Qian, Xiandu Jin, Zeyan Peng, Fan Huang, Peipei Li, Liping Wei, Zhi Qi, Xin Qi

  • June 5, 2026

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