RNA biomarker signatures for prediction of acute kidney injury in acute coronary syndrome patients undergoing PCI

Abstract

Abstract Background Acute kidney injury (AKI) represents a critical complication in patients with acute coronary syndrome (ACS), particularly in patients undergoing percutaneous coronary intervention (PCI). Current tests for detecting early AKI, such as creatinine and cystatin C, have modest sensitivity. This study explores the role of bioinformatics in creating an implementable predictive key gene in cardiorenal pathogenesis and evaluates the diagnostic potential of GTF2I, ANGPTL4, and MMP14 in predicting AKI in ACS patients. Methods This is a single-center prospective observational cohort study that enrolled 167 participants: healthy controls (n = 60), ACS patients (n = 56), and ACS patients with AKI (n = 51). Baseline clinical and renal markers were measured 24 h pre-PCI, with RNA biomarkers (GTF2I, ANGPTL4, MMP14) assessed at 48 h post-PCI, with daily creatinine monitoring performed for up to 6 days after PCI. Results GTF2I, ANGPTL4, and MMP14 were significantly elevated in ACS patients, with further increases in ACS-AKI patients. GTF2I showed the strongest predictive accuracy for AKI (AUC = 0.98), outperforming creatinine and cystatin. ANGPTL4 correlated negatively with serum creatinine (r = − 0.213, P = 0.006), suggesting a modulatory role in renal injury, while MMP14 elevations were pronounced in ACS-AKI. Notably, the combined biomarker panel achieved the highest diagnostic accuracy (AUC = 0.99), underscoring its potential as a robust early predictor of AKI. Subgroup analysis in diabetic patients revealed differential biomarker expression between AKI and non-AKI cases. Logistic regression confirmed albuminuria, ANGPTL4, GTF2I, and MMP14, in addition to several metabolic biomarkers, as significant predictors of AKI. Conclusion GTF2I, ANGPTL4, and MMP14 are promising biomarkers for predicting AKI in ACS patients and could be integrated into clinical practice for early AKI detection, improving patient management and outcomes.