Excessive oxidative stress drives pathological ventricular remodeling after acute myocardial infarction (AMI), yet adaptive cardiomyocyte mechanisms are poorly understood. We analyzed 64,510 human cardiomyocytes from five integrated single-cell datasets to delineate oxidative stress heterogeneity. Using quartile thresholds of a composite oxidative stress score, cells were stratified into three distinct subpopulations: high oxidative stress (HOX, score > 2.608), dynamic transient oxidative stress (DTOX), and low oxidative stress (LOX, score < 2.061). Paradoxically, HOX cells exhibited severe oxidative stress alongside significantly higher cellular plasticity than DTOX and LOX cells (p < 0.001), as confirmed by CytoTRACE and pseudotime trajectory analyses. This subpopulation demonstrated a unique “metabolic activation–immune suppression” signature and served as a central communication hub. An integrative machine-learning framework incorporating six distinct algorithms and independent cohort validation identified five core marker genes (TRIM63, ETFDH, TXNIP, CKMT2, and PDK4). These genes demonstrated stable diagnostic capability for AMI in independent validation cohorts (AUCs 0.688–0.721, all p < 0.001) and were specifically enriched in HOX cells. Our work reveals a previously unrecognized adaptive state in post-infarction cardiomyocytes, offering promising new targets for precision diagnosis and intervention.
Ao Wang (Fri,) studied this question.