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<p>Silent Myocardial Infarction (SMI)&#xa0;is a clinically underrecognized phenotype along the myocardial infarction continuum that progresses without anginal symptoms. Its prevalence in diabetes, chronic kidney disease, and the elderly reflects contributions from neuropathy, autonomic dysfunction, and neurogenic silencing. Emerging evidence indicates that SMI reflects a biologically biased phenotype within the myocardial infarction continuum shaped by immune-metabolic and neurogenic modulation rather than representing a distinct entity. Biomarkers such as sCD36, galectin-3, sST2, and GDF-15 capture fibrotic and inflammatory remodeling, while NETosis-linked markers (CitH3, MPO–DNA) highlight thrombo-inflammation. Lipidomic stressors, including ceramides and β-hydroxybutyrate, further define ischemic burden. Spatial omics and single-cell analyses identify enrichment of immune-regulatory macrophage programs associated with restrained inflammation without establishing the causality for symptom absence. A tiered approach—biomarker screening followed by imaging—supports risk stratification. This review integrates mechanistic and translational insights, proposing a pragmatic framework for early diagnosis and biologically aligned treatment of SMI.</p>

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Silent Myocardial Infarction Revisited: Immuno-metabolic Mechanisms, Multimodal Biomarkers, and Translational Diagnostics

  • 期刊论文

  • 发表日期：

    2026年3月5日

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  • Yashvi Pethani,
  • Neha Pethani,
  • Dilip Pethani,
  • Rima Shah,
  • Darshil Shah,
  • Jignesh Shah

摘要

Silent Myocardial Infarction (SMI) is a clinically underrecognized phenotype along the myocardial infarction continuum that progresses without anginal symptoms. Its prevalence in diabetes, chronic kidney disease, and the elderly reflects contributions from neuropathy, autonomic dysfunction, and neurogenic silencing. Emerging evidence indicates that SMI reflects a biologically biased phenotype within the myocardial infarction continuum shaped by immune-metabolic and neurogenic modulation rather than representing a distinct entity. Biomarkers such as sCD36, galectin-3, sST2, and GDF-15 capture fibrotic and inflammatory remodeling, while NETosis-linked markers (CitH3, MPO–DNA) highlight thrombo-inflammation. Lipidomic stressors, including ceramides and β-hydroxybutyrate, further define ischemic burden. Spatial omics and single-cell analyses identify enrichment of immune-regulatory macrophage programs associated with restrained inflammation without establishing the causality for symptom absence. A tiered approach—biomarker screening followed by imaging—supports risk stratification. This review integrates mechanistic and translational insights, proposing a pragmatic framework for early diagnosis and biologically aligned treatment of SMI.