Detecting early‐warning biomarkers associated with heart‐exosome genetic‐signature for acute myocardial infarction: A source‐tracking study of exosome

Abstract

AbstractThe genetic information of plasma total‐exosomes originating from tissues have already proven useful to assess the severity of coronary artery diseases (CAD). However, plasma total‐exosomes include multiple sub‐populations secreted by various tissues. Only analysing the genetic information of plasma total‐exosomes is perturbed by exosomes derived from other organs except the heart. We aim to detect early‐warning biomarkers associated with heart‐exosome genetic‐signatures for acute myocardial infarction (AMI) by a source‐tracking analysis of plasma exosome. The source‐tracking of AMI plasma total‐exosomes was implemented by deconvolution algorithm. The final early‐warning biomarkers associated with heart‐exosome genetic‐signatures for AMI was identified by integration with single‐cell sequencing, weighted gene correction network and machine learning analyses. The correlation between biomarkers and clinical indicators was validated in impatient cohort. A nomogram was generated using early‐warning biomarkers for predicting the CAD progression. The molecular subtypes landscape of AMI was detected by consensus clustering. A higher fraction of exosomes derived from spleen and blood cells was revealed in plasma exosomes, while a lower fraction of heart‐exosomes was detected. The gene ontology revealed that heart‐exosomes genetic‐signatures was associated with the heart development, cardiac function and cardiac response to stress. We ultimately identified three genes associated with heart‐exosomes defining early‐warning biomarkers for AMI. The early‐warning biomarkers mediated molecular clusters presented heterogeneous metabolism preference in AMI. Our study introduced three early‐warning biomarkers associated with heart‐exosome genetic‐signatures, which reflected the genetic information of heart‐exosomes carrying AMI signals and provided new insights for exosomes research in CAD progression and prevention.