A multigene diagnostic model based on five conserved hub genes distinguished myocardial infarction from non-MI controls with strong predictive performance (AUC = 0.904).
A cross-species integrative analysis identified five conserved hub genes in myocardial infarction, yielding a diagnostic model with high predictive accuracy (AUC = 0.904).
Effect estimate: AUC 0.904
Myocardial infarction (MI) is a leading cause of mortality worldwide. Identification of robust and translatable molecular markers remains challenging due to inter-dataset and inter-species variability. In this study, we performed a cross-species integrative analysis to identify conserved hub genes and potential therapeutic targets in MI. Analysis revealed five hub genes (IL6, SERPINE1, MMP14, PLAUR, and ENO1), which were consistently validated across human peripheral blood and multiple animal models. A multigene diagnostic model demonstrated strong predictive performance (AUC = 0.904). The model was developed to distinguish myocardial infarction (MI) samples from non-MI control samples in an independent peripheral blood dataset. Drug–gene interaction analysis identified candidate therapeutic compounds. These results are computational predictions from the DGIdb database and do not represent validated therapeutic effects in myocardial infarction. These findings highlight conserved molecular mechanisms of MI and provide potential biomarkers and therapeutic targets with translational relevance.
Sheng et al. (Mon,) conducted a other in Myocardial infarction. Multigene diagnostic model vs. Non-MI control samples was evaluated on Distinguishing myocardial infarction samples from non-MI control samples (AUC 0.904). A multigene diagnostic model based on five conserved hub genes distinguished myocardial infarction from non-MI controls with strong predictive performance (AUC = 0.904).
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